Perceptions of the Design-Build Project Delivery Method among Small Florida Construction Firms

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Title:
Perceptions of the Design-Build Project Delivery Method among Small Florida Construction Firms
Physical Description:
1 online resource (131 p.)
Language:
english
Creator:
Harrow, Adrienne I
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
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Thesis/Dissertation Information

Degree:
Master's ( M.S.B.C.)
Degree Grantor:
University of Florida
Degree Disciplines:
Building Construction
Committee Chair:
Issa, Raja Raymond A
Committee Members:
Olbina, Svetlana
Lucas, Elmer D

Subjects

Subjects / Keywords:
design-build -- ethical
Building Construction -- Dissertations, Academic -- UF
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Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
The purpose of this research is to evaluate the Design-Build delivery method and its ethical impacts. Is it possible that this delivery system is in favor of large companies and is unequal to all bidders that submit a bid? This experimental design was based on a common survey method,availability sampling, through email and postal addresses. The techniques used in the questionnaire were simple question and answer responses including yes,no, sometimes, other and extended responses. The major statistical analysis was done by performing Chi-Squared Hypothesis Testing to determine which hypothesis to accept or reject.  Based on the Chi-Squared Tests performed, the researcher was able to draw a conclusion that paralleled her hypothesis: Design-build can be used as form of bid-rigging. In the perception of the respondents, Design-Build is illegal and unethical and should be modified or abolished. These findings are limited by the small sample size, the regional limitations to the State of Florida and the small company size of the respondents.
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In the series University of Florida Digital Collections.
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Includes vita.
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Includes bibliographical references.
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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.
Statement of Responsibility:
by Adrienne I Harrow.
Thesis:
Thesis (M.S.B.C.)--University of Florida, 2013.
Local:
Adviser: Issa, Raja Raymond A.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2014-08-31

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UFRGP
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Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046050:00001


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1 PERCEPTIONS OF THE DESIGN BUILD P ROJECT DELIVERY METHOD AMONG SMALL FLORIDA CONSTRUCTION FIRMS By ADRIENNE IVAH HARROW A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE R EQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2013

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2 2013 Adrienne Ivah Harrow

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3 To the Harrow and Kay Family

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4 ACKNOWLEDGMENTS I thank my parents for alwa ys supporting me through the odd endeavors I wish to pursue. They have shown me everything, and I can finally start giving something back to them I thank my brother for being a helpful guide through life and all law associated matters. I thank my sister for coaching me through all business related and life situations that occurred. I thank my great grandparents for showing me how to live a happy and successful life through perseverance and hard work. I thank my grandparents for teaching me how to be reso urceful as well as being kind to others. I thank my wonderful boyfriend for always encouraging me to keep going even through the hard times. I thank my boyfriends family for showing unconditional support. I thank my uncles and aunts, blood and not blood r elated, for being there to talk to when I need to vent about my crazy family I thank my friends for their emotional support and always having a shoulder for me to cry on. I thank my advisor for being calm and helpful especially when I am struggling. I th ank the members of my thesis committee for being supportive even though we d id not always see eye to eye. I thank the director, directors secretary and the M.E. Rinker, Sr. School of Building Construction for giving me this opportunity to learn what I lov e. I thank my tutors of statistics who tutored me through odd hours because of my hectic schedule. I thank my editors who show me something new every day. I thank everyone who participated in completing my survey, because without you I wouldnt have data. I thank everyone who has ever influenced me positively and negatively, because without your motivation, I would not be where I am today.

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5 TABLE OF CONTENTS Page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES .......................................................................................................... 11 LIST OF FIGURES ........................................................................................................ 14 LIST OF ABBREVIATIONS ........................................................................................... 16 ABSTRACT ................................................................................................................... 1 7 CHAPTER 1 INTRODUCTIONARY REMARKS .......................................................................... 18 Choosing the Topic ................................................................................................. 18 Background of Topic ............................................................................................... 18 Motivation of Study ................................................................................................. 19 Scope of the Study ................................................................................................. 19 Gaps/Limitations of Previous Studies ..................................................................... 19 Contribution of Study .............................................................................................. 20 Aims and Objectives ............................................................................................... 20 Hypothesis .............................................................................................................. 20 2 LITERATURE REVIEW .......................................................................................... 21 Define Delivery Methods ......................................................................................... 22 Design Bid Build, Traditional Delivery Method ................................................. 22 Advantages of DesignBid Build ................................................................ 22 Disadvantages of DesignBid Build ............................................................ 22 Construction Management (CM as Agent) ....................................................... 23 Advantages of CM ..................................................................................... 23 Disadvantages of CM ................................................................................. 24 Construction Management at Risk (CMAR) ...................................................... 24 Advantages of CMAR ................................................................................ 24 Disadva ntages of CMAR ............................................................................ 25 Design Build ..................................................................................................... 25 Advantages of DesignBuild ....................................................................... 26 Disadvantages of DesignBuild .................................................................. 26 Hybrids ............................................................................................................. 27 Advantages of hybrids ............................................................................... 28 Similarities .............................................................................................................. 28 Differences .............................................................................................................. 28 Differences between Procurement and Deliv ery Process ....................................... 29 History ..................................................................................................................... 29

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6 DBIA ....................................................................................................................... 31 Does It All Work? .................................................................................................... 31 Jurisdictions ............................................................................................................ 34 In the Beginning ...................................................................................................... 35 Why the Change? ................................................................................................... 36 Faces of Design Build ............................................................................................. 36 Contractor led Design Build ............................................................................. 36 Designer led Design Build ................................................................................ 37 Selection Process ................................................................................................... 38 Why BV Rather Than LB? ....................................................................................... 39 Why Disputes? ........................................................................................................ 40 How Many DesignBuilds? ...................................................................................... 41 How Many Design Builds in Lawsuits? ................................................................... 41 So Why is Design Build, Bid Rigging? .................................................................... 41 Subjective Criteria ................................................................................................... 41 Objective Criteria .................................................................................................... 42 Conflic ts in Design Build Process ........................................................................... 42 Bid Rigging ............................................................................................................. 43 Some Solutions to DesignBuild ............................................................................. 44 3 METHODOLOGY ................................................................................................... 46 Measures ................................................................................................................ 46 Validity and Reliability ...................................................................................... 47 Subjects/ Participants ............................................................................................. 48 Preparations ........................................................................................................... 49 Data Collection ....................................................................................................... 50 Timeline ............................................................................................................ 51 Data Analysis .......................................................................................................... 51 4 RESULTS ............................................................................................................... 56 Assumptions ........................................................................................................... 56 Limitations ............................................................................................................... 56 Potential Sources of Error ....................................................................................... 57 Random Sampling Errors ................................................................................. 57 Non Sampling Errors ........................................................................................ 57 Response errors ........................................................................................ 57 Researcher errors ...................................................................................... 58 Interviewer errors ....................................................................................... 58 Participant errors ........................................................................................ 58 Non response errors .................................................................................. 58 Question Response Analysis .................................................................................. 58 Question 17 ...................................................................................................... 58 Numerical results ....................................................................................... 59 Hypotheses ................................................................................................ 59 Analysis ...................................................................................................... 59

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7 Chisquared test ......................................................................................... 60 Question 12 ...................................................................................................... 60 Numerical results ....................................................................................... 60 Hypotheses ................................................................................................ 60 Analysis ...................................................................................................... 61 Chisquared test and results ...................................................................... 61 In depth ...................................................................................................... 61 Question 13 ...................................................................................................... 62 Numerical results ....................................................................................... 62 Hypotheses ................................................................................................ 62 Analysis ...................................................................................................... 62 Chisquared test and results ...................................................................... 63 Question 22 ...................................................................................................... 63 Numerical results ....................................................................................... 63 Hypotheses ................................................................................................ 63 Analysis ...................................................................................................... 63 Chisquared test and results ...................................................................... 64 Question 3 ........................................................................................................ 64 Num erical results ....................................................................................... 64 Description ................................................................................................. 65 Question 4 ........................................................................................................ 65 Numerical results ....................................................................................... 65 Description ................................................................................................. 65 Question 7 ........................................................................................................ 65 Numerical results ....................................................................................... 66 Description ................................................................................................. 66 Question 8 ........................................................................................................ 66 Numerical results ....................................................................................... 66 Description ................................................................................................. 67 Question 9 ........................................................................................................ 67 Numerical results ....................................................................................... 67 Description ................................................................................................. 68 Question 10 ...................................................................................................... 68 Numerical results ....................................................................................... 68 Description ................................................................................................. 68 Questio n 1 ........................................................................................................ 69 Numerical data ........................................................................................... 69 Hypotheses ................................................................................................ 69 Analysis ...................................................................................................... 69 Chisquared test ......................................................................................... 70 Question 2 ........................................................................................................ 70 Numerical data ........................................................................................... 70 Analysis ...................................................................................................... 70 Question 5 ........................................................................................................ 70 Numerical data ........................................................................................... 71 Analysis ...................................................................................................... 71

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8 Question 6 ........................................................................................................ 71 Numerical data ........................................................................................... 71 Hypotheses ................................................................................................ 72 Analysis ...................................................................................................... 72 Chi Squared Test and Results ................................................................... 72 Question 11 ...................................................................................................... 72 Numerical data ........................................................................................... 73 Hypotheses ................................................................................................ 73 Analysis ...................................................................................................... 73 Chi squared test and results ...................................................................... 7 3 In depth ...................................................................................................... 73 Quest ion 14 ...................................................................................................... 74 Numerical data ........................................................................................... 74 In depth ...................................................................................................... 74 Question 15 ...................................................................................................... 75 Numerical data ........................................................................................... 75 In depth ...................................................................................................... 75 Question 16 ...................................................................................................... 75 In depth ...................................................................................................... 75 Question vs. Question Analysis .............................................................................. 76 Question 17 vs. Question1 ............................................................................... 76 Analysis ...................................................................................................... 76 Hypotheses ................................................................................................ 77 Limitations .................................................................................................. 77 Question 17 vs. Question 3 .............................................................................. 77 Analysis ...................................................................................................... 77 Hypotheses ................................................................................................ 78 Limitations .................................................................................................. 78 Question 17 vs. Question 6 .............................................................................. 79 Analysis ...................................................................................................... 79 Hypotheses ................................................................................................ 79 Limitations .................................................................................................. 80 Question 17 vs. Question 7 .............................................................................. 80 Analysis ...................................................................................................... 80 Hypotheses ................................................................................................ 81 Limitations .................................................................................................. 81 Question 17 vs. Question 8 .............................................................................. 81 Analysis ...................................................................................................... 81 Hypotheses ................................................................................................ 82 Limitations .................................................................................................. 82 Question 17 vs. Question 9 .............................................................................. 82 A nalysis ...................................................................................................... 82 Hypotheses ................................................................................................ 83 Limitations .................................................................................................. 83 Question 17 vs. Question 10 ............................................................................ 83 Analysis ...................................................................................................... 84

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9 Hypotheses ................................................................................................ 84 Limitations .................................................................................................. 85 Question 17 vs. Question 11 ............................................................................ 85 Analysis ...................................................................................................... 85 Hypotheses ................................................................................................ 86 Limitations .................................................................................................. 86 Question 17 vs. Question 12 ............................................................................ 86 Analysis ...................................................................................................... 86 H ypotheses ................................................................................................ 87 Limitations .................................................................................................. 87 Question 17 vs. Question 13 ............................................................................ 87 Analysis ...................................................................................................... 87 Hypotheses ................................................................................................ 88 Limitations .................................................................................................. 88 Question 17 vs. Question 15 ............................................................................ 88 Analysis ...................................................................................................... 89 Hypotheses ................................................................................................ 89 Limitations .................................................................................................. 89 Question 17 vs. Question 22 ............................................................................ 90 Analysis ...................................................................................................... 90 Hypotheses ................................................................................................ 90 Lim itations .................................................................................................. 91 Question 11 vs. Question 9 .............................................................................. 91 Analysis ...................................................................................................... 91 Hypotheses ................................................................................................ 92 Limitations .................................................................................................. 92 Question 11 vs. Question 12 ............................................................................ 92 Analysis ...................................................................................................... 92 Hypotheses ................................................................................................ 93 Limitations .................................................................................................. 93 Question 11 vs. Question 13 ............................................................................ 93 Analysis ...................................................................................................... 93 Hypotheses ................................................................................................ 94 Limitations .................................................................................................. 94 Question 11 vs. Question 15 ............................................................................ 94 Analysis ...................................................................................................... 94 Hypotheses ................................................................................................ 95 Limitations .................................................................................................. 95 5 DISCUSSION ....................................................................................................... 107 Major Patterns ...................................................................................................... 108 Comparison of Results .......................................................................................... 108 What We Know Now ............................................................................................. 109 Implications ........................................................................................................... 110 6 CONCLUSION ...................................................................................................... 111

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10 Contribution .......................................................................................................... 111 Research Results Compared to the Literature Review ......................................... 112 Limitations of the Research .................................................................................. 112 7 RECOMMENDATIONS ......................................................................................... 114 First Step .............................................................................................................. 114 Second Step ......................................................................................................... 114 Third Step ............................................................................................................. 114 Final Step .............................................................................................................. 115 APPENDIX A LETTER TO RECIPIENTS (EMAIL) ..................................................................... 116 B LETTER TO RECIPIENTS (MAIL) ........................................................................ 117 C SURVEY/ QUESTIONNAIRE ............................................................................... 118 LIST OF REFERENCES ............................................................................................. 129 BIOGRAPHICAL SKETCH .......................................................................................... 131

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11 LIST OF TABLES Table page 4 1 Numerical Results of Question 17 ...................................................................... 59 4 2 Chisquared test table ........................................................................................ 60 4 3 Numerical Results of Question 12 ...................................................................... 60 4 4 ChiSquared Test and Results ............................................................................ 61 4 5 Numerical Results to Question 13. ..................................................................... 62 4 6 ChiSquared Test and Results ............................................................................ 63 4 7 Numerical Results of Question 22 ...................................................................... 63 4 8 ChiSquared Test and Results ............................................................................ 64 4 9 Numerical Results for Question 3 ....................................................................... 64 4 11 Numerical Results of Question 4 ........................................................................ 65 4 12 Description of Numerical Results ........................................................................ 65 4 13 Numerical Results of Question 7 ........................................................................ 66 4 14 Description of Numerical Results ........................................................................ 66 4 15 Numerical Results of Question 8 ........................................................................ 66 4 16 Description of Numerical Results ........................................................................ 67 4 17 Numerical Results of Question 9 ........................................................................ 67 4 1 8 Description of Numerical Results ........................................................................ 68 4 19 Numerical Results of Question 10 ...................................................................... 68 4 2 0 Description of Numerical Results ........................................................................ 68 4 21 Numerical Data of Question 1 ............................................................................. 69 4 22 Chisquared test ................................................................................................. 70 4 23 Numerical Data for Question 2 ........................................................................... 70 4 24 Numerical Data of Question 5 ............................................................................. 71

