Citation
Optimal Building Performance

Material Information

Title:
Optimal Building Performance Exploring Human Behavior Impacts on Energy and Water Consumption in Campus Residential Halls
Creator:
Driza, Pamelajean N
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (319 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Design, Construction, and Planning
Design, Construction and Planning
Committee Chair:
PARK,NAM-KYU
Committee Co-Chair:
TORRES,MARUJA
Committee Members:
AHRENTZEN,SHERRY
SWISHER,MARILYN E
Graduation Date:
12/19/2014

Subjects

Subjects / Keywords:
Buildings ( jstor )
Dormitories ( jstor )
Energy consumption ( jstor )
Toilets ( jstor )
Universities ( jstor )
Water conservation ( jstor )
Water consumption ( jstor )
Water flow ( jstor )
Water resources ( jstor )
Water usage ( jstor )
Design, Construction and Planning -- Dissertations, Academic -- UF
behavior -- energy -- leed -- performance -- water
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Design, Construction, and Planning thesis, Ph.D.

Notes

Abstract:
Under mounting pressure from users, stakeholders, and governmental agencies many universities have made commitments to incorporate environmental literacy into their courses and adopt the LEED building standards throughout their campuses. Despite the growing use of this rating system research has indicated that occupant behaviors remain an obstacle to long-term building efficiency, particularly in residence halls (Bekker et al., 2010). Thus, this study investigates how accurately occupant behaviors are accounted for in the LEED rating system and determine if any relationships exist between behavioral constructs and occupants consumption of resources? Utilizing a comparative case study approach, three LEED certified residence halls were examined. Qualitative and quantitative methodologies, including demographic profiles, building consumption data, a survey, resource-tracking exercises, and interviews were designed to assess the environmentally significant behaviors (ESB) of residents. Collected data were then compared to the LEED referenced settings for water and energy, and two behavioral theory frameworks in order to determine how actual resident behaviors compared to current estimates for resource consumption. Consistent with previous research, all three cases demonstrated a discrepancy between their predicted and actual performance levels. Findings also revealed that residents utilized water less often and energy more often than stipulated by the current default settings. Finally, resident ESBs were most influenced by subjective and personal norms, altruistic and biospheric values, attitudes, and behavioral intentions. Based on findings, it was determined that the referenced settings do not differentiate between building types or reflect the actual behaviors of residents. Additionally, it was clear that improved building performance relies upon a balance between technological solutions and improved occupant behaviors. Recommendations are given to support the improved performance of residence halls through community-based social marketing techniques and other strategies. This study aids in the continued development of the LEED rating system and the understanding of occupant ESBs in residence halls. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2014.
Local:
Adviser: PARK,NAM-KYU.
Local:
Co-adviser: TORRES,MARUJA.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-06-30
Statement of Responsibility:
by Pamelajean N Driza.

Record Information

Source Institution:
UFRGP
Rights Management:
Copyright Driza, Pamelajean N. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
6/30/2015
Resource Identifier:
974372536 ( OCLC )
Classification:
LD1780 2014 ( lcc )

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1 OPTIMAL BUILDING PERFORMANCE: EXPLORING HUMAN BEHAVIOR IMPACTS ON ENERGY AND WATER CONSUMPTION IN CAMPUS RESIDENCE HALLS By PAMELA JEAN NICHOL DRIZA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2014

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2 © 2014 Pamela Jean Nichol Driza

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3 To all who have continued to support my passion for sustainable design and building performance. This accomplishment will forever be a reminder that dedication, perseverance , and an awful lot of self discipline can lead to great things

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4 ACKNOWLEDGMENTS This research would not have been possible without the dedication and support of many people. I owe a debt of gratitude to the University of Florida , Interior Design Department for their contribution through a doctoral fellowship, numerou s scholarships, and renewed graduate teaching assistantships . Throughout my tenure I could always depend on each of you to reciprocate your consideration, gratitude, and respect. I appreciate the many opportunities I had to learn from each of you while co instructing and collaborating together. Your certainty in my ability to balance a dissertation study, instructor load, and the day to day happenings of life gave me the confidence I needed to face any obstacle without reservation. Thank you so much for enc ouraging my intellectual curiosity and for allowing me to grow professionally in so many ways. I would like to thank David Schwieder and Meghan Brennan for their guidance and expertise with SPSS and SAS. Without your assistance with these programs the sta tistical analysis of this project would not have been possible. Equally, I would not have been able to complete my final semester in the Ph.D. program without the support and financial assistance of the management at Steelcase , Inc h for encouraging my personal growth and for recognizing the value in this personal endeavor. I would also like to thank my commi ttee chair, Dr. Nam Kyu Park; co chair, Dr. Maruja Torres Antonini ; and committee members, Dr. Sherry Ahrentzen and Dr. Marilyn Swisher, for their unrelenting support and willingness to accept this challenge. I am grateful to Dr. Park for ushering me through a mixed methods research study and encouraging me to submit my work to a number of academic journals and conferences. ability to complete this study in record time is due in part to her prompt reviews and her

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5 commitment to being an amazing educator. I am also grateful to Dr. Ahrentzen for broadening my understanding of case studies, providing positive feedback, and for offering her expertise on sustainable practices. I am especially grateful to Dr. Swisher for her authenticity, unique perspective of community development, and for openin g the world of advanced research methods to me. Without all of your professional guidance, scholarly expertise, and the generous sharing of your time this study could not have been realized. This has been an amazing journey for me and I sincerely thank you all for your sustained encouragement and individual contributions to my doctoral degree. I would also like to acknowledge my parents, Yvette and Ornel Cotera , my brothers and sister in law, Ornel, Julian , and Jamie Cotera, and my grandmothers, Miriam Fer nandez and Ampa Cotera for their support throughout my graduate degrees. One of the greatest parts of this accomplishment is knowing how proud they are of me. I love you all very much and thank you for being my constant pillar of encouragement. I would als o like to recognize my adopted uncles Robin Hunt and Mike Connor, in laws Karen, Corey, Paige , Linda and the rest of the Driza and Murphy clan , my dearest friends Rebecca Nychyk, Natasha Ellis, Kevin and Colleen Priest, and the rest of my network of family and friends for being a foundation of support, compassion, and inspiration. You each vicariously lived through the exciting, stressful, tearful, and gratifying moments of this e xperience with me and without you it would not have been half as much fun . Thank you all for your love and reassurance. Finally a nd principally, my deepest thanks go to Omar Driza, my husband, champion, and soul mate. Without his encouragement through each of the long nights

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6 of writing, this accomplishment would have no meaning. Without his personal sacrifices and endless patience while supporting me through this process, this victory would have no value. His strength and ambitious nature was a constant ins piration to me and he never let me forget where I could find my own fortitude. The life that we are building together was my incentive to accomplish this goal and I am proud that I get to share this glory with you. Thank you so much for being my partner an d for having so much faith in me. Thank you for unconditionally loving me and for enduring this test of the human spirit with me. Thank you for being the most amazing man a wife could possibly ask for and for being the inexhaustible voice that drove me to prevail.

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7 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 12 LIST OF FIGURES ................................ ................................ ................................ ........ 14 LIST OF ABBREVIATIONS ................................ ................................ ........................... 16 ABSTRACT ................................ ................................ ................................ ................... 19 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 21 2 LITERATURE REVIEW ................................ ................................ .......................... 25 The LEED Rating System ................................ ................................ ....................... 25 Water Efficiency Category ................................ ................................ ................ 26 En ergy & Atmosphere Category ................................ ................................ ....... 28 Foundations for Predicting Water Consumption ................................ ..................... 31 The Energy Policy Act of 1992 and 2005 ................................ ......................... 32 Uniform Plumbing Code 2006 ................................ ................................ .......... 33 In ternational Plumbing Code of 2006 ................................ ............................... 34 Water Use Reduction Template ................................ ................................ ....... 35 Foundations for Predicting Energy Consumption ................................ .................... 38 ANSI/ASHRAE/IESNA Standard 90.1 2007 ................................ ..................... 38 Optimized Energy Performance Template ................................ ........................ 39 ............................... 41 The Higher Education Community Adopts the LEED Rating System ..................... 45 Predicted vs. Actual Performance for Water and Energy in Higher Education ................................ ................................ ................................ ...... 48 Pacific Lutheran University (PLU) ................................ ................................ ..... 48 Oregon Health & Science University (OHSU) ................................ ................... 50 Environmentally Significant Be havior in Residence Halls ................................ . 51 Understanding Environmentally Significant Behavior ................................ ............. 53 Theory of Planned Behavior ................................ ................................ ............. 55 Value Belief Norm Theory ................................ ................................ ................ 57 Limi tations of Theoretical Behavioral Models ................................ ................... 59 Application of Theoretical Models to Consumption in Residence Halls .................. 60 3 RESEARCH METHODOLOGY ................................ ................................ ............... 71 Research Design ................................ ................................ ................................ .... 71 Mixed Method ology ................................ ................................ .......................... 72

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8 First Stage ................................ ................................ ................................ ........ 73 Second Stage ................................ ................................ ................................ ... 75 Third Stage ................................ ................................ ................................ ....... 75 Case Selection ................................ ................................ ................................ ........ 77 Case Settings ................................ ................................ ................................ ... 78 Case Profiles ................................ ................................ ................................ .... 79 Case one ................................ .................... 80 Case two ................... 81 Case three ............................. 83 Utilizing Typical Cases ................................ ................................ ..................... 84 Research Instruments ................................ ................................ ............................. 85 Demographic Profiles ................................ ................................ ....................... 86 Building Consumption Data ................................ ................................ .............. 87 Survey ................................ ................................ ................................ .............. 88 Resource Tracking Exercise ................................ ................................ ............. 89 Interview ................................ ................................ ................................ ........... 90 Survey and Interview Instrument Development ................................ ...................... 90 Background Concepts ................................ ................................ ...................... 91 Systematized Concepts ................................ ................................ .................... 96 Indicators ................................ ................................ ................................ .......... 97 Pilot Test for Sur vey and Interview ................................ ................................ . 105 ................................ ................................ ............... 107 Data Collection ................................ ................................ ................................ ..... 108 Demographic Profiles ................................ ................................ ..................... 108 Building Consumption Data ................................ ................................ ............ 108 Su rvey ................................ ................................ ................................ ............ 109 Resource Tracking Exercise ................................ ................................ ........... 110 Interview ................................ ................................ ................................ ......... 110 Data Analysis ................................ ................................ ................................ ........ 111 4 FINDINGS ................................ ................................ ................................ ............. 125 Case One ................................ ............................. 125 Demographic Profiles ................................ ................................ ..................... 125 Building Consumption ................................ ................................ .................... 127 Water consumption ................................ ................................ .................. 127 Energy consumption ................................ ................................ ................ 127 Accuracy of LEED Default Settings for Water ................................ ................ 128 Survey findings for water fixture usage and flow durations ...................... 129 Resource tracking findings for water fixture usage and flow durations .... 129 Interview findings for w ater fixture usage and flow durations ................... 130 Energy Related Schedules ................................ ................................ ............. 131 Survey findings for energy related schedules ................................ .......... 132 Resource tracking findings for energy related schedules ......................... 132 Interview findings for energy related schedules ................................ ....... 133 Case Two dley North ............................ 134 Demographic Profiles ................................ ................................ ..................... 134

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9 Building Consumption ................................ ................................ .................... 135 Water consumption ................................ ................................ .................. 135 Energy consumption ................................ ................................ ................ 137 Accuracy of LEED Default Settings for Water ................................ ................ 139 Survey findings for water fixture usage and flow durations ...................... 139 Resource tracking findings for water fixture usage and flow durations .... 139 Interview findings for water fixture usage and flow durations ................... 140 Energy Related Schedules ................................ ................................ ............. 140 Survey findings for energy related schedules ................................ .......... 1 40 Resource tracking findings for energy related schedules ......................... 141 Interview findings for energy related schedules ................................ ....... 142 Case Three ank Hall ................................ ...... 143 Demographic Profiles ................................ ................................ ..................... 143 Building Consumption ................................ ................................ .................... 144 Water consumption ................................ ................................ .................. 144 Energy con sumption ................................ ................................ ................ 145 Accuracy of LEED Default Settings for Water ................................ ................ 147 Survey findings for water fixture usage and flow durations ...................... 147 Resource tracking findings for water fixture usage and flow durations .... 147 Interview findings for water fixture usage and flow durations ................... 148 Energy Related Schedul es ................................ ................................ ............. 148 Survey findings for energy related schedules ................................ .......... 148 Resource tracking findings for energy related schedules ......................... 149 Interview findings for energy related schedules ................................ ....... 150 Findings for Contextual Instruments ................................ ................................ ..... 150 Summary of Demographic Profiles ................................ ................................ . 151 Summary of Building Consumption ................................ ................................ 152 Findings for Research Question 1.1: Accuracy of LEED Default Settings for Water ................................ ................................ ................................ ................. 154 Summary of Water Fixture Usage and Flow Durations Based on Survey ...... 155 Summary of Water Fixture Usage and Flow Durations Based on Resource Tracking Exercise ................................ ................................ ........................ 155 Summary of Water Fixture Usage and Flow Duration s Based on Interview ... 156 Findings for Research Question 1.2: Accuracy of LEED Default Energy Schedules ................................ ................................ ................................ .......... 157 Summary of Energy Related Schedules Based on Survey ............................ 157 Summary of Energy Related Schedules Based on Resource Tracking Exercise ................................ ................................ ................................ ...... 158 Summary of Energy Relate d Schedules Based on Interview ......................... 158 Findings for Research Question 2: Relationship between Behavioral Constructs and Consumption of Resources ................................ ................................ ........ 159 Survey Findings ................................ ................................ ................................ .... 159 Fit between Current Behaviors and Theoretical Framework ........................... 159 Identifying Relevant Behavioral Cons tructs ................................ .................... 160 Summary of Behavioral Construct Findings ................................ ................... 161 Interview Findings ................................ ................................ ................................ . 162

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10 General Knowledge of LEED Certification ................................ ...................... 162 Behavioral Constructs ................................ ................................ .................... 165 Topic 4: Values ................................ ................................ ........................ 166 Topic 5: Beliefs ................................ ................................ ........................ 169 Topic 6: Attitudes ................................ ................................ ..................... 173 Topic 7: Subjective and Personal Norms ................................ .................. 176 Topic 8: Perceived Behavioral Controls ................................ ................... 178 Topic 9: Behavioral Intentions ................................ ................................ .. 181 5 DISCUSSION ................................ ................................ ................................ ....... 199 Comparison bet ween Cases ................................ ................................ ................. 199 Accuracy of LEED Default Settings for Water ................................ ....................... 201 Improving Fixture Usage and Water Duration Defaults ................................ .. 204 Accuracy of LEED Default Energy Schedules ................................ ...................... 205 Improving Energy Related Schedules ................................ ............................ 207 Relationship between Behavioral Constructs and Consumption of Resources ..... 209 General Knowledge of LEED Certification. ................................ ..................... 209 Values in Residence Halls ................................ ................................ .............. 211 Beliefs in Residence Halls ................................ ................................ .............. 212 Attitudes toward Conserving Water and Energy in Residence Halls .............. 213 Subjective and Personal Norms in Residence Halls ................................ ....... 214 Perceived Behavioral Controls in Residence Halls ................................ ......... 216 Behavioral Intentions in Residence Halls ................................ ....................... 217 Recommendations ................................ ................................ ................................ 218 Adjustments to the LEED Certification Process ................................ .............. 218 Require a Cost for Consumption ................................ ................................ .... 219 Require a Program for Fostering Sustainable Behaviors ............................... 221 Incentives ................................ ................................ ................................ . 224 Convenience ................................ ................................ ............................ 225 Early Education of Sustainable Practices ................................ ....................... 226 Theoretical Considerations for Studies on Campus Settings .......................... 228 Limitations and Future Studies ................................ ................................ ............. 231 Conclusions ................................ ................................ ................................ .......... 234 APPENDIX A ............................ 238 B CHIDLEY NORTH RESIDENCE HALL FLOOPLANS ................................ .......... 244 C FRANK RESIDENCE HALL FLOOPLANS ................................ ........................... 246 D IRB APPROVAL ................................ ................................ ................................ ... 249 E CONSENT FORMS ................................ ................................ .............................. 250 F SURVEY INSTRUMENT ................................ ................................ ....................... 254

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11 G RESOUR CE TRACKING INSTRUME NT ................................ .............................. 266 H INTERVIEW INSTRUMENT ................................ ................................ ................. 267 I QUALITATIVE INTERVIEW ANALYSIS CODES AND FINDINGS ....................... 270 J SOCIAL INFLUENCE APP ROACHES AND COMMUNIT Y BASED SOCIAL MARKETING TECHNIQUES ................................ ................................ ................ 294 LIST OF REFERENCES ................................ ................................ ............................. 300 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 319

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12 LIST OF TABLES Table page 2 1 LEED v4 for New Construction (NC) point matrix ................................ ............... 62 2 2 LEED v4 Water Efficie ncy (WE) category ................................ ........................... 62 2 3 LEED v4 Energy & Atmosph ere (EA) category ................................ ................... 62 2 4 Federal water standards for plumbing fixtures and fittings required by Energy Policy Act of 1992 and 2005 ................................ ................................ ............... 62 2 5 Water conserving fixtures and fittings required by Uniformed Plu mbing Code of 2006 ................................ ................................ ................................ ............... 63 2 6 Required capacity at fixture supply pipe outlet required by Intern ational Plumbing Code of 2006 ................................ ................................ ...................... 63 2 7 Default Occupancy Numbers ................................ ................................ .............. 64 2 8 USGBC default fixture uses, by occupancy type ................................ ................ 64 2 9 Default fan schedule originally based on offic e building settings ........................ 65 2 10 Default service hot water schedule originally based on offic e building settings .. 65 2 11 Default lighting schedule originally based on offic e building settings .................. 66 2 12 Tangible Actions Requir ed by the ACUPCC ................................ ....................... 66 2 13 STARS Credits that LEED Certified Buildings can Contribute to . ....................... 67 2 14 Variables influencing environmentally si gnificant behavior ................................ . 68 3 1 Eas t Village Construction Profile ................................ ................................ ...... 115 3 2 Chidley North Residence Hall Construction P rofile ................................ ........... 115 3 3 Fran k Hall Construction Profile ................................ ................................ ......... 115 3 4 LEED Defaults for Water Fixture Usage and Flow Durations, and ANSI/ASHRAE/IESNA 90.1 Settings for Fans, Hot Water, and Lig hting .......... 116 3 5 Cronbach Alpha Scores for Pilot Test ................................ ............................... 117 3 6 S ummary of the Guiding Principles Used to Design Each Survey Section ....... 118

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13 4 1 Demographic Profiles of Universities ................................ ................................ 184 4 2 Demographic Profiles of Survey Participants ................................ ................... 185 4 3 Survey Participant Water Fixture Usage and Flow Durations vs LEED Default Settings ................................ ................................ ................................ ............ 186 4 4 LEED Default Settings ................................ ................................ ...................... 187 4 5 ANSI/ASHRAE/IESNA 90.1 Default Energy Schedule ................................ ..... 188 4 6 ANSI/ASHRAE/IESNA 90.1 Default Energy Schedule ................................ ..... 189 4 7 Confirmatory Factor Analysis Fit Function Tests ................................ .............. 190 4 8 Eigenvalues of the Reduced Correlation Matric ................................ ................ 190

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14 LIST OF FIGURES Figure page 2 1 Schematic Representation of Constructs in the Theory o f Planned Behavior .... 69 2 2 Schematic Representation of Constructs in the Value Belief Norm Theory o f Environmentalism ................................ ................................ ............................... 69 2 3 Theoretical Framework of Study Based on Constructs from the Theory of Planned Behavior and the Value Belief Norm Theory of Environmenta lism ...... 70 3 1 Illustration of Research Design ................................ ................................ ......... 120 3 2 Emor . ................................ ............................... 121 3 3 North Carolina Central University North Residence Hall . .................. 122 3 4 Appalachian State Uni ................................ ...... 123 3 5 Illustration of Data Collecting Instruments ................................ ........................ 124 4 1 East Village Water Consumption Between 2010 2014 ................................ ..... 191 4 2 East Village Energy Consumption Between 2010 2014 ................................ ... 191 4 3 Chidley North Water Consumption Between 2012 2014 ................................ .. 192 4 4 Chidley North Energy Consumption Between 2012 2014 ................................ 192 4 5 Frank Hall Water Consumption Between 2010 2014 ................................ ........ 193 4 6 Frank Hall Energy Consumption Between 2010 2014 ................................ ...... 193 4 7 Survey Findings Related to Fan Schedule ................................ ....................... 194 4 8 Survey Findings Relate d to Hot Water Schedule ................................ .............. 194 4 9 Survey Findings Related to Lighting Schedule ................................ ................. 195 4 10 Resource Tracking Findings Related to Fan Schedule ................................ ..... 195 4 11 Resource Tracking Findings Related to Hot Water Schedule ........................... 196 4 12 Resource Tracking Findings Rela ted to Lighting Schedule .............................. 196 4 13 Scree Plot Based on Exploratory Factor Analysis ................................ ............ 197 4 14 Rotation between Factor 1 and Factor 2 ................................ .......................... 197

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15 4 15 Rotation between Factor 1 and Factor 3 ................................ .......................... 198 4 16 Rotation between Factor 2 and Factor 3 ................................ .......................... 198

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16 LIST OF ABBREVIATIONS AASHE Association for the Advancement of Sustainability in Higher Education AC Awareness of Consequences ACUPCC AGFI Adjusted Goodness of Fit Index ANSI American National Standards Institute AR Ascription of Responsibility ASHRAE American Society of Heating, Refrigerating and Air Conditioning Engineers ASME American Society of Mechanical Engineers BTU British Thermal Unit CBSM Community Based Social M a rke ting CFA Confirmatory Factor Analysis DOE Department of Energy EA Energy & Atmosphere EPAct Energy Policy Act ESB Environmentally Significant Behavior FTE Full Time Equivalent GAL Gallons GBES Green Building Education Services GFI Goodness of Fit Index GPM Gallons per minute HVAC Heating, Ventilation and Air Conditioning IAMPO International Association of Plumbing and Mechanical Officials ID Innovation in Design

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17 IEA International Energy Agency IEQ Indoor Environmental Quality KWH Kilowatt Hour KGAL One Thousand Gallons KLB One Kilopound LEED Leadership in Energy and Environmental Design M BTU One Million British Thermal Units MR Materials & Resources MWH Megawatt H our NAM Norms Activation Model NEP New Environmental Paradigm Scale NC New Construction NYU New York University OHSU Oregon Health & Science University POE Post Occupancy Evaluation PLU Pacific Lutheran University PSI Pound per Square Inch REC Renewable Energy C ertificate RMSEA Root Mean Square Error of Approximation RP Regional Priority SEC Seconds SS Sustainable Sites STARS Sustainability Tracking and Rating System SQ FT Square feet TAG Technical Advisory Group

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18 THM One British Therm TPB Theory of Planned Behavior UNEP United Nations Environment Programme U.S. United States USGBC U nited States Green Building Council VBN Value Belief Norm Theory of Environmentalism WE Water Efficiency WK Week WKD Weekend

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19 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the R equirements for the Degree of Doctor of Philosophy OPTIMAL BUILDING PERFORMANCE: EXPLORING HUMAN BEHAVIOR IMPACTS ON ENERGY AND WATER CONSUMPTION IN CAMPUS RESIDENCE HALLS By Pamela Jean Nichol Driza December 2014 Chair: Nam Kyu Park Cochair: Maruja Torres Antonini Major: Design, Construction and Planning Under mounting pressure from users, stakeholders, and governmental agencies many universities have made commitments to incorporate environmental literacy into their courses and adopt the LEED buildi ng standards throughout their campuses. D espite the growing use of this rating system research has indicate d that occupant behaviors remain an obstacle to long term building efficie ncy, particularly in residence halls ( Bekker et al. , 2010 ). Thus, this stud y investigate s how accurately occupant behaviors are accounted for in the LEED rating system and determine if any relationships exist resources ? Utilizing a comparative case study approach , three LEED certified residence halls were examined . Qualitative and quantitative methodologies, including demographic profiles , building consumption data, a s urvey, resource tracking exercises , and interview s were de signed to assess the environmentally sig nificant behaviors (ESB) of residents . Collected data were then compared to the LEED referenced settings for

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20 water and energy, and two behavioral theory frameworks in order to determine how actual resident behaviors compared to current estimates for resour ce consumption . Consistent with previous research, all three cases demonstrated a discrepancy between their predicted and actual performance level s . Findings also revealed that residents utilized water less often and energy more often than stipulated by the current default settings. Finally , resident ESBs were most influenced by subjecti ve and personal norm s , altruistic and biospheric values, attitude s , and behavioral intention s . Based on findings, i t w as determined that the referenced settings do not differentiate between building types or reflect the actual behavior s o f residents . Additionally, it was clear that impr oved building performan ce relies upon a balance between technological solutions and imp roved occupant behaviors . Recommendations are given to support the improved performance of residence halls through community based social marketing techniques and other strategies . This study aids in the continued development of the LEED rating system and the understanding of occupant ESBs in residence halls.

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21 CHAPTER 1 INTRODUCTION For three decades there has been a growing awareness of how the building sector impacts the global environment. It is estimated that residential and commercial buildings contribute as much as one third of the total greenhouse gas emissions (United Nations Environment Programme [UNEP], 2009), consume 40 percent of produced energy ( International Energy Agency [ IEA ], 20 12 ), and represent the third largest category o f water consumption in the U.S. ( U.S. Green Building Council [USGBC], 2013c ). In order to address the growing threat of noxious emissions and depleting natural resources, governmental regulations are target ing the urban planning market and driv ing the desi gn of enhanced performance buildings (Hadi & Halfhide, 2011). As a result, building performance assessment tools have been developed and widely Environmental Assessment Method (BREE AM), the Comprehensive Assessment System for Building Environmental Efficiency (CASBEE), the Green Building Challenge, Green Globes, and Leadership in Energy and Environmental Design (LEED) ( Fowler & Rauch, 2006) . Notable among these tools is the U . S . LEED system , which is the leading building assessment tool in the U.S. and second most used rating system in the world with over 7 3 ,415 certified projects ( USGBC, 2014 ). Th is assessment tool focus es on reducing the ecological foot print of built environments and ha s been connected to increased user satisfaction, positive impacts on occupant health, and reduction in maintenance costs ( Singh, Syal, Grady, & Korkmaz, 2010 ). States (U.S.) have begun to embrace green building standards in an effort to increase recruitment,

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22 enhance reputational value, and lower operational costs ( The Princeton Review, 2011; University Le aders f or a Sustainable Future, 2008 ) . As the entities resp onsible for training the next generation of leaders, many of these institutions have made commitments to incorporate sustainability and environmental literacy into their courses, research, building operation methods, and campus residences. The LEED certifi cation of higher edu cation buildings and residence halls has notably experienced an exponential growth since 2002 and by 2009 accounted for 13% of all LEED certified projects (Galayda & Yudelson, 2010). The strong association between LEED and the potential reduction in environmental impacts has provided additional impetus for campuses to continue to certify their new and existing buildings. However , despite the growing use of this rating system , research has indicated that occupant behavior remains an obsta cle to long term building efficie ncy, particularly in residence halls where water and energy co nsumption experiences up to a 50% increase ( Driza et al., 2012; Petersen, Shunturov, Janda, Platt, & Weinberger, 2007 ). isparities often exist between how buildings are designed to operate and how they actually perform. Numerous factors can explain a , p.1 ). For example, a ll too often the water use calculations and energy simulation models utilized to obtain points within the LEED system are based on assumptions of behaviors that do not accurately represent the end users ( Clevenger & Haymaker, 2006; Men assa & Azar, 2012 ; USGBC, 2013b ). As a result of oversimplifying occupancy schedules , referenced standards , and underestimati ng the important role that user behavior play s in overall building

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23 performance , the variation between predicted and actual resource consumption is estimated to range between 30% and 100% ( Azar & Menassa, 2010; Turner, 2006 ; Yudelson, 2010 ). Even the largest, USGBC funded, study of LEED certified buildings acknowledged the variability between predicted and measured performance and conc luded that it has significant implications for life cycle cost evaluations (Turner & Frankel, 2008). Thus, one could surmise that a follow up investigation into end user behaviors is a critical component to improving future predictions for higher education settings, their residence halls, and ultimately the LEED rating system. Statement of Purpose . In an effort to b etter understand the trends in building performance the USGBC release d an updated rating system in 2013, LEED v4 . This system built on the fundamental structure of the previous rating guides by focusing on harmonizing prerequisites and credits, revising credit weightings, and identifying regionally specific environmental issues ( USGBC, 2013a ). Part of the requirements for this ra ting system also mandate available water and energy consumption data so that research on building performance could continue to shed light on operating inefficiencies. This revised commitment to impro ve the organization of its certification process and develop a product that will meet the needs of a range of dynamic project s . However, while the USGBC has been successful in clarifying its procedures with this newest update, it remains unclear if the req uirements for predicting water and energy consumption adequately consider the behaviors of actual building users, including those in student housing . Without addressing and understanding occupant behavior, it seems unlikely that the current gap between int ended building performance and actual consumption

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24 would come to a satisfactory close. Therefore, the goal of this study is to investigate and answer the following research questions and sub questions : 1. How accurately are occupant behaviors accounted for by the current LEED rating for predicting water and energy consumption? 1.1 How accurate are the LEED referenced standards for water usage and flow durations in residence halls? 1.2 How accurate are the LEED referenced standards for fan, water heater, and lighting schedules in residence halls? 2. What relationship , if any, exist s between behavioral constructs and oc cupant s consumption of water and energy in LEED certified re sidence halls?

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25 CHAPTER 2 LITERATURE REVIEW This chapter reviews the literature that is relevant to the LEED rating system and environmentally significant behaviors. The tools used for predicting water and energy consumption are first reviewed. The adoption of the LEED rating system and its certific ation process in higher education settings are then discussed. A foundation for understanding environmentally significant behaviors in the context of residence halls is established by reviewing existing behavioral research . Finally, a theoretical framework for the study and the use of behavioral theories including the Th eory of Planned Behavior and Value Belief Norm Theory are described. The LEED Rating System realized that the buildi ng industry lacked a system for measuring sustainable construction. By 1998, a diverse composition of USGBC committee members launched the first LEED Pilot Program, better known as LEED Version 1.0 (Winchip, 2012). Since then, the rating system has continu ed to be modified and has evolved to undertake a number of initiatives. In addition to a rating system dedicated to building operational and maintenance issues, LEED addresses the different project development and delivery processes that exist in the U.S. building design and construction market. To date, the USGBC has created rating systems for specific building typologies, sectors, and project scopes including, LEED for Core & Shell, LEED for Commercial Interiors, LEED for Healthcare, LEED for Homes, LEED for Neighborhood Development, LEED for New Construction, LEED for Retail, and LEED for Schools (USGBC, 2011b ).

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26 The LEED rating systems are market driven and help to evaluate environmental performance from a who le building perspective. LEED v4 for New Construction is organized into seven categories : Sustainable Sites (SS), Water Efficiency (WE), Energy & Atmosphere (EA), Materials & Resources (MR), Indoor Environmental Quality (IEQ) , Innovation in Design (ID), and Regional Priority (RP) ( USGBC, 2013b ). Each category in a LEED rating system is sub divided into a list of prerequisites and credits. Prerequisites are required green building practices that must be addressed for a project to be a viable candidate for certification . Credits are optional strategies that a project team may elect to pursue in order to gain certification. Each credit in the LEED rating n of points between credits is based ( USGBC, 2013b , p. 13 ) . As a project progresses throu gh design development and construction, the project teams responsible for the design and cons truction of a building will submit documentation to demonstrate their compliance with each prerequisite, credit , and their associated referenced industry standards. The more credits and relative points a project team achieves, the higher their building wil l be rated within the LEED system . Platinum is the highest level of certification, followed by Gold, Silver , and Certified. Table 2 1 illustrates the matrix of points required to reach each level of certification for LEED v4 . Water Efficiency Category The Water Efficiency category encourages project teams to utilize sustainable strategies and technologies to reduce the amount of potable water consumed within buildings while still meeting the needs of the occupants and systems ( USGBC, 2013b ). Using large vol umes of water threatens the reserves in aquifers, increases maintenance

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27 costs for building operations, and increases consumer fees for additional municipal supplies and treatment facilities. By minimizing the demand and conserving potable water, buildings can reduce costs through lower fees, less sewage volume, and less energy consumption when it is integral to the supply water ( USGBC, 2013b ) . The WE category is designed to address water consumption associated with restrooms, landscaping, and process water for building systems. In order to successfully achieve the prerequisite and credits within this category design teams are encouraged to strategically plan conservative water systems early in the design process and to continue to monitor flow rates after co nstruction has been completed and the building has been occupied. Therefore, LEED certified building are likely to have integrated a combination of technologies to help track and conserve the water that flows from regulated fixtures in and outside of the b uilding. Some suggested methods for reducing indoor potable water include the use of water efficient faucets, showerheads and toilets , waterless urinals , and recycling graywater (Winchip, 2012). The USGBC also suggests a variety of strategies for reducing outdoor water use. For example, design teams are encouraged to specify native and/or adaptive plants, which are naturally inclined to grow well in the local climate and will require less water. X eriscaping , a type of landscaping and gardening that reduces or eliminates the need for supplemental irrigation, is another method that can be utilized ( Green Building Education Services [GBES], 2009). For arid areas where supplemental irrigation is necessary, the installati on of a drip or bubbler distribution system could be an effective solution. These types of h igh performance irrigation systems include efficient water supply and control technologies , which respond to weat her conditions (USGBC, 2011b ).

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28 Finally, choosing an alternative water source may also be a suitable option for reducing the outdoor consumption of potable water. Both stormwater and graywater systems can be installed onsite, collected in cisterns, barrels or storage tanks, and utilized on demand for irriga tion purposes (GBES, 2009). Finally, buildings can utilize a series of cooling towers, boilers, chillers , and heating, ventilation and air conditioning (HVAC) systems to regulate the indoor environmental conditions . The installation of each of these system s typically includes an attached water line and therefore has the potential to contribute to wards overall potable water consumption and costs. Although these systems often require a water source to properly operate, it is entirely unnecessary for the sourc e to be potable. Thus, the USGBC suggests a number of strategies to reduce the consumption of water for process needs. Some such strategies include specifying water efficient building systems and substituting non potable rainwater or graywater for processe d water needs. Finally, submetering all water using systems is highly recommended so that leaks can be detected and restored as quickly as possible ( GBES, 2009 ). Table 2 2 illustrates the prerequisite, credits, and total number of points that may be awarde d within the LEED v4 WE category. Energy & Atmosphere Category Generating electricity from fossil fuels, such as oil and coal, negatively affects the environment at each step of its production including its extraction, refining, distribution, and consumpti on. The activities associ ated with cultivating fossil fuels have been linked to the generation of carbon dioxide, nitrogen oxide and sulfur dioxide gas, which deplete the ozone layer and endanger the health of ecosystems ( America's Energy Future Panel on E nergy Efficiency Technologies , 2010 ) . Therefore, the Energy & Atmosphere

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29 category encourages project teams to address their consumption of fossil fuels in four primary ways: reducing the demand of energy , improving energy efficiency, using alternative forms of energy, and monitoring ongoing energy performance . In order to identify synergistic strategies amongst these elements, it is essential for project teams to utilize an integrated design process, an approach that emphasizes the collaboration and com munication among professionals throughout the life of a project ( Winchip, 2012 ) . design. Early in the integrated design process, teams must critically consider a in order to ensure that the final built environment does not exceed occupant needs. By appropriately scaling a facility, designers can instantly impact the energy demands from excess plug loads, lighting grids, and HVAC systems. It is also recommended that projects ascertain if opportunities exist for capturing incident energy. [USGBC, 2011b , p. 48). Additionally, the proper orientation of a building can allow teams to take advantage of natural ventilation, solar energy, and daylighting opportunities. For instance, if a building is oriented on a site to maximize southern exposure and minimize western exposure, designers can take advantage of the sun for daylight, passive sola r heating during winter months, and reduced cooling cost during summer months (GBES, 2009). Exterior architectural features such as light shelves and awnings have also been known to impact energy demand by reducing the need for artificial lighting, heating , and cooling. Finally, project teams can reduce the demand for

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30 energy by installing insulation and effectively sealing the building envelope to protect from heating and cooling losses (USGBC, 2011b ). In an effort to improve energy efficien cy, LEED v4 ref erences the requirements in the ANSI/ASHRAE/IESNA 90.1 2007 energy standard. This guide establishes minimums for the energy efficient design of a variety of buildings, including commercial and high rise residential spaces. This reference guide addresses an d provides provisions for designing building envelopes, HVAC systems, hot water heaters, and lighting systems ( American Society of Heating, Refrigerating and Air Conditioning Engineers [ASHRAE], 2009). Integrated design teams may also utilize p rograms such as ENERGY STAR to help in their selection of energy efficient appliances and equipment. ENERGY STAR is a joint program of the U.S. EPA and the U.S. Department of Energy that protects the environment by promoting energy efficient products and practices. Th rough its partnership with more than 20,000 private and public organizations, ENERGY STAR delivers technical information, tools, and labeling that consumers need to choose energy consuming products. Products that are frequently ENERGY STAR qualified includ e appliances, computers, electronics, lighting, fans, battery chargers, water heaters, heating and cooling equipment, and building products ( ENERGY STAR, 2013 ). With the technological advancements in renewable energy options, it is now more feasible to mee with renewable energy sources. Some of the available sources across the globe include hydro, wind, solar, bio mass, geo thermal and hydrogen energy ( Karthikeyan, 2012 ) . Use of these sustainable energy sources has fewer ecologica l impacts than the production and consumption of

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31 traditional fossil fuels . The application of renewable energies for LEED projects can come in the form of on site and off site sources. Thus, an alternative for projects that may not have the capacity for installing solar panels, wind mills or turbine equipment, there is now the option for purchasing offsite renewable energy from utility providers . Renewable Energy C ertificate (REC s ) are t radable, non tangible energy commodities that represent proof that one megawatt hour (Mw h) of electricity was generated from an eligible renewable energy source ( National Renewable Energy Laboratory, 2005). In addition to supplementing a building s use of fossil fuels , the purchase of RECs also helps to generate a demand for additional renewable energy sources . Finally, it is highly recommended that all integrated design teams plan for and install the necessary equipment to monitor the ongoing energy performance of buildings . In doing so, facility operators will have the ability to verify that energy consuming equipment is functioning as expected and can quickly identify malfunctions should they arise over time. Additionally, the LEED v4 system recommends that all operating staff be formally trained to use the energy savin g systems to ensure that sustainable strategies are properly utilized. Table 2 3 illustrates the prerequisite, credits, and total number of points that may be awarded within the LEED v4 EA category. Foundations for Predicting Water Consumption Each prereq uisite and credit in the LEED rating system references an industry standard that represents a best practice for designing, constructing, and operating sustainable buildings. In order to be awarded points for any one credit in the rating system, project tea ms must adhere to the requirements described by each industry standard as well as the documentation templates developed by the USGBC. This study first investigates the prediction tools used for estimating water and energy consumption

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32 in campus residential halls, where significant increases have been noted in resource use ( Bekker et al. , 2010 ; Building Research Establishment, 2012 ; Driza & Park, 2013 ). Thus, the standards described herein are those that align with WE, Credit 3 Water Use Reduction and EA, Credit 1 Optimized Energy Performance ( USGBC, 2013b ). In order to better assess how accurately occupant behaviors are accounted for by theses referenced standards, each has been described below. The Energy Policy Act of 1992 and 2005 WE, Credit 3 Water U se Reduction references four industry standards: the Energy Policy Act of 1992, Energy Policy Act of 2005, Uniform Plumbing Code of 2006, and the International Plumbing Code of 2006 ( USGBC, 2013b ). The enactment of the Energy Policy Act (EPAct) of 2009 rep resented more than five years of committed input by numerous conservation specialists, water managers, environmental organizations, and elected representatives. Although this federal standard primarily addresses energy conservation strategies, it was recog nized that a number of methods for reducing energy consumption were a direct result of sustaining water. For example, by conserving the amount of water that needs to be treated, transported, and heated, energy demands are consequently reduced ( National Ren ewable Energy Laboratory, 2002) . Thus, the act was developed to simultaneously outline methods for reducing water consumption. The EPAct of 1992 was organized to address three components of water consumption. Maximum water use rates were first regulated for toilets, urinals, showerheads, and faucets manufactured after January of 1994. Test procedures for establishing flow rates were and still remain the responsibility of the American Society of Mechanical Engineers (ASME) and the American National Standar ds Institute (ANSI).

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33 Additionally, the EPAct of 1992 requires manufactures to permanently adhere product the Department of Energy (DOE) assist states governments in creating incentive programs for consumers to replace existing fixtures for products that meet the EPAct standards (Vickers, 1993 ). In 2005, the EPAct was passed as a bill by the U.S. Congress an d subsequently signed into law by President George W. Bush. In addition to explicitly setting the previously outlined components of water consumption into law, the updated EPAct of 2005 stipulated tax incentives and loan guarantees for the implementations of conservation methods (Holt & Glover, 2006). Since the release of LEED Version 2.0 in March of 2000, the USGBC has referenced the maximum water use rates presented in the EPAct of 1992 ( USGBC, 2001) update d to also include an alignment with the EPAct of 2005. These flow rates are now used by the USGBC to define the baseline performance required of plumbing fixtures in LEED certified buildings. Table 2 4 illustrates the water use standards required by the EP Act of 1992 and 2005. Uniform Plumbing Code 2006 The International Association of Plumbing and Mechanical Officials (IAMPO) developed the Uniform Plumbing Code of 2006 as a national standard. This ANSI accredited code is intended to safegua rd property and p ublic welfare by regulating the desi gn, construction, installation, operation, maintenance and use of plumbing systems . Each section within the code was developed using the American National Standards -a pro cess in which representatives from a variety of design industries come together to achieve consensus on plumbing

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34 practices ( International Association of Plumbing an d Mechanical Officials [IAMPO], 2006). The codebook in its entirety is reviewed every three years and revisions are made to respond to industry advancements. For Credit 3 Water Use Reduction in the latest version of the LEED system, the USGBC specifically references Section 402.0 : Water Conserving Fixtures and Fittings of the Uniform Plumbing Cod e of 2006 ( USGBC, 2013b ). This section defines the flow rate standards for water efficient fittings, water cl osets, urinals, and metered faucets. Similar to the EPAct Code of 1992 and 2005, flush tank, flushometer, and flushometer valve operated toilets ar e subject to an average consumption of not more than 1.6 gallons per flush. Additionally, this section reinforces that urinals shall have an average water consumption of not more than 1.0 gallon per flush. Unique to this code is its definition for metered faucets. Section 402.4 Metered Faucets states that self closing or self closing metering faucets, which are typically installed in airports, train stations or other transient public facilities, are required to deliver no more than 0.25 gallons of water per use (IAMPO, 2006). Since the revision of the LEED rating system in 2009 the USGBC has referenced this standard to guide project teams in selecting efficient fixtures. Table 2 5 has been provided to illustrate the flow rates defined by the Uniform Plumbing Code of 2006. International Plumbing Code of 2006 The International Plumbing Code of 2006 is a standard that sets minimum requirements for the design, installation, and function of plumbing systems. This code provides criteria for a variety of plumbing components including water heating equi pment, anti scalding devices, backflow prevention devices, and water pipe sizing. Every three years, the International Code Council publishes an updated codebook,

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35 which reflects on the latest advancements in the plumbing industry. Each section within the c odebook has been established through the governmental consensus process, which allows for an open forum of debates and refinements by public safety officials. The International Plumbing Code is the most widely adopted plumbing standard in the U.S. and is a lso used as the basis for plumbing standards in several other countries ( International Code Council, 2006) . The latest version of the LEED system requires project teams to references the Section 604, Design of Building Water Distribution System if they chose to pursue Credit 3 Water Use Reduction. Similar to the previously described codes, this section defines equivalent maximum flow rates for toilets, urinals, showerheads, and faucets. However, unique to this standard is the minimum flow pressure set for residential and commercial fixture demands during peak hours , or a time frame of high customer demand ( International Code Council, 2006) . By providing a guideline for flow pressure, this standard ensures that fixtures and appl iances receive an adequate supply of water to function and meet occupant needs. Table 2 6 has been provided to illustrate the minimum flow pressures defined by the International Plumbing Code of 2006. Water Use Reduction Template In order to be awarded p oints for WE, Credit 3 Water Use Reduction project teams must first meet WE, Prerequisite 1 by employing water conserving strategies that in aggregate use a minimum of 20% less potable water than a building built to conventional code standard (USGBC, 2011b ). As an extension of this prerequisite, WE, Credit 3 then requires an additional 10% savings, for a total 30% reduction in indoor potable water use. Utilizing the USGBC developed Water Use Reduction Template

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36 project teams calculate a baseline and a design case. A baseline case is generated by multiplying the estimated occupancy and fixture usage with the fixture flow rates outlined in the Energy Policy Act of 1992, Energy Policy Act of 2005, Uniform Plumbing Code of 2006, and the International Plumbing Cod e of 2006. Similarly, a design case is predicted by multiplying the estimated occupancy and fixture usage with the tested fixture flow rates documented in the manufacturer cutsheets for installed products ( USGBC, 2013b ). The comparison of the baseline and design case is used to predict the minimum water savings percentage of a LEED certified building. Project teams are provided a number of default calculation settings for approximating occupancy and the usage of water closets, urinals, lavatory faucets, sh owerheads, kitchen sink faucets, and pre rinse spray valves. The default settings Technical Advisory Group (TAG); a multidisciplinary team of volunteer engineers, university faculty members, water industry experts, and environmental consultants who review the requirements for each WE credit and guide the development of the LEED reference guides ( USGBC, 2013b ). As conceded by the WE TAG, project teams may approximate their occupancy based on project scope, unit number and size, or building square footage. In most new construction cases, project teams will provide a Full time equivalent (FTE) and total building us er calculation based on the number of full time, part time and transient projects that include a residential space, the number or residents may be estimated based on the number and size of each bedroom unit. For example, teams may assume

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37 two residents per 1 bedroom unit, three residents per 2 bedroom unit, and so on. Finally, if occupancy is unknown during design, which is typically the case for mixed use and core and she ll projects, teams may use the 2004 ASHRAE adapted Default Occupancy Count chart, which provides an occupancy estimate by square footage USGBC, 2013b ). Table 2 7 has been provided to illustrate the default occupancy counts adapted from ASHRAE. Default fixt ure usage rates are also provided for each USGBC recognized occupant type. FTE, transient, retail customers, and residential users have each been paired with an estimate for their daily fixture use and the duration each fixture is used for. Currently the e stimates provided by the USGBC for residential fixture usage and flow durations indicate that male and female residents will utilize a water closet 5 times per day. It is also anticipated that both types of residents will use a lavatory faucet 5 times per day for a duration of 60 seconds each, a showerhead once a day for 480 seconds, and a kitchen sink 4 times per day for a duration of 60 seconds per use (USGBC, 2013b). It should be noted that the USGBC does not distinguish between different types of reside ntial settings, such as a single family homes, apartments, or residence halls. Additionally, while the current consideration of occupant impacts on water consumption, many times the methodology used to establish the def aults were unclear. With the exception of the Default Occupancy Count chart, the latest LEED reference guide does not indicate if the se de fault settings have been tested or based on preexisting standards ( USGBC, 2013b ). Table 2 8 has been provided to illus trate the default fixture usage rates defined by the USGBC.

