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Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2008-02-29.

Permanent Link: http://ufdc.ufl.edu/UFE0021040/00001

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Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2008-02-29.
Physical Description: Book
Language: english
Creator: Basham, Matthew J
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Matthew J Basham.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Campbell, Dale F.
Electronic Access: INACCESSIBLE UNTIL 2008-02-29

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Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021040:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021040/00001

Material Information

Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2008-02-29.
Physical Description: Book
Language: english
Creator: Basham, Matthew J
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Matthew J Basham.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Campbell, Dale F.
Electronic Access: INACCESSIBLE UNTIL 2008-02-29

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021040:00001


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COGNITIVE APPLICATIONS OF PE RSONALITY TESTING: MEASURING ENTREPRENEURIALISM IN AMER ICAS COMMUNITY COLLEGES By MATTHEW JOHN GEORGE BASHAM A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007 1

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2007 Matthew John George Basham 2

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To my children, Matthew and Madison 3

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ACKNOWLEDGMENTS I wish to acknowledge my dissertation chair, Dr. Dale F. Campbe ll for his inspiration, guidance, and leadership throughout the doctoral program. I also wish to acknowledge and thank Dr. Linda Behar-Hornstein for her input a nd guidance during the de velopment of this dissertation. I thank Drs. Lawren ce W. Tyree, David Honeyman, a nd Lynn Leverty for serving on the committee. Finally, I would like to acknowle dge Dr. Mary Ann Ferguson for the years of tutelage during my masters de gree program. She instilled the wisdom and knowledge necessary for conducting quantitative research. 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................7 LIST OF FIGURES .........................................................................................................................9 ABSTRACT ...................................................................................................................................10 CHAPTER 1 INTRODUCTION................................................................................................................. .12 Innovation and Entrepreneurialism Is a Must ........................................................................14 Hire the Right People, Keep Them and Keep Them Happy ..................................................14 Growing Your Own Leaders...........................................................................................15 Hiring Administrators ......................................................................................................16 Focus On Your Mission ..........................................................................................................17 Establish Partnerships .............................................................................................................17 Purpose of the Study ...............................................................................................................18 Research Questions .................................................................................................................19 Research Hypotheses ..............................................................................................................20 Significance of the Study ........................................................................................................20 Definition o f Terms ................................................................................................................21 Limitations ..............................................................................................................................21 2 LITERATURE REVIEW.......................................................................................................23 Entrepreneurialism ..................................................................................................................23 Defining Entrepreneurialism ...........................................................................................24 History Of Entrepreneurialism ........................................................................................24 Reasons For The Rise Of Entrepreneurialism .................................................................25 Faculty And University Entrepreneurialism: The Curriculum ........................................26 Forces Shaping Entrepreneurialism In Higher Education: College operations ...............27 Culture Of Entrepreneurialism: Community Outreach ...................................................28 Personality Testing .................................................................................................................29 The Psychological Foundations Of Personality Testing: Two Models ...........................29 The Jungian Model ..........................................................................................................30 The Five Factors Model ...................................................................................................31 Contemporary Personality Test Constructs: Some Debates ............................................34 Personality Testing For Job Selection ....................................................................................39 Personality Testing In The Workplace ............................................................................42 A Caveat: Personality Testing In The Workplace ...........................................................43 Legalities Of Personality Testing ....................................................................................43 5

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Personality Traits Of Entrepreneurs .......................................................................................46 Summary .................................................................................................................................50 3 RESEARCH METHODOLOGY...........................................................................................58 Purpose Of The Study .............................................................................................................58 Research Problem ...................................................................................................................58 Research Questions .................................................................................................................59 Research Hypotheses ..............................................................................................................59 Research Design .....................................................................................................................60 Research Instrument ...............................................................................................................60 The Expert Report ...........................................................................................................62 The Entrepreneurial Potential Summary Report .............................................................64 Instrument Validity And Reliability ................................................................................65 Data Collection .......................................................................................................................66 Population ...............................................................................................................................66 Data Analysis ..........................................................................................................................67 4 RESULTS...................................................................................................................... .........72 Aggregate Data-Descriptive Statistics ....................................................................................72 Research Hypothesis One .......................................................................................................72 Research Hypothesis Two ......................................................................................................73 Research Hypothesis Three ....................................................................................................75 5 DISCUSSION................................................................................................................... ......84 Discussion Of The Results ......................................................................................................84 Research Hypothesis One ................................................................................................84 Research Hypothesis Two ...............................................................................................86 Research Hypothesis Three .............................................................................................87 The WAVE And Entrepreneurial Characteristics ...........................................................87 Suggestions For Future Research ...........................................................................................88 Implications For Community College Administrators ...........................................................91 Conclusion ..............................................................................................................................94 APPENDIX A THE SCALE DESCRIPTIONS..............................................................................................97 B DESCRIPTIVE STATISTICS..............................................................................................113 C FISHERS LSD CONTRASTS............................................................................................131 LIST OF REFERENCES .............................................................................................................137 BIOGRAPHICAL SKETCH .......................................................................................................153 6

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LIST OF TABLES Table page 2-1 Ph.D.-Level Courses that ma y deal with entrepreneurialism. ................................................51 2-2 Top 26 geographic entrepre neurial zones based on number s of patents issued in 1999. ...51 2-3 Personality tests and the Five Factors Model .........................................................................52 3-1 Reliability summary for Saville Consulti ng WAVE. Alternate form normative, ipsative, and combined .....................................................................................................................69 3-2 Single dimension and composite validities ............................................................................70 4-1 Unpaired Students t-Te st results for research hypothe sis one for the descriptive statistics. .............................................................................................................................76 4-2 Unpaired Students t-Test results for research hypothesi s one for the Entrepreneurial Potential Summary Report. ................................................................................................76 4-3 Unpaired Students t-Test results for research hypothesi s one for the Entrepreneurial Potential Profile Report. .....................................................................................................77 4-4 Unpaired Students t-Te st Results for research hypothe sis one for the descriptive statistics. .............................................................................................................................77 4-5 Unpaired Students t-Test results for research hypothesi s two for the Entrepreneurial Potential Summary Report .................................................................................................78 4-6 Unpaired Students t-Test results for research hypothesi s two for the Entrepreneurial Potential Profile Report. .....................................................................................................78 4-7 Pearson Correlation matrix for the Entrepreneurial Potential Summary variables. ...............79 4-8 Eigenvalues for the Entreprene urial Potential Summary variables. .......................................79 4-9 Pearson Correlation Matrix for the Entrepreneurial Potential Profile variables. ...................80 4-10 Eigenvalues for the Entreprene urial Potential Profile variables. ..........................................81 4-11 Factor pattern coefficients for the Entrepreneurial Potential Profile. ...................................81 B-1 Executive Summary-aggregate ............................................................................................113 B-2 Psychometric Profile-aggregate ...........................................................................................114 B-3 Competency Potential Profile-aggregate .............................................................................115 7

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B-4 Entrepreneurial Potential Summary-aggregate ....................................................................115 B-5 Entrepreneurial Potential Profile-aggregate .........................................................................116 B-6 Executive Summary-doctorates ...........................................................................................117 B-7 Executive Summary-non-doctorates ....................................................................................118 B-8 Psychometric Profile-doctorates ..........................................................................................119 B-9 Psychometric Profile-non-doctorates ...................................................................................120 B-10 Competency Profile-doctorates .........................................................................................121 B-11 Competency Potential Profile-non-doctorates ...................................................................121 B-12 Entrepreneurial Potential Summary-doctorates .................................................................121 B-13 Entrepreneurial Potential Summary-non-doctorates ..........................................................122 B-14 Entrepreneurial Potential Profile-doctorates ......................................................................122 B-15 Entrepreneurial Potential Summary-non-doctorates ..........................................................123 B-16 Executive Summary-entrepreneurial school leaders ..........................................................124 B-17 Executive Summary-non-entr epreneurial school leaders ..................................................125 B-18 Psychometric Profile-ent repreneurial school leaders .........................................................126 B-19 Psychometric Profile-nonentrepreneurial school leaders .................................................127 B-20 Competency Potential Profile -entrepreneurial school leaders ...........................................128 B-21 Competency Potential Profilenon-entrepreneurial school leaders ....................................128 B-22 Entrepreneurial Potential Summ ary-entrepreneuria l school leaders ..................................128 B-23 Entrepreneurial Potential Summ ary-entrepreneuria l school leaders ..................................129 B-24 Entrepreneurial Potential Profile-entrepreneurial school leaders ......................................129 B-25 Entrepreneurial Potential Prof ile-non-entrepreneur ial school leaders ...............................130 C-1 Entrepreneurial Potential Summary contrasts ......................................................................131 C-2 Entrepreneurial Potential Profile contrasts ..........................................................................131 8

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LIST OF FIGURES Figure page 2-1 The linear model of forms of en trepreneurialism in higher education. ..................................54 2-2 Intersection of the academic and economic worlds. ...............................................................54 2-3 The Five Factor Model structure.............................................................................................54 2-4 Predictors of job success by assessment method. ...................................................................55 2-5 Where do entrepreneurs get their ideas? .................................................................................55 2-6 Measures for entrepreneurial networks..................................................................................55 2-7 The relationship between entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on neuroticism. ........................................................................56 2-8 The relationship between entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on extraversion. .......................................................................56 2-9 The relationship between entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on openness. ............................................................................56 2-10 The relationship between entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on agreeableness. .............................................................57 2-11 The relationship between entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on conscientiousness.......................................................57 3-1 Theoretical structure of the WAVE. .......................................................................................71 4-1 Scree plot for the Entrepreneurial Potential Summary...........................................................82 4-2 Scree plot for the Entrepreneurial Potential Profile. ...............................................................82 4-3 Factor pattern coeffi cient plot for the Entrepreneurial Potential Profile. ...............................83 A-1 The thought cluster, sections and dimensions. ....................................................................111 A-2 The influence cluster, sections and dimensions. ..................................................................111 A-3 The adaptability cluste r, sections and dimensions. ..............................................................112 A-4 The delivery cluster, sections and dimensions. ...................................................................112 9

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Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy COGNITIVE APPLICATIONS OF PE RSONALITY TESTING: MEASURING ENTREPRENEURIALISM IN AMER ICAS COMMUNITY COLLEGES By Matthew John George B asham August 2007 Chair: Dale F. Campbell Major: Higher Education Administration Community college administrators have hist orically been hailed as being innovative, entrepreneurial, and responsive to change of local bus iness and community needs. The rise of prominence of community colleges in th e 1960s would cause unforeseen problems for administration in the early 21 st century. The longevity of these ear ly hire administrators preceded a wave of retirements of the baby boomer administrators with turnover rates as high as 75% being predicted by researchers. Administrators began holding focus groups, c onferences, and seminars to determine the best plan of attack for dealing with these predictions. Some be gan to grow their own leaders by financing their better administra tors through doctorate programs wh ile others began to revise their hiring practices by using more comprehens ive screening processes, including personality testing use. With such high turnover and attrition and a relatively inexperienced talent pool administrators will have to proceed with caution when selecting crucial positions in their senior leadership team, especially in those positions requiring entrepreneurial talents. This study found entrepreneurialism, as a cognitive application of personality testing, is learnable, is not 10

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specifically found in any region of community college administrato rs, and the WAVE instrument is valid, reliable, and does measur e what it intends to measure. 11

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CHAPTER 1 INTRODUCTION Throughout the last one hundred years community colleges have been hailed for their mission of serving the community and business n eeds while providing open access to education for all students (Roueche & Jones, 2005; Boggs, 2002; Vaughn, 2000; Boone, 1997). This open door policy led to an explosion of growth in the community colleges. In the 1960s, community colleges opened at a rate of one per week (Vaughn, 2000). Histori cally community colleges have also been commended for their quick response in serving the needs of the community and businesses (see also Blau, McVeigh, and Land, 2000). Business and industry look to community co lleges to provide on-demand skills training for workers in their service area and contract training is a gr owing aspect of the community services functions at community colleges. The colleges have the flexibility to respond quickly to the training needs of business and industry, in pa rt because much of what is taught under the community services umbrella does not requ ire approval by the govern ing board or state coordinating agency (Vaughn, 2000, p. 12). Overall, the community college system has seen unprecedented growth in student enrollment and prosperity while still maintain ing their ability to re spond to community and business needs (Blau et al., 2000). Despite this prosperity, some community college leaders seemingly have been lulled into complacency. In 1993, the Wingspread Group report predicted troubles for community colleges if the trend towards complacency were not reversed. The report warned of the lagging sociopolitical forces, the rapid ri se of technology, and the growing need for entrepreneurialism in higher education. Several other predecessors also echoed this sentiment (e. g., the Nation at Risk, 1983 report from the National Commission on Excel lence in Education; The Condition of 12

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Education: Post Secondary Edu cation, 1988 from the National Center for Educational Statistics; A Time for Results, the Governors 1991 Repor t on Education (as cited in Stone, 1995)). Such an ominous forecast ought to have inspired college personnel to rally and refocus. Sadly, this did not happen. Some merely hit th e snooze button on the national wake up-call and now are less prepared for turbulent times and the subsequent changes that must be made (Roueche & Jones, 2005, p. x). Not all community college leaders ignored th ese signs. Some community college leaders, academicians, and politicians began to explore th e issues further. In 1995 the University of Florida, Department of Education Leadership, Administration and Policy began annually sponsoring the Community College Futures Conference in Orlando, Florida. On average, 60 select chancellors, board of trustee members, pr esidents, and senior vice presidents from around the United States annually participated in discussions to identify the top issues facing community colleges each year (Campbell, ODaniels, Ba sham, & Berry, 2007; Campbell, 2006; Campbell & Tison, 2004; Community College Futures, 2003; Campbell & Evans, 2001, Campbell & Kachik, 2001). The top issues facing community college s from the 2006 Community College Futures Assembly identified were: 1. Innovation and entrepreneurialism is a must for survival. 2. Hire the right people, keep th em, and keep the right people. 3. Focus on your mission and strengths. 4. Establish partnerships (Campbell et al., 2007). The participants said together these four i ssues would establish the blueprints for the future of community college administrators a nd their changing missions (Campbell et al., 2007). 13

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Innovation and Entrepreneurialism is a Must The first critical issue identified comm unity colleges having to become more entrepreneurial or innovative organizations. Rapid innovation, societal change, and an uncertain world are reshaping the environm ent within which institutions have historically functioned (Flannigan, Greene & Jones, 2006, p. 1). Thus, for community colleges to become more entrepreneurial should not be too difficult given th eir historically rapid re sponse to change. In many community colleges a culture of change, both within and without the mission, must first be embraced in order to become more entrepreneurial: Entrepreneurial organizations must choose risk taking, trust, and passion. They must cultivate an insatiable appeti te for change, thrive on creativ e problem solving, and relying on courageous leadership. They will be shaped by people who have unique talents and abilities for identifying inventive responses to environmen tal challenges and who possess a sense of purpose and an unwavering commitment to achieving the colleges mission (Flannigan et al, 2006, p. 2). Flannigan also said in order to become en trepreneurial you must first have the right people in place. Finding entrepreneurs however, can be a problematic issue. Ryan (2004) said that entrepreneurs are more likely to be found in a limited number of entrepreneurial regions that are identified by the numbers of patents developed in those areas, rather than interspersed throughout the nation. Hire the Right People, Keep Them, and Keep Them Happy The second issue is hiring the right people and keeping them. Research has shown the baby boomer administrators who were hired in the 1960s and 1970s durin g the explosion of community college growth are retiring in wave s (Fields, 2004; Romero, 2004; Amey, Van Der Linden, & Brown, 2002; Amey & Van Der Linden, 2002; Campbell & Associates, 2002; Berry, Hammons, & Denny, 2001; Bureau of Labor Statistics, 2001) with some predicting as high as a 14

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75% turnover before 2011 (Roueche & Jones, 2006; Boggs, 2002; Campbe ll & Associates, 2002; Shults, 2001; Vaughan, 2000; Campbell & Leverty, 1997). Some researchers have noted more than 1,500 studies on the problems associated with employee turnover and attrition (Barrick & Zimmerman, 2005). This problem is not unique to community colleges, but is universal among all sectors of industry both here in the United States and internationally (Lavigna & Hays, 2004). Some community college administrators held summits to explore the overarching issues associated with recruiting and hiring community college administrators. They concluded that searches would be expensive, competition would be great, and that the ramifications of a poor choice would be extremely cos tly, especially with respect to productivity, morale, and institutional image (Belcher & Montgomer y, 2002; Campbell & Associates, 2002; Lloyd, 2002). Replacing a poor choice c ould cost schools up to two or thr ee years in lost productivity and countless revenue (see also Sanford, 2005) with some sources claiming up to 150 % of base pay as the potential losses per y ear (OConnor & Fiol, 2004). They concluded the only two options available would be to grow your own leaders or to hire them from other institutions. Growing Your Own Leaders Many schools such as Georgia Perimete r College (Belcher & Montgomery, 2002), Parkland College (Harris, 2002), Daytona Beach Community College (Sharples & Carroll, 2002), developed programs to grow their own l eaders by establishing th eir own conferences, seminars, and training opportunities for middle or lower management. Other schools, such as Macomb Community College (Lorenzo & DeMart e, 2002), developed recruiting processes to attract future leaders near the end of their docto ral training to become leaders-in-training for oneto-three years. While these programs are to be lauded for heeding the warnings and being proactive in grooming future leaders, Kuttler (2006) recently pointed out: We may have done our 15