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12 4 25 Numerical Data of Question 6 ............................................................................. 71 4 26 ChiSquared Test and Results ............................................................................ 72 4 27 Numerical Data for Question 11 ......................................................................... 73 4 28 ChiSquared Test and Results ............................................................................ 73 4 29 Numerical Data for Question 14 ......................................................................... 74 4 30 Numerical Data for Question 15 ......................................................................... 75 4 31 Question 17 vs. Question 1 Observed Data ....................................................... 76 4 32 Question 17 vs. Question 1 Expected Data ........................................................ 77 4 33 Question 17 vs. Question 3 Observed Data ....................................................... 78 4 34 Question 17 vs Question 3 Expected Data ........................................................ 78 4 35 Question 17 vs. Question 6 Observed Data ...................................................... 79 4 36 Question 17 vs. Question 6 Expected Data ....................................................... 79 4 37 Question 17 vs. Question 7 Observed Data ...................................................... 80 4 38 Question 17 vs. Question 7 Expected Data and P Value .................................. 80 4 39 Question 17 vs. Question 8 Observed Data ...................................................... 81 4 40 Question 17 vs. Question 8 Expected Data ....................................................... 82 4 41 Question 17 vs. Question 9 Observed Data ...................................................... 83 4 42 Question 17 vs. Question 9 Expected Data ....................................................... 83 4 43 Question 17 vs. Question 10 Observed Data .................................................... 84 4 44 Question 17 vs. Question 10 Expected Data ..................................................... 84 4 45 Question 17 vs. Question 11 Observed Data .................................................... 85 4 46 Question 17 vs. Question 11 Expected Data ..................................................... 85 4 47 Question 17 vs. Question 12 Observed Data .................................................... 86 4 48 Question 17 vs. Question 12 Expected Data ..................................................... 87 4 49 Question 17 vs. Question 13 Observed Data .................................................... 88

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13 4 50 Question 17 vs. Question 13 Expected Data ..................................................... 88 4 51 Question 17 vs. Question 15 Observed Data .................................................... 89 4 52 Question 17 vs. Question 15 Expected Data and P Value ................................ 89 4 53 Question 17 vs. Question 22 Observed Data .................................................... 90 4 54 Question 17 vs. Question 22 Expected Data ..................................................... 90 4 55 Question 11 vs. Question 9 Observed Data ...................................................... 91 4 56 Question 11 vs. Question 9 Expected Data ....................................................... 91 4 57 Question 11 vs. Question 12 Observed Data .................................................... 92 4 58 Question 11 vs. Question 12 Expected Data ..................................................... 93 4 59 Question 11 vs. Question 13 Observed Data .................................................... 93 4 60 Question 11 vs. Question 13 Expected Data ..................................................... 94 4 61 Question 11 vs. Question 15 Observed Data .................................................... 95 4 62 Question 11 vs. Question 15 Expected Data ..................................................... 95

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14 LIST OF FIGURES Figure page 2 1 Design Bid Build: Construction Delivery Process [Adapted from Guyer, P. E., R.A. (2012). "Ethical Issues in DesignBuild."] .................................................... 45 2 2 Design Build: Construction Delivery Process [Adapted from Guyer, P. E., R.A. (2012). "Ethical Issues in DesignBuild."] .................................................... 45 3 1 Validity vs. Reliability [Adapted from Sosulski, P. C. W. a. K. (2002). "Quantitative Methods in Social Sciences." QMSS eLessons, . (June 9, 2013).] ...................................................................... 48 3 2 Timeline of Data Collection ................................................................................. 51 4 1 Pot ential Sources of Error [Adapted from Liu, R. F. a. A. (2008). Research Methods for Construction, Wiley Blackwell. West Sussex, United Kingdom.] .... 96 4 2 Could DB be used as a form of bid rigging? ....................................................... 97 4 3 Should the DB project delivery method be allowed for public projects? ............. 97 4 4 Should the DB project delivery meth od be allowed for private projects? ............ 98 4 5 Are DB bids structured to provide equal opportunity for all bidders? .................. 98 4 6 Number of Employees ........................................................................................ 99 4 7 Annual Volume of Business ................................................................................ 99 4 8 Quantity of projects bid on over past five year .................................................. 100 4 9 Quantity of DB projects bid on over past five years .......................................... 100 4 10 Quantity of DB projects awarded over past five years ...................................... 101 4 11 Quantity of DB projects that have been awarded, over the past five years that were public projects .......................................................................................... 101 4 12 What business are you in? ............................................................................... 102 4 13 What type of business are you? ....................................................................... 102 4 14 What type of business are you? ....................................................................... 103 4 15 Map of city and state respondents are loca ted in ............................................. 104

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15 4 16 What project delivery method do you prefer? ................................................... 105 4 17 Do you prefer working on DB projects? ............................................................ 105 4 18 Have you always been able to meet the criteria required in the DB RFP? ....... 106

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16 LIST OF ABBREVIATIONS BV Best Value CII Construction Industry Institute CM Construction Management CMAR/CMR C onstruction Management at Risk DB Design Build DBB Design Bid Build DBIA Design Build Institute of America FTC Federal Trade Commission GMP/GMCPF Guaranteed Maximum Price LB Lowest Bid PDM Project Delivery Method RFP Request for Proposal SIC Intentionall y so written SOQ Statement of Qualifications UK United Kingdom US United States of America

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17 Abs tract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction PERCEPTIONS OF THE DESIGN BUILD PROJECT DELIVERY METHOD AMONG SMALL FLORIDA CONSTRUCTION FIRMS By Adrienne Ivah Harrow August 2013 Chair: Raymond Issa Major: Building Construction The purpose of this research is to evaluate the DesignBuild delivery method and its ethical impacts. Is it possible that thi s delivery system is in favor of large companies and is unequal to all bidders that submit a bid? This experimental design was based on a common survey method, availability s ampling, through email and postal addresses. The techniques used in the questionnaire were simple question and answer responses including yes, no, sometimes, other and extended responses. The major statistical analysis was done by performing ChiSquared Hypothesis Test ing to determine which hypothesis to accept or reject. Based on the Chi Squared Test s performed, the researcher was able to draw a conclusion that paralleled her hypothesis: Desig n build can be used as form of bidr igging. In the perception of the respondents, Design Build is illegal and unethical and should be modified or abolished. These findings are limited by the small sample size, the regional limitations to the State of Florida and the small company size of the respondents

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18 CHAPTER 1 INTRODUCTIONARY REMARKS The purpose of this research is to evaluate the DesignBuild delivery method and its ethical impacts Should society have designbuild as a delivery method or should it be illegal because it rigs the bids on a project? Design Build does have many good attributes but does that mean society should accept it? What should we accept? This is important to examine because society should be committed to ethical practices. Unethical practices tend to be illegal or detriment al to society as a whole. This study will evaluate the perceptions of survey respondents of design build project delivery method and evaluate its in ner workings. Choosing the Topic The spe cific problem in designbuild can have detrimental effects on socie ty and may not actually help enough to outweigh these consequences. These negative effects wi ll be elaborated on later in this thesis. The authors father is involved in real estate construction and has had many conflicts relating to design build bids and the anti small contractor bias in the criteria in the Request for Proposal (RFP). This inspired the author to research the topic in order to help her father in future conflicts and help other landowners and contractors with bidding ethics. Background of Topic Design Build is a project delivery method that allows the owner to have one contract with one entity instead of multiple contracts. The contractor, engineer, architect, and designers all work within one unit. The contactor is typically the team leader and holds all the responsibility including communicating with the owner. Not all contractors

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19 use designbuild as a delivery method, which will allow for a comparison in this research. Motivation of Study This topic was selected because of the authors int erest level in design build delivery methods. The authors goal is to find out if design build is bid rigging. In most of the literature review, there are no studies on design build regarding bid rigging. Scope of the Study The direction of the thesis is to figure out whether designbuild is the right choice for our society The Haskell Company, based solely on designbuild delivery process, believes that DesignBuild is the best delivery process because it puts the entire team under the same roof and woul d therefore give the company a competitive edge ( Jackson 2011 ) On the other hand, i f Design Build is not the ideal choice, we need to come up wit h another solution thats new or use existing delivery processes like Design Bid Build, Construction Management, or Construction Management at Risk which will be discussed later on in the thesis. Gaps/Limitations of Previous Studies There have been numerous studies that investigate the effect of design build on construction. However, there have been few studies on design build as it relates to its ethical dilemma, bid rigging. The main study, based on case studies, that is the most relative to this research is by Guyer (2012) He describes how DB is based on subjective criteria rather than objective criteria and shows through RFPs how it can be easily bid rigged, and therefore illegal and unethical.

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20 Contribution of Study This research can be performed conti nuously in different areas to evaluate the design build delivery method and how ethical/legal its practices are compared to current laws This study could be repeated again in multiple, different locations to ensure reliability and then possibly change the current laws that support DB. This study will prove the perceptions of DesignBuild as it relates to bid rigging by construction related firms. Aims and Objectives Should DB be the main delivery method of the future or should it be outlawed so society u ses only objective criteria for bids? Should the judicial board just leave DB alone or promote it? Should the judicial board decide the delivery methods used for public and/or private bids? Should they abandon the DB delivery method completely and use something that is more objective and equal for all bidders? Hypothesis The authors hypothesis is that the negative impacts will outweigh t he positive benefits of Design Build. This delivery method should be abandoned and replaced with a delivery method that t reats all bidders and more equally and is more effective for all the parties involved. The main focus of the bidding process should be based on objective criteria rather than subjective criteria.

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21 CHAPTER 2 LITERATURE REVIEW There are different types of pr oject delivery methods (PDMs): DesignBid Build, Design Build, and Construction Project Management (2011). The Construction Industry Institute (CII) maintains that there are really only three fundamental PDMs: designbid build (DBB), design build (DB), an d construction manager at risk (CMR) (Touran et al. 2011). These are not the only types of delivery methods; there are other less popular methods and combinations of methods also (2011). In relatively recent years there has emerged a striving among clients for a hybrid method of procurement which: 1. Recognizes the importance of quality as well as price; 2. Gives the client the requisite degree of control over quality; 3. Avoids confrontation; and 4. More accurately reflects the way that buildings are build (sic), recognizing the benefits in terms of cost and quality of getting all parties in the construction process on board as soon as possible(Mosey 1998). The PDM is the process by which a construction project is comprehensively designed and constructed for an ow ner including project scope definition, organization of designers, constructors and various consultants, sequencing of design and construction operations, execution of design and construction and closeout and start up(Touran et al. 2011). An owners primary goal in choosing a delivery method is to ensure that it will meet the project objectives and at the same time allow the project to be delivered on time and within budget (2011).

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22 Define Delivery Methods Design Bid Build, Traditional Delivery Method DBB is the traditional PDM in which an owner retains a designer to furnish complete design services and then advertises and awards a separate construction contract based on the designers completed construction documents. In DBB, the owner owns the details of design during construction and as a result, is financially liable for the cost of any errors or omissions encountered in construction, called the Spearin doctrine ( Touran et al. 2011). The drawings and specifications and other documents form par t of the final building contract, but the contractor is not responsible for the design content of the drawings and specifications, only for constructing the works in accordance with them(Mosey 1998). Advantages of Design Bid Build Some of the advantages o f DBB are: 1. Low price competition that takes place on a design the owner has commissioned and approved; 2. Owners want independent contracts with their design professionals and no potential conflict of interest between the design and construction team members ; and 3. From a liability and process perspective, the designbid build model has the added benefit of predictability (Robert F. Cushman 2001). Disadvantages of DesignBid Build The fundamental flaw in traditional procurement is that the contractor does not necessarily have an understanding of the design process by which the drawings and specifications have been arrived at. He is required to price against them but not to adopt them as if they were his own. Typically, this can lead to the following problems: 1. Differences of opinion and interpretation between the design team and the contractor regarding implementation of the designs;

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23 2. Claims by the contractor as regards late provision of any further details to be prepared by the design team after the building contract has been entered into and after works have commenced on site; 3. Further claims by the contractor for variations to the original drawings and specifications, with consequent additional time and cost, whenever these documents are adjusted in any way by the design team, even if the design team believe that they are providing clarification rather than variation(Mosey 1998). Construction Management (CM as Agent) The CM covenants with the Owner to furnish his best skills and judgment for obtaining a quality controlled project on time and within budget. The C M agrees to provide the leadership for integrating all of the project participants into a team for purposes of providing efficient business administration and management of the project. An Agent is in fiduciary relationship with the Owner, which obligates the CM to a high duty of are and loyalty on the part of the CM to the Owner ( Juliana 2005) The contractual duties of the CM are as followed: Keep the Owner advised and informed Disclose information relevant to the Owners interest Make recommendations for Owner actions Often, responsible for scheduling and overall coordination of the project Proactively assess construction progress and the Contractors performance toward achieving timely completion within the budget ( Juliana 2005 ) Advantages of CM One of the primary advantages of CM as Agent is utilizing the CMs c onstruction expertise during the PreConstruction Phases, to advise on design constructability, scheduling, cost and budget control, contract and bid document preparation, and other issues ( Juliana 2005) This delivery method benefits projects that are considered to be fast paced projects ( Juliana 2005)

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24 Disadvantages of CM The major disadvantage of CM is that whether the C onstruction Manager individual has sufficient knowledge and experience on the project that they are contracted to ( Juliana 2005) The owner is dependent on the Construction Managers expertise and services they can provide ( Juliana 2005) Construction Management at Risk (CMAR) CM A R projects are projects with a contract between an owner and construction manager who will be at risk for the final cost and time of construction (Touran et al. 2011). This delivery method keeps the contracts separate just like the traditional method and it releases the set of plans and specifications to the CM A R (Touran et al. 2011). Typically, CM R contracts contain a provision in which the CM A R stipulates a guaranteed maximum price above which the owner is not liable for payment (Touran et al. 2011). Advantages of CMAR There are two major reasons for choosing the CM A R delivery method: constructa bility and faster phasing of construction (Touran et al. 2011). This method of procurement requires the contractor only to manage these subcontractors and suppliers, but not to accept full responsibility for their default or insolvency (management contr acting), or for the construction client itself to engage these subcontractors and suppliers under separate direct contracts, with no single main contractor but instead another independent professional (not usually a designer) engaged by the client to programme (sic), manage and coordinate the project (construction management)(Mosey 1998).

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25 Disadvantages of CMAR Using this approach the CMAR takes on the considerable risk of unforeseeable design development or added work. Disputes often arise to the deg ree of design development, or detailed design work, the CMAR has undertaken ( Juliana 2005) However, the CMAR s performance risk can be relocated to the subcontractors if the CMAR allows subcontractors and suppliers to aid and provide bids ( Juliana 2005) Design Build DB is a PDM in which the owner procures both design and construction services in the same contract from a single, legal entity referred to as the design/builder. This method typically uses request for qualifications/ request for proposal procedures rather than the DBB invitation for bids procedures (Touran et al. 2011).Due to the fact that designbuild is bec oming popular, the firm that is contracting with the owner is usually a construction firm and the primary leader would be the general contractor (Guyer 2012). No doubt this pattern will continue in the future because 1. General contractors have demonstrated over many decades that they are better marketers than professional engineers, and 2. State laws provide generally that only a licensed construction contractor can enter into a contract with an owner to provide construction services (Guyer 2012). Design and build is the term used to describe one way of achieving the completion of building or engineering works, including works of construction, alteration, repair and demolition, and whether they relate to residential, commercial or industrial buildings (build ing works) or infrastructure works such as roads, bridges, pipelines, harbors or decontamination of land (engineering works)(Mosey 1998). The DB team becomes liable for all costs including design and construction (Touran et al. 2011). Similarly with CM R, the builder in DB is allowed to input advice in the early stages of constructability

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26 for the design process in order to produce the most efficient construction process (Touran et al. 2011). As a result, DB is the delivery method which has the greatest ability to compress the project delivery period and as a result is often used for fast track projects (Touran et al. 2011). Advantages of Design Build One of the fundamental advantages of design and build and develop and construct is the requirement for the contractor to buy into the design process, to adopt precontract designs as if they were his own and to have full knowledge of the design process by developing the detail of those designs. Hand in hand with this knowledge comes responsibility for maki ng sure that those designs can successfully be turned into the completed works ( Mosey 1998). Design build allows for buildability (an experienced contractor can spot practical problems in a design that might make it difficult to build) and value engineering (an experienced contractor can work out a cheaper way of achieving the same end result) (Mosey 1998). Disadvantages of DesignBuild Some of the disadvantages of DB are: 1. Time and cost of implementing a competitive designbuild process. The time and cost to prepare the scope of work definitions for Requests for Proposals can be substantial, depending on how much design the owner wants to establish itself. Often the owner will need to have a consultant assisting it in this process. 2. Owner interference. O wners who are used to having full control and oversight over each and every aspect of the design may have problems in successfully implementing a design build program. An overly involved owner may impact the efficiency of the design builders progress, del aying the work and increasing the designbuilders costs. It may also impose design constraints on the designbuilder, potentially damaging the single point of responsibility protection.