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38 Foundations for Predicting Energy Consumption ANSI/ASHRAE/IESNA Standard 90.1 2007 In order to achieve points for EA, Credit 1 Optimized Energy Performance, project teams must adhere to the requir ements established by one of the following standards: ANSI/ASHRAE/IESNA Standard 90.1 2007: Energy Standard for Buildings Except Low Rise Residential, ASHRAE Advanced Energy Design Guide for Small Office Buildings 2006, ASHRAE Advanced Energy Design Guide for Retail Buildings 2006, ASHRAE Advanced Energy Design Guide for Small Warehouses and Self Storage Buildings 2008, ASHRAE Advanced Energy Design Guide for K 12 School Buildings, and the New Building Institute, Advanced Buildings Core Performance Guide ( U SGBC, 2013b ). Prior to completing the documentation for this credit, project teams would select a compliance path based on their construction type and project size. As this study centers on higher education student housing settings, one can infer that ANSI /ASHRAE/IESNA Standard 90.1 2007 is the most appropriate reference to further investigate. This compliance path establishes minimum requirements for the energy efficient design of commercial and high rise residential buildings. Originally published in 1975 , the standard has undergone a number of revisions in response to the rapid changes in technology and energy prices. There are many states that now reference this standard or its equivalent to guide the construction and renovation of buildings (ASHRAE, 200 9). ASHRAE 90.1 is divided to guide the proper simulation of several building components including the building envelope, HVAC, hot water heaters, and lighting systems. The simulation of the building envelope, or the protective barrier that separates the interior and exterior environments of a building is carefully regulated to ensure that

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39 the intended building design is aptly represented (Winchip, 2012). This section of the code provides information on modeling regionally appropriate insulation for buildi ng roofs, above grade walls, and below grade walls. Additionally, requirements are established for properly simulating the reflective surfaces of building roofs, exterior wall assemblies, and other shading devices. This standard also outlines methods for s imulating energy efficient HVAC systems and hot water heaters. For both mechanical systems project teams are required to simulate the equipment capacities and efficiencies as defined by the product manufacturer. Requirements are established for modeling th ermally insulated piping for both system types and specifying the use of appropriate circulation pumps and temperature controls. Finally, lighting systems must abide by the power density requirements prescribed by this standard. This section helps project teams to minimize energy consumption by installing adequate lighting fixtures and lighting controls (ASHRAE, 2009). Optimized Energy Performance Template In order to be awarded points for EA, Credit 1 Optimized Energy Performance project teams must first m eet EA, Prerequisite 2 by demonstrating either a 10% improvement in proposed energy costs for new buildings or a 5% improvement for major renovations ( USGBC, 2013b ). As an extension of this prerequisite, EA, Credit 1 provides a point for every 2% increment of savings, resulting in a 12% 48% range of recognized reduction in energy expenses. Utilizing the USGBC developed Optimized Energy Performance Template project teams calculate a baseline and a design case. In order to calculate the baseline performance o f a building, computer simulation models are generated according to ANSI/ASHRAE/IESNA Standard 90.1 2007 (USGBC 2013c ) . The design case is then generated utilizing the proposed energy conserving

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40 strategies as well as the mandatory provisions provided in AN sections 5.4 Building Envelope Requirements, 6.4 Heating, Ventilation and Air Conditioning Requirements, 7.4 Service Water Requirements, 8.4 Power Requirements, 9.4 Lighting, and 10.4 Other Equipment Requirements of ANSI/ASHRAE/IESNA Stan dard 90.1 2007 (USGBC 2013c ) . The comparison of the baseline and design case is then used to predict the minimum percentage of energy cost savings in LEED certified buildings. Frequently engineers will estimate building operation and occupancy schedules b personal communication, February 6 th , 2013). However, several default schedules have been available since the ASHRAE 90.1 standard was released in 1989. Operating schedules ill ustrate the peak demand of several building features including HVAC fans, service hot water , and lighting. Currently the referenced ANSI/ASHRAE/IESNA fan schedule indicates that occupants will utilize the HVAC system during two peak periods or time frames of high customer demand. The first peak period is between 6:00am 7:00pm (13 hrs) where approximately 67% of occupants are expected to utilize this building system. The second peak period is between 7:00pm 11:00pm (4 hrs) where approximately 33% of occupant s are expected to utilize this system. Additionally, the hot water schedule indicates that approximately 21.7% of occupants will utilize the hot water heater between the peak hours of 9:00am 6:00pm. Finally, the lighting schedule indicates that approximate ly 37% of occupants will utilize the overhead lighting system between the peak hours of 10:00am 7:00pm (ASHRAE, 2009 ) . It is noted that s ince the release of ASHRAE Standard 90.1 1989, none of the subsequent code revisions have

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41 updated information regarding peak occupancy and occupancy schedules , and the same schedules are used for bo th commercial and high rise residential buildings (ASHRAE, 1989) . Thus, unless noted otherwise by project programs, simulation models may potentially default to the fan, hot wat er, and lighting schedules illustrated in Tables 2 9, 2 10 and 2 11. the LEED Rating System Despite s kepticism building performance or cost savings, it has undeni ably become the most recognized green building standard in the U.S. The widespread governmental adoption of green construction standards began in 2006 when congressional representatives enlisted the General Service Administration (GSA) to evaluate the pred ominant building rating systems in the U.S. At that time, this list consisted of the BREEAM, CASBEE, Green Building Challenge, Green Globes, and LEED rating tools. The review criteria for this evaluation were defined by the sustainable design drivers found ed by the Energy Policy Act of 2005, the Federal Leadership in High Performance and Sustainable Buildings Memorandum of Understanding, the Energy and Transportation Efficiency Management Circular, the Greening the Government through Efficient Energy Manage ment Order, and the Greening the Government through Waste Prevention, Recycling and Federal Acquisition Order ( Fowler & Rauch, 2006) . As a result of this evaluation many prominent governmental departments, including the GSA, the U.S. Department of Agricult ure (USDA), the Environmental Protection Agency (EPA), and the U.S. Department of Energy (DOE), officially adopted the LEED rating system and began to stimulate its assimilation at the state and local levels ( Fowler & Rauch, 2006; U.S. General Services Adm inistration [GSA], 2013) . The various LEED initiatives that have

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42 since been included in legislation, executive orders, and ordinances, have helped to shape the green building objectives and high performance requirements in the U.S. Shortly following the release of its report, the GSA became the first federal member of the USGBC and has helped in the development of subsequent LEED Rating System Reference Guides. For the last decade the GSA has designed all of its new and renovated buildings to meet a LEED Silver standard and has recently increased its minimum requirements to LEED Gold. Additionally, the GSA has committed to register all of its certified buildings with the additional LEED for Existing Buildings system within five years of their construction and occupancy (GSA, 2013) . As of June of 2010 the GSA had 48 LEED certified projects and manages the work environments for over one million federal employees. Its next steps are to make its conferences greener by utilizing LEED certified facilities and lod ging, and by renovating its historic properties to LEED Gold or Platinum standards (GSA, 2013) . In June of 2006, the USDA issued Departmental Regulation No. 5500 001 ( U.S. Department of Agriculture [USDA], 2013) . This guideline required that all new const ruction and major renovations of USDA facilities receive a minimum LEED Silver rating. In 2007 these requirements, along with additional procedures for addressing the consumption of resources in existing USDA facilities, were integrated into the department Performance Plan. To this day, the USDA regularly updates these two policies and now utilizes a number of LEED rating systems including the LEED for New Construction, LEED for Com mercial Interiors, and LEED for Existing Buildings ( USDA, 2013) .

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43 In 2006, the EPA determined that all of its new facility construction, major renovations, and new building acquisitions over 20,000 square feet would meet a minimum LEED Silver rating. As m ost of its major offices are in leased locations, the EPA created the Best Practice Lease Provision form, which integrates LEED principles into standard lease language (USGBC, 2011c ). This document enhances traditional lease terms by emphasizing the import ance of conservation energy and water. Additionally, the signature leasing agreement includes procedures for ensuring the long term environmental performance of properties. By integrating these provisions into the on and acquisitions plans, the EPA has been successful in establishing 19 work environments that meet either a LEED Silver, LEED Gold, or LEED Platinum rating. In February of 2008, the Secretary of Energy issued DOE Order 430.2B and Executive Order 13423 to the various division leaders at the Department of Energy ( U.S. Department of Energy, [DOE], 2013) . These documents instructed that all new department buildings and major renovations with a value of five million dollars or more meet a minimum LEED Gold standard. These directives also required that the selection criteria for acquiring newly leased spaces give preference to LEED Gold properties. Later that same year the DOE established a High Performance and Sustainable Buildings Implementation Plan to det ail how it would pursue these LEED initiatives. By May of 2011, the department adopted the more stringent DOE Order 436.1, which provided guidelines for managing sustainability across the federal organization and achieving net zero in future building stock s. To date, the DOE continues to support the

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44 advancement of the LEED rating system by contributing to reference guide updates and providing related training workshops to the public ( DOE, 2013). Pressure from prominent federal departments to sustainably a ddress built environments has impacted the design and construction of sites at the state and local level. Most significant to this study are the regulations found in the states of Georgia and North Caro lina, where the four residence halls examined in this study are located. Elizer and Mudy Hall of Emory Oxford College, Frank Hall of Appalachian State University, and Chidley North of North Carolina Central University are described in further detail in Chapter 3. The Georgia based county surrounding Emory O subject to Ordinance #03 0 1693, which requires that all city funded projects over 5,000 square feet or costing two million dollars, meet a minimum Silver rating ( USGBC, 2011c ) . While the college itself may not solely benef it directly from city funds, the college administration took it upon itself to adopt similar requirements as a part of the Oxford College Strategic Plan and continues to LEED certify its new and existing construction today ( Emory Oxford College, 2013b ). Si milarly, the North Carolina based residence halls of Appalachian State University and North Carolina Central University are subject to state Senate Bill 581, which promotes the achievement of LEED certifications by reducing permitting fees and offering par tial rebates ( USGBC, 2011c ) . In addition to the state regulation, the county surrounding North Carolina Central requires all new construction over 10,000 square feet to be a minimum LEED Gold. As

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45 a r standard ( North Carolina State University, 2013) . The use of the LEED rating system has currently been integrated into 442 localities, 34 state governments, and 14 fede ral agencies and departments ( USGBC, 2011c ). It is estimated that government owned or occupied LEED buildings make up 30% of all LEED certified projects and account for approximately six hundred million square feet of constructed building space (Katz, 2012 ; USGBC, 2011d ). As a result of mandating the use of this rating system the governmental sector has endeavored to lead by example by addressing their environmental impact, operational costs, and the maintenance of publicly funded facilities. The Higher Edu cation Community Adopts the LEED Rating System With approximately 74% of U.S. academic entities receive governmental funding (U.S. Department of Education, 2012; The Princeton Review, 2011) a strong correlation may be seen between the rate in which governm ental entities adopted the LEED rating system and the number of educational buildings certified with this rating system today. There are approximately 140,000 schools, colleges, and universities in the U.S., and lation attends school or sets foot on a campus every day ( The Princeton Review, 2011). For years, American colleges and universities have strived to meet the needs of these students, faculty, and prospective donors with the most innovative and functional f acilities ranging from laboratories to dormitories. As a result, the higher education sector has become a multi billion dollar industry that now totals over 273 million square feet of construction (Basu, 2011). Due to this financial value, their prominence in construction, and the leading role universities play in training and educating future generations , campuses have experienced

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46 mounting pressure from impending litigation, international and domestic regulations, and shareholder s , to adopt sustainable pra ctices and reduce their consumption of resources ( Worth, 2005) . According to the USGBC, higher education institutions have certified buildings under a variety of LEED rating systems including LEED for New Construction, LEED for Commercial Interiors, LEED f or Existing Buildings, and a new LEED Pilot Portfolio Program, which is a volume application process that enables the certification of multiple campus buildings at once ( USGBC, 2014 ). At the end of 2009, buildings on colleges and university campuses accoun ted for over 13% of all LEED certifications and 3,000 additional projects were registered for future certification with the USGBC (Galayda & Yudelson, 2010). entities and campuses, it was directly built into two of the higher education sustainability initiatives developed in 2006; the Commitment (ACUPCC) and the Association for the Advancement of Sustainability in Higher Education ( AASHE; USGBC, 2014 ). The [ACUPCC] is a high visibility effort to address global climate disruption undertaken by a network of colleges and universities that have made institutional commitments to eliminate net greenhouse gas emissions from specific campus operations, and to promote the research and educational efforts of higher education to equip society to re Pres This initiative provides a framework for higher education institutions to implement comprehensive plans in reducing their climactic impacts. Additionally, the ACUPCC supports signatories in their efforts to educate students who will help in developing the social, economic, and technological solutions to reverse global warmin g. Committed institutions are obligated to initiate two of seven listed tangible actions to reduce

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47 greenhouse gases, such as setting a target date for achieving climate neutrality and establishing mechanisms for tracking progress on climate goals. One of t he available options to signatories is to establish a policy that all new campus construction will be built to meet a LEED Silver standard. To date, 655 colleges and universities have become signatories of this sustainable initiative, making the ACUPCC the largest U.S. sustainability initiative in the higher education community ( USGBC, 2014 ). Table 2 12 has been provided to help illustrate the tangible actions required by the ACUPCC. Finally i n January of 2010 AASHE, an entity that empowers institutions to sustainably transform their campuses by providing resources and a network of support, launched its first pilot STARS program . The STARS rating system was designed to facilitate information sharing about higher education sustainability practices and performance. Additionally, this program is intended to provide a framework for understanding sustainability in all sectors of higher education and building a stronger community of green campuses (AASHE, 2012). There are two methods for earning a STARS rati ng. Institutions that wish to participate anonymously may be rated as a STARS Reporter where as published institutions may earn points towards one of the four levels of STARS; Bronze, Silver, Gold and Platinum. Currently, this system awards points in two c redit areas for a having a building certified under the LEED for New Construction, LEED for Existing Buildings, or LEED for Commercial Interiors systems. To date, over 300 institu tions are participants in STARS, making it the second largest U.S. sustainabi lity initiative in the higher education community ( USGBC, 2014 ). Table 2 13 has been provided to highlight the STARS credits that LEED certified buildings can contribute to.

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48 Predicted vs. Actual Performance for Water and Energy in Higher Education Up until recently the integration of building controls and technological features has been viewed as the primary means for design teams to meet building efficiency goals (Arens, Federspiel, & Huizenga, 2005). Campus profiles across the country typically de scribe their conservation achievements by listing the sustainable systems even the best technological solutions alone cannot guarantee high performance. From the list of coll eges and universities that are signatories and participants in the ACUPCC, STARS, and LEED rating systems, the following cases have been selected to demonstrate how occupant behavior can supersede automated building controls and impact predicted water and energy consumption. Pacific Lutheran University (PLU) The Morken Center for Learning and Technology was the first building at Pacific to receive a LEED Gold certification . This new construction building was completed in January of 2006 and houses three departments: the School of Business, the Department of Computer Science & Computer Engineering, and the Department of Mathematics ( Peter Li Education Group, 2008 ). The three story uage of the PLU campus in form, material, and craft, while incorporating innovations in technology and flexibility. Morken Center totals approximately 57,000 sq. ft. and includes classrooms, laboratories, faculty offices, conference rooms, a two story atri um, and café (Zimmer Gunsul Frasca Architects, 2013). Building responsibly in an environmental context was a key concern for the departments housed in the Morken Center and thus, was a driving focus for the design team. Potable water consumption was predic ted to be reduced by 50% through

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49 the installation of low flow fixtures and waterless urinals. Additionally, this building is best known and published for the cutting edge technologies utilizes to reduce energy consumption by a predicted 49% (Bennett, 2008) . According to the architect of record, Zimmer Gunsul Frasca Architects, the following sustainable strategies were integrated into the design of the Morken Center: west elongation and slender form allow for significant use of on site resources of sun, wind and light. An optimized envelope design allows the designed building systems to achieve remarkable efficiency. A ground source heat pump system, which circulates water through pipe coiling 300 feet down into the site offsets the need for grid power to heat and cool the facility, and provides occupants with individual lights and shut them off when rooms are unoccupied [and] the light fixtures used emit 25% more lig ht and are 33% more efficient than standard fixtures . ( 2013) While this building has been successful in conserving resources in relation to a baseline case, the latest STARS report reveals that the predicted level of water and energy savings has yet to be reached. Despite the use of water conserving fixtures current consumption in this building is 31% below a baseline case; 19% less than the original estimate (AASHE, 2012). Similarly, a review of the energy consumption during a 2009 post occupancy evaluati on indicated that the building had been experiencing an upward energy path since its opening. As a result, the latest STARS rating indicates that the energy consumption of this building is 23% below a baseline case; 26% less than anticipated. R esearchers f ound that users consumed more than fou r times the energy from plugged in electronics than what was forecasted by engineers (Reed, 2009) . It was also suspected that this increase could be attributed to an underestimation in total building occupancy ( Krzmarz ick, 2009 ).

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50 Oregon Health & Science University (OHSU) T he highly acclaimed Oregon Health & Science Univers ity's (OHSU) Center for Health & Healing was the first medical r esearch institution in the world to achieve a LEED Platinum . This building was completed in October of 2006 and is home to center was designed to support educational, research, and personal wellness activities. As the only research facility of its kind in Oregon and the first building on the universities new 10 acre satellite campus, the design team endeavored to establish precedence for further site development. All of the mechanical and plumbing systems in the building were selecte d with the intent of conserving resources. For example, green roofs and an on site bioreactor were designed to process rainwater, wastewater , and groundwater , to then be reused for landscaping irrigation, radiant cooling, and non potable plumbing needs ( Ge rding Edlen Development, 2010). As a result of these implemented strategies, the water conservation was anticipated to be 56% less then a baseline case. Additionally, a variety of sustainable solutions were applied to reduce total energy consumption. S olar power generators were designed to double as sunshades , efficient chilling beams were utilized in lieu of central air conditioning, and the first micro turbine plant in the state of Oregon was installed on site to contribute to this buildings 49% predictio n in savings (Gerding Edlen Development, 2010). However, despite the accolades OHSU has earned for its revolutionary design, a n internal post occupancy evaluation ( POE ) indicated that electrical and plumbing systems have not performed as anticipated. M eter ed data for water indicated that consumption volume s experienced a 61% increase from the design case. Researchers attributed part of this increase to an underestimation of transient users and the fi xture use per building occupant.

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51 Additionally, the POE rev ealed that twice as much energy was consumed by users than what was anticipated during the design process of the building (Reed, 2009). accurate means to assess true energy nee ds and plug loads and possibly ways to control changes to plug loads. This could include a better understanding during the client engagement phase of how people use technology for work what kinds of equipment/technologies, when used, for how long, and fo al., 2009, p. 47 ). Unlike technological solutions occupant behaviors have only recently been considered to be more than a tangential element in building performance (Lutzenhiser et al., 2012). As the list of cases similar to P LU and OHSU continues to grow it has become clear that the components traditionally specified in LEED certified buildings, such as lighting sensors, low flow fixtures, and automated systems, are insufficient as the sole solution for enhancing building perf ormance ( Fowler & Rauch, 2008 ; Torcellini et al., 2006) . For this reason a shift in the traditional green building paradigm is arguably required to better balance actual occupant behaviors with desired building performance levels. Environmentally Significa nt B ehavior in Residence H alls Environmentally significant behavior (ESB) is defined as the extent to which a behavior changes the availability of materials and resources in the environment (Stern, 2009). The relationship between ESB s and the efficiency of building features, such as HVAC, electrical, and potable water systems, has yet to be understood in much depth in campus residential settings (Bekker et al., 2010). Thus far, studies have confirmed that campus residents are generally, if not entirely unaw are of their ESB s and consumption

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52 of resources. It is purported that dormitory residents frequently have little incentive to moderate behaviors because their rental fees are not directly related to the amount that they consume. As a result, studies have sh own a higher consumption rate in these building settings as compared to individually billed apartments or educational buildings. For example, one recent case study investigated the resource consumption of campus almond and Cumberland Halls. After tracking resource consumption throughout the winter and spring season it was determined that campus occupants consumed 35% more resources than the average private resident (Bekker et al., 2010, p . 327). Similarly, in 2009 New York University (NYU) initiated the NYUnplugged program, an energy conservation challenge, after realizing that its residence halls consumed a quarter of the campuses total electrical use. It was estimated that dormitory occupants were each consuming up to 500 kilowatt hours household. Additionally, the carbon emission associated with the electricity used by s of coal, one million gallons of gasoline and twenty thousand barrels of oil (New York University, 2013). A s a result of personal choices, such as long showers, leaving lights on , and unused electronic plugged in , previous studies have estimated that occupant behavior account for up to 50% of residential consumption, while the remaining balance depends on the building characteristics and installed equipment ( Building Research Establishment, 2012 ; Driza & Park, 2013; Petersen, Shunturov, Janda, Platt, & Weinberger, 2007 ) . Such stud ies may suggest that residence halls are an ideal location for further

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53 investigating the relationship between occupant ESB s and their consumption of resources. Understanding Environmentally Significant Behavior As the impact of occupants is better understood in relation to building design, it has become more critical to view behavior as a dynamic factor within the LEED certification process. Since 2005 the National Research Council has aligned with this logic and has considere d ESB to be one of the top five priorities in ecological research. Currently, this entity founds its research on the belief that built environments can only be safe and effective if designed with human behavior in mind (The National Academies, 2013). Thus, studies in social psychology have strived to offer clues as to why people engage in unsustainable behaviors despite their contribution to broader consequences, such as air and water pollution, climate change, and resource depletion (Manning, 2009). Psych ological and neurological evidence suggests that human thinking is the product of two sepa rate systems of reasoning: a conscious, rule based system, which is rational and deliberate, and an unconscious, associative system, which is sensory driven, impulsiv e ) . The rule based system works slowly and makes decisions based on the careful consideration of acquired facts. By contrast, the associative system arrives at quick decisions based on subtle sensory cues such as familiarity, emotional reactions, and mental imagery. Although many individuals may perceive that their decisions have been made based on thoughtful deliberation, it is acknowledged that the associative system plays a powerful role in every action and can

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54 influence or even override the conclusions of the rule based system (Manning, 2009 ; Sloman, 2002 ). Since as early as 1970 , a number of variables that influence ESB s have been identified and organized in to four classifications: Contextual Factors, Personal Capabilities, Habit and Routine, and Attitudinal Factors. These four factors form the foundation for the theories that seek to explain the motives that underlie ESB. The Contextual Factors that influenc e ESB relate to variables of constrains or facilitations, such as the availability of technology, convenience to public transit, or legal and regulatory requirements. The Personal Capability category acknowledges the influence that financial resources, soc ial status, and literacy have Habit and Routines category recognizes subconscious, fixed ways of thinking or feeling based on the repetition of a behavior. Finally, Attitudinal Factors are those that are based on personal v alues, attitudes, and behavior specific norms and beliefs . Generally, the stronger the contextual influences are on an individual, the less personal factors contribute to E S B s . However, patterns of influences on behavior have shown that when contextual inf luenc es are weak or cannot be changed , personal factors are likely to be the strongest influence on behavior. Therefore, social psychologists have suggested that attention center on personal factor variables in order to better understand ESB s ( Stern, 2005) . Table 2 14 has been provided to illustrate the classifications of variables that guide behavior. The characteristic heterogeneity of ESB s has led to the development of several theoretical approaches to understanding these behavioral patterns. To this day, debates continue in the behavioral research field as to which theoretical model best represents

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55 sustainable behaviors. However, social en vironmental researchers frequently cite and utilize the Theory of Planned Behavior (TPB) and the Value Belief Norm Theory of Environmentalism (VBN; Ajzen, 1991; Stern, 2000). Often the preference for a theoretical framework is associated with the view that pro environmental behavior is guided either by self interest or pro social motives. Self interest motivation is demonstrated own health risks. By contrast, pro oncern for the next generation, other species, or whole eco systems ( Bamberg, Hunecke, & Blöbaum, 2007) . Theory of Planned Behavior Researchers who believe that ESB is guided by self interest tend to rely on rat ional choice models such as the Theory of Pl anned Behavior. TPB has evolved as an extension of Fishbe heory of Reasoned Action , which aimed to predict behavior based on individual attitudes and subjective norms (Oreg & Katz Gerro, 2006) . According to the constructs of this theory, att confidence in and attachment to a behavioral outcome. Together with the notion of what valued peers might think of the behavior, also referred to as subjective norms, these attitudes lead to an intention to act. Behav ioral intentions are assumed to capture the motivational factors that influence a behavior and are indications of the p erceived likelihood of one performing a behavior (Ajzen, 1991). Unique to the TPB model is its inclusion of perceived behavioral controls or the conviction that requisite resources and opportunities must be present in order to perform a behavior. Perceived behavioral controls, such as time, money, or skills, are included in the TPB model as an exogenous construct that has both a direct effe ct on behavior and an indirect effect on behavioral

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56 by their perceived ability to perform the behavior (Bandura, Adams, Hardy, & Howell, 1980). Therefore, TPB postulates that when people perceive that they have little control over performing a behavior because of a lack of requites resources, then their intentions to perform the behavior may be low even if they have favorable attitudes and/or subjective norms concerning t he behavior (Ajzen, 1991). Figure 2 1 has been provided to schematically represent the constructs associated with the TPB model. The use of the TPB model has helped to explain the variance in behavioral intention and has been applied to a wide variety of behavioral contexts, including those related to transportation choices, recycling, and green consumerism ( Wilson & Dowlatabadi, 2007) . Hundreds of studies that have been summarized in meta analyses and reviews and have found that TPB explained an average 25% and 39% of the variance in behavior and intention, respectively, with perceived behavioral controls the most significant antecedent (Montaño & Kasprezyk, 2008; Wilson & Dowlatabadi, 2007 ). As a result, it is believed that the TPB framework is an effect ive tool for studying present environmental behavior as well as explaining future behaviors. For example, in several research studies that examined the propensity for individuals to recycle utilizing the TPB model , it was found that attitudes towards recyc ling helped to predict behavioral intention s , which in turn represented the actual recycling of materials by participants (Boldero, 1995 ; Cheung et al., 1999 ; Taylor & Todd, 1995). Additionally, in e organic vegetables, it was determined that attitudes toward green consumerism, subjective norms, and

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57 grown food (Sparks & Shepherd, 1992). Finally, a study was co nducted to examine California Nevada Truckee River Watershed of California Nevada. The analysis was based on 733 telephone interviews, where participants were asked to a nswer a series of water conservation questions using a 7 point disagree agree response. The results indicated that the TPB framework collectively accounted for two thirds of the water conserving behaviors (Trumbo & O'Keefe , 2001). Value Belief Norm Theory Researchers who believe that environmental behavior is guided by pro social motives tend to prefer the VBN frameworks. The VBN theory is an adaptation of Activation model (NAM) and proposes a framework to examine the relationship between values and environmental behavior (1977; Bamberg, Hunecke, & Blöbaum, 2007). Both models focus on the role individual choices play on personal norms; however, the VBN model expands upon the NAM in several significant ways (Stern, 2005). Unlike the NAM, thi s theory aimed to incorporate the New Environmental Paradigm Scale (NEP) or the worldview on the vulnerability of the environment to human interference. Additionally, the VBN model has a hierarchical character that views values as causal antecedents to wor act as filters for new information so that congruent attitudes and beliefs (i.e., concerns about specific environmental problems or attitudes toward certain behaviors) are more Steg, & Vlek, 2004, p. 72). The VBN theory assumes that personal norms for pro environmentalism, such as reducing the consumption of water and energy, are activated when a) an individual believes that violating these norms would adversely effect the thing s that they value, and b) individuals bear significant

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58 responsibility for the resulting consequences of unsustainable behavior. In research literature these notions are respectively referred to as the awareness of consequences (AC) and the ascription of re sponsibility (AR; Hansla, Gamble, Juliusson, & Garling, 2008). It should be noted that AC is closely related to the attitude toward frugality concept. Frugality of behavior is not directly concerned with the consequences of a behavior, such as CO2 emission s, but with the resources required to perform a environmental behavior, since it leads to a reduction in electrical use, and therefore, CO 2 263). Thus, frugal behavior may be thought of as an extension of AC. Figure 2 2 has been provided to schematically represent the constructs associated with the VBN Theory and the attitude toward frugality concept. Several stu dies have used the VBN framework to help explain the environmental attitudes and behaviors exhibited by the general public. Evidence has shown that depending on the type of behavior being studied, such as private sphere behaviors, policy support actions, o r environmental citizenship, the VBN model can explain 19% to 35% of its variance (Kaiser, Hübner, & Bogner, 2005). For example, studies have successfully explained the connection between values and general environmental concerns (Schultz & Zelezny, 1999), as well as more specific environmental beliefs (Stern & Dietz, 1994; Stern, Dietz & Guagnano, 1995). Other studies have also shown Grieneeks, & Rokeach, 1983), as well as the willingness of individuals to take action to protect the environment from human impacts (Stern & Dietz, 1994). Additionally, the VBN theory has been applied to studies that investigate occupant consumption of

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59 energy (Ibtissem, 2010; Poortinga, Steg, & Vle k, 2004). For example, a study was conducted in the Netherlands to examine the association between environmental impact values and the household consumption of energy. A total of 455 residents throughout the Netherlands responded to a survey, which used a Likert type scale to measure their environmental values, worldviews, environmental beliefs, and energy consumption behaviors. Consistent with earlier research, study results indicated that environmental concerns as well as different types of environmental behavior were clearly related to participant values. The review of all four of the survey sections indicated that the VBN model accounted for as much as 60.4% of the variance in behavior. Researchers concluded that the VBN framework was a useful tool for e xamining the motivational determinants of environmental behavior and that the study results show that values were especially able to explain the variance in intent oriented measures of environmental behavior (Poortinga, Steg, & Vlek, 2004). Limitations of Theoretical Behavioral M odels While these studies provide optimistic findings for the use of the TPB and VBN models, it should be noted that both models have their limitations ( Wilson & Dowlatabadi, 2007) . It has become clear that despite the importance of values and attitudes, they often do not translate directly into actual behavior. Many research studies have identified critical gaps and barriers between these constructs and actual behaviors (Blake 1999; Kollmuss & Agyeman 2002; Stern 2000). For example, individual are likely to prioritize personal factors differently . While study participants may agree that values , such as respect for nature and environmental protection , are important the critical question is whe ther individuals are willing to make tr ade offs, implicit or explicit, for one value versus another . Additionally, ext ernal contextual obstacles such as the lack of

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60 practical choices, rewards, advertising , and social expectations ability to exhibit pro environmental behav iors (Leiserowitz, Kates, & Parris, 2004) . Thus, predicting volitional behaviors remains a complex process even with the h elp of the TPB and VBN models and work remains to be done to fully identify and understand the key relationships between attitudes, su bjective norms, perceived behavioral controls, behavioral intentions, values, beliefs, personal norms, and ESB . Application of Theoretical Models to Consumption in Residence Halls There are economic and marketing studies concerned with resource consumptio n that have found that the predictive power of the TPB and VBN theories increases when constructs are included from both models. For example, in Clark, Kotchen and Moore involvement in green electricity programs, it was found that altruistic values (VBN value construct), environmental attitudes (TPB attitude construct), household income (TPB perceived behavioral control construct), and sociodemographic characteristics (TP B subjective and VBN personal norm construct) were all significant factors for explaining program participation (as cited in Kallbekken, Rise, & Westskog, 2008). Similarly, studies that utilize community based social marketing or a systematic application of marketing concepts and techniques used to achieve specific behavioral goals for a social good, have also been successful in combining constructs from both theor etical models ( McK enzie Mohr , 2013 ) . For example, in Goldstein, Griskevicius, and was discovered that messages that referenced constructs from both theories, such as env ironmental values (VBN value construct), the ability to reduce an environmental threat (TPB perceived behavioral control construct), and sustainable community

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61 practices (TPB subjective norm construct), were 12% more successful than messages that did not (a s cited in McK enzie Mohr , 2013 ). Thus, based on the context of this study and the review of literature on the TPB and VBN theories this study will investigate and VBN t heories. Figure 2 3 has been provided to schematically represent the theoretical constructs and framework utilized within this study.

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62 Table 2 1. LEED v4 for New Construction (NC) point m at rix ( USGBC, 2013b ) Certification Level Number of Points Required Certified 40 49 points Silver 50 59 points Gold 60 79 points Platinum 80 points or more 110 possible points: 100 base points, 6 points for ID, 4 bonus points for RP Table 2 2. LEED v4 Water Efficiency (WE) category ( USGBC, 2013b ) Credit Title Points WE Prerequisite 1 Water Use Reduction, 20% Required WE Credit 1 Water Efficient Landscaping, 50%, 100% 2 4 points WE Credit 2 Innovative Wastewater Technologies, 50% 2 points WE Credit 3 Water Use Reduction, 30%, 35%, 40% 2 4 points 10 possible points Table 2 3. LEED v4 Energy & Atmosphere (EA) category ( USGBC, 2013b ) Credit Title Points EA Prerequisite 1 Fundamental Commissioning Required EA Prerequisite 2 Minimum Energy Performance Required EA Prerequisite 3 Fundamental Refrigerant Management Required EA Credit 1 Optimized Energy Performance 1 19 points EA Credit 2 On site Renewable Energy 1 7 points EA Credit 3 Enhanced Commissioning 2 points EA Credit 4 Enhanced Refrigerant Management 2 points EA Credit 5 Measurement and Verification 3 points EA Credit 6 Green Power 2 points 35 possible points Table 2 4. Federal water standards for plumbing fixtures and fittings required by Energy Policy Act of 1992 and 2005 (Vickers, 1993 ) Product Maximum Water Use Gravity tank type toilet 1.6 gal/flush Flushometer tank toilet 1.6 gal/flush Electromechanical hydraulic toilet 1.6 gal/flush Blowout toilet 3.5 gal/flush Commercial gravity tank type, white two piece toilet 1.6 gal/flush Flushometer valve 1.6 gal/flush Urinals 1.0 gal/flush Showerheads 2.5 gpm Lavatory faucet 2.5 gpm Lavatory faucet replacement aerator 2.5 gpm Kitchen faucet 2.5 gpm Kitchen faucet replacement aerator 2.5 gpm Gallons per flush (gal/flush), Gallons per minute (gpm)

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63 Table 2 5. Water conserving fixtures and fittings required by Uniformed Plumbing Code of 2006 (IAMPO, 2006 ) Product Maximum Water Use Flush tank water closet 1.6 gal/flush Flushometer water closet 1.6 gal/flush Flushometer valve 1.6 gal/flush Urinals 1.0 gal/flush Self closing faucet 0.25 gpm Self closing metering facuet 0.25 gpm Gallons per flush (gal/flush), Gallons per minute (gpm) Table 2 6. Required capacity at fixture supply pipe outlet required by International Plumbing Code of 2006 (I nternational Code Council, 2006 ) Product Maximum Water Use Bathtub 8 psi Bidet 4 psi Combination fixture 8 psi Dishwasher, residential 8 psi Drinking fountain 8 psi Laundry tray 8 psi Lavatory 8 psi Shower 8 psi Shower, temperature controlled 20 psi Sillcock, hose bibb 8 psi Sink, residential 8 psi Sink, service 8 psi Urinal, valve 15 psi Water closet, blow out, flushometer valve 25 psi Water closet, siphonic, flushometer valve 15 psi Water closet, tank, close coupled 8 psi Water closet, tank, one piece 20 psi Pound per square inch (psi)

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64 Table 2 7. Default occupancy n umbers ( USGBC, 2013b ) Construction Type Gross Sq. Ft. Per Employee Gross Sq. Ft. Per Transients General office 250 0 Retail, general 550 130 Retail or service (e.g., financial, auto) 600 130 Restaurant 435 95 Grocery store 550 115 Medical office 225 330 R and D or laboratory 400 0 Warehouse, distribution 2,500 0 Warehouse, storage 20,000 0 Hotel 1,500 700 Educational, daycare 630 105 Educational, K 12 1,300 140 Educational, postsecondary 2,1000 150 Square footage (Sq. Ft.) Table 2 8. USGBC default fixture uses, by occupancy type ( USGBC, 2013b ) Fixture Type FTE ( Use/Day) Transient ( Use/Day) Retail Customer ( Use/Day) Resident ( Use/Day) Water closet, female 3 0.5 0.2 5 Water closet, male 1 0.1 0.1 5 Urinal, female 0 0 0 n/a Urinal, male 2 0.4 0.1 n/a Lavatory faucet (Duration 15 sec; 12 sec. autocontrol; 60 sec. residential) 3 0.5 0.2 5 Showerhead (Duration 300 sec.; 480 sec. residential) 0.1 0 0 1 Kitchen Sink (Duration 15 sec.; 60 sec. residential) 1 0 0 4 Seconds (sec)

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65 Table 2 9. Default fan schedule originally based on office building settings (Mukhopadyay, Baltazar, Kim, & Haberl, 2011 ) Hour/ Wk/ Wkd Fan use in a 24 hour period Hour 1 2 3 4 5 6 7 8 9 10 11 12 Week 0 0 0 0 0 0 1 1 1 1 1 1 Sat. 0 0 0 0 0 0 1 1 1 1 1 1 Sun. 0 0 0 0 0 0 0 0 0 0 0 0 Fraction of power used in a 24 hour period cont. Hour 13 14 15 16 17 18 19 20 21 22 23 24 Week 1 1 1 1 1 1 1 1 1 1 0 0 Sat. 1 1 1 1 1 1 0 0 0 0 0 0 Sun. 0 0 0 0 0 0 0 0 0 0 0 0 Week (Wk), Weekend (Wkd) Table 2 10. Default service hot water schedule originally based on office building settings (Mukhopadyay, Baltazar, Kim, & Haberl, 2011 ) Hour/ Wk/ Wkd Fan use in a 24 hour period Hour 1 2 3 4 5 6 7 8 9 10 11 12 Week 0.05 0.05 0.05 0.05 0.05 0 .07 0.07 0.19 0.35 0.38 0.39 0.47 Sat. 0.05 0.05 0.05 0.05 0.05 0.08 0.07 0.11 0.15 0.21 0.19 0.23 Sun. 0 .04 0.04 0.04 0.04 0.04 0.07 0.04 0.04 0.04 0.04 0.04 0.06 Fraction of power used in a 24 hour period cont. Hour 13 14 15 16 17 18 19 20 21 22 23 24 Week 0.57 0.54 0.34 0.33 0.44 0.26 0.21 0.15 0.17 0.08 0.05 0.05 Sat. 0.2 0 0.19 0.15 0.12 0.14 0.07 0.07 0.07 0.07 0.09 0.05 0.05 Sun. 0.06 0.09 0.06 0.04 0.04 0.04 0.04 0.04 0.04 0.07 0.04 0.04 Week (Wk), Weekend (Wkd)

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66 Table 2 11. Default lighting schedule originally based on office building settings (Mukhopadyay, Baltazar, Kim, & Haberl, 2011 ) Hour/ Wk/ Wkd Fraction of power used in a 24 hour period Hour 1 2 3 4 5 6 7 8 9 10 11 12 Week 0.05 0.05 0.05 0.05 0.05 0.1 0.1 0.3 0.9 0.9 0.9 0.9 Sat. 0.05 0.05 0.05 0.05 0.05 0.05 0.1 0.1 0.3 0.3 0.3 0.3 Sun. 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 Fraction of power used in a 24 hour period cont. Hour 13 14 15 16 17 18 19 20 21 22 23 24 Week 0.8 0.9 0.9 0.9 0.9 0.5 0.3 0.3 0.2 0.2 0.1 0.05 Sat. 0.15 0.15 0.15 0.15 0.15 0.05 0.05 0.05 0.05 0.05 0.05 0.05 Sun. 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 Week (Wk), Weekend (Wkd) Table 2 1 2 . Tangible actions r equired by the ACUPCC ( Pres Commitment, 2013 ) ACUPCC signatories commit to initiating two or more of the following seven specified tangible action options to reduce greenhouse gases within the two years after their implementation st art date. 1. Establish a policy that all new campus construction will be built to at least the U.S. Green Building Council's LEED Silver standard or equivalent. 2. Adopt an energy efficient appliance purchasing policy, requiring purchase of ENERGY STAR certified products in all areas for which such ratings exist. 3. Establish a policy of offsetting all greenhouse gas emissions generated by air travel paid for by our institution. 4. Encourage use of and provide access to public transportation for all fa culty, staff, students and visitors at our institution. 5. Within one year of signing this document, begin purchasing or producing at least 15% of our institution's electricity consumption from renewable sources. 6. Establish a policy or a committee that supports climate and sustainability shareholder proposals at companies where our institution's endowment is invested. 7. Participate in the Waste Minimization component of the national RecycleMania competition, and adopt 3 or more associated measures to reduce waste. Number of Signatories to Date: 665

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67 Table 2 13. STARS credits that LEED certified buildings can c ontribute to (AASHE, 2012). Credit Number Credit Criteria OP Credit 1 Building Operations and Maintenance (7 points) Institution owns and operates buildings that are: 1) Certified under the LEED® for Existing Buildings: Operations & Maintenance (O&M) Green Building Rating System, and/or 2) Operated and maintained in accordance with sustainable operations and maintenance guidelines and polic ies that cover the following: Impacts on the surrounding site Energy consumption Usage of environmentally preferable materials Indoor environmental OP Credit 2 Building Design and Construction (4 points) Institution owned buildings that were constructed or underwent major renovations in the past three years are: 1) Certified under the LEED® for New Construction and Major Renovations, LEED for Commercial Interiors, and/or LEED for Core and Shell Green Building Rating Systems, and/or 2) Designed and built in accordance with green building guidelines and policies that cover the following topics: Impacts on the surrounding site Energy consumption Usage of environmentally preferable materials Indoor environmental quality Water consumption Reporter: Anonymous, Bronze: 25 pts, Silver: 45 pts, Gold: 65 pts, Platinum: 85 pts

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68 Table 2 14. Variables influencing environmentally significant behavior (Stern, 2005 ) Classification Variable Contextual Factors Available technology; Embodies environmental impact, e.g. energy efficiency of buildings, vehicles; materials in consumer products; Legal and regulatory requirements; Material costs and rewards (payoffs)l Convenience, e.g., of public transit, recycling; Social norms and expectations Personal Capabilities Financial resources; Literacy; Social status; Behavior specific knowledge and skills Habit and Routine T hinking or feeling based on the previous r epetition Attitudinal Factors Personal values; General environmentalist disposition (abstract norm); Behavior specific (concrete) norms and beliefs; Nonenvironmental attitudes, e.g., about product attributes; Perceived costs and benefits of action

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69 Figure 2 1 . Schematic r epresentation of c onstructs in the Theory of Planned Behavior ( Ajzen , 1991 ) Figure 2 2 . Schematic r epresentation of c onstructs i n the Value Belief Norm Theory (Stern, 2005) Behaviors Behavioral Intentions Perceived likelihood of performing the behavior Attitudes Overall evaluation of a behavior Subjective Norms Percieved social pressure Perceived Behavioral Controls P erceived barriers to completing a behavior Values Biospheric Altruistic Egoistic Beliefs Ecological worldview (NEP) Adverse consequences for valued objects (AC) Feeling of responsibility for resulting consequences (AR) Personal Norms Ones sense of obligation to behave in a certain way Behaviors

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70 Figure 2 3 . Theoretical framework of study based on c onstructs from the Theory of Planned Behavior and the Value Belief Norm Theory (Ajzen, 1991; Fujii, 2006; Stern, 2005) Behaviors As they relate to water and energy consumption Behavioral Intentions Perceived likelihood of one conserving resrources Attitudes Overall evaluation of water and energy saving behaviors Subjective Norms Percieved social pressure to conserve resources Personal Norms Sense of obligation to take pro environmental action to conserve water and energy Beliefs Ecological worldview (NEP) Adverse consequences for valued objects (AC) Percieved ability to reduce threat (AR) Values Biospheric Altruistic Egoistic Perceived Behavioral Controls P erceived barriers such as lack of incentive, knowledge, habits, cooperation of others, etc.