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job too well and have created a stockpile of leadership candida tes with plenty of graduate degrees, but not enough positions to go around. Beyond the process of developing leaders it is paramount to be able to make the distinction between the people who can help w ith change from those who cannot (Campbell & Associates, 2002). The people must also be able to function in a t eam and within the culture and fit of the institution. Codling (2004) has shown pr omotion from within may not necessarily be the best path in academic leadership. Codling states that promotions in education tend to be more anchored in academic prowness rather than lead ership and management prowness and therefore promotions should be more carefully screened on abilities, rather than promoting for the sake of promoting. Drucker, urged all leaders in enterprise (s) that have sailed in calm waters for a long time (such as the just passing very prosperous 1980s and 1990s)needs to cleanse itself of the products, services, ventures that only absorb resources the products services, ventures that have become yesterday (Drucker, 2002, p.43 (as cited in Roueche & Jones, 2005 )). This includes the staff and administration as well. If someone gi ves you an answer: that is the way we have always done it, then they need to be re placed (Kotter, 1996). During the 2006 Community College Futures Assembly, O. Lester Smith said the movers know when to give up and move onthose that do not move on, are probably the dead wood and are probably the ones who are complaining about change. Those are the peopl e that you may not necessarily want in your organization (Smith, 2006). Hiring Administrators There is a variety of methods that may be used in the hiring process, such as using checking references, interviewing, personality te sting or even assessmen t centers which have been researched. Some methods, such as person ality testing, have been shown to be more accurate in predicting future job success than others (Bain & Mabey, 1999). Companies in the 16

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United States are gaining in their confidence in personality testing (Gettler, 2004; Kluger, Watson, Laidlaw, & Fletcher, 2002) and have been estimated as spending more than $400,000,000 a year on using personality testing in both the hiring process and evaluation processes (Gettler, 2004). Combining two or more methods can dramatically improve the success rate, such as combining personality testing wi th references checking (Greengard, 2002). This data has been corroborated by other researchers as well (e. g., Gettler, 2004; Robertson & Smith, 2001; Schmidt & Hunter, 1998). Focus on Your Mission The third issue is the need to focus on your mission. The mission of the community college is to serve the community while providing education to all who seek it. The mission of most community colleges is shaped by these commitments: Serving all segments of society thro ugh an open-access admissions policy that offers equal and fair treatment to all students Providing a comprehensive educational program Serving the community as a community-based institution of higher education Teaching and learning Fostering life-long learning (Vaughn, 2000, p. 3) According to the 2006 Futures focus group members some community colleges may also have to re-write their mission to better meet th e needs of a changing society (Campbell, et al., 2007). Establish Partnerships The fourth issue is to establish and main tain partnerships th roughout the community. Many colleges formed successful collaborations a nd partnerships to bette r serve their community (e. g., Chambers, Weeks, & Chaloupka, 2003; Sink & Jackson, 2002; Pauley, 2001; Russell, 17

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2001; Seehusen, 2000; Warren, 2000; Smith, O pp, Armstrong, Stewart & Isaacson, 1999). For example, at Blue Ridge Community College in Flat Rock, North Carolin a, the administration formed partnerships with 12 non-profit organi zations and government agencies physically located on or adjacent to the cam pus in order to share resources and to enhance common goals (Sink & Jackson, 2002, p. 36). Their collaboration a llowed the community to be able to reach more clients, share resources, provide employ ees with professional and personal development opportunities, and to introduce th eir clients to the colleges educational programs (Sink & Jackson, 2002, p. 46). Purpose of the Study Researchers have begun writing case studies abou t some of the institutions who chose to ignore either the warnings in the Wingspread report, the critical issues from the Futures Conference, or both. For example, some commun ity colleges started cl osing their doors and turning away students. In 2003, North Carolina es timated having to turn away more than 56,000 students because they lacked the resources to training more students (Roueche & Jones, 2005). Some researchers have written about the st eadily decreasing funding for community colleges (Brenneman, 2005; Boggs, 2004; Levin, 2004; Katsin as, 2002; Keener, Ca rrier, & Meaders, 2002; Watkins, 2000). Others have written about the concerns relative to the mass retirements facing hiring education (Fulton-Calkins & Milling, 2005; Boggs, 2004; Levin, 2004; Shults, 2001). Still yet others have writ ten about the facilities and build ings erected in the 1960s and 1970s that are now rapidly deterior ating and are now in need of substantial repair or replacement (Boggs, 2004; Levin, 2004). Since projected grow th rates of 13-17% per annum has been predicted for all community colleges during the first decade of the 21 st century these problems are likely to be exacerbated (Roueche & J ones, 2005; Boggs, 2004; Fields, 2004; Vaughn, 2000). 18

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The purpose of this study was to focus on the first two critical issues identified in the 2006 Community College Futures Assembly: innovation and entrepreneurialism is a must for survival and hire the right people, keep them, and keep the right people. As indicated, since more than 70% of community college administrators will retire within the next five years, there is little margin for error during the hiring process, especially in an environment requiring entrepreneurialism or entrepreneur ial traits or characteristics. This study did this by: examining if entrepreneurialism can be learned, examining if entrepreneurial leaders are more likely to be found in certain areas of the country, and examining if the personality test instrument used here (the WAVE) adequately measur es the personality characteristics of entrepreneurs. This research will be able to assist decision-making in the community college administrative hiring process by pin-pointing the key characteristics of entrepreneurs for use during the screening of potential candidates in their applicati ons, interviews, and other hiring instruments. Saville, Ltd., has ag reed to allow the researcher to use this instrument pro bono for the purposes of scientific resear ch and to build the normative pool of data for future testing of higher education administrators. Research Questions Can entrepreneurialism be lear ned? In other words, what is the relationship between the level of entrepreneurialism (as a cognitive application of personality characteristics) of community college administrators with doctorate degrees and community college administrators without doctorate degrees? What is the relationship of entrepreneurialis m in community college administrators with respect to economic region? Does the WAVE explain the factors involve d with measuring entrepreneurialism for community college administrators? 19

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Research Hypotheses H 1 : Those community college administrators with doctorate degrees wi ll have significantly higher mean scores for entrepreneurialism than those community college administrators without doctorate degrees. H 0 : They will not exhibit any significant difference. H 2 : The community colleges in areas identifi ed as entrepreneurial economic regions will have administrators who have significantly higher levels of entrepreneurialism than those community college administrators who are not in entrepreneurial economic regions. H 0 : They will not exhibit any significant difference. H 3 : The factors of the WAVE will contain the appropriate factors to be used as a tool for measuring entrepreneurialism as a cognitive application of personality traits of community college administrators. H 0 : The WAVE will not. Significance of the Study In response to the declining state appropriations the surviv al of community colleges is contingent on their ability to become more i nnovative, creative, and entrepreneurial by funding their own building and facility replacements, a nd ensuring open access in the face of double-digit annual growth, while competing with private and for-profit institutions. As previous researchers have suggested the survival of community co lleges will depend upon the entrepreneurialism of their current and future leaders. The significance of this study will be to give community college personnel the ability to identify a tool for examining entrepreneuria l characteristics for leadership development and personal development programs, especially during this time of high turnover, attrition and growing enrollments. For more than a hundred years personality research has been focused upon a narrow selection of personality assessment instruments. Thus, this study will continue the discussion of the use of personality testing in the hiring process but will add a new thread of academic research with personality testing of comm unity college administrators. Fina lly, but most importantly, this study will be one of the very few studies ta king a cognitive approach towards the overall 20

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understanding of how personality traits help to predict potential job success. Many researchers have recently begun suggesting correlative studi es of personality tests and their cognitive application, but not many have done so. Definition of Terms Administrator refers to a pe rson whose duties exclude teaching as their permanent fulltime job. Individuals who are program directors, directors, deans, directors, department chairpersons, vice presidents, regist rars, or presidents will be c onsidered to be administrators. Community college refers to a regionally a ccredited institution of higher education that offers the associates degree as its highest degree (Vaughn, 2000, p. 2). Community colleges that have recently adopted baccalaureate programs in the past five years will also be identified as community colleges. For the purposes of this study entrepreneuriali sm or entrepreneur will be defined as a cognitive application of personal ity traits as calculated by th e ENTRECODE system within the Saville Holdings, Ltd. suite of products. A sten unit is defined as being an abbrevia tion for standard ten unit, meaning a nominal measure from one to ten. The units themselves have no clearly defined st atus of being equally distanced between the units. The WAVE refers to the personality test and correlating reports, the Executive Summary, the Psychometric Profile, the Entrepreneurial Potential Summary, and the Entrepreneurial Profile, developed by Saville Holdings, Ltd. Limitations Data will be collected from the leadership of three community colleges and two community college board of officers and therefore will not represent the community college system as a whole. 21

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This study will be conducted among public co mmunity colleges in the United States therefore the results may not be generalizable to private, for-profit, or community colleges outside of the United States. The participants of this study will only in clude community college administrators. The results may be generalizable to all community college administrators but not to college, university, or K-12 administrators. The participant responses will be assumed to be honest and representative of their viewpoints. Since the participants are volunteers, it is likely that there will be some bias from self-selection. The study only used one research instrument from the thousands of available personality tests in the United States. The test was administered to respondents in an unsupervised fashion using computerbased testing. There is no mechanism for ensuri ng the respondents stayed on task, other than making inferences from the data after collection. 22

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CHAPTER 2 LITERATURE REVIEW The empirical study of personality differences is sometimes like a rough ride through a desert without orientation (lack ing constructs, established methods, and replicable empirical findings), sometimes like an expedition into a jungle (facing an inextricab le net of many similar but nonidentical constructs, diverse es tablished methods, and contradi ctory findings), and sometimes like a puzzle (trying to put togeth er apparently incoherent piece based on established constructs and methods). The current quest for pe rsonality types is of the last kind. -Jens B. Asendorpf (2002) The purpose of this chapter is to present a re view of the growing scholarly literature on entrepreneurialism and personality testing in rela tion to each of the guiding research questions. An overview of research findings re lated to this study is provided in this chapter. This chapter is organized under three broad headings: (a) entrepreneurialism, (b) personality testing, and (c) personality characteristics of entrepreneurs. Entrepreneurialism The Community College Futures Assembly pa rticipants have said that community college administrators need to be more entr epreneurial in order to survive into the 21 st century (Campbell et al., 2007; Campbell & Tison, 2004; Community College Futures, 2003; Campbell & Evans, 2001, Campbell & Kachik, 2001) and others in literature (e. g., Flanagan, Greene & Jones, 2006; Brenneman, 2005; Fl annigan et al., 2005; Lee & Rhoads, 2004). Entrepreneurialism has been linked to economic growth and tec hnological innovation (Str andman, 2006; Shattock, 2005; Baum & Locke, 2004). In th is section a literature review containing the definition of entrepreneurialism, the brief hi story of entrepreneurialism, a nd the reasons for the rise of entrepreneurialism in academia will be explored. 23

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Defining entrepreneurialism Researchers cannot seem to agree upon a common definition of entrepreneurship (Strandman, 2006; Zhao & Seibert, 2006; Sha ttock, 2005; Busenitz, West, Shepherd, Nelson, Chandler & Zacharakis, 2003). The recent wo rks on the theoryhave demonstrated how difficult it is to explore and define entrepreneur ial behavior since obviou sly no single model or theory will capture all elements of the puzzle (Auteri, 2003, p. 172). Moreover, it seems the literature uses the term innova tive interchangeably with entr epreneurialism (Barnett, 2005). According to Schumpeter an entrepreneur may be described as an indi vidual with a specific attitude towards change, who is able to carry out new combinations in th e process of production (Auteri, 2003, p. 172). In general en trepreneurs are those individuals who get an idea, product, or company from point A to point B, usually when there is a risk, financial, cultural, or intellectual, involved with getting from point A to point B (Barnett, 2005). Drucker (1985) says that entrepreneurship is something that can be taught and something that ca n be learned by anyone who can face up to decision-making has the ability to be an entrepreneur however there is no evidence of any empirical stud ies validating this hypothesis. Some researchers, such as Shattock (2005) have traced the ev olution of the term academic intrapreneur as an alternate definition of entrepreneur through several research studies to the foundation entrepreneurial research set by Drucker (1985). Th e literature he traced defines an academic intrapreneur as an academic change agent who rivals the traditional academic bureaucracy, structure, and procedures to creat e successful departments in spite of existing conditions, rather than con tinuing business as usual. History of Entrepreneurialism Jean Baptiste Say was the first to observe th at the essence of the economic role of an entrepreneur is that of shif ting economic resources away from and lower and into higher 24

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productivity and greater yields (Kwiatkowski, 2004, p. 205). A vast majority of literature points back to Schumpeter in the 1930s as a guiding force in the devel opment of entrepreneurialism and entrepreneurialism studies (e. g., Strandman, 2006) that was later reinvigo rated by applications of educational entrepreneurialism in United States in the 1990s (Lee & Rhoads, 2004) and then into the United Kingdom, Belgium, the Netherlands, and Germany (Editors, 2004). Schumpeter was interested in seeing how entrepreneurialism affected the economic growth within and across countries. Later, research on entrepreneurialism was also grounded heavily in the works of Drucker (1998). The idea of an entrepreneurial university has been largely attributed to Burton Clark at the University of California-Los Angeles in the late 1980s (Shattock, 2005; Sharma, 2004). Clark set out the notion that universities need to break out of the bonds constraining them by restrictive funding revenue streams from the government and to seek out to become self-sufficient. In order to do this, entrepreneurial institutions need to encourage innovative academic behavior and to develop collaborative partnerships with industry and commerce. Late r research suggests the need for understanding the culture of entrepreneurialism (Shattock, 2005). Reasons for the rise of entrepreneurialism The growing global crisis in sustainability has led the United Nations to declare 20052014 the Decade of Education for Sustainable Developmentour sustainability initiatives involves three dimensions: the curriculum, college operations, and community outreach (Bardaglio, 2005, p. 18-19). Several re searchers have called for the rise of entrepreneurialism to create sustainable developments in education: declining stat e funding (Pusser, Gansneder, Gallaway, & Pope, 2005; Lee & Rhoads, 2004), the wake up call by reports including A Nation at Risk and the Wingspread Group reports (R ouche & Jones, 2006). This call was inevitable from the Neo-Darwinian evolution of world wide business (Bhide, 2000), or from the growing 25

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prominence of for-profit institutions, such as th e University of Phoenix, DeVry, Strayer, Kaplan, and Corinthian Colleges (Brenneman, 2005; Doane & Pusser, 2005; Pusser et al., 2005; Zerbinati & Souitaris, 2005). A shift in the fo cus on the business aspects of community colleges began to rise as the leaders of private comm unity colleges began to focus on how to create a more attractive educational setting than thei r public counterparts (Brenneman, 2005). However, despite decades of research on entrepreneurialism there is still very little research on entrepreneurialism in academia, even less on the pe rsonality characteristics of administrators in academia (Zhao, Siebert, & Hills, 2005), and no res earch on cognitive applica tions of personality characteristics. Faculty and university entrepreneurialism: The curriculum Several researchers have argued for more en trepreneurialism trai ning in college and university curriculum (Zahara & Gibert, 2005 ; Anderseck, 2004; Schulte, 2004; Teczke & Gawlik, 2004; Tchouvakhina, 2004). They argue for the creation of technology centers, facilitation of start-up capital, low interest loans, and even providing industrial space if needed. Faculty entrepreneurialismdefined as the e ffort of faculty to generate revenue for themselves or their institutions (Lee & R hoads, 2004, p. 739) has come to the forefront of discussions of higher education administration as of late. As facu lty are pushed more and more into a variety of roles that may conflict with their philosophical values just to make the bottom line look good (Levin, 2004). Faculty consulting, according to Lee and Rhoads (2004), is a barrier to implementation of entrepreneurial activiti es in higher education. They say some faculty may even feel there is a conflict of interest in entrepreneurial activities and the pure scientific value of researchthat the push for f unding may cloud judgments about results. Barnett (2005) has stated there is a linear re lationship of entrepreneurialism present in all higher education institutions ( Figure 2-1 ). On one end is the innovative institution or the 26

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complacent institution, content with continuing th eir business as usual with some occasional new ideas. On the other end is the self-reliant in stitution whose entreprene urial activities have allowed it to become self-sufficient. And, as the model shows, as the level of self-reliance increases, so does the level of risk. Many of the more prevalent Ph.D. programs in educational administration, leadership, and community college administration at North Carolina State University, the University of California-Los Angeles, the University of Fl orida, the University of Michigan, and the University of Texas includes components of entrepreneurial training through the use of case studies or courses on entrepreneurship ( Table 2-1 ). There has been a proliferation of entrepreneurial courses in higher education but very little accountabi lity assessments of the effectiveness of these programs. Research does s upport the tenet that entr epreneurialism can be learned, at least by students who aspire to become entrepreneurs, but only from the personality trait perspective, and not necessarily from th e cognitive perspective (Zhao, Seibert, & Hills, 2005). Forces shaping entrepreneurialism in higher education: College operations Non-profits are actually spinni ng off for-profit organizations in response to the rise of the for-profit organizations (Auteri, 2003; Fincher, 2002). Some of the for-profit organizations spun off include corporate training programs (Doane & Pusser, 2005; Zahara & Gibert, 2005), schools of continuing education (Brenneman, 2005; Doane & Pusser, 2005; Pusser, et al., 2005; Zahara & Gibert, 2005), distance learning acad emies (Brenneman, 2005), partnering with for-profit organizations (Finch er, 2002) and real estate ope rations/technology parks, including shopping malls, retirement villages (Bardagl io, 2005; Schulte, 2004), and hotels (Doane & Pusser, 2005). Other schools are focusing on auxiliary sources of revenue by re-evaluating the profitability of their boo kstore contracts, dining halls, student residences, parking divisions, and 27