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27 3. Incomplete design definition. The counterpoint to the benefit of ear ly price guarantee is the fact that many owners are accustomed to having 100% complete design package before obtaining a construction price. Depending on the procurement method used for designbuild, price may be set at an early stage of design, leaving the potential for disputes over what is and is not within the scope of the contract. 4. Reliance on the design builders A/E. Some owners do not like the idea of having the A/E of record financially tied to the contractor. 5. Evolving licensing and public procurem ent laws. Substantial progress has been made toward facilitating the use of designbuild for public agencies. However, it still remains difficult in many jurisdictions for public agencies to use designbuild effectively. Likewise, many of the licensing law s around the country are not friendly to alternative project delivery and can force parties to use creative contract arrangements to obtain the single point of responsibility. 6. Lack of substantial judicial precedent. Because the designbuild system is rela tively new in modern times, and because of the lack of conflict to date, few cases exist to describe to the parties their respective rights, responsibilities, and liabilities. This can be unsettling to those who have been involved in other delivery systems where these issues have been well established for many years ( Mosey 1998) Hybrids Hybrids, a new combination procurement method that has come about it known as Design manage construct; wh ich is a combination of construction management and designbuild (Mosey 1998). The contractor in this process is asked to submit an offer to perform the role of construction manager during a preconstruction period and then convert to design and build contractor when the design of the works has been completed and lump sum price has been agreed(Mosey 1998). There are two parts under this procurement method, phase 1, preconstruction, and phase 2, construction (Mosey 1998). Almost every implementation, how ever, of designbuild has been done by altering traditional competitive bidding laws, regulations, policies and practices to permit contract award to be based on subjective criteria(Guyer 2012).

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28 Advantages of h ybrids From the design and build contractor s point of view, there are also significant advantages in this mixture of construction management with design and build: 1. The contractor can be confident of subcontract prices received, without conducting accelerated or informal subcontract tenders during a limited main contract tender period; 2. The contractor can assess accurately and price the design development risk, having been involved in the design process together with the design team throughout; 3. The contractor can assume responsibility on an informed basis for a design with which he has been involved from the outset; 4. Most importantly, the contractor can enjoy the prospect of a negotiated job at a sensible price, rather than a main contract won by tendering a lump sum price at a cut throat margin in the hope that this may be made up with variations or other claims at a later stage in the works(Mosey 1998). Similarities Under both design and build and traditional procurement, the main contractor will be heavily reliant on a significant number of other parties engaged by it to perform specific parts of the works (sub contractors) and to supply specific materials and goods required for the purpose of the works (suppliers) (Mosey 1998). Differences The Design Build Institute of America (D B IA) defines t he difference between design/build delivery and traditional delivery methods, where an architect/engineer prepares a set of plans and specifications for competitive bid, in terms of the warranty. In design/build the design builder warrants to the owner that the end product is free of defects (Connor 2003). The only way that changes can occur is if there are blatant changes in the scope of the project (Connor 2003). The design builder is not allowed claims for design errors (Connor 2003).

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29 By contrast, i n designbid build the owner warrants to the contractor that the design is free of defects. This is the key to other competitive bid environment and this the reason for change orders when designs are incomplete or contain errors the owner is making good on the warranty (Connor 2003). Another difference between DB and DBB procurement is their relationship of the owners professional agent (if applicable) which depends on what type and quantity of directions is given from the owner and the consequences that ensue (Mosey 1998). Furthermore, it would be unsafe to just reduce each method to their pros and cons because each procurement method should be evaluated on an individual basis that considers the owners needs and priorities (Mosey 1998). Differences between Procurement and Delivery Process A construction delivery process defines: Contractual relationships between participants in the project Authorities, processes and reporting relationships A construction procurement process defines: Criteria for award of contract Process for award of contract (Guyer 2012). Design bid build is a combination of the delivery and the procurement process (Guyer 2012) For public and private owners, there are two types of criteria for awarding contracts, including designbui ld contracts; subjective and objective (Guyer 2012). History To achieve optimum success, the delivery method should be chosen based on the specific project; followed by selecting the right people to maximize the efficiency of

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30 the delivery method (Lucas 20 13). One way an owner may choose a delivery method is based on past failures throughout history (2011). Design Build could be considered the oldest method dating back to the Pharaohs master builders whose works have survived the test of time (Connor 2003). The traditional designbid build approach is surprisingly, a new system that has only been around for about 160 years ( Cushman 2001). However, the design build system has been around for four millennia, and is known as the master builder concept ( Cushman 2001). Historically, the master builder took on his palace or cathedral commission knowing that he had to complete it and that the client body would be in no mood to hear the explanation if any part fell off or did not work. The risk of incarcerat ion or excommunication may have been more compelling than modern commercial incentives, but there was no doubt in anyones mind as to who carried the can (Mosey 1998). The master builder would take full credit and responsibility for the project ( Cushman 2 001). The master builder was able to integrate conceptual design with functional performance all the way through the medieval times (Cushman 2001). History not only provides failures to improve upon but also it provides the circumstances that started th e desire for new delivery methods. The industrial revolution created new materials, which in turn needed more design information in order to construct (2011). This started the separation between designer and contractor (Lucas 2013). This gap grew larger as the inventions increased, and profit became the primary goal for construction (2011). But, The common law concept of the lumpsum contract relying on the traditional trade practices gradually eroded (2011). Now, construction is

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31 becoming a more knowledgeable trade with educated workers and the industry is looking for a new delivery method to maximize efficiency. DBIA The Design Build Institute of America (DBIA) changed the way some professionals view designbuild (Cushman 2001). Formed in 1993, DBIA is a nonprofit organization dedicated to expanding the use of designbuild and promulgating the best designbuild practices (Cushman 2001). DBIA would try to reassure the public and private sector regarding concerns about th is delivery process when it was es tablished (Cushman 2001). DBIA created a Manual of Practice that detailed the process and addressed these concerns, while also demonstrating how to use this process properly and efficiently (Cushman 2001). This manual not only shows publications regarding designbuild but also contains a cookbook for how to approach this delivery system (Cushman 2001). DBIAs outreach program with owners, as well as its active involvement in procurement and licensing reform, has had a major impact on how the industry per ceives the process(Cushman 2001). Does It All Work ? Design and build should work. It allows the designers to design and the builders to build. In this sense every partner in the project is doing what they do their best, and each contributes to the fulles t in the project (Mosey 1998). On the other hand, Design Bid Builds major flaw is the delays associated with the process. These delays are attributed to the step by step process because each step relies on the completion of the previous step. In order to fix this problem, the delivery method, DesignBuild, was created to reduce the major players to just the owner and designbuilder (2011). But not all jurisdictions allow this to happen. While design build attempts to simplify and hasten

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32 building construc tion, it is not the answer to every owners prayer for a well designed and well built building for a fair and economical price (2011). There are always going to be conflicts when two people are negotiating, they just vary in the degree of conflicts ( Lucas 2013). As with designers and their consultants, the more persons involved in a project the greater the potential for disagreements, disputes, and problems, especially in placing responsibility for deficiencies in the work. Design Build does little to change this fact (2011). Many commercial developers continue to prefer traditional procurement, working in close cooperation with design teams and contractors, often engaged under partnering arrangements on a series of projects(Mosey 1998). Another factor that may persuade an owner into contracting with a designbuild firm is what type of reputation the company has established ( Lucas 2013). If the company has a good reputation, then the owner may be more inclined to choose the designbuild firm even if that is their first time using design build ( Lucas 2013). Design build is seen by many as a way to reduce or eliminate such problems and inefficiencies. But there is no sure an overriding reason why it should, because the same problems can exist within the design build team: It depends on the key persons and the relations and differences among them (2011). Furthermore, it should promote better communication and trust between contractor and designer since their goals are mutual; however, it can do nothing radically new or special for trust and communication between contractor and owner (2011). That is why it is very important that the owner and designbuilder must have an outstanding positive relationship (2011). But to be

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33 successful in any construction jo b delivery method you should have an outstanding positive relationship with the owner (2011). Design Build is supposed to be a great new delivery system that solves almost all the c urrent problems of construction. H owever it can only solve these problems by placing the owner in a disadvantageous position (2011). The only way to fix this problem for the owner is to hire a professional advisor or agent that supports you, as the owner and gives cost and selection feedback (2011). This professional advisor or agent that is in between the owner and the designbuilder, also known as bridging, in turns creates the original traditional designbid build delivery method relationships (2011). But if the costs savings are supposed to be produced by cutting the middle man out, the professional advisor or agent, how can you obtain both? In designbuild project some possible ways of reducing the total costs include the following (with likely alternatives or counter arguments added): Making a designbuild contract that s tipulates either a fixed or a guaranteed maximum cost (GMCPF) to the owner; a fixed cost for a commonplace building or a GMCPF for an unusual one (This can be done also in a traditional arrangement.) Saving project time and related indirect costs by overlapping designing and building (This can be done also in a traditional arrangement by having several sub projects, several separate contractors, and a construction manager.) Saving project time and costs by more direct communications (This too can be achieved in a traditional project.) Saving direct costs through innovative design and building methods (This can be achieved by value engineering and by involving either a building contractor, a construction manager, or a cost consultant in the design process lea ding to a traditional contract ) ( 2011) From these cost saving items, it appears to show that the same advantages achieved by designbuild can be achieved with the traditional method as well (2011).

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34 Therefore, even at first glance, designbuild appears to reduce pro blems in deficiencies in work and delegation of powers, where in fact the potential problems not only extends to design build; a designbuild project may make the potential problem for an owner even larger because contractor and designer now are together in seeking to share the same profit (2011). The only way to make this profit sharing work is to have the designer and the contractor in one cohesive unit within the same designbuild company (2011). Often, however, that is not the case, in part because i n many jurisdictions a registered architect cannot provide architectural services from within construction company, or because a construction company cannot provide what are seen legally as architectural services (2011). The fact remains that dealing w ith a diverse group of designers and/or a diverse group of contractors leaves the construction client feeling uncomfortable as to who carries the ultimate responsibility for delivering the end product(Mosey 1998). Jurisdictions In the court system, it is very difficult to figure out who is at fault when it comes to disputes in the construction industry. In the traditional contract method, the division of responsibility is highly detailed and laid out in the AIA Document A201 or Document CCD2 and their mea ns of communication are much more direct, immediate and informal (2011).This makes it a little easier for the court system to find out who is truly at fault and who needs to compensate who m and for how much. However, in designbuild contract method, every thing is opposite. Design Build contracts put all the responsibilities as one single responsibility for many professionals under that single umbrella (Ellis 2008). Furthermore, this hinders the court system from finding out who is at fault and how to compe nsate the owner for problems found (2011). However, the

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35 consolidation of legal right and responsibilities can, and in my experience generally does, greatly reduce the temptation to pursue imaginative claims (Mosey 1998). The construction industry still separates design and construction mostly, because the U.S. government developed public contract laws continuing the separation of design and construction (Cushman 2001). Construction contracts were to be awarded on the basis of lowest responsible bidder to protect the public from corruption (Cushman 2001). However, the construction industry wanted a better mousetrap, and therefore came up with designbuild, where the design and construction are together (Cushman 2001). In the B eginning The AIAs firs t code of ethics, adopted in 1909, forbade its members from participating in designbuild projects due to a perceived conflict of interest in protecting the owner while at the same time profiting from the construction labor and materials (Solomon 2005). T he local and national laws were made based on designbid build contracting method so that no other method could be utilized (Solomon 2005). Design build has shifted its legality status recently. the landscape of construction agreements has changed considerably as construction projects have become more complex and the development of building systems designed by members of our Society are called to perform at ever increasing levels(Connor 2003). AIA adopted a new Code of Ethics in 1986 that no longer for bade design build; the federal government has gradually come to embrace the process; and according to G. William Quatman, FAIA, a licensed architect and attorney with the law firm of Shughart Thomson and Kilroy in Kansas City, Missouri currently all but si x states have laws that permit some level of designbuild for public projects (Solomon 2005).

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36 Why the Change? Over the years, design build enthusiasts believe that designbid build builds separation and conflicts between the parties involved since they have separate contracts with the owner (Solomon 2005). Owners are fed up with designbid build; they are demanding designbuild because it saves time and money and reduces conflict (Solomon 2005). Faces of Design Build One of the first things architects need to understand is that there are many permutations of designbuild (Solomon 2005). The contractor does not have to lead the project, even though that is how it is run most of the time (Solomon 2005). In addition, designbuild can have an agent working on behalf of the owner to ensure the owner gets what they are asking for (Lucas 2013). The service, for example, can be provided by a project specific joint venture between an architecture firm and a contracting company, a single company that has both des igners and builders on staff, or an individual developer, builder, or architect who subcontracts the other necessary expertise and skills for a given project(Solomon 2005). Another author, Michael C. Connor, noted that Design Build can be delivered in on e of two ways: Contractor led designbuild or Designer led designbuild (Connor 2003). According the DesignBuild Contracting Handbook (Cushman 2001) there are more than just two faces of DesignBuild. However, the researcher will be explaining the pri mary faces of Design Build in a subsequent section. Contractor led Design Build In contractor led designbuild, the contractor is responsible for hiring all employees and subcontractors and creating the contracts between them for the project

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37 (Connor 2003). Design firms that joint venture with the contractor may not realize that there is a lot of liability behind this type of partnership (Connor 2003). Contractors carry performance bonds on most projects and have significant financial resources to control losses on an isolated project. Design firms typically do not maintain such financial resources (Connor 2003). If the joint venture should fail, the design firm does not have financial resources as stated above or financial backing in order to finish the job, which could result in financial troubles for the design firm (Connor 2003). In order to make it work for the design team, designers will limit their input to just documents with respect to the desi gn development (Connor 2003). Most two part designbu ild contracts allow for the contractor to be paid for developing this level of documentation to formulate a guaranteed maximum price (GMP) as Phase One. If the price and/or terms of the final construction contract are not agreeable, the parties will separate (Connor 2003). The GMP was created by the contractor with the designers documents and these documents should have little modifications (Connor 2003). If the project moves forward, the modification will be sorted out through the shopdrawing phase by t he contractor (Connor 2003). Designer led Design Build Designer led design build should only be undertaken if the designer has construction experience inhouse and has a relationship with the bonding companies commensurate with a contractor. Designers als o may be faced with large general liability or umbrella insurance premiums due to taking on construction liability where exposure to loss of life is much higher under the care of the prime (Connor 2003). In this case, a construction safety incentive progr am is necessary (Connor 2003). However, if a design firm desires to go into designbuild, creating a separate company

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38 (usually a limited liability company) to perform the construction tasks might shield the design firm from construction liability(Connor 2003). Another problem the designers may run into is state licensing laws because all states license architects and engineers, but not all states license contractors (Connor 2003). Selection Process Selection of the appropriate alternative PDM is a complex decisionmaking process (Touran et al. 2011). Trust is a major factor of completing a project with any delivery method (Connor 2003). An effective design and build contract requires an increased level of trust between the client and contractor in any event, and should be less dependent on regular and intrusive monitoring of the contractors performance(Mosey 1998). The owner must rely upon the contractor to provide the quality the owner expects without cutting corners and the contractor must rely upon the owner not to abuse the no change order environment. When this ingredient is in place and competent people do the work, designbuild can be a wonderful experience for all parties (Connor 2003). The most successful designbuild projects that Willi am Hellmuth, AIA, president of HOK, has been associated with are those that are selected through a competition in which the submissions are judged on value, not just the lowest price(Solomon 2005). The best value (BV) practice is also known as designbui ld and lowest bid (LB) procurement is known as the traditional method or designbid build (Yu and Wang 2012). In a number of cases, the government procurement officers are confronted with liability of illegally favoring a contractor when BV is adopted ins tead of LB because of the concern that the contracted values of BV procurements are usually higher than those of LB procurements(Yu and Wang 2012). Because of this concern, there are