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71 CHAPTER 3 RESEARCH METHODOLOGY This chapter presents the research methods for this study. A n over view of the research design is first described. Detailed descriptions are then provided for each case and the utilized research instruments . These descriptions help to explain how LEED prediction tools and occupant ESBs will be examined in residence hall s . Finally the data analyses used in this study are explain ed. Research Design A comparative case study approach was utilized i n order to investigate the following research questions and sub questions: 1. How accurately are occupant behaviors accounted for by the current LEED rating icting water and energy consumption? 1.1 How accurate are the LEED referenced standards for water usage and flow durations in residence halls? 1.2 How accurate are the LEED referenced standards for fan, water heater, and lighting schedules in residence halls? 2. consumption of water and ener gy in LEED certified residence halls? Th e case study approach is a qualitative research method and empirical inquiry about a contemporary phenomenon ( et within its real world contex t. C ase studies emphasize detailed contextual analysis of a limited number of events or conditions and their relationships (Soy, 2006). The approach is optimally suited for developing an understanding of complex issues especially when the boundaries between phenomenon and context are not and can add strength to previously conducted research. This approach has been used in various fields and profession s as an established me thod of education and research.

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72 Social scientists, in particular, have made wide use of this method to examine contemporary real life situations related to ESB ; thus being the rational e for the application of this method in this study . For example, researchers have used the case study approach to successfully evaluate the pro environmental behaviors of 7 th and 8 th grade students in Illinois and Missouri ( Culen & Volk, 2000); environmental attitudes, motivations, and values in Maine (Ko tchen & Reiling, 2000); and household waste management in the United Kingdom (Barr, 2007) . In each of these studies, the case study approach provided a method to describe, evaluate, and explain the relevant environmentally significant behaviors of their st udy participants. For the purpose of th is research , t hree cases used to systematically assess behaviors related t o energy and water consumption within residence halls . These cases , considered typical, were selected based upon their similar geographical location and level of achievement within the LEED rating system. For example, e ach residence hall was located in the southeast region of the United States, had achieved a LEED Gold certification, and provided evidence of its application for WE, Credit 3 Water Use Reduction and EA, Credit 1 Optimized Energy Performance . Results from the three cases, were examine and comp ared to obtain findings, draw conclusions, and issue recommendations. Mixed Methodology Additionally, a mix ed method s approach was utilized in order to better understand research outcomes . One of the strengths of a mix ed method s approach is that it brings together the benefits of both th e quantitative and qualitative paradigms and often claims greater validity and reliability of results ( Schram, 2014 ). According to Greene and

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73 Carac illi (2003), the complexity of a research problem justifies the use of multip le rese arch approaches. Triangulation is among the foundational strategies of m ixed methods research, which refers to cross corroborating the findings derived from diverse research methods . The t riangulation of study findings elaborates upon and explains the result from one method with the result of other to increase validity and understanding . A s described by Greene and his colleagues, one of the limitations is it that the purpose for choosing a mixed methods design is at times not made clear, which can l ead to confusion in the design phase of a study (as cited in Bazeley, 2002, p. 3). Thus, in this research, careful consideration was given to three phases in which data was collec ted and analyzed using five different instruments . First Stage During t he fi rst stage of research d emographic profiles were established for each campus and survey participants from each residence hall. Profiles helped to illustrate the types of occupants at each location and provide details regarding gender , grade point average, s tandardized test scores, ethnicity, and length of time within each residence hall. B uilding consumption records were also used to illustrate current water and energy consumption rates. Meter readings for these resources provide d a basis of comparison between current consumption and the predicted performance of each residence hall. In this stage , a survey instrument was also used to assess the environmentally significant behaviors of residents in each hall. In an era in which a wealt h of information is highly accessible and rapidly changing, many researchers use surveys to knowledgably inform and challenge existing assumptions (Gideon, 2012). A researcher may choose to utilize a survey when it is necessary to make statistical inferenc es about a population being studied. A survey generally consists of a target

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74 population, a method of collecting data , and individual questions or items that can be statistically analyzed as data . Since survey research is almost always based on a sample of a population, the success of the research is dependent on the r epresentativeness of the sample. The target population can range from the general population of a given country , to specific groups of people within a country, to members within a professional organization, or as in the case of this study, a list of students enrolled in a school system ( Groves et al., 2009). These flexible and utilitarian characteristics of surveys have previously helped to make them an ideal tool for assessing user attitudes to wards sustainable practices, values assigned to environmentalism , and other behaviors that impact energy and water consumption ( Boldero, 1995 ; Fujji, 2006 ; Ibtissem, 2010 ; Kaiser, Hübner , & Bogner, 2005 ; Taylor & Todd, 1 995 ) . ap proach for research conceptualization, measurement, and validation was utilized for constructing the survey instrument to ensure study validity. This approach allowed for the operationalization of the TPB and VBN theory constructs by identifying background concepts in literature, defining terms, and establishing indicators th at were relative to this study. The survey instrument was organized into nine sections: Section 1: Water Use, Section 2: Energy Use, Section 3: Environmental Values, Section 4: Environmental Beliefs, Section 5: Attitudes towards Conserving Water and Energy , Section 6: Subjective and Personal Norms, Section 7: Perceived Behavioral Controls, Section 8: Behavioral Intentions, and Section 9: Demographics. Survey sections 1 2 established predictions for water use, water flow, and energy schedules. Sections 3 8 i dentified the relevant behavioral constructs that

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75 impacted the consumption of water and energy in each residence hall. Section 9 provided demographic information for each survey participant. Second Stage In the second stage of this research s urvey section s 1 2 were further examined with volunteers who participated in a resource trackin g exercise. The self report method is a type of instrument that allows researchers to measure behaviors based on a study participants own reporting of their experience rather methods are used frequently in psychology to assess the frequency of baseline behaviors, causal triggers for certain behaviors, and to assess change in behavior over a self report method, a participant is typically asked to record the frequency and circumstances surrounding particular behaviors at set or random intervals, once to multiple times per day. This method is a common type of measure in the social sciences and is also referred to as ( Hektner, Schmidt & Csikszentmihalyi , (Shiffman, Stone & Hofford , 2008 Hemphill & Lehman , 1992). One of the key advantages to using self reporting is that research subjects are able to record data closer in time to when they occur, rath er than requiring them to depend on less reliable retrospection. The resource tracking exer cise helped to record consumption of resources over a three day period and allowed individuals to reflect on the amount of resources they consume. Third Stage Finally, survey sections 3 8 were furt her examined during interviews, which h elped to identify why certain TPB and VBN constructs were relevant to consumption in

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76 the context of LEED certified residence halls . At the most basic level, interviews are based on conversation, with the emphasis being on researchers asking questions and l istening, and participants providing a response (Rubin & Rubin, 1995; Warren, 2001). unfold the meanings of 1). Anthropologists, sociologists and psychologists have long used interviews to obtain necessary background knowledge for research. Interviews for research or evaluation purposes differ in some significant ways from other familiar kinds of interviews or conver sations. Unlike conversations , which are usually mutual exchanges, research interviews involve an interviewer who is in charge of structuring and directing the questi oning. Their purpose is to derive interpretations, not facts or laws, from responses, as g enerally such interviews emphasize promoting intellectual understanding rather than producing personal change (Kvale, 1996 ; Sewell, 2013 ). In practice, open ended, qualitative interview questions are often used as a framework for participants to respond in a way that accurately represents their point of view about a topic. Qualitative interviewing is most useful for researchers to evaluate pr ograms that are aimed at individualized outcomes, explore individual differences implementation at different sites, evaluate programs that are seen as dynamic or evolving, and t o understand the meaning of a program to its participants (Sewell, 2013). Additionally, social scientists have used interviews to give context to survey designs, provide an interpretation of survey results, and initiate a dialogue with research

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77 participant s that encourages feedback as well as new insights (Fern, 2001; Kitzinger, 1995). Thus in this study, interviews were selected as an instrument to contextualize survey results and obtain first hand feedback related to behavioral constructs from building oc cupants . Finally, p rior to the utilization of these five instruments in the study, each data collection tool was piloted and run through several rounds of cognitive testing. These s and appropriately measured the TPB and VBN constructs. Figure 3 1 has been provided to illustrate the research design utilized in this study. Case Selection In Case Studies in Planning: Comparative Advantages and the Problem of Generalization (2003), Sco tt Campbell examines the emphasis on the case study method in planning research. While the case study approach is praised for providing many advantages over other methodologies, Campbell argues for the strategic selection of study sites. The different type s of project locations can most simply be divided into two categories: typical cases and exceptional cases. The typical case can be thought of as a dissimilar case (Ca mpbell, 2003). The choice between the two relies heavily on the represent and replicate patterns of the larger population. Exceptional cases are more effective for challengi (Campbell, 2003, p. 9). For the purpose of this study, typical cases were selected so that generalizations and s uggestions of improvements would be relevant to the larger population of LEED cer tified buildings. The following descriptions of each case

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78 climate, level of achievement within the LEED rating system, and construction help to illustrate the similar characteristics shared by each residence hall. Case Settings R esearch has revealed that climate is an integral component of building performance ( Energy Information Administration, 2009) . It may then be assumed that residents in areas that experience extreme variations in climatic conditions will consume more resources in response to external conditions than residents in temperate locations. Thus, in order to zero in on behavior patterns that are a result of per sonal the sample residences for this study were all located within the s outheastern region of the United States, where climactic variances are expected to be moderate and comparable (National Climactic Data Center, 2012). For additional control, all of th e selected residence halls received their LEED certifications after January of 2009. This criterion helped to ensure that uniform industry standards were applied throughout the construction of each building and that installed systems were assessed and veri fied by a commissioning agent. It is well documented that the proper installation of buildin g features can impact overall resource consumption (Lutzenhiser, Hu, Moezzi, Levenda & Woods, 2012). For example, improperly sealing a building may lead to leaks, t he excessive use of the HVAC system, and ultimately contribute to unnecessary energy consumption . Similarly, the improper installation of plumbing fixtures may contribute to unwarranted potable water use . Therefore, by ensuring that a commissioning agent w as present during construction, the study controls for consumption impact s that are rela ted to faulty buildin g characteristics versus those directly related to occupant behaviors.

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79 Each building selected for this study m et a series of sustainability benchm arks. For example, documentation was requested to verify the achievement of LEED Gold certification renovations. In this manner this study controls any variation in resource consumption that wo uld be a result of differences between referenced standards and credit requirements. Additionally, documentation was provided for each sample residence hall to support their achievement of WE Credit 3 Water Use Reduction and EA Credit 1 Optimized Energy Pe rformance. Through this it was assured that all of the sample buildings were designed to save a minimum of 20% in water consumption and 10% in energy costs as compared to a baseline case of similar size and construction ( USGBC, 2013b ) . Ultimately, these cr iteria were intended to control the selection of study sites to ensure that each building was reasonably comparable. Case Profiles online resource that lists LEED certified projects by location, owner, project name, certification level, and construction type ( USGBC, 2013c ). Residence halls located in the southeastern region that met the required LEED criteria were short listed and their housing directors were c ontacted via email. Of the original list of 12 universities and colleges, Emory Oxford College, North Carolina Central University, and Appalachian State University met the required criteria and agreed to participate. The following profiles have been provid ed to describe the design features, LEED credit achievements, and the overall d esign intent of each residence hall. This information also helps to describe the types of users and occupant needs that each building was designed to meet.

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80 Case o ne Emory Located on the south side of the campus and bordered by the Haygood Avenue and W. Moore S treet thoroughfares , Elizer Hall and Murdy Hall make up what is known as the East Village. These two residence halls inclu de a number of student oriented amenities such as a demonstration kitchen large enough to host cooking classes, a fitness room, four terraces, and a number of community lounges and study rooms ( Emory Oxford College, 2013b) . This location also serves as the main departure point for the Oxford Emory Shuttle, which offers service to the downtown Atlanta three times a day . Elizer and Murdy Hall are three stories tall each and collectively house 350 freshman and sophomore students (Appendix A). Resident floors c ontain two large community restrooms and dormitory rooms have been equipped with a sink. Within the complex, 90 % of the accommodations are double occupancy rooms, 8 % are single occupancy rooms, and the remainder is triple occupancy rooms ( Emory Oxford Coll ege, 2013b) . East Village is a 112, 600 sq. ft. new construction project. It was awarded LEED Gold certification in April of 2009 and was the first building to receive USGBC Eaton Corporation, 2013) . The design of the complex focused on addressing resource consumption and user needs in a variety of ways. Low flow plumbing fixtures and dual flush toilets were utilized to reduce consumption of potable water. Additionally, energy recovery ventilation units and air side eco nomizers were installed in all of the public spaces to further enhance the performance of the HVAC system. A commissioning agent was hired during the planning phase of East Village to ensure that synergies were identified between energy consuming building features. Widespread individual lighting and thermal controls were

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81 introduced into the regularly occupied spaces in order to enhance user satisfaction. The building was also designed and oriented to optimize the filtration of natural daylight and provide o ccupants with ample views to the outdoors ( Eaton Corporation, 2013) . As a environmental cues were designed into the building to remind students to conserve resources. For example, the e xterior of the complex was artistically devised to highlight the collection and recycling of rainwater. Additionally, all of the public spaces were these strategies the d esign team for East Village predicted a 30% saving in water consumption and a 28% savings in energy costs ( Emory Oxford College, 2013b) . Table 3 1 summarizes the construction profile for E ast Village; Figure 3 2 shows interior and an exterior view of the complex. Case t wo Chidley North Residence Hall is l ocated on the southeast side of North Carolina campus . Bordered by the S. Alston Avenue and E . Lawson Street thoroughfares, this location serves as the departure point for three bus stops that connect to the surrounding city of Durham. This resid ence hall replaced the Chidley as forced to close its doors in 2006 due to severe mechanical equipment issues ( Allison, 2011) . Referencing this history, the design of Chidley North reflected the architectural character of the overall campus and the neighborhood block on which it is loca ted. Chidley North is four stories tall and houses up to 517 sophomore student s (Appendix B). Each residence floor contains a full kitchen, study lounge, laundry room, and recycling station. Within the apartment style student living spaces, 96 % of rooms ar e

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82 double occupancy (6 of these rooms are ADA accessible end suites) and 4% of rooms are single occupancy ( Lord Aeck Sargent, 2012) . This 134,000 sq. ft. building was completed in August of 2011 and is the first ified gold by the USGBC ( Lord Aeck Sargent, 2012) . The project team utilized a number of green features and strategies to reduce the consumption of water and energy. For example, water efficient plumbing fixtures were used throughout and a 28,000 gallon un derground cistern was installed to rainwater. The integrated design team used three strategies to address energy efficiency. First, the exterior of Chidley North features an insul ated concrete form (ICF) wall assembly, which provides almost double the thermal insulation of traditional concrete masonry. Second, the architects custom designed a shaded curtain wall of extruded aluminum shapes and high performance insulated glazing. Fi nally, an energy recycle the latent energy in exhaust fans, reduce humidity levels, and condition the building at lower costs. Since the completion of this residence h all, the university has used the building as a tool to educate students and community members about green building practices. This green education component was earned Chidley North one credit point under the LEED Innovation and Design category. As a resul t of the sustainable strategies applied in this residence hall the project team predicted a 30% saving in water consumption and a 28% savings in energy costs ( Lord Aeck Sargent, 2012) . Table 3 2 summarizes the construction profile for Chidley North and Fig ure 3 3 illustrates sample interior and exterior views of this residence hall.

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83 Case t hree Frank Res idence Hall is l ocated on the west side of Appalachian State campus and is bordered by the Stadium Drive and Rivers Street thoroughfares. This hall is situated on an AppalCart route, which provides public transportation throughout the city of Boone. This residence hall was originally built in the jor renovation in 2008 to better meet the needs of Appalachian State University, 2010) . As part of year housing plan, Frank Hall was the first of many new construction and renovation projects to r eceive a LEED gold certification from the USGBC. Frank Hall is six stories tall and houses up to 203 freshman, sophomore, junior, and senior students (Appendix C). Each resid ence floor contains a full kitchen, communal bathroom, study lounge, recycling sta tion, and laundry facility. All student living spaces are double occupancy and feature an energy efficient water source heat system for winter use ( Appalachian State University, 2010 ). This 40,900 sq. ft. building was completed in the fall of 2009 and was the first Fox, 2011; New Atlantic Contracting, 2007 ) . The original building was retrofitted to incorporate a number of sustainable features to address water and energy consumption. For example, low flow showerheads, faucets, and dual flush toilets were installed in all communal restrooms. Additionally, the project team sought to reduce energy consumption by placing cupant use. Interior spaces were also equipped with motion sensors and efficient T 5 /T 8 florescent bulbs ( Appalachian State University, 2010 ). Finally, Frank Hall is home to the environmen tal

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84 personal living, initiates sustainability focused activities on campus, and raises environmental awareness in the community. As a result of the sustainable strategies applied in this residence hall the project team predicted a 20% saving in water consu mption and a 35% savings in energy costs (Appalachian State University, 2010 ; Fox, 2011) . Table 3 3 summarizes the construction profile for Frank Hall and Figure 3 4 provides interior and exterior views of the residence. Utilizing Typical Case s It can be inferred from the provided descriptions that East Village, Chidley North, and Frank Hall represent appropriate platforms for advancing this research study as their shared traits allow for optimal comparisons . For example, e ach residence hall made similar , if not identical , predictions for its total water and energy consumption . T he building designs frequently utilized similar strategies to address the demand of potable water and energy. For instance , all three cases installed efficient plumbing fixtures, such as low flow showerheads, faucets, and dual flush toilets to reduce the indoor consumption of potable water. Also, each building utilized a similar strategy for reducing the energy demand of their HVAC syst e m. Finally, all of the buildings claimed to provide some form of education program, which promote d pro environmental living and environmental awareness. As Campbell (2003) suggests, s imilar starting conditions can lead to similar outcomes and thus, build a compelling basis for drawing conclusions. Additionally, each building share s similar characteristics with the larger population of sustainable higher education housing. For example, a ccording to the USGBC a sustainable higher e ducation building promote s occupant and environmental health by recognizing performance in six key areas: sustainable site development, water savings, energy efficiency, materials selection, indoor environmental quality , and

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85 innovation in design ( USGBC, 2013c ). By addressing each ke y area it is possible to needs within a community. In this study, selecting buildings that were certified under the LEED rating system helped to assure that residence halls building approach to sustain ability . The similarities betwee n the selected residence halls and the larger population of sustainab le higher education buildings suggest that each i s an example of a typical case . Thus, in the context of this research study, the similar conditions of each site provide a strong foundation for drawing conclusions about the larger population of sustainably built and LEED certified higher education buildings. Research Instruments Demographic profiles and buil ding consumption records were used to contextualize the collected data in this study . A s main data sets, a s urvey, resource tracking exercise , and interview s were also utilized to investigate the accuracy of prediction tools in the LEED rating system and examine the connections between occupant behavioral constructs and the consumption of resources in residence hall s. In order to reveal the accuracy of the tools used to predict water and energy consumption , t TAG members need to be evaluated . As previously described in the Foundations for Predicting Water Consumption and Foundations for Predicting Energy Consumption (pg. 31, pg. 37 ) sections of this study, the USGBC utilizes defaults and standards for water fixture usage, water fixture flow durations, fan schedules, service hot water schedules, and lighting schedules ( ASHRAE, 2009; USGBC, 2013b ) . While the LEED default settings ar e specific for residential settings, it is unclear if they are tailored to the behaviors within residence halls. Additionally, the energy standards for fans, hot water,

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86 and lighting are currently designed for commercial settings and may not be appropriate for residential settings. Thus, r esearch instruments were designed to quantify the accurac y of defaults referenced by the LEED rating system ( illustrated in Table 3 4) by comparing them to the ac tual water and energy consumption of residents in each hall. In order to determine if a relationship exists between behavioral constructs and environmentally significant attitudes, subjective norms, perceived behavioral contro ls, behavioral intentions, values, beliefs, and personal norms expressed by each resident. According to reviewed literature these constructs from the TPB and VBN theories will provide a foundation for understanding and explaining t he ESBs in each residence hall. Thus, research instruments were designed to establish how occupants appraise water and energy conserving behaviors (attitudes); if there are existing social pressures to conserve resources (subjective norms); if students perceive obstacles to saving water and energy within their residence hall (perceived behavioral controls); how hard residents are willing to work to conserve resources (behavioral intentions); if resident behaviors are focused on the welfare of the environment, other people, or thems elves (values); identify occupant beliefs with regards to sustainable practices (NEP, AC, AR); norm). Figure 3 5 has been provided to illustrate the data collecting i nstruments employed in this study. Demographic Profiles Demographi cs profiles provide quantifiable statistics about a given population at a specific point in time. This type of instrument is wi dely used in public opinion poll s, marketin g, and social scienc e research to examine characteristics about a population

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87 including their gender , age , ethnicity , knowledge of languages , disabil ities , mobility, home ownership, employ ment status, and even location (Klauke, 1989 ). In this study, d emographic profiles were established for each campus and survey participants from each residence hall . P rofiles for each campus provided quantifiable stat istics regarding the internationalism. Additionally, demographic profiles for survey participants provided quantifiable data regarding gender, age, ethnicity, internationalis m, and length of residency in each dormitory . Building Consumption Data Each case s water and energy consumption was examined utilizi ng three data sets: the baseline case, design case, and meter readings. As described in the Foundations for Predicting Wat er Consumption (pg. 31) and the Foundations for Predicting Energy Consumption (pg. 37) section s of this study, LEED applicants are required to document the baseline and predicted volume of resources that will be consumed from regulated water and energy fixt ures . The comparison of the baseline and design case is used to predict the minimum water savings in WE, Credit 3 Water Use Reduction and the minimum energy savings in EA, Credit 1 Optimized Energy Performance. Additionally, selected residence halls in this study sub metered their water and energy consumption and were able to provide a minimum of two years of consumption data . Similar to a water or electric bill, metered consumption informati on for each building itemized the mont h to month sewage convey ance, indoor water , steam, chilled water , and electrical use. The baseline, design case, and metered data helped to illustrate the water and energ y performance of each case by providing a basis of comparison betw een current consumption and predicted perfor mance rates .

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88 Survey The survey i nstrument consists of a series of multiple choice and 5 point bipolar scale questions . Sets of questions are organized into nine sections: Section 1: Water Use, Section 2: Energy Use, Section 3: Environmental Values, Section 4: Environmental Beliefs, Section 5: Attitudes t owards Conserving Water and Energy, Section 6: Subjective and Personal Norms, Section 7: Pe rceived Behavioral Controls, Section 8: Behavioral Intentions, and Section 9: Demographics. Sections 1 2 are designed to respond to research q uestion 1 and its sub questions by examining how accurately the LEED default settings and referenced standards for water and energy represented the actual consumption of students in residence halls As LEED default settings for fixture usage and flow durations are not available specifically for residence halls, the survey was developed using the LEED default settings f or residential settings. Similarly, the ANSI/ASHRAE/IESNA 90.1 schedules for fans, hot water, and lighting are currently designed for commercial settings only. Therefore, th e survey questions for actual energy consumption are developed based on the current ANSI/ASHRAE/IESNA 90.1 commercial settings. Sections 3 8 are guided by the background concepts, systematized concepts, and indicators relevant to the TPB and VBN theories and help to respond to research question 2. Therefore, these q uestions focus on assessing attitudes towards conserving water and energy and related indicators (behavioral and evaluation factors), subjective norms and related indicators (normative factors and motivations to comply), perceived behavioral controls and related indicators (control and perceived power beliefs), behavioral intentions and related indicator (intent), values and related indicators (biospheric, altruistic and egoistic values), beliefs and related indicators (awareness of

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89 consequences and ascription of responsibil ity), and personal norms and related indicator (obligation). Finally, Section 9 is designed to better understand the populations within each residence hall. Questions focus on resident demographics, the length of time students have lived in their residence dormi tory room is located. Appendix F provides an example of the survey instrument and Table 3 6 summarizes the guiding principles used to design each survey section. Resource Tracking Exercise Section 1 and 2 recall their use of water and energy resources. Therefore at the conclusion of the survey r esidents were asked if they would be willing to participate in an IRB approved, self reported, resource tracking exercise in order to better understand their daily use of water and energy. T he resource tracking exercise helped to enhance the reliability and validity of the research by verify ing that survey results were a true representation of actua l consumption . Additionally, this data collection method helped in creating a better understanding of the consumption of r esources within residence halls and allowed for conclusions to be draw with regards to research question 1 and its sub questions. Each resource tracking participant was asked to record their consumption of water and energy from the bathroom sinks, toilets, showerheads, kitchen sinks, lights and air conditioners in their residence hall . These locations coincided with those for which the USGBC offers design teams a default consumption setting. Utilization from each of these areas was then self reported on a formatted tracking form that required participants to indicate the date, time, du ration , and frequency of their use from each water fixture or energy feature . A ppendix G has been provided to illustrate an example of the resource tracking exercise instrument.

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90 Interview During scheduled interviews participants were asked to respond to th ree types of open ended questions : main questions that begin and guide the conversation, probes to clarify answers or request further examples, and follow up questions that pursue the implications of answers to main questions (Rubin & Rubin, 1995; Warren, 2001). Interview questions covered nine different topic areas: Topic 1: LEED Knowledge , Topic 2: Tracked Water Consumption, Topic 3: Tracked Energy Consumption, Topic 4: Environmental Values, Topic 5: Environment al Beliefs, Topic 6: Attitudes t owards Conse rving Water and Energy, Topic 7: Subjective and Personal Norms, Topic 8: Perceived Behavioral Controls, and Topic 9: Behavioral Intentions. Similar to the structure of the survey , Topic s 1 3 are designed to evaluate the accuracy of the USGBC utilized defau lt settings and help to respond to research question 1 and its sub questions. Topics 4 9 help to assess the relationship between behavioral constructs and the consumption of resources in res idence halls and help to respond to research question 2. A ppendix H has been provided to illustrate an example of the interview instrument. Survey and Interview Instrument Development Developing instruments that have firm foundations in theory can help to provide the most precise and efficient measurements ( Barry, Chaney, Stellefson, & Chaney, 2011). Behavioral theories not only provide a systematic framework for examining and understanding events but can also afford insight into why individuals chose to perform or not perform certain behaviors (Glanz, Rimer, Lewis, 2002). The TPB and VBN theories are among the most widely used explanatory theories with regards to ESB, and

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91 thus have been selected to guide the creation of the survey and interview instruments used in this study. Due to the co mplexities associa ted with mea suring and interpreting behaviors, it is recommended that investigators utilize a purposeful decision making process while developing instruments. In literature it is noted that too few researchers truly understand how to operationalize theorie s in their own investigations and as a result, jeopardize the reliability of their findings ( Barry, Chaney, Stellefson & Chaney, 2011 ; DeVellis, 2003 ; Thyer, 1992 ) . As described by Adcock and Collier (2001), high measurement validity is critical for genera ting reliable results in social research. Valid measurement is achieved when scores (including the results of qualitative classification) meaningfully capture the ideas contained in the corresponding concept. This definition parallels that of Bollen (1989 , p. give essentially the same definition. (p. 530) Therefore, in order to ensure the validity of survey and i nterview questions, and the reliability of findings , approach for research conceptualization, measurement, and validation was utilized while constructing data collecting instruments. Background Concepts At the first and bro adest level of approach , it is essential to select a theoretical framework for the study and identify the general social scientific meaning s of the constructs within selected theories . This first level, also known number of disciplines, fields, and theoretical perspectives ( Adcock & Collier, 2001) . Background concepts are frequently used differently between disciplines. Thus, to

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92 effectively utilize the TPB and VBN theories in this study it was necessary to establish how their constructs had been previously defined in relation to building performance, ficant behaviors. Attitude towards a behavior construct. The term attitude is characterized by a disconcerting degree of ambiguity and confusion. As a result of its use as an plicit Fishbein & Ajzen, 1975, p.1). For example, in literature attitudes have been considered to be a conceptual independent determinant of intention. In these e or unfavorable ). Attempts have also been made to explain social disorders like crime, gangs, or discriminatory behavior, such as stereotypes or prejudice by pointing to a particular attitude ( Ajzen & Fishbein, 1977 ; LaPiere, 1934; Ostrom, 1969) . Still others have related attitudes to performance, such as individual job satisfaction and morale ( Fishbein & Ajzen, 1975). Finally, a ttitudes towards products have been used in the past to explain various aspects of co nsumer behavior. In such studies attitudes are used to describe loyalty and image of a brand (Brehm and Cohen, 1959). In each of these studies the term attitude is inconsistently defined as either a predispos ition to an action, a learned behavior, or a favorable or unfavorable appraisal towards an object, person or institution (Jacobsen, 2011). Subjective norm c onstruct. Frequently, subjective norms are described as the perceived social pressure a person migh t feel to perform or not perform a specific behavior (Ajzen, 1991; Ajzen, & Fishbein, 1980; Harland, Staats, Wilke, 1999 ; Kaiser,

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93 Ranney, Hartig & Bowler, 1999 ) . For example, Kaiser, Hübner, and Bogner ( 2005 ) define subjective norms as the perceived expect ations of relevant others. Similarly, Trumbo and O'Keefe ( 2001 social norms involving an act. It is clear that across disciplines this construct relates to actions by promising to provide or withhold a Perceived behavioral control construct. The term perceived behavioral controls has been utilized differently (1991) TPB model, this construct refers to the extent to which a person has the required opportunities and resources to perform a behavior. By contrast, the concept of Perceived Locus of Control refers to a generalized expectancy that remains stable across situations and forms of action ( Rotter, 1966). Still others, such as the theory of to succeed at a given task. In such cases this theoretical construct is considered a (Atkinson, 1964, p. 242). Finally, in the concept of Perceived Self Efficacy, behavioral action required to deal with prospective situations illustrated by these examples, behavioral controls are inconsistently perceived as either exogenous or endogenous factors, depending on the context of a study.

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94 Behavior al intention c onstruct. I n the Theory of Reasoned Action ( Fishbein & Ajzen, 1975 perform a behavior . Similarly, in the TPB model b ehavioral i ntentions refer to d people are willing to try, or how much of an effort they are planning to exert, i n order to perform the behavior Finally, in a study that sought to predict pro environmental behaviors using both the TPB and VBN theories , this construct measured the how motivational factors influenced a behavior . Additionally, behavioral intentions were considered the most proximal predictor of behavior, which in turn was anteceded by attitudes, social norms, and perceived behavioral controls (Oreg & Katz Gerro, 2006) , which aligned with the traditional framework o f the TPB model . The similar application for this construct in the Theory of Reasoned Action, the TPB model and social science studies, such as that by Oreg & Katz Gerro (2006), suggest that behavioral intentions are universally believed to be central to i nfluencing behaviors and that the stronger the intention is to engage in a behavior, the more likely it will be performed . Value c onstruct. Among studies that centered on pro environmentalism there appears to be consensus on the term values. For example, according to Paul Stern As such, VBN utilizes three classifications of values including egoistic (motivated by self interest), altruistic (motivated to help others), a nd biospheric (motivated to help the environment). to provide a standard for motivating an behavior. Similarly, Mustapha Ibtissem (2010) describes values as one aspec

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95 Therefore, values may be thought of as the guiding principles in a life. Belief construct. The term belief has been utilized differently in a number of theories. For example, a an idea conceived in a certain manner, b) an idea that has a great in fluence on the mind, c) an act of mind rendering realities influential on the mind, d) something that makes ideas forceful and vivacious (Gorman, 1993). By contrast to this general definition Paul Stern (2005) specifically utilizes this construct to refer ecological worldview in the Value Belief Norm Theory . In it, beliefs refer to an environmental behaviors, such as reducing car use or producing less household waste, would have a negativ e effect on the things they value (awareness of consequences) and that they bear significant responsibility for the consequences of anti environmental behavior (ascription of responsibility). The difference that we find between the uses of this construct i n these theories is its focus on environmentally significant behaviors in the latter. Thus, when operationalizing this construct a researcher would want to consider the context of their study and determine if a general or environmentally specific definitio be more appropriate. Personal Norm Construct. In both the VBN theory and the model of Altruistic Behavior personal norms describe an internalized sense of obligation to act in a certain way ( Schwartz, 1968 ; Stern, 2005). This theore tical construct motivates behavior by providing an individual with clues of what is likely to be an effective and adaptive action

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96 in any given situation. In general , personal norms are believed to provide a decision making shortcut and information processing advantage when one is deciding on how to behave in a particular setting According to such literature it is believed that there is consensus on the term Based on the review of literature on the TPB and VBN constructs, it was clear that there is consensus on the definitions for subjective norms, behavioral intentions, values, and personal norms. Conversely, the attitude and perceived behavioral control cons truct from the TPB model and belief construct from the VBN model were accompanied by a broad range of background concepts acros s disciplines, which complicate their application in this study as there is not a shared understanding of these terms across the social science. For this reason they were further operationalized in the following step of to ensure their appropriate use while developing data collection instruments. Systematized Concepts The focus of each adopted construct is narrowed at the second level of Adcock approach for research conceptualization, measurement, and formulation of explicit construct defin itions that are applicable within a given context. As Adcock and Collier (2001) describe, can routinely include a variety of construct meanings depending upon the discipline, field, and theoretical perspective in which they a re utilized . Thus, the development of systematized concepts means knowledgably choosing among those that are the most suitable . In dealing with the choices that arise in establishing the systematized concept, lity inherent in these choices as

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97 & Collier, 2001 , p. 532). For this step, scholars will commonly associate a matrix of potential meanings with the background concepts. This matrix helps limit the range o f plausible definitions and environmentally significant behaviors in residence halls, definitions were selected from scholars who utilized similar theoretical frameworks to assess environmentally significant behaviors. Study topics ranged from pro environmental policy development, to ESB, water and energy consumption, recycling tendencies, and green consumerism. The list below cont ains the s ystematized construct definitions that were adopted for this research: A ttitudes toward a s pecific behavior are defined as evaluation of a behavior ( Ajzen, 1991 ) . Subjective norms are defined as the perceived expectations of relevant others ( Kaiser, Hübner, & Bogner, 2005). Perceived behavioral controls are overall measures of perceived control over the behavior ( Ajzen, 1991 ) . Behavioral Intentions are the perceived likelihood of performing a behavior ( Oreg & Katz Gerro, 2006 ) Values are the guiding principles in life (Stern, 2005) . Beliefs are the perspective from which an individual considers their ecological worldview (Stern, 2005) Personal norms are sense of obligation to behave in a certain way ( Schwartz, 1968 ) . Indicators Once systematized concepts were established, constructs were operationalized

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98 any systematic scoring procedures, ranging from simple measures to c omplex aggregated indices. For each systematized construct that is operationalized, the indicators or construct measures that others have used in comparable studies can be identified and listed. As Adcock and Collier (2001) describe, the availability of tw o or more alternative indicators can help to create a starting point for convergent or discriminant validation. To complete this step, the studies previously utilized during the rated high reliability. Attitude towards a behavior i ndicators . During a study by De Groot and Steg (2008) , a survey was conducted among students of th e University of Groningen to ass ess their attitudes towards recycling. The survey included two categories of indicators: behavioral factors and evaluative judgments. Behavioral factors refer to confidence that the performance of a behavior correlates with a specific outcome. ou tcome. Survey r espondents indicated whether they t hought recycling paper, chemical disposal, and glass was bad good (behavioral factor), unnecessary necessary (behavioral factor), negative positive (behavioral factor), not fun fun (behavioral factor), unimportant important (evaluative judgment), or useless useful (behavioral factor) on 7 point scales. Scores on each item were averaged and resulting scores on recycling attitude s ranged from 1 unfavorable to 7 favorable. To ensure that survey questions were statistically reliable, De Groot and Steg (2008) determined the Cronbach alpha, or coefficient of internal consistency, of each survey item. On a scale where 0.6

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99 or greater demonstrates internal consistency , the utilized indicators demonstr ated hi gh According to De Groot and Steg (2008) study, an association can be ehavioral factors , evaluative judgments, and resulting attitudes towards a behavior . Th erefore, these indicators were adopted for use in this study. Of particular interest in this investigation are the behavioral factors that align with those that the USGBC associates with reducing resource consumption. Thus, study instruments assess the per ceived level of confidence residents have in conservation behaviors by unplugging electronics, using efficient equipment, reporting leaks, and taking shorter showers ( USGBC, 2013b ) . Additionally, the e valuative judgments that are relevant in this study cor relate with how important residents believe it is to reduce their energy and water consumption in their residence hall. Subjective norm i ndicators. Research by Icek Ajzen (1991) suggests that two indicators characterize subjective norms: normative factors and motivations to comply. Normative factors are concerned with the likelihood that important referent individuals or groups approve or disapprove of performing a given behavior. Motivations to comply refer to the level of i nfluence referent groups have (1991) explains that a reliable global measure of subjective norms is obtained by asking of their performing a given behavior. Empirical i nvestigations have shown that the best correspondence between such global measures of subjective norms is usually obtained with bipolar scoring of normative factors and unipolar scoring of motivations to comply (Ajzen & Fishbein, 1980). Bipolar scorings me asure either positive or negative response

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100 to a statement whereas unipolar scales prompt a respondent to think of the presence or absence of a quality or attribute. It may be inferred by such studies that an association is distinguished between normative factors , motivations to comply , and resulting subjective norms. Therefore, these indicators were adopted for use in this study. investigation are the normative factors that also align with those the USGBC associates with reducin g resource consumption. Thus, study instruments assess the perceived performing conservation behaviors such as turning off lights, adjusting the thermostat, unplugging unused electronics, turning off faucets, taking shorter showers, and reporting leaks ( USGBC, 2013b ). Additionally , instruments assessed the level of i nfluence friends, family, faculty, housing staff, and neighbors had on the performance of sustainable behaviors. Perceiv ed behavioral control i ndicators. In a study where the TPB and the VBN models were empirically compared, perceived behavioral controls were measured using two indicators: control beliefs and perceptions of power. Control beliefs refer to the p erceived like lihood that a facilitating or constraining condition will occur. Perceptions of power refer to the effect these constraining or facilitating conditions have on making a behavior easy or difficult to perform (Kaiser, Hübner, & Bogner, 2005). In the reviewed study participants responded to 10 behavioral statements on a 5 point bipolar scale. A sample item from the survey stated, using a clothes dryer is . . . simple complicated . Analyzed data indicated that the applied

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101 indicators and subsequent scale demonstrated some measure of reliability with a a lpha of .58 (Kaiser, Hübner, & Bogner, 2005). As demonstrated by Kaiser, Hübner, and Bogner ( 2005 ), an empirical association exists between control beliefs , perceived power , and resulting perceived behavioral controls. Therefore, these indicators were adopted for use in this study. I n consideration certified residence halls instruments were developed to assess the frequency in which residents fa ce constraining or facilitating conditions to conserving resources (control belief) and the extent to which these conditions make conservation easy or difficult (perceived power). Based on literature, some of the constraining and facilitating conditions t hat were applicable to the case stud y population included a lack of incentives, time, money, skills, or cooperation of others ( Ajzen, 1985 ; Trumbo & O'Keefe , 2001). Behavioral intention i ndicator. In the previously mentioned study by Kaiser, Hübner, and Bogner ( 2005 ) behavioral intentions were measured using a single indicator: intent. Intent here refers to the p erceived likelihood of performing a behavior . For this research participants responded to 10 behavioral statements on a 5 point bipolar scale. A sample item from the survey stated, ain from using a clothes dryer . . . determined undetermined Analyzed data indicated that the applied indicator and subsequent scale demonstrated reasonable reliability with a a lpha of .6 8 (Kaiser, Hübner, & Bogner, 2005). Based on these research findings, it is believed that an empirical association Therefore, this indicator was adopted for use in thi s study. T he behavioral intentions

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102 relevant to this study would be those associated with minimizing water and energy consumption in the residence hall. Based on the literature, it is important to note that the in tention to perform a behavior diminish es whe n behaviors are costly, time consuming or difficult. For example, this happens when consumers pay more to buy sus tainable products or when people use public transport (Ibtissem, 2010). Steg, Dreijerink & Abrahamse (2005) attribute this to the fact that relatively costly behaviors are less connected to behavioral norms than less costly ones. Additionally, literature indicates that perceived behavioral controls are an exogenous variable that have both a direct effect on behaviors and an indirect effect on behavioral intentions. Thus, it is understood that if sample residents perceive that they have little control over performing a behavior or believe that a behavior is costly, time consuming or difficult, then their intentions to perf orm that behavior may be low even if they have favorable attitudes and/or subjective norms concerning the behavior (Ajzen, 1991). Value i ndicators. In 2008, researchers Judith De Groot and Linda Steg adapted asure value orientations in t he Netherlands. Confirmatory factor analysis (CFA) was used to draw solid conclusions about the distinction between three value indicators: egoistic, altruistic, and biospheric orientations. Associations were computed between value items and the three motivating factors. ranged from acceptable to good where egoistic orientations had a score of .65, altruistic orientations had a score .72 , and biospheric orientations had a score of .83. Furt hermore, explained variances for the egoistic, altruistic, and biospheric value orientation s were sufficient as well, with

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103 variances ranging from 49% for the egoistic, 55% for the altruistic, and 67% for the biospheric value orientatio n ( De Groot & Steg, 2 008). It is clear from this literature that an empirical association exists between egoistic tendencies , altruistic tendencies , biospheric tendencies, and an individual s resulting values ( De Groot & Steg, 2008) . Therefore, these indicators were adopted for use in this study. An adaptation of was utilized to determine the extent t motivated by self interest, interest in the wellbeing of others, or an interest in the wellbeing of the environmen t. Additionally, use of this scale will help to establish if a predominant value orientation exists amongst residents in LEED certified residence halls. Belief i ndicators. In 2003, a survey utilized the VBN theory , and the revised NEP scale , awareness of consequences and ascription of responsibility indicators to assess factors affecting the acceptability of energy policies ( Steg, Dreijerink & Abrahamse, 2005 ). The revised NEP scale measures perceptions such as limits to growth, balance of nature, steady s tate economy, and spaceship earth , to understand environmental concern ( Dunlap & Van Liere, 2010; Dunlap, Van Liere, Mertig, & Jones, 2000) . Additionally, the awareness of consequence and the ascription of responsibility indicators measure to not behaving sustainably consequences of unsustainable behaviors, respectively . In Steg, Dreijerink and Abrahamse utilize d a scale ranging from 1 totally disagree to 5 totally agree to indicate the extent to which they agreed with 15 NEP items that describe d a relationship betwe en humans and the environment . The internal

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104 consistency of this scale .73 . Respondents also rated the extent to which they agreed with 6 items reflecting an awareness of environmental problems related to energy use (awareness of consequence s ). Examples of such survey items stated with 6 it ems reflecting whether they felt r esponsible for these problems (a scription of responsibility ). Examples of such survey items stated l jointly responsible for the Analyzed data indicated that the applied indicator and subsequent scale demo nstrated high reliability with a a lpha of .75 and .80, respectively. As seen in the study by Steg, Dreijerink and Abrahamse (2005 ) , an empirical association can be draw n consequences, ascription o f responsibility, and resulting beliefs. Therefore, these indicators were adopted for use in this study. T he instruments in this study utilized an adapted version of the NEP scale to determine if a predominant worldview exists amongst residents in LEED cer tified residence halls. Additionally, of interest in this investigation are the awareness of consequences and ascription of responsibility measures that also align with those the USGBC assoc iates with resource consumption such as climate change and depleti ng natural resources ( USGBC, 2013b ). Personal norm i ndicator. In a study where the TPB and the VBN models were empirically compared, personal norms were measured using a single indicator : obligations. Obligations sense of duty to behave in a certain way

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105 (Kaiser, Hübner, & Bogner, 2005). In this study participants responded to 10 behavioral statements on a 5 point bipolar scale. A sample item from the survey stated, feel an obligation towards the environment and/or toward s other people, I refrain from using a clothe s dryer . . . agree Analyzed data indicated that the applied indicator and subsequent scale demonstrated a high reliability with a a lpha of . 8 2 (Kaiser, Hübner, & Bogner, 2005). As seen in the study by Kaiser, Hübner, and Bogner ( 2005) , an empirical association can be drawn between ones sense of obligation to behave in a certain way and resulting personal norms. Therefore, this indicator was adopted for use in this study. Subsequently, inst ruments in this study were designed to sense of obligation to perform behaviors that also align ed with those the USGBC associates with reducing resource consumption such as turning off lights, adjusting the thermostat, unplugging unused electronics, turning off faucets, taking shorter showers, and reporting leaks ( USGBC, 2013b ). Pilot Test for Survey and Interview Collins (2001) reminds us that when designing survey or interview instruments , researchers should aim to provide results that are valid, reliable, sensitive, unbiased and complete. Or, as explained by Fowler (1995): In other words we want to be certain that our questions measure the concepts or behaviors we want them to measure, that the data produced represent 'true' values for these measures and do not contain too much random variability, that our questions are sens itive enough to measure important real differences or c hanges, and that our study covers all the dimensions of the topic under investigation. Thus, prior to finalizing the survey and interview instruments for this study, each item went through several roun ds of cognitive testin g. Cognitive testing or cognitive

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106 interviewing is a field research method used primarily in pre testing survey and interview instruments. This method allows researchers to collect verbal information regarding survey or interview respo nses to evaluate whether questions are measuring the construct the researcher intends . The data collected was then used to adjust problematic questions before utilizing the instrument with a full sample (Willis , 2005 ) . Various cognitive methods have been d eveloped and applied to test study instruments. These include card sorts, cognitive interviewing, confidence ratings, paraphrasing, and response latency timing (Czaja, 1998; Forsyth & Lesser, 1991; Jobe & Mingay, 1991). Over the last 25 years the use of co gnitive testing, particularly cognitive interviewing, has become increasingly widespread in many western government statistical agencies and laboratories (Collins, 2001). For this study, five cognitive interviews were conducted to ensure that questions wer constructs, and constructed to provide an ease of reading for participants; to ensure that that survey sections we re sequenced in a logical order. As Adcock and Collier (2001) describe, it is also important to ensure that survey and interview items have the same meaning for different population sub groups. Thus, cognitive interviews were conducted with students who li ved in environmentally friendly residence halls at a local university as they represe nted a similar population to this comparative ca se study . The think aloud and probing interview techniques were utilized during each one hour long interview (Collins, 20 01; Willis, 2005 ). For example, participants were made aware that they were helping to test study instruments. They were also informed that the goal of the exercise was to better understand the validity of each question and to

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107 think aloud as they proceeded through each section. As participants responded to questions they were probed to elaborate on their answers and their understanding of each question. In this way participants were able to provide invaluable feedback with regards to the overall structure o f instruments and individual questions. For example, suggestions were made to change certain phrases, such as global warming or resource exhaustion, to more neutral alternatives. Additionally, questions were refined for comprehension and to better represen t a broad range of attitudes and personal norms. Reliabi lity, as measured by a statistical test , is a useful primary tool accepted by many educators for determining objective test effectiveness is item analysis, which examines Thus, prior to survey instrument , it was pilot tested with 49 students who live d in residence hall s at a southeastern public university. Each section of the survey was tested for reliability by running an inter item correlation. As previously noted, a rule of thumb for describing the internal consistency of s as follows: less than 0.5 is unacceptable, 0.5 0.6 is poor, 0.6 0.7 is acceptable, 0.7 0.9 is good, and 0.9 or greater is considered excellent ( George & Mallery, 2003; Kline, 1999) . Thus, in order to ensure a strong int ernal consistency in this study, survey i tems wit less than 0.6 were considered to have low reliability and were eliminated from the final survey. In total, 35 survey items were eliminated from the pilot tested survey in order to .82 across each of the survey sections. Table 3 5 illustrates the Cronbach alpha scores that correlate with the ordinal survey items in this study.