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research operations, including patenting and lice nsing (Doane & Pusser, 2005; Zahara & Gibert, 2005). These expanding services and areas cause overlaps between the academic world and the economic world ( Figure 2-2 ). What typifies the successful for-profits is a clear focus on education and training for employ ment, coupled with an emphasis on the student as client, or consumer, rather than supplicant (Brenneman, 2005, p. 8). Culture of entrepreneurialism: Community outreach Attracting talent is one th ing, but attracting entreprene urs is another (Ryan, 2004, p. 37). She says quality of life is key for attracting and keeping entrepreneurs in your area. What do your workers like to do after 5 p.m.? is one question she urges employers to ask. She cites Dells recent decision to move into Austin Te xas was based largely upon the music scene to resonate with their young, digital workforce. Ry an also adds that entrepreneurs like the company of other entrepreneurs and urges researchers and compan ies to correlate entrepreneurs with the numbers of patents in an area ( Table 2-2 ). Moreover, an increasing amount of recruiters are starting to feed off the entrepreneurial zones. Hiring an entrepreneur is step one, keep ing them is step two. A growing share of funding allocated to universities on a competitive basis imp lies progressively more intense competition to attract and keep talent (Zahar a & Gibert, 2005, p. 33). Moreover cities have joined in the competition, not only for recruiting talent to the areas, but to attract young talent to build foundations for the future (Dewan, 2006). This study will focus on entrepreneurial pers onality traits and finding entrepreneurs by using a cognitive application of a personality test. In the next section will be an exploration of the theoretical components of personal ity psychology and personality testing. 28

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Personality Testing There has been little written on the philosophi cal underpinnings of personality types and characteristics. There simply are no writings from Aristotle, Socrates, Plato, Kant, Descartes, or any other philosophers that dwell on the topic of personality to form a classical philosophical basis for personality testing (Vernon, 1933). A ny mention of persona lity in classical philosophical literature generally refers to the character of an individual, not the concept of personality itself (e. g., Dobson, 1919). The field of personality psychology has been advancing for more than one hundred years as a newer subset of psychological research. Personality psychology studies the characteristics of individuals and those characterist ics related to the cognitive abili ty, behavior, and motivation of individuals in a variety of setti ngs through the use of a variety of personality testing mechanisms (Srivastava & John, 2006). In this next section the foundations and history of personality testing is explored. The Psychological Foundations of P ersonality Testing: Two Models Not until the late 1800s and early 1900s did th e foundations of personality research begin to be constructed with the explosion of psychol ogical research into th e ego, the conscious, and the subconscious by researchers such as Sigmund Freud, Jean Piaget, B.F. Sk inner, and others (e. g., Holt, 2005; Green, 1996; Fisher, 1882, p. 16-17). One of the dominant issues in personality research lately has been on the structure of personality and how to best measure personality (Grice, 2004; Tuerlinckx, 2004; Jack son, Furnham, Forde, & Cotter, 2000). There are three main approaches to this: (1) an idi ographic approach concerned with the individual, their growth and how they interpret and respond to reality (Grice, 2004), or th e extrovert approach, (2) the nomethetic approach concerned w ith the generalities involved with personality research and the need to quantify and identify tra its in people (or the introvert approach) and in groups (Grice, 29

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2004), or (3) somewhere inbetween by studying personality traits, demographics and correlations to group behaviors (Grice, 2004; Tuerlinckx, 2004). From there perspectives on the characteristic s and types of personalities have been explicated, but most literature on personality and personality testing is generally grounding in the works of Carl Jung, a student/colleague of Sigmund Freud (Lampe, 2004; Moore, Dietz, & Dettlaff, 2004; Wheeler, Hunton, & Bryant, 2004; Isaken, Lauer, & Wilson, 2003; Saville & Willson, 1991; McRae & Costa, 1989) or the Five Factors Model developed by Allport and Odbert (1936; (as cited in Bernard, Wals h & Mills, 2005); McRae, Costa & Busch, 1986). The Jungian Model Jung described the three components of persona lity or psyche as the ego, the personal unconscious and the collective unconscious: Jung's theory divides the psyche into thr ee parts. The first is the ego, which Jung identifies with the conscious mind. Closel y related is the personal unconscious, which includes anything which is not presently cons cious, but can be. The personal unconscious is like most people's understanding of the unc onscious in that it includes both memories that are easily brought to mind and those that have been suppressed for some reason. But it does not include the instinct s that Freud would have it in clude. But then Jung adds the part of the psyche that makes his theory stand out from all others: the collective unconscious. You could call it you r "psychic inheritance." It is the reservoir of our experiences as a species, a kind of knowledge we are all bor n with. And yet we can never be directly conscious of it. It influences all of our expe riences and behaviors, most especially the emotional ones, but we only know about it indirect ly, by looking at those influences (Boeree, 2006). Jung determined that all people have two basic pers onalities: of being an in trovert or of being an extrovert. Introverts tend to think inward or stick to themselves. Extroverts tend to think of others and the social aspects and activities (McRae & Costa, 1989). [ Jung] postulated that individuals relate to the worl d through two sets of opposed f unctions: the rational (or judging) functions of feeling and the irrational (or perceiving) functions of sensing and intuition (McRae & Costa, 1989). It is from these four functions (sensing, thinking, intuiti on, and feeling) and two 30

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basic personalities (introve rts and extroverts) that form the basi s of characteristics for personality testing. The Five Factors Model The Five Factors Model (FFM), grounded in the work of Allport and Odbert (1936 (as cited in Bernard, Walsh & Mills, 2005) is ge nerally regarded as the consensus model for measuring personality characteristics broadly and systematically by de composing the broader personality into five general factors (Bernard, et al., 2005; Furnham & Crump, 2005; Asendorpf, 2002; Briggs, 1992; McAdams, 199 2; McCrae, Costa & Busch, 1986) in a way more refined than the Jungian Model. Allpor t heartily endorsed the use of common traits as convenient approximations and argued that factor analysis an d other statistical devices could best be used to educe the proper factors of personality traits (Briggs, 1992; p. 289). However, personality psychologists have also cautioned to not be too enamored with any one model, such as the FFM, that seems to find consistently high reliabil ity and validity. From the standpoint of a multifaceted personology the FFM is one important mode l in personality studies not the integrative model of personality (McAdams, 1992, p. 355). Still, there are others who ascribe to the Five Factors Model theory yet believe the basic range of personality factors lies somewhere between three and six factors ( Table 2-3 ). Overall, McAdams (1992) says the fundamental components of personality traits lie in Freuds Theories of the ego, superego, the id, an d others. He said the core characteristics of personality traits are related to human nature and the periphery ch aracteristics are related to the differences between human beings. Whereas Furnham & Crump (2005) generally agree but instead see personality testing as being more indicative of cognitive, affective, and social aspects of functioning (see also Isaken, Lauer & Wilson, 2003). When looking at an overall psychological model of personality McAdams s uggested we should not be concerned with 31

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focusing upon the overall few main factors, but should, at the same time, be focused upon the many mid-level factors too. Toge ther, these will comprise an adequate representation of a personality (see also Bernar d, et al., 2005; Furnham & Crum p, 2005; Costa & McRae, 1992). The FFM used the lexical approach in its deve lopment. The lexical approach to the study of personality descriptors means we use words to understand the behaviors of people with traits. The more words used to describe a trait, the greater variation that can result in the interpretation of the statement by individual. In some instances single words are used and in other instances phrases are used. The advantage to using phrases over single adjectives is the richness it provides. The disadvantage is the longer the phrase s the more variation in interpretation that may results. This is the foundation of lexicol ogy (Briggs, 1992; McAdams, 1992). The FFM started with over 400,000 adjectives describing personality traits which, over time, were condensed into five main components ( Figure 2-3 ): neuroticism, introversion/extraversion, openness to experience, agreeableness, and conscientiousness (Briggs, 1992; McAdams, 1992). Neuroticism is measured in the Five Factor s Model as the opposite of being maladjusted or being socially emotional. Neurotic people ar e seen as emotionally unstable. Extraversion is seen as being sociable, enjoying groups and the company of others in contrast to being an introvert. Openness is measured as being open to new experiences, being cu rious about things as opposed to being a person who enjoys things th ey way they are. Kunce, Cope, & Newton (1991) refer to this as the difference between the n eed for stability and the need for change. Agreeableness is measured as being sympathetic a nd eager to help others. Conscientiousness is measured as being self-contro lling, meticulous, organized, pur poseful, scrupulous, and planning (Bernard, et. al., 2005; Sato, 2005; Costa & McRae, 1992). 32

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Since the FFM was derived from foundation adje ctives for every possible personality trait theorists suggested the FFM should be valid a nd reliable across cultures as well. McAdams (1992) has said the FFM has been found valid and reliable for use in English, German, Japanese, Chinese, Tagalog (Filipino), and Modern Hebrew. To the contrary, Asendorpf (2002) has said we cannot expect a high degree of consistency across languages and cultures, among other items. The FFM is generally accepted as one of th e pillar foundations for studying personality psychology, also known as persono logy (McAdams, 1992). Some, such as John (1989, as cited in McAdams, 1992) use the biological classifica tions of animals into genus, species, and subspecies as an analogy to break personalities in to domains, clusters, and facets. He also likens personality traits as a map of elements are pl aced in a periodical chart of the elements. Some domains could be likened to the noble gases, so me to metals, and some heavy metals. McCrae and Costa (1989) have said just as studying the common English terms describing the human anatomy can in no way provide an adequate unders tanding of the human being in society, neither can a study of personality traits be considered an adequate un derstanding of a human and the cognitive applications of that human in society (as cited in McAdams, 1992). There has been some disagreement historically on personality traits and whether or not personality traits change over time. Some, such as McRae & Costa (1984, as cited in McAdams, 1992) have said personality traits are fixed, ri gid and do not change no matter how life changes around the person. Pedersen & Reynolds (1998) have criticized some of these samples in these studies. They noted the samples tended to all be post-college adults and s uggested the ability to change a personality trait slows with age. Sti ll others, such as Saville (2006b) have said personalities are constantly changing and each personality changes enough to warrant remeasurement every 18 to 24 months. Howard and Howard (2005) found people in their 20s tend 33

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to have reductions in their trai ts in extroversion, the need for st ability (openness to experience), and originality (also a part of openness to experience) thus su pporting Savilles claim of trait changing over time and possi bly even in a short period. Contemporary Personality Test Constructs: Some Debates Personality tests or individual assessments have been descri bed as a set of procedures that measure an individuals j ob related knowledge, skills, ability, and personality characteristics for the purpose of making a recommendation, or infe rence, about an individuals suitability for a job (Kwaske, 2004, p. 187 (as cited in Prie n, Schippmann, & Prien, 2003); Highouse, 2002; Jeanneret & Silzer, 1998). An early debate ensued with the construction and design of personality tests in psychometric analysis: to use short adjectives (i .e., Interpersonal Adjec tives Scales, Minnesota Multiphase Personality Inventory, NEO Personality Inventory) or to use phrases and sentences within the test (ie., Eysenck Personality Questionnaire-Revised, Myers-Briggs Type Indicator, the Saville Occupational Personali ty Questionnaire (OPQ)). Some of these tests used hundreds or even thousands of adjectives or phrases as their methodology (Briggs, 1992), making them bulky, cumbersome, and time-consuming (Sato, 2005; Petrides, Jackson, Furnham, & Levine, 2003). Some of these tests received criticisms of their items as being sub tle, as being too long, as being too ambiguous, as being biased, as being bizarre, as us ing conjunctions in items, as having negative items, as having litt le understanding of criteria by the developers and users, as having too long of scales, as ha ving non-self referring items, as containing idioms, and having items that may be seen as an intrusion of indi vidual privacy (Saville, 2006b). For example, tests may confuse what they are measuring in an ambiguous fashion: being friendly and having friends is not the same as the need for friends (Saville, 2006; McAdams, 1992) Over time the researchers used factor analysis and principal component analysis to reduce the items to their 34

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core of around 100 items (Briggs, 1992). Generally most personality tests are based upon those items correlating to between three and six over a ll factors in their theo retical foundation (Great Ideas, 2001). Critics have said some scales in personality testing have artificially inflated inter-item reliability (Saville, 2006). For example, in a test of alcohol consumption an inter-item reliability of the instrument was reported to be within the .90 range. Norma lly this would indicate a very reliable test however in practice the questions me rely were all the same issue: I drink a lot, I often drink, very often I drink, et c. Saville (2006b) has noted a pr eference for scales with interitem reliabilities in the .60 range as being high ly reliable while actual ly measuring different facets of factors. Another criticism of personality testing is commonly referred to as the Barnum Effect. A personality test was administered to a group of employees with th e results being given to them two weeks later. Half of the group received their actual scores and the other half received the same score from one person in the group. All were asked how closely the results fit their actual characteristics, in their opinion. More than 80% of the entire group ag reed the results fitted themselves (Saville, 2006b). Personality tests, according to Saville (2006), can be classified in one of three categories: deductive, inductive, or validation-centric. Test s such as the Myers-Briggs Type Indicator (MBTI) or the Occupational Personality Ques tionnaire (OPQ) are based more on a deductive style of testing, that meaning, application to the real world, and future performance from personality characteristics can be deduced from th e scores. These tests are used to determine the personality characteristics and the resulting jobs or careers which may best suit an individual. In contrast tests such as the 16PF or NEO-Persona lity Inventory he says are more inductive and 35

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designed to tell the individual something about themselves and their current level of performance. The WAVE is a combination of the tw o styles, or what Saville refers to as being validation centric. The WAVE is designed to show the personality characteristics of an individual, what environments they work best and do not work best within, and can deduce a growth and learning plan for the individual. The WAVE has also been designed to take advantage of technological advances for questionnaire design (Saville, 2006b). Other researchers have disagreed with the earlier versions of th e WAVE and the development of the instrument and scales (such as Closs, 1996; Cornwall & Dunlap, 1994; McRae & Costa, 1989) but now, 13 years later, other researchers are supporting the methods espoused by Saville (Saville, 2006b; e.g., Chan, 2005). Briggs (1992) has said the better personality tests to assess the Five Factor Model are the NEO-PI and the Hogan Personality Inventory (HPI) both of which preceeded the WAVE. The NEO-PI, developed by Costa and McRae (1992), uses three broad domains, each with six clusters of eight facets to asse ss the Five Factor Model. To assess this, Costa and McRae used factor analysis, with varimax and validmax rota tion. An abbreviated form of the NEO-PI, called the FFI, was also developed. Costa and McRae (1992) found about 75% correlation between the items in the abbreviated version and the longer version, implying abbreviated forms can measure similar traits in a more condensed and abbreviated form (Briggs, 1992). The HPI, developed by Hogan, uses six broad domains or scales, with 43 subscales or Homogeneous Item Clusters (HICs), using 310 ite ms overall to assess th e Five Factor Model. Hogan divided the extraversion factor into ambi tion and socialability. He argued while these are both components of extraversion society delineate s these two factors into separate meanings. Hogans primary objective is to show that pers onality measures, when properly developed and 36

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competently used, will predict criteria that matter to consumers outside of psychology (Briggs, 1992, p. 277). The HPI is being used to as a pe rsonality assessment for job selection and placement (Briggs, 1992). Both the NEO-PI and the Hogan Personality inventory were designed to show their robustness and demonstrable stability over many decades (Briggs, 1992). One criticism of these two instruments is to normalize the data in an ipsative fashion since subject-standardization scores have been shown to result in more stab le factor structures across samples and in an overall reduction of correlations among domain scores (Briggs, 1992, p. 279). Furthermore, Briggs (1992) has said the next generation of personality assessment should use more mid-level items and categories or primary constructs in their design. The WAVE is just one of more than 2500 diffe rent personality tests being used in the United States (Hough & Oswald, 2005). The United States Patent Office includes patent number 5,551,880 for the development of an employee succe ss prediction system (Bonnstetter & Hall, 1996). With many different tests available personal ity test researchers ha ve yet to come to a consensus on a number of issues with respect to personality testing: Researchers have yet to agree about the futu re research agenda for personality testing (Hogan, 2005; Hough & Oswald, 2005; Murphy & Dzieweczynski, 2005) There has been much debate about the cons istency of personality tests (Saville, 2006b; Grice, 2004; Asendorpf, 2002; Baron, 1996; Closs, 1996; Briggs, 1992; McAdams, 1992; Saville & Willson, 1991; McRae & Costa, 1989) Researchers have shown little regard for measurement validity (Saville, 2006b; Hogan, 2005; Hough & Oswald, 2005; Murphy & Dziew eczynski, 2005; Stricker & Rock, 1998) and criterion validities for pe rsonality variables (Saville, 2006a; Saville, 2006b; Hogan, 2005; Hough & Oswald, 2005; Stricker & Ro ck, 1998). Hough and Oswald (2005) have said that validities in the .10-.30 range are common and deemed acceptable among personality researchers. 37

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Researchers have shown little regard for practical applications of personality testing (Saville, 2006b; Hogan, 2005; Hough & Oswald, 2005; Murphy & Dzieweczynski, 2005; Grice, 2004; McAdams, 1992) Overall the quality of personality testing re search is generally substandard (Bernard, Walsh, & Mills, 2005; Hogan, 2005; Hough & Oswald, 2005; Murphy & Dzieweczynski, 2005; Wiggins & Broughton, 1991) In the past the most outspoken critics of pers onality testing were behavioral psychologists who are largely extinct (Hogan, 2005; Hough & Oswald, 2005; Murphy & Dzieweczynski, 2005) The choice of personality test for research projects are generally hasty and poorly selected (Hough & Oswald, 2005) Personality tests leave too mu ch room for faking (Winkelspecht, Lewis, & Thomas, 2006; Goffin & Christiansen, 2003; McFarla nd, 2003; Costa & McRae, 1997) or leave too much room for self-reporting bias (Campbell, Bonacci, Shelton, Exline, & Bushman, 2004; Costa & McRae, 1997) Outside of personality test researchers th ere is little acceptanc e of the results of personality tests as a correlative measur e of cognitive ability (Hough & Oswald, 2005) The on-going controversy between use of norma tive and ipsative testing (Christiansen, Burns & Montgomery, 2005; Meade, 2004; Ma rtinussen, Richardsen & Varum, 2001; Baron, 1996; Cornwall & Dunlap, 2004; Closs, 1996; Saville & Willson, 1991; Johnson, Wood & Blinkhorn, 1988). The link between personality research and practical application is poorly understood (Saville, 2006b; Hough & Oswald, 2005) Newer versions of personality tests are not be ing designed to take advantage of advances in computerized testing (Sav ille, 2006b; Potosky & Bobko, 2004) After decades of criticism for the use of pers onality testing construction researchers now are beginning with a renewed emphasis on personality tes ting research, especially with its cognitive applications to the workplace (Savil le, 2006b; Hough & Oswald, 2005; Murphy & Dzieweczynski, 2005; McAdams, 1992). 38