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39 many barriers in order to stop personnel from adopting the BV procurement method (Yu and Wang 2012). Unfortunately, there has yet to be any objective model developed to support a BV decision (Yu and Wang 2012). Why BV Rather Than LB? BV refers to the procurement method that selects the contractor most advantageous to the cl ient by contemplating prices and other factors. Advantages of LB over BV methods include a simplified process of solicitation preparation and review, a simplified selection process, and the difficulty of protest by the bidders Their disadvantages comprise ignorance of quality, assumption of perfect (unambiguous) plans and specifications, and assumptions of minimum requirements meeting clients need (Yu and Wang 2012). In order to decide which method is best for the owner, researchers have developed different evaluation methods, such as simple weighting, multicriterion decision making (including multi attribute utility theory, analytical hierarchy process), cluster analysis, fuzzy set theory, discriminant analysis, and etc. (Yu and Wang 2012). In BV procu rements, the best contractor is that of which the contractor is unique in such a way as to distinguish him/herself from the competition (Yu and Wang 2012). That is, the contractors should be heterogeneous in providing their works (or products), meeting the criteria that are more beneficial to the client (Yu and Wang 2012). This will be the prerequisite for deciding BV or LB (Yu and Wang 2012). If a client can measure the heterogeneity of the contractors, he or she should be able to determine whether to a dopt BV or LB (Yu and Wang 2012). The heterogeneity is the different quality (conceived by the consumers and measured by a set of predefined selection criteria) of contractors (in a bid competition) that reaches equilibrium of price in the market (Yu and Wang 2012). The price equilibrium in the market is a state in which

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40 economic forces are balanced and, in the absence of external influences, the (equilibrium) values of economic variables remain constant (Yu and Wang 2012). The contractor will offer a bidprice on the basis of the performance of work he or she commits (in the plans) to provide to the client. As a result, the heterogeneity of contractors is associated with the combination of bidprice and the performance they offer (Yu and Wang 2012) Why Disputes? The apportionment of responsibility between designers and contractors, as well as between designers themselves, has been the cause of many complex construction disputes. This is in turn has encouraged the renaissance of a procurement arrangement under which the contractor accepts responsibility for the design of the works as well as their execution (Mosey 1998). In the past decade, there has been a pendulum shift in the industry from designbuild doubters to designbuild advocates. F or example: Some in the industry have come to believe that using designbuild is the way to solve any problem on any project. They forgot that designbuild is simply a delivery method, and that other key issues including procurement approach, proper contractual risk allocation, and perhaps most importantly, the owners willingness to pay a reasonable price for what they are asking are vital to project success as the delivery system. The design build process is being misused by many owners. Consider the owner who uses designbuild simply as a way of avoiding liability for improper design. The owner might design the project to a significant extent (from 30% to as much as 90% of the design) and then solicit designbuild proposals, with the low bidder winning the award. This is a designbid build approach based on incomplete plans and specifications; it does not have the characteristics of a properly developed designbuild process. Given the largely positive press that designbuild has received, many owners fail to think carefully about whether it is the best delivery system to achieve their unique project needs. This may be as problematic as those owners in past years who would not even consider designbuild because of their commitment to other

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41 project deli very systems. The reality is that some projects are not suitable for designbuild particularly when an owner needs broad control and has a high level of distrust as to whether the designbuilder should have discretion over project design parameters(Cushman 2001). Due to these limitations and disputes, it is important to analyze the project before choosing the appropriate delivery system (Cushman 2001). How M any Design Build s ? Currently, we are told that design a nd build takes up nearly 40 per cent of the UK construction market share, and the attractions of greater cost and time certainty as well as a single point responsibility are hard to deny(Mosey 1998). How M any Design Builds in Lawsuits? When asked for his views, one of my clients immediately pointe d out the alternative title Design and Build Inaction, and of course it is true that not every D&B project is a runaway success. However, of the several hundred design and build contracts which my firm has drafted and negotiated over the last decade, les s than ten to my knowledge have ever found their way to court or arbitration(Mosey 1998). So W hy is Design Build, Bid Rigging? This situation raises the ethical issues for professional engineers (and architects). It also raises ethical issues for public agency managers (many of whom may be professional engineers). And it raises business issues for private owners that they would be wise to consider (Guyer 2012). Subjective Criteria The concepts underlying the criteria are laudable: award the contract to the most qualified competitor; award the contract to the most experienced contractor; award the contract to the competitor who will deliver best value to the awarding agency or

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42 company. However, in making a judgment about which competitor is best qualified, most experienced, or will deliver the best value, subjective judgments must be made. When subjective judgments are permitted in the award process there is the opportunity for inappropriate covert criteria to be used, such as: 1. Political patronage 2. Exchange of favors (candidly, bribes) 3. Personal relationships (Guyer 2012). The criteria is created by managers that are making subjective judgments in order to form a guideline for a bidding process(Guyer 2012).These managers that are in charge of making the wei ghting criteria, will usually use a point system to evaluate the bids (Guyer 2012). Such point systems are not objective because subjective judgments must be made in determining how many points to award each competitor on specific subjective criterion (G uyer 2012). The weighting of criteria is subjective (Guyer 2012). The only way to institutionalize long term integrity of an agencys or companys procurement process is if it is based on the only practicable objective criterion: lowest cost as determi ned by competitive bidding (Guyer 2012). Objective Criteria An objective criterion does not allow subjective criteria as an option because it would influence the awarding bid process (Guyer 2012). The one and only objective criterion is lowest cost (Guyer 2012). Conflicts in DesignBuild Process Where is the dividing line between the engineers responsibility to the economic interests of the general contractor and the cost, quality and serviceability interests of the building owner( Guyer 2012)? When usi ng someone elses money, public agencies, the procurement process loses integrity because the government is just utilizing taxpayers

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43 money, not money directly from their pocket (Guyer 2012). It is also important in the private sector where stockholders money is spent and corporate management has a duty to expand corporate funds wisely and without waste (Guyer 2012). In other words, the integrity of the procurement process is question able and becomes an ethical issue (Guyer 2012) Designbuild contracts should not be awarded based on subjective criteria that can be manipulated by managers in order to award contracts to inappropriately favored contractors (Guyer 2012). There is no reason that designbuild has to be based on subjective criteria since all of the real benefits of the design build construction delivery process can be realized for the benefit of the owner using a construction procurement process that utilizes objective criteria for award of the designbuild contract and thereby protects the integrity of the procurement process (Guyer 2012). Public and private sectors parallel this statement (Guyer 2012). Bid Rigging Bid rigging, similar to price fixing agreements, are illegal under the Sherman Act ( Parkman and White 2011) This act states that all forms of bidding schemes are illegal ( Parkman and White 2011) Bid rigging refers to competitors that agree to reduce competition in the bidding process by any number of methods, including submitting artificially high bids or having one firm agree not to submit a bid at all By preventing the lowest possible bid from being submitted, a bidding firm is able to charge a premium for its se rvices. This deprives the contracting party of the benefit of the competitive bidding process(i.e. performance of the job at the lowest possible cost) ( Parkman and White 2011) With respect to anti competitiveness, the Sherman act states Every contract, combination in the form of trust or otherwise, or conspiracy, in restr aint of trade or commerce among the several states, or with foreign nations, is declared to be illegal

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44 ( Parkman and White 2011) In sum, under the first section of the Sherman Antitrust Act, in order to show a violation, the prosecution must prove three elements beyond a reasonable doubt. The government must show the exist ence of an agreement, which unreasonably restrains competition, and affects interstate commerce ( Parkman and White 2011 ) The U.S. Supreme Court said in Spectrum, Inc v. McQuillan "The purpose of the [Sherman] Act is not to protect businesses from the working of the market; it is to protect the public from the failure of th e market. The law directs itself not against conduct which is competitive, even severely so, but against conduct which unfairly tends to destroy competition itself. This focus of U.S. competition law, on protection of competition rather than competitors, i s not necessarily the only possible focus or purpose of competition law (Spectrum Sports, Inc v. McQuillan 506. U.S. 447 1993). Some Solutions to DesignBuild The primary legal alternatives for DesignBuild are DesignBid Build, Construction Management, and Construction Management at Risk that are based on objective criteria such as lowest cost ( Guyer 2012) These solutions have been detailed in the beginning of th is Chapter

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45 Figure 21. Design Bid Build: Construction Delivery Process [Adapted from Guyer, P. E., R.A. (2012). "Ethical Issues in DesignBuild."] Figure 22. Design Build: Construction Delivery Process [Adapted from Guyer, P. E., R.A. (2012). "Ethical Issues in DesignBuild."] OWNER ENGINEER GENERAL CONTRACTOR SUB CONTRACTOR OWNER GENERAL CONTRAC TOR ENGINEER SUB CONTRACTOR

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46 CHAPTER 3 METHODOLOGY The research will examine the designbuild survey data collected and will determine what, if any, consensus there is on design build. Many different players in the industry were contacted to fill out the survey questionnaire in an attempt to provide a variation, large number of responses. The goal of this experiment is to determine whether companies view designbuild as bid rigging, a process considered illegal and unethical. These responses to the survey will be organized to facilitate review and study of their relation to the subject of designbuild, and its practices and ethical dilemmas. Once all of the opinions of the responding companies have been analyzed, the researcher will compare them to the demographic data to test whether there are significant trends related to location, size of company, monetary units, type of company, employee count, project type and amount, RFP requirements, preference of delivery method, and protestation of bids. Measures The researcher used a survey to conduct her experiment. Th e survey used surface mail as well as a website survey link sent to the recipients so they could fill out the survey whichever method they preferred. For the recipients that were only contacted via email, the researcher attached a copy of the survey and had the same link for the survey website. To ensure unbiased results the survey was returned anonymously though the website or postal addressed with no return address. Al l surveys mailed contained a prepostage stamped envelope with the researchers address in order to encourage the

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47 recipient to fill it out and to make sure that they did not have to perform any extra work that would deter them from completing and returning the survey. No personal interviews were conducted in an attempt to minimize any bias due to predisposition of the researchers beliefs on the subject. The researcher did provide contact information in the letter to the recipients in case they needed any as sistance or had any concerns. In one case, the researcher was contacted regarding a subject's suitability for the survey. The researcher remained unbiased during this phone call and explained the purpose of the survey was to gather opinions from a wide range of firms. The survey was written without question bias of all types. To ensure that it was unbiased, the researcher had the survey reviewed by multiple people, including professional editors and her advisor The survey consisted of twenty two questions with a majority being multiple choice with an extended response to contribute qualitative data as well, especially if they had filled out other. The answers were tabulated by frequency of answers selected For example, ten yess, twelve nos, zero some times, five not applicable, and some no responses. The first few questions were informative in order to compare them to the main bid rigging question regarding DesignBuild. The frequency scores indicated the number of times each answer option was select ed Some questions allowed the respondent to circle all that apply. The questionnaire measured whether designbuild could be used as a form of bid rigging and if it should be allowed for public and/or private projects. Validity and Reliability The relia bility of the re search cannot be proven because the researcher has only performed this survey one time according to the nonprobability sampling method.

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48 Therefore, there is no evidence of reliability available unless the researcher is able to conduct this survey more times and in other locations. The validity of this data is that we are measuring what the researcher hopes to measure. This research is valid because it does stack up with other variables in the data. Therefore, currently the research is valid but no reliable. A depiction of this meaning is shown in Figure 31. Figure 3 1. Validity vs. Reliability [Adapted from Sosulski, P. C. W. a. K. (2002). "Quantitative Methods in Social Sciences." QMSS eLessons, . (June 9, 2013). ] Subjects/ Participants The researcher did a comprehensive search on G oogle and other search engines to find contractors and people involved with the bidding process, such as architects, lawy ers, owners and landlords The majority of survey recipients were contractors as they are the most familiar with delivery methods including designbuild. The researcher collected recipients from the S outheast with a focus on major cities in Florida.

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49 Nonpr obability sampling, Availability Sampling, was the method that was chosen for this research. This method was chosen because it was a largescale social survey and the researcher could not select the kinds of probability samples. Using this method, the results will not show the likelihood that any element of a population will be selected for the study which is the main drawback of this type of method. This methods primary advantage is that it is very easy for the researcher to find subjects for the study. Al so, it used good for using as a preliminary survey to figure out if the questions make sense to the respondents. Since this is the first survey discussing this information, this is the appropriate method to use. Also, since there are always new firms getti ng established in construction, the researcher woul d not know the population or an estimate of it. Therefore, the drawback to this method is relevant no matter the situation. Another drawback to nonprobability sampling is that it does not involve random selection whereas probability sampling does. This does not mean that it is not representative of the population though. It just means that the researcher cannot depend upon the rationale of the probability theory. Again, we cannot perform probability sampli ng because it is not feasible in this type of survey since its social research. Preparations In preparation of this thesis, the researcher conducted a literature review, to make sure that her topic was original and to analyze the data that was previously done with respect to her topic. Through this literature review, the researcher found that her topic was original, and that there was very little data or papers regarding a correlation

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50 between designbuild and bid rigging This meant the researcher would hav e to conduct her own in depth research as described throughout this methodology. Data Collection The researcher sent out 505 surveys which includes a combination of emails and postage mailings. The researcher received forty four survey responses Not all of the respondents completed the whole survey so most of the total responses for the questions varied. The surveys were sent out through mail and email on March 15, 2013. The researcher started receiving responses that day on surveymonkey.com, which is th e survey website the researcher used in order to collect the data. Mailed responses started to arrive the following week. No follow up emails or mailing s were used since it was an anonymous survey and there would be no way to figure out who did/ did not fi ll out the survey in order to only send the follow up letters to them. The end date for data collection was June 9, 2013. The materials were sent to recipients via email or mailed. Each package contained a letter to the recipient, the survey, a self addressed stamped envelope (if mailed via post office), and a definition list of useful terms relevant to the survey. This made sure that all recipients could answer the question on a level playing field with no discrepancies which could reduce the response err ors made by participants. The letter to the recipient is located in Appendix A This letter introduced the survey and gave instructions to either fill out and return through mail with the self addressed stamped envelope or fill out the survey online with t he link provided. The letter also contained the researchers contact information just in case a recipient had any concerns, questions or comments. The letter encouraged the recipient to fill out the survey to the best of their abilities while remaining anonymous. Anonymity was used to ensure unbiased results

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51 A copy of the survey is located in Appendix C The self addressed stamped envelope was also provided to encourage participation. Timeline Figure 32. Timeline of Data Collection Data Analysis Several researc h questions are being addressed; therefore, the researcher will describe the data analysis that will be used for each research question as follows:

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52 1. A response to research question one, regarding the business the recipient is in, will be g enerated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 2. A response to research question two, regarding the type of business of the recipient, will be generated by recording frequencies, and graphing the frequencies in a bar and pie chart. 3. A response to research question three, regarding the amount of employees the recipient has, will be generated by recording frequencies in terms of bins and graphing them in a histogram. 4. A response to research question four, regarding the annual volume of business, will be generated by recording frequencies in terms of bins and graphing them in a histogram. 5. A response to research question five, regarding location of recipient, will be generated by recording frequencies in terms of bins and graphing them in a table and a map. 6. A response to research question six, regarding the type of project delivery method preferred, will be generated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 7. A response to research question seven, regarding the amount of projects bid on over past five years, will be generated by recording frequencies in terms of bins and graphing them in a histogram. 8. A response to research question eight, regarding the amount of DB projects bid on, will be generated by recording frequencies in terms of bins and graphing them in a histogram. 9. A response to research question nine, regarding the amount of DB projects awarded, will be generated by recording frequencies in terms of bins and graphing them in a histogram. 10. A response to r esearch question ten, regarding the amount of DB projects awarded in public projects, will be generated by recording frequencies in terms of bins and graphing them in a histogram. 11. A response to research question eleven, regarding preference on DB projects, will be generated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. Also, a response to this extended answer results will be generated by coding the data and organizing it in bullet points.