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108 Data Collection Demographic profiles and building consumptio n records were first used to provide a context for data collected from each residence hall. A finalized survey, resource tracking, and interview instruments were then developed b ased on the defined background concepts, systematized concepts, selected const ruct indicat ors, and pre testing results. These study tools were collectively titled The Environmentally Significant Behavior in LEED Residence Halls Surve y and I nterview i nstrument and are further described below. Demographic Profiles Demograph ic profiles for each case were develo ped to provide a context for understanding t he findings drawn from the surveys, resource tracking exercise, and interview instruments. General demographic information was obtained from sources such as institutional webs ites and published enrollment data, cost of attendance, gender and ethnicity ratios, and standardized test score averages. These resources were used to develop campus profiles for each university. Specific information pertaining to student housing resident s was obtained from the housing Directors at each institution and the residents who completed Section 9 : Demographics in the Environmentally Significant Behavior in LEED Residence Ha lls Survey and Interview instrument . This information was used to develop the demographic profile for survey participants. Building Consumption Data With the help of university housing staff and campus facility management the templates used to document compliance with WE, Credit 3 Water Use Reduction and EA, Credit 1 Optimized Energy Performance were collected . These templates indicate the initial design case and baseline case figures in kgal and Mb tu units. Additionally, a

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109 minimum of two years of metered water and energy data was obtained from each campus . Similar to a utility bill, this type of metered consumption i nformation itemizes the month to month utilization of a plumbing and electrical syste ms. Metered consumption for electrical (kWh), steam ( thm ) and chill water (kLbs) systems were conve rted to Mb tus units. Finally, figures for the design and baseline case, and total indoor w ater and energy consumption, were translated into line graphs to illustrate performance and reveal any disparities. Survey Volunteers for the Enviro nmentally Significant Behavior in LEED Residence Halls Survey and Interview were recruited from among the current residents at the four sample residence halls: Elizer Hall and Murdy Hall at Emory Oxford College, Chidley North at North Carolina Central Univ ersity, and Frank Hall at Appalachian State University. An IRB approved digital copy of the survey was sent to residence hall directors who then facilitated the distribution of the survey by forward ing a web link to their respective residents via email. Throughout a four week timeframe, responses were collected from a minimum of 20% of the total occupants in each dormitory . The survey took approximately 30 minutes to complete and participation was completely voluntary. All survey participants provided a d igitally signed consent form, were eighteen years old or older , and resided in their respective residence hall for a minimum of one month prior to completing the survey. Finally, a t the end of the survey, residents were asked if they would be willing to pa rticipate in a resource tracking exercise and qualitative interview residence hall.

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110 Resource Tracking Exercise Residents who indicated that they would be willing to participate in a resource tracking exercise and qualitative interview session were contacted via email to reserve a timeframe and to obtain an electronic consent form . Four days prior to each scheduled interview participants received a reminder email containing instr uctions for accurately completing the resource tracking form s . For the three consecutive days prior to each interview p articipants self report ed their use of water and energy from bathroom sinks, toilets, showerheads, kitchen sinks, lights, and air conditi oners in their residence hall. These locations coincided with those for which the USGBC offers design teams a default consumption setting. Each tracking form requested that participants documented the date, time, duration, and frequency of their use from e ach water fixture or energy feature. R esource tracking forms were then electronically returned to the primary investigator prior to the start of each interview. A minimum of 10 resource t racking forms were collected fro m participants in each residence hall. As in the survey, all participants were eighteen years old or older and have resided in their respective residence hall for a minimum of one month Interview Interviews are often conducted with a representative sample of a larger p opulation, whose responses can then be used to form generalizations about that population (Warren, 2001). Thus, a minimum of 10 interviews were conducted for each residence hall. Each interview was approximately one hour long and participation was complete ly voluntary. Interviews were conducted at a time chosen by participants via telecommunication (web cam) after a cop y of the signed consent form had been received. As in the survey and resource tracking exercise , all interview participants were

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111 eighteen ye ars old or older and had resided in their respective residence hall for a minimum of one month . permission , interviews were videotaped. For confidentiality purposes, only the principal investigator had access to the videotape and pe rsonally transcribe d each recording in order to remove any identifiers during transcription. All of the original recordings were erased upon completion of the study in order to keep the identity of participants confidential . Data Analysis Five data set s including demographic profiles, building consumption data , a survey, resource tracking exercise, and interviews were used to quantitatively and qualitatively examin e each case . Demographic profiles and building consumption data first helped to provide a co ntext for data collected from each residence hall. Participant responses to survey Sections 1 2, the resource tracking exercise, a nd Topics 2 3 of the interview were then leveraged to determine how accurately occupant behaviors are accounted for in the LEE for predicting water and energy consumption (research question 1, 1.1, and 1.2). Finally , findings from survey Sections 3 8 and interview Topics 1 and 4 9 were used to determine if a relationship exists between the TPB and VBN con in L EED certified residence halls (research question 2). The data analysis methods utilized to answer research questions 1 and 2 in this study are further described below. Demographic profile informat ion collected from university websites, published resources , and Section 9: Demographics of The Environmentally Significant Beh avior in LEED Residence Halls Survey and Interview instrument was organized and illustrated in tables. The design case, baseline case, and a minimum of two years of month to month meter readings for water and energy were translated into line graphs to illustrate the

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112 performance of each residence hall . These consumption trends were then compared in order to document the percentage change between each consumption type . The demographic profiles and building consumption data helped to provide a context for subsequent data collected from each residence hall. To answer research question 1 and its sub questions , th e resource tracking exercise and Section 1: Water Use, Section 2: Energy Use , Topic 2: Tracked Water Consumption and Topic 3: Tracked Energy Consumption of The Environmentally Significant Beh avior in LEED Residence Halls Survey and Interview instrument wer e analyzed using descriptive statistics. R atio, in terval, and nominal scale information regarding water usage, water flow durations, and lighting, fan and hot water schedules were organized into tables. These figures were compared to the LEED default stand ards in order to document the percentage change between each consumption type. To answer research question 2, the software for advance statistics, SAS, was used to perform a conf irmatory factor analysis (CFA) and exp loratory factor analysis (EFA) on Section 3: Environmental Values, Section 4: Environmental Beliefs, Section 5: Attitudes t owards Conserving Water and Energy, Section 6: Subjective and Personal Norms, Section 7: Perceived Behavioral Controls, and Section 8: Behavioral Intentions. In order to run each statistical analysis, a value from 1 5 was first assigned to each ordinal sca le type question in each of the sections. For example, in Section 6, a 5 was assigned to high pro environmental personal norms and a 1 was assigned to low environmental personal norms. The completed CFA and EFA then helped to identify the theoretical const ructs and indicators that most influence current ESBs in each residence

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113 hall. A CFA is a statistical technique used to confirm the factor structure of a set of observed variables. CFA allows an investigator to test the hypothesis that a relationship betwee n observed variables and their underlying latent constructs exists . As a type of square test, goodness of fit index (GFI), adjusted goodness of fit index (AGFI) and Ro ot Mean Square Error of Approximation (RMSEA), in order to determine the adequacy of model fit to the data (Suhr, 2006). Acceptable model fit is indicated by a chi square value close to zero, a GFI and AGFI value equal or greater than 0.90, and a RMSEA val ue of 0.06 or less ( Baumgartner & Hombur, 1996; Hu & Bentler, 1999). Conversely, EFA is used to explore the underlying factors in a set of observed variables without imposing a preconceived structure on the outcome. By establishing a factor eigenvalue, scr ee plot, and total percent of variance explained, an EFA is able to identify the factors that account for the most variability in a data set (Child, 1990). In order for a factor to be selected it will generally have an eigenvalue greater than or equal to 1 . However, this criterion should be used with caution if an important factor has an eigenvalue just below levels off and correlates with the number of factors that should be generated. Selected factors should also explain more than 80% of the variability from the original set of constructs (Rahn, 2014). Using ATLAS.ti , a powerful software for analyzing qualit ative data ( ATLAS.ti , 2013 ) , interview responses for Topic 1: LEED Knowledge , Topic 4: Environmental Values, Topic 5: Environmental Beliefs, Topic 6: Attitudes towards Conserving Water and Energy, Topic 7: Subjective and Personal Norms, Topic 8: Perceived Behavioral

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114 Controls, and Topic 9: Behavioral Intentions were e xamined . ATLAS.ti is intended to help researchers uncover and systematically analyze complex phenomena concealed in unstructured data such as text, multimedia, or geospatial documents . The progr am provides tools that allow a user to locate, code , and annotate findings in primary data material, to determine frequencies, weigh and evaluate their im portance, and to visualize the complex relations between them. The intent of this analysis was to draw connections between different ideas or proces ses that were mentioned in the interview ources in residence halls. Thus, interview responses were organized, tagged , measured for frequency, and cross tabulated to iden tify associations between selected theoretical constructs and the ESBs of interviewees. Upon completion of the data analysis, results were compared to determine the accuracy of LEED default settings and to determine if a relationship exists between reside nt and their actual consumption of water and energy within each dormitory. This comparison provided a foundation for the discussion of were made for further improving the pre diction t ools in the LEED rating system.

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115 Table 3 1. East Village construction p rofile ( Emory Oxford College, 2013b ) Emory Oxford College GSc 112, 600 (New Construction) Year Built 2008 LEED Certification Level Gold (awarded 2009) Occupancy 350 students Architecture and Interior Design Jova/Daniels/Busby Civil Engineering Southern Civil Engineers Landscape Architecture ECOS Structural Engineering Eberly Stone Mechanical Engineering Johnson Spellman Electrical Engineering Barnett Consulting Engineers LEED Consultant Eaton Corporation Gross Square Footage (GSF) Table 3 2. Chidley North construction p rofile (Lord Aeck Sargent, 2012 ) North Carolina Central University GSF 134,000 (New Construction) Year Built 2011 LEED Certification Level Gold (awarded 2012) Occupancy 500 students Architecture and Interior Design Lord Aeck & Sargent Civil and Structural Engineering Steward Engineering Landscape Architecture HadenStanziale Mechanical and Electrical Engineering Stanford White LEED Consultant Lord Aeck & Sargent Gross Square Footage (GSF) Table 3 3. Frank Hall construction p rofile (Appalachian State University, 2010 ) Appalachian State University GSF 40,900 (Major Renovation) Year Built 2009 LEED Certification Level Gold (awarded 2010) Occupancy 203 students Architecture and Interior Design Calloway Johnson Moore and West Mechanical, Electrical and Plumbing Engineering CJMW Architecture LEED Commissioning System WorCx Gross Square Footage (GSF)

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116 Table 3 4 . LEED d efaults for water fixture usage and flow d urations , and ANSI/ASHRAE/IESNA 90.1 s ettings for fans, hot water, and l ighting Fixture Type LEED Default Setting ( Use/Day) Usage ASHRAE Setting ( % Use) Water closet, female 5 Fan 67%, 33% Water closet, male 5 Hot Water 21.7% Lavatory faucet 5 Lighting 37% Showerhead 1 Kitchen Sink 4 Fixture Type LEED Default Setting ( sec) Peak Period Average (sec) Lavatory Faucet Showerhead Kitchen sink 60 480 60 Fan 6:00am 7:00pm (13 hrs) 7:00pm 11:00pm (4 hrs) Hot Water 9:00am 6:00pm (9 hrs) Lighting 10:00am 7:00pm (9 hrs) Seconds (sec), Hours (hrs); Percentage (%)

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117 Table 3 5 . Cronbach alpha scores for pilot t est Survey Section Indicator Internal Consistency Section 3: Environmental Values Biospheric Values .83 Good Altruistic Values .72 Good Egoistic Values .65 Acceptable Section 4: Environmental Beliefs New Environmental Paradigm .81 Good Awareness of Consequences .87 Good Ascription of Responsibility .91 Excellent Section 5: Attitudes t owards Conserving Water and Energy Behavioral factors .87 Good Evaluation .95 Excellent Section 6: Subjective and Personal Norms Normative Factor .93 Excellent Motivation to comply .67 Acceptable Obligation .92 Excellent Section 7: Perceived Behavioral Controls Perceived Power .79 Good Control belief .75 Good Section 8: Behavioral Intentions Intent .84 Good N= 49 Students Living in Residence H all s

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118 Table 3 6 . S ummary of the guiding principles used to design each survey s ection Survey Section Related Standard or Theory Construct Indicators Systematized Concept Definition Section 1: Water use USGBC default fixture uses, by occupancy type Refer to Table 2 8 USGBC default flow durations Refer to Table 2 8 Section 2: Energy Use USGBC default fan schedule Refer to Table 2 9 USGBC default service hot water schedule Refer to Table 2 10 USGBC default lighting schedule Refer to Table 2 11 Section 3: Environmental Values VBN construct: Values The guiding principles in life. Egoistic values Self interests motivate conduct Altruistic values The interest in others wellbeing motivates conduct Biospheric values The interest in the wellbeing of the environment motivates conduct Section 4: Environmental Beliefs VBN construct: Beliefs New Environmental Paradigm The perspective from which an individual considers their ecological worldview Awareness of Consequences Concern that there are consequences to not behaving sustainably Ascription of Responsibility A feeling of responsibly for the consequences of unsustainable behaviors Theory of Planned Behavior (TPB); Value Belief Norm Theory (VBN)

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119 Table 3 6 . Continued Survey Section Related Standard or Theory Construct Indicators Systematized Concept Definition Section 5: Attitudes t owards Conserving Water and Energy TPB construct: Attitudes Personal evaluation of a behavior Behavioral factors Holding that the performance of a certain behavior correlates with specific outcomes Evaluation Attachment to a behavioral outcome Section 6 : Subjective and Personal Norms TPB construct: Subjective norms Perception about whether most people approve or disapprove of the behavior Normative factor The perceived social pressure felt to perform or not perform a behavior Motivation to comply Influence to behave in a way that is acceptable by others VBN construct: Personal Norms Obligation S ense of obligation to behave in a certain way Section 7 : Perceived Behavioral Controls TPB construct: Perceived Behavioral Control Overall measure of perceived control over a behavior Control Beliefs Perceived likelihood of occurrence of each facilitating or constraining condition Perceived Power Perceived effect of each condition in making behavioral performance difficult or easy Section 8: Behavioral Intentions TPB construct: Behavioral intentions Intent Perceived likelihood of performing a behavior Theory of Planned Behavior (TPB); Value Belief Norm Theory (VBN)

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120 Figure 3 1 . Illustration of research d esign

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121 A B C D E F Figure 3 2 . A) East Village aerial view ( New South Construction, 2013 ) . B) Elizer Hall e ntrance (Photo courtesy of author) . C) Elizer Hall lobby ( New South Construction, 2013 ) . D ) Water c ollection f eature (Photo courtesy of author). E) Private b athroom (Photo courtesy of author) . F) Public study r oom (Photo courtesy of author).

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122 A B C D E F Figure 3 3 . Main lobby ( West, 2012 ) . B) Chidley North exterior elevation ( West, 2012 ) . C) Double occupancy r oom ( West, 2012 ) . D) Typical c orridor (Photo courtesy of author) . E) Public study r oom (Photo courtesy of author) . F) Communal k itchen (Photo courtesy of author) .

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123 A B C D E F Figure 3 4 . Residence Hall. A) Frank Hall a erial view ( New Atlantic Contracting, 2007 ) . B) Frank Hall entrance (Photo courtesy of author) . C) Typical corridor (Photo courtesy of author) . D) Main lobby ( New Atlantic Contracting, 2007 ) . E ) Double occupancy room (Photo c ourtesy of author) . F) Communal kitchen (Photo courtesy of author) .

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124 Figure 3 5 . Illustration of data collecting i nstruments

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125 CHAPTER 4 FINDINGS This chapter presents the research outcomes for this study as they related to research question 1 and 2. Findings relevant to research question 1 , which accessed the accuracy of the LEED default settings and referenced energy schedules, are first examined . The d emographic profiles, buildin g consumption readings, select ive survey sections , the resource tracki ng exercise, and select ive interview topics were used to investigate the consumption of water and energy within each case . The d emographic profiles and building consumption instruments are summarized for all three cases and help to contextualize the outcomes from the survey, resource tracking exercise, and interview s . A synthesis of findings related to research question 1 and its sub questions is then provided. Findings pertinent to research question 2 , which investigated the relationship between behavioral constructs and resource consumption in residence halls , are then described . S ections of the su rvey and interview topics that specifically examined the constr uct from the TPB and VBN models are reviewed for all three case s. Finally, summaries ar e provided to better capture the outcomes from the confirmatory factor analysis, explorato ry factor analysis, and the qualitative analysis of interviews . Case One Demographic Profiles According to the projected expenses for t he 2013 2014 academic year at Emory Oxford , students can anticipate paying $37,800 for tuition and approximately $14,852 towards fees, room and board, books, and incidentals. Published demographic statistics also indicated that 1,240 ( 45% ) of the 2,755

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126 College in 2013 were male and 1,515 ( 55% ) were female. On average admitted students had a GPA between 3.52 3.90, an SAT score between 1860 2120, and an ACT score between 27 32. Of the students accepted into the fall seme ster 1,157 ( 42% ) identified their ethnicity as White/Caucasian, 331 ( 12% ) were African American, 220 ( 8% ) were Hispanic, 882 ( 32% ) were Asian, 2 7 ( 1% ) were Native American, 138 ( 5 % ) chose not to specify , and none indicated that they were Pacific Islander o r Other. Additionally, 2,259 ( 82% ) of students were admitted from among 36 states and 496 ( 18% ) were international students who traveled from among 21 different nations ( Emory Oxfor d College, 2013 a). Further information regarding the educational and econom ic histories of student families was considered confidential and was therefore not disclosed. Table 4 1 illustrate s the demographic profile f or the population at Emory Oxford College. In total, 112 (32%) of the 350 occupants in East Village submitted a res ponse to the web based survey. While 123 ( 35 % ) of East Village population are male and 228 ( 65 % ) are female (M. Sheets, personal communication, April 14 th , 2014), r esponses indicated that 29 ( 26% ) of respondents were male and 83 ( 74% ) were female. Of this sample, 104 ( 93% ) were between the ages of 18 19, 8 ( 7% ) were between the ages of 20 21, and none indicated that they were 22 years old or older. A total of 38 ( 34% ) of survey participants identified their ethnicity as White/Caucasian , 16 ( 14% ) were African American, 10 ( 9% ) were Hispanic, 46 ( 4 1 % ) were Asian, 2 ( 2 % ) claimed Other, and none indicated that they were Pacific Islander or Native American. Finally, 8 ( 7% ) indicated that they were international students from Brazil, China, J amaica or India. Table 4 2 illustrate s the demographic profile f or

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127 Building Consumption As previously described in the Building Consumption Data (pg.107 ) section of this study, original LEED templates for WE, Credit 3 Water Use Reduction and EA, Credit 1 Optimized Energy Performance were collected to establish the initial design intent and baseline case for each residence hall. Additionally, a minimum of two years of metered water and energy dat a was obtained from eac s facilities department. The comparison between the initial design intent data, baseline case data, and metered consumption data helped to identify if a gap existed between how each building was designed to perform and how they actually perform on a yearly basis. Water consumption Consumption readings from East Village were collected for January 2010 to J from the regulated water closets, lavatory faucets, showerheads, and kitchen sin ks averaged 3,603.3 kgals per year . I t was noted that consumption made large increases of 16% between 2012 2013 and 17% between 2013 2014. Additionally, according to the LEED template provided for WE Credit 3 Water Use Reduction, the calculated baseline and design case value s for indoor water consumption from regulated fixtures were 3,847.8 kgals and 2,533.8 kgals per year , respectively. These initial findings for East Village ind icated that actual consumption was an average of 6.4% below a baseline case and 42.2 % above the design case. Figure 4 1 ha s been provided to illustrate the water consumption of East Village between the years of 2010 2014. Energy consumption Indoor energy consumption from the fan, hot water heating, and lighting systems in East Vil lage averaged 2,603.2 Mbtus per year for the metered readings taken

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128 between January of 2010 and January of 2014. Additionally, according to the LEED template provided for EA Credit 1 Optimized Energy Performance, the calculated baseline and design case va lues for energy consumption from regulated fixtures were 5,704 Mbtus and 4309 Mbtus per year , respectively. These findings for East Village ind icated that actual consumption was 54.4% below a baseline case and 39.6 % below the design case. Figure 4 2 has be en provided to illustrate the energy consumption of East Village during its first four years of operation. The irregularly high variation from the baseline case prompted further investigation into the LEED documentation and energy consumption and for this building. The template calculations for EA, Credit 1 Optimized Energy Performance were reviewed and despite being overcapacity at the time of this study (M. Sheets, personal communication, October 3 rd 4% of the estimates provide d in this LEED document . Additional consumption data for Financial, Resource Planning and IT Department (D. Colbert, personal communication Novembe r 22 nd , 2013). However, this additional data did not conclusively explain why electrical readings were so low between 2010 2014 and could not be used to determine if there was or was not an error with the meters. Accuracy of LEED Default Settings for Water As previously described in the Foundations for Predicting Water Consumption (pg. 31 ) section of this study, the USGBC provides default fixture usage rates and durations f or residential settings , indiscriminate of the residential type . Currently the estima tes provided by the USGBC (2013b) for fixture usage rates and durations indicate that male and female residents will utilize a water closet 5 times per day. Additionally, it

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129 is anticipated that both types of residents will use a lavatory faucet 5 times per day for a duration of 60 seconds each, a showerhead once a day for 480 seconds, and a kitchen sink 4 times per day for a duration of 60 seconds per use ( illustrated in Table 3 4 ). Research question 1 and sub question 1.1 seek to assess the accuracy of the LEED default settings related to water consumption. Thus, Section 1: Water Use of the survey , the resource tracking exercise, and Topic 2: Tracked Water Consumption of the interview instrument, were designed to compare the referenced LEED default values f or water with the actual consumption reported by residents. Survey findings for water fixture usage and flow d urations Based on the 112 survey responses from East Village, female and male residents estimated that they used the water closet within their re sidence hall 3 and 2 times per day, respectively. Additionally, both resident types responded that they used a lavatory faucet 3 times per day for an average of 30 60 seconds per use, a showerhead once per day for 720 or more seconds, and none of the surve y participants believed that they used the kitchen sink on a daily basis but believed that it ran for 1 29 seconds when its use was necessary. Table 4 3 has been provided to illustrate the difference between the LEED default settings , and the water fixture usage and flow duration suggested by survey participants in East Village. Resource tracking findings for water fixture usage and flow d urations A total of 13 5 tracking forms were collected for this study 45 of which came from the 15 residents who participated in the resource tracking exercise and interview from East Village (9 females and 6 males). Based on the three days of water tracking information collected from East Village participants, female and male occupants used residence hall water clos ets 2.9 and 2.7 times per day, respectively. Additionally, the

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130 average of both resident types suggested that lavatory faucet were used 2.8 times per day for 145.3 seconds per use, showerhead were used 1.4 times per day for 934 seconds, and the kitchen sink was used 0.2 times per day for 42.7 seconds per use. Table 4 4 illustrates the difference between the LEED default settings and the water fixture usage of residents who participated in the resource tracking exercise. I nterview findings for water fixture u sage and flow durations In the Topic 2: Tracked Water Consumption section of the interview, the 15 participants from East Village were asked to reflect on their utilization of LEED regulated water fixtures. Thus, after tracking their use of showers, toilet s, lavatory sinks, and kitchen sinks for three days participants were asked if their water consumption was more, less or about what they expected. Once participants defined how self aware they were of their own consumption, they were asked to defined what contributes the most to their daily consumption of water. The qualitative analysis of interviews from East Village indicated that regardless of gender, 11 ( 73.3% ) of the participants believed that their consumption of regulated fixtures was about what they expected, 2 (13.3 % ) believed that their water consumption was more, and 2 ( 13.3% ) believed it was less. Participant s who indicated that their consumption was about the same attributed the majority of their water consumption to the regular use of showe rs ( 6, 40%) and sinks ( 3, 20%), and the adherence to a daily routine ( 3, 20%). For example, when describing their water between 10 shing my hands throughout Those that noted that their water consumption was more than anticipated attributed this increase to longer showers ( 2, 13.3%). Finally, those who be lieved their consumption

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131 was less indicated that they took faster showers ( 1, 6.7%), made fewer visits to the toilet ( 1, 6.7%), and had busy schedules that caused them to be out of East Village for long periods of time ( 1, 6.7%). Appendix I helps to illust rate the qualitative analysis of interview responses from East Village. Energy Related Schedules As previously described in the Foundations for Predicting Energy Consumption (pg. 37 ) section of this study, the USGBC applies the ANSI/ASHRAE/IESNA 90.1 stand ard to enhance the energy performance of buildings. This industry standard provides fan, service hot water, and lighting schedules for project teams to use while developing building energy models. Currently the referenced ANSI/ASHRAE/IESNA fan schedule indicates that occupants will utilize the HVAC system during two peak periods or time frame s of high cu stomer demand . The first peak period is between 6:00am 7:00pm (13 hrs) where approximately 67% of occupants are expected to utilize this building system. The second peak period is between 7:00pm 11:00pm (4 hrs) where approximately 33% of occupants are expe cted to utilize this system. Additionally, the referenced ANSI/ASHRAE/IESNA hot water schedule indicates that approximately 21.7% of occupants will utilize the hot water heater between the peak hours of 9:00am 6:00pm . Finally, the referenced ANSI/ASHRAE/IE SNA lighting schedule indicates that approximately 37% of occupants will utilize the overhead lighting system between the peak hours of 10:00am 7:00pm ( ASHRAE, 2009 ; illustrated in Table 3 4 ) . Research question 1 and sub question 1.2 s ought to assess the accuracy of the LEED referenced standards related to energy consumption. Thus, data collected from the survey ( Section 1: Energy Use ), the resource tracking exercise, and the interview ( Topic 3:Tracked Energy Consumption ) were analyzed to compare the refer enced

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132 LEED default values for energy with the actual consumption reported by residents. The following sections will present all of the findings for energy related schedules from these instruments. Survey findings for energy related s chedules Based on the 112 survey responses from East Village, 60 ( 54% ) respondents indicated that they utilized the HVAC system throughout a 24 hour period. Additionally, respondents indicated that they utilized the hot water heater during two peak periods. The first was betwee n 8:00am 12:00pm (4 hrs) where approximately 27 (24 .3 % ) respondents believed that they utilized the hot water system. The second peak period was between 8:00pm 2:00am (6 hrs) where 31 ( 28% ) participants estimated that they utilized the hot water heater. Fi nally, participants also indicated that they utilized the overhead lighting during two peak periods. The first was between 7:00am 12:00pm (5 hrs) where approximately 30 (26.8 % ) respondents estimated that they utilized the overhead lighting system. The second peak period was between 1:00pm 2:00am (13 hrs) where approximately 54 (4 7.8 % ) of respondents believed that they utilized the overhead lights. Table 4 5 has been provided to illustrate the percentage difference between the energ schedules created for ANSI/ASHRAE/IESNA 90.1. Resource tracking findings for energy related s chedules Based on the three days of energy tracking information collected from 15 East Village residents, approximately 12 (81.9 % ) of the resource tracking exercise participants indicated that they utilized the HVAC system throughout a 24 hour period. Tracking forms also suggested that occupants utilized the hot water heater during two peak periods. The first was between 8:00am 1:00pm (5 hrs) where approximately 3

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133 ( 22.2% ) participants utilized the hot water system. The second peak period was between 7:00pm 12:00am (5 hrs) where up to 3 ( 20% ) participants utilized the hot water heater. Finally, partic ipants also denoted that they utilized the overhead lighting during two peak periods. The first was between 8:00am 1:00pm (5 hrs) where approximately 3 ( 20.9% ) participants utilized the overhead lighting system. The second peak period was between 4:00pm 2: 00am (10 hrs) where approximately 6 ( 39.8% ) of participants stated that they accessed the overhead lights. Table 4 6 has been provided to illustrate the percentage difference between the energy schedules reported resource tracking exercise participants and the schedules referenced in the ANSI/ASHRAE/IESNA 90.1 standard. Interview findings for energy related s chedules In the Topic 3:Tracked Energy Consumption section of the interview, the 15 participants were asked to refl ect on their utilization of ANSI/ASHRAE/IESNA regulated energy systems. Thus, after tracking their use of the HVAC and lighting systems for three days participants were asked if their energy consumption was more, less , or about what they expected. Once par ticipants defined how self aware they were of their own consumption, they were a sked to defined what contributed the most to thei r daily consumption of energy. The qualitative analysis of i nterviews from East Village indicated that 6 ( 40% ) participants bel ieved that their consumption of regulated energy systems was about what they expected, 5 ( 33.3% ) noted that their energy consumption was more, and 4 ( 26.7% ) believed it was less. Participants who indicated that their consumption was about the same attribut ed the majority of their energy consumption to their regular use of the HVAC unit ( 5, 33.3%) and overhead lights in their room ( 3, 20%). Those that indicated that their energy consumption was more than anticipated

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134 attributed this increase to a more frequen t use of the HVAC system ( 3, 20%), leaving electronics plugged in ( 1, 6.7%), and leaving the lights turned on unnecessarily ( 1, guess is that [my consumption was more] b ecause I run the air conditioning all the time. It runs pretty much 24 hours. The building is set at about 72 degrees, so it just runs to consumption was less contributed thi s decrease to keeping the lights turned off ( 4, 26.7%), having a busy schedule that caused them to be out of East Village for long periods of time ( 4, 26.7%), and turning off the air conditioning when leaving their room (1, 6.7 %). Appendix I helps to illus trate the qualitative analysis of interview responses from East Village. Case Two Demographic Profiles According to the projected expenses for the 2013 2014 academic year at North Carolina Central Univers ity students can anticipate paying $6,901 for tuition and approximately $15,519 towards fees, room and board, books, and incidentals. Based upon the college portrait provided for North Carolina Central University, 1476 ( 33% ) of the 4,472 students admitted in 2013 were male and 2,996 ( 67% ) were female. On average students had a GPA of 2.99, an SAT score between 790 930, and an ACT score between 15 19. Of the students admitted to the fall semester 224 ( 5% ) identified their ethnicity as White /Caucasian, 3,756 ( 84% ) were African American, 80 ( 2% ) were Hispanic, 45 ( 1% ) were Asian, 45 ( 1% ) were Native American, 45 ( 1% ) were Pacific Islander, 89 ( 2% ) claimed Other, and 179 ( 4 % ) chose not to specify. Additionally, 4,427 ( 99% ) of students were admi tted from within the United States and 45 ( 1% ) were

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135 international students ( Nort h Carolina Central University, 2013 ). Additionally , 2,862 ( 64% ) of incoming students at North Carolina Central University are reported to come from low income families ( Nort h C arolina Central University, 2013 ). Table 4 1 illustrate s the demographic profile for the population at North Carolina Central University. A total of 149 (30%) of the 500 occupants from Chidley North submitted a response to the web based survey instrument. While 250 ( 50% ) of the population are male and 250 ( 50% ) are female (M. Rouillard , personal communication, April 14 th , 2014), r esponses to Section 9 : Demographics from this residence hall indicated that 43 ( 29% ) of respondents were male and 106 ( 71% ) were female. Of this sample, 104 ( 70% ) were between the ages of 18 19, 39 ( 26% ) were between the ages of 20 21, 4 ( 3% ) were between the ages 22 23, 2 ( 1% ) were between the ages of 24 25, and none were 26 years old or older. A total of 16 ( 11% ) s urvey participants identified their ethnicity as White/Caucasian, 121 ( 81% ) were African American, 2 ( 1% ) were Hispanic, 3 ( 2% ) were Asian, 3 ( 2% ) were Native American, 4 ( 3% ) claimed Other, and none were Pacific Islander. Finally, 3 ( 2% ) indicated that th ey were international students from the Bahamas. Table 4 2 illustrate s the demographic profile for the survey participants from Chidley North. Building Consumption Water consumption Consumption readings from Chidley North were collected from January 2012 to January 2014. water closets, lavatory faucets, showerheads, and kitchen sinks averaged 3,457.6 kgals per year . According to the LEED template provided for WE Credit 3 Water Use Reduction, the calculated baseline and design case values for indoor water

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136 consumption from regulated fixtures were 6,452.0 kgals and 4,337.4 kgals per year , respectively. These initial fi ndings for Chidley North ind icated that actual consumption was an average of 46.4% below a baseline case and 20.3 % below the design case . Figure 4 3 has been provided to illustrate the water consumption of Chidley North between the years of 2012 2014. The irregularly high variation from the baseline case for Chidley North prompted further investigation into the water consumption and LEED documentation for this building. As anticipated, the LEED documents for Chidley North indicated that the default settings for water fixture use and flow rates were applied. Thus, the over estimation of water closets, lavatory sinks and kitchen sinks would have skewed the original baseline and prediction line to make actual consumption appear to be significantly below both re ference points. Additionally, m etered readings for this building indicated that during the first full year of operation, only 95.6 kgals were consumed. This is approximately 191.2 gallons each year and 0.52 gallons each day per resident. B ased on the unrea listically low water meter readings for this particular building it was believed that this system was malfunctioning. The Facilities Service Engineer at Chidley North confirmed this assessment and indicated that since the building s opening in August of 20 11 he had contacted City of Durham inspectors twice to examine the abnormally low water consumption at this building (T. Tran, personal communication, February 6 th , 2013). However, the cause for the low meter readings was not reported as resolved until Nov ember of 2013. Upon con tacting the State Construction O ffice in Raleigh, North Carolina the Engineering Supervisor reve a led tha t meters for Chidley; one for low flow and one for high flow. Apparently only one meter

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137 was working during the first full year of reporting (2011/2012). The seco nd year of reporting (2012/2013 Thagard, personal communication, November 20 th , 2013). Based on the State water consumption reports, residence halls in the area average 5,000 gallons per student per year in domestic water Some higher due to cooling tower make up and some lower for buildings with (L. Thagard, personal comm unication, November 20 th , 2013). It is noted that despite the overestimation of the baseline case and the underestimation of meter readings during the year of 2013, the average water use for Chidley North was still 367.69 kgals more than a baseline standar d. This suggests that the corrected meter readings for 2014 2015 will significantly exceed the existing baseline case should current consumption rates continue. Energy consumption Indoor energy consumption from the fan, hot water heating, and lighting sy stems in Chidley North averaged 5,478.7 Mbtus per year for the metered readings taken between January of 2012 and January of 2014. According to the LEED template provided for EA Credit 1 Optimized Energy Performance, the calculated baseline and design cas e values for energy consumption from regulated fixtures were 9,478 Mbtus and 7,444 Mbtus per year , respectively. These findings for Chidely North ind icated that actual consumption was 42.2% below a baseline case and 26.4 % below the design case . Figure 4 4 has been provided to illustrate the energy consumption of Chidley North during its first two years of operation. The LEED templates for EA, Credit 1 Optimized Energy Performance were also reviewed for Chidley North. The reported tenancy at the time of this study was within

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138 1.2% of the estimates provided in the LEED documents (M. Rouillard, personal communication, September 3 rd , 2013). However, despite the accuracy of occupancy prediction s , a case study presented at the Annual State Construction Conference i n 2013 similarly noted an unusually high variation (68%) from the baseline case (Thagard, 2013). It was determined at that time tha incomplete f any th , 2013). The collection of additional consumption readings from the universities Facilities Service Engineer indicated that meter readings for Chidley North remained incomplete b y the en d of the 2013 academic year (T. Tran, personal communication, November 20 th , 2013). When additional information regarding these issues was requested from the State Construction Office in Raleigh, North Carolina the Engineering Supervisor stated Chidley steam meter continues to be problematic, which I am slowly learning is typical for steam meters. A more reliable method would be to meter the condensate going back to the steam plant instead of the steam going into the building. Steam meter repairs and calibration are ongoing at Chidley, but data were not available in September. It is also noted that natural gas is used for domestic water heating in the summer when the steam plant is off line for maintenance. Our data show that there is gas use for the months of June, July and August and for some reason minimal use in th , 2013). Thus, based on the continued confirmation that meter readings were incomplete between the years of 2012 2014, it is believed that current performance for this building is deceptively low.

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139 Accuracy of LEED Default Settings for Water Survey findings for wa ter fixture usage and flow d urations A ccording to the 149 survey responses to Section 1: Water Use , female residents in Chidley North estimated that they used the water closet 3 times per day while males predicted that they used this fixture 3.5 times per day. Both resident types anticipated that they used a lavatory faucet 4 times per day for an average of 120 180 seconds per use and a showerhead 2 times per day for 720 or more seconds. Similar to responses from East Village we find that none of the survey participants believed that they used the kitchen sink on a daily basis but predicted that it ran for 1 29 seconds when its use was necessary. Table 4 3 has been provided to illustrate the difference between the LEED default settings, and the water fixture usage and flow duration suggested by survey participants in Chidley North. Resource tracking findings for water fixture usage and f low d urations A total of 51 tracking forms were collected from the 17 residents who participated in the resource tracking ex ercise and interview from Chidley North (11 females and 6 males). Similar to the self reported usage female residents from Chidley North indicated that they used the water closets 3.4 times per day while males used this fixt ure 2.8 times per day. Both resident types signified that they used a lavatory faucet 2.8 times per day for an average of 190.6 seconds per use, a showerhead 1.2 times per day for 1085.3 seconds per use, and the kitchen sink was used 0.1 times per day for an average of 34.1 seconds per use. Table 4 4 illustrates the difference between the LEED default settings and the water fixture usage of residents who participated in the resource tracking exercise.

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140 Intervi ew findings for water fixture usage and flow d ura tions The 17 Chidley North interviews indicated that 12 ( 70.6% ) of participants believed that their consumption of regulated fixtures was about what they expected, 3 ( 17.6% ) believed that their water consumption was more, and 2 ( 11.8% ) believed it was less . Residents who indicated that their consumption was about the same attributed the majority of their water consumption to the regular use of showers ( 11, 64.7%), the adherence to a daily routine ( 3, 17.6%), and the use of sinks ( 1, 5.9%) and toilets ( 1, 5.9%). Those that noted that their water consumption was more than anticipated credited the bulk of their consumption to longer showers ( 2, 11.8%) and the more frequent use of toilets ( 1, to warm it up and it takes a little while. I let it run for like 10 minutes before I get in. I consistently take about a 35 minute shower, so 10 minutes of that is just letting the l ess than anticipated were either unsure of their contributing factor (1, 5.9%) or indicated that they took faster showers ( 1, 5.9%) than expected. Appendix I illustrates the qualitative analysis of interview responses from Chidley North. Energy Related Sch edules Survey findings for energy related s chedules According to the 149 responses to survey Section 2: Energy Use , approximately 60 ( 40% ) participants from Chidley North indicated that they utilized the HVAC system throughout a 24 hour period. Similar to the findings for East Village, participants estimated that they utilized the hot water heater during two peak periods. The first was between 7:00am 11:00am (4 h r s) where approximately 33 ( 22.3% ) participants projected that they utilized the hot water syste m. The second peak period was between

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141 8:00pm 1:00am (5 hrs) where approximately 41 ( 27.6% ) participants believed that they utilized the hot water heater. Finally, occupants also estimated that they utilized the overhead lighting during two peak periods. Th e first was between 6:00am 12:00pm (6 hrs) where approximately 32 ( 21.3% ) participants anticipated that they utilized the overhead lighting system. The second peak period was between 3:00pm 3:00am (12 hrs) where approximately 53 ( 35.8% ) participants predicted that they utilized the overhead lights. Table 4 5 has been provided to illustrate the percentage difference schedules created for ANSI/ASHRAE/IESNA 90.1. Resour ce tracking findings for energy related s chedules Based on the three days of energy tracking information collected from 17 resource tracking and interview participants from Chidley North, approximately 13 ( 76.1 % ) utilized the HVAC system throughout a 24 ho ur period. Similar to East Village residents, the p articipants from Chidley North also expressed that they utilized the hot water heater during two peak periods. The first was between 7:00am 11:00am (4 hrs) where approximately 2 ( 9.8% ) participants utilize d the hot water system. The second peak period was between 6:00pm 11:00pm (5 hrs) where up to 4 ( 23.5% ) participants utilized the hot water heater. Finally, participants also indicated that they utilized the overhead lighting during two peak periods. The f irst was between 9:00am 3:00pm (6 hrs) where approximately 3 ( 20.6% ) participants overhead lighting system. The second peak period was between 5:00pm 1:00am (8 hrs) where approximately 7 ( 42.9% ) participants utilized the overhead li ghts. Table 4 6 has been provided to illustrate the percentage difference between the energy schedules reported

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142 tracking exercise participants and the schedules referenced in the ANSI/ASHRAE/IESNA 90.1 standard. Interview findings for energy related s chedules Based on the qualitative analysis of the 17 interviews from Chidley North , 8 ( 47.1% ) participants believed that their consumption from regulated energy systems was about what they expected, 6 ( 35.3% ) noted that their energy consumption was more, and 3 ( 17.6% ) believed it was less. Participants who indicated that their consumption was about the same attributed the majority of their energy consumption to their regular use of the HVAC unit ( 5, 29.4%) and overhead lights in their room ( 3, 17.6%), and consistently leaving electronics plugged in (3, 17.6%) . Those that indicated that their energy consumption was higher than expected attributed this increase to a more frequent use of the HVAC ( 4, 23.5%), leavi ng electronics plugged in ( 2, 11.8%), and leaving the lights turned on unnecessarily ( 2, 11.8%). Finally, those who believed their consumption was less contributed this decrease to turning off the lights ( 3, 17.6%), HVAC ( 1, 5.9%) and TV ( 1, 5.9%) when not in use; having a busy schedule that caused them to be out of Chidley North for long periods of time ( 1, 5.9%); using natural daylight ( 1, 5.9%), and unplugging unused electronics ( 1, 5.9%). For example, one resident unplug everything when I leave. So that includes chargers, printers, and the iron. Like if only time that I run the air conditioner is when I sleep. So when I am running back and 6:30am until about 9:00pm or 10:00pm it s App endix I helps to illustrate the qualitative analysis of interview responses from Chidley North.