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Personality Testing for Job Selection Research on personality test ing for job selection has gone on for almost a hundred years however, the 1990s saw a renewed emphasis for researchers to begin more extensive examinations of which mechanisms woul d most accurately predict job success ( Figure 2-4 ). Baines and Mabey (1999) showed the use of re ferences only in the interview process would correspond to a candidate working out in a positi on only 10 % of the time. In fact, researchers have shown interviewing, while the most commonly used tool in the hiri ng process, is still a highly flawed and imperfect tool. Some of the fl aws include stereotyping of candidates, primacy effects, similarity effects, and negative inform ation weighting bias (Barclay, 1999). Personality testing, however, would be the highest mechanis m at 40% while only requiring about 2 hours worth of time. Work sample tests and assessm ent center approaches, while being a slightly higher predictor of job success, require much more time and effort than pe rsonality testing. It is generally noted however, the highe r the position of authority the more rigorous the applicant screening process should be (Wilk & Capelli, 2003). Several researchers agree usi ng personality tests in the hi ring process will generally correlate to a greater leve l of success than by using other methods (e. g., Chan, 2005; Viswesvaren, Ones, & Hough, 2005; Robertson & Smith, 2001; Terpstra, Kethley, Foley, & Limpaphayom, 2000; Bain & Mabey, 1999; Schmidt & Hunter, 1998; Salgado, 1998; Frei & McDaniel, 1997; Van Scotter & Motowidlo, 1994; Motowidlo & Van Scotter, 1994; Ones, Visweveran & Schmidt, 1993; Barrick & M ount, 1991; Tett, Jackson, & Rothstein, 1991). Personality tests have become the norm in hiring for certain occupations, including law enforcement (e. g., Barrett, Miguel, Hurd, Lu eke, & Tan, 2003; Varela, Scogin, & Vipperman, 1999) and the health care industry (e. g., Socolof & Jordan, 2006). Krell (2005) said personality tests, combined with a benchmark analysis of po sitions, can be used to help generate questions 39

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for interviews and follow-up interviews, gauge comfort levels of the interviewee with the position, set job roles and responsib ilities, and customize hiring practices. It should be noted however, personality testing has been said to only be useful in j obs which correlate to the test. For example, a test which includes a section on interpersonal skills will only be useful for a job requiring interpersonal skills (e. g., Viswesvare n, Ones, & Hough, 2005). In short, researchers have said personality tests are not the be-all, end-all for every position or career. Using personality testing for prescreening appl icants for job fit and team fit has reduced attrition and turnover rates as much as 61% in corporations. At Benchm ark Assisted living the turnover rates routinely surpassed 80%. By using a personality test as part of a prescreening mechanism their attrition rate dropped to 29% three years after implem enting its use (Krell, 2005). Researchers generally agree people choose their career based upon their interests and preferences however, sometimes an outside n eed of the person dictates searching for employment in a position that may not be well-s uited to their strengths. For example is the motivation of the applicant to the position based solely upon the pay for the position or based on the interests of the applicant? For this reason pe rsonality tests are well-s uited (Balkis & Isiker, 2005; Krell, 2005). Unlike job assessment center approaches (e g., Chan, 2005; Borman, 1997) researchers have said screening processes should look more into how the prospect fits the culture and environment of a company and how adaptable they can be for changing positions within the company, since job roles and functions can vary upon tasks and assignments in the contemporary corporation, rather the wholly focusing upon the ch aracteristics of an individual in a certain position (Chan, 2005; Collins, 2005; Krell, 2005; Borman, 1997). Selecting for adaptability, interactional skills, a willingness to learn, and a repertoire of multiple skills predicted to be 40

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important to future organizational functioni ng will be increasingly important (Borman, 1997, p. 302). Collins (2005) has said the task ahead is not only to get the right person on the bus, but to get the right people in the right seats in order for the bus to f unction properly (see also Krell, 2005). Some may argue using personality tests ma y exclude someone from a position in an arbitrary manner however this is not the case with most usag es of personality testing: What employers are not doing is using the te sts to weed out applicants who are not a cookie-cutter match of the ideal employee. To the contrary, HR professionals are using personality profiles to analyze the organizatio ns bench strength and to find a variety of candidates who possess the dive rse personalities and styles that the organization needs (Krell, 2005, p. 48). Krell (2005) said employers are using personality tests for currently employees to determining the characteristics of their existing employees and then, in turn, are using those results to determine who is ideally suited for a position an d thus can be given more free reign and who may need to have additional help to be more productive. The ability to fit a job is not the only porti on which needs to be considered, the prospect must also fit the team as well (Chan, 2005; Kr ell, 2005; Borman, 1997). Researchers generally agree teams should be very heterogeneous in their compositions (e. g., Borman, 1997) yet research on understanding work groups and team dynamics, as it applies to personnel selection and staffing is still a long way off (Borma n, 1997; see also Chan, 2005; Landy, Shankster, & Kohler, 1994). A final fit here to be considered, which is differe nt from a corporate hiring, is how well the person will fit with the other member s of the school. We want to make sure that were not adding leaders in [per sonality] areas where were alr eady heavy. We want to make sure we have the right qualities to guide use th rough the unique challenges of our next stage of growth (Haselman, 2003 (as cited in Krell, 2005, p. 47)). Leaders who are hired in the corporate 41

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world typically do not also have to be ble ssed by faculty or a board (Lapovsky, 2006; Funk, 2005). In fact some researchers in the K-12 sy stem have found the best succession plans are those which have been blessed by th e organization (Fink & Brayman, 2006). Potential employees are said to also exhi bit more positive attitudes during the hiring process when faced with more extensive testing si nce they equate extensive testing with quality and interest (Rafaeli, 1999). A pplicant perceptions have been found to be positively correlated with actual and perceived performance on selection tools during the hiring process (Hausknecht, Day & Thomas, 2004). Using a personality test or not researchers have warned about potential common mistakes in the hiring process such as making a ru shed decision (Messner, 2005; Lloyd, 2002), becoming enraptured with a candidate (also known as the ha lo effect because they went to the same school, participated in the same fraternal organizati ons, etc.) (Messner, 2005; Lloyd, 2002), or skipping reference checks (Messner, 2005) as the primary reasons fo r making poor hiring choices. Personality Testing in the Workplace Personality testing is also gaining mo mentum as an on-going tool for employee development (Krell, 2005). While earlier resear ch tended to denounce pers onality testing, later research is lauding the gains in the instruments (Gettler, 2004). For example, the Yankee Candle company recently added personality testing as a leadership team development exercise (Krell, 2005). Companies now integrate personality a ssessments with skills tests, leadership evaluations, 360-degree reviews, and other performance manage ment processes and systems (Krell, 2005, p. 48). The resulting ga p analysis is then used to de velop training programs to help leaders prepare for the future ne eds of the company (Krell, 2005). Krell added personality testing is being used to give organizations a snapshot of the benchmark strengths and weaknesses of their executive teams. In this manner hiring new 42

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associates to the execu tive team can look for a good fit with the team and avoid becoming too heavy on managers without having enough leaders. We just want to make sure were not adding leaders in [personality] areas where were alr eady heavywe want to make sure we have the right qualities to guide us through the unique challenges of our next stage of growth (Haselman, as quoted in Krell, 2005, p. 50). No research has been found to s how how personality testing can be used in leadership development for community college administrators. A Caveat: Personality Testing in the Workplace While personality testing is enjoying a renewed emphasis of interest as of late some researchers have said personality testing is on ly one facet of the holis tic personality of an individual. What is missing in the research, they say, is a measure of cognitive ability measurement along with personality tests as m echanisms for predicti ng job success (Howell, 2004; Neubert, 2004a; Neubert, 2004b; Sinha, 2004; Stupak, 2004; LePine & Dyne, 2001). Legalities of personality testing Not all psychological tests are valid for use, or for use in certain areas of the United States or elsewhere. Tests used in the hiring process must adhere to guidelines from the Equal Employment Opportunity Co mmission (Krell, 2005). Section 3: Discrimination defi ned: Relationship between use of selection procedures and discrimination. A. Procedure having adverse impact cons titutes discrimination unless justified. The use of any selection procedure which ha s an adverse impact on the hiring, promotion, or other employment or membership opportunities of members of any race, sex, or ethnic group will be considered to be discriminatory and inconsistent with these guidelines, unless the procedure has been validated in accordance with these guidelines, or the provisions of section 6 of this part are satisfied. B. Consideration of suitable alternative selection procedures. Where two or more selection procedures are available which serve the user's legitimate interest in efficient and trustworthy work manship, and which are substantially equally valid for a given purpose, the user should use the procedure which has been demonstrated to have the lesser adverse impact. Accordin gly, whenever a validity study is called for by these guidelines, the user should include, as a part of the validity study, an investigation of suitable alternative selection procedures and suitable alternative methods of using the 43

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selection procedure which have as little adverse impact as possible, to determine the appropriateness of using or validating them in accord with these guidelines. If a user has made a reasonable effort to become aware of such alternative proce dures and validity has been demonstrated in accord with these guide lines, the use of the te st or other selection procedure may continue until such time as it should reasonably be reviewed for currency. Whenever the user is shown an alternativ e selection procedure with evidence of less adverse impact and substantial evidence of validity for the same job in similar circumstances, the user should investigate it to determine the appropriateness of using or validating it in accord with these guidelines. Th is subsection is not intended to preclude the combination of procedures into a significantly more valid proce dure, if the use of such a combination has been shown to be in compliance with the guidelines (Equal Employment Opportunity Commission, 2007). To have a better understanding of the guideline s Pfenninger (as cited in Krell, 2005) has identified eight questions to answer before selecting a personality test for use in your organization which align with the Equal Em ployment Opportunity Commission (EEOC) guidelines: 1. What is the assessment designed to measur e and accomplish, and how will that benefit the organization? 2. Does the assessment come with an accompanying job analysis tool that allows for the thorough identification of the jobs requirements? 3. Is the assessment free of bias with respect to the responde nts age, gender or ethnic group? 4. Is the assessment reliable? That is are peoples scores on it relatively consistent over time (repeatable)? 5. Is the assessment valid? That is does it effectively predict relevant workplace behaviors that drive metrics such as sales, employee longevity, customer satisfaction and others? 6. Is documentation supporting questions 3, 4, a nd 5 readily available in the form of a technical manual or equivalent documentati on that is consistent with EEOC guidelines? 7. Is research on questions 3, 4, and 5 on-going? 8. What are the key implementation issues, such as cost, time it takes to complete the assessment, data security, scalability to al l levels of the organi zation (note that many assessments can only be used at certain hierar chical levels or with certain jobs) on-going support from the vendor, and degree of empha sis on client self-sufficiency/knowledge transfer? (Krell, 2005, p. 52) 44

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Selection of personality tests th at do not adhere to these guide lines may expose your organization to potential litigation. There has been some litigation with respect to personality testing. For example, in Soroka v. Dayton Hudson, 19 Cal. App. 4 th 1200 (1991) this class acti on case the suit involved objections to the use of the California Psyc hological Inventory (CPA) and the Minnesota Multiphasic Personality Inventory (MMPI) when seeking employment as a security guard at Target on invasion of privacy grounds. Among the quest ions in these tests were items such as the belief in a god or gods, whether or not they atte nd church, and questions about their sex lives. The suit was settled out of court with no admission of wrong doing. Further in Karraker v. RentA-Center, Inc., 2005 U.S. App. LEXIS 11142 (June 14, 2005) the MMPI was later found to violate the Americans with Disability Act (ADA) specifically 42 U.S.C. 12112 (d)(3), (4)) (Daniel, 2005; Canoni, 2005; Proskauer-Rose, 20 04). The court found the test was designed to identify mental illness and not job-fit. The courts have been inconsistent on their rulings (e. g., Karraker v. Rent-A-Center, Inc., 316 F. Supp. 2d 675, C.D. Ill. 2004; Thompson v. Borg-Warner Protective Services, Corporation, 1996 U.S. Dist. LEXIS 4781 (N.D. Calif. 1996); Soroka v. Dayton Hudson, 235 Cal. App. 3d 654 (1991)). This is not to say all personality tests shoul d be avoided. Any test that may screen for psychological or medical issues should be care fully considered by legal counsel (HR Magazine News Staff, 2005; Terpstra, Kethley, Foley, & Limpaphayom, 2000). Fu rther, Canoni (2005) suggests before a personality test is used the employer conduct an assessm ent of the extent of their use throughout the company; a thorough analysis of the de sign and purpose of the test should be conducted; similar inquiries to em ployment agencies which provide employment screening be made of tests being used; an analysis of the effec tiveness of the test and whether 45

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they have been helpful be conducted; and an anal ysis of the test with respect to ADA laws be conducted by legal counsel. Personality traits of entrepreneurs In a broad sense entrepreneurs like to look for opportunities to explo it for the benefit of the company (or school). Shaver (2005) stated as contemplation is the essential ingredient of reflective thought, action is an es sential ingredient of entrep reneurial behavior. Identifying opportunities, finding ways to take advantage of them, enlisting others in the cause, and executing a plan all require doi ng (p. 21). One key aspect of an entrepreneur is a person inclined to ask why is it this way is also like ly to ask why cant it be different? or why cant it be better? (Shaver, 2005, p. 21). Entrepreneurs prefer working in unstructured environments where their creativity can run free, especially when they can have control of the entire decision-making process in the venture (Zhao & Seibert, 2006). Entrepreneurs are not the ni ne-to-five employees. In fact, they tend to be work-a-holics, staying on task until complete d (Zhao & Seibert, 2006). This fact has been corroborated by several researchers (e. g., Shattock, 2005; Zhao & Seibert, 2006). Not everyone is an entrepreneur. In fact entr epreneurs like to spe nd their time reflecting and contemplating how to make things better, ra ther than enjoying what they have around them. Schroder (2006) says would-be en trepreneurs should ask themselves two questions: first, do I have what this takes? And second, does this give me what I want? (p. 24). Furthermore, Bhide (1994) says entrepreneurs [are] smart enough to recognize mistakes and change strategies (p. 161). Bhide (1994) says entreprene urs get their ideas, from thi nking and contemplation, from four primary inspirations: (1) from ideas they encountered ear lier, from other employers or elsewhere, which they are modify ing or replicating, (2) from se rendipitous discovery, (3) from 46

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the PC generation, or (4) by peru sing research literature ( Figure 2-5 ). Entrepreneurs are always on the lookout for new opportunities. Drucker ( 1998) says entrepreneurs will first look for opportunities in internal and exte rnal locations. Four such areas of opportunity exist within a company or industry: unexpected occurrences, incongruities, pro cess needs, and industry and market changes. Three additional sources of oppor tunity exist outside a company: demographic changes, changes in perception, a nd new knowledge (Drucker, 1998, p. 150). Entrepreneurialism is linked th roughout the literature with risk taking (e.g., Shattock, 2005; Ponticell, 2003). However, there are very few studies with respec t to risk taking and education. In fact, Ponticell (2003) has claimed th ere to have found only three studies as a basis for her study on risk taking characteristics of t eachers. She found the earlie r claims of the three characteristics of risk (loss, significance of loss, and uncertainty) were not sufficient to explain the overall elements of risk and the constructs of emotion, gain, social interaction, organizational processes, and collective group values should be included. Is becoming entrepreneurial a be-all, endall solution? Researchers are leary of entrepreneurs for several reasons. First, entreprene urs feel they must be all things to everyone. Given the fast-paced changes community college leaders face this is more of a norm. Second, entrepreneurs are constantly be ing distracted by small problems which can make them feel like they are performing menial tasks, lessening thei r prestige. They are unnerv ingly vulnerable, they do not respond well to volatilities Finally, they have little control of their own time, staying focused upon completion of tasks. If some part of their staff were to leave during a project it may derail the whole thing (Schroeder, 2006). Is the higher educational system ripe for en trepreneurial efforts? Drucker (1998) says whenever an industry has a steadily growing ma rket but falling profit ma rginsan incongruity 47