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53 12. A response to research question twelve, regarding DB for public projects, will be generated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. Also, a response to this extended answer results will be generated by coding the data and organizing it in bullet points. 13. A response to resear ch question thirteen, regarding DB for private projects, will be generated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P value to the alpha value, and explaining the outcomes in terms of the null and alternati ve hypothesis. 14. A response to research question fourteen, regarding the amount of RFP criteria, will be generated by recording frequencies and graphing the frequencies Also, a response to this extended answer results will be generated by coding the data and organizing it in bullet points. 15. A response to research question fifteen, regarding meeting the RFPs criteria, will be generated by recording frequencies and graphing the frequencies Also, a response to this extended answer results will be generated by coding the data and organizing it in bullet points. 16. A response to research question sixteen, regarding not meeting criteria in RFP, will be generated by recording frequencies and graphing the frequencies. Also, a response to this extended answer results wi ll be generated by coding the data and organizing it in bullet points. 17. A response to research question seventeen, regarding DB in reference to bid rigging, will be generated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 18. A response to research question eighteen, regarding protests of bids not awarded, will be generated by recording frequencies and graphing the frequencies. 19. A response to research question nineteen, regarding bonds for protesting a bid, will be generated by recording frequencies and graphing the frequencies. 20. A response to research question twenty, regarding amount of bonds to protest a bid, will be generated by recording frequencies and graphing the frequencies. 21. A response to research question twenty one, regarding amount of bonds lost to protest a bid, will be generated by recording frequencies and graphing the frequencies. 22. A response to research question twenty two, regarding DB in reference to equal opportunity for bidders, will be generated by recording frequencies, graphing the frequencies, calculating the P Value, comparing the P value to the alpha value, and explaining the outcomes in ter ms of the null and alternative hypothesis.

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54 23. Question 17 vs. Question1 : A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 24. Question 17 vs. Question 3 : A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 25. Question 17 vs. Question 6 : A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 26. Question 17 vs. Question 7 : A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, com paring the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 27. Question 17 vs. Question 8 : A comparative response to these two questions will be generated by determining frequencies in comparison, calcul ating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 28. Question 17 vs. Question 9 : A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 29. Question 17 vs. Question 10: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 30. Question 17 vs. Question 11: A comparative response to these two questions will be ge nerated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 31. Question 17 vs. Question 12: A comparative response to these two q uestions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 32. Question 17 vs. Question 13: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value,

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55 comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 33. Question 17 vs. Question 15: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 34. Question 17 vs. Question 22: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hy pothesis. 35. Question 11 vs. Question 9 : A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 36. Question 11 vs. Question 12: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 37. Question 11 vs. Question 13: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis. 38. Question 11 vs. Question 15: A comparative response to these two questions will be generated by determining frequencies in comparison, calculating P Value, comparing the P Value to the alpha value, and explaining the outcomes in terms of the null and alternative hypothesis.

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56 CHAPTER 4 RESULTS The survey response rates were low overall. The researcher mailed and emailed a plethora of surveys, but unfortunately a low number of participated due to uncontrollable forces like nonresponse bias. The respondent demographic is detailed in the methodology section. The researcher did not use common demographics as they would not be relevant to the survey. The author deleted some of the question res ults that did not correspond to the primary purpose of this research. These questions are 18, 19, 20, and 21 and are available to view in Appendix C These results could be used as a secondary source to further investigate DB as they have to do with monetary volumes for protesting awards of bids Assumptions The researcher made a preliminary assumption in order to do the following representation of data and statistical analysis. This assumption was to not include the participants that answered Not Applicable or did not answer. Limitations One main limitation with the Chi Squared T ests performed in this data analysis is if more than 20% of the expected values are less t han five, then the Chi Squared T est will not perform at a 100% confidence level. Theref ore, some of the data will not perform at a 100% confidence level unless more samples were retained to increase the expected values. The researcher will note which data this applies to.

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57 According to the results, the majority of respondents dealt with resid ential and commercial projects. The other industries are highly underrepresented due to the limitations of the survey. Potential Sources of Error Figure 41shows the potential sources of error in a diagram to show the hierarchy of errors. Random Sampling Errors Random Sampling Errors are the variations between the population mean and the sample mean. The responses the researcher received were overwhelmingly from residential and commercial businesses; the sample did not return many from other types of businesses. Non Sampling Errors Non sampling errors found in this research are the approach, lack of incentives, questionnaire design, scales, and interviewing method. A primary limitation is the survey model itself; there is very little incentive for individuals to fill out this survey. They do not receive any compensation nor does it further them in their career so they see little motivation except for the fact that they are helping a masters student complete her thesis. The scale of this thesis was large in terms of surveys sent but was small since the respondent quantity was so limited. Response errors Response errors are inaccuracies, mis analyzed, or mis recorded that can be made by the researcher, interviewer and/or participant. These are broken down in more detail below.

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58 Researcher errors Measurement Population definition and sampling Data analysis Interviewer errors Participant selection Questioning and recording Participant errors Inability Unwillingness Non response errors A n on response error occurs when the recipients do not respond at all or when they have no obligation to fill out entire survey. Question Response Analysis The main reason for the research is to figure out if the DesignBuild delivery and procurement method is legal and/or ethical i n the form of bid rigging. The questions will be analyzed in order of their relevance and importance to the study, with demographic analysis and additional qualitative data to follow. Question 17 This question of the survey was posed in order to find if D B could be used as form of bid rigging. The responses from the survey indicated that the majority of the sample population agreed that DB delivery method could be used as a form of bid rigging. Figure 42 shows that more than 50% agreed that the DB deliver y method could be used as a form of bid rigging. Table 41 are the results from the survey, which breaks down the sample population into their respective answer choices.

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59 Numerical results Table 41. Numerical Results of Question 17 A Yes B No C Sometimes D Not applicable 17 5 6 2 Hypotheses Null Hypothesis: There is no difference in observation frequencies and expected frequencies. There is not a significant difference. Variables are independent. Alternative Hypothesis: There is a difference between observation frequencies and expected frequencies. There is a significant difference in the respondents responses. Variables are related. Analysis The null hypothesis is rejected and we accept the alternative hypothesis according to Table 42. There is a dif ference between observation frequencies and expected frequencies. We can say with 99% certainty that there is a significant difference in the respondents responses. More respondents chose Yes over any other answer. Just by looking at the histogram Figur e 42, the level of significance, is quite large as we have proven in the statistics analysis. These results show that almost all the respondents believe that designbuild is a form of bid rigging. The researcher would like to remind you that bid rigging is illegal and unethical. Bid rigging is illegal under the Sherman Act and is defined as when competitors agree to eliminate competition for some piece of defined business, whether it be a sale, a contract, or a project ( Justice 2005)

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60 Chi squared test Table 42. Chisquared test table Sample Obse rvations Expected Yes 17 9.33333333 No 5 9.33333333 Sometimes 6 9.33333333 Question 12 This question on the survey was posed in order to find out if the DB project delivery method should be allowed for public projects. The responses from the survey indicated that more respondents believe that DB should be allowed for public projects. In Figure 43, the answer choice Yes more than doubles answer choices no, and sometimes. Numerical results The numerical results are given in Table 43 to show the distribution of answer choices. Table 43 Numerical Results of Question 12 A Yes B No C Sometimes D Not Applicable 17 7 8 3 Hypotheses Null Hypothesis : There is no difference in whether the respondents believe DB should be allowed for public projects. Alternative Hypothesis: There is a difference in whether the respondents believe DB should be allowed for public projects. P value 0.0086517

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61 Analysis The P Value is less than the alpha value (0.05) so we reject the null hypothesis which is there is no difference in observed and expected as shown in Table 44 Therefore, there is a significant difference in the values presented. Reviewing the results presented, these respondents believe that DB should be allowed to be utilized in public projects. Chi squared test and r esults Table 44 ChiSquared Test and Results Observed Expected Yes 17 10.666667 No 7 10.666667 Sometimes 8 10.666667 P Value 0.058207 In depth Of th ese responses, the researcher asked the respondents the reasoning for their answers. The following are the reasons: Preferential towards Design Build in Public Projects Lower Costs Less Complicated Communications Owner Relationship Opposed to Design Build in Public Projects Unfair Advantages to Large Companies Labor Intensive Financial Risk all on Contractor Bids Based on Subjective Criteria (Performance and Prescriptive Specs) Conditionally Preferential towards Design Build in Public Projects Keeps costs Reasonable Not Applicable

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62 Question 13 This question on the survey was posed in order to find out if the DB project delivery method should be allowed for private projects. The responses from the survey indicated that more respondents believe that DB shoul d be allowed for private projects. This is overwhelming shown in Figure 44 and Table 45 since over 75% of the respondents voted yes. Numerical results Table 45 Numerical Results to Question 13. Yes No Sometimes Not Applicable 29 2 3 0 Hypotheses Null Hypothesis: There is no difference in whether the respondents believe DB should be allowed for private projects. Alternative Hypothesis: There is a difference in whether the respondents believe DB should be allowed for private projects. Analysis Th e P Value is less than the alpha value (0.05 and 0.01). So we can say that we reject the null hypothesis and accept the alternative hypothesis according to Table 46 The alternative hypothesis states that there is a significant difference in the observed versus the expected outcome. In fact we can say that with not only 95% confidence but also with 99% confidence.

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63 Chi squared test and r esults Table 46 ChiSquared Test and Results Observed Expected Yes 29 11.33333333 No 2 11.33333333 Sometimes 3 11 .33333333 P value 0.0000000010 Question 22 This question of the survey was posed in order to find out if DB bids are structured to provide equal opportunity for all bidders. The responses form the survey indicated that the majority of the sample population believe that DB bids are not or are sometimes structured to provide equal opportunities for all bidders, as shown in Figure 4 5 and Table 47 Numerical results Table 47 Numerical Results of Question 22 A Yes B No C Sometimes D Not Applicable 3 8 8 5 Hypotheses Null Hypothesis: There is no difference in whether the respondents believe DB is structure d to provide equal opportunity for all bidders. Alternative Hypothesis: There is a difference in whether the respondents believe DB is structure d to provide equal opportunity for all bidders. Analysis The P Value is greater than the alpha value (0.05) according to Table 48 Therefore, we fail to reject the null hypothesis and reject the alternative hypothesis. The

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64 null hypothesis states that this is no difference in the observed frequencies versus the expected frequencies. Although there is no statistical difference in responses, there is a visual difference in responses shown through the graph and the frequencies. In this question, respondents explai n that design build projects sometimes or do not provide an equal opportunity environment for all bidders. The responses of sometimes and no answers were identical and over double the yes answer choice. Chi squared test and r esults Table 48 ChiSquared Test and Results Observed Expected Yes 3 6.33 No 8 6.33 Sometimes 8 6.33 P Value 0.26826245 Question 3 This question of the survey was posed in order to show the number of employees in the company. As shown by Figure 46 Table 49 and Table 41 0 the number of employees is skewed right with an average of thirty two employees per company. This data will be compared with other question data later to discover if there are any relationships. Numerical results Table 49 Numerical Results for Question 3 Bin Frequency 0 1 40 28 80 4 120 3 160 0 200 1 More 1

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65 Description Table 41 0 Description of Numerical Results Mean 32.8421053 Standard Error 8.27905258 Median 13 Question 4 This question of the survey was posed in order to find the annual volume of business, in dollars of each company. As shown by Figure 47, Table 41 1 and Table 4 1 2 the quantity of projects data is skewed right with an average of $ 29,578,717.9 annual volume of business. This data will be compared with other question data later to discover if there are any relationships. Numerical results Table 41 1 Numerical Results of Question 4 Bin Frequency $45,000,000 29 $90,000,000 7 $135,000,000 0 $180,000,000 2 $225,000,000 0 $270,000,000 1 $315,000,000 0 More 0 Descr iption Table 41 2 Description of Numerical Results Mean $29,578,717.9 Standard Error $8,826,328.7 Median $5,000,000.0 Question 7 This question of the survey was posed in order to find the quantity of projects bid on over the past five years. As shown by Figure 48, Table 41 3 and Table 4 1 4 the

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66 quantity of projects data is skewed right with an average of 938 projects bid on per company over past five years. This data will be compared with other question data later to discover if there are any relati onships. Numerical results Table 41 3 Numerical Results of Question 7 Bin Frequency 4000 36 8000 1 12000 0 16000 0 20000 0 24000 0 28000 1 More 0 Description Table 41 4 Description of Numerical Results Question 8 This question of the survey was posed in order to find the quantity of DB projects bid on over the past five years. As shown by Figure 49, Table 41 5 and Table 41 6 the quantity of projects data is skewed right with an average of eighty nine DB projects bid on per company over past five years. This data will be compared with other question data later to discover if there are any relationships. Numerical results Table 41 5 Numerical Results of Question 8 Bin Frequency 300 35 600 1 Mean 938.684211 Standard Error 661.3055 12 Median 100

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67 Table 415 Cont. 900 0 1200 0 1500 0 1800 0 More 1 Description Table 41 6 Description of Numerical Results Mean 89.1621622 Standard Error 54.3012467 Median 10 Question 9 This question of the survey was posed in order to find the quantit y of DB projects awarded over the past five years. As shown by Figure 410, Table 41 7 and Table 41 8 the quantity of projects data is skewed right with an average of 47 DB projects awarded per company over past five years. This data will be compared wi th other question data later to discover if there are any relationships. Numerical results Table 41 7 Numerical Results of Question 9 Bin Frequency 200 34 400 1 600 0 800 0 1000 0 1200 1 1400 0 More 0

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68 Description Table 41 8 Description of Nume rical Results Mean 47.5555556 Standard Error 33.4837664 Median 5 Question 1 0 This question of the survey was posed in order to find the quantity of DB projects that have been awarded, over the past five years that were public projects. As shown by Figu re 4 11, Table 419 and Table 42 0 the quantity of projects data is skewed right with an average of five DB projects awarded per company over past five years were public projects This data will be compared with other question data later to discover if there are any relationships. Numerical results Table 419. Numerical Results of Question 10 Bin Frequency 25 36 50 0 75 0 100 0 125 0 150 0 175 1 More 0 Description Table 42 0 Description of Numerical Results Mean 5.08108108 Standard Error 4.4 5049148 Median 0

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69 Question 1 This question of the survey was posed in order to find what type of business the firm was in. According to Figure 412, and Table 42 1 more than 50% were commercial and residential companies that responded to the survey. Nu merical data Table 42 1 Numerical Data of Question 1 A (Residential) B (Commercial) C (Industrial) D (Heavy Civil) E (Environmental) F (Other) 19 25 3 2 2 6 Hypotheses Null Hypothesis: There is no difference between the numbers of firms from each industry that responded to the survey. Alternative Hypothesis: There is a difference between the numbers of firms from each industry that responded to the survey. Analysis The P Value is less than the alpha value (0.05 or 0.01) according to Table 42 2 Therefo re, we can reject the null hypothesis and accept the alternative hypothesis with a 99% confidence level. This means there is a difference between the numbers of firms from each industry that responded to the survey. The main difference is that more residential and commercial recipients responded over other industries. This is clearly visible in figure 4 12 Just as a reminder, the limitation in this question is that some of these industries are underrepresented due to the convenience sampling method.