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143 Case Three Demographic Profiles According to the projected expenses for the 2013 2014 academic year at Appalachian State University students can anticipate paying $6,712 for tuition and approximately $13,870 towards fees, room and board, books, and incidentals. Based upon the institutional research published by Appalachian State University 1,384 ( 48% ) of the 2 , 883 students admitted in 2013 were ma le and 1,499 ( 52% ) were female. On average students had a GPA of 3.96, an SAT score between 1129 1141, and an ACT score between 24.1 26.1. Of the students admitted to the fall semester of 2013 2,479 ( 86% ) identified their ethnicity as White/Caucasian, 115 ( 4% ) were African American, 115 ( 4% ) were Hispanic, 58 ( 2% ) were Asian, 29 ( 1% ) were Native American, 29 ( 1% ) were Pacific Islanders, 58 ( 2% ) chose not to specify , and none claimed Other . Additionally , 2,854 ( 99% ) of students were admitted from among the U nited States and 29 ( 1% ) were international students ( App alachian State University, 2013). Further information regarding the educational and economic histories of student families was considered confidential and was therefore not disclosed . Table 4 1 illus trate s the demographic profile for Appalachian State University. A total of 56 (28%) out of the 203 occupants from Frank Hall submitted a response to the web based survey. While 101 ( 50% ) of the population are male and 102 ( 50% ) are female ( J. Lorello , personal communication, April 14 th , 2014), r esponses to Section 9 : Demographics from this residence hall indicated that 20 ( 36% ) of respondents were male and 36 ( 64% ) were female. Of this sample, 49 ( 87% ) were between the ages of 18 19, 7 ( 13% ) w ere between the ages of 20 21, and none were 22 years old or older. A total of 49 ( 87% ) survey participants identified their ethnicity as

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144 White/Caucasian, 3 ( 5% ) were African American, 3 ( 5% ) were Asian, 1 ( 2 % ) claimed Other, and none were Native American or Pacific Islander. Finally, 3 ( 5% ) indicated that they were international students from Canada or China. Table 4 2 illustrate s the demographic profile for the survey participants from Frank Hall. Building Consumption Water consumption Building consumpti on readings from Frank Hall were collected from January 2010 to January 2014. water closets, lavatory faucets, showerheads, and kitchen sinks averaged 1,030.3 kgals per year . According to the LEED template provided for WE Credit 3 Water Use Reduction, the calculated baseline and design case values for indoor water consumption from regulated fixtures were 2,158.7 kgals and 1,666.0 kgals per year , respectively. These initial findings for F rank Hall ind icated that actual consumption was an average of 52.3% below a baseline case and 38.2 % below the design case . Figure 4 5 has been provides to illustrate the water consumption of Frank Hall between the years of 2010 2014. The irregularly high variation from the baseline case for Frank Hall prompted further investigation into the water consumption and LEED documentation for this building. Similar to Chidley North, the LEED documents for Frank Hall indicated that the default set tings for water fixture use and flow rates were applied. Again the over estimation of water closets, lavatory sinks and kitchen sinks would have skewed the original baseline and prediction line to make actual consumption appear to be significantly below bo th reference points. Despite these overestimations, however, the m etered readings for this building indicated that during the first four years of operation,

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145 an average of 1,030.3 kgals were consumed. This is approximately 5,075.4 gallons each year and 13.9 gallons each day per resident. This estimate falls within 1.5% of the 5,000 gallon per year average provided by the Engineering Supervisor at the State Construction Office in Raleigh, North Carolina. The Energy Analyst at Appalachian State University also confirmed that significant efforts had been taken on campus to toilets and urinals using as much as 1/8 less water than prior fixtures. Residence halls are under a separate m Richardson, personal communication, December 2 nd , 2013). Thus, it seems plausible that the low consumption rates at Frank Hall are indeed accurate. Energy consumption Indoor energy consumpti on data for Frank Hall averaged 10,662.8 Mbtus per year for the metered readings taken between January of 2010 and January of 2014. Additionally, according to the LEED template provided for EA Credit 1 Optimized Energy Performance, the calculated baseline and design case values for energy consumption from regulated fixtures were 4,027 Mbtus and 2,985 Mbtus per year , respectively. These findings for Frank Hall ind icated that actual consumption was 164.8% above a baseline case and 257.2 % above the design cas e . Figure 4 6 has been provided to illustrate the water consumption of F rank Hall during its first four years of operation. Finally, t he LEED templates for EA, Credit 1 Opt imized Energy Performance were reviewed for Frank Hall . The reported tenancy at the t ime of this study was within 1.5 % of the estimates provided in the LEED documents ( J . Lorello , personal communication, August 27th , 2013). However, despite the accuracy of occupancy

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146 prediction s , a n energy consumption summary of 18 residence halls on Appalachian foot and 21.11 M btu s per student; making this building the largest energy consumer certified residence halls and the third largest consumer amongst all 18 of the reported campus buildings. (P. Richardson, personal communication, January 31 st 2013). In response to an inquiry regarding this buildings disappointment for ASU since its only real value so far is the LEED certification. The energy consumption is one of the worst on campus, but most of that we think is due to bad sequences of operation. We hope to make it more efficient sometime in the futu re. 31 st s Energy Analyst, it is believed that the current energy performance findings for Frank Hall are accurately high. It is noted however that continued research and efforts for reducing energy consumption are currently taking place on Appalachian State Unive 2013, which resulted in a 25% reduction in energy consumption. The sequencing of building systems is also under review in order to improve current performance. Additionally, across campus other LEED certified buildings, such as Mountaineer Hall, have shown to be very successful at reducing energy consumption. The previously mentioned energy consumption summary indicated that Mountaineer used 65% les s

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147 energy than Frank Hall and 72% less energy per square foot than other residence halls of similar size. According to the university analyst some a key difference amo ngst the two residence halls was that Mountaineer was designed and implemented with energy efficiency as a design goal while Frank hall was designed and implemented to only meet the LE ED Gold checklist (P. Richardson, personal communication, November 22 nd , 2013). Accuracy of LEED Default Settings for Water Survey findings for water fixture usa ge and flow d urations B ased on the 56 survey responses to Section 1: Water Use from Frank Hall, female residents estimated that they used the water closet in their residence hall 3.5 times per day while males anticipated that they used this fixture 3 times per day. Both resident types predicted that they used a lavatory faucet 3.5 times per day for an average of 1 29 seconds per use and a showerhead 2 times per day for 480 600 seconds. For the third time we find that occupants did not feel that they used th e kitchen sink on a daily basis but estimated that it ran for 1 29 seconds when its use was necessary. Table 4 3 has been provided to illustrate the difference between the LEED default settings, and the water fixture usage and flow duration suggested by su rvey participants in Frank Hall. Resource tracking findings for water fixture usage and flow d urations A total of 39 tracking forms were collected from 13 residents who participated in the resource tracking exercise and interview from Frank Hall (8 females and 5 males). B ased on the self reported consumption of Frank Hall participants, female residents used the water closet in their residence hall 3.3 times per day while males denoted that they used this fixture 3 times per day. Both resident types indicate d that they used a

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148 lavatory faucet 3.1 times per day for an average of 129.3 seconds per use, a showerhead 1.2 times per day for 855.5 seconds, and the kitchen sink was used 0.5 times per day for an average of 118.5 seconds per use. Table 4 4 illustrates t he difference between the LEED default settings and the water fixture usage of residents who participated in the resource tracking exercise. Interview findings for water fixture usage and flow d urations Frank Hall interviews revealed that 7 ( 53.8% ) us ed regulated fixtures as predicted, 4 ( 30.8% ) utilized water fixtures less, and 2 (15.4 % ) noted that they used more. Participants who indicated that their consumption was about the same attributed the majority of their water consumption to the regular use of showers ( 5, 38.5%), the adherence to a daily routine ( 4, 30.8%), and use of sinks ( 2, 15.4%) and toilets ( 2, 15.4 %). Those tha t noted that their water consumption was more than anticipated credited this increase to more frequent uses of sinks ( 1, 7.7%) and toilets ( 1, 7.7%). Finally, those who believed their consumption was less than anticipated indicated that they had busy sched ules that prevented them from using fixtures in Frank Hall ( 2, 15.4%) and they took faster showers ( 2, 15.4%) than they expected. For example, one often but even when (FH6_Female). Appendix I illustrates the qualitative analysis of interview responses from Frank Hall. Energy Related Schedules Survey findings for energy related s chedules According to the 56 survey responses to Section 2: Energy Use approximately 26 ( 46.8% ) participants from Frank Hall indicated that they utilized the HVAC system

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149 throughout a 24 hour period. Additionally, participants indicated that they utilized the hot water heater during tw o peak periods. The first was between 8:00am 10:00am (2 hrs) where approximately 11 ( 19% ) of participants believed that they utilized the hot water system. The second peak period was between 7:00pm 11:00pm (4 hrs) where approximately 13 ( 24% ) participants estimated that they utilized the hot water heater. Finally, participants also indicated that they utilized the overhead lighting during two peak periods. The first was between 7:00am 12:00pm (5 hrs) where approximately 15 ( 26.2% ) participants notated that they utilized the building lighting system. The second peak period was between 1:00pm 1:00am (12 hrs) where approximately 25 ( 45% ) of participants estimated that they utilized the overhead lights. Table 4 5 has been provided to illustrate the percentage difference between the energy schedules reported by Frank Hall ANSI/ASHRAE/IESNA 90.1. Resource tracking findings for energy related s chedules Acco rding to the 13 resource tracking exercise s from Frank Hall approximately 10 ( 74.5% ) participants used the HVAC system throughout a 24 hour period. Additionally, tracking forms suggested that residents utilized the hot water heater during two peak periods. The first was between 7:00am 12:00pm (5 hrs) where approximately 3 ( 25.6% ) participants used hot water. The second peak period was between 8:00pm 10:00pm (2 hrs) where approximately 2 ( 12.8% ) participants utilized the hot water heater. Finally, interview participants also noted that they utilized the overhead lighting during two peak periods. The first was between 10:00am 2:00pm (4 hrs) where approximately 3 ( 25% ) participants overhead lighting system. The second peak period was bet ween 5:00pm 1:00am (8 hrs) where approximately 7

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150 ( 52.6% ) participants utilized the overhead lights. Table 4 6 has been provided to illustrate the percentage difference between the energy schedules reported by Frank tracking exercise partici pants and the schedules referenced in the ANSI/ASHRAE/IESNA 90.1 standard. Interview findings for energy related s chedules The analysis of the 13 interviews from Frank Hall indicated that 6 ( 46.2% ) used more energy than anticipated, 4 ( 30.8% ) used about w hat they expected they would, and 3 ( 23.1% ) consumed less. Residents who indicated that their energy consumption was more than anticipated attributed this increase to the regular use of overhead lights in their room ( 4, 30.8%), consistently leaving electronics plugged in ( 2, 15.4%), and the more frequent use of the HVAC ( 1, [contribute] now that the time has changed. We have to turn the lights on earlier. Also, the air conditioning [contributes the most] because its on when the building turns it on. that their consumption was about the same attributed the majority of their energy consumption to their regular use o f the HVAC ( 3, 23.1%) and overhead lights in their room ( 4, 30.8%). Finally, those who believed their consumption was less contributed this decrease to turning off the lights ( 1, 7.7%), having a busy schedule that caused them to be out of Frank Hall for lo ng periods of time ( 1, 7.7%), and using natural daylight ( 1, 7.7%). Appendix I helps to illustrate the qualitative analysis of interview responses from Frank Hall. Findings for Contextual I nstruments The following sections summarize the demographic profil e and building consumption data for all three case s. The demographic profile summary illustrate s the

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151 participants of this study and the population of each campus. T he building consumption summary illustrates the water and energy performance for each case . This information helps to reveal some of the similarities between each typical case and provides a context for the findings relevant to research question 1, its sub questions, and research question 2. Summary of Demographic Profiles According to the demog raphic profiles for each university, projected tuition and fee expenses for the 2013 2014 academic year were the highest for Emory Oxford students at a total of $52,652. North Carolina Central University and Appalachian State University could be considered more economical by comparison wi th tuition and fee costs totaling $22,420 and $20,582, respectively. Published statistics also indicated that both Emory Oxford and Appalachian State admitted approximately 2,819 students into the 2013 fall semester, of whi ch approximately 1,325 (47%) were male and 1,494 (53%) were female. By contrast, North Carolina Central admitted 4,472 students of which 1,476 (33%) were male and 2,996 (67%) were female. Here we see a difference in the ratio of males to females between No rth Carolina Central and the other two case locations. It was also noted that on average, both Emory Oxford and Appalachian State students had a GPA of up to 3.93, an SAT score of approximately 1563, and an ACT score of 27. Again this presented a contrast academic scores where students had an average GPA of 2.99, an SAT score of approximately 860, and an ACT score of 17. Additionally, of the students accepted into the fall semester most of the students from Emory Oxfor d identified their ethnicity as White/Caucasian (1,157, 42%) and Asian (882, 32%). Similarly, the majority of entering students from Appalachian State identified their ethnicity as White/C aucasian (2,479,

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152 86%), whereas the majority of students from North C arolina Central identified their ethnicity as African American (3,756, 84%). Finally, it was noted that Emory Oxford admitted more international students (496, 18%) in the 2013 fall semester than both North Carolina Central 95, 1%) an d Appalachian State (29, 1%). Of the 112 residents from East Village and the 149 residents from Chidley North who submitted a response to the web based survey, approximately 27% (29 and 43, respectively) were male and 73% (84 and 106, respectively) were female. By contrast, 36% (20) of the 56 respondents from Frank Hall were male and 64% (36) were female. Based on the collected survey responses, it was clear that the large majority of residents in each case were between the ages of 18 21. Neither East Village nor Frank Hall c ontained residents over the age of 22. However, 6 (4%) of the respondents from Chidley North were between the ages of 22 25. Responses also indicated that the majority of resi dents from all three case s had lived in their residence hall for 1 4 months. Simi lar to the demographic profiles for each university, most of the students from Emory (41, 46%), the majority of students from North Carolina Central ide ntified their ethnicity as African American (121, 81%), and the majority of residents 87%). Finally, it was noted that East Village housed more international students (8 , 7%) than both Chidley North (3, 2%) and Frank Hall (2, 5%). Summary of Building Consumption Overall, none of the buildings consumed water or energy as predicted by their LEED documents. In some cases, consumption rates where above the baseline case but m ost frequently building performance was documented approximately 48.8% below

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153 the baseline performance level. For example, based on water consumption meter readings, East Village, Chidley North, and Frank Hall were approximately 6.4%, 46.4%, and 52.3% below their baseline cases, respectively. Operating below a baseline case is generally a sign of building efficiency and suggests that buildings are conserving resources. However, further investigation into the consumption of each building revealed that water m eters were malfunctioning for most of the first two years of Chidley eight months of consumption in this building correctly reflected the actual usage of residents (T. Tran, personal communication, February 6 th , 2013). Based on the corrected figures, Chidley North is expected to significantly exceed the baseline case if residents continue to consume resources at the same rate. Th us, if the points awarded for Credit 3 Wat er Use Reduction were reevaluated for Chidley North, it would lose 2 points . While a similar investigation into the meter readings of East Village and Frank wou ld be nece ssary to verify if their current variations from the baseline are accurate representations of their performance. However, if these readings are accurate East Village would also lose 2 points and Frank Hall would earn 1 point for Credit 3 Water Use Reductio n . All of the residence halls would retain their LEED Gold rating despite the weighing of points. Similarly, energy consumption readings for each building also demonstrated high variations from the baseline case. East Village and Chidley North were found to be 54.5% and 42.2% below the baseline, while Frank Hall was found to be 164.8% above the baseline case. No evidence could be found to support or negate the reduction in

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154 electrical use for East Village. Thus, if these readings were accurate, East Village would earn 4 points for EA, Credit 1 Optimized Energy Performance but retain its LEED Gold certification . Conversely, the discovery of malfunctioning steam meters for Chidley North confirmed that its 42.2% reduction was deceptively low. According to the S tate Thagard, personal communication, November 20 th , 2013). Without the accurate steam meter readings, it is not possible to reevaluate the points for Chidley North, but it is unlikely that it would exceed its 28 % design case prediction. Finally, information January 31 st 2013). Furthermore, it was discovered that despite having photovoltaic cells installed on its roof, Frank Hall was the third largest consumer of energy on its campus. Thus, Frank Hall would lose 8 points for EA, Credit 1 Optimized Energy Performance but retain its LEED Gold certification. Findings for Research Question 1 .1 : Accuracy of LEED Default Settings for Water Data collected from the survey, the resource tracki ng exercise, and the interviews were averaged for all three cases and compare to the LEED default referenced standards for water and energy. The average of the three case s helped to provide a foundation for making generalizations about the l arger population of LEED certified residence halls. The following sections will present the summaries of instruments relevant to sub question 1.1 and 1.2, and will demonstrate the similarities between each typical case .

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155 Summary of Water Fixture Usage and Flow Durations Based on Survey Table 4 3 illustrates the comparison between the LEED default settings and the average water fixture usage of survey participants from the three cases. An average of the 317 documented usage rates and durations from all three surveys suggest that female occupants in residen ce halls use a water closet 3.2 times per day estimates the average usage derived from survey responses is 36% l ower for females and 44% lower for males. The average rates for all buildings also suggests that campus residents use a lavatory faucet 3.5 times per day for approximately 50.3 89.7 seconds per use, a showerhead 1.3 times per day for 480 680 or more second s, and that a kitchen sink was used less than one time per day for 1 29 seconds per use. Based on these survey findings, the average usage rate for lavatory faucets high as 49.5% above the default flow duration of 60 seconds. Also, the average usage 41.7% or more above the default flow duration of 480 seconds. Finally, the average daily usage between 51.7% 98.3% below the default flow duration of 60 seconds. Summary of Water Fixture Usage and Flow Durations Based on Resource Tracking Exercise Table 4 4 illustrates the comparison between the LEED default settings and the water fixture usage of residents who participated in the tracking exercise. An average of the usage rates and durations from the total 135 resources tracking forms suggest that female occupants in residence halls use a water closet 3.2 times per day and that males

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156 use a water closet 2.8 times per day. Notably, these average rates correspond exactly with those established by survey findings. Therefore, when compared to the USGBC p redictions the tracking form usage rates were also 36% lower for females and 44% lower for males. The average of all of the tracking forms also suggest that campus residents use lavatory faucets 2.9 times per day for an average of 155.1 seconds per use, a showerhead 1.3 times per day for 958.3 seconds per use, and a kitchen sink 0.3 times per day for 65.1 seconds per use. Based on these findings, the tracked usage rate for lavatory faucets currently the default flow duration of 60 seconds. Also, the average usage rate for showerheads is currently 30% above the Again it is noted that the tracked usage rate for showerhead s is identical to that which was defined by the survey participants. Finally, the average daily usage of kitchen sinks is currently 92.5% less than the USGBC projected and is 8.5% above the default flow duration of 60 seconds. Summary of Water Fixture Usa ge and Flow Durations Based on Interview Based on responses from a total of 45 interviews, it was clear that r esidents from all three universities were self aware of their consumption of water and energy. For example, after tracking their own use of water from regulated fixtures such as showers, sinks, and toilets, 11 ( 73.3% ) interview participants from East Village, 12 ( 70.6% participants from Chidley North, and 7 ( 53.8% ) participants from Frank Hall indicated that they used about as much as they anticipated. Most frequently, showers were identified as the location for the majority of water consumption to occur. For this reason, those residents who consumed less water than anticipated frequently noted that they

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157 took shorter showers then they originally perceived. Appendix I helps to illustrate the analysis of intervie w responses from the three case s . Findings for Research Question 1 .2 : Accuracy of LEED Default Energy Schedul es Summary of Energy Related Schedules Based on Survey An average of the energy related schedules for all three universities (317) would suggest that 47.2% of residence hall occupants utilized the HVAC throughout a 24 hour period. This is approximately a 53.5% increase from the ANSI/ASHRAE/IESNA fan schedule, which indicated that occupants would utilize the HVAC system during two peak periods ( ASHRAE, 2009 ) . Figures 4 7 have been provided to illustrate the survey findings that are relevant to the ANSI/ASH RAE/IESNA 90.1 fan schedule. Additionally, an average of survey responses would also imply that 20.3 % and 25.6% of campus residents would utilized the hot water heater during the peak hours of 7:00am 11:00am (4 hrs) and 8:00pm 1:00am (5 hrs) , respectively . This is approximately a 19.9% decrease from the ANSI/ASHRAE/IESNA hot water schedule, which indicated that occupants would utilize the hot water system during one peak period ( ASHRAE, 2009 ) . Figures 4 8 have been provided to illustrate the survey finding s that are relevant to the ANSI/ASHRAE/IESNA 90.1 hot water schedule. Finally, the average of survey responses also suggested that 25% and 40.5% of residents would utilized the overhead lighting during the peak hours of 7:00am 12:00pm (5 hrs) and 1:00pm 2 : 00am (13 hrs) , respectively . This is approximately a 49.3% increase from the ANSI/ASHRAE/IESNA lighting schedule , which indicated that occupants would utilize the overhead lighting system during one peak period ( ASHRAE, 2009 ) . Figures 4 9 have been provide d to illustrate the survey findings that are relevant to the ANSI/ASHRAE/IESNA 90.1 lighting schedule.

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158 Summary of Energy Related Schedules Based on Resource Tracking Exercise An average of the tracked energy findings for all three universities (135) would suggest that 77.5 % of occupants in campus residence halls utilize the HVAC system throughout a 24 hour period. This is appro ximately an 87.7 % increase from the ANSI/ASHRAE/IESNA 90.1 fan schedule . Figures 4 10 has been provided to graphically illustrate how the resource tracking exercise findings for each case compare to the LEED referenced fan schedule. Additionally, an average of tracking responses would also imply that 19.2 % and 11.6 % of campus residents utilize the hot water heater during the peak ho urs of 7:00am 11:00am (4 hrs) and 6 :00pm 1 2 :00am (6 hrs) , respectively. This is approximately a 97.1 % decrease from the ANSI/ASHRAE/IESNA 90.1 hot water schedule. Figures 4 11 has been provided to graphically illustrate how the resource tracking exercise f indings for hot water compare to the LEED referenced standard . Finally, the average of tracking responses also suggested that 20.9% and 43.9 % of residents would utilize the overhead lig hting during the peak hours of 9:00am 3:00pm (6hrs) and 4:00pm 1 :00am ( 9 hrs) , respecti vely. This is approximately a n 8.4 % increase from the ANSI/ASHRAE/IESNA 90.1 lighting schedule. Figures 4 12 ha s been provided to graphically illustrate how the resource tracking exercise findings for each case compare to the LEED reference d lighting schedule Summary of Energy Related Schedules Based on Interview With the exception of responses from Frank Hall where 6 ( 46.2% ) participants indicated that they used more energy than they originally anticipated, approximat ely 7 (43.6%) participants from East Village and Chidley North noted that their tracked usage of the HVAC and lighting systems was about what they expected. In general the use of HVAC units was identified as the major contributor towards energy consumption in East

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159 Villa ge and Chidley North, however residents from Frank Hall frequently noted that they utilized the overhead lights for longer periods of time than anticipated. Finally, residents that consumed less energy than anticipated in all three universities typically s tated that it was a result of realizing that they used th e overhead lights less often tha n expected. Appendix I helps to illustrate the qualitative analysis of interview resp onses from the three case s. Findings for Research Question 2: Relationship b etween Behavioral Constructs and Consumption of Resources Research question 2 sought to assess if a relationship exists between behavioral , Sections 3 8 of the survey were designed to evaluate the p revalence of constructs from the TPB and VBN models within each residence hall. C onstructs from each of these theories included attitudes towards conserving resources, subjective norms , perceived behavioral controls, behavioral intentions , valu es, beliefs and personal norms. The following sections present the findings from the conf irmatory factor analysis (CFA) and exp loratory factor analysis (EFA) . Survey Findings Fit b etween Current Behaviors and Theoretical Framework In order to ensure a sufficient sample size for a confirmatory factor analysis it is recommended that 5 20 cases be provided per parameter (Suhr, 2006) . Thus, the 317 survey responses from all three universities were analyzed together. To determine the significance of the analysis several fit functions, including a chi square, G FI, AGFI , and RMSEA test were utilized. The chi square , GFI and AGFI test s were first used to determine the diff erence between the observed behaviors and the theoretical framework

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160 of constructs utilized in this study (refer to Figure 2 3) . A chi square v alue closer to zero indicate s a good fit ( Suhr, 2006) , however survey responses resulted in a chi square value of 193.3. Similarly, a GFI and AGFI equal to or greater than 0.9 indicates good model fit ( Baumgartner & Hombur, 1996) , however survey responses resulted in a GFI and AGFI value of 0. 88 and 0.8 1 , respectively. Finally, a RMSEA test was utilized to analyze any potential discrepancy between the hypothesized model and the observed population . A RMSEA value of 0.06 or less indicates an acceptable model fit, however survey responses resulted in a RMSEA value of 0.1 (Hu & Bentler, 1999 ). Overall, fit function tests associated with the confirmatory factor analysis demonstrated that observed behav iors did not fit the theoretical framework model illustrated in Figure 2 3 . Therefore, an exploratory factory analysis was conducted to determine the underlying Table 4 7 has been provided to illustrate the fit function findings associated with the confirmatory factor analysis. Identifying Relevant Behavioral Constructs The goal of the exploratory factor analysis was to distinguish as much of the common variance as possible in the first factor. Subsequent f actors then intended to account for the remaining common variance until no common variance remained. In this way, the Based on the exploratory factor analysis of the 31 7 surve y responses , three factors with a cumulative variance of 1.0 5 were retained. Factor 1 res ulted in an eigenvalue of 5.07 and explained appro ximately 78.5% of the variance, Factor 2 findings demonstrated an eigenvalue of 1.10 and explained approximately 17.1 % of the variance and Factor 3 resulted in an eigenvalue of 0.59 and explained approximately 9.2% of the variance. The scree plot also confirms the extraction of three factors by demonstrating

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161 leveling off above the third factor. Table 4 8 and F igure 4 13 have been provided to illustrate the eigenvalue findings and the scree plot . Additionally, factor loadings help to identify the correlations between survey items. For example Factor 1 demonstrated a significant loading around the s ubjective norms construct ( friends, family, faculty, housing staff, and neighbors ) . Similarly, Factor 2 demonstrated a significant loading around the altruistic and biospheric indicators of the v alue construct. Finally, Factor 3 demonstrated a significant loading around the attitude, intention , and personal norm constructs. To improve the interpretation of factor loadings, findings were graphed and rotated . Rotating factors helped to confirm that constru cts loaded appropriately across all three factors. Fig ures 4 14, 4 15, and 4 16 have been provided to illustrate the rotation of factors about the reference axis. To further develop the initial theoretical framework for this study (illustrated in Figure 2 3) a path analysis was considered. However, resident s were only asked to define their level of environmentalism during interviews but were not asked to do so while completing the survey. This behavioral inference is used to develop a regression model while utilizing the SAS program and is necessary to compl ete a path analysis. For this reason , only the interview responses could have be en used to identify models that described resident ESBs. This significantly reduced the size of the sample group and did not provide the 10 cases for every parameter that is re commended for a path analysi s (Streiner, 2005). Thus, this was identified as a limitat ion and is included in the Limitations and Future Studies (pg. 230 ) section of this study. Summary of Behavioral Construct Findings Based on the confirmatory factor analysis and the use of several fit function tests it was clear that resident behaviors did not fit the initial theoretical framework model

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162 illustrated in Figure 2 3 . Therefore, an exploratory factory analysis was conducted to The exploratory factor analysis of survey responses indicated that three factors would be retained. Factor loadings and th e rotation of reference axes help ed to identify the cor relations between survey items: Factor 1 demonstrated a significant loading around the subjective norms construct ( friends, family, faculty, housing staff, and neighbors); Factor 2 demonstrated a signi ficant loading around the altruistic and biospheric ind icators of the value construct ; and Factor 3 demonstrated a significant loading around the attitude, intention, and personal norm constructs. Interview Findings As previously described, r esearch quest ion 2 sought to assess if a relationship Thus , Topic 1: LEED Knowledge , Topic 4: Environmental Values, Topic 5: Environment al Beliefs, Topic 6: Attitudes t owards Conservin g Water and Energy, Topic 7: Subjective and Personal Norms, Topic 8: Perceived Behavioral Controls, and Topic 9: Behavioral Intentions were designed to further understand how behavioral constructs influenced ESBs in residence halls . This section describes the findings from the interviews that are relevant to each of these topic area s . General Knowledge of LEED Certification In the Topic 1: LEED Knowledge section of the interview , participants were asked if they were aware that their building was LEED certified and if they could describe the role the USGBC or LEED played in the construction of their residence hall . Additionally , participants were asked if any green features were contributing to wards water and energy conservation in their residence hall . These questions helped to establish

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163 sustainable construction of their residence , the intent for the residence to perform efficiently , and their own knowledge of available sustainable features. Based on the qualitative analysis of 15 interviews from East Village , 11 ( 73.3% ) of the participants were cognizant that their building was LEED certified and 8 ( 53.3% ) were able to describe what the LEED system was with some detail. For example , ce hall had to meet certain requirements to be LEED, such as building materials that were sustainable, so that the building would be able to function more sustainably, like us (EV4 _Female). Conversely, 4 ( 26.7% ) of the East Village participants were unaware that their building was LEED certified , and 8 ( 53.3% ) indicated that they were unfamiliar with what the USGBC and/or LEED system represented . For example, when asked or if he could d escribe the role the USGBC and know what that is . I have never hear d _Male). With regards to the sustainable features in East Village, part icipants attri buted water conservation to existing low flow water fixtures ( 9, 60%) , dual flush toilets ( 8, 53.3%), the water bottle refill stations ( 6, 40%) , and signage that helped to describe green features , such as the refill station and dual flush toi lets ( 3, 20%) . A total of 2 ( 13.3% ) participants indicated that they were unfamiliar with any features that contributed towards water conservation in their residence hall. S imilarly, residents attributed energy conservation to the existing lighting sensors in their rooms and hallways ( 15, 100%), energy efficient appliances in the laundry room ( 2, 13.3%), and building insulation ( 2, 13.3%).

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164 By contrast only 1 ( 5.9% ) of the 17 Chidley North interview participants were aware that their building was LEED certi fied and none were able to describe what the LEED system was . For example, one student stated, I think I have heard of LEED. I ). Additionally, 16 ( 94.1% ) participants were unfamiliar with their building s LEED certification and 17 ( 100% ) indicated that they were also unfamiliar with what the USGBC and/or LEED system represented . Therefore when asked about the ir the role the USGBC and LEED played in the construction of their residence hall the majority of students made I have no idea. No one has mentioned that to me and I ale). In Chidley North, residents attributed water conservation to existing dual flush toilets ( 10, 58.8%), low flow water fixtures ( 8, 47.1%), and signage that helped to describe green features, such as the dual flush toilets ( 3, 17.6%). A total of 3 ( 17.6% ) participants indicated that they were unfamiliar with any features that contributed towards water conservation in their residence hall. Similarly, residents attributed energy conservation to the exist ing lighting sen sors in their hallways ( 16, 94.1%) and the promotion of green living by housing staff ( 1, 5.9%). One participant (5.9%) indicated that they were unfamiliar with any features that contributed towards energy conservation in their residence ha ll. Finally, 7 ( 53.8 % ) of the 13 Frank hall interview participants were aware that their building was LEED certified but only 1 ( 7.7% ) was able to describe what the LEED system was in some detail. For example, the participant indicated, know that we are

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165 they said FH12 _Male). Alternately , 6 ( 46.2% ) of the participants were unfamiliar with 9 ( 69.2 % ) indicated that they were also unfamilia r with the USGBC and/or LEED system . As a result, when asked about the role the USGBC and LEED played in the construction of their residence hall or if they had any participants would frequently state, estly not sure on that one. I have not heard of either one of those and t know I was in a LEED certified With regards to the green features in Frank Hal, participants attributed water conservation to the dual flush toilets ( 9 , 69.2%), existing low flow water fixtures ( 6, 46.2%), signage that helped to describe green features, such as the dual flush toilets ( 3, 23.1%), the water bott le refill stations ( 5, 15.4%), and user awareness of consumption ( 3, 7.7%). A total of 5 ( 15.4 % ) participants indicated that they were unfamiliar with any features that contributed towards water conservation with in their residence hall. Similarly, residents attributed energy conservation to the existing lighting sensors in their hallways ( 13, 100%) a nd the solar panels on the roof of their building ( 6, 46.2 %). Behavioral Constructs In general, the Topic 4 : Value s , Topic 5: Beliefs, Topic 6: Attitudes, Topic 7: Subjective/Personal Norm s , Topic 8: Perceived Behavioral Controls, and To pic 9: Behavioral Intentions section s of the interview required participant s to reflect on how their own behaviors aligned with each theoretical construct while utilizing water and

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166 energy in their residence hall . P articipants from each sample site were asked to explain thei r rationale for exhibited sustainable or unsustainable behaviors in their residence hall. Finally, students were asked to reflect on how their ESBs would be different , if at all, when they were outside of the context of their residence hall. These question s helped to better understand the factors that influenced behaviors and further contextualize d the findings from the survey and resource tracking exercise. Topic 4: V alues In the Topic 4: Values section of the interview , participants were read the following question : If you bought an energy efficient car instea d of a standard gas car would it be because it was cheaper on fuel, because it has lower emissions and is healthier for people, or because it produces less CO2 which protects the environm ent? Each option in this scenario represented either an egoistic, altruistic , or biospheric value orientation. Participants were then asked to reflect on why the ir selected value orientation was important to them and how, if at all, this orientation influenced their consumption of resources in their residence hall. Based on the 15 i nterviews from the East Village, 11 ( 73.3 % ) participants identified with an egoistic value orientation , 5 ( 33.3% ) identified with a biospheric value orientation, and 1 ( 6. 7% ) identified with an altruistic value orientation. Those who were motivated by egoistic values indicated that this orientation was important because they had a desire to save money ( 10, 66.7%), expressed having a tight budget ( 3, 20%) and stated that whi le saving money was their primary driver, an energy efficient car also benefited the environment ( 2, 13.3%) and safeguarded future generations from dangerous car emissions ( 1, 6.7%) . Those who were motivated by a biospheric value orientation noted that the y were driven to preserve the health and safety of the environment ( 4, 26.7%) or were concerned for the

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167 health, safety, and welfare of future generations ( 1, 6.7% ) . The participant who was motivated by a n altruistic value orientation indicated that they di d so out of concern for the health, safety, and welfare of future generations ( 1, 6.7%). Finally, while 7 ( 46.7% ) of interviewed residents indicated that their consumption of water and energy was motivated by their value orientation, 7 ( 46.7% ) indicated th at their consumption was not. Of the later , 6 ( 40% ) indicated that the disconnect between their values and their consumption of resources was a product of their utility costs being set regardless of their use. For example, students fr om this hall have never connected those myself. Thinking about it now, I can see how they could t ter how m he two (EV15_Male). Of the 17 participants from Chidley North, 15 ( 88.2% ) identified with an egoistic value orientation and 3 ( 17.6% ) identified with a biospheric value orientation. None of the interviewed residents indicated that they were motivated by altruistic values. Those who were motivated by egoistic values indicated that this orientation was important because they had a desire to save money ( 13, 76.5%) and exp ressed having a tight budget ( 7, 41.2%). Those who were motivated by a biospheric value orientation noted that they were driven to preserve the health and safety of the environment ( 2, 11.8 %) or were concerned for t he health, safety, and we lfare of future generations ( 1, 5.9 %). Additionally, while 2 ( 11.8% ) of interviewed residents indicated that their consumption of water and energy was motiva ted by their value orientation 12 ( 70.6% ) indicated that

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168 their consumption was not; primarily as a result of their utility costs being set regardless of their use ( 9, 52.9%). For example, students from Chidley North would often say, already in our housing so I already paid ersonally paying for it. I mean it would probably be different if I lived in an apartment and had to pay for it. But as CN9_Fem ale). Lastly, the 13 in terviews from Frank Hall revealed that 8 ( 61.5% ) of the participants identified with an egoistic value orientation , 6 ( 46.2% ) identified with a biospheric value orientation, and 1 ( 7.7% ) identified with an altruistic value orientation. Those who were motivated by egoistic values indicated that this orientation was important because they had a desire to save money ( 5, 38.5%), exp ressed having a tight budget ( 2, 15.4%), and stated that while saving money was a primary driver, they recognized that an energy efficient car also benefited the environment ( 1, 7.7%) and safeguarded future generations from dangerous car emissions ( 1, 7.7% ). Those who were motivated by a biospheric value orientation noted that they were driven to preserve the health and safety of the environment ( 4, 30.8 %) or were concerned for the health, safety, and welfare of future generations (1, 7 .7%). T he participant who was motivated by an altruistic value orientation also indicated that they did so out of concern for the health, safety, and welfare of future generations (1, 7 .7%). Additionally , unlike the other two residence hall s, 8 ( 61.5 % ) of the interviewed resid ents indicated that their consumption of water and energy was motivated by their value orientation. Conversely, 5 ( 38.5% ) indicated that their consumption was not, primarily as a result of their utility

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169 costs being set regardless of their use ( 4, 30.8 %). W hen asked how their consumption was influenced by their value orientation, s tudents from Frank Hall would state , just try to do the best that I can and save as much water and energy as I can. not about the whole cheapness thing, its just abou though I am not directly paying for the water and energy, I know that somebody is Topic 5: Beliefs In the Topic 5: Beliefs section of the interview participants were asked to define themselves on a 5 point scale from Environmental. They were then asked to reflect on why the selected environmental belief was important to them . Residents were also asked if the y believed any consequences existed in their re sidence hall for not behaving sustainably and if they felt any responsibility for the negative impacts unsustainable behaviors might have on their place of residence. The 15 i nterviews from East Village reveled that 10 (66.7%) participants defined themselves ro E 3 ( 20% ) 2 ( 13.3% ) were y Pro a E i ndicated that they were generally conscious of their use of resources and were interested in environmental topics and/or legisl ation (8, 53.3%) . However, 3 ( 20%) of the residents in this group also noted that they did not have stronger environmental perspective s because sustainable behaviors, like shorter showers or turning off lights, were considered inconvenient ( 3, 20%) or they required a regular reminder t o be have sustainably ( 1, 6.7 %). Similarly, t hose with a did not have stronger environmental

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170 perspectives because sustainable behaviors were considered inconvenient ( 3, 20%) . T more sustainable because they did not believe it was necessary (2, 13.3%) . For example, i t was often stated that they did not see evidence of or believe that the environment was truly impacted by human behaviors. For example, one such resident stated , we are changing what would be happen ing anyway With regards to the AC and AR indicators of the belief construct, 12 ( 80.0% ) residents did no t perceive a consequence to behaving unsustainably in their dormitory, 1 ( 6.7% ) did , and 3 ( 20% ) believed that there could be a consequence but had never witnessed one first hand . Therefore, when asked about the consequences of unsustainable behaviors in East Village students would state , I have never heard of anyone getting into trouble for that. B Fi nally , 6 ( 40% ) of the interview participants indicated that they would not feel responsible if the consumption of resources in their building was higher than anticipated, 5 ( 33.3% ) said that they would, and 4 ( 26.7% ) indicated that while they would not feel directly re sponsible they could at least recognize how their behavior contributed to the buildings overall consumption. The qualitative analysis of 17 Chidley North interviews revealed that 12 ( 70.6% ) of the participants defined themselves as 4 ( 23.5% ) we re -

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171 1 ( 5.9% ) was Neutral did not hav e stronger environmental perspectives because sustainable behaviors were considered inconvenient ( 5, 29.4%), sustainable practices were not considered a priority ( 4, 23.5%), residents required a regular reminder to behave sustainably ( 3, 17.6%), and residents want ed further evidence to confirm that humans were impacting the environment ( 1, 5.9%). For example, residents often conserve energy or water but at the same time I try not to waste it. It j ust depends on what is convenient with my lifestyle the same times it people down and tells them to turn off the water or lights. I Also , 2 ( 11.8% ) of Somewhat Pro environmental perspective indicated that they were generally conscious of their consumption and were interested in environmental topics and/or le gislation. However, 1 ( 5.9% ) of these participants noted that they did not have stronger environmental perspectives because sustainable behaviors were considered incon venient . Finally, th e participant indicat ed that they did not have stronger environmental p erspectives because they did not see evidence to confirm that human s impact ed the environment ( 1, 5.9 %), sustainable behaviors were considered inconvenient ( 1, 5.9%) and they required a regular reminder to behave sustainably ( 1, 5.9%). With regards to the AC and AR indica tors of the belief construct, 13 ( 76.5 % ) participants did no t perceive a consequence to behaving un sustainably in

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172 their dormitory and 4 ( 23.5 % ) believed that there could be a consequence but had never witnessed one first hand. Additionally, 7 ( 41.2 % ) of the interview participants indicated that they would not feel responsible if the consumption of resources at Chidley North was higher than antici pated, 4 ( 23.5% ) said that they would, and 6 ( 35.3% ) indicated that while they would not feel directly responsible they could recognize how their behavior would contribute to overall consumption. The 13 i nterviews from Frank Hall demonstrated that 7 ( 53.8% ) of the e 5 ( 38.5% ) were Pro 1 ( 7.7% ) was Those with E they were generally conscious of their use and were interested in environmental topics and/or legislation ( 7, 53.8%). However, 2 ( 15.4% ) of these residents noted that they did not have s tronger environmental perspectives because sustainable behaviors were considered inconvenient. conserving and I believe that important to protect the environment. But it is not something Similarly, those with a Very Pro e nvironmental were generally conscious of their consumption of resources and had an interest in environmental topics and/or legisl ation (5, 38.5 %). Finally, the participants with Neutral indicated that they did not have stronger environmental perspectives because sustainable behaviors w ere considered inconvenient ( 1, 7.7%). With regards to the AC and AR indicato rs of the belief construct, 9 ( 69.2 % ) of the residents did no t perceive a

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173 consequence to behaving unsustainably in their dormitory , 2 ( 15.4% ) did, and 2 ( 15.4 % ) believed that there could be a consequence but had never witnessed one first hand. Additionally, 9 ( 69.2 % ) of interview participants indicated that they would feel responsible if the consumption of resources in their building was higher than anticipated, 3 ( 23. 1 % ) said that they would not, and 1 ( 7.7 % ) indicated that they could understand how their behav ior would contribute to overall consumption. Topic 6: Attitudes In the Topic 6: Attitudes section of the interview participants were asked to describe on a s c ale from 1 10, where 1 was not important and 10 was very important, how important it was to save w ater and energy in their residence hall. They were then asked to reflect on the level of importance they chose for both water and energy. Finall y residents were also asked to suggest a method for effectively reduce water and energy consumption in their res idence hall. On a scale from 1 10, 11 ( 73.3% ) of the 15 East Village interview participants rated the importance of conserving water between 5 6.9, 2 ( 13.3% ) were between 3 4.9, 1 ( 6.7% ) was between 7 8.9 , and 1 (6.7%) was between 9 10. None o f the participants rated t he importance of water conservation between 1 2.9. Additionally , 8 ( 53.3% ) of the participants indicated that the importance of conserving energy was between 5 6. 9, 4 ( 26.7% ) were between 3 4.9, 2 ( 13.3% ) were between 7 8.9, and 1 ( 6.7% ) was between 9 10. Similar to the attitudes for water, none of the participants stated that the importance of en ergy conservation was between 1 2.9 . Most frequently, residents with scores below a 5 indicated that the conservation of resources was no t more important because i t was not a daily consideration; generally because sustainable behaviors were considered inconvenient ( 10, 66.7%) , they did not believe that they used many resources , so saving more was believed to be unnecessary