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existsWhen an industry grows quicklythe criti cal figure seems to be in the neighborhood of 40% growth in ten years or less its structure changes (p. 150154). Recall the earlier figure of Rouche and Jones (2006) community college enro llments are growing by 13-17% per year, the equivalent of more than 130-170% for a ten year pe riod, if growth is sustained. Entrepreneurs, or persons with entrepreneurial tende ncies, tend to gravitate towards institutions and positions of entrepreneurialism (Zhao & Seibert, 2006). Witt (2004) proposed a model for meas uring entrepreneurial networks ( Figure 2-6 ). The moderating variables m i are specific for each start-up and i ndicate that the causal links between the different versions of the independent variab le depend on external factors, for example, the founders entrepreneurial aspira tions, networking abilities, abso rptive capacities, and gender (Witt, 2004, p. 396). He did not test it but establishe d it for future consideration in effectiveness of entrepreneurial studies. Personality traits of entrepreneurs have b een studied from a variety of perspectives including entrepreneurial cognition and opportun ity recognition (Ardivhville, Cardozo, & Ray, 2003 (as cited in Zhao & Seibert, 2006)), entreprene urial role motivati on (Baum and Locke, 2004), and entrepreneurial career intention (Cra nt, 1996; Zhao, Seibert & Hills, 2005 (as cited in Zhao & Seibert, 2006)). In fact, many of the st udies have been inconclusive, have reported no significance, or have reported entrepreneurialism as a personalit y characteristic has no merit for study. Still researchers believe the earlier tests were premature, ill-conceived, and warrant further study because the early tests did not measure the full range of personality as it applies to job performance, job satisfaction, and leadership (Zhao & Seibert, 2006; Baum & Locke, 2004). Baum and Locke (2004) studied the effects of the environment for creating challenges to incubate entrepreneurial conditions: (1) extreme uncertainty (n ewness of products, markets, and 48

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organizations), (2) resource shortages (financi ng, knowledge, operations assets, and legitimacy), (3) surprises, and (4) rapid change. The study suggested passion, tenacity, and communication are the most important traits for entrepreneurial leaders. They were, howev er, quick to point out there may be a causal relationship between experience and skill, since entrepreneurs tend to work longer hours, be more focused on the task at ha nd, and therefore may be seen as being more experienced with these traits. In this section we have seen a variety of pers onality traits of entrepreneurs. Entrepreneurs are focused, are risk-takers, can see or disc over new opportunities readily, are more open to people than other times, are reflective, are visi onaries, are good at bui lding new projects, are good at evaluating problems and making decisi ons, and are good at creating innovation. Entrepreneurs are not really focused on enjoymen t and do not respond well to volatility. Finally entrepreneurs tend to gravitate towards entrepreneurial institutions, to be with other entrepreneurs. In the next section we will examine, from a broader perspective, personality testing and measurement. Zhao and Seibert (2006) found support for se veral hypotheses using the Five Factors Model to study the relationship between entrep reneurialism and manage rs. They found support for entrepreneurs being higher in extraversion, openness, and conscientiousness and managers being higher in neuroticism and agreeableness than entrepreneurs ( Figures 2-7 -2-11). Zhao & Seibert (2006) concluded more research n eeds to be conducted on differentiating between entrepreneurialism and managers by using comp rehensive personality testing. They caution, however, that personalit y traits, entrepreneurialism include d, can change over the life cycle of ventures. Furthermore they concluded the underl ying information about en trepreneurialism and managers can be useful in employee selection. Large organizations often seek to promote 49

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innovation who will take on an entrepreneurial role within the firm (intrapreneurs) and move them into key positions. The findings from this study may be used to develop appropriate selection and placement criteria for such decisions (p. 267). Summary The literature review in this chapter gives justification for this quantitative study. The scholarly work describes the traits of entr epreneurs; regions of entrepreneurialism and entrepreneurial community colleges; the foundatio ns of personality testing; an overview of popular personality tests; the le gal implications of using personality testing in employment screening and entrepreneurial traits with respect to the five factor model. Zhao & Seibert (2006) found entr epreneurs to be significantly different from managers on four of the five factors and thus should be included in future resear ch on entrepreneurial characteristics. They also suggest personality characteristics change ove r time and thus altering them is possible through learning. In the following chapter the methodology for th e quantitative study is explained. Chapter 4 is a presentation and analysis of the data for each of the four research questions. The last chapter presents a discussion of the findings, suggestions for future research, and overall implementation possibilities. 50

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Table 2-1. Ph.D.-Level Courses that May Deal with Entrepreneurialism. University Course North Carolina State ELP 720: Cases in educational administration University http://ced.ncsu.edu/elps/el/edd.html University of California262J Entrepreneurial leadership and education: seminar for Los Angeles education and business leaders http://www.registrar.ucla.e du/catalog/catalog05-07-3-23.htm University of Florida EDH6931 Special topics: case studies in higher education http://www.coe.ufl.edu/Leadersh ip/Programs/edleadership.html University of Michigan EDUC 859. Advanced topics in educational administration and policy EDUC 875. Managing change and quality in higher education institutions. http://www.soe.umich.edu/coursede scriptions/800/index.html#ed8 74 University of Texas Entrepreneurialism in the community college lecture, several mentions (pg. 5); see also pg. 9 .0 Entrepreneur http://edadmin.edb.utexas.edu/cclp/blockguide.pdf All websites last acces sed February 2, 2007 Table 2-2. Top 26 Geographic Entrepreneurial Zones Based on Nu mbers of Patents Issued in 1999. Rank City, State # patents Rank City, State # patents #1 San Jose, CA 5664 #14 Rochester, NY 1568 #2 Boston, MA 3806 #15 Houston, TX 1567 #3 Chicago, ILL 2929 #16 Orange County, CA 1473 #4 Los Angeles, CA 2348 #17 Washington, DC 1299 #5 Minneapolis-St. Paul, MN 2181 #18 Seattle, WA 1296 #6 Detroit, MI 1964 #19 Phoenix, AZ 1152 #7 Philadelphia, PA 1849 #20 Newark, NJ 1136 #8 San Diego, CA 1748 #21 Boise City, ID 1093 #9 New York, NY 1704 #22 Middlesex, NJ 1091 #10 San Francisco, CA 1700 #23 Atlanta, GA 1045 #11 Dallas, TX 1644 #24 New Haven, CT 1033 #12 Oakland, CA 1589 #25 Raleigh-Durham, NC 939 #13 Austin, TX 1571 #26 Portland, OR 930 Source: http://www.uspto.gov/web/offices/ac/ ido/oeip/taf/reports.htm#by_geog Last accessed February 18, 2007 51

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Table 2-3. Personality Tests and the Fi ve Factors Model (Great Ideas, 2001) Authors Extraversion Agreeableness ConscientiousEmotional Intellect/ Surgency ness Stability Openness Adler superiority/ social interest social interest social interest superiority striving striving Bakan agency communion communion communion agency Bales dominant social-emotion task task initiative orientation or ientation orientation Bartholomew model of model of other (r) anxiety (r) Block low ego high ego ego ego control control resiliency resiliency Buss & activity impulsivity emotionality Plomin (r) Catell exvia pathemia s uperego adjustment v. independent strength anxiety subdueness Comry extraversion femininity orderliness & emoti onal rebelliousness & activity social stability conformity Costa & extraversion agreeableness conscientiousneuroticism openess McCrae ness (r) Digman beta alpha alpha alpha beta Erikson basic trust Eysenck extraversion pyschoticism pyschoticism neuroticism Fiske confident social c onformity emotional inquiring self-expressadaptability control ion Freud pyschosexual pyschosexual psychosexual development development development Goldberg surgency agreeableness conscientiousemotional intellect ness stability Gough extraversion consensuality control flexibility Guilford social paranoid thinking emotional activity disposition (r) introversion stability Hogan ambition likeability prudence adjustment intellectance Homey moving toward Jackson outgoing, self-protective work dependence aesthetic/ social orientation (r) orientation (r) intellectual leadership Leary control/ affiliation/ dominance love Maslow selfselfactualization actualization McAdams power intimacy intimacy intimacy power motivation motivation motivation motivation motivation r means reverse scored. 52

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Table 2-3 (continued). Personal ity Tests and the Five Factor s Model (Great Ideas, 2001). Authors Extraversion Agreeableness ConscientiousEmotional Intellect/ Surgency ness Stability Openness Myers-Briggs extraversionfeeling v. judging v. intuition v. introversion thinking perception sensing Peabody power love work affect intellect Rank individuation union union union individuation Rogers personal personal growth growth Skinner socialization soci alization socialization Tellegen positive positive constraint negative absorption emotionality emotionality emotionality Watson socialization socialization socialization Wiggins agency communion communion communion agency Zuckerman extraversion pys choticism, neuroticism psychoticism, impulsivity, (r) impulsivity, sensation sensation seeking (r) seeking r means reverse scored. 53

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innovative proactive adaptive self-reliant Low soft Risk High hard Figure 2-1. The linear model of forms of entrep reneurialism in higher ed ucation (Barnett 2005). Academic World -Start-ups Economic World -Education (incubators) -SMEs -Research -Tech. Transfer -Corporations -Administration centers -Banks -science parks -other economic structures Figure 2-2. Intersection of the academic and economic worlds (Zahara & Gibert, 2005, p. 35). introversion/ extraversion neuroticism conscientiousness agreeableness openness to experience Figure 2-3. The Five Fact or Model structure. 54

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Assessment Method Prediction (1.00 = perfect) References 0.10 Unstructured interview 0.25 Structured interview 0.35 Personality questionnaire 0.40 Work sample tests 0.46 Assessment center appr oach scores 0.60 Figure 2-4. Predictors of job success by assessment method (Bain and Mabey, 1999). Figure 2-5. Where do entrepreneurs get their ideas? (Bhide, 1994) 1) Replicated or modified an idea encountered through previous employ ment. 2) Discovered serendipitously. 3) Swept into the PC revolution. 4) Disc overed through systematic research for opportunities. Activities to build m i Information and and sustain network services being contacts provided by network partners Structure of the m i existing network m i -time spent on -frequency of new networking -number of network information being -frequency of partners provided Communications -diversity of the network -extent of support with actual and (family, fr iends, others) from network potential network -density of the network partners partners (contacts between network partners) Figure 2-6. Measures for entrepre neurial networks (Witt, 2004, p. 395). 55

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Neuroticism Vulnerability Self-confidence High anxiety Calm -0.5 0.37 0 +0.5 Hostile Even-tempered Depression Relaxed E M Self-conscious Impulsiveness Figure 2-7. The relationship betwee n entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on neuroticism. Extraversion Prefer alone time Cheerful Reserved -0.5 0 +0.22 +0.5 Like people & large Quiet groups Independent M E Seek excitement & stimulation Figure 2-8. The relationship betwee n entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on extraversion. Openness Conventional Creative Narrow in interests -0.5 0 +.36+0.5 Innovative Unanalytical Imaginative M E Reflective Untraditional Figure 2-9. The relationship betwee n entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on openness. 56

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Agreeableness Trusting Manipulative Forgiving Self-centered -0.5 0.16 0 +0.5 Caring Suspicious Altruistic Ruthless E M Gullible Figure 2-10. The relationship betw een entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on agreeableness. Conscientiousness Achievementmotivational -0.5 0 +.45+0.5 Dependability Organized M E Deliberate Methodological Figure 2-11. The relationship betw een entrepreneurs (E) and managers (M), as it pertains to the Five Factors Model category on conscientiousness. 57

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CHAPTER 3 RESEARCH METHODOLOGY This chapter explains the research methodology used in this study. In this chapter the research purpose, problem, design, instrument, population, data collection and data analysis methods are described and explained. Purpose of the Study The purpose of this study was to focus on the first two critical issues identified in the 2006 Community College Futures Assembly: innovation and entrepreneurialism is a must for survival and hire the right people, keep them, and keep the right people. As indicated, since more than 70% of community college administrators will retire within the next five years, there is little margin for error during the hiring process, especially in an environment requiring entrepreneurialism or entrepreneur ial traits or characteristics. Th is study attempted to do this by: examining if entrepreneurialism can be learned, examining if entrepreneurial leaders are more likely to be found in certain areas of the c ountry, and examining if the WAVE adequately measures the personality characteristics of entrepreneurs. It is hoped this research will be able to assist decision-making in the community college administrative hiring process by pin-pointing the key characteristics of entrepreneurs for use during the screening of potential candidates in their applicati ons, interviews, and other hiring instruments. Research Problem As indicated, since more than 70% of commun ity college administrators will retire within the next five years, and there is a plethora of administrators that will need to be hired. There is, thus, very little margin for erro r during the hiring process, especi ally in those positions requiring entrepreneurial characteristics. 58

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Research Questions Drucker (1985) and others from the literature review have said entrepreneurialism can be learned however no research can be found to have empirically substantiated those claims. The first research question is an exploration of this relationship: Can entrepreneurialism be learned? In other words, what is the relationship between the level of entrepreneurialism (as a cognitive application of personality charac teristics) of community college administrators with doctorate degrees and community college administrators wit hout doctorate degrees? The literature has also shown entrepreneurialism has been linked and may be more prevalent in certain geographic areas of the country than in others (Ryan, 2004). Wh at is the relationship between the level of entrepreneurialism and non-entrepreneuria lism with respect to economic region? There is little research linking personality trait to cognitive application, even fewer studies on entrepreneurialism as a personality tra it with cognitive applications and no mention of any research on personality traits of community college administrators, entrepreneurialism as a personality trait in educators, nor cognitive appl ication of either in higher education. Does the WAVE explain the factors i nvolved with measuring entrepreneurialism as a cognitive application for community college administrators? Research Hypotheses H 1 : Those community college administrato rs with doctorate degrees will have significantly higher mean scores for entrepreneurialism than those community college administrators without doctorate degrees. H 0 : They will not exhibit any significant difference. H 2 : The community colleges in areas identifi ed as entrepreneurial economic regions will have administrators who have significantly higher levels of entrepreneurialism than those community college administrators who are not in entrepreneurial economic regions. H 0 : They will not exhibit any significant difference. 59

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H 3 : The factors of the WAVE will contain the appropriate factors to be used as a tool for measuring entrepreneurialism as a cognitive application of personality traits of community college administrators. H 0 : The WAVE will not. Research Design Survey research will be administered th rough the use of a questionnaire to measure personality characteristics of co mmunity college administrators. Statistical analysis, including descriptive statistics, analysis of variance, and appropriate follow-up stat istical procedures, will be used to determine if entrepreneurialism can be learned, where entrepreneurialism is more likely to be found, and if the WAVE is a suit able tool for measuri ng entrepreneurialism. Research Instrument As mentioned in the literatur e review, there are more than 2,500 different personality tests available today. Briggs (1992) said in considering which measure to adopt for a particular research project, one must understand its stre ngths and weaknesses ( p. 256). Briggs (1992) concluded when choosing an instrument for person ality research one should be careful to balance optimization of results with costs and limitations of the instrument. Thus far we have seen a variety of debates of the use of personality tests with subsequent evolutions, as you would expect, having attempted to remedy the shortcomi ngs of their predecessors. The third generation of the WAVE personality test, developed by Saville Consulting, Ltd., continues trend by combining the features of generations of persona lity testing into an instrument for assessing personality traits, while being h eavily grounded in research and able to withstand the debates and criticisms of personality testi ng. The robustness of the WAVE a nd the convenience of having the instrument available for research were the reason s for selecting the WAVE for use in this study. The WAVE is a behavioral questionnaire deve loped for use in selecting, developing, and establishing career paths in business (Saville & Holdsw orth Ltd., 1996 (as cited in 60

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Campbell & Kachik, 2002)). Dr. Peter Saville, wi nner of the lifetime achievement award from the British Psychological Association for his tirel ess efforts in developing personality testing created the 3 rd version of his instrument name d the WAVE (Saville, 2006b). His 20 th Century personality testing used: separate measures fo r personality, motivation, competency, and culture; they under-utilized technology; and had a poor interface between individual and corporate data. The third-generation WAVE test is founded upon, what Saville calls, the 21 st Century personality testing criteria: the WAVE is a comprehe nsive assessment model; understanding of both motivation and talent; a measure for the culture of both the workplace and person; fully exploits technology; and focuses on poten tial areas for distortion (S aville, 2006b). The WAVE is: an integrated suite of assessment tools offering sophisticated indi vidual and corporate diagnostics that allows you to get high defin ition quality, spot talent and potential more accurately, uncover leadership and team development competencies, identify fresh insights in coaching feedback, enhance retentio n by assessing person-jo b and culture fit, and do all of this quickly while reducing the risk of candidate ch eating (Saville, 2006a). The WAVE is a personality test, grounded in the th eories of the Five Factors Model, to measure 108-facets ( Figure 3-1 ) using 9-point Likert-type normative scale items (very strongly disagree; strongly disagree; disagree; slightly disagree; unsure; slightly agre e; agree; strongly agree; very strongly agree). The WAVE is based upon four clusters, instead of five, including thought, influence, adaptability and delivery. The 4 cluste rs each contain 3 sections each section contains 3 dimensions, and each dimension contains 3 face ts. During the test each facet will be presented two to three times. The repetition allows for testi ng for self-reporting bias and acquiescence bias. Saville uses normative items because they are independent measure scales, people can freely choose responses, and fact or analysis can be easily in terpreted. After six items are answered ipsative tes ting further forces the respondent to select the highest and lowest items of each grouping until a rank order is achieved for the grouping. According to Saville the 61

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advantages of ipsative ranking ar e ipsative ranking forces the re spondent to rank characteristics which are more or less important than others controls certain type s of normative response distortion, and is more difficult to fake than nor mative. The disadvantages of ipsative ranking are the interdependence of responses can distort profiles, particularly with few scales the rankings force correlations between scales down, and the use of standard statis tical techniques are not accurate however these cr iticisms are largely dismissed by authorities like Cronbach (Saville, 2006b). Furthermore, the disadvantages for the earlier versions of the WAVE, according to Saville, are the extremity response bias, acquies cence bias, central tende ncy, socially desirable response bias, and raised correlations betweens scal es but these all have been remedied in the latest version of the WAVE (Saville, 2006b). The proprietary nature of the WAVE precludes inclusion of the instrument here for scientific analysis. The questionnaire takes about 30-45 minutes to fi nish on average, after which there is an array of reports available to the respondent some of which include, but are not limited to: the personal report, the expert report and the entrepreneurial potential report. The personal report is generated at no charge to provide feedback for the candidate. In a two-to-three page report the individual is given a profile ch art, some narrative statements, a nd is intended to provide easy understanding of the report. The Expert Report The Expert Report provides rich detail for th e human resources professional to support talent management decision making. The Expert Report includes an Executive Summary Profile, a Psychometric Profile overview, a Psychometric Pr ofile, normative-ipsative splits, motive-talent splits, predicted culture/e nvironment fits, and a competency potential profile. The executive summary report within the Expert Report shows the scores for the four clusters (thought, influence, adaptability, and delivery) and 12 secti ons (vision, judgment, 62