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70 Chi s quared test Table 42 2 Chisquared test Type Frequency Expected Residential 19 9.5 Commercial 25 9.5 Industrial 3 9.5 Heavy Civil 2 9.5 Environmental 2 9.5 Other 6 9.5 Question 2 This question of the survey was posed in ord er to find out what type of business the firm was. According to Figure 413 and Table 42 3 more than 50% were S corporations and Corporations that responded to the survey. Numerical data Table 42 3 Numerical Data for Question 2 A Sole Proprietorship B C orporatio n C Partnershi p D S Corporatio n E Trust F Non Profit Organizatio n G Other 0 16 2 20 1 3 0 Figure 414 illustrate s that almost half of the respondents are S Corporations. Analysis A limitation to this question is that the business types are not equally distributed over all types of businesses. This could possibly provide skewed data results as discussed further in the potential sources of error subsection in the results section. Question 5 This question of the survey was posed in order to find where each firm was located. According to Figure 415 and Table 4 2 4 more respondents were from P Value 0.0000000005

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71 Gainesville, Florida and the near by surrounding area than any other respondents. Only one respondent was from Georgia; we will disregard the Georgia respondent Numerical data Table 42 4 Numerical Data of Question 5 City, State Frequency Gainesville, Florida 18 Newberry, Florida 2 Tampa, Florida 3 Orlando, Florida 2 South Florida 4 Florida (Other) 7 Peachtree, Georgia 1 Analysis A majority of the part icipants were located in Gainesville, Florida. The range location of participants is from Georgia to Florida. Some participants only wrote South Florida or Florida even though they were asked to write a specific city. This may hinder the major results in comparison with locations. Question 6 This question of the survey was posed in order to find out what project delivery method the firm preferred. As shown in Figure 416 and Table 42 5 more respondents prefer DB over the other delivery methods. About 50% of the respondents chose Design Build as their preference. Numerical data Table 42 5 Numerical Data of Question 6 A Design Build B Construction Management (CM) C CM @ Risk D Design Bid Build E Not Applicable 24 10 4 4 4

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72 Hypotheses Null Hypothesis : There is no difference between what type of delivery method is preferred by contractors. Alternative Hypothesis: There is a difference in what type of delivery method is preferred by contractors. Analysis The P Value is less than alpha value (0.01), ther efore we reject the null hypothesis and accept the alternative hypothesis according to Table 42 6 The variables (answers) are related to one another. With 99% confidence, contractors do have a preference for delivery method. Looking at the data, it is cle ar that DB is preferred method. Chi Squared Test and Results Table 42 6 ChiSquared Test and Results Answer Observed Expected Design Build 24 10.5 CM 10 10.5 CM @ Risk 4 10.5 DBB 4 10.5 P Value 0.00001256 Question 11 This question of the survey w as posed in order to find out if the firm preferred working on DB projects. As shown by Figure 417 and Table 42 7 more respondents chose yes, that they prefer working on DB projects. This question is not directly in comparison with any other delivery met hod, it is just an independent question.

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73 Numerical data Table 42 7 Numerical Data for Question 11 A Yes B No C Sometimes D Not Applicable 21 7 9 2 Hypotheses Null Hypothesis: There is no difference between preferences of DB by respondents Alternativ e Hypothesis: There is a difference between preferences of DB by respondents Analysis Since the P Value is less than the alpha value (0.05 and 0.01), we can reject the null hypothesis and accept the alternative hypothesis according to Table 428. Therefor e, contractors do prefer DB projects in general, not just in comparison to other delivery methods as described in question six. Chi squared test and r esults Table 428. ChiSquared Test and Results Observed Expected Yes 21 12.333333 No 7 12.333333 Som etimes 9 12.333333 P Value 0.0095745 In depth The researcher also asked why or why not, to this question. The following are the results of the qualitative data: Preferential towards Design Build Single Responsibility to Owner Flexibility

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74 Owner Relationship Opposed to Design Build Too much competition T oo much risk on GC Conditionally Preferential towards Design Build As long as we are in control Proper Zoning Profitable If the client has the Capitol Not Applicable Question 14 This question of the s urvey was posed in order to find out how many criteria were present in the RFP on average, in their DB projects and what the criteria was that were present. Table 429 shows numerical data that represents each respondents quantity of the average number of criteria. Only a few respondents answered this question, instead they responded to the openended question, What were the criteria listed? Numerical data Table 429. Numerical Data for Question 14 Numerical Answers 20 7 20 30 12 Average 17.8 In depth 1. Criteria Vary Per Project Multiple subcontractors with different c riteria Verbal r equests from c lients 2. RFPs are the Criteria

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75 The Entire RFP Too many to list 3. Not Applicable Question 15 This question of the survey was posed in order to find out if the firm has always been able to meet the criteria required in the DB RFP. As shown in Figure 418 and Table 430, more respondents were able to meet or at least sometimes meet the criteria required by the DB RFP. Numerical data Table 43 0 Numerical Dat a for Question 15 A Yes B No C Sometimes D Not Applicable 13 2 9 9 In depth 1. Always able to meet the Criteria Depends on Project 2. Not a lways able to meet the Criteria Otherwise we do not participate 3. Sometimes able to meet the Criteria Yes Mostly, However sometimes RFP contains errors Unforeseen Circumstances Prevent Meeting Criteria 4. Not Applicable Question 16 This question in the survey was posed in order to find out what they have done if the firm has not been able to meet all the criteria required in the DB RFP In depth This is a breakdown of the answers given by coding qualitative data. 1. No Participation

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76 Decline to Bid / Pursue 2. Not Applicable 3. Attempt to meet Criteria Hire employee in the needed field(s) Question vs. Question Analysis Question 1 7 vs. Question1 This question analysis was posed in order to find the relevance between what type of project the firm builds and how they view DB in terms of bid rigging. Analysis Since the P Value is less than the alpha (0.05), we can reject the null hypothesis and accept the alternative hypothesis according to Tables 4 3 1 and 4 3 2 The alternative hypothesis is stating that there is meaning based on what type of project the firm builds, is how they view DB in terms of bid rigging. Furthermore, residenti al and commercial view DB more as bid rigging over the other types of projects built. Of all the answers, bid rigging was a more popular answer for all projects over not bid rigging or sometimes bid rigging. Table 43 1 Question 17 vs. Question 1 Observed Data Observed Bid rigging Not bid rigging Sometimes Totals Residential 8 1 3 12 Commercial 6 5 7 18 Other 2 5 0 7 Totals 16 11 10 37

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77 Table 43 2 Question 17 vs. Question 1 Expected Data Expected Bid rigging Not bid rigging Sometimes Residen tial 5.189189189 3.567567568 3.24324324 Commercial 7.783783784 5.351351351 4.86486486 Other 3.027027027 2.081081081 1.89189189 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and t he types of projects that participants build. Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and the types of projects that participants build. Limitations Of the nine expected values six of them were less tha n five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 3 This question analysis was posed in order to find the relevance between number of employees and how the firms view DB in terms of bid rigging. Analysis Since the P Value is less than the alpha (0.10), we can rejec t the null hypothesis and accept the alternative hypothesis according to Tables 4 3 3 and 43 4 The alternative hypothesis suggests there is a relationship between number of employees and how the firms view DB in terms of bid rigging. Therefore, the smaller the company (X<25), the more likely it is for them to agree that DB is bid rigging. This is true for the P Value 0.025549382

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78 opposite, as in for larger companies (X>75), the less likely it is for them to agree that DB is bid rigging. Table 43 3 Question 17 vs. Question 3 Observed Data Observed # of Employees Bid rigging Not bid rigging Sometimes Totals X<25 12 2 5 19 25<=X<=75 3 1 1 5 X>75 1 3 0 4 Totals 16 6 6 28 Table 43 4 Question 17 vs. Question 3 Expected Data Expected Bid rigging Not bid rigging Sometimes X<25 10.857143 4.071428571 4.0714286 25<=X<=75 2.8571429 1.071428571 1.0714286 X>75 2.2857143 0.857142857 0.8571429 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and number of em ployees in a firm. Alternative Hypothesis: There is a statistical difference between views on DB as bid rigging and number of employees in a firm. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. P Value 0.0798839

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79 Question 17 vs. Question 6 This question analysis was posed in order to find the relevance between preference of delivery method and how the firms view DB in terms of bid rigging. Analysis Since the P Value is less than the alpha (0.05), we can reject the null hypothesis and accep t the alternative hypothesis according to Tables 4 35 and 436. The alternative hypothesis is stating that there is meaning based on preference of delivery method, is how the firms view DB in terms of bid rigging. Although respondents that answered yes to bid rigging where about equal distribution between DB and NonDB, the respondents that answered no to bid rigging were all DB firms and no respondents answered no to bid rigging that were non DB. Table 43 5 Question 17 vs. Question 6 Observed Data Obser ved Bid rigging Not bid rigging Sometimes Totals (A) Design Build 7 8 4 19 (B) Non design build 8 0 3 11 Totals 15 8 7 30 Table 436. Question 17 vs. Question 6 Expected Data Expected Bid rigging Not bid rigging Sometimes (A) Design Build 9.5 5. 066666667 4.4333333 (B) Non design build 5.5 2.933333333 2.5666667 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and the preference on delivery methods. P Value 0.0379807

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80 Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and the preference on delivery methods. Limitations Of the six expected values three of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 7 This question analysis was posed in order to find the relevance between view on DB in terms of bid rigging and quantity of projects bid on over past five years. Analysis The P Value is greater than the alpha value (0.10), so we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 4 37 and 4 38. Therefore, we cannot prove statistically there is a relationship between view on DB in terms of bid rigging and quantity of projects bid on over past five years. Table 437. Question 17 vs. Question 7 Observed Data Observed Yes No Sometimes Totals X<50 4 1 2 7 50<=X<=200 6 4 5 15 X>200 5 2 0 7 Totals 15 7 7 29 Table 438. Question 17 vs. Question 7 Expected Data and P Value Expected Yes No Sometimes X<50 3.620689655 1.689655172 1.689655172 50<=X<=20 0 7.75862069 3.620689655 3.620689655 X>200 3.620689655 1.689655172 1.689655172 P Value 0.460735

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81 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and the quantity of projects bid on over past five years Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and the quantity of projects bid on over past five years. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the m inimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Ques tion 8 This question analysis was posed in order to find relevance between views on DB in terms of bid rigging and amount of DB projects bid over the past five years. Analysis The P Value is greater than the alpha value (0.10), so we fail to reject the nul l hypothesis and cannot the alternative hypothesis according to Tables 4 39 and 44 0 Therefore, we cannot prove statistically there is a relationship between views on DB in terms of bid rigging and amount of DB projects bid over the past five years. Tabl e 439. Question 17 vs. Question 8 Observed Data Observed Bid rigging Not bid rigging Sometimes Totals X<10 7 2 3 12 10<=X<=50 5 4 3 12 X>50 2 2 1 5 Totals 14 8 7 29

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82 Table 440. Question 17 vs. Question 8 Expected Data Observed Bid rigging Not bid rigging Sometimes X<10 5.793103448 3.310344828 2.896551724 10<=X<=50 5.793103448 3.310344828 2.896551724 X>50 2.413793103 1.379310345 1.206896552 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and amount of DB projects bid on over past five years. Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and amount of DB projects bid on over past five years. Limitations Of the nine expected v alues seven of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 9 This question analysis was posed in order to find relevance between views on DB in terms of bid rigging and amount of DB projects awarded over the past five years. Analysis The P V alue is greater than the alpha value (0.10), so we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 4 4 1 and 4 4 2 Therefore, we cannot prove statistically there is a relationship between views on DB in te rms of bid rigging and amount of DB projects awarded over the past five years. P Value 0.841500769

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83 Table 44 1 Question 17 vs. Question 9 Observed Data Observed Bid rigging Not bid rigging Sometimes Totals X<5 6 1 4 11 5<=X<=10 3 5 2 10 X>10 6 2 1 9 Totals 15 8 7 30 Table 44 2 Question 17 vs. Question 9 Expected Data Expected Bid rigging Not bid rigging Sometimes X<5 5.5 2.933333333 2.566666667 5<=X<=10 5 2.666666667 2.333333333 X>10 4.5 2.4 2.1 Hypotheses Null Hypothesis: There is no s tatistical difference between views on DB is bid rigging and amount of DB projects awarded over past five years. Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and amount of DB projects awarded over past five y ears. Limitations Of the nine expected values seven of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lac k of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 10 This question analysis was posed in order to find relevance between views on DB in terms of bid rigging and amount of DB projects awarded ov er the past five years that were public projects. P Value 0.188061396

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84 Analysis The P Value is greater than the alpha value (0.10), so we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 443 and 4 44. Therefore, we cannot pr ove statistically there is a relationship between views on DB in terms of bid rigging and amount of DB projects awarded over the past five years that were public projects. Table 443. Question 17 vs. Question 10 Observed Data Observed Bid rigging Not bi d rigging Sometimes Totals X<3 2 1 0 3 3<=X<=7 0 X>7 0 0 1 1 Totals 2 1 1 4 Table 444. Question 17 vs. Question 10 Expected Data Expected Bid rigging Not bid rigging Sometimes X<3 1.5 0.75 0.75 3<=X<=7 0 0 0 X>7 0.5 0.25 0.25 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and amount of DB projects awarded over past five years that were public projects. Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and amount of DB projects awarded over past five years that were public projects. P Value 0.40600585

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85 Limitations Of the nine expected values all of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Du e t o the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 11 This question analysis was posed in order to find relevance between preference of DB and how the firms view DB in terms of bid rigging. Analysis Since the P Value is less than the alpha (0.05), we can reject the null hypothesis and accept the alternative hypothesis according to Tables 4 45 a nd 446. The alternative hypothesis is stating that there is meaning based on preference of DB and how the firms view DB in terms of bid rigging. Table 445. Question 17 vs. Question 11 Observed Data Observed Bid rigging Not bid rigging Sometimes Total (A) Yes 8 8 4 20 (B) No 4 0 0 4 (C) Sometimes 2 4 3 9 Total 14 12 7 33 Table 446. Question 17 vs. Question 1 1 Expected Data Expected Bid rigging Not bid rigging Sometimes (A) Yes 8.4848485 7.272727273 4.2424242 (B) No 1.6969697 1.454545455 0.8 484848 (C) Sometimes 3.8181818 1.909090909 1.9090909 P Value 0.0535344

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86 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and the preference of DB. Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and the preference of DB. Limitations Of the nine expected values seven of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 12 This question analysis was posed in order to find relevance between view on DB in terms of bid rigging and if DB should be allowed for public projects. Analysis Since the P Value is greater than the alpha (0.10), we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 447 and 4 4 8 Theref ore, we cannot prove statistically there is a relationship between views on DB in terms of bid rigging and if DB should be allowed for public projects. Table 447. Question 17 vs. Question 12 Observed Data Observed Bid rigging Not bid rigging Sometimes Totals (A) Yes 6 6 3 15 (B) No 4 0 1 5 (C ) Sometimes 3 2 3 8 Totals 13 8 7 28

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87 Table 448. Question 17 vs. Question 1 2 Expected Data Expected Bid rigging Not bid rigging Sometimes (A) Yes 6.964285714 4.28571429 3.75 (B) No 2.321428571 1.4285714 3 1.25 (C ) Sometimes 3.714285714 2.28571429 2 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and if DB should be allowed for public projects. Alternative Hypothesis: There is a st atistical difference between views on DB is bid rigging and if DB should be allowed for public projects. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 13 This question analysis was posed in order to find relevance between views on DB in terms of bid rigging and if DB should be allowed for private projects. Analysis Since the P Value is greater than the alpha (0.10), we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 449 and 4 50. Therefore, we cannot prove statistically there is a relationship between views on DB in terms of bid rigging and if DB should be allowed for private projects. P Value 0.36261059