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174 ( 2, 13.3%), or th ey were not actively aware of their own consumption or of methods to reduce their own consumption further ( 2, 13.3%). For example, one East Village a 30 minute sh , much energy. I keep the lights off and even when I forget they turn off by themselves. When asked how to effectively reduce the consumption of resources in their residence hall, 11 ( 73.3% ) of the participants suggested that additional technologies , such as motion sensored faucets, could be installed. Finally, 9 ( 60 %) suggested improving resident awareness so that occupan ts could be better informed of conservation opportunities and the importance of sustainable behaviors. On a scale from 1 10, 11 ( 64.7% ) of the 17 Chidley North interviewees rated the importance of conserving water between 5 6.9, 3 (17.6 % ) were between 1 2 .9, 1 ( 5.9% ) was between 3 4.9, 1 (5.9%) was between 7 8.9 , and 1 (5.9%) was between 9 10. Additionally, 11 ( 64.7% ) of the participants indicated that the importance of conserving energy was between 5 6.9, 3 ( 17.6% ) were between 3 4.9, 2 ( 11.8% ) were betwe en 7 8.9, and 1 (5 .9% ) was between 9 10. None of the participants rated the importance of energy conservation between 1 2.9. Most frequently, residents with scores below a 5 indicated that conservation of resources was not more important because they did n ot believe that they used many resources , so saving more was believed to be unnecessary ( 4, 23.5 %), they were discouraged from conserving more because of a lack of community support ( 3, 17.6%), and there was not a financial benefit or personal impact for c onserving more ( 3, 17.6%). For example, one resident indicated that saving water

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175 When asked how to effectively reduce the consumption of resources in their residence hall, 10 (5 8.8 % ) participants suggested that additional technologies, such as motion s ensored faucets and occupancy sensored lights in their bed room s , could be installed. Also 5 ( 29.4 % ) participants suggested improving resident awareness so that occupants could be better informed of conservation opportunities and the importance of sustainable behaviors. Finally, 4 ( 23.5% ) believed that charging for utilities would help to reduce the consumption of resources. On a scale from 1 10, 6 ( 46.2% ) of the 13 Frank Hall interviewees rated the importance of conserving water between 7 8.9, 3 ( 23.1% ) were between 5 6.9, 2 (15.4 % ) were between 9 10, 1 ( 7.7% ) was between 1 2.9 , and 1 (7.7%) was between 3 4.9. Additionally, 9 ( 69.2 % ) of the participants indicated that the importance of conserving energy was between 7 8.9, 2 ( 15.4 % ) were between 9 10 , 1 (7.7%) was between 5 6.9, and 1 (7.7 %) was between 4 5.9 . None of the participants rated the importance of energy conservation between 1 2.9 and 3 4.9 . Most frequently, residents with scores below a 5 indicated that conservation of resources was not more important because they did not believ e that they used many resources , so saving more was believed to be unnecessary ( 2, 15.4%). Unlike East Village and Chidley North, in this particular building residents most frequently indicated that conservation was important because it contributed to envi ronmental health ( 10, 76.9%) , resources were an expensive commodity to waste ( 4, 30.8%), and it was believed to be considerate to maintain a supply of resources for others ( 3, 23.1 % ). When asked how to continue to

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176 reduce the consumption of resources in their residence hall, 11 ( 84.6 % ) suggested improving resident awareness so that occupants could be better informe d of conservation opportunities. For example, participants people n eed to be informed of what they use daily and how much there is actually available. Also, I think that there should be a limit for how much everyone should use. main thing Finally , 6 ( 46.2% ) of the participants suggested that additional technologies, such as motion sensored faucets and occupancy se nsored lights in their bedrooms, could be installed. Topic 7:Subjective and Personal Norms In the Topic 7: Subjective and Personal Norms section of the interview participants were asked to identify referent groups who most influenced their adoption of sustainable behaviors. These groups helped to define the subjective norms influencing the residents in each dormitory. Additionally, interview participants where asked to describe any feelings of obligations t hey had for behaving sustainably in their re sidence hall and why they found th ese behaviors to be important. In this way, the presence of personal norms in each residence hall could be better understood. Finally, students were asked to describe if their ESBs changed at all when they were not in thei r residence hall. This helped to understand how resident behaviors were influenced by subjective and personal norms while in or out of their residence hall. T he qualitative analysis of 15 East Village interview s indicated that environmental b ehaviors were most influenced by family members ( 7, 46.7%), friends ( 7, 46.7%), housing staff ( 2, 13.3%), college faculty ( 2, 13.3%), and environmental experts ( 2,

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177 13.3%). However, d espite the clear influence from a wide range of referent groups, w hen asked to describe their personal sense of obligation to conserve water and energy in their residence hall , 8 ( 53.3% ) indicted that they only felt somewhat o bligated, 4 ( 26.7% ) felt very obligated, and 3 ( 20% ) did not feel obligated at all . Of those that we re somewhat obligated 5 ( 33.3% ) indicated that they had learned to do so at home. For not leav e water running so those are things that I learned to do at home. So I know that here because Finally, 10 ( 66.7 % ) of the East Village interview pa rticipants indicated that their ESBs remain ed the same regardles s of being in the residence hall or at their home; while 4 ( 26.7% ) indicated that their behaviors were better when they returned home. The 17 Chidley North interviews revealed that participant s environmental behaviors were most influenced by family membe rs ( 8, 47.1%), environmental experts ( 6, 35.3%), and housing staff ( 4, 23.5%). W hen asked to describe their personal sense of obligation to conserve water and energy in their residence hall , 8 ( 47.1 % ) indic a ted that they only felt somewhat obligated, 8 ( 47.1 % ) did not feel obligated at all, and only one ( 5.9% ) felt very obligated. Of those that were somewhat obligated 7 ( 41.2% ) indicated that they had learned to do so at home but that conservation was generally driven by a concern for costs as oppose to a concern for the environment. For example, It was never really something that came up unless the bills tant to me, it a

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178 young age _Female). Finally, 11 ( 64.7% ) of the Chidley North interview participants indicated that they were more cognizant of their ESBs at their homes then in their residence hall, while 6 ( 35.3% ) st ated that their behaviors remained the same. Finally the 13 Frank Hall interv iews indicated that participant s environmental behaviors were most influenced by family members ( 4, 30.8%), environmental experts ( 4, 30.8%), housing staff ( 3, 23.1%), college fa culty ( 3, 23.1%), and friends ( 3, 23.1%). When asked to describe their personal sense of obligation to conserve water and energy while in Frank Hall , 8 ( 61.5 % ) indicat ed that they felt very obligated, 4 ( 30.8% ) were somewhat obligated, and 1 ( 7.7% ) was not obligated at all. Of those that were very obligated 7 ( 53.8% ) indicated that conserving was a habit learned from home and 4 ( 30.8 % ) indicated that they were sincerely driven by a concern for the environment. For My p arent are VERY environmentally friendly. When I was a kid, if my shower ran over a couple of minutes I would hear about it. But at the footsteps or go my own way. I have ch osen the road where I want to conserve the environment because it is important to me (FH5_M ale). Finally, 7 ( 53.8% ) of the Frank Hall interview participants indicated that their ESBs remain ed the same regardless of being in the residence hall or at their home; while 6 ( 46.2 % ) indicated that their behaviors were better when they returned home. Topic 8: Perceived Behavioral Controls In the Topic 8: Perceived Behavioral Controls section of the interview participants were asked to describe any constraining or facilitating conditions that impacted the conservation of resources in their residence halls . The qualitative analysis of 15 East Village interviews revea led that 14 ( 93.3% ) of the participants believed that the existing

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179 technologies in their building, suc h as the sensored lights and dual flush toilets, helped to facilitate their reduction of water and energy consumption. Conversely, 7 ( 46.7% ) of the participants were reluctant to conserve water or energy because sustainable practices, such as the use of lo w flow faucets or unplugging electronics, took too much time . makes me take longer showers because it takes forever to rinse off Additionally, 7 ( 46.7% ) indicated that they did not feel educated on the rationale for behaving su sta inably in the residence hall, 6 ( 40% ) did not believe they were educated on the features that e xisted in their re sidence hall , and 4 ( 26.7% ) also indic a ted that the absence of a cost incentive made it difficult to consider sustainable behaviors a priority . Of t hose who felt that education was a constraini ng condition, 6 ( 4 0% ) indicated that they wou ld be willing to participate in a sustainability education program, however only 3 ( 20% ) believed that they would apply what they learned. These residents also projected that 20 35% of East Village population would agree to participate in such a pr ogram. Fina lly, of those who believed that set costs were a constraining condition 2 (13.3 % ) indicated that they would not support a policy where students were cha rged for their own utilities and 2 (13.3 % ) indicated that they would. Similar to East Village , the 17 Chidley North interviews revealed that the large majority of participants ( 11, 64.7%) believed that the existing technologies in their building, such as the low flow faucets and dual flush toilets, helped to facilitate their reduction of water and energy consumption. Additionally, 12 ( 70.6 % ) of the participants indic a ted that the absence of a cost incentive made it difficult to consider sustainable

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180 behaviors a priority. For example, not costing me anything. I know how in my Additionally, 8 ( 47.1 % ) indicated that they did not believe they were educated on the features that existed in their residence, 5 ( 29.4% ) were reluctant to conserve water or energy because sustainable practices took too much time, 4 ( 23.5% ) did not feel educated on the ra tionale for behaving sustainably in the residence hall, and 4 ( 23.5% ) stated that the lack of daily prompts made it difficult t o remember to be sustainable. Of those who believed that set costs we re a constraining condition 7 (41.2 % ) indicated that they would not support a policy where students were cha rg ed for their own utilities and 5 (29.4%) i ndicated that they would. Fina lly, of those who felt that education was a constraining condition, 4 (23.5 % ) indicated that they would be willing to participate in a sustainability ed ucation program, however only 3 (17.6 % ) believed that they would apply what they learned. These residents als o projected that 5 20 % of Chidley North s total population would agree to participate in such a program. Similar to the other two sites, the large majority of the 13 Frank Hall participants ( 9, 69.2%) believed that the existing technologies in their build ing, such as the solar panels and dual flush toilets, helped to facilitate their reduction of water and energy consumption. Interviews also revealed that the absence of a cost incentive made it difficult for 6 ( 46.2% ) of participants to consider sustainabl e behaviors a priority. For example, several residents of Frank Hall stated,

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181 Additionally, interviewees indicated that the lack of cooperation by other residents ( 5, 38.5%) and lack of education on existing features ( 3, 23.1 % ) made it difficult to conserve resources in their residence . Of those who believed that set costs were a constraining condition 4 (30.8 %) indicated that they would support a policy where students were charged for their own utilities, 1 ( 7.7 % ) indicated t hat they would not , and 1 ( 7.7 % ) would need additional information about the policy before deciding whether to support it or not. Additionally, of those who felt that education was a constraining condition, 3 ( 23.1% ) indicated that they would be willing to participate in a sustainability ed ucation program, however only 1 ( 7.7% ) believed that they would apply what they learned. These re sidents also projected that over 50 % of total population would agree to participate in such a program. Topic 9 : Behavioral Intentions Finally, in the Topic 9: Behavioral Intentions section of the interview participants were asked to describe their short term and long term intentions of conserving water and energy. Participants were also asked to describe how they would go about reaching these goals if intentions were set to reduce future consumption. In East Village 6 ( 40% ) of the 15 interview participants stated that it was unlikely that they would reduce their consumption of reso urces over their next semester, 3 ( 20% ) indicated that it was very likely, 3 ( 20% ) indicated that it was somewhat unlikely, and 2 ( 13.3% ) believed that it was somewhat likely. Those who believed that they would reduce their level of consumption by some degree generally felt that they would do so by taking shorter showers ( 3, 20%) and being more self aware ( 3, 20%). When these same residents

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182 were asked if they intended to reduce their consumption of resources after moving o ut of East Village and purchasing their own home , 11 ( 73.3% ) stated that their final behaviors would be a direct result of a monetary incentive. For example, residents freq uently stated money coming out of my pocket (EV14_Male) and (EV7_Male). According to the analysis of the 17 Chidley North interviews 9 ( 52.9% ) of interview participants stated that it was unlikely that they would reduce their consumption of resources over their next semester, 5 ( 29.4% ) indicated that it was somewhat likely, 2 ( 11.8% ) indicated that it was very likely, and 1 ( 5.9% ) believed that it was somewhat unlikely. Those who believed that they would reduce their level of consumption by some degree generally felt that they would do so b y taking shorter showers ( 7, 41.2%), b eing more self aware ( 2, 11.8 %) , and turning off the lights and faucets more often ( 2, 11.8%) . When these same residents were asked if they intended to reduce their consumption of resources after moving out of Chidley North and purchasing their own home, a n average of 11 ( 64.7 % ) sta ted that their behavioral intentions would b e direct ly connected to a monetary incentive. For example, residents I would probably be more strict on myself. For one, now I would be paying for it. So I would try to adopt s ome better habits. So seeing the bills and really being affected by it would make a big difference (CN3_Fem ale) and Yes. I think that I would be using less of both water and energy. It would be because of the cost and wanting to spend ale).

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183 In Frank Hall 6 ( 46.2% ) of the 13 interview participants stated that it was very likely that they would reduce their consumption of resources over their next semester, 4 ( 30.8% ) indicated that it was unlikely, 3 ( 23.1% ) indicated that it was somewhat likely, and none of the interview participants indicated that it was somewhat unlikely. Those who believed that they would reduce their level of consumption by some degree generally felt that they would do so by taking short er showers ( 5, 38.5%) and turning off the lights more often when leaving their rooms ( 5, 38.5 %). When these same residents were asked if they intended to reduce their consumption of resources after moving out of Frank Hall and purchasing th eir own home, 5 ( 38.5 % ) stated that their intentions would change because of the direct connection to a monetary incentive. For example, such I would be more conscious of things because that would be a bill that I would have to take care of. So it would really be more monetarily driven (FH1_Female) and I think they would. Once you throw in that cost factor and once my own income determines where I am going in life, then there is that incentive. I would probably be very environmentally conscious because the use of water and energy all add up and I would want to spend as little as possible FH8_Fem ale).

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184 Table 4 1. Demographic profiles of u niversities Gender GPA Test Scores Ethnicity International Student Emory Oxford Admitted Fall 2013=2755 M F 1240 ( 45% ) 1515 ( 55% ) 3.52 3.90 SAT ACT 1860 2120 27 32 Wh./ Caucasian Afr./ American Hispanic Asian Nat ./ American Pacific Islander Other Did not Identify 1157 331 220 882 27 0 0 138 (42%) (12%) (8%) (32%) (1%) (0%) (0%) (5%) Yes No 496 ( 18% ) 2259 ( 82% ) North Carolina Central Admitted Fall 2013= 4472 M F 1476 ( 33% ) 2996 ( 67% ) 2.99 SAT ACT 790 930 15 19 Wh./ Caucasian Afr./ American Hispanic Asian Nat ./ American Pacific Islander Other Did not Identify 224 3756 89 45 45 45 89 179 ( 5% ) ( 84% ) ( 2% ) ( 1% ) ( 1% ) ( 1% ) ( 2% ) ( 4% ) Yes No 45 ( 1% ) 4429 ( 99% ) Appalachian State Admitted Fall 2013= 2883 M F 1384 ( 48% ) 1499 ( 52% ) 3.96 SAT ACT 1129 1141 24.1 26.1 Wh./ Caucasian Afr./ American Hispanic Asian Nat ./ American Pacific Islander Other Did not Identify 2479 115 115 58 29 29 0 58 ( 86% ) ( 4% ) ( 4% ) ( 2% ) ( 1% ) ( 1% ) ( 0% ) ( 2% ) Yes No 29 ( 1% ) 2854 ( 99% ) Male (M); Female (F); S cholastic Aptitude Test (S AT ); American College Testing (ACT) ; White (Wh); African (Afr); Native (Nat)

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185 Table 4 2 . Demographic p rofiles of survey p articipants Gender Age Time in resident (months) Ethnicity International Student East Village Survey Participants=112 M F 29 ( 26% ) 84 ( 74% ) 18 19 20 21 22 23 24 25 26+ 104 ( 93% ) 8 ( 7% ) 0 ( 0% ) 0 ( 0% ) 0 ( 0% ) 1 1 4 5 8 9 12 +12 5 ( 4% ) 90 ( 80% ) 1 ( 1% ) 1 ( 1% ) 15 ( 13% ) Wh./ Caucasian Afr./ American Hispanic Asian Nat ./ American Pacific Islander Other Did not Identify 38 16 10 46 0 0 2 0 ( 34% ) ( 14% ) ( 9% ) ( 41% ) ( 0% ) ( 0% ) (2 % ) ( 0% ) Yes No 8 ( 7% ) 104 ( 93% ) Chidley North Survey Participants=149 M F 43 ( 29% ) 106 ( 71% ) 18 19 20 21 22 23 24 25 26+ 104 ( 70% ) 39 ( 26% ) 4 ( 3% ) 2 ( 1% ) 0 ( 0% ) 1 1 4 5 8 9 12 +12 6 ( 4% ) 122 ( 82% ) 8 ( 5% ) 0 ( 0% ) 13 ( 9% ) Wh./ Caucasian Afr./ American Hispanic Asian Nat ./ American Pacific Islander Other Did not Identify 16 121 2 3 3 0 4 0 ( 11% ) ( 81% ) ( 1% ) ( 2% ) ( 2% ) ( 0% ) ( 3% ) ( 0% ) Yes No 3 ( 2% ) 146 ( 98% ) Frank Hall Survey Participants= 56 M F 20 ( 36% ) 36 ( 64% ) 18 19 20 21 22 23 24 25 26+ 49 ( 87% ) 7 ( 13% ) 0 ( 0% ) 0 ( 0% ) 0 ( 0% ) 1 1 4 5 8 9 12 +12 0 ( 0% ) 50 (89 % ) 0 ( 0% ) 0 ( 0% ) 6 (11 % ) Wh./ Caucasian Afr./ American Hispanic Asian Nat ./ American Pacific Islander Other Did not Identify 49 3 0 3 0 0 0 1 ( 87% ) ( 5% ) ( 0% ) ( 5% ) (0 % ) ( 0% ) ( 0% ) ( 3% ) Yes No 3 ( 5% ) 53 ( 95% ) Male (M); Female (F) ; White (Wh); African (Afr); Native (Nat)

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186 Table 4 3. Survey p articipant water fixture usage and flow d urations vs LEED default s ettings Fixture Type East Village ( Use/Day) Chidley North ( Use/Day) Frank Hall ( Use/Day) Average ( Use/Day) LEED Default Setting ( Use/Day) Average vs. LEED Water closet, female 3 3 3.5 3.2 5 36% Water closet, male 2 3.5 3 2.8 5 44% Lavatory faucet 3 4 3.5 3.5 5 30% Showerhead 1 2 1 1.3 1 +30% Kitchen Sink 0 0 0 0 4 100% Fixture Type East Village ( sec) Chidley North ( sec) Frank Hall ( sec) Average (sec) LEED Default Setting ( sec) Average vs. LEED Lavatory Faucet 30 60 120 180 1 29 50.3 89.7 60 16.2% to +49.5% Showerhead 720+ 720+ 480 600 480 680+ 480 0% to +41.7% Kitchen sink 1 29 1 29 1 29 1 29 60 98.3% to 51.7 Seconds (sec)

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187 Table 4 4 . Resource t racking p water fixture usage and flow d urations vs LEED default s ettings Fixture Type East Village ( Use/Day) Chidley North ( Use/Day) Frank Hall ( Use/Day) Average ( Use/Day) LEED Default Setting ( Use/Day) Average vs. LEED Water closet, female 2.9 3.4 3.3 3.2 5 36% Water closet, male 2.7 2.8 3 2.8 5 44% Lavatory faucet 2.8 2.8 3.1 2.9 5 42% Showerhead 1.4 1.2 1.2 1.3 1 +30% Kitchen Sink 0.2 0.1 0.5 0 .3 4 92.5% Fixture Type East Village ( sec) Chidley North ( sec) Frank Hall ( sec) Average (sec) LEED Default Setting ( sec) Average vs. LEED Lavatory Faucet 145.3 190.6 129.3 155.1 60 +158.5% Showerhead 934.0 1085.3 855.5 958.3 480 +99.6% Kitchen sink 42.7 34.1 118.5 65.1 60 +8.5% Seconds (sec)

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188 Table 4 5 . Survey nergy usage and peak p eriods vs ANSI/ASHRAE/IESNA 90.1 d efault energy s chedule Usage East Village ( % Use) Chidley North ( % Use) Frank Hall ( % Use) Average ( % Use) ASHRAE Setting ( % Use) Average vs. ASHRAE Fan 60 ( 54% ) 60 ( 40% ) 26 ( 46.8% ) 47.2% 67%, 33% +53.5% Hot Water 27 ( 24.3% ) 31 ( 28% ) 33 ( 22.3% ) 41 ( 27.6% ) 11 (19%) 13 ( 24% ) 20%, 25.6% 21.7% 19.9% Lighting 30 ( 26.8% ) 54 ( 47.8% ) 32 (21.3%) 53 ( 35.8% ) 15 (26.2%) 25 ( 45% ) 25%, 40.5% 37% +49.3% Peak Period East Village ( hrs) Chidley North ( hrs) Frank Hall ( hrs) Average ( hrs ) ASHRAE Setting ( hrs) Average vs. ASHRAE Fan 12:00am 11:59pm (24 hrs) 12:00am 11:59pm (24 hrs) 12:00am 11:59pm (24hrs) 12:00am 11:59pm (24hrs) 6:00am 7:00pm (13 hrs) 7:00pm 11:00pm (4 hrs) +7 hrs Hot Water 8:00am 12:00pm (4 hrs) 8:00pm 2:00am (6 hrs) 7:00am 11:00am (4 hrs) 8:00pm 1 :00am (5 hrs) 8:00am 10:00am (2 hrs) 7:00pm 11:00pm (4 hrs) 7:00am 11:00am (4 hrs) 8:00pm 1:00am (5 hrs) 9:00am 6:00pm (9 hrs) =9 hrs Lighting 7:00am 12:00pm (5 h rs) 1:00pm 2:00am (13 hrs) 6:00am 12:00pm (6 h rs) 3:00pm 3:00am (12 hrs) 7:00am 12:00pm (5 hrs) 1:00pm 1:00am (12 hrs) 7:00am 12:00pm (5 hrs) 1:00pm 2:00am (13 hrs) 10:00am 7:00pm (9 hrs) +9 hrs Hours (hrs); Percentage (%)

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189 Table 4 6. Resource tracking p usage and peak p er iods vs ANSI/ASHRAE/IESNA 90.1 default energy s chedule Usage East Village ( % Use) Chidley North ( % Use) Frank Hall ( % Use) Average ( % Use) ASHRAE Setting ( % Use) Average vs. ASHRAE Fan 12 (81.9%) 13 ( 76.1 %) 10 ( 74.5 %) 77.5 % 67%, 33% + 87.7 % Hot Water 3 ( 22.2 %) 3 ( 20 %) 2 ( 9.8 %) 4 ( 23.5 %) 3 ( 25.6 %) 2 ( 12.8 %) 19.2 %, 11.6 % 21.7% 97.1 % Lighting 3 ( 20.9 %) 6 ( 39.8 %) 3 ( 20.6 %) 7 ( 42.9 %) 3 ( 25 %) 7 ( 52.6 %) 20.9 %, 43.9 % 37% +8.4 % Peak Period East Village ( hrs) Chidley North ( hrs) Frank Hall ( hrs) Average ( hrs ) ASHRAE Setting ( hrs) Average vs. ASHRAE Fan 12:00am 11:59pm (24 hrs) 12:00am 11:59pm (24 hrs) 12:00am 11:59pm (24hrs) 12:00am 11:59pm (24hrs) 6:00am 7:00pm (13 hrs) 7:00pm 11:00pm (4 hrs) +7 hrs Hot Water 8:00am 1 :00pm (5 hrs) 7:00pm 12 :00am (5 hrs) 7:00am 11:00am (4 hrs) 6 :00pm 1 1:00p m (5 hrs) 7:00am 12:00p m (5 hrs) 8:00pm 10 :00pm (2 hrs) 7:00am 11:00am (4 hrs) 6 :00pm 1 2 :00am (6 hrs) 9:00am 6:00pm (9 hrs) +1 hr Lighting 8:00am 1 :00pm (5 h rs) 4 :00pm 2:00am (10 hrs) 9:00am 3 :00pm (6 h rs) 5:00pm 1 :00am (8 hrs) 10:00am 2:00pm (4 hrs) 5 :00pm 1:00am (8 hrs) 9:00am 3 :00pm (6 hrs) 4:00pm 1 :00am (9 hrs) 10:00am 7:00pm (9 hrs) +6 hrs Hours (hrs); Percentage (%)

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190 Table 4 7 . Confirmatory factor analysis fit function t ests Fit Function Test Value Accepted Value Chi Square 193.3457 Value close to zero GFI 0.8782 Value equal to or greater than 0.90 AGFI 0.8090 Value equal to or greater than 0.90 RMSEA 0.1049 Value equal to or less than 0.06 Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI) and Root Mean Square Error of Approximation (RMSEA) Table 4 8 . Eigenvalues of the reduced correlation m atric Eigenvalues Differences Proportion Cumulative 1 5.07031587 3.96486694 0.7853 0.7853 2 1.10544894 0.51223388 0.1712 0.9565 3 0.59321506 0.32148012 0.0919 1.0484 4 0.27173494 0.08447665 0.0421 1.0905 5 0.18725829 0.08807268 0.0290 1.1195 6 0.09918561 0.05690903 0.0154 1.1349 7 0.04227658 0.09413133 0.0065 1.1414 8 0.05185475 0.04885271 0.0080 1.1334 9 0.10070746 0.02530017 0.0156 1.1178 10 0.12600763 0.05011942 0.0195 1.0983 11 0.17612705 0.04283811 0.0273 1.0710 12 0.21896516 0.02032681 0.0339 1.0371 13 0.23929197 0.0371 1.0000

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191 Figure 4 1 . East Village water c onsumption b etween 2010 2014 Figure 4 2 . East Village energy consumption b etween 2010 2014 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 2010-2011 2011-2012 2012-2013 2013-2014 Unit (kgal) Academic Year Actual Predicted Baseline 0 1000 2000 3000 4000 5000 6000 2010-2011 2011-2012 2012-2013 2013-2014 Unit (Mbtu) Academic Year Actual Predicted Baseline

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192 Figure 4 3 . Chidley North w a ter consumption b etween 2012 2014 Figure 4 4 . Chidley North energy consumption b etween 2012 2014 0 1000 2000 3000 4000 5000 6000 7000 8000 2012-2013 2013-2014 Unit (kgal) Academic Year Actual Predicted Baseline 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 2012-2013 2013-2014 Unit (Mbtu) Academic Year Actual Predicted Baseline

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193 Figure 4 5 . Frank Hall Water consumption b etween 2010 2014 Figure 4 6 . Frank Hall energy consumption b etween 2010 2014 0 500 1000 1500 2000 2500 2010-2011 2011-2012 2012-2013 2013-2014 Unit (kgal) Academic Year Actual Predicted Baseline 0 2000 4000 6000 8000 10000 12000 2010-2011 2011-2012 2012-2013 2013-2014 Unit (Mbtu) Academic Year Actual Predicted Baseline

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194 Figure 4 7 . Survey f indings related to fan s chedule Figure 4 8 . Survey findings r elated to hot w ater s chedule 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 1:00am-2:00am 2:00am-3:00am 3:00am-4:00am 4:00am-5:00am 5:00am-6:00am 6:00am-7:00am 7:00am-8:00am 8:00am-9:00am 9:00am-10:00am 10:00am-11:00am 11:00am-12:00pm 12:00pm-1:00pm 1:00pm-2:00pm 2:00pm-3:00pm 3:00pm-4:00pm 4:00pm-5:00pm 5:00pm-6:00pm 6:00pm-7:00pm 7:00pm-8:00pm 8:00pm-9:00pm 9:00pm-10:00pm 10:00pm-11:00pm 11:00pm-12:00am 12:00am-1:00am Percentage of Occupants Using Fan Time of Day East Fan Use Chidley Fan Use Frank Fan Use Default Fan Setting 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 1:00am-2:00am 2:00am-3:00am 3:00am-4:00am 4:00am-5:00am 5:00am-6:00am 6:00am-7:00am 7:00am-8:00am 8:00am-9:00am 9:00am-10:00am 10:00am-11:00am 11:00am-12:00pm 12:00pm-1:00pm 1:00pm-2:00pm 2:00pm-3:00pm 3:00pm-4:00pm 4:00pm-5:00pm 5:00pm-6:00pm 6:00pm-7:00pm 7:00pm-8:00pm 8:00pm-9:00pm 9:00pm-10:00pm 10:00pm-11:00pm 11:00pm-12:00am 12:00am-1:00am Percentage of Occupants Using Hot Water Tiime of Day East Hot Water Use Chidley Hot Water Use Frank Hot Water Use Default Hot Water Setting

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195 Figure 4 9 . Survey findings r elated to l ighting s chedule Figure 4 10 . Resource t racking findings r elated to f an s chedule 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1:00am-2:00am 2:00am-3:00am 3:00am-4:00am 4:00am-5:00am 5:00am-6:00am 6:00am-7:00am 7:00am-8:00am 8:00am-9:00am 9:00am-10:00am 10:00am-11:00am 11:00am-12:00pm 12:00pm-1:00pm 1:00pm-2:00pm 2:00pm-3:00pm 3:00pm-4:00pm 4:00pm-5:00pm 5:00pm-6:00pm 6:00pm-7:00pm 7:00pm-8:00pm 8:00pm-9:00pm 9:00pm-10:00pm 10:00pm-11:00pm 11:00pm-12:00am 12:00am-1:00am Percentage of Occupants Using Lighting Time of Day East Lighting Use Chidley Lighting Use Frank Lighting Use Default Lighting Setting 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1:00am-2:00am 2:00am-3:00am 3:00am-4:00am 4:00am-5:00am 5:00am-6:00am 6:00am-7:00am 7:00am-8:00am 8:00am-9:00am 9:00am-10:00am 10:00am-11:00am 11:00am-12:00pm 12:00pm-1:00pm 1:00pm-2:00pm 2:00pm-3:00pm 3:00pm-4:00pm 4:00pm-5:00pm 5:00pm-6:00pm 6:00pm-7:00pm 7:00pm-8:00pm 8:00pm-9:00pm 9:00pm-10:00pm 10:00pm-11:00pm 11:00pm-12:00am 12:00am-1:00am Percentage of Occupants Using Fan Time of Day Default Fan Setting East Fan Tracking Chidley Fan Tracking Frank Fan Tracking

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196 Figure 4 11 . Resource t racking f indings r elated to hot w ater s chedule Figure 4 12 . Resource t racking findings r elated to l ighting s chedule 0% 5% 10% 15% 20% 25% 30% 1:00am-2:00am 2:00am-3:00am 3:00am-4:00am 4:00am-5:00am 5:00am-6:00am 6:00am-7:00am 7:00am-8:00am 8:00am-9:00am 9:00am-10:00am 10:00am-11:00am 11:00am-12:00pm 12:00pm-1:00pm 1:00pm-2:00pm 2:00pm-3:00pm 3:00pm-4:00pm 4:00pm-5:00pm 5:00pm-6:00pm 6:00pm-7:00pm 7:00pm-8:00pm 8:00pm-9:00pm 9:00pm-10:00pm 10:00pm-11:00pm 11:00pm-12:00am 12:00am-1:00am Percentage of Occupants Using Hot Water Time of Day Default Hot Water Setting East Hot Water Tracking Chidley Hot Water Tracking Frank Hot Water Tracking 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1:00am-2:00am 2:00am-3:00am 3:00am-4:00am 4:00am-5:00am 5:00am-6:00am 6:00am-7:00am 7:00am-8:00am 8:00am-9:00am 9:00am-10:00am 10:00am-11:00am 11:00am-12:00pm 12:00pm-1:00pm 1:00pm-2:00pm 2:00pm-3:00pm 3:00pm-4:00pm 4:00pm-5:00pm 5:00pm-6:00pm 6:00pm-7:00pm 7:00pm-8:00pm 8:00pm-9:00pm 9:00pm-10:00pm 10:00pm-11:00pm 11:00pm-12:00am 12:00am-1:00am Percentage of Occupants Using Lighting Time of Day Default Lighting Setting East Lighting Tracking Chidley Lighting Tracking Frank Lighting Tracking

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197 Figure 4 13. Scree p lot based on exploratory factor a nalysis Figure 4 14 . Rotation b etween Factor 1 and Factor 2 -1 0 1 2 3 4 5 6 0 2 4 6 8 10 12 14 Eigenvalue Factor Proportion Altruistic (Val. 1) Egoistic (Val. 2) Biospheric (Val.3) Beleifs Attitude Housing (Sub. 1) Friends (Sub. 2) Neighbors (Sub. 3) Family (Sub. 4) Faculty (Sub. 5) Personal Norm Percieved Beh. Con. Intentions -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 -1.00 -0.50 0.00 0.50 1.00 Factor 1 Factor 2 Altruistic (Val. 1) Egoistic (Val. 2) Biospheric (Val.3) Beleifs Attitude Housing (Sub. 1) Friends (Sub. 2) Neighbors (Sub. 3) Family (Sub. 4) Faculty (Sub. 5) Personal Norm Percieved Beh. Con. Intentions

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198 Figure 4 15 . Rotation b etween Factor 1 and Factor 3 Figure 4 16 . Rotation b etween Factor 2 and Factor 3 Altruistic (Val. 1) Egoistic (Val. 2) Biospheric (Val.3) Beleifs Attitude Housing (Sub. 1) Friends (Sub. 2) Neighbors (Sub. 3) Family (Sub. 4) Faculty (Sub. 5) Personal Norm Percieved Beh. Con. Intentions -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 Factor 1 Factor 3 Altruistic (Val. 1) Egoistic (Val. 2) Biospheric (Val.3) Beleifs Attitude Housing (Sub. 1) Friends (Sub. 2) Neighbors (Sub. 3) Family (Sub. 4) Faculty (Sub. 5) Personal Norm Percieved Beh. Con. Intentions Altruistic (Val. 1) Egoistic (Val. 2) Biospheric (Val.3) Beleifs Attitude Housing (Sub. 1) Friends (Sub. 2) Neighbors (Sub. 3) Family (Sub. 4) Faculty (Sub. 5) Personal Norm Percieved Beh. Con. Intentions -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 Factor 2 Factor 3 Altruistic (Val. 1) Egoistic (Val. 2) Biospheric (Val.3) Beleifs Attitude Housing (Sub. 1) Friends (Sub. 2) Neighbors (Sub. 3) Family (Sub. 4) Faculty (Sub. 5) Personal Norm Percieved Beh. Con. Intentions

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199 CHAPTER 5 DISCUSSION This chapter discusses the findings of this study and helps to illustrate the significance of results relative to research question 1, its sub questions, and research question 2. R ecommendations are made for improving the LEED rating system, its referenced standards, and programs that address relevant behavioral constructs in LEED certified residence halls . Limitat ions are then discussed to hig hlight how this study could be further improved. Additionally, future studies on building performance and occupant ESBs are suggested in order to expand the body of knowledge in sustainability research. Finally, concluding sta tements ar e provided to summarize the key findings of this study. Comparison b etween Case s Based on the case profiles and interviews it was ev ident that the three case s shared many similarities with regards to their location, LEED certification level, s age, and water and energy conservation features . These characteristics could focus on actual occupant behaviors, their relationship to the LEED default s ettings , and the ANSI/ASHRAE/IESNA 90.1 schedules. Fo r example, all three case s were located in the southeast of the United States and were rated LEED certified Gold. East Village and Chidley North were predicted to reduce their water consumption by a mini mum of 30% and their energy c onsumption by a minimum of 28%. In this regard, it was noted that Frank Hall was different with a predicted water savings of 20% and a predicted energy savings of 35% as it was the only residence hall to utilized solar pan els a s a method for reducing energy consumption . Still, a ll three cases were

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200 primarily the home to underclas smen between the ages of 18 19. Additionally, interview participants recognized similar sustainable featu res within their residence halls , such as low fl ow fixtures, dual flush toilets, motion sensors, thermostat controls, and recycling programs. As referred to in the Case Selection (pg. 76) section of this study, Campbell (2003) research describes how the similar starting conditions of typical cases le a d to similar outcomes and thus, built a compelling basis for drawing conclusions . Consistent with this research a ll three cases demonstrated that the performance predictions made during the LEED certification process are not a guarantee of actual consumpt ion or utility cost savings. Based on the findings r elevant to the LEED default settings and ANSI/ASHRAE/IESNA 90.1 schedules this can be attributed to the discrepancy that exists between how o ccupants are predicted to consume resources and how they actual ly do . Similar to the wide range of building performance noted in studies by Azar and Menassa (2010), Turner (2006), and Yudelson (2010) , va riations in this study fluctuated from 54.5% below to 164.8 % above a baseline case . With regards to socio economic factors , it was noted that the populations in each building were quite different. Both Emory Oxford and Appalachian State admitted students with an average GPA ranging from 3.52 3.96. However, the average student admitted at North Carolina Central had a si gnificantly lower GPA at 2.99. The demographic profiles for each university also indicated that projected tuition and fee expenses for the 2013 2014 academic year were more than twice as much for Emory Oxford students than those that attended North Carolin a Central and Appalachian State. Additionally, it was found that 64% (2,862) of the incoming students at North Carolina

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201 Central ca me from low income families ( Nort h Carolina Central University, 2013 ). While a similar statistic is not published for either o f the other two schools, the significantly higher tuition cost at Emory Oxford might suggest that many of these studen ts come from affluent families. esearch suggesting that social class and ed ucation affect and shapes willingness to solve environmental problem ( Dunlap & Jones, 2002 ; Harper, 2008 ) . For example, c ross cultural studies have shown that middle class people show more concern for the environment than working class people . environmental activism is believed to be the result of education, greater access to resources, and a greater sense of personal efficacy. By contrast, i t is suspected that the economic instability of the w orking clas s causes them to be more concerned about physical needs such as food and shelter, versus concerns about nature and the preservation of the environment ( Ali beli & Johnson, 2009 ; Suttton 2009). Such socio economic differences between each university help ed t o provide clues while interpret ing the environmentally significant behavior of occupants throughout this study . They also helped in the development of appropriate recommendations found later in this chapter. Accuracy of LEED Default Settings for Water S urvey findings revealed that occupant behaviors in each case were not accurately predicted by the LEED default setting s . This was consistent with research by Azar and Menassa (2010 ) who also note d how occupants play an important role in the variation betwe en prediction and actual performance . Usage rates were often over estimated by an average of 37% and fixture flow rates were often underestimated by an average of 46%. For example, as seen in Table 4 3 t he average of al l three cases su ggest that female and male residents utilize wat er closets in residence hall s

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202 significantly less than the current default setting for residential construction . Both genders from a ll three residence halls also r esponded that they used the kitchen s ink s and the lavatory faucet s less , and the showerhead s more often per day than predic ted by the LEED default setting . Finally, d iscrepancies were also noted with regards to fixture flow duration s , which were shorter for kitchen sinks and longer for lavatory faucets and showerheads. A large variation also existed amongst the cases with regards to their fixture flow rates. Interviews with residents from each case may help to explain this incongruity as 10 (76.9%) Frank Hall participants felt strongly about conserving because it contribu ted to the health of the environment. By contrast, only 1 (6.7%) participant from East Village and none from Chidley North shared these same sentiments. According to behavioral research, the attitude construct is closely related to the performance of a beh avior or a predisposition to wards an action ( Fishbein & Ajzen, 1975; Jacobsen, 2011). Thus, t he stark difference in atti tudes towards conserving water c ould help to explain why Frank Hall occupants consistently consumed the le ast amount of water from lavat ory and showerhead fixtures. Similar to the survey findings, the three days of water tracking information from each case revealed a discrepancy between the LEED default setting and the actual consumption of occupants. As seen in Table 4 4 , f emale and male occupants from each case used the residence hall water closets less than predicted. Additionally, tracking information from both occupant types suggested th at lavatory faucet s and kitchen sinks were used less often for longer periods of time, and showerheads were used more often for l onger periods of time than the defaults settings propose for residential construction .