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evaluation, leadership, impact, comm unication, support, resilience, fl exibility, structure, drive, and implementation). The Psychometric Profile fu rther breaks down the four clusters and 12 sections into 36 dimensions (inventive, abstract, strategic, insightful, practically minded, learning oriented, analytical, factual, rational, purposeful, directing, empowering, convincing, challenging, articulate, self-promoting, inter active, engaging, involving, attentive, accepting, resolving, self-assured, composed, receptive, posi tive, change-oriented, organized, principled, activity-oriented, dynamic, striving, enterprising, meticulous, reliab le, and compliant). The next portion of the expert report is predicted culture /environment fit of the candidate. This is the portion of the report which highli ghts the aspects of the culture, job, and environment which are likely to enhance or inhibit the candidates success. The final porti on of the Expert Report is the competency profile report which predicts a persons potential on 12 competency items (achieving success, adjusting to change, communicating with people, creating innovation, evaluating problems, executing assignments, making judgments, presenting information, projecting confidence, providing le adership, providing support, a nd structuring tasks). Each of these items is measured against scores from prev iously tested subjects in the same country and given a percentage ranking agains t the pool. For example a report may show an individual scored in the top 1% for a competency item with respect to the pool. Recall at this time Saville, Ltd., has agreed to allow the researcher to use this in strument pro bono for the purposes of scientific research and to build the normative pool of da ta for future testing of higher education administrators. Several features of the WAVE delineate it from other contemporary psychometric tests including the ratings acq uiescence scoring, consistency of rank ings scoring, motive-talent split agreement scoring, and normative-ipsative agreem ent scoring. During the test the respondent 63

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will be asked the same facet items several times. From this the ratings acquiescence scoring and consistency of rankings scoring is generated. First, the ratings ac quiescence is a measure of how generously or harshly the respondent has been du ring the personality test Next, the consistency of rankings similarly shows how consistently the respondent ha s reported on similar items. The Motive-Talent split identifies what the candidate sees as things they are good at, are able to do, or is likely to be driven to do. This also help s to predict sustained performance and uncover areas of underperformance. The report shows an M fo r the motive, or what motivates the person whereas the T shows the level of talent fo r the person on that item (hence, they are underperforming their capabilities. This will identify an area for growth potential). The normative-ipsative splits helps to provide a rank ordering of the candidates key attributes. This combination helps to control for distortion more than any other combination (Saville, 2006b). This split is used to see where the candidate wo uld like to be, where they think they are, and what the candidate is most likely to do when the chips are dow n. Where a 3 or more sten unit difference in normative-ipsative measures is found is a good indicator of an area of interest to the test interpreter. This may be indicative of some faking, poten tial exaggeration, or not fully concentrating on the test. Where the ipsative is 3 stens higher than the normative the candidate may be overly modest, or especi ally hard on self-criticism. The Entrepreneurial Potential Summary Report Finally, the Entrepreneurial Report is useful for identifying sources of entrepreneurial talent in the organization or individual based upon a cognitive assessment of the personality traits. The first portion is an Entrepreneurial Po tential Summary which is intended to provide an overview of the scores. The summary contains scor es for getting in the zone, seeing possibilities, creating superior opportunities, staying in the zone, opening up to the world, and building capability. The second portion is the Entrepreneur ial Potential Profile wh ich provides a more in64

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depth analysis. The potential pr ofile includes achievement dr ive, compelling vision, energy, action-oriented, big picture, options thinking, savvy, problem seeking, delighting customers, focus, positive mindset, self-determining, pe rsistence, expressing passion, purposeful networking, creating partnerships building up the team, experi ential learning, and staying on track. Instrument Validity and Reliability The test-retest reliability coefficients for the normative WAVE scales and items, based on a sample of 112 participan ts, ranged from 0.71 to 0.91 with a median of 0.81 ( Table 3-1 ). Mean inter-item correlations of .29 to .40 have been said to be ample indications of homogeneity with alpha coefficients between .48 and .61 (Briggs, 1992). Single dimension validity and composite cross validity ranged from 0.09 to 0.78 with a median of 0.56 ( Table 3-2 ). Dimension validity is the correlation between a single Professional Styles scale dimension (weighted combination of ipsativ e and normative scores) with the matched work performance criterion. Total sample ma tched is N = 556-658 (sample size varied due to no evidence option on criterion ratings). Cross validate d is the correlation of the composite regression equation from initial sa mple on hold out sample based on a hold out sample of N = 252-316. All validi ties correlated for attenuation based on the reliability of the criteria (based on 236 pairs of criterion ratings). No furt her correlations were applied (e. g., restriction of range, predictor unreliabi lity). The composite validity of each of the two Professional Styles forms in relation to overall job proficiency is 0.34 and 0.42 (N = 325). The composite validity of each of the tw o Professional Styles forms in establishing external ratings of potential for promotion is 0.54 and 0.64 (N = 324) (Saville, 2006a). The Saville WAVE personality test has also been correlated agai nst the 16PF, the Myers Briggs Type Indicator, the Gordon Personal Profile, a nd the DISC. Results of construct validation studies suggest the Saville WAVE is valid a nd measures what it is intending to measure (Campbell & Kachik, 2002; Saville & Holdsworth, 1996). Specific item correlations and general information about the WAVE items is included in Appendix A. 65

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The WAVE was chosen as the research inst rument because it, more than any other instrument, has shown consistent validity and re liability over time, has shown its resilience to criticisms of personality test ing by adapting and overcoming issues, has used an empiricallyderived construction of scales using self-ratings, observer ratings, supervised delivery, unsupervised delivery, and has been validated for use in a variety of cu ltures and languages. For these reasons the WAVE should mer it the label as being a robust instrument worthy of selection herein. Data Collection Train-the-trainer sessions were held in Jacksonville, Florida in July and October 2006 by Saville Consulting, Ltd. Respondents answered the online questionnaire between August and December 2006 as part of a national project to develop Unites States norms for community college leadership. Fifteen community colleges in 12 states were invited to participate in the norming process as well as several governi ng and oversight board of community college business and management. Respondents were provid ed basic results by personal report, expert report, and entrepreneurial potential report. The pa rticipants were treated in accordance with the ethical standards of the American Psychological A ssociation and the participants were assured of anonymity in the reporting phases. In the interest of social science resear ch Saville Consulting, Ltd., agreed to release a small subs et of the collected data for disse rtation research in return for first right of viewing after defense. Population The final sample includes community college presidents, board of trustees, and senior leadership from Arizona, Indiana, and North Carolina. Two commun ity college oversight boards, their senior leadership, and th eir national members (from various community colleges) are also included. 66

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These groups together comprised an overall population of 168 respondents. Within this the population contained 154 memb ers from community colleges and 64 association board members for community college oversight; 40 memb ers with doctorate degr ees (Ph.D. or Ed.D.) and 148 without; and the population in cluded 33 members within sixty miles of areas identified entrepreneurial economic regions an d 135 members outside of them. Data Analysis The first hypothesis analyzed by grouping thos e individuals in the sample who have a doctorate degree and comparing th em to those who do not having a doctorate degree with respect to their attributes of entrepre neurialism. Next a two-way mixed measures analysis of variance (ANOVA) was used between the means for the group with the doctorates and those without doctorates using the data from the executive su mmary, psychometric profile and entrepreneurial potential reports. Scheffes Post Hoc procedure was used for individual analysis. The second hypothesis was tested in the same manner as the first hypothesis except instead of separating the sample by those with doctorate degrees and t hose without doctorate degrees the sample was separated by those community colleges within the top 26 entrepreneurial economic regions and those not within the top 26 entrepreneurial economic regions. This is grounded within the theoretical f oundations espoused by Ryan (2004) and Shattock (2005) in the literature review. Next a two-way mixed measur es analysis of variance (ANOVA) was used between the means for the group in the entrepreneurial zone s and those not within the entrepreneurial zones using the data from the executive summary, psychometric profile and entrepreneurial potential reports. Scheffes Post Hoc procedure was used for individual analysis. The third hypothesis was tested using factor analysis on the entrepreneurial potential summary and entrepreneurial prof ile summary scales. An alpha level of 0.05 was used for all statistical tests. The goal of factor analysis is to identif y the level of homogeneity and 67

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unidimensionality of the factors until the point is reached where fu rther iterations yield no further distinctions (Bernard, Walsh & Mills, 2005; Montag & Levin, 1995; Briggs, 1992). McAdams (1992) has said a common criticism of factor-analytic studies of pe rsonality traits is that they are arbitrary and atheore tical. It is well-known that while fa ctor analysis is a sophisticated quantitative tool, a great deal of subjective and sometimes arb itrary decision making goes into (a) the choice of items, (b) the choice of fact or-analytic procedures and rotations, and (c) the labeling of obtained factors (p. 334). The choice of factor analysis also allowed for comparison to similar studies using factor analysis to de termine the validity and reliability with other instruments. 68

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Table 3-1. Reliability summary for Saville Consulting WAVE. Alternate form normative, ipsative, and combined (N = 153). Normativ e test-retest reliabili ty on invited access (N = 112) Profession Styles Alternate Alternate Alternate Test-Rest Dimension Form Form Form Normative Normative Ipsative Combined Inventive 0.91 0.87 0.91 0.88 Abstract 0.85 0.77 0.83 0.76 Strategic 0.84 0.79 0.84 0.73 Insightful 0.82 0.72 0.79 0.76 Pragmatic 0.85 0.83 0.86 0.81 Learning Oriented 0.86 0.84 0.87 0.78 Analytical 0.85 0.79 0.84 0.73 Factual 0.79 0.79 0.81 0.77 Rational 0.91 0.88 0.92 0.82 Purposeful 0.87 0.80 0.87 0.71 Directing 0.89 0.84 0.89 0.83 Empowering 0.90 0.85 0.89 0.80 Convincing 0.85 0.78 0.84 0.74 Challenging 0.86 0.81 0.86 0.86 Articulate 0.91 0.86 0.91 0.86 Self-promoting 0.89 0.84 0.89 0.80 Interactive 0.90 0.85 0.90 0.89 Engaging 0.87 0.83 0.87 0.79 Involving 0.79 0.81 0.81 0.74 Attentive 0.83 0.85 0.86 0.71 Accepting 0.78 0.82 0.81 0.75 Resolving 0.88 0.84 0.88 0.80 Self-assured 0.86 0.78 0.85 0.76 Composed 0.90 0.84 0.89 0.72 Receptive 0.81 0.73 0.78 0.80 Positive 0.85 0.81 0.85 0.82 Change Oriented 0.85 0.82 0.86 0.76 Organized 0.86 0.88 0.88 0.77 Principled 0.81 0.77 0.81 0.80 Activity Oriented 0.90 0.86 0.89 0.78 Dynamic 0.87 0.81 0.87 0.78 Striving 0.86 0.79 0.85 0.80 Enterprising 0.93 0.89 0.93 0.91 Meticulous 0.87 0.87 0.89 0.80 Reliable 0.89 0.89 0.91 0.83 Compliant 0.89 0.90 0.91 0.83 69

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Table 3-2. Single dimension and co mposite validities (Saville, 2006a) Criterion Single Single Cross Cross Dimension Dimension Validated Validated Validity Validity Composite Composite IA SA Validity IA Validity SA Generating Ideas 0.42 0.44 0.44 0.41 Exploring Possibilities 0.21 0.36 0.44 0.47 Developing Strategies 0.54 0.56 0.68 0.68 Providing Insights NS 0.20 0.42 0.38 Implementing Practical Solutions NS NS 0.09 0.29 Developing Expertise 0.19 0.19 0.35 0.38 Analyzing Situations 0.26 0.34 0.30 0.36 Documenting Facts 0.29 0.27 0.29 0.27 Interpreting Data 0.46 0.42 0.44 0.62 Making Decisions 0.48 0.50 0.64 0.64 Leading People 0.68 0.66 0.77 0.70 Providing Inspiration 0.62 0.64 0.64 0.64 Convincing People 0.26 0.26 0.56 0.60 Challenging Ideas 0.47 0.49 0.45 0.47 Articulating Information 0.66 0.60 0.68 0.68 Impressing People 0.32 0.30 0.56 0.45 Developing Relationships 0.42 0.50 0.64 0.66 Establishing Rapport 0.63 0.57 0.71 0.67 Team Working 0.32 0.32 0.46 0.40 Understanding People 0.35 0.31 0.47 0.40 Valuing Individuals 0.34 0.28 0.46 0.44 Resolving Conflict 0.38 0.38 0.48 0.40 Conveying Self-Confidence 0.40 0.34 0.66 0.78 Coping with Pressure 0.36 0.34 0.32 0.30 Inviting Feedback 0.26 0.22 0.40 0.32 Thinking Positively 0.40 0.38 0.42 0.48 Embracing Change 0.42 0.48 0.42 0.34 Organizing Resources 0.32 0.38 0.22 0.42 Upholding Standards 0.21 0.21 0.20 0.16 Completing Tasks 0.26 0.31 0.34 0.41 Taking Action 0.54 0.56 0.56 0.54 Pursuing Goals 0.28 0.42 0.44 0.46 Tackling Business Challenges 0.42 0.38 0.48 0.45 Checking Details 0.39 0.31 0.24 0.23 Meeting Timescales 0.45 0.43 0.41 0.43 Following Procedures 0.26 0.24 0.44 0.14 NS-not scored 70

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4 clusters (thought, infl uence, adaptability, delivery) 12 sections 36 dimensions 108 facets 4 Clusters Yields 12 sections : Thought ( vision, judgment, evaluation ) Influence ( leadership, impact, communication ) Adaptability ( support, resilience, flexibility ) Delivery ( structure, drive, implementation ) Figure 3-1. Theoretical structure of the WAVE. 71

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CHAPTER 4 RESULTS In this chapter we will reveal the results of the data gathering and analysis process as described in chapter three. The results for each hypothesis will be shown in order. Chapter five will be a discussion of those results and their a pplicability to community college administrators. Aggregate Data-Descriptive Statistics For the aggregate groups the mean, standa rd deviation, skewness and kurtosis are presented in Appendix B The aggregate data appears to be distributed normally with no large deviations for skewness or kurtosi s. The data also suggests the respondents are overall slightly more positive in self-ratings than many, (M = 6.79, SD = 1.86); consistent in rank ordering of characteristics (M = 5.63, SD = 1.82); overall the degree of alignment between motive and talent scores are typical of most people (M = 5.24, SD = 1.90); and ove rall the degree of alignment between normative and ipsative scores is ty pical of most people (M = 4.92, SD = 2.09). Research Hypothesis One This hypothesis centered on the general re search question of whether or not entrepreneurialism can be learned. H 1 : Those community college administrato rs with doctorate degrees will have significantly higher entrepreneurial personal ity characteristics than those community college administrators w ithout doctorate degrees. H 0 : They will not exhibit any significant difference. The data was divided into two samples, one cont aining those individuals w ho have a doctorate (n = 40) and those who do not (n = 128). The data for this hypothesis appears to be distributed normally with no large deviations for skewne ss or kurtosis. The data also suggests the respondents are overall more posit ive in self-ratings than many; consistent in rank ordering of characteristics; overall the degree of alignment between motive and talent scores are typical of most people; and overall the degree of alignmen t between normative and ipsative scores is 72

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typical of most people ( Table 4-1 ). There is a significant differe nce for ratings acquiescence for those with a doctorate degree and those without, t(168) = 1.90, p = 0.03 (one-tailed) and for normative-ipsative agreement, t(168) = -3.11, p < 0.000 (one-tailed). A 6x2 two-way mixed method analysis of variance (ANOVA) was calcu lated to account for both within and between group variance and to seek support for the hypoth esis with respect to the entrepreneurial potential summary results. With an alpha le vel of 0.05 significance was found to support the research hypothesis of being able to learn entrepreneurialism from the entrepreneurial potential summary, F(6, 1001) = 11.63, p < 0.001. A 21x2 two-way mixed method analysis of variance (ANOVA) was calculated to account for both with in and between group variance and to seek support for the hypothesis with respect to the entr epreneurial potential pr ofile results. With an alpha level of 0.05 significance was found to suppor t the research hypothesis of being able to learn entrepreneurialism, from the entrep reneurial potential summary, F(21, 3506) = 13.367, p < 0.001. Unpaired one-tail students t-tests were used to determine significance of the individual items on the entrepreneurial potential summary ( Table 4-2 ) and entrepreneurial potential profile scores ( Table 4-3 ). Finally, Fishers Least Significan t Difference (LSD) method was used to search for significance in the interactions betw een the means for the entrepreneurial potential summary report and for the entrepre neurial potential profile report ( Appendix C ). Research Hypothesis Two This hypothesis centered on the general re search question on discerning whether entrepreneurialism is more prevalent in certain areas of the country whic h have been labeled as entrepreneurial economic regions. H 2 : The community colleges in areas identifi ed as entrepreneurial economic regions will have administrators who have a significantly higher level of entrepreneurialism than those community college administrators who are not in entrepreneurial economic regions. H 0 : They will not exhibit any significant difference. 73