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88 Table 449. Question 17 vs. Question 13 Observed Data Obser ved Bid rigging Not bid rigging Sometimes Totals (A) Yes 11 5 6 22 (B) No 2 0 0 2 (C ) Sometimes 0 1 0 1 Totals 13 6 6 25 Table 450. Question 17 vs. Question 1 3 Expected Data Expected Bid rigging Not bid rigging Sometimes (A) Yes 11.44 5.28 5. 28 (B) No 1.04 0.48 0.48 (C ) Sometimes 0 0.24 0.24 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and if DB should be allowed for private projects. Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and if DB should be allowed for private projects. Limitations Of the nine expected values six of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 15 This question analysis was posed i n order to find relevance between views on DB in terms of bid rigging and ability to meet criteria required in the DB RFP. P Value 0.272959205

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89 Analysis Since the P Value is greater than the alpha value (0.10), we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 451 and 4 52. Therefore, we cannot prove statistically there is a relationship between views on DB in terms of bid rigging and ability to meet criteria required in the DB RFP. Table 451. Question 17 vs. Question 1 5 O bserved Data Observed Meet Criteria Yes No Sometimes Totals Yes 9 3 3 15 No 0 0 2 2 Sometimes 5 0 2 7 Totals 14 3 7 24 Table 452. Question 17 vs. Question 1 5 Expected Data and P Value Expected Yes No Sometimes Yes 8.75 1.875 4.375 No 1.1666666 67 0.25 0.583333333 Sometimes 4.083333333 0.875 2.041666667 P Value 0.133111 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and ability to meet criteria required in the DB RFP. Alternative Hypothesis : There is a statistical difference between views on DB is bid rigging and ability to meet criteria required in the DB RFP. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the minimum requirements for Chi Sq uared Test. Due to the limitations of the

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90 sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 17 vs. Question 22 This question analys is was posed in order to find relevance between firms view on DB in terms of bid rigging and views on whether the structure of DB is unequal to all bidders. Analysis Since the P Value is less than the alpha value (0.05), we reject the null hypothesis and accept the alternative hypothesis according to Tables 4 53 and 454 Therefore, the people who believe DB is bid rigging also believe that the structure of DB is unequal to bidders. Table 453. Question 17 vs. Question 22 Observed Data Observed Bid rig ging Not bid rigging Sometimes Totals (A) Yes 4 2 0 6 (B) No 8 2 3 13 (C) Sometimes 0 3 4 7 Totals 12 7 7 26 Table 454. Question 17 vs. Question 22 Expected Data Expected Bid rigging Not bid rigging Sometimes (A) Yes 2.769230769 1.615384615 1.61 5384615 (B) No 6 3.5 3.5 (C) Sometimes 3.230769231 1.884615385 1.884615385 Hypotheses Null Hypothesis: There is no statistical difference between views on DB is bid rigging and whether DB is equal for all bidders. P Value 0.042142308

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91 Alternative Hypothesis: There is a statistical difference between views on DB is bid rigging and whether DB is equal for all bidders. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 11 vs. Question 9 This question analysis was posed in order to find relevance between preference of DB and amount of DB projects awarded over the past five years. Analysis The P Value is less than the alpha value (0.01), so we reject the null hypothesis and accept the alternative hypothesis according to Tables 455 and 456. Therefore, we can prove that there is a statistical relationship between preference of DB and amount of DB projects awarded over the past five years. Table 455. Question 1 1 vs. Question 9 Observed Data Observed Yes No Sometime s Totals X<3 4 6 2 12 3<=X<=10 4 1 6 11 X>10 11 0 0 11 Totals 19 7 8 34 Table 456. Question 1 1 vs. Question 9 Expected Data Expected Yes No Sometimes X<3 6.705882353 2.470588235 2.823529412 3<=X<=10 6.147058824 2.264705882 2.588235294 X>10 6 .147058824 2.264705882 2.588235294

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92 Hypotheses Null Hypothesis: There is no statistical difference between whether DB is preferred and amount of DB projects awarded over the past five years. Alternative Hypothesis: There is a statist ical difference between whether DB is preferred and amount of DB projects awarded over the past five years. Limitations Of the nine expected values six of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 11 vs. Question 12 This question analysis was posed in order to find relevance between preferences of DB and if DB should be allowed for public projects. Analysis The P Value is greater than the alpha value (0.10), so we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to T ables 457 and 4 58. Therefore, we cannot prove statistically there is a relationship between preferences of DB and if DB should be allowed for public projects. Table 457. Question 1 1 vs. Question 12 Observed Data Observed Allow Public Projects Yes No S ometimes Totals Yes 12 1 2 15 No 3 2 1 6 Sometimes 4 1 4 9 Totals 19 4 7 30 P Value 0.000314969

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93 Table 458. Question 1 1 vs. Question 12 Expected Data Expected Yes No Sometimes Yes 9.5000 2.0000 3.5000 No 3.8000 0.8000 1.4000 Sometimes 5.7000 1.2000 2.1000 Hypotheses Null Hypothesis: There is no statistical difference between whether DB is preferred and if DB should be allowed for public projects. Alternative Hypothesis: There is a statistical difference between whether DB is preferred and if DB should be allowed for public projects. Limitations Of the nine expected values seven of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data as sumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 11 vs. Question 13 This question analysis was posed in order to find relevance between preference of DB and whether D B projects should be allowed for private projects. Analysis The P Value is less than the alpha value (0.10), so we reject the null hypothesis and accept the alternative hypothesis according to Tables 459 and 460. Table 459. Question 1 1 vs. Question 1 3 Observed Data Observed Allow Private Projects Yes No Sometimes Totals P Val ue 0.188730608

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94 Yes 18 3 1 22 No 0 1 0 1 Sometimes 1 1 1 3 Totals 19 5 2 26 Table 460. Question 1 1 vs. Question 13 Expected Da ta Expected Yes No Sometimes Yes 16.07692308 4.230769231 1.692 307692 No 0.730769231 0.192307692 0.076923077 Sometimes 2.192307692 0.576923077 0.230769231 Hypotheses Null Hypothesis: There is no statistical difference between whether DB is preferred and if DB should be allowed for private projec ts. Alternative Hypothesis: There is a statistical difference between whether DB is preferred and if DB should be allowed for private projects. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the minimum req uirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations. Question 11 vs. Question 15 An alysis The P Value is greater than the alpha value (0.10), so we fail to reject the null hypothesis and cannot accept the alternative hypothesis according to Tables 461 and 4 62. Therefore, we cannot prove statistically there is a relationship between preferenc e of DB and ability to meet criteria required in the DB RFP. P Value 0.072086

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95 Table 461. Question 1 1 vs. Question 15 Observed Data Observed Meet Criteria Yes No Sometimes Totals Yes 9 3 3 15 No 0 0 2 2 Sometimes 5 0 2 7 Totals 14 3 7 24 Table 462. Question 1 1 vs Question 15 Expected Data Expected Yes No Sometimes Yes 8.75 1.875 4.375 No 1.16666667 0.25 0.58333333 Sometimes 4.08333333 0.875 2.04166667 P Value 0.133111 Hypotheses Null Hypothesis: There is no statistical difference between whether DB is preferred and ability to meet criteria required in the DB RFP. Alternative Hypothesis: There is a statistical difference between whether DB preferred and ability to meet criteria required in the DB RFP. Limitations Of the nine expected values eight of them were less than five, therefore not meeting the minimum requirements for Chi Squared Test. Due to the limitations of the sample size our analysis of data assumes the test is valid. However, the lack of responses for several categories makes it difficult to make any firm declarations.

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96 Figure 4 1. Potential Sources of Error [Adapted from Liu, R. F. a. A. (2008). Research Methods for Construction, Wiley Blackwell. West Sussex, United Kingdom.]

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97 0 2 4 6 8 10 12 14 16 18 A Yes B No C Sometimes FREQUENCY ANSWER CHOICES Could DB be used as a Form of Bid Rigging? Figure 42. Could DB be used as a form of bid rigging? 0 5 10 15 20 A Yes B No C Sometimes FREQUNECY ANSWER CHOICES Should the DB project delivery method be allowed for public projects? Fi gure 43. Should the DB project delivery method be allowed for public projects?

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98 0 5 10 15 20 25 30 35 Yes No Sometimes FREQUENCY ANSWER CHOICES Should the DB delivery method be allowed for private projects? Figure 44. Should the DB project delivery method be allowed for private projects? 0 2 4 6 8 10 A Yes B No C Sometimes FREQUENCY ANSWER CHOICES Are DB bids structured to provide equal opportunity for all bidders? Figure 45. Are DB bids structured to provide equal opportunity for all bidders?

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99 0 10 20 30 0 40 80 120 160 200 More FREQUENCY BIN Number of Employees Frequency Figu re 4 6. Number of Employees 0 5 10 15 20 25 30 35 FREQUENCY BIN Annual Volume of Business ($) Frequency Figure 47 Annual Volume of Business

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100 0 10 20 30 40 4000 8000 12000 16000 20000 24000 28000 More FREQUENCY BIN Quantity of Projects bid on over past 5 years Frequency Figure 48. Quantity of projects bid on over past five year 0 10 20 30 40 300 600 900 1200 1500 1800 More FREQUENCY BIN Quantity of DB projects bid on over past 5 years Frequency Figure 49. Quantity of DB projects bid on over past five years

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101 0 10 20 30 40 200 400 600 800 1000 1200 1400 More FREQUENCY BIN Quantity of DB projects awarded over past 5 years Frequency Figure 410. Quantity of DB projects awarded over past five years 0 10 20 30 40 25 50 75 100 125 150 175 More FREQUENCY BIN Quantity of DB projects that have been awarded, over the past 5 years, that were public projects Frequency Figure 411. Quantity of DB projects that have been awarded, over the past five years that were public projects

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102 Figure 412. What business are you in? 0 5 10 15 20 25 B Corporation C Partnership D S-Corporation E Trust F Non-Profit Organization FREQUENCY ANSWER CHOICES What type of business are you? Figure 413. What type of business are you?

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103 What type of business are you? B Corporation C Partnership D S-Corporation E Trust F Non-Profit Organization Figure 414. What type of business are y ou?

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104 Figure 415. Map of city and state respondents are located in

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105 0 5 10 15 20 25 30 A Design-Build B Construction Management (CM) C CM @ Risk D Design-Bid-Build FREQUECNY ANSWER CHOICES What Project Delivery Method do you Prefer? Figure 416. What project delivery method do you prefer? 0 5 10 15 20 25 A Yes B No C Sometimes FREQUENCY ANSWER CHOICES Do you prefer working on DB projects? Figure 417. Do you prefer working on DB projects?

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106 0 2 4 6 8 10 12 14 A Yes B No C Sometimes FREQUENCY ANSWER CHOICES Have you always been able to meet the criteria required in the DB RFP? Figure 4 18. Have you always been able to meet the criteria required in the DB RFP?

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107 CHAPTER 5 DISCUSSION The results of this study show that Design Build is a form of bid rigging and respondents which are a sample of the population agree with this statement The research findings support the researchers initial hypothesis al most completely. The researcher believed there would be a larger opposition to DB in public projects since they are funded by the government, which is funded by tax dollars. Furthermore, tax dollars are being utilized for this more expensive delivery metho d, rather than using lowest cost to save taxpayers money. However, this was not the case as shown in question # in the results. The author was proven correct in regards to the crux of the hypothesis, design buil d being considered big rigging. These findings also show what people to perceive as illegal (Design Build because its bid rigged) are what they prefer in the work place as a construction delivery method. Therefore, respondents preference is unethical and illegal, yet we continue to allow this process to exist. Do we disregard other laws because we enjoy what they are banning or stating? No, we dont, we enforce them to the fullest ability of law enforcement. For example, Cuban cigars are illegal in the United States but plenty of people in the U.S. prefer them. The U.S. continues to follow its laws and keep these cigars banned. So why are we not banning DesignBuild if its illegal under the Sherman Act? The author believes it could be due to, an idiom, known as the snowball effect. Design Build was initially of small significance and built upon itself, becoming larger (more serious, more important), and faster at an increased rate. Since this happened it was very hard to step back and evaluate the delivery process properly because of the rapid rate o f popularity. Therefore, no authority questioned it, and it became the front

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108 runner for construction delivery methods. Correspondingly, no big firms with verbal and financial power questioned it since it was working in their favor. So they arent currently concerned as to whether its bid rigging, which is illegal. On the other hand, small firms who it mostly affects poorly, cant fight back because they are not big enough since they generally have less mone tary resources, have less manpower, and less lawy ers on their team. Consequently, bi g Design Build firms triumph and DesignBuild remains legal. Major Patterns One major pattern is that big firms prefer DesignBuild unlike smaller firms which dont prefer DesignBuild. However, most of both size firms believe that DesignBuild is bid rigging. The other primary pattern is that DesignBuild is based on subjective criteria. This criteria can be defined in such a way that basically the winner is handpicked, because they were the only contractor/bidder to fit the criteria. How is this not the definition of bid rigging and illegal under the Sherman Act already? The exception to the pattern is that the respondents believe that public and private projects should be allowed to use designbuild even though they agr eed it was bid rigging. Comparison of Results A potential for residential and commercial businesses being oversampled is there are simply more of those types of businesses in Florida and Georgia. Another reason that this may be the case, is that the searc h engine, google.com, which was used to find potential businesses to survey, could be biased or have used previous search history to tailor the results This could have provided skewed results that were more geared toward commercial and residential busines ses

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109 What We Know Now The main thing that the author now knows or understands that she did not know before was that a lot of people in the industry agree with the authors hypothesis, that designbuild can be used as a form of bid rigging. Surprisingly, t his DB bid rigging scheme can be performed with little effort by the client public or private. A hypothetical example of how DB is being utilized illegally is as follows: An owner who creates the RFP, for bidders to make a Statement of Qualifications (SOQ ), can make it so that the criteria, which is subjective in nature, is very narrow with respect to the qualifications desired. This will in turn constrict the bidders from participating because they wont meet this specific criteria thats unimportant to t he project completion or how the project would be scheduled or flow. An example of a tapering criteria is having an architect or engineer inhouse rather than contracting, subcontracting or joint venturing the respective work of these individual professi ons If the bidders are being restricted based on these subjective criteria that are not relevant to the performance of the bidder, then these clients/owners are not following fair competitive practices that allow all bidders to apply if they can perform t he job correctly within the clients desired budget The clients can basically handpick the bidder they wish to award the project to, without even considering other bidders. This may be legal in private situations without an official bidding process, but i t is definitely illegal for the government or public projects where it is their responsibility to remain unbiased by hiring the bidder objectively Besides, how can you hire objectively, if you are using subjective criteria as a basis?