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203 Based on the resource tracking data , we see again that the L EED default settings for water usage do not accurately depict the consu mption behaviors of students in residence halls. In this context , the predicted usage rates were often over estimated by an average of 41 % and fixture flow rates were often underestimated by a n average of 89 %. Similar to the survey findings, the resource tracking data also revealed a discrepancy amongst the cases with regards to the flow duration of showerheads and sinks . For example, occupants ran the showerhead for an average of 894.8 seconds per use in East Village and Frank hall , and 1,085.3 seconds pe r use in Chidley North . Interviews with occupants from each residence hall indicated that 12 (70.6%) Chidley North participants felt that the absence of a cost incentive made it difficult for t hem to want to save resources , while only 4 (26.7%) from East V illage and 6 (46.2%) from Frank Hall shared the same sentiments . Again we turn to behavioral research, which states that the perceived behavioral control construct is an exogenous variable that has a direct effect on behaviors and an indirect effect on behavioral intentions. As a result , literature supports that if sample residents perceive that they have little control over costs then their intentions to perform a behavior will be low (Ajzen, 1991) . Thus, the prominence of this constraining condition in Chidley North might help to explain why these residents co nsumed the most amount of water from showerhea d fixtures. In the Topic 2: Tracked Water Consumptio n section of the interview participants f rom each case were asked to reflect on their own water consumption. The qualitative analysis of interviews from each re sidence hall indicated that approximately 66% of occupants from each case believed that their consumption of regulated fixtur es was

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204 about what they expected. Additionally, p articipants for all three case s who indicated that their consumption was about the same attributed the majority of their water consumption to the regular use of showe rs and the adherence to a daily routine . Those from Ea st Village and Chidley North that noted that their water consumption was more than anticipated attributed this increase to l onger showers, while Frank Hall participants cited sinks and toilets as the prominent culprits . Finally, those from all three case s who believed that their cons umption was less consistently stated that t hey took faster showers than they originally thought. Improving Fixture Usage and Water Duration Defaults As previously described in the Water Use Reduction Template (pg. 35) section o f this study, integrated design teams rely upon the LEED default settings to complete the documentation for WE Credit 3 Water Use Reduction. Therefore it is critical for such teams to have a reliable measure of occupant consumption so that they can knowled geable design buildings that conserve water. However, t he results of the survey instrument , the resource tracking exercise , and the interviews consistently demonstrated for all three cases that these settings were not accurate . The similar findings amongst each residence hall make a strong case that the LEED default settings need to be further examined and tailored to better reflect the behaviors of occupants in different residential settings. For example, s tudent residents typically spend an average of 12. 5 hours a day outside of their residence hall in classes, di ning rooms, social events, and part time jobs (College Parents of America, 2014; Pranabudi, 2014). By contrast, the LEED d efault values for water use appeared to better characterize a population t hat spent longer periods of time within their residence, such as the occupants of a single family home or apartment. Additionally, t he default values for flow

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205 duration also appear ed to better represent a n idealistic figure for what individuals should consume if they were actively conserving resources . However, as seen in Appendix I the large majority of occupants from each case at Pro e xhibited both sustainable and unsustainable behaviors. Thus, a strong case is also made for the LEED default settings to reflect a full range of environmental and non environmental behaviors. Accuracy of LEED Default Energy Schedules Accordin g to the case profiles and interviews , all three universities used similar technological features, such as motion sensors, thermostat controls, and energy recovery systems , to reduce their energy consumption. These similar technologies helped to provide a control in th e interior environment of each case so that comparisons ANSI/ASHRAE/IESNA schedules for fans, hot water , and lighting . Based on the survey responses from all three cases energy consumption was generally consistent for fan, hot water , and lighting schedules. For example, a s seen in Table 4 5 , approximately 47% of the partici pants from all three case s indicated that they utilized the HVAC system over a 24 hour period. This provided compelling evidence that occupant behaviors in residence halls do not correspond with the current ANSI/ ASHRAE/IESNA 90.1 fan schedule. Instead, this energy standard for fans appears to better model two peak periods that correspond with business and janitorial hours between 6:00am 7:00pm and 7:00pm 11:00pm . Additionally, in contrast to the ANSI/ASHRAE/IESNA 90.1 hot water and lighting schedules, surveys from all three cases consistently demonstrated that participants u sed these systems during two pea k periods. For example, approxi ma tely 20 % of occupants utilized the h ot water system between 7:00am 11:0 0am and 25.6 % utilized the hot water between 8:00pm -

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206 1:0 0 am. Similarly, approximately 25 % of occupants utilized the overhead lighting system between 7:00am 12:00pm and 40.5 % utilized the lights between 1:00pm 2:00am . The similarity between all three cases strongly suggests that the ANSI/ASHRAE/IESNA 90.1 standard does not accurately account for occupant behaviors in re sidence halls. Primarily this appears to be due to the commercial origi ns of this standard. Peak periods appear to better reflect the business hours of commercial properties and are not tailored to reflect the unique schedule of occupants in residence halls. Similar to survey findings, the three days of energy tracking inform ation for all three case s were generally consistent for fan, hot water and lighting schedules. As a result of having a significantly smaller sample size, the schedules derived from the tracking exercises exhibited more dramatic shifts betw een peak periods when compared to the survey derived schedules . However, despite this difference these data sets exhibited similar patterns with regards to their peak hours . The similarities between the survey and resource tracking exercise findings provided strong evidence that the current ANSI/ASHRAE/IESNA 90.1 standard does accurately represent the occupant behaviors in residence halls. For example, as seen in Table 4 6, an average of 77.5 % of the partici pants from all three case s indicated that they utilized the HVAC system over a 24 hour period . Akin to survey findings, tracking data from all three cases demonstrated that participants used the hot water system during two peak period s. For example, approximately 19.2 % of occupants utilized the hot water system between 7:00am 11:00am and 11.6% utilized the hot water between 6:00pm 12:00am . Also , approximately 20.9% of occupants utilized the overhead lighting system between

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207 9:00am 3:00pm and 4 3.9% utilized the lights between 4:00pm 1:00am . Again this case study reveals that the does not allow this standard to accurately respond to the consumption behavior of student residents. In the Topic 3 : Tracked Energy Consu mption section of the interview occupants from each case were asked to reflect on their own energy consumption. As seen in Appendix I, t he qualitative analysis of interviews indicated that 43.6 % of occupants from East Village and Chidley North believed that their consumption of regulated fixtures was about what they expected. By contrast, 30.8% (4) of occupants from Frank Hall believed that their consumption was about what they expected. P artic ipants from all three case s who indicated that their consumption was about the same or more at tributed the majority of their energy consumption to the regular use the HVAC system and overhead lighting . Residents from all three universities who consumed more than anticipat ed attributed this increase to the frequent use of the HVAC system and overhead lights . Finally, those from all three case s who believed that cons umption was less consistently stated that t hey turned off the lights more often than they originally thought. Improving Energy Related Schedules As previously described in the Optimized Energy Performance Template (pg. 39) section of this study, integrated design teams must use the ANSI/ASHRAE/IESNA 90.1 schedules for fans, hot water, and lighting to complete the documentation for EA Credit 1 Optimized Energy Performance . It is critical for integrated design teams to have a reliable measure of occupant consumption so that they can knowledgeable create environments that compete with the environmentally significant behaviors of occupants. However, t he triangulation of the survey , the resource tracking exercise, and interview

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208 findings revealed that the referenced ANSI/ASHRAE/IESNA 90.1 standard did not accurately predict occupant behaviors. As supported by the researc h of Turner (2006) and Yudelson ( 2010), who also noted similar disparities with energy modeling, the difference between the predicted occupant behaviors and actual behaviors lead to a wide range of variations from the baseline case for each residence hall. Most frequently, occupants in residence halls accessed energy related systems more often than projected by the ANSI/ASHRAE/IESNA 90. 1 fan, hot water, and lighting schedules. Additionally, responses to the surveys and resource tracking exercise suggested that campus residents utilize fans for 7 hours longer, hot water heaters for 30 minutes longer, and lighting systems for 7.5 hours lon ger then des cribed by the ANSI/ASHRAE/IESNA 90.1 default schedules. The consistency of data in this case study strongly suggests that further investigation is required to confirm a more accurate prediction for occupant fan, hot water, and lighting use in r esidence halls. When compare d to the actual consumption of residents in each case it was clear that the ANSI/ASHRAE/IESNA 90.1 s chedules were limited in their scope. These guide s were originally developed for co mmercial buildings and thus do not account f or a population that can occupy a space for a 24 hour period. As a result, the peak periods of occupants who accessed energy systems in residence halls were an inverse of occupants who access ed energy systems in commercial building s . For example, while the ANSI/ASHRAE/IESNA 90.1 hot water schedule suggests one peak perio d between 9:00am 6:00pm , the da ta sets from this study suggests peak period s between 7:00am 11:00am and 8:00pm 1:00am . Th e referenced standard peak periods follow the logic that commercial building users do not use resources in their office outside of business

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209 hours . However, because of the residential cont ext of the three case s, occupants behave in direct opposition to commercial users by not using resources in th eir residence hall during business hours because they are presumably in class. Additionally, unlike commercial building users, residents have the opportunity to utilize energy systems for longer periods of time because of their 24 hour access. Finally, des pite the conservative predictions of indoor energy consumption, occupants in each hall exhibited both sustainable an d unsustainable behaviors (refer to Appendix I) . Therefore, this case study supports that a necessary next step for the ANSI/ASHRAE/IESNA 90 .1 standard would involve the development of addi tional schedules for residential settings, including residence halls, that reflect a full range of environmental and non environmental behaviors. Relationship b etween Behavioral Constructs and Consumption o f Resources General K nowledge of LEED C ertification. It was clear from interview responses (refer to Appendix I) th at the majority of participants certification and could describe the impact this rating system had on the construction of their residence hall. Also, residents frequently recognized how the existing low flow water fixtures and sensored lights contributed towards the conservation of resources in their hall. By contrast, only 1 (5.9%) of the Chidley North participants was aware that they lived in a LEE D certified residence hall and all were unfamiliar with what the USGBC and/or LEED system represented. When asked about the available conservation technologies in their building, these resid ents were the most familiar with the installed dual flush toilets and the lighting sensors. Finally, 7 (53.8%) of the Frank Hall interview participants were aware that their building was LEED certified but only 1 (7.7%) was

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210 able to describe this system in some detail. Similar to Chidley North, residents from Frank Hall were the most familiar with how the installed dual flush toilets and the lighting sensors contributed towards the conservation of resources in their building. It was clear from these findings that the residents of Chidley North were the least inform ed about the USGBC and/or LEED system , and the certification of their residence hall. It is believed that the ability for East Village and Frank Hall residents to recognize and describe fe atures is related to exposure to educational resources . For example, residents from East V illage and Frank Hall noted that they had observed signage on their resident walls or school websites , which described the certification and features of their residence hall . By contrast, only one (5.9%) resident from Chidley North mentioned that a description of features was provided at the beginning of the semester and that some of the dual flush toilets still had instruction stickers attached (CN9_Female). During site visits , the community director s also made note of sustainable features on their premises that helped to educate residents about sustainability , such as the water collection feature in the East Village courtyard and the at Frank Hall t hat allowed the second floor residents to live amongst others who had similar ESBs (J. Lorello , personal communication, July 10th, 2013; M. Sheets, personal communication, July 8th, 2013) . These findings align with research by Alibeli and Johnso n ( 2009 ) which states that a strong relationship exists between educational attainm ent and environmental concerns. While education does not guarantee the adoption of sustainable behavior, it is unlikely that they could be fostered if an environmental concern has not yet been built through instruction.

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211 Values in Residence Halls The qualitative analysis of beha vioral norms from all three cases revealed that the majority of interview participants were driven by egoistic values or self interests . Most frequently, interview p articipants noted that this was in response to a desire to being set and the absence of a monetary consequence for unsustainable behaviors, students from both East Vill age and Chidley North frequently indicated that their consumption of resources was not motivated by their egoistic values. By contrast, over half of the interviewees from Frank Hall indicated that their consumption of resources was motivated by their egois tic and often stated that this resulted from their consideration for those responsible for additional costs incurred from excessive consumption. One reason for Frank Hall s unique position can be seen i n a comparison to other resident s concerns. For exam ple , as seen in Appendix I Frank Hall occupants more frequently cited that they were concerned for the health, safety and welfare of future generations and the preservation of the natural environment . Additionally, with access to continued education in the it seems natural that residents in Frank Hall would share a deeper interes t in environmental protection. Here again we see an alignment with the research by Alibeli and Johnso n ( 2009 ) and that of Samuelsson and Kaga (2008) who ad vocate that education helps to foster sustainable behaviors. However, in this case, it could also be said that t community is successful in fostering sustainable behaviors because it established a social norm for residents to follow.

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212 Beliefs in Residence H alls The analysis of beliefs in each site revealed that the majority of East Village and comparison, the majority of the interview participants from Chidle y North considered generally conscious of their consumption of resources and had an interes t in environmental topics or legislation. Conversely, those residents from Chidley North with priority. When interviewees were asked to describe why they were not more pr o environmental, participants from all three universities most frequently stated that sustainable behaviors, such as shorter showers or turning off lights, were considered to be inconvenient. Finally, the majority of residents in each hall did not perceive a consequence to behaving unsustainably in their dormitory and an average of 7 (40.6%) of residents from East Village and Chidley North indicated that they would not feel responsible if the consumption of resources was higher than anticipated by housing a uthorities. Here again Frank Hall was distinctive when the majority of interview participants indicated that they would in fact feel responsible if the consumption of resources in their dormitory was higher than anticipated. A ue motivation to behave consistently with their beliefs could be attributed to a stark difference in their environmental interests. For example, as seen in Appendix I interviews revealed that the large majority of residents from Frank Hall were interested in environmental topics a nd legislation in comparison to residents from East Village and Chidley North. I n light of the other behaviors that Frank

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213 Hall residents have exhibited, it seems clear that the culture of this residence hall helps to support an int erest in protecting the environment and use of sustainable practices. Attitudes t oward Conserving Water and Energy in Residence H alls Interview respons es indicated that over half of East Village and Chidley North participant considered the importance of water and energy conservation to be between a 5 6.9 on a scale from 1 10, where 1 was the least important and 10 was the most important. By contrast, over half of Frank Hall interviewees ranked the importance of conserving these same resources between a 7 8.9. Most frequently participants from each university who ranked conservation below a 5 indicated that they did not feel these behaviors were more important beca use they were not a daily consideration, generally because such behavior s were considered inconvenient or because they did not believe that they used many resources, so saving more wa s considered to be unnecessary. Unlike the other sites, the majority of F rank Hall participants stated that conservation was important because it contribut ed towards environmental health, resources were considered an expensive commodity to waste, and it was believed to be considerate to maintain a supply of resources for others . Finally, when each student was asked to describe an effective method for reducing the current consumption of resources in their residence hall, the majority of the Frank Hall interviewees suggested raising resident awareness of conservation opportunities while the majority of East Village and Chidley North interview participants suggested that additional technologies, such as motion sensored faucets, be installed. Interestingly, Frank Hall residents consistently exhibited strong environmental attitudes w ith regards to the conservation of water and energy. Unlike the other case s, these residents maintained a high degree of concern for environmental health and the

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214 welfare of others. According to the Director of The Honors College at Appalachian State, the b ehaviors of residents in Frank Hall may be a reflection of the continued sustainability education on campus. In an interview the Director stated : As I have reviewed the applications for honors students, I have found that maybe 1% of students have come in w ith a real concern about resources, such as water . However, in my experience working with juniors and seniors who have been on campus for a while, it is clear that they become much aware of the preciousness of resources. For example, in a recent writing as signment, I asked my students to imagine how some issue in the future might shape laws and regulations. Without being prompted to reflect on the environment , 2 out of 11 of my students wrote about water scarcity as a huge problem in the future . So ultimate ly , I believe that some of them might come aware of environmental issues but they all leave aware of environmental issues as a result of the daily education here on campus ( L. Jones, personal communication, January 31st , 2014) Additionally, during the cour se of this study it was noted that a water main break on the Appalachian State campus discolor ed the water for a few days. It was also noted that this had happened in the past. Thus, it is possible that in addition to the education on campus, residents at Frank Hall periodically receive a visual reminder in the discoloration of water, that this resource is precious and not to be taken for granted. Subjective and Personal Norms in Residence H alls The qualitative analysis of interviews from all three unive rsities suggested that resident s environmental behaviors were most inf luenced by their family members. It seemed appropriate then that those residents who possessed somewhat or very high personal norms to conserve water and energy in their residence hall frequently stated that they did so as a result of learning such behaviors in their parental homes. Of all three sites, Frank Hall had the highest percentage of residents who indicated that they felt very obligated to conserve resources , East Vill age has the highest percentage of residents who indicated that they felt somewhat obligated to conserve resources, and

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215 Chidley North ha d the highest percentage of residents who indicated that they did not feel obligated to conserve resources . Finally, over half of the East Village and Frank Hall interviewees indicated that their ESBs remained the same regardless of whether they were home or in their residence hall. By contrast, over half of the Chidley North interview participants indicated that they were more cognizant of their ESBs at home, generally as a result o f a direct financial incentive. In this case it was clear that residents e xhibited behaviors that were established at home. B ased on the consistency of behaviors across each residence hall, it can be assumed that Frank Hall residents came from families with strong environmental concerns, followed by East Village residents who ca me from families with moderate environmental concerns, and then Chidley North residents who came from families with weak environmental concerns. With 64% of students coming from low income homes, it may not be surprising that sustainable practices were not a higher priority for Chidley North residents and their families . According to socio economic research by Sutton (2009) , members of the middle class who have greater access to resources and a greater sense of personal efficacy are known to be more concern for the environment . Conversely, members of the working class experience a higher degree of economic instability food and shelter ( Ali beli & Johnson, 2009 ). Thus, it is unlikely that many of the residents from Chidley North would have regularly practiced sustainable behaviors in their homes for the sake of preserving the environment. This is supported by the fact that 11 (64.7%) of Chidley North residents claimed that they were only cogniza nt of their ESBs when there was a direct relationship to a financial incentive.

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216 Perceived Behavioral Controls in Residence H alls The analysis of perceived behavior controls revealed that the majority of residents from all three universities believed that t he existing technologies in their building, such as the sensored lights and dual flush toilets, helped to facilitate their sustainable behaviors. However, approximately 13 (40.6%) of interview participants from East Village and Chidley North did not feel t hat they were well educated on the features that existed in their residence or the rationale for conserving resources, and 7 (47.8%) participants from all the universities believed that the absence of a cost incentive made it difficult for them to consider sustainable behaviors a priority. Of those residents that indicated that education was a constraining condition to their sustainable behaviors the majority said that they would be willing to participate in a sustainability education program. However, as s een in Appendix I, only 3 (22.2%) of interviewees believed that they would actually apply what they learned in the program. Furthermore, with the exception of Frank Hall participants who projected a participation rate of over 50%, residents generally predi cted that only 12.5 27.5% of their total residence hall population would agree to participate in an educational program. Additionally, of those residents that indicated that cost was a constraining condition 8 (61.5%) of Frank Hall interviewees indicated t hat they would be willing to support a policy where residents were charged for their own use of utilities. By contrast only 4 (21.4%) of participants from East Village and Chidley North indicated that they would support such a policy. Findings here begin to reveal the extent to which occupants rely upon the efficacy of technological features. Additionally, they also support the impact that education programs and financial incentives have on the populations within residence halls. By now these themes have been reiterated by a number of constructs, including

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217 values, attitudes, subjective norms and personal norms. In line with the mission of institutions of higher education and their signed sustainability commitments, they could take on the co curricular education of campus residents to improve the adoption of sustainable behaviors . However , what this consistency ultimately suggests it that the LEED rating system could significantly improve the water and energy performance of residence halls by integratin g educational programs and financial incentives into its requirements. While this might not be necessary for all construction types, it is clear that the combination of these tools could significantly influence the adoption of sustainable practices in resi dence halls. Behavioral Intentions in Residence H alls The analysis of behavioral intentions in each site revealed that nearly half of the participants from East Village and Chidley North did not have an intention of reducing their consumption of water or energy next semester. By contrast, nearly half of interviewees from Frank Hall believed it was very likely that they would reduce their consumption of resources. Of those residents from all three universities who believed that they would reduce their leve l of consumption by some degree, it was generally stated that they would d o so by taking shorter showers, tu rning off the lights more often, and being more self aw are. Finally, when residents were asked if they intended to reduce their consumption of resou rces after moving out of their respective residence hall and purchasing their own home, approximately nearly half of the interview participants indicated that they would and an average of 58.8% from each residence hall added that their intentions would cha nge at that point because of the direct connection to a monetary incentive.

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218 Once again the residents of Frank Hall were distinctive in their desires to continuously improve their consumption of resources. Unlike East Village and Chidley North these reside nts consistently distinguished themselves as a group with high levels of environmental consciousness. While one explanation for this awareness might be be the campus w ide educat ion and physical reminders that, according to the Director of The Honor College, reminded students that resources are a precious commodity (L. Jones, personal communication, January 31st , 2014) . Additionally, the analysis of behavioral intentions reiterates that the presence of a monetary incentive is closely tied to the adoption of desired sustainable behaviors in LEED certified residence halls . This consistency provides additional evidence of the real need for this feature to be integrated into the LEED rating system. Recommendations This section helps to emphasize the by providing recommendation s for improving the LEED rating system; its referenced standards , and developing programs that address relevant behavioral constructs in residence halls. Thes e practical implications ultimately aim to improve the variance between the way buildings are designed and the way they p e r form by honing in on gaps in the LEED ra Adjustments to the LEED Certification Process Similar with the examples described in the Pacific Lutheran University (pg. 48) and Oregon Health & Science University (pg. 49) sections of thi s study, this case study demonstrated that building performance predictions are not a guarantee of actual consumption or utility cost savings. As supported by the research of Petersen et al.

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219 (2007) misunderstandings about the importance of occupant behavio rs lead to significant v ariations above and below the baseline cases in this study. While it is often assumed to be a sign of high performance to fall below the baseline case, sites such as Chidley North are a reminder that building system malfunctions can present a deceptive picture of building consumption. Additionally, cases such as Frank Hall are evidence that even the best technological solutions , like solar panels, cannot guarantee building efficiency. The prevalence of such inconsistencies raise a qu estion about the credibility of the LEED rating system and can make it difficult for building stakeholders to see the value in future certifications. In support of such concerns, the Engineering Supervisor at the State Construction Office in Raleigh, North Carolina stated: inaccurate modeling and inaccurate gathering and reporting of meter data continues to hurt our efforts in gathering building data. As a result, it is difficult to show interested parties that the investment in high performance buildings p ays back based on utility savings (L. Thagard, personal communication, November 20th, 2013). Therefore, in order to ensure that LEED certified buildings consistently represent examples of high performance, it is recommended that projects receive anticipat ed points for the first year of operation and only be awarded final certification after performance levels have been determined. In this way the integrity of the LEED certification proc ess may be enhanced and campus housing in particular will be confident that they are delivering exceptional environments to their stakeholders, staff , and student resident s. Require a Cost for Consumption Most residence halls a cross the country, including those from the three cases in this is viewed as a convenience and represents an incentive for choosing to live on

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220 Howe ver, despite the range of socio economic backgrounds demographic profiles , it was clear from the interviews that values, perceived behavioral controls, and behavioral intentions were directly impacted by the perception that such pre paid utilities were free of charge . For example, despite exhibiting strong egoistic values and the desire to save money, students fre quently did not associate the conservation of resources with a direct or indirect cost savings. As seen in Appendix I u p to 70.6% of residents indicated that their consumption of resources was not motivated by their value orientation because their utility costs were set regardless of the amount they used. Additionally, when discussing perceived behavioral controls, students frequently noted that the absence of a cost incentive posed a constraint for actively conserving resources in their residence halls. As a result, up to 70.6% of residents indicated that they did not consider environmentally significant behaviors a priority because they were not directly affected by making sustainable choices. Finally, an average of 41.2% of all interviewees anticipated th at their consumption of water and energy would remain the same or eve n be worse next semester. Often attributed this sentiment to a lack of a monetary consequence and a matter of convenience. However, when these same residents were asked if they intended to reduce their consumption of resources after purchasing their own home, an average of 44.5% of interviewees indicated that they would and 58.8% stated that these intentions were a direct result of a monetary incentive. Based on the interv iew responses from residents in each hall, it was clear that

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221 a direct result of the perception that utilities were free, residents indicated that they purposefully took lon ger showers, would leave the lights on, or leave unused electronics plugged in. While utility cost savings may be a motive for students to initially choose campus dormitories, it is clear that this model directly impacts the sustainable goals that administ rators are setting for campuses across the country. As revealed in behavioral research by Bolderdijk, and Steg ( 2014 ): F inancial incentives (e.g., discounts, deposits, rebates, subsidies) make desired consumer behavior (e.g., the purchase of organic foo d, recycling cans) financially attractive. They are considered to be persuasive in as far as they allow consumers to save money, which can be used to purchase more of the goods and services they desire. Similarly, financial disincentives (e.g., surcharges, fines, fees, taxes) make undesired consumer behavior financially unattractive because they limit the amount of desirable goods and services people can purchase. In sum, because incentives impact the amount of money available to spend on other products and services, larger incentives should result in more behavior change ( p. 7) Thus, it is recommended that the USGBC require that LEED certified residence hall s individually meter consumption by room, similar to that of an apartment, or by floor. In this way a consequence may be associated with the excessive consumption of resources and an incentive may be provided to individual residents or for resident floors that conserve. This recommendation would also benefit campuses as it provides an opportunity for op erational cost savings throughout the year. Require a Program for Fostering Sustainable Behaviors While a component of sustainability relies on the physical construction and installation of technologies in buildings, this study is a reminder that the cons tant cooperation of occupants is necessary to optimize building performance levels. By shifting the focus from technology to actual user behaviors, one can ensure long term and permanent changes in the performance of residence halls. For example,

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222 photovolt aic cells, like those installed on the roof of Frank Hall, are frequently used as a sustainable alternative for producing clean energy. However, even if installed correctly, studies have shown that due to outdoor exposure these systems experience a 0.5% 9. 8% degradation in power generation per year ( Quintana, King, McMahon, & Osterwald, 2002). Therefore, if a facility were to rely on this type of technology to mitigate their consumption of coal burning fuels, the gradual degradation of the photovoltaic cell s would eventually render these efforts obsolete. Additionally, with enrollment being in a constant state of flux at universities, it is difficult to ensure that all buildings users are trained to properly utilize existing technologies. The constant fluct uation in enrollment also makes it difficult for designers to predetermine optimal building sizes and system capacities. For example, according Bureau, there has been a steady rise in college enrollments since the recession hit in 2008. Thus, is unlikely that existing buildings on university campuses were sized appropriately for the surge of students over the last few years. Therefore, if users are not properly educated and bui ldings are not designed to meet the needs of a variable population, consumption data are inevitably going to reflect an increased use of electrical equipment, plug in loads, and water consumption even if high performance technologies have been included. Without a shift in environmentally significant behavior, technological strategies will always be just temporary solutions. Therefore, in order to ensure that user behaviors are purposefully considered during the development and certification of LEED buildi ngs it is recommended that the USGBC require project teams to develop and

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223 submit programs that focus on fostering sustainable behaviors during the certification process. It could be argued that sustainability programs should be the responsibility of univer sities administration . However, few campuses have documented successful programs under the LEED Innovation & Design category and research has continued to reveal the high consump tion of resources on campuses. By integrating t his requirement into the LEED r ating system, universities who are already under pressure by state and local governments to green their campuses , would have an additional incentive for truly addressing occupant behaviors . In particular, sustainable programs that utilize social influence approaches and community based social marketing (CBSM) techniques have emerged over the past decade as attractive alternatives to information intensive sustainability campaigns. These types of methods seek to foster broad sustainable behaviors in communit ies by combining knowledge from psychology and social marketing. This emergence can be traced to a growing understanding on the part of program planners that conventional campaigns, which rely heavily or exclusively on media advertising, can be effective in creating public awareness and improved understanding of issues but are limited in their McKenzie Mohr, 2000, p. 546 ). By focusing at the root of the problem, programs that utilize social influence and CBSM techniques provide opportunities for long term behavioral change and a shift in the current paradigm for using resources. The following CBSM techniques are recommended in direct relation to the behaviors exhibited by the occupants within the three cas e s. A more exten sive list of social influence approaches and CBSM techniques has also been provided in Appendix J to assist in the continued development of future campus programs.

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224 Incentives As previously described in the Require a Cost for Consumption ( pg. 218 ) section o Many studies have documented a similar motivational barrier and have found that extrinsic and intrinsic rewards are very effective in promoting and encouraging sustain able actions (Adachi & Rowlands, 2010; Aronoff, Champion, Lauer, & Pahwa, 2013; Conn, 2009; McKenzie & Smith, 2010; Sorice, & Conner, 2010). Based on such studies it is clear that when individuals discover that they will gain either a tangible or intangibl e reward by performing desired behaviors, they are motivated to participate in of the faculty admitted to the fact that they would be more likely to conserve energy if t Lauer, & Pahwa, 2013, p. 5). Additionally, in recent years several competitions have been implemented across college c ampuses to see which residence hall could achieve the grea test reductions in water and energy consumption. Often times free drinks, food, communities to substantially decrease their use of resources (New York University, 2013; Oregon S tate University, 2012; University of Florida, 2014; University of Oregon, 2014). Thus, extrinsic and intrinsic rewards represent a promising tool to include in campus environmental programs that seek to create sustainable behavior change. In order for ince ntives to be used effectively, Doug McKenzie Mohr (2013), an environmental psychologist and the founder of community based social marketing, advises that they be large enough to be taken seriously, but small enough not to diminishing returns. Additionally, incentives should be closely paired with the desired

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225 brings attention to the cost of using disposable bags and increases motivation to bring Moh r, 2013, p. 116). Incentives must also be visible or well advertised so that the target population will be aware of its existence and have a chance to participate. Finally, it is noted that reductions in consumption based on extrinsic motivations alone can rewards are very powerful and encourage more rapid behavior change, indirect rewards have been shown to be more effective in promoting long term behavioral change in a ff, Champion, Lauer, & Pahwa, 2013, p.5). Thus, it is important to consider the use of an intrinsic versus an extrinsic incentive based on an interventions time frame (Aronoff, Champion, Lauer, & Pahwa, 2013; Conn, 2009; McKenzie Mohr, 2013). Convenience As seen in Appendix I, up to 66.7% of participants indicated that they did not behave sustainably because activities, such as shorter showers or turning off lights, were considered to be inconvenient. According to the Self Perception theory, individuals co observations of their own behavior and the circumstances in which they occur (Bem, to engage in sustainable behaviors conveniently, the very act of engaging in those behaviors will shape their attitudes. For example, prior to introducing curbside recycling in one study, most individuals did not have strong attitudes regarding the importanc e of waste reduction. However, when these same individuals began to use their new curbside recycling bins their participation in recycling led them to view themselves as

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226 the type of person who believed that waste reduction was important (Burn & Oskamp, 198 6; McKenzie Mohr, 2013) . Thus, in the context of residence hall s environmental programs may be designed to make sustainable behaviors more convenient than the alternative, non sustainable activity. Some examples might be to place recycling bins in dormitor y rooms, provide closer parking for car poolers, install energy efficient appliances and lighting, occupancy sensors, low flow fixtures, and insulated windows. Early Education of Sustainable Practices As evident by the analysis of interview responses in Appendix I an average of 54.3% of participants indicated that they felt obligated to behave sustainably because it was a lifestyle that they had learned at home. For example, when such students were asked to explain why they felt it was i mportant to conser ve resources residents stated, conservation. It was very important to her while I was growing up so I would say that is o my family to protect the environment and preserve the resources that we have, so it i s important to me important because those things were instilled in me throughout somebody who never did that stuff to do them later in life (FH8_Female). It was also clear from the comparison of ESBs betw een East Village and Frank Hall that education must go beyond just the attainment of sustainability knowledge . For example, despite having the strongest knowledge of the LEED rating system and the certifi cation of their residence hall, the residents of East Village rarely exhibited sustainable behaviors as strong ly as the residents of Frank Hall. A s a result of their apparently sustainable

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2 27 upbringings , Frank Hall residents more readily adopted a sustainable lifestyle and chose to surround themselves with like minded reside nts by seeking resources such as the Thus, based on these findings and literature that examines the role education plays on developing sustainable societies, there is a consensus that environmental education must begin in the home and ideally early childhood education is about laying a sound intellectual, psychological, emotional, social and physical foundation for development and lifelong learning, it has an enormous potential in fostering values, attitudes, skills and behaviors that support Samuelsson & Kaga, 2008, p.12). As our first educators, Throughout our childhood and into our adul thood, individuals will consciously and unconsciously test these programmed behaviors, opting to replicate them or reject them (Gross, 2013). It is clear from studies of childhood education that parents, siblings, grandparents and other extended family mem bers can effectively undertake the instruction of sustainable practices, such as conserving water and energy. Thus, on campuses where formal sustainability education programs exist it is important to provide opportunities for families to participate so tha t they might continue to reinforce desired behaviors at home. Additionally, in areas where formal programs are not offered, community outreach programs might be established so that families can receive necessary education and pass that on to their children . In this way families and other discuss what could be done differently in daily ( Samuelsson & Kaga, 2008, p.13) .

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228 Theoretical C onsiderations for Studies on Campus Settings As described in the Understanding Environmentally Significant Behavior (pg. 52) section of this study, r esearch surrounding the conduct of young adults on campus settings suggest that subjective norms and behavioral intentions are predominate meta analysis of 8097 college students it was determined that young adults were more susceptible to subjective norms than older adul establish their self identity (Erikson, 1950). This case study was consistent with evidence from life span developmental psycho logy literature, which indicates that adolescents and young adults are particularly sensi tive to a real or perceived pressure to conform to social norms. As Rivis and Sheeran (2003) state: As a result of transitioning from junior to senior school, and then college to university, young people are frequently faced with the challenge of establish ing new friendships. Imitating the behavior of peers may therefore be an attempt to gain group acceptance and achieve categorization as a group member, which are strong needs among adolescents (p. 229). Thus, since adolescents and young adults have the mos t contact with their peers during their enrollment in educational institutions it is generally found that subjective norms play a critical role to these types of populations (Castro, Maddahian, Newcomb, & Bentler, 1987; Eiser & van der Pligt, 1984; Terry, Hogg & White 1999, Rivis & Sheeran, 2003). Additionally, this case study was in line with studies that have shown a strong connection between intentions and the behaviors of adolescents on campus settings. For example, in a study that employed the Theory of Planned B ehavior (TPB) to investigate the factors underlying intentions and frequency of use of cannabis amongst 249 college students, a strong correlation was found between intentions and the self -

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229 reported use of this drug (Connor & McM illan, 1999). Si milarly, in three studies that assessed the alcohol consumption of 178, 176, and 159 Leeds University students , a correlation of . 35, .50, and .37 was found between and their past consumption of alcohol. Furthermore, this study als o noted that the correlations between these and later behaviors was v irtually identical, at .35, .48 and .35 (Conne r, Warren, Close & Sparks, 1999 ). Finally in a study of 122 Griffith University students, various be havior theories including the T he ory of Reasoned Action and the Theory of Planned Behavior were used to explain alcohol use among young adults. A structured questionnaire was helped to rate variables on a 7 point unlikely likely scale. Students intentions, past behaviors , and the perceptio n of what important others thought they should do (subjective norms) proved to be the strongest predictors of behavior ( . The exploratory factor analysis conducted in this study indicated that three factors would be retained. Figures 4 13, 4 14, and 4 15 illustrate how t he rotation of reference axes significant ly load around the subjective norms construct in Factor 1 ; the altruistic and biospheric indicators of the value construct in Factor 2 ; a nd the attitude, behavioral intention , and personal norm constructs in Factor 3 . As previously described , subjective norms and behavioral intentions emerged as significant theoretical constructs in this study as expected , h owever, it was also found that at titudes, altruistic and biospheric values, and personal norms represent a strong connection to ESBs in the context of campus housing . It is believed that these additional constructs emerged amongst the student populations for a variety of reasons. For exam ple, on average, 19. As the l iterature

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230 surrounding subjective norms suggested, these additional construct s w ere prevalent due to t he age of the sample population . Such r esearch has shown age to be a demographic variable that is strongly associated with level of environmentalism (McMillan, Hoban, Clifford, & Brant, 1997 ; Müderrisoglu & Altanlar, 2011). Generally, younger adults are more likely to hold environmental attitudes than older adults because they are often less integrated into society and can more readily criticize industrial and governmental policies. A lso , the students at each of the universities are growing up in an era where environmental issues are readily discussed a nd debated ; making it easier for these young adults to be aware of their own environmental impacts and subsequently leading to a value in sustainable practices (Allitt, 2014; McMillan, Hoban, Clifford, & Brant, 1997). Studies have also concluded that resid ents of urban areas , such as those surround Emory Oxford, North Carolina Central University, and Appalachian State, generally associate with greater environmentalism than those in rural areas (McMillan, Hoban, Clifford, & Brant, 1997; Milton, 2013; Yu, Lor a Wainwright, Edmunds, & Thomas, 2013) . One explanation for this difference in attitudes is that urban residents often live in more polluted environments while rural dwellers often depend on their lands for economic purposes, such as agriculture. Thus, it may be said that the residents at each university are more aware of environmental natur e for t he aesthetic, intrinsic qualities esteemed by adherents of the New Environmental Paradigm Hob an, Clifford, & Brant, 1997, p.93) . Fin ally , interviews conducted in this study as well as other research has demonstrated how parents and guardians influence the environmental behaviors of young adults. For example, in a study that investigated the

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231 extent to which young adolescents environmental behaviors , such as the reuse of paper and recycling, it was found that parents influenced their recycling behaviors via sanctions and their re use of paper behavior via communi cation of problem knowledge ( Matthies, Selge, & Klöckner, 2012 ) . In a similar study, 601 Danish families were surveyed to determine the extent to which ryday pro environmental behavior was the outcome of their own pro environmental attitude s or the product of social influence wit hin the family. R esults show ed that the env ironmental behavior is heavily influenced by the dominating norms within the family and in particular by how strongly they are manif behavior ( Gronhoj & Thogersen, 2012 , p. 292 ). Therefore, in addition to the subjective norms and behavioral intention constructs suggest that altruistic and biospheric value s , attitude s , and personal norms should also be considered. Base on the cited beh s findings, strong evidence exists to support the influence that these additional constructs have on this type of population. Future studi es that examine similar populations could benefit by considering these constructs early in the development of their instruments as well as hone in on how these constructs manifested in their sample sites. Limitations and Future Studies While much was discovered in this study with regards performance and the theoretical constructs that influenced occupant behaviors in residence halls, a number of limitations and future research topics were a l so identified. This research was limited to investigating the prediction tools and relative occupants behaviors associated with WE Credit 3 Water Use Reduction and EA Credit 1 -

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232 Optimized Energy Performance of the LEED rating system . However, t he LEED rating system also includes other measurable c red its within the Sustainable Sites, Water Efficiency (WE) , Energy & Atmosphere (EA), and Indoor Environmental Quality categories that prediction tools and occupant behaviors may impact . For example, SS Credit 7.1 Heat Island Effect: Non Roof , WE Credit 1 Water Efficient Landscaping , WE Credit 3 Water Use Reduction , EA Credit 1 Optimized Energy Performance , EA Credit 3 Enhanced Commissioning , EA Credit 5 Measurement & Verification , and IEQ C redit 7.2 Thermal Comfort: V erification award points by allow i ng applican ts to make predictions on the performance of building system s or rely ing on building users to follow through on prescribed steps after final certification has been issued ( USGBC, 2013b) . However, the USGBC does not currently have a verification system to ensure that the buildings actu ally perform as predicted or that users complete the prescribed steps post occupancy . This particular aspect of the LEED rating system has been questioned by designers, architects , engineers , and energy experts who argue that because occupant behaviors and building performance is not tracked, certified buildings may be falling short of their sustainable goals ( Swearingen, 2014 ) . Therefore, future research may investigate how these prediction t ools can be more accurate , how user s environmentally significant behavior may impact these c redits , and how the long term performance of LEED certified buildings can be tracked and authenticated . By a ddressing these other categories , research will continu e to enhance the holistic whole building approach that the USGBC has strived for in their new LEED v4.0 revision . Data for the survey, resource tracking exercise, and interview was limited to a four week collection period between the months of October and November in 2013. This

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233 represents 25 % of a semester on a campus that hosts a Fall, Spring , and Summer session. While the ANSI/ASHRAE/IESNA 90.1 schedules for fans, hot water, and recommendations would be stronger if occupant behavior s were tracked for all three semesters and averaged for an entire year. In this way, the prediction tool could begin to account for behaviors that are a direct result of seasonal changes in climate. Ad ditionally, this and the theoretical constructs that influences behaviors revealed a number of insights that could be used to improve sustainability programs and contribute to the body of knowledge surrounding behav ioral theories. However, this study was limi ted to assessing each case population based on the collected and provided demographic profile information. F urther analysis may also investigate a variety of factors that literature ha s found to have som e in fl uence, positive or negative, on pro environmental behavio r such as economic and social status, and cultura l factors. As seen in this study, students from each case exhibited some unique characteristics that could be attributed to these. Thus, further inves tigation into these variables is could help to explain why individuals who are in similar LEED certified buildings respond differently to sustainability initiatives. Campus administrators may then use this research to tailor their environmental programs to respond to the external factors that are most applicable to their student body. Finally, analysis and exploratory factor analysis of occupant responses . W hile t hese analyses made it possible to identify the TPB and VBN constructs that most influenced resident

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234 ESBs, they are not able to suggest a new theoretical model for how these constructs influence behavior. Therefore, a path analysis of survey results would help to further illustr ate how occupants are influenced by the subjective norm, altruistic and biospheric value, attitude, intention, and personal norm constructs . A path analysis is an extension of multiple regressions that allows for the analysis of more complicated models. Th is statistical tool examines situations in which there are several final dependent variables. determine whether a specific model is correct; it can only determine whe ther the data Conclusions Despite the growing use of the LEED rating system in the higher education market, research has indicated that occupant behavior s remain an obstacle to long term building efficiency ( Petersen, Shunturov, Janda, Platt, & Weinberger, 2007 ). As previously described in the Literature Review (pg. 25 ) of this study, the USGBC has stated that flaws with energy modeling and inaccurate assumptions regarding occupant behavior often results in disparities between how buildings are designed to operate and how they actually perform (USGBC, 2011a). As a consequence of oversimplifying occupancy schedules, water use trends, and underestimating the importan t role that users plays in building performance, the variation between predicted and actual resource consumption was approximately 48.8% in this study and has been seen to range between 30% and 100% in other research ( Azar & Menassa, 2010; Turner, 2006; Yu delson, 2010 ). Thus, the three case s in this research and the others , like those described in the Pacific Lutheran University (pg. 48) and Orego n Health and Science University (pg. 49) sections of this study , are examples of this incongruity and

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235 underscore how technological features alone cannot guarantee high building performance. In an effort to improve future predictions for higher education settings, their residence halls, and ultimately the next revision of the LEED rating system, this study first sought to identify end user consumption trends as they related to water and energy. sustainability programs and contribute to the body of knowledge surrounding behavioral the ories. Overall, findings from 317 survey responses, 135 resource tracking forms, and 45 interviews revealed that occupants in residence halls accessed water fixtures less often for longer periods of time and energy related systems more often for longer per iods of time than stipulated by the current LEED default settings and ANSI/ASHRAE/IESNA 90.1 standard . Both prediction tools were limited in their scope and did not accurately respond to the unique characteristics of student residents. The ANSI/ASHRAE/IESN A 90.1 standard in particular was clearly tailored for commercial buildings and thus, does not re present the consumption patterns found in residential setting s . occupant consumption and did not appropriately represent a full range of sustainable and unsustainable behaviors. Thus, this case study provides evidence that LEED default settings and referenced standards need to be further investigated so that they can better reflect the ful l range of sustainable and unsustainable behavior s found in residence halls . Final ly, it was found that resident ESBs were most influenced by the subjective norm, altruistic and biospheric values, attitude, behavioral intention, and personal norm constructs from the TPB and VBN theories. The relationship between

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236 these constructs and the consumption of resources revealed the importance of education, upbringing, and monetary incentives in residence halls . Thus, r ecommendations are given to support the improved performance of residence halls through enhances prediction tools, education prog rams, and community based social marketing techniques . The LEED rating system is a perfectible instrument and as we learn more about the contribution of user behaviors to building performance, the system should evolve to more specifically address this comp onent as a key factor. Thus, the ultimate goal of this research is to leverage findings to knowledgeably recommend improvements for the next LEED rating system and its certified buildings. Additionally, study findings may help to justify further refine ment s to the referenced industry standards and the LEED default settings. As a result, integrated design teams may rely on the provided tools for predicting water and energy consumption and the variance between designed and actual performance may be curtailed. By highlighting the relationship between occupant behaviors and the actual consumption of water and energy, design decisions and building operation methods may be better guided to reliably result in the high performance of buildings and the conservation o f resources. By conducting this research those within the higher education building sector will have additional tools to foster sustainable behaviors and address the overall consumption of resources on their campuses. For many years, the higher education sector has made efforts to respond to the mounting pressure from impending litigation, international and domestic regulations, and shareholder s , to adopt sustainable practices . The hundreds of institutions that have become signatories and adopters of

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237 educa tional charters and rating systems such as the American College and University made this evident. As leaders in the role of training and educating future generations, colleges and universities have a responsibility to provide sustainable built environments that demonstrate a reduction in water and energy use. Additionally, the successful application of sustainable practices has given campuses cost saving opportunities and an additio nal competitive edge for recruiting and retaining students, faculty and staff. Thus, by closing the gaps that currently exist between user behaviors and target efficiency goals, campus settings may markedly meet their pro environmental commitments and enha nce their reputational values. It is hoped that this study will serve as a foundation for continued research in environmentally significant behaviors and help to guide the progress of sustainable design practices .

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238 APPENDIX A MURDY HALL FLOOPLANS FIRST FLOOR ELIZER RESIDENCE HALL

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239 SECOND FLOOR ELIZER RESIDENCE HALL

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240 THIRD FLOOR ELIZER RESIDENCE HALL

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241 FIRST FLOOR MURDY RESIDENCE HALL

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242 SECOND FLOOR MURDY RESIDENCE HALL

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243 THIRD FLOOR MURDY RESIDENCE HALL

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244 APPENDIX B CHIDLEY NORTH RESIDENCE HALL FLOOPLANS FIRST FLOOR CHIDLEY NORTH RESIDENCE HALL SECOND FLOOR CHIDLEY NORTH RESIDENCE HALL

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245 THIRD FLOOR CHIDLEY NORTH RESIDENCE HALL FOURTH FLOOR CHIDLEY NORTH RESIDENCE HALL

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246 APPENDIX C FRANK RESIDENCE HALL FLOOPLANS FIRST FLOOR FRANK RESIDENCE HALL SECOND FLOOR FRANK RESIDENCE HALL

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247 THIRD FLOOR FRANK RESIDENCE HALL FOURTH FLOOR FRANK RESIDENCE HALL

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248 FIFTH FLOOR FRANK RESIDENCE HALL SIXTH FLOOR FRANK RESIDENCE HALL

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249 APPENDIX D IRB APPROVAL

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250 APPENDIX E CONSENT FORMS Informed Consent Protocol Title: Environmentally Significant Behaviors in LEED Residence Halls Survey Please read this consent document carefully before you decide to participate in this study. Purpose of the research study: The goal of this study is to knowledgeably recommend improvements for the U.S. Green Building Leadership in Energy and Environmental Design an assessment tool focuses on reducing the ecological footprint of built environments and implicitly, to help advance sustainability on collegiate campuses and elsewhere. What you will be asked to do in the study: This survey is designed to understand the consumption of water and energy in your residence hall. You will be asked to respond to 9 sections of multiple choice questions. Questions focus on your environmentally significant behaviors. Environmentally significant behavior is defined as the extent to which a behavior changes the availability of materials and resources in the environment. Finally, at the conclusion of the survey you will be asked to provide your demographic information and information regarding the length of time that you have lived in your residence hall. Time Required: Approximately 30 minutes Risks/Benefits: There are no direct benefits and there is no more than minimal risks to the participants associated with this study. Compensation: Students will be compensated with a coupon book valued at $18.00. Good for Hershey Co. products. Confidentiality: Your identity will be kept confidential to the extent provided by law. Your information will be assigned a code number. Your name will not be used in any report. Voluntary participation: Your participation in this study is completely voluntary. There is no penalty for not participating.

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251 Right to withdraw from the study: You are free to withdraw your consent to participate and may discontinue your participation at any time without consequence. Whom to contact about your rights as a research participant in the study: IRB02 Office, Box 112250, University of Florida, Gainesville, FL 32611 2250; phone 352 392 043 I have read the above consent form and would like to participate in this study. First Name __________________________ Last Name _________________________________ I verify that I am at least 18 years old or older. Yes ___________ No _____________

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252 Informed Consent Protocol Title : Environmentally Significant Behaviors in LEED Residence Halls Interview Please read this consent document carefully before you decide to participate in this study. Purpose of the research study: The goal of this study is to knowledgeably recommend improvements for the U.S. an assessment tool focuses on reducing the ecological footprint of built environments and implicitly, to help advance sustainability on collegiate campuses and elsewhere. What you will be asked to do in the study: This interview is designed to better understand your environmentally significant behaviors and how they relate t o your consumption of resources in your residence hall. Environmentally significant behavior is defined as the extent to which a behavior changes the availability of materials and resources in the environment. As a participant in this interview, you will be asked to discuss your consumption of resources after tracking your use of water and energy from select locations in your residence hall (bathroom sinks, toilets, showerheads, kitchen sinks, lights, outlets, and air conditioners) for three days. Consumpt ion from each of these areas will be recorded on a formatted tracking form provided to you. During the interview you will be asked to respond to a series of open ended questions, which have been developed to further investigate your environmentally signifi cant behaviors. This interview will be conducted at a time/date of your choice via teleconference (web cam) after I have received a copy of your signed consent form. The signed consent form may be delivered via email. Time Required: Approximately 1 hour Risks/Benefits: There are no direct benefits and there is no more than minimal risks to the participants associated with this study. Compensation: Students are compensated with coupons valued at $3.00 for Breyers, Good Humor, Magnum, and Popsicle product s. Confidentiality: With your permission I would like to videotape this interview. Only the research team, including myself and my research advisors, will have access to the videotape, which will

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253 be transcribed, removing any identifiers during transcripti on. The recording will be erased at the conclusion of the study. Your identity will be kept confidential to the extent provided by law and your identity will not be revealed in the final manuscript. Voluntary participation: Your participation in this stud y is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from the study at anytime without consequence. Whom to contact about your rights as a research participant in the study : IRB02 Office, Box 112250, University of Florida, Gainesville, FL 32611 2250; phone 352 392 0433 Agreement: I have read the procedure described above. I voluntarily agree to participate in the procedure and I have received a copy of this description. Participant: ___________________________ Dat e_________________ Principal Investigator : __________________ Dat e________________

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254 APPENDIX F SURVEY INSTRUMENT

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266 A PPENDIX G RESOURCE TRACKING IN STRUMENT DAY 1 LEED Residence Halls Water and Energy Consumption Tracking Form Name:_________________________ Date:________________ 1. How long in total did the water run and at what time of day did you use each of the following fixtures in your residence hall: Length water ran for Time of day Length water ran for Time of day Length water ran for Time of day Length water ran for Time of day Length water ran for Time of day Show er Ex. 8 min . Ex. 9:00am Shower cont. Bathroom sink Bathroom sink cont. Toilet Toilet cont. Kitchen sink Kitchen sink cont. 2. How long in total and at what time of day did you use each of the following items in your residence hall: Length item ran for Time of day Length item ran for Time of day Length item ran for Time of day Length item ran for Time of day Lengt h item ran for Time of day Bedroom Air Conditioner Bedroom Air Conditioner Cont. Lights in your bedroom Lights in your bedroom cont.

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267 A PPENDIX H INTERVIEW INSTRUMENT Environmentally Significant Behavior in L EED Residence Halls Interview 1 (LEED). Can you explain the role that the USGBC and LEED played in the construction of your residence hall? 1a. Can you identify the sustainable features in your residence hall? 2 (Water). After completing the resource tracking exercise, was your water consumption more, less, or about what you expected? 2a. What do you think contributed to you using ( interviewer refers to level of consumption mentioned ) ? 2 b. Do you think the green features in your building are contributing to water conservation ( interviewer may refer to low flow faucets in bathrooms and kitchens, showerheads, toilets )? 2 c. Are you satisfied with these green features ( water efficiency )? 3 (Energy). After completing the resource tracking exercise, was your energy consumption more, less, or about what you expected ? 3a. What do you think contributed to you using ( interviewer refers to level of consumption mentioned )? 3 b. Do you think the green features in your building are contributing to energy conservation ( interviewer may refer to controlled air conditioning, l ighting sensors )? 3 c. Are you satisfied with these green features ( lighting levels, thermal comfort )? 4 (Values ). ( Interviewer reads the scenario below to determine your participants value orientation egoistic, altruistic, biospheric ) If you bough t an energy efficient car instead of an standard gas car would if be because it was cheaper on fuel , because it has lower emissions and is healthier for people, or because it produces less CO2 which protects the environment ? 4a. Why is ( interviewer refers to scenario mentioned ) important to you? 4b. How does your desire to ( interviewer refers to scenario mentioned ) m otivate your co nsumption of water and energy in your residence hall?

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268 5 (Beliefs). Based on the following scale, how would you describe you rself ? 5a. Why have you chose n this level of environmental belief ? 5b. (AC) Are consequences if you behave un sustainably in your residence hall ? Are you concerned about these consequences? 5c. (AR) Do you feel responsib le for the se consequence s fo r example, if the energy or water bill cost more than your housing staff anticipated ? 6 (Attitudes). How important is it to you to reduce water consumption in your residence hall? How important is it to you to reduce energy consumption in your residence h all? 6a. Why is it/is it not important to you to conserve these resources? 6b. What could be done to reduce more water and energy in your residence hall? 7 (Subjective/Personal Norm). With regards to your environmental behavior , whose opinion is the most important to you (Interviewer should check groups mentioned by resident) ? Why are their opinions important to you? ____ Housing Staff ____ Friends ____ Neighbors in your residence hall ____ Family ____ College faculty ____ Other 7a. How would (interviewer refers to referent group mentioned) behave sustainably? 7b. Why do you think (interviewer refers to referent group mentioned) would find these sustainable behaviors important? 7c. Do you personally feel obligated to conserve water and energ y in your residence hall? 7d. Why do you/do you not think it is important to conserve these resources?

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269 7e. Do your environmental behaviors change when you are not in your residence hall ( interviewer may suggest when residents go home for breaks or leave on vacation )? 8 (Perceived behavioral controls). Is there anything that might make it difficult for you to conserve water and energy in your residence hall (Interviewer should check items mentioned by resident) ? ____ Money (lack of monetary incentive) ___ _ Time (extra time turning faucets off/unplugging electronics) ____ Knowledge (educated on green features such as low flow faucets in bathroom and kitchens, showerheads, toilets/HVAC controls, lighting sensors) ____ Authority (Control over existing features) ____ Cooperation of other residents ____ Other 8a. How frequently do you encounter (interviewer refers to items mentioned) in your residence hall? 8b. Is there anything that might make it easier for you to conserve water and energy in your residence hall (Interviewer should check items mentioned by resident). ____ Money ____ Time ____ Knowledge ____ Authority ____ Cooperation of other residents ____ Other 8c. How frequently do you encounter (interviewer refers to items mentioned) in your residence hall? 9 (Behavioral intention). How likely is it that you will reduce your water and energy consumption next semester? 9a. How would you do this? 9b. Could you describe the expectations of your future environmental behavior after leaving this residence hall?

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270 APPENDIX I QUALITATIVE INTERVIEW ANALYSIS CODES AND FINDING S Question Definition Code East Village N=15 Chidley North N=17 Frank Hall N=13 1. Role that the USGBC or LEED played Aware that they are living in an environmentally certified hall but may/may not have been able to recall the LEED system by name. Aware of certification 11 73.3% 1 5.9% 7 53.8% Could describe LEED and/or USGBC in detail Described in some detail 8 53.3% 0 0.0% 1 7.7% Observed signage which described the LEED certification of the building. LEED certification signage 5 33.3% 1 5.9% 4 30.8% Heard of the name LEED through third party, such as a housing staff or survey. However, students may not have been able to describe what LEED was. Recognizes the name LEED 11 73.3% 5 29.4% 6 46.2% Did not know they were living in a LEED certified building. Unaware of LEED certification 4 26.7% 16 94.1% 6 46.2% Completely unfamiliar with USGBC/LEED or both. Unfamiliar 8 53.3% 17 100% 9 69.2% 1a. Sustainable features in residence Recognized the dual flush toilet systems in the building Building dual flush 0 0.0% 13 76.5% 8 61.5% Recognized the installation of water bottle filling stations in the building and their contribution to waste reduction Building refill station 5 33.3% 0 0.0% 3 23.1% Recognized the installation of an occupancy sensored Building sensored lights 10 66.7% 8 47.1% 9 69.2%

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271 light in the building (ie. in rooms, hallways, communal restrooms, laundry rooms, elevators) Recognized the installation of solar panels on the roof of the building Building solar panels 0 0.0% 0 0.0% 5 38.5% Observed signage in or around the building which described the availability of sustainable technologies Building sustainable feature signage 0 0.0% 3 17.6% 1 7.7% Recognized the building regulated temperature range. Building thermostat control 0 0.0% 4 23.5% 4 30.8% Student is a part of a living green community initiative or other environmental society Environmental Society 0 0.0% 0 0.0% 8 7.7% Recognized that the use of hand dryers reduces the generation of waste Hand dryers 0 0.0% 0 0.0% 3 7.7% Recognized the use of large window which allowed access to natural daylight Large window 0 0.0% 0 0.0% 9 7.7% Recognized the installation of a low flow or sensored water fixture in the building (ie. showerhead, sink). Low flow building fixture 5 33.3% 1 5.9% 5 15.4% Recognizes the use of low VOC paints and its contribution to indoor quality Low VOC paint 3 20.0% 0 0.0% 1 0.0% Provided an example that was misidentified as a sustainable feature in the building (ie. universal design element, fire safety component). Misidentified building feature 0 0.0% 3 17.6% 4 0.0% Recognizes the collection of water on site Onsite water collection 4 26.7% 0 0.0% 8 0.0%

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272 Recognized the availability of recycling bins and stations. Recycling program 5 33.3% 1 5.9% 3 7.7% Was unfamiliar with the sustainable features in their building. Unfamiliar with sustainable features 0 0.0% 1 5.9% 0 0.0% 2. Water consumption Based on tracking exercise water consumption was less than expected Water was less 2 13.3% 2 11.8% 4 30.8% Based on tracking exercise water consumption was more than expected Water was more 2 13.3% 3 17.6% 2 15.4% Based on tracking exercise water consumption was as expected Water was the same 11 73.3% 12 70.6% 7 53.8% 2a. Largest contributor to water use Occupant feels that having a busy social or class schedule keeps them out of the building and contributes the most to their conservation of water Busy water schedule 2 13.3% 1 5.9% 2 15.4% Occupant feels that fast showers helps them consume less water Fast showers 2 13.3% 1 5.9% 2 15.4% Occupant feels that fewer toilet uses are contributing to their conservation of water Fewer toilets 1 6.7% 0 0.0% 0 0.0% Occupant attributes their use of water to their adherence to a routine Routine water use 3 20.0% 3 17.6% 4 30.8% Occupant feels that their showers contribute the most to their consumption of water Showers 8 53.3% 14 82.4% 6 46.2% Occupant feels that their use of lavatory/kitchen sinks contribute the most to Sink 3 20.0% 1 5.9% 3 23.1%

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273 their consumption of water Occupant feels that their toilet use contribute the most to their consumption of water Toilets 2 13.3% 3 17.6% 1 7.7% 2b. Features contributing to water conservation Recognized the dual flush toilet systems Dual Flush toilet 8 53.3% 10 58.8% 9 69.2% Recognized the installation of a low flow or sensored water fixture (ie. showerhead, sink) Low flow fixtures 9 60.0% 8 47.1% 6 46.2% Provided an example that was misidentified as a sustainable feature (ie. universal design element, fire safety component) Misidentified feature 0 0.0% 2 11.8% 0 0.0% Recognized the installation of water bottle filling stations and their contribution to waste reduction Refill station 6 40.0% 0 0.0% 2 15.4% Observed signage which described the availability of sustainable technologies Sustainable feature signage 3 20.0% 3 17.6% 3 23.1% Was unfamiliar with the water conserving features in their building. Unfamiliar with water saving features 2 13.3% 3 17.6% 2 15.4% Noted that user awareness is a characteristic that contributes to water conservation User awareness 0 0.0% 0 0.0% 1 7.7% 3. Energy consumption Based on tracking exercise energy consumption was less than expected Energy was less 4 26.7% 3 17.6% 3 23.1% Based on tracking exercise energy consumption was more than expected Energy was more 5 33.3% 6 35.3% 6 46.2% Based on tracking Energy was 6 40.0% 8 47.1% 4 30.8%

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274 exercise energy consumption was as expected the same 3a. Largest contributor to energy use Occupant feels that their use of the air conditioner contributes the most to their consumption of energy Air Conditioner 8 53.3% 9 52.9% 4 30.8% Occupant feels that having a busy social or class schedule keeps them out of the building and contributes the most to their conservation of energy Busy energy schedule 5 33.3% 1 5.9% 1 7.7% Occupant feels that utilizing existing natural light contributes the most to their conservation of energy Existing natural light 1 6.7% 1 5.9% 1 7.7% Occupant feels that keeping lights off contributes the most to their conservation of energy Keeping lights off 4 26.7% 4 23.5% 1 7.7% Occupant feels that plugged in and unused electronics contributes the most to their energy use Leaving electronics plugged in 1 6.7% 3 17.6% 2 15.4% Occupant feels that their use of the lights contributes the most to their consumption of energy Lights 4 26.7% 5 29.4% 6 46.2% Occupant feels that turning off the TV when not in use contributes the most to their conservation of energy Turing off the TV 0 0.0% 1 5.9% 0 0.0% Occupant feels that unplugging unused electronics contributes the most to their conservation of Unplugging unused electronics 0 0.0% 1 5.9% 0 0.0%

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275 energy 3b. Features contributing to energy conservation Recognized the use of energy efficient appliances (ie. washers and dryers) Appliances 2 13.3% 0 0.0% 0 0.0% Recognized the use of energy saving building materials (such as insulation) Building materials 2 13.3% 0 0.0% 0 0.0% Housing staff actively promotes the reduction of energy use Promotion of energy reduction 0 0.0% 1 5.9% 0 0.0% Recognized the installation of an occupancy sesored light (ie. in rooms, hallways, communal restrooms, laundry rooms, elevators) Sensored lights 15 100.0% 16 94.1% 13 100.0% Recognized the installation of solar panels on the roof Solar panels 0 0.0% 0 0.0% 6 46.2% Was unfamiliar with the energy conserving features in their building. Unfamiliar with energy saving features 0 0.0% 1 5.9% 0 0.0% 4. Values Suggests an egoistic value orientation Cheaper on fuel 11 73.3% 15 88.2% 8 61.5% Suggests an altruistic value orientation Healthier for people 1 6.7% 0 0.0% 1 7.7% Suggests an biospheric value orientation Protects the environment 5 33.3% 3 17.6% 6 46.2% 4a. Why values Concern for the health safety and welfare of other people and/or future generations Concern for health 1 6.7% 1 5.9% 5 38.5% Values the health, safety and preservation of the natural environment Environment 6 40.0% 2 11.8% 6 46.2% Occupant has a long commute or frequently uses the car Frequent use of car 2 13.3% 1 5.9% 2 15.4% Occupant expresses the desire to save Save money 10 66.7% 13 76.5% 5 38.5%

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276 money Value orientation is associated with being efficient and saving the occupant time Saves time 0 0.0% 1 5.9% 0 0.0% Occupant expresses a sense of having a small budget Tight budget 3 20.0% 7 41.2% 2 15.4% 4b. How values motivate consumption Value orientation helps occupant to be more aware of their consumption of resources Aware of use 7 46.7% 2 11.8% 8 61.5% Saving money is not a motivational factor because cost are set regardless of use Cost is set 6 40.0% 9 52.9% 4 30.8% Value orientation does not motivate the occupants consumption of water or energy Does not motivate consumption 7 46.7% 12 70.6% 5 38.5% The occupants desire to save time allows them to save resources because they use electronics/fixtures as efficiently as possible Efficiency 1 6.7% 1 5.9% 0 0.0% Although value orientation does not currently motivate consumption the occupant suggested that they could if changes were made (such as posting energy and water bills, charging for actual usage) Potential for future motivation 1 6.7% 5 29.4% 1 7.7% Motivated to save resources because it helps to prepare one for future utility bills. Preparing for future 0 0.0% 1 5.9% 0 0.0% 5. Beliefs Occupant identifies self as neutral Neutral 3 20.0% 12 70.6% 1 7.7% Occupant identifies self as not Not environmental 0 0.0% 0 0.0% 0 0.0%

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277 environmental Occupant identifies self as somewhat not environmental Somewhat not 2 13.3% 1 5.9% 0 0.0% Occupant identifies self as somewhat pro environmental Somewhat pro 10 66.7% 4 23.5% 7 53.8% Occupant identifies self as very pro environmental Very pro 0 0.0% 0 0.0% 5 38.5% 5a. Why beliefs Occupant will conserve but might just as frequently forget to maintain sustainable behaviors Breaks even 3 20.0% 5 29.4% 0 0.0% Behaves sustainably when it is convenient Convenience 6 40.0% 7 41.2% 3 23.1% Needs further evidence to believe that the environment is impacted by human behaviors Evidence 2 13.3% 1 5.9% 0 0.0% Occupant is conscious of use and is interested in environmental topics and/or legislation Interest in environment 8 53.3% 2 11.8% 12 92.3% Behaving sustainably is not readily recalled unless reminded Needs a reminder 1 6.7 % 4 23.5% 0 0.0% Environmental consciousness is not considered a priority at this time Not a priority 2 13.3% 4 23.5% 0 0.0% 5b. AC Occupants believes that a consequence exists but has not witnessed it Believes so 3 20.0% 4 23.5% 2 15.4% Occupant identified a consequence for using too many resources in their residence hall. Consequence present 1 6.7% 0 0.0% 2 15.4% Occupant does not believe that a consequence exists (this includes reprimands from housing staff and may No consequence exist 12 80.0% 13 76.5% 9 69.2%

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278 also include reprimands from roommates) It is not believed that other occupants consider similar consequences Others are not concerned 5 33.3% 6 35.3% 2 15.4% 5c. AR Occupant does not consider themselves to be a significant contributor to the overall consumption in residence hall No recognition 6 40.0% 7 41.2% 3 23.1% Occupant recognizes their contribution to the overall consumption at their residence hall Recognizes contribution 5 33.3% 4 23.5% 9 69.2% Occupant generally does not feel responsible but can see how their usage technically contributes to overall consumption Some recognition 4 26.7% 6 35.3% 1 7.7% 6. Attitude energy On a scale from 1 10, occupant considers energy conservation to be a 10 Energy 10 1 6.7% 1 5.9% 2 15.4% On a scale from 1 10, occupant considers energy conservation to be a 3 Energy 3 2 13.3% 2 11.8% 0 0.0% On a scale from 1 10, occupant considers energy conservation to be a 3.5 Energy 3.5 1 6.7% 1 5.9% 0 0.0% On a scale from 1 10, occupant considers energy conservation to be a 4 Energy 4 1 6.7% 0 0.0% 0 0.0% On a scale from 1 10, occupant considers energy conservation to be a 4.5 Energy 4.5 0 0.0% 0 0.0% 1 7.7% On a scale from 1 10, occupant considers energy conservation to be a 5 Energy 5 3 20.0% 6 35.3% 0 0.0%

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279 On a scale from 1 10, occupant considers energy conservation to be a 5.5 Energy 5.5 1 6.7% 0 0.0% 0 0.0% On a scale from 1 10, occupant considers energy conservation to be a 6 Energy 6 3 20.0% 1 5.9% 1 7.7% On a scale from 1 10, occupant considers energy conservation to be a 6.5 Energy 6.5 1 6.7% 4 23.5% 0 0.0% On a scale from 1 10, occupant considers energy conservation to be a 7 Energy 7 2 13.3% 1 5.9% 3 23.1% On a scale from 1 10, occupant considers energy conservation to be a 7.5 Energy 7.5 0 0.0% 1 5.9% 0 0.0% On a scale from 1 10, occupant considers energy conservation to be a 8 Energy 8 0 0.0% 0 0.0% 6 46.2% 6. Attitude water On a scale from 1 10, occupant considers water conservation to be a 10 Water 10 1 6.7% 1 5.9% 2 15.4% On a scale from 1 10, occupant considers water conservation to be a 2 Water 2 0 0.0% 1 5.9% 1 7.7% On a scale from 1 10, occupant considers water conservation to be a 2.5 Water 2.5 0 0.0% 2 11.8% 0 0.0% On a scale from 1 10, occupant considers water conservation to be a 3 Water 3 1 6.7% 0 0.0% 0 0.0% On a scale from 1 10, occupant considers water conservation to be a 3.5 Water 3.5 1 6.7% 1 5.9% 0 0.0% On a scale from 1 10, occupant considers water conservation to be a 4 Water 4 0 0.0% 0 0.0% 1 7.7% On a scale from 1 10, Water 5 6 40.0% 6 35.3% 0 0.0%

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280 occupant considers water conservation to be a 5 On a scale from 1 10, occupant considers water conservation to be a 5.5 Water 5.5 1 6.7% 2 11.8% 0 0.0% On a scale from 1 10, occupant considers water conservation to be a 6 Water 6 3 20.0% 2 11.8% 1 7.7% On a scale from 1 10, occupant considers water conservation to be a 6.5 Water 6.5 1 6.7% 1 5.9% 2 15.4% On a scale from 1 10, occupant considers water conservation to be a 7 Water 7 1 6.7% 0 0.0% 4 30.8% On a scale from 1 10, occupant considers water conservation to be a 7.5 Water 7.5 0 0.0% 1 5.9% 0 0.0% On a scale from 1 10, occupant considers water conservation to be a 8 Water 8 0 0.0% 0 0.0% 2 15.4% 6a. Why attitude Occupant feels that conservation is important because it considerate to share resources with others Consideration for other 2 13.3% 1 5.9% 3 23.1% Occupant feels that conservation is important to contribute to environmental health Contribute to environmental health 1 6.7% 0 0.0% 10 76.9% Occupant feels that conservation is convenient to help the environment Convenient to do 2 13.3% 2 11.8% 0 0.0% resource because it is perceived to be an expensive commodity/an expense that the Expensive resource 1 6.7% 3 17.6% 4 30.8%

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281 occupant will face in the future Occupant is not actively aware of their own consumption/aware of how to reduce their consumption Lack of awareness 2 13.3% 1 5.9% 0 0.0% Conserving resources is not supported by their roommate/general community so occupant is discouraged from conserving for themselves Lack of community support 1 6.7% 3 17.6% 1 7.7% Occupant feels that more important because resources are a necessity Necessity 1 6.7% 2 11.8% 0 0.0% Occupant does not believe that they receive a financial benefit for conserving resources in their residence halls No financial benefit 1 6.7% 3 17.6% 1 7.7% Occupant does not believe that they are personally affected by conserving resources in their residence halls No personal impacts 1 6.7% 3 17.6% 1 7.7% Not a consideration that always occurs to the occupant on a day to day basis (may be due to lack of convenience) Not a consideration 10 66.7% 2 11.8% 1 7.7% Not more important to conserve because occupant does not feel that they use very much in the first place Not much used 2 13.3% 4 23.5% 2 15.4% Occupant feels that conservation is important because resources are taken for granted notes lack of access by others, or Taken for granted 0 0.0% 2 11.8% 0 0.0%

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282 need to contribute to a greater good) 6b. What could reduce more water and energy If occupants are held accountable for their unsustainable actions then they would reduce their consumption Accountability 1 6.7% 2 11.8% 1 7.7% Occupant believes that the addition/or adjustment of building technologies will help to further reduce consumption (sensored sinks faucets, motion sensored lights, shower times, etc) Additional technologies 11 73.3% 10 58.8% 6 46.2% Occupant believes that if residents were charged for utility usage then they would reduce their consumption Charge for utility usage 0 0.0% 4 23.5% 1 7.7% Occupant believes that if residents were better informed of the importance of sustainable behaviors/or conservation opportunities then they would reduce their consumption Improve resident awareness 9 60.0% 5 29.4% 11 84.6% Does not believe that or cannot recall if an effective method exists for reducing resource consumption in the residence hall Not effective 2 13.3% 4 23.5% 0 0.0% Occupant believes that if more signage was posted then residents would reduce their consumption Provide signage 0 0.0% 1 5.9% 1 7.7%

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283 7. Subjective Norms own environmental behavior, college most important College faculty 2 13.3% 1 5.9% 3 23.1% own environmental opinion is the most important Expert 2 13.3% 6 35.3% 4 30.8% own environmental opinion is the most important Family 7 46.7% 8 47.1% 4 30.8% own environmental opinion is the most important Friends 7 46.7% 1 5.9% 3 23.1% own environmental behavior, housing most important Housing staff 2 13.3% 4 23.5% 3 23.1% own environmental opinion is the most important Neighbors 1 6.7% 1 5.9% 0 0.0% 7a. How subjective norm Occupant identified a conscious use of resources as a methods for behaving sustainably Be conscious 1 6.7% 2 11.8% 4 30.8% Occupant could not identify how their referent group would behave sustainably Could not identify 2 13.3% 0 0.0% 0 0.0% Occupant identified owning energy efficient bulbs/appliances as a method for behaving sustainably Energy efficient bulbs 3 20.0% 1 5.9% 1 7.7% Occupant identified owning an energy efficient car/alternative transportation as a Energy efficient car 0 0.0% 1 5.9% 1 7.7%

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284 method for behaving sustainably Occupant identified informing others as a method for behaving sustainably Inform others 3 20.0% 4 23.5% 4 30.8% Occupant identified building insulation or insulated windows as a method for behaving sustainably. Install insulation 1 6.7% 0 0.0% 0 0.0% Occupant identified limited showers/low flow shower heads as a method for behaving sustainably Limit showers 7 46.7% 9 52.9% 7 53.8% Occupant identified limited time indoors as a method for behaving sustainably Limit time indoors 0 0.0% 1 5.9% 1 7.7% Occupant identified limited use of air conditioner as a method for behaving sustainably Limit use of AC 4 26.7% 2 11.8% 3 23.1% Occupant identified limited cellphone use as a method for behaving sustainably Limit use of cellphone 0 0.0% 1 5.9% 0 0.0% Occupant identified turning off/unplugging electronics as a method for behaving sustainably (includes TVs, radios, computers, cellphones) Limit use of electronics 2 13.3% 2 11.8% 2 15.4% Occupant identified turning off lights/use of natural light as a method for behaving sustainably Limit use of lights 6 40.0% 9 52.9% 7 53.8% Occupant identified limited sink/use of low flow faucets use as a method for behaving sustainably Limit use of sinks 8 53.3% 1 5.9% 6 46.2% Occupant identified recycling, reusing, or composting as a Recycle 5 33.3% 5 29.4% 6 46.2%

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285 method for behaving sustainably Occupant identified owning solar panels or solar water heaters as a methods for behaving sustainably Solar power features 1 6.7% 2 11.8% 4 0.0% 7b. Why subjective norm Occupant believes that their referent group behaves sustainably because they appreciate the access they have to resources/and or understand that others opportunities Appreciate access 2 13.3% 1 5.9% 0 0.0% Occupant believes that their referent group behaves sustainably because they care about the health, safety, wellness of the environment Cares about environment 5 33.3% 8 47.1% 9 69.2% Occupant believes that their referent group behaves sustainably because they do not like to be wasteful of resources or money 4 26.7% 4 23.5% 5 38.5% Occupant believes that their referent group behaves sustainably because they care about future generations access to resources and/or a healthy environment Future generations 4 26.7% 3 17.6% 6 46.2% Occupant believes that their referent group behaves sustainably because they want to prevent global warming Global warming 1 6.7% 1 5.9% 0 0.0% Occupant believes that their referent group behaves Knowledge of impacts 2 13.3% 2 11.8% 4 30.8%

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286 sustainably because they are knowledgeable about user impacts to the environment Occupant believes that their referent group behaves sustainably because learned from home, school, or a club Learned behavior 0 0.0% 2 11.8% 1 7.7% Does not connect referent group actions to a real desire to protect the environment No connection 3 20.0% 1 5.9% 0 0.0% 7c. Personal Norms Occupant personally does not feel obligated to conserve resources Not obligated 3 20.0% 8 47.1% 1 7.7% Occupant personally feels mildly obligated to conserve resources (particularly when they are convenient) Somewhat obligated 8 53.3% 8 47.1% 4 30.8% Occupant personally feels very obligated to conserve resources Very obligated 4 26.7% 1 5.9% 8 61.5% 7d. Why personal norms Occupant does not feel that it is necessary to conserve more than what is convenient/more than what others are conserving around them Above necessary 4 26.7% 1 5.9% 0 0.0% Obligation is driven by a cost incentive Driven by cost 3 20.0% 7 41.2% 4 30.8% Occupant is driven to protect the natural environment Driven by environment 5 33.3% 0 0.0% 4 30.8% Occupant is driven not to waste resources Driven by waste 5 33.3% 1 5.9% 7 53.8% Obligation to conserve resources was previously established at home Habit from home 7 46.7% 8 47.1% 9 69.2% Conservation Learned in 1 6.7% 1 5.9% 1 7.7%

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287 techniques were previously practiced in an educational entity (school, club) school Consumption is already low in residence hall (perhaps due to existing technologies or personal efforts) Low consumption 0 0.0% 2 11.8% 1 7.7% Occupant is unsure of how to conserve resources/does not know why it would be important to save resources in the residence hall Low knowledge 2 13.3% 2 11.8% 0 0.0% Obligation to conserve resources was not previously established at home Not a habit from home 1 6.7% 5 29.4% 2 15.4% 7e. Change in behavior Environmental behaviors are better when the occupant is home (this may be due to a cost incentive, presence of a reminder, or matter of convenience) Better at home 4 26.7% 11 64.7% 6 46.2% Environmental behaviors stay the same regardless of location (includes home, hotels, residence hall) Stay the same 10 66.7% 6 35.3% 7 53.8% Environmental behaviors are worse when the occupant is home (this may be due to accommodations) Worse at home 1 6.7% 0 0.0% 0 0.0% 8. Perceived behavioral controls Occupant feels that behaving sustainably takes too much time (extra time using low flow features, unplugging electronics, recycling, Extra time 7 46.7% 5 29.4% 2 15.4%

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288 etc) Lack of control over the existing features/future features in residence hall Lack of authority 1 6.7% 1 5.9% 2 15.4% The lack of cooperation by others makes it difficult to conserve resources Lack of cooperation 4 26.7% 2 11.8% 5 38.5% The absence of a cost incentive makes it difficult for the occupant to want to save resources No cost incentive 4 26.7% 12 70.6% 6 46.2% Obstacles are not observed beyond self motivation and/or essential resource consumption No obstacles 0 0.0% 0 0.0% 2 15.4% The absence of reminders makes it difficult for the occupant to save resources No reminders 0 0.0% 4 23.5% 1 7.7% Occupant does not feel well educated on existing features and thus does not feel that they use them properly Not educated on features 6 40.0% 8 47.1% 3 23.1% Occupant does not feel educated on the rationale for behaving sustainably Not educated on rationale 7 46.7% 4 23.5% 0 0.0% Occupant enjoys using resources as a method for relaxing Stress relief 1 6.7% 2 11.8% 1 7.7% 8a. Frequency of constraint Occupant encounters constraining condition 2 3 days per week 2 3 day constraint 1 6.7% 3 17.6% 1 7.7% Occupant encounters constraining condition 4 5 days per week 4 5 day constraint 2 13.3% 2 11.8% 2 15.4% Occupant encounters constraining condition everyday Everyday constraint 12 80.0% 15 88.2% 11 84.6% Occupant is unsure of how often they Unsure constraint 0 0.0% 1 5.9% 1 7.7%

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289 encounter constraining conditions 8b. Facilitating conditions Occupant attributes an existing technology with making conservation easier Availability of existing technology 14 93.3% 11 64.7% 9 69.2% Knowing how to conserve for oneself and being willing to apply that knowledge Being knowledgeable 2 13.3% 1 5.9% 3 23.1% A busy class or social schedule keeps this individual out of the residence hall where they physically cannot contribute to overall consumption Being out of hall 0 0.0% 2 11.8% 5 38.5% Occupant believes that an incentive would make it easier for occupants to conserve resources (such as a monetary incentive, free food, etc) Create an incentive 1 6.7% 1 5.9% 0 0.0% Occupant attributes an existing educational signage with making conservation easier Educational Signage 0 0.0% 2 11.8% 1 7.7% Occupant attributes the encouragement by housing staff with making conservation easier Encouraged by housing 0 0.0% 1 5.9% 1 7.7% Occupant does not believe that a facilitating condition exists None 0 0.0% 1 5.9% 0 0.0% 8c. Frequency of facilitating condition Occupant encounters facilitating condition 4 5 days per week 4 5 day facilitation 0 0.0% 2 11.8% 2 15.4% Occupant encounters facilitating condition everyday Everyday facilitation 14 93.3% 10 58.8% 11 84.6% Occupant never encounters a facilitating condition Never facilitation 0 0.0% 2 11.8% 0 0.0%

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290 Occupant rarely encounters facilitating condition (less than once a month) Rare facilitation 0 0.0% 2 11.8% 0 0.0% Occupant is unsure of how often they encounter a facilitating condition Unsure facilitation 0 0.0% 1 5.9% 0 0.0% 8d. Sustainability educational program Believes that 20% 35% of residents would also participate in the sustainability education program 20% 35% of residents 5 33.3% 4 23.5% 3 23.1% Believes that 35% 50% of residents would also participate in the sustainability education program 35% 50% of residents 0 0.0% 2 11.8% 1 7.7% Believes that 5% 20% of residents would also participate in the sustainability education program 5% 20% of residents 6 40.0% 7 41.2% 4 30.8% An incentive would need to be available in order to obtain participants (such as a course credit, food, etc) Incentive required 7 46.7% 3 17.6% 8 61.5% Believes that less than half of attendants will apply learned methods of conservation Not apply 2 13.3% 4 23.5% 5 38.5% Believes over 50% of residents would also participate in the sustainability education program Over 50% of residents 0 0.0% 1 5.9% 3 23.1% Does not believe that the majority of other residents care about sustainability issues Residents 4 26.7% 1 5.9% 6 46.2% Would participate if the program did not interfere with class schedule. Scheduling 2 13.3% 4 23.5% 1 7.7% Believes that more Would apply 3 20.0% 4 23.5% 3 23.1%

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291 than half of attendants will apply learned methods of conservation Would not participate in the sustainability education program Would not participate 3 20.0% 1 5.9% 0 0.0% Would participate in the sustainability education program Would participate 9 60.0% 7 41.2% 11 84.6% 8e. Utility charge policy Can see the benefits to such a policy but is concerned about potential increased cost Unsure about policy 0 0.0% 2 11.8% 0 0.0% Would like additional information about costs and environmental benefits prior to providing or denying support. Would need additional information 5 33.3% 0 0.0% 3 23.1% Would not support the policy out of concern for increased living costs Would not support 7 46.7% 8 47.1% 1 7.7% Can see the benefits to such a policy and believe that it would help to reduce overall consumption Would support 2 13.3% 5 29.4% 8 61.5% 9. Behavioral intention Anticipates that their consumption will be generally the same, improvements are expected Somewhat likely 2 13.3% 5 29.4% 3 23.1% Anticipates that their consumption will be generally the same, but some improvements are possible Somewhat unlikely 3 20.0% 1 5.9% 0 0.0% Anticipates that their consumption will be exactly the same or worse next semester Unlikely 6 40.0% 9 52.9% 4 30.8%

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292 Anticipates that their consumption will be reduced significantly next semester Very likely 3 20.0% 2 11.8% 6 46.2% 9a. How behavioral intentions Consumption would be reduced by becoming involved and educated in an environmental club Join a club 1 6.7% 0 0.0% 0 0.0% Will not be in the building as often and thus cannot use Out of building 1 6.7% 0 0.0% 0 0.0% Consumption of energy will be reduced by unplugging unused electronics Remember to unplug 0 0.0% 0 0.0% 1 7.7% Consumption of resources will continue as usual Same behaviors 7 46.7% 9 52.9% 4 30.8% Consumption of resources will be reduced by being more self aware Self awareness 3 20.0% 2 11.8% 2 15.4% Consumption of water will be reduced by taking shorter showers Taking shorter showers 3 20.0% 7 41.2% 5 38.5% Consumption of energy will be reduced by turning off lights more Turning of lights more 1 6.7% 2 11.8% 5 38.5% Consumption of energy will be reduced by turning off the AC when not in use Turning off the AC 1 6.7% 2 11.8% 0 0.0% Consumption of water will be reduced by turning off the sink when not actively in use Turning off the sink 1 6.7% 1 5.9% 1 7.7% Consumption of energy will be reduced by using natural daylight opportunities Using daylight 1 6.7% 1 5.9% 1 7.7% 9b. Future intentions Anticipates recycling on a more regular basis (generally due to convenience) Active recycling 0 0.0% 1 5.9% 0 0.0% Would be more active Be conscious 1 6.7% 4 23.5% 1 7.7%

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293 of telling others to conserve when in their home of others Would check to make sure that plumbing is not leaking Check for leaks 0 0.0% 1 5.9% 0 0.0% Occupant notes a motivation by a utility bill Mention of utility bill 11 73.3% 11 64.7% 5 38.5% Does not anticipate any changes in environmental behavior in the future No future change 3 20.0% 2 11.8% 4 30.8% Anticipates purchasing energy saving technologies as a method for reducing energy consumption (energy star appliances, compact florescent light bulbs, solar panels etc) Purchase of energy saving technologies 4 26.7% 5 29.4% 3 23.1% Anticipates purchasing water saving technologies as a method for reducing water consumption (low flow faucets, dual flush toilets, etc) Purchase of water saving technologies 4 26.7% 2 11.8% 3 23.1% Anticipates utilizing natural ventilation as a method for reducing energy consumption Use of natural ventilation 0 0.0% 1 5.9% 0 0.0% Occupant anticipates reducing energy consumption/heighten ed consciousness of use Will reduce energy 5 33.3% 11 64.7% 5 38.5% Occupant anticipates reducing water consumption/heighten ed consciousness of use Will reduce water 5 33.3% 10 58.8% 5 38.5%

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294 APPENDIX J SOCIAL INFLUENCE APP ROACHES AND COMMUNITY BASED SOCIAL MARKETING TECHNIQUES Based on the findings derived from the CFA and EFA in this study, it was clear that resident ESBs were most influenced by the subjective norm, altruistic and biospheric value, attitude, behavioral intention, and personal norm constructs from the TPB and VBN theories. In the context of residence hall s, it may be assumed t hat environmental programs would be most effective if they utilized social influence approaches and CBSM techniques that zeroed in on these prevalent constructs. Some of the most popular and widely used social influence approaches and CBSM techniques to en courage behavior change are public commitments, block leaders, modeling, prompts, incentives, and conveniences (Abrahamse & Steg, 2013; McKenzie Mohr, 2013 ). The following may be used by campus administration in their efforts to foster sustainable behavior s on their campuses. These techniques have been tailored to address the prominent constructs that most influenced the student residents in this study. Public Commitments Commitment making is generally defined as the binding of an individual to a certain o pinion or behavior (Kiesler, 1971). Commitment techniques have shown to be effective in promoting a diverse variety of sustainable behaviors including using public transportation, installing low flow water features, increasing curbside recycling, reducing energy consumption, and reducing air pollution (Abrahamse & Steg, 2013; Aronoff, Champion, Lauer, & Pahwa, 2013; Lu & Perl, 2006; McKenzie Mohr Associates & Lura Consulting, 2001). For example, when parents in a school parking lot of Toronto, Canada public ly committed to reduce their contribution to air pollution by not to let their

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295 car engines run idle, the frequency of engine idling was reduced by 32% and idling duration by 73% (McKenzie Mohr Associates & Lura Consulting, 2001). It is suggested by the Se lf Perception theory that this technique is effective because individuals who make public commitments experience a strong internal pressure (personal norm) to behave consistently. The need for individuals to behave consistently is rooted in its connection to other character traits such as honesty and integrity. By contrast, those who behave inconsistently are perceived to be untrustworthy and unreliable (Bem, 1972). Additionally, it is also believed by social theorist that public commitments encourage behav ior change through social pressure (subjective norm) because individuals naturally want to gain social approval and avoid social sanctions, so that other people will like them. Thus individuals are more likely to stick to commitments they make publicly ver sus privately (Abrahamse & Steg, 2013; Keizer and Schultz, 2012; Lokhorst, Werner, Staats, van Dijk, & Gale, 2013; Shippee & Gregory, 1982). Finally, it is said that when people publicly commit themselves to engage in certain behaviors, the attitudes and v alues that are relevant for this behavior are more significant and remain stable over time (Abrahamse & Steg, 2013; Kiesler, 1971; Pallak, Cook, & Sullivan, 1980). Therefore, environmental programs in LEED certified residence halls might utilize public com mitments, such as a signed and posted commitment to reduce showers to less than 15 minutes, as a method for ensuring that occupants act in accordance to sustainable initiatives in their buildings. Block Leaders Commitment strategies have also been shown to be effective when combined with block leader advocates. A block leader is a community resident who actively

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296 engages in a desired behavior and who agrees to speak to other people in their community to help promote their participation in a program. As sug gested by social scientists, users are most likely to change their behavior in response to direct appeals from others (subjective norm; McKenzie Mohr, 2013) . This in part is explained by the Diffusion of Innovation theory, which indicates that social netwo rks play an important role in the diffusion of information (Rogers, 1995). While research has indicated that the extent to which information spreads though a social network depends on the number and the strength of social ties , these systems have been conn ected to a wide range of phenomena, including voting behaviors, the spread of obesity, and recycling habits (Abrahamse & Steg, 2013; Burn & Oskamp, 1986; Christakis & Fowler, 2009; Granovetter, 1973). The effectiveness of block leaders may also be attribut ed to the so will try to establish a meaningful relationship with them (behavioral intention; Cialdini, be effective because the use of existing social networks increases the chances of information reaching a certain group (diffusion of information), as well as increasing the chances that people in this network act on this information because it comes from someone they know certified residence halls, environmental programs might utilize block leaders, such as Resident Assistants and Community Directors, as a method for ensuring tha t occupants adopt desired behaviors. These leaders could help monitor resident ESBs and help to inform those who are unaccustomed or unfamiliar with conservation practices.

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297 Modeling derates engaging in a behavior when they observe other people who engage in this behavior" Abrahamse & Steg, 2013, p. 1774). Several studies have documented the impact that m 1983; Cialdini, 2003; Goldstein, Cialdini, & Griskevicius, 2008). For example, at the that encourages that showers be turned off while users soap up. On average, only 6% of users were found to comply despite a random sample of students demonstrating that 93% were aware of the sign and its message. However, when a research accomplice modeled the desired water conserving behavior, the percentage of students who turned off the shower to soap up shot up to 49%. Additionally, when two accomplices modeled the desired behavior, the number of people who followed suit rose to 67% ( Aronson & 1983; McKenzie Mohr, 2013). Modeling is effective in changing behaviors because it helps individuals to discern what behaviors are approved or disapproved of (subjective norm) and which behaviors are normally engaged in (personal norms). Additionally, acco rding to social learning theory, the learning of new skills typically occurs in a social context, which highlights that social influence plays a key role in the learning process (Bandura, 1977). Therefore, as a component of an environmental program in LEED certified residence hall, Community Directors might assign modeling confederates to help in assimilating the adoption of sustainable behaviors, such as turning off the lights when leaving a room, turning off the sink while brushing your teeth,

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298 or taking q uick showers. By modeling desired behaviors, these affiliates would subliminally demonstrate what behaviors are approved or disapproved of in their community and would provide an example for those who are unfamiliar with conserving practices. Prompts Whi le social influences and CBSM techniques are effective in endorsing sustainable behaviors all are susceptible to the most human of traits: forgetting (McKenzie & Smith, 2010). Turning off lights, turning down thermostats, unplugging unused electronics, and turning off the sink while brushing our teeth are just a few of the innovations such as a programmable thermostat can free us from the burden of continually remembering to carry out an activity. Most repetitive actions, however, have have been used as an effective tool to remind building occupants to engage in desired sustainable behavio number of studies have helped to show that prompts are effective in changing behaviors and contribute tow ard the success of environmental programs (de Kort, McCalley, & Midden, 2008; Duffy & Verges, 2009; Kurz, Donaghue, & Walker, 2005; Luyben, 1984). For example, in a study that took place in Perth, Australia educational pamphlets were first provided to hou seholds encouraging them to reduce their water consumption. However, this information intensive sustainability campaign had no impact on the actual behaviors of residents. By contrast, when prompts were installed on various household

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299 devices, such as sink faucets and shower fixtures, residents reduced their consumption of water by 23% (de Kort, McCalley, & Midden, 2008). Studies have also helped to determine that prompts need to be presented in close proximity to the behavior they are meant to promote in or der to be effective. Based on the location and visibility of prompts, studies have demonstrated a 67% decrease in energy consumption, 100% increase in recycling, and a 350% reduction in littering (Houghton, 1993; Luyben, 1984; Luyben & Cummings, 1982). In the context of LEED certified residence halls, environmental programs might utilize prompts, such as visual reminders near outlets, light switches, and water fixtures, such as sinks, toilets, and showers, to remind occupants to conserve. This strategy coul d help to foster sustainable behaviors, reduce operation costs, and help to educate those who are unaccustomed or unfamiliar with conservation practices.

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319 BIOG RAPHICAL SKETCH In 2006, Pamela N. Driza graduated from the University of Florida (UF) with a Bachelor of Design and a keen interest in sustainabi lity. Whether by luck or fate, she started working for an Atlanta based firm that not only embraced e nvironmen tally conscious design but also encouraged their clients to do the same since 1999. While surrounded by United States Green Building Council (USGBC) members and avid green designers, her college founded interests were quickly nurtured into a budding passio n for sustainable practices. She became a LEED Accredited Professional with a specialty in building design and construction (BD+C), and worked closely with clients on a series of certified projects. Sometime after becoming a licensed designer and the LEED Administrator for her office, she felt it was important to share the knowledge she had gained while crafting sustainable interiors. In 2008 she decided to start her own business , Leaping for GREEN, and began to instruct LEED courses for a wide client base including designers, architects, and engineers. It was at this time that Pam realized how passionate she was about sustainability and decide d to enhance her knowledge of LEED building performance by pursuing a and doctoral degree . Since enrolling in the graduate program at UF , she has worked as a GTA and course instructor for several upper division design studios, has presented her 2011 /2013 IDEC con ference s in Colorado and Louisiana , and was a first place winner of the Witter s C ompetition . Ultimately, Pam hope s to leverage her research findings to improve the LEED rating system and pursue a career that will allow her to combine her research and desi gning skills.