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The data was divided into two samples, one containing those indi viduals who in the entrepreneurial economic regions (n = 33) and those who are not (n = 135). The data for this hypothesis appears to be distributed normally with no large deviations for skewness or kurtosis. The data also suggests the respondents are overall slightly more positive in self-ratings than many; fairly consistent in ra nk ordering of characteristics; overall the degree of alignment between motive and talent scores are typical of most people; and overall the degree of alignment between normative and ipsative scores is typical of most people ( Table 4-4 ). A 6x2 two-way mixed method analysis of vari ance (ANOVA) was calculated to account for both within and between group variance and to s eek support for the hypothesis with respect to the entrepreneurial potential summary results. With an alpha le vel of 0.05 significance was found to support the research hypothesis of entrepre neurs being more likely to be found in entrepreneurial economic regions, F(6, 1001) = 8.563, p <0.001. A 21x2 two-way mixed method analysis of variance (ANOVA) was calculated to account for both with in and between group variance and to seek support for the hypothesis with respect to the entr epreneurial potential pr ofile results. With an alpha level of 0.05 significance was found to support the research hypothesis of entrepreneurs being more likely to be found in entrep reneurial economic regions, F(21, 3506) = 11.612, p <0.001. Unpaired one-tail students t-tests were used to determine significance of the individual items on the entrepreneurial potential summary ( Table 4-5 ) and entrepreneurial potential profile scores ( Table 4-6 ). Finally, Fishers least significant di fference method was used to search for significance in the interactions between the m eans for the entrepreneurial potential summary report and for the entrepreneur ial potential profile report ( Appendix C ). 74

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Research Hypothesis Three This hypothesis centered on the general research question of whether or not the WAVE instrument adequately measures the appropriate factors with resp ect to entrepreneurialism of community college administrators. H 3 : The factors of the WAVE will contain the appropriate factors to be used as a tool for measuring entrepreneurialism as a cognitive application of personality traits of community college administrators. H 0 : The WAVE will not. Factor analysis was performed for this hypothesis. Table 4-7 shows the Pearson correlation matrix for the six variables in the entrepreneur ial potential summary. Cronbachs alpha for the six factor scale is 0.90. The Eigenvalues are shown in Table 4-8 and the Scree plot is shown in Figure 4-1 Factor analysis was performed for this hypothesis. Table 4-9 shows the Pearson correlation matrix for the eighteen variables in the entrepreneurial potential summary. Cronbachs alpha for the six factor scal e is 0.92. The Eigenvalues are shown in Table 4-10 and the Scree plot is shown in Figure 4-2 Factor pattern coefficient plot ( Figure 4-3 ) and coefficients are also shown ( Table 4-11 ). In this chapter the results of the study were presented. In the next chapter the discussion of these results and suggestions for future research will conclude the paper. 75

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Table 4-1. Unpaired Students t-Test results for research H ypothesis One for the descriptive statistics. Executive Summary Item Ph.D.s NonDiff Students p Mean Mean Unpr. T Ratings acquiescence 7.28 6.64 0.63 1.90 0.03* Consistency of rankings 5.55 5.65 -0.10 -0.30 0.38 Motive-talent agreement 5.08 5.29 -0.21 -0.62 0.27 Normative-ipsative agreement 4.05 5.20 -1.15 -3.11 0.00** (* p < 0.05, ** p < 0.01). Table 4-2. Unpaired Student s t-Test results for Research Hypothesis One for the Entrepreneurial Potential Summary Report. Entrepreneurial Potential Item Ph.D.s NonDiff Students p Mean Mean Unpr. T Getting in the zone 7.30 6.89 0.41 1.25 0.11 Seeing possibilities 8.00 7.33 0.67 2.23 0.01* Creating superior opportunities 7.15 6.65 0.50 1.56 0.06 Staying in the zone 7.48 6.77 0.70 2.41 0.01* Opening up to the world 6.65 6.02 0.63 1.92 0.03* Building capacity 7.03 6.65 0.38 1.19 0.12 (* p < 0.05, ** p < 0.01) 76

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Table 4-3. Unpaired Student s t-Test results for Research Hypothesis One for the Entrepreneurial Potential Profile Report. Entrepreneurial Potential Ph.D.s NonDiff Students p Profile Item Mean Mean Unpr. T Achieving drive 7.48 7.23 0.25 0.80 0.21 Compelling vision 6.83 6.11 0.72 2.37 0.01* Energy 7.40 6.78 0.62 1.86 0.03* Action-oriented 6.48 6.52 -0.05 -0.14 0.45 Big picture 8.10 7.29 0.81 2.67 0.00** Options thinking 7.38 6.63 0.75 2.54 0.01* Savvy 7.35 7.20 0.15 0.49 0.31 Problem seeking 6.48 5.64 0.83 2.42 0.01* Synthesis 6.75 6.52 0.23 0.68 0.25 Problem solving 6.75 6.55 0.20 0.68 0.25 Delighting customers 5.80 5.76 0.04 0.12 0.45 Focus 7.13 6.66 0.46 1.47 0.07 Positive mindset 7.03 6.50 0.53 1.69 0.05* Self-determining 7.13 6.62 0.51 1.64 0.05* Persistence 7.05 6.36 0.69 2.13 0.02* Expressing passion 6.80 5.96 0.84 2.74 0.00** Purposeful networking 6.08 5.56 0.51 1.47 0.07 Creating partnerships 6.63 6.23 0.40 1.19 0.12 Building up the team 7.30 6.13 1.18 3.68 0.00** Experiential learning 5.53 6.30 -0.77 -2.65 0.00** Staying on track 6.65 6.76 -0.11 -0.33 0.37 (* p < 0.05, ** p < 0.01) Table 4-4. Unpaired Students t-Test Results for Research H ypothesis One for the descriptive statistics. Executive Summary ENTR.s Non-mean Diff. Students p mean Unpr. T Ratings acquiescence 6.88 6.77 0.11 0.30 0.38 Consistency of rankings 5.82 5.58 0.24 0.68 0.25 Motive-talent agreement 4.91 5.32 -0.41 -1.11 0.13 Normative-ipsative agreement 4.94 4.92 0.02 0.05 0.48 (* p < 0.05, ** p < 0.01) 77

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Table 4-5. Unpaired Student s t-Test results for Research Hypothesis Two for the Entrepreneurial Potential Summary Report Item ENTR.s Nonmean Diff. Students p mean Unpr. T Getting in the zone 7.06 6.97 0.09 0.26 0.40 Seeing possibilities 7.73 7.43 0.30 0.91 0.18 Creating superior opportunities 6.39 6.86 -0.47 -1.35 0.09 Staying in the zone 7.03 6.92 0.11 0.35 0.36 Opening up to the world 6.45 6.10 0.36 1.00 0.16 Building capability 7.03 6.67 0.36 1.07 0.14 (* p < 0.05, ** p < 0.01) Table 4-6. Unpaired Student s t-Test results for Research Hypothesis Two for the Entrepreneurial Potential Profile Report. Item ENTR.s Nonmean Diff. Students p mean Unpr. T Achieving drive 7.33 7.27 0.06 0.18 0.43 Compelling vision 6.55 6.21 0.33 1.01 0.16 Energy 6.82 6.96 -0.14 -0.38 0.35 Action-oriented 6.61 6.49 0.12 0.31 0.38 Big picture 7.76 7.41 0.34 1.03 0.15 Options thinking 7.00 6.76 0.24 0.76 0.22 Savvy 7.21 7.24 -0.02 -0.07 0.47 Problem seeking 5.91 5.82 0.09 0.23 0.41 Synthesis 6.06 6.70 -0.64 -1.82 0.04* Problem solving 6.42 6.64 -0.22 -0.72 0.24 Delighting customers 5.64 5.80 -0.16 -0.45 0.33 Focus 6.73 6.79 -0.06 -0.17 0.43 Positive mindset 6.67 6.61 0.05 0.15 0.44 Self-determining 6.85 6.71 0.14 0.41 0.34 Persistence 6.39 6.56 -0.16 -0.46 0.32 Expressing passion 6.85 5.99 0.86 2.60 0.01* Purposeful networking 6.03 5.60 0.43 1.15 0.13 Creating partnerships 6.21 6.35 -0.14 -0.38 0.35 Building up the team 7.09 6.24 0.85 2.44 0.01* Experiential learning 5.85 6.18 -0.33 -1.04 0.15 Staying on track 6.76 6.73 0.03 0.09 0.46 (* p < 0.05, ** p < 0.01) 78

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79 Table 4-7. Pearson Correlation matrix for the Entrepreneurial Potential Summ ary variables. Entrepreneurial Potential Summary Item GIZ SP CSO SITZ OTW BC Getting in the zone (GIZ) 1.00* Seeing possibilities (SP) 0.68* 1.00* Creating superior opportunities (CSO) 0.61* 0.63* 1.00* Staying in the zone (SITZ) 0.78* 0.61* 0.55* 1.00* Opening up to the world (OTW) 0.60* 0.48* 0.45* 0.59* 1.00* Building capability (BC) 0.67* 0.59* 0.56* 0.67* 0.48* 1.00* (* p < 0.05, ** p < 0.01). Table 4-8. Eigenvalues for the Entrepre neurial Potential Summary Variables. F1 F2 F3 Eigenvalue 3.62 0.15 0.03 Variability (%) 60.43 2.42 0.44 Cumulative % 60.43 62.85 63.29

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80 Table 4-9. Pearson Correlation Matrix for the Entrepreneurial Potential Profile Variables. (* p < 0.05) Legend: achievement drive (AD); compelling vision (CV); energy (EN); action orie nted (AO); big picture (BP) ; options thinking (OT); savvy (SA); problem seeking (PS); synthesis (SYN); problem solving (PRS); delighting customers (DC); focus (FO); positive mindset (PM); self-determining (SD); pe rsistence (PER); expressi ng passion (EP); purposeful networking (PN); creating partnerships (CP); building up the team (BUT); experiential learning (EL); and staying on track (SOT). EPP AD CV EN AO BP OT SA PS SY N PRS DC FO PM SD PER EP PN AD 1.00* CV 0.51* 1.00* EN 0.66* 0.53* 1.00* AO 0.56* 0.42* 0.62* 1.00* BP 0.44* 0.59* 0.45* 0.40* 1.00* OT 0.27* 0.61* 0.34* 0.14 0.61* 1.00* SA 0.59* 0.50* 0.51* 0.56* 0.44* 0.33* 1.00* PS 0.29* 0.40* 0.44* 0.12 0.18* 0.35* 0.24* 1.00* SYN 0.23* 0.32* 0.26* 0.19* 0.49* 0.42* 0.27* 0.09 1.00* PRS 0.59* 0.51* 0.60* 0.46* 0.53* 0.47* 0.55* 0.23* 0.51* 1.00* DC 0.23* 0.06 0.02 0.17* 0.02 -.19* 0.13 -.23* 0.08 0.05 1.00* FO 0.63* 0.52* 0.51* 0.51* 0.49* 0.33* 0.55* 0.12 0.25* 0.46* 0.33* 1.00* PM 0.42* 0.27* 0.60* 0.36* 0.33* 0.21* 0.32* 0.45* 0.13 0.25* -0.05 0.20* 1.00* SD 0.53* 0.55* 0.47* 0.43* 0.40* 0.36* 0.56* 0.26* 0.25* 0.38* 0.09 0.49* 0.30* 1.00* PER 0.50* 0.33* 0.45* 0.43* 0.32* 0.12 0.45* 0.27* 0.13 0.32* 0.33* 0.50* 0.42* 0.37* 1.00* EP 0.47* 0.63* 0.43* 0.27* 0.33* 0.44* 0.45* 0.60* 0.11 0.32* -0.14 0.35* 0.38* 0.50* 0.32* 1.00* PN 0.33* 0.36* 0.28* 0.10 0.11 0.25* 0.26* 0.54* -0.01 0.23* -0.14 0.13 0.33* 0.22* 0.25* 0.58* 1.00* CP 0.70* 0.58* 0.58* 0.41* 0.33* 0.37* 0.57* 0.48* 0.16* 0.55* 0.06 0.51* 0.34* 0.56* 0.46* 0.63* 0.53* BUT 0.40* 0.40* 0.42* 0.18* 0.40* 0.32* 0.38* 0.48* 0.03 0.26* 0.05 0.43* 0.44* 0.24* 0.45* 0.57* 0.47* EL 0.39* 0.25* 0.35* 0.42* 0.34* 0.20* 0.48* 0.23* 0.33* 0.46* 0.14 0.28* 0.24* 0.23* 0.31* 0.20* 0.12 SOT 0.64* 0.36* 0.58* 0.56* 0.44* 0.16* 0.47* 0.20* 0.28* 0.50* 0.36* 0.54* 0.37* 0.30* 0.48* 0.19* 0.04 CP BUT EL SOT CP 1.00* BUT 0.42* 1.00* EL 0.27* 0.18* 1.00* SOT 0.37* 0.27* 0.52* 1.00*

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Table 4-10. Eigenvalues for the Entrepre neurial Potential Profile variables. F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 Eigenvalue 8.09 1.96 1.28 0.72 0.50 0.37 0.22 0.16 0.12 0.04 0.01 Variability(%) 38.51 9.32 6.09 3.42 2.39 1.77 1.04 0.76 0.58 0.20 0.07 Cumulative % 38.51 47.83 53.92 57.34 59.74 61.51 62.55 63.30 63.89 64.08 64.15 Table 4-11. Factor pattern coefficients for the Entrepreneurial Potential Profile. F1 F2 Achievement drive 0.116 0.087 Compelling vision 0.090 -0.068 Energy 0.117 -0.009 Action oriented 0.051 0.115 Big picture 0.087 0.033 Options thinking 0.071 -0.128 Savvy 0.093 0.067 Problem seeking 0.061 -0.264 Synthesis 0.033 0.087 Problem solving 0.072 0.074 Delighting customers 0.016 0.109 Focus 0.093 0.146 Positive mindset 0.057 -0.070 Self-determining 0.037 0.048 Persistence 0.063 0.053 Expressing passion 0.116 -0.323 Purposeful networking 0.039 -0.172 Creating partnerships 0.096 -0.088 Building up the team 0.026 -0.060 Experiential learning 0.038 0.061 Staying on track 0.089 0.284 81

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Scree plot0 0.5 1 1 .5 2 2.5 3 3.5 4 F1 F2 F3axisEigenval u 0 20 40 60 80 1 00Cumulative variability Figure 4-1. Scree plot for the En trepreneurial Potential Summary. Scree plot0 1 2 3 4 5 6 7 8 9 F1F2F3F4F5F6F7F8F9F1 0F1 1axisEigenval u 0 20 40 60 80 1 00Cumulative variability Figure 4-2. Scree plot for the En trepreneurial Potential Profile. 82

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Variables (axes F1 and F2: 47.83 %)Staying on track Experiential learning Building up the team Creating partnerships Purposeful networking Expressing Passion Persistence Selfdetermining Positive mindset Focus Delighting customers Problem solving Synthesis Problem seeking Savvy Options thinking Big picture Action oriented Energy Compelling vision Achievement drive -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 -1-0.75-0.5-0.2500.250.50.751F1 (38.51 %)F2 (9.32 % Figure 4-3. Factor pattern co efficient plot for the Entrepreneurial Potential Profile. 83

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CHAPTER 5 DISCUSSION In this study entrepreneurialism as a personality characteristic has b een explored both in literature and empirically. In this chapter a disc ussion of the results, suggestions for future research and implications for community colle ge administrators will conclude this study. Discussion of the Results Research Hypothesis One Drucker (1985) said entrepre neurialism can be learned. With hypothesis one the goal was to empirically substantiate this claim. The construction of the cells based upon respondents having a doctorate degree or not having a doctorate degree is admittably suspect for this hypothesis. In a way the construction of this hypothesis was more of convenience as having a degree of any sort shows the ability to learn, as could several other de finitions. Given the group composition of community college presidents, association board members for community college oversight and senior leaders it may seem a sound decision but will only be generalizable to this type of group composition. Should this st udy have included staff and less senior managers the operationalization of entrepreneurialism being learnable may have needed to be constructed differently. The WAVE was designe d for senior leaders and admi nistrators and this, in my opinion, would be an appropriate use of the education variable in this study. The descriptive data showed significantly hi gher mean scores for those with doctorate degrees in acquiescence ratings. In other words the data has shown t hose without doctorate degrees tend to rate themselves lower with resp ect to their personality characteristics than those with doctorate degrees. In this instance the data showed those with doctorate degrees tended to rate themselves about the same as those w ithout doctorate degrees. The normative-ipsative agreement is higher for those w ithout doctorate degrees than fo r those with doctorate degrees. 84

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This would suggest those with doctorates would al so tend to rate themselves more accurately the first time around and have less ipsative forced choi ce selections to make later. This may suggest those with doctorate degrees may be more trus ting, more accurate, more humble, or even less positive than those without doctorate degrees. One could say those with doctorate degrees tended to stay more focused on the task while completing the questionnaire as well. The results in the ANOVAs for the entrepreneurial potential summary and entrepreneurial profile summary show highly significant results for suppo rting the hypothesis of entrepreneurialism being a learnable trait. Fo llow up t-tests for the entrepreneurial potential summary further showed those with doctorate degrees are significantl y more likely to be better at seeing possibilities, staying in the zone, and being more open to the world than non-doctorates. There is no significant difference between the two groups with respect to getting in the zone, creating superior opportunities, or building capac ity. These may be the traits which are common to both groups or may not be common to either group. Since the mean scores were well above average for these items this researcher would l ean toward the former argument of these being traits common to both groups, suggesting entrepre neurial tendencies a nd certain traits are common to the majority of community college administrators irrespective of educational attainment. Follow up t-tests for the entrepreneurial pote ntial summary further showed those with doctorate degrees are significantly more likely to be better at co mpelling vision, energy, big picture, options thinking, problem seeking, pos itive mindset, self determining, persistence, expressing passion, building up the team, and expe riential learning than non-doctorates for the entrepreneurial profile summary. There is no sign ificant difference between the two groups with respect to achieving drive, action-oriented, savvy, synthesis, problem solving, delighting 85

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customers, focus, purposeful networking, creating partnerships or staying on track. These may be the traits which are common to both groups or may not be common to either group. Since the mean scores were above average for these items this researcher would lean toward the former argument of these being traits common to both groups, suggesting entrepre neurial tendencies and certain traits are common to the majority of community college administrators irrespective of educational attainment. We have seen doctorate training, in some instances, can lead to an increase in entrepreneurialism however this may be a causal effect at best. Research Hypothesis Two With hypothesis two the goal was to substantiate the claims of other researchers, such as Ryan (2004) who decided entrepre neurialism was more of a regiona l trait. The construction of the cells based upon respondents being located within 60 mile s of a center of economic entrepreneurialism is suspect for this hypothe sis since other research ers have used other delineations to derive entrepreneur ial areas and no where in literature is there a limit of within 60 miles for boundaries of economic regions of entrepreneurialism. For example, Charlotte, North Carolina has been recently named as numb er two as an entrepreneurial region in the United States by the Entrepreneur.com a nd was not represented on this list (e.g., http://www.entrepreneur.com/bestcities/index.html ). The results in the ANOVAs for the entrepreneurial potential summary and entrepreneurial profile summary show highly significant results for suppo rting the hypothesis of entrepreneurialism being a regional characteristic. Follow up t-tests for the entrepreneurial potential summary showed no diffe rences and follow up t-tests fo r the entrepreneurial profile summary showed only significant differences in expressing passion and building up the team for those administrators in entrepreneurial ec onomic regions. On the other hand for those administrators not in entreprene urial economic regions they show ed significantly higher scores 86

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for synthesis. These may be the traits which are common to both groups or may not be common to either group. Since the mean scores were above average for these items and the t-tests showed no difference, then this researcher would lean to ward the former argument of these being traits common to both groups, suggesting entrepreneuria l traits are common to the majority of community college administrators irrespective of economic region. Research Hypothesis Three With hypothesis three the goal was to ascer tain whether the WAVE entrepreneurial instrument adequately measures entrepreneuria lism. Factor analysis of the entrepreneurial potential summary and entrepreneurial profile summary showed strong correlations and highly significant results over the instrument. Eigenva lues for the entrepreneurial potential summary and entrepreneurial profile summary explain better than 60% of entrepreneurial characteristics showing it to be a valid instrument. With a Chronbachs alpha of 0.90 and 0.92 we also have reason to believe this is a reliable instrume nt. Eigenvalues for the entrepreneurial profile summary show clusters of six to eight grouping or a possible six to eight factors represented in the 21 variables. If we were to use just six fa ctors then we could assume they break down into the six factors represented in the entrepreneurial potential summary. Therefore, the results of the factor analysis gives the researcher further affirmation of the validity and reliability of the entrepreneurial instruments w ithin the WAVE instrument. The WAVE and Entrepreneurial Characteristics Overall this group of administrators exhibi ted the highest means on the entrepreneurial scale for seeing the big picture, savvy, and achievi ng drive. Seeing the big picture would seem to be very interesting. If these administrators were good at seeing the big picture, then why didnt they heed the warnings in the reports? The lo west (in order) were prob lem seeking, experiential learning, and delighting customers. Problem seeki ng, given the literature on the administrators 87

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ignoring the warnings, follows the literature and would seem to be logical. Delighting customers, on the other hand, does not make sense given th e literature on community colleges responding to the needs of the community and may need furt her research. Perhaps the middle managers are better suited to addressing the community, rather than the top administrators. How this may be handled in an interview may be simply asking the candidate about their opinion of visions for the future of the institution and compare them to what the board and senior leaders have been discussing. Suggestions for Future Research There are several suggestions for future res earch which could stem from this study. As the literature review showed res earch has not been clear in their definition of entr epreneurialism. What is entrepreneurialism? Is someone really entrepreneurial or do they just have a personality which supports entrepreneurial behavior? A study could be done to help further delineate between entrepreneurialism, innovation, and creativ ity. Is a community college which has been labeled as entrepreneurial really an entreprene urial school? Or, perhaps, are they labeled as entrepreneurial because the administrators are we ll-traveled, have great research teams, and can identify good opportunities that begin at other schools and adopt them in their own institution? There seems to be a difference between creation a nd adoption which needs to be studied further. In the first hypothesis we looked at whether entrepreneurialism can be learned. Perhaps a future study could ensue by following a group of entrepreneurs in trai ning and longitudinally study their entrepreneurial scores to see if en trepreneurialism can be learned. How long does it take to become entrepreneurial or become more entrepreneurial? This also begs the question: What are the positions requiring entrepreneurialism in community college administration? Are there only certain ones or does every position require a modicum of entrepreneurialism? Another possible study could examine whether entrepreneur ial community college leaders are recruited to 88

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more senior leadership positions at other co mmunity colleges and grow other entrepreneurial leaders? What is the best way to train and build entrepreneurial leaders? Once you have them then what is the best way or wa ys to keep entrepreneurial leader s? The first hypothesis also dealt specifically with community college administrators Perhaps a future study may wish to compare and contrast with entrepreneuriali sm of administrators in public f our-year institutions and private institutions as well. The second hypothesis dealt with regions of entrepreneurial economic activity using the number of patents in an area to define it as an area of entrepre neurialism. This, in turn, implied the causality for finding entrepreneurs more in these regions. Perhaps someone could do a comparative analysis using a variety of different definitions of entrepreneurial economic regions. For example, future studies could use the numbe r of patents, the number of copyrights, the number of new corporations, the number of museums, the number of night clubs, the number of alternative news publications, the growth of popula tion in an area, or even something completely different to define an entrep reneurial economic region. A future study may also even wish to examine the areas of economic entrepreneurialism comparatively against administrators of fouryear and private colleges. The third hypothesis looked for validity and reliability of the WAVE entrepreneurial instrument. This research suggests the WAVE entr epreneurial instrument is valid, reliable, and measuring what it intends to measure. However, the WAVE results have a shelf-life of 18 to 24 months (Saville, 2006b). Perhaps a future study may examine the viability of using the WAVE as part of the annual evaluation of community co llege administrators and to help build their learning plans, especially for those positions re quiring entrepreneurialism. A larger sample size may be used in the future to re-examine the structural model of th e WAVE as it pertains 89

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specifically to higher education ad ministrators to deduce if there are three, four, or more main factors. The WAVE should be validated according to th e criterion set forth in the Five Factors Model if not already done. Th is chapter has made some possible correlations but nothing substantive, nor empirical. Since the WAVE is a proprietary instrument this may indeed have already been done. There are a few suggestions for future resear ch from the literature as well. First, Baum and Locke (2004) suggested studie s be conducted outside of the building industry to corroborate their findings linking entrepreneuria lism to certain personality characteristics of leaders. This study has extended a similar methodology into th e higher education realm however similar studies could be performed for K-12 and university administrators. Baum and Locke (2004) also suggest future studies linking entr epreneurialism to venture growth of the schools. I would add the recommendation to conduct the research in a longitudinal fashion or as a case study (as suggested by Zhao & Seibert, 2005). Next, research has suggested entrepreneurs further correlate highly on being both a transactional and transformational leader. A tr ansactional leader is one who focuses on the economic exchanges between leaders and followers to allow them to work well over a short period of time to realize the full potential of th e organization. A transformational leader is one who has the ability to recognize th e needs of the followers, to allow them to fully realize the potential of the individual (Tarabishy, Solo mon, Fernald, & Sashkin, 2005). Further research may be conducted on examining the differences between leaders and followers in community college administration (as well as in other industries) as it pertains to transactional and transformational leaders. 90

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Third, in all of the mention of personality traits and testing fo r personality traits there has been little mention of trust as a personalit y characteristic. This applies to both how the administrator trusts others, their subordinates, and their superiors. In the opinion of this researcher there needs to be further examina tion of how trust plays into the role of the administrator. If you are a president or board member how do you know you can trust the decision-making of your senior leaders? How do you know they are not holding down a potential senior leader in a junior positi on who may have the abilities to out-shine the senior leadership? This, especially in a time of high turnover and attrition, will be paramount for community college administrators. The WAVE can take the guesswork out of this process by being used by presidents as accountability measures of their senior staff in evaluating the middle and upper management personnel. Finally, the WAVE can be used as a benchmark for identifying stre ngths and weaknesses of the administrative personnel and should be able to be used for the team as a whole. Why would you want to hire another manager in an organization already top-heavy with managers? Perhaps hiring a leader may be more prudent. Th is would also make for an excellent follow-up study. Researchers generally agree teams should be very heterogeneous in their compositions (e.g., Borman, 1997) yet research on understand ing work groups and team dynamics, as it applies to personnel selection a nd staffing is still a long way o ff (Borman, 1997; see also Chan, 2005; Landy, Shankster, & Kohler, 1994). Implications for Community College Administrators This study has shown community college admi nistrators possess entrepreneurial traits irrespective of educational level or regionalism. This logically fo llows the historical trend of community colleges being quick to respond to cha nge throughout the literat ure. This leaves a 91

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variety of implications for community college administrators with respect to succession planning, turnover and attri tion, and collaborations. Using the WAVE could be a very vital tool in assessing entrepreneurial traits while updating and maintaining succession planning charts. If the philosophy of your community college is to hire outside for your senior leaders then your searches need not be concentrated in only certain areas of the country. If the philoso phy of your community college is to promote from within then it is very possible to be ab le to grow your own entr epreneurs. Once you have found them, one way or the other, then keeping th em will also be a challenge, especially in a time of high turnover and attrition. Turnover and attrition will create a vari ety of problems for community college administrations. Researchers have concluded se arches would be expensive, competition would be great, and the ramifications of a poor choi ce would be extremely costly, especially with respect to productivity, morale, and institut ional image (Belcher & Montgomery, 2002; Campbell & Associates, 2002; Lloyd, 2002). This paper has focused upon hiring the right person for positions requiring entrepreneurialism wh ich is based upon the assumption of replacing positions from retirements however, some auxilia ry hiring will occur through the attrition and turnover of positions from employees who may not necessarily agree with the choice of the new hire. Some researchers, such as Barrick and Zimmerman (2005) have studied this phenomenon. There are research studies on morale and productivity issues resulting from rapid turnover and attrition. Making a poor choice, or even a series of poor choices, may force an administrator into making budget cuts where there is little r oom. This follows from over-spending, duplicate spending, and duplicative serv ices. If not with personnel, then where is an administrator to being 92

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the trimming and cutting process? Student serv ices? Maintenance? Light bills? What about external competition from those for-profit educa tional institutions nipping at the state budget? The Community College Futures Conference participants have shown fiscal matters to be the dominant concern for community college admini strators, especially during these years of turnover and attrition. Coupled w ith increasing student enrollme nts and aging buildings, having administrators with entrepreneurial characteristics is a key for remaining solvent. Does this mean there should be more of a fo cus on performance-based funding? The Carl Perkins Vocational Technical Act calls specifically for community colleges to improve program completion rates, the placement rates, and to measure graduate persistence ( http://www.ed.gov/offices /OVAE/CTE/perkins.html ). President Bush recently signed the new budge calling for $1.3 billion in reductions for voca tional and technical programs from the lack of the ability to show demons trable gains in accountability (Democratic Staff, 2005). Thus signaling the movement in the United St ates towards performance based funding. It has been said the United States is drama tically behind on accountab ility and assessment with respect to performance based funding and our focus should be upon effective teaching and learning, not just upon increasing student numbers (Sharma, 2004). Recently this ideology has demonstrated its value in Australian and Canada through multi-fa ceted approaches to institutional effectiveness. In fact one of the 2007 Bellwether fi nalists in planning, governance, and finance, was a multi-faceted plan for inst itutional effectiveness at Mohave Community College. This increasing government oversight is trumpeting the call to increase entrepreneurial activities at community colleges and other ed ucational institutions. Some may say if an institution moves towards becomi ng entrepreneurial, are they in danger of straying from their 93

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mission and fundamentally altering the character and personality of the institution? Will this move them away from being what made them successful in the first place? Should community college leaders possess more government relation skills? This trait is directly unexplored but f acets of it may be indirectly related to it. In the face of declining state funding our leaders of tomorrow are going to ha ve to be more adept with working with government. This can be however, acrimonious at be st. Lest we recall the run-ins with one of the first truly exceptional educators, Socrates, who was condemned to death by the government for corrupting the youth. In the immortal words of Socrates: I drank what? Will community colleges that fail to be entrepreneurial be forced into collaborations with private institutions? Will licensure efforts, such as within North Carolina, pervade into other states for private institutions of education? Will we see more change in governance of community colleges to be the gateway to four-year institutions? Will the four-year institutions be tiered into research and n on-research organizations? Conclusion Becoming more entrepreneurial is a top-dow n change in culture for everyone in the community college simply because most schools ha ve become seemingly complacent during this time of high turnover and attriti on. Sharma (2004) says entreprene urialism should start with the business faculty and administration because the business faculty will allow any lead that might turn a profit whereas the faculty like education would not rec ognize a business opportunity if it fell on them. Thus, everyone in the organization, high and low, should receive some sort of entrepreneurial training. Entrepreneurial organizations must choose risk taking, trust, and passion. They must cultivate an insatiable appeti te for change, thrive on creativ e problem solving, and relying on courageous leadership. They will be shaped by people who have unique talents and abilities for identifying inven tive responses to environmen tal challenges and who possess 94

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a sense of purpose and an unwavering comm itment to achieving the colleges mission (Flannigan et al, 2006, p. 2). Given the fast-moving pace entrepreneurs enjoy acad emia, especially in those systems heavily laden with bureaucracy, this may not be suitable This may, in fact, be a barrier to becoming entrepreneurial. The research here does not imply hiring t hose with entrepreneurialism tendencies is the only way to be successful in community college lead ership, but instead a good team should include, at the minimum, a modicum of entrepreneurialistic tendencies. The Wingspread Report, the conferences, a nd other research have called for more entrepreneurial leaders. This research reinfo rces that position: the leaders of tomorrows community colleges must be entrepreneurial or possess some faction of entrepreneurial training. These leaders will need to abandon the traditional position of maintaining the status quo. They will need to focus upon more long-range planning seemingly escaped the leaders of yesterday who are retiring in waves today. Should community colleges band together and insist upon standardized curriculum for developing leaders? Perhaps they should co llaborate and develop competency-based testing. In this fashion l eaders possess certain minimum standards can be readily identified which will be beneficial in times of heavy turnover and attrition. Community colleges have shown the ability to respond quickly to the needs of business and the community. This study has shown entrepreneurialism to be a personality tra it found in community college administrators. This trai t is not localized to any area of the country but is fairly welldispersed. The WAVE is a valid and reliable in strument for personality assessment. The major conclusion of this study is the Entrepreneurial Re port is a measure of cognitive ability which, when combined with the Expert Report, can give a more well-rounded assessment of an individual, which is something earlier research on personality te sting has not done extensively: linking personality traits to c ognitive applications. Perhaps this is the missing puzzle piece 95

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mentioned earlier in the literat ure by Auteri (2003) and Asendorpf (2002). Since we have seen entrepreneurial tendenc ies are found throughout the community college leadership collective, these two tools, in my opinion, are good indicato rs of success for future leaders and should be used in the assessment process whether it is a hiri ng process, annual evaluation process, or just to be used to gauge the composition of the team. 96

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APPENDIX A THE SCALE DESCRIPTIONS Recall from Figure 3-1 the WAVE is composed of four clusters: thought, influence, adaptability, and delivery. Each of these clusters is divided into three sections, three dimensions per section, and three f acets per dimension yielding a total of 12 sections, 36 dimensions and 108 facets. The Thought Cluster The thought cluster (see Figure A-1) is composed of visi on, judgment, and evaluation sections and inventive, abstract, strategic, insightful, practically minded, learning oriented, analytical, factual, and rational dimensions. Inventive Dimension The inventive dimension is composed of the creative, original, and radical facets. Less than 40% of the benchmark group scored highly in the inventive dimension making this a less than usual attribute. High scor ers for the inventive dimension ar e fluent in generating ideas, produce lots of ideas; are confident in their ability to genera te unusual ideas; favor radical solutions to problems; very much enjoy the creative process (Saville, 20 06). If someone scores high on the inventive dimension they are very like ly also to score highly on being strategic (r = 0.49), abstract (r = 0.44), and insi ghtful (r = 0.41) dimensions a nd are likely to score low on being compliant (r = -0.50). If so meone scores in the moderate range on the inventive dimension they are very likely to also score high on be ing change oriented (r = 0.36), empowering (r = 0.34), dynamic (r = 0.31), learning oriented (r = 0.31) convincing (r = 0.31), and analytical (r = 0.30) dimensions. 97

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Abstract Dimension The abstract dimension is composed of the conceptual, theoretical, and learning by thinking facets. About half of the benchmark group scored highly in the abstract dimension making this a common attribute. High scorers enjoy thinking about and developing concepts; develop concepts well; apply theories a lot; li ke applying theories and believe they do this effectively; need to understand th e underlying principles to learn effectively (Saville, 2006). If someone scores high on the abstract dimension th ey are very likely to score highly on being learning oriented (r = 0.51) analytical (r = 0.48), and inventive (r = 0.33). Strategic Dimension The strategic dimension is composed of th e developing strategy, visionary, and forward thinking facets. About half of the benchmark group scored highly in the strategic dimension making this a common attribute. High scorers a re good at developing eff ective strategies and derive real satisfaction from this; need to have, and feel able to create, an inspiring vision for the future; think long-term; are likely to be seen as visionary (Saville