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110 Implications The implications of this research could be forwarded to the U.S. Supreme Court in order to make this delivery process illegal. This is important to consider because as stated in the Sherman Act, this anti trust law increases competition fairness and interstate commerce practices that keep society moving effectively. Society needs to move positively and fairly in order for effective competition to exist. The only way to do this is by using low est cost, an objective criteria, used in the designbid build method o r other objective criteria based methods

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111 CHAPTER 6 CONCLUSION With all this is mind, there is no way to deny the seriousness of the subjective criteria in DB delivery method and how this is potentially a bid rigging process. The Federal Trade C ommissio n (FTC) prides itself on protecting competitive practices that go against this type of bid rigged process. The federal trade commissions bureau of competition champions the rights of American consumers by promoting and protecting free and vigorous compet ition ( Commission 2008) In the research that was done, there was not a lot of discussion on DB as a bid rigging process. The FTC hasnt looked into this bid rigg ing scheme by any means. Hence, the need to present, further investigate and submit these findings to the appropriate government entity The researcher has an accepted hypothesis stating that DB could be used as a form of bid rigging since it is based on subjective criteria. The results of the survey clearly show DB is considered bid rigging by members on the construction industry. To extend this thought, if it is bid rigging, then by definition in law, it is illegal. Contribution All infor mation gather ed from the survey, th ese corresponding findings and interpretations derived from them are all contributions of this research. These findings could be further investigated and prove to the U.S. Supreme Court that DB is in violation of the Sherman Act and that other possible methods need to be utilized that are legal. Based on the survey results, delivery methods abiding by objective criteria such as DBB, CM, or CMAR can be used as sufficient replacements. This research signifies the importance of fair competition and reaffirms the foundation for the Sherman Act.

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112 Research Results Compared to the Literature Review Since there is only one other experiment that looks at this topic, the researcher can only compare to that research as described in the literatur e review. Since this previous research was based solely on case studies, there is lack of analysis on public opinion of the topic. The new understanding of DBs ethical dilemma is that it s subjective and something needs to be done to abolish or modify the DB delivery method. Limitations of the Research While the researcher is confident regarding the scholarly aspect of the research conducted, her findings and the significance of the work, she recognizes that it is still only an in depth study into a very t iny aspect of the field. The researcher will explain limitations of this research which are sample size, possible survey wording, location, and practical realities The sample size which represents the population, is too small for this research. Unfortunat ely, due to a multitude of reasons discussed previously, many recipients did not respond or responded partly Most of the results couldnt function at 100% confidence level do to the shortage of responses. Therefore, the results are still valid but are not sufficient to be the sole basis of any conclusions As such, current literature and case studies were used in conjunction to arrive at a more reliable conclusion. The survey wording may perhaps have be en another limitation because it was fashioned by a construction student, not someone employed in the construction field. This may have led to abysses in communication barriers that the researcher could not av oid because she was not employed during schooling. If this is not the cause perhaps its due to lac k of participant knowledge of the topic. For instance, if the recipient or

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113 participant did not always or ever engage in DB, they may not partake or may mark Not A pplicable in an effort to avoid coming across as biased. The location may have influence d t he results, since Florida and Georgia are just two states of the whole U.S. Just as in political races, states even cities vary in degrees of preferences. A c onstruction firm in Boise, Idaho might not have the same priorities or views as a similar firm in Tampa, Florida. The researcher would have to expand her sample size to include more than just two states. The reality of DB is that it is currently ethical, legal and quite increasingly preferred as shown in the results. This may never change, even if it does fall under a violation of the Sherman Act T his popularity and the fact that big firms benefit from it would result in a fierce defense during any potential judiciary proceedings Besides even within the most comprehensive and large scale study, t here are still limitations by virtue of the possible scope, methodological restrictions, and practical realities. All claims and generalizations therefore, have to be tempered by this knowledge, and should be made using precautionary measures in survey res earch. The researcher appreciates the limitations of this study and in the future would like to improve upon these shortcomings.

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114 CHAPTER 7 RECOMMENDATIONS First Step The first step a follow up study would be to acquire more samples of the population in or der to draw a more reliable conclusion. In order to accomplish this, the researcher would need to collect more contact information from the population, including email and mailing addresses. This search for recipients should go more in depth by getting a m ore diverse group of business types. The researcher would have to compile a more thorough list that would allow the demographics to be equally distributed. Second Step The instructions in the survey would be more forceful with the goal of increasing compl etion of the entire survey instead of bits and pieces The researcher would also eliminate the answer choice sometimes as discussed before in the Results Section: Potential Sources of Error. Fewer options to write in answers or give alternate responses will allow for a more concentrated answer pool, and simpler analysis. The researcher would like to add another question to the survey that asks whether the business has ever been a victim to bid rigging from another party from DB. Third Step The researcher would try to come up with an incentive program in order to motivate more recipients to participate. This could ameliorate the small sample size and expected values in turn, allowing the researcher to use the Chi Squared Test with 100% confidence level. Th e researcher may decide to go door to door to companies to have

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115 an interview about the survey in order to get more qualitative results as well as more accurate results. Final Step The survey would be fine tuned to include stronger, more concise questions that would allow the participant to make fewer mistakes. The survey letter that explains the instructions would also have a section that explains who is applicable to fill out this survey so there will be no confusion.

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116 APPENDIX A LETTER TO RECIPIENTS ( EMAIL) March 14, 2013 To whom it may concern, Hello, my name is Adrienne Harrow. I am currently a student at the University of Floridas M.E. Rinker Sr. School of Building Construction and I am conducting a study on Design Build delivery methods. I have attached a questionnaire inquiring about your companys construction operations. While your participation is voluntary, I would appreciate you taking 10 minutes of your valuable time to help me with this research. All of your answers will be confidential, and you do not have to answer any question you do not want to. To take the survey online, please follow the link below: https://www.surveymonkey.com/s/3KFFNCP Some questions are openended and may require a longer response. There are lin es given for written responses. If you have any questions, comments or concerns please feel free to contact me. My contact information is provided at the bottom of this letter. Any contact method is acceptable. Thank you for your time. I look forward to r eceiving your questionnaire responses. Sincerely, Adrienne Harrow

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117 APPENDIX B LETTER TO RECIPIENTS (MAIL) March 14, 2013 To whom it may concern, Hello, my name is Adrienne Harrow. I am currently a student at the University of Floridas M.E. Rinker Sr. School of Building Construction and I am conducting a study on Design Build delivery methods. I have attached a questionnaire inquiring about your companys construction operations. While your participation is voluntary, I would appreciat e you taking 10 minutes of your valuable time to help me with this research. All of your answers will be confidential, and you do not have to answer any question you do not want to. There is a postage paid addressed envelope enclosed for your return of th e questionnaire. If you would prefer to take the survey online, please follow the link below: https://www.surveymonkey.com/s/3KFFNCP Some questions are openended and may require a longer response. There are lines given for written responses. If you feel you need more room to write, please feel free to add more paper with your answers. If you have any questions, comments or concerns please feel free to contact me. My contact information is provided at the bottom of this letter. Any contact method is accep table. Thank you for your time. I look forward to receiving your questionnaire responses. Sincerely, Adrienne Harrow

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118 APPENDIX C SURVEY/ QUESTIONNAIRE 1. What business are you in? (Please circle all that apply) (d) We build residential. (e) We build commercial. (f) We build industrial. (f) We build heavy civil. (g) We build environmental. (h) Other : _______________ 2. What type of business are you? Please see footnote for explanations. (a) Sole Proprietorship (b) Corporation (c) Partnership (d) S Co rporation (e) Trust (f) Non Profit Organization (g) Other : ________________________ 3. How many employees do you currently have? 4. What is your annual volume of business? $ 5. What city and state are you located in?

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119 _____________________________ _______ 6. What type of project delivery method do you prefer? Please see footnotes for explanations. (a) Design Build (b) Construction management (CM ) (c) CM @ Risk (d) Design Bid Build (Traditional ) (e) Not applicable 7. How many projects have you bid on over the past 5 years? 8. How many DesignBuild projects have you bid on over the past 5 years? 9. How many DesignBuild projects have you been awarded over the past 5 years? 10. How many of the DesignBuild projects that you have been awarded, over the past 5 years, were public projects? 11. Do you prefer working on DesignBuild projects?

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120 (a) Yes (b) No (c) Sometimes (d) Not applicable Why or Why not? ______________________________________________________________________ __________________ ____________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ____________________________________________ 12. Should the Desi gn Build project delivery method be allowed for public projects? (a) Yes (b) No (c) Sometimes (d) Not applicable Please explain answer. ______________________________________________________________________ _______________________________________________ _______________________ ______________________________________________________________________ ______ 13. Should the DesignBuild project delivery method be allowed for private projects?

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121 (a) Yes (b) No (c) Sometimes (d) Not applicable Please explain answer. ______________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ _____________________________________________ _________________________ ________ 14. In your DesignBuild projects, how many criteria are present in the RFP (Request for Proposal) on average? If not applicable, write N/A. ________________________________________________________________ ________What wer e the criteria listed? ______________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ______ 15. Have you alw ays been able to meet the criteria required in the DesignBuild RFP? (a) Yes (b) No

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122 (c) Sometimes (d) Not applicable Please explain answer. ________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ______________ 16. If you have NOT been able to meet all the criteria required in the DesignBuild RFP, what have you done? If not applicable, write N/A. ________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ______________________________________ 17. Could Design Build be used as a form of bid rigging? (a) Yes (b) No (c) Sometimes (d) Not applicable Please explain answer. ________________________________________________________________ ______________________________________________________________________

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123 ______________________________________________________________________ ______________________________________________________________________ ______________ 18. Have you ever protested a bid because you were not awarded the bid? (a) Yes (b) No (c) Other : _________ (d) Not applicable Please explain answer. ________________________________________________________________ ________ Did you w in the bid after protesting? ______________________________________________________________________ ______________________________________________________________________ ____ 19. Did you ever have to provide a bond in order to protest a bid? (a) Yes (b) No (c) Other : __________ (d) Not applicable

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124 20. Over the past 5 years, how many of your bids required a bond in order to protest? 21. If you did NOT win the protest addressed in Question #18, did you lose the bond if it was required? (a) Yes (b) No (c) S ometimes (d) Monetary bond was not required. (e) Not applicable Please explain answer. ______________________________________________________________________ ______________________________________________________________________ _____________________________ _________________________________________ ______________________________________________________________________ ________ 22. Are Design Build bids structured to provide equal opportunity for all bidders? (a) Yes (b) No (c) Sometimes (d) Not applicable

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125 Ple ase explain answer. ______________________________________________________________________ ______________________________________________________________________ ______________________________________________________________________ ______ Footnotes: Sole proprietors are unincorporated businesses. They are also called independent contractors, consultants, or freelancers. There are no forms you need to fill out to start this type of business. The only thing you need to do is report your business income and ex penses on your Form 1040 Schedule C. This is the easiest form of business to set up, and the easiest to dissolve. (An LLC with only a single shareholder, a so called single member LLC, is taxed as a sole proprietor on a Schedule C.) Corporations are incorporated businesses. Every form of business besides the sole proprietor is considered a separate entity, and this often provides a measure of legal and financial protection for the shareholders. The shareholders of corporations have limited liability prote ction, and corporations have full discretion over the amount of profits they can distribute or retain. Corporations are presumed to be for profit entities, and as such they can have an unlimited number of years with losses. Corporations must have at least one shareholder. Partnerships are unincorporated businesses. Like corporations, partnerships are separate entities from the shareholders. Unlike corporations, partnerships must have at least one General Partner who assumes unlimited liability for the busi ness. Partnerships must have at least two shareholders. Partnerships distribute all profits and losses to

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126 their shareholders without regard for any profits retained by the business for cash flow purposes. (LLCs are taxed as partnerships, unless they choose to be taxed as corporations.) S Corporations have features similar to a partnership. An S corporation must have at least one shareholder, and cannot have more than 100 shareholders. If any shareholder provides services to the business, the S Corp must pay that shareholder a reasonable salary. This salary is a separate payment from distributions of profits or losses. Trusts are usually formed upon the death of an individual and are designed to provide continuity of the investments and business activities of the deceased individual. N onprofits are corporations formed for a charitable, civic, or artistic purpose. Nonprofits are generally exempt from federal and state taxation on their income, and so they are often called "exempt organizations." Nonprofits have substantial responsibiliti es for reporting their activities, income, and assets to ensure that they are in compliance with federal and state laws governing charities. Explanations are provided by: http://taxes.about.com/od/taxplanning/a/incorporating_2.htm Design/Build Owner has one contract with design/build (D/B) firm. D/B firm handles design and construction. All subcontractors work for D/B firm Construction Management (CM)

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127 Owner has multiple contracts with Architect, Construction Manager (CM), and contractors Architect designs building Architect prepares construction documents with the involvement of the CM. CM seeks bids from contractors of various trades. Owner contracts directly with each tradesman. CM schedules and manages th e construction. CM is responsible exclusively to the owner and acts in the owner's interests at every stage of the project. Construction Management at Risk (CMAR) Allows the owner to interview and select a fee based firm, based upon qualifications and experience, before the design and bidding documents are fully completed. The construction manager and design team work together to develop and estimate the design. A guaranteed maximum price (GMP) is provided by the CM, who then receives proposals from and awards subcontracts to subcontractors The design team is selected separately and reports directly to owner. The CM at Risk contracts directly with multiple subcontractors and has single point of responsibility for the delivery of the project.

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128 The CM also provides advisory professional management assistance to the owner prior to construction, offering schedule, and budget and constructability advice during the project planning phase. Traditional Design Bid Build Owner has two Contracts one with the Architect and one with the General Contractor Architect designs building and prepares construction documents Ow ner selects GC(s) for negotiating construction contracts or soliciting bids. General Contractors (GC) submit bids to owner. GC contracts with subcontractors (plumbing, electrical, carpentry, etc.) Upon Architect's certification, Owner makes payments to GC, who pays subcontractors. Design team is selected separately and reports to the owner.

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129 LIST OF REFERENCES (2011). Pearson Construction Technology: BCN5705UFL Construction Project Management Course Notes Pearson Learning Solutions, USA. Charles N. Juliana, E. a. G. R., LLP (2005). "Construction Management/ DesignBuild." 207. Commission, F. T. (2008). "FTC Guide to the Anti Trust Laws." Connor, M. C. (2003). "Legal Exposure in Design/Build Contracts." ASHRAE Journal 45(8), 49. Guyer, P. E., R.A. (2012). "Ethical Issues in DesignBuild." Jackson, B. J. (2011). Design Build: DesignBuild Essentials Delmar, Cengage Learning. U. S. D. o. Justice (April 2005). "An Anti Trust Primer for Federal Law Enforcement Personnel." A. T. Division, ed. L iu, R. F. a. A. (2008). Research Methods for Construction, Wiley Blackwell. West Sussex, United Kingdom. Lucas, D. D. (2013). "Design Build Lecture." University of Florida. Mosey, D. (1998). Design and Build in Action, Chandos Publishing Limited, Oxford En gland. Parkman and White, L. (2011). "Bid Rigging." < http://www.antitrustcriminalattorney.com/antitrustschemes/bid rigging/> Rebecca Ellis, P. E. (May 2008). "Desig n Build Vs. Design Bid Build." Commissioining, BNP Media Engineered Systems. Robert F. Cushman, M. C. L. (2001). Design Build Contracting Handbook, Aspen Law and Business, Gaithersburg, New York. Solomon, N. B. (2005). "The Hopes and Fears of DesignBui ld." Architectural Record, 193(11), 167174. Sosulski, P. C. W. a. K. (2002). "Quantitative Methods in Social Sciences." QMSS eLessons, . (June 9, 2013). Touran, A., Gra nsberg, D. D., Molenaar, K. R., and Ghavamifar, K. (2011). "Selection of Project Delivery Method in Transit: Drivers and Objectives." Journal of Management in Engineering, 27(1), 2127.

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130 Yu, W. d., and Wang, K. W. (2012). "Best Value or Lowest Bid? A Quanti tative Perspective." ASCE Journal of Construction Engineering & Management, 138(1), 128134.

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131 BIOGRAPHICAL SKETCH The author graduated from the Warrington College of Business at the University of Florida in May 2011. Her concentration was Urban and Regional Planning which focused on the planning aspect of construction and zoning. She is currently enrolled in the M.E. Rinker, Sr. School of Building Construction at the University of Florida. She plans to graduate in August 2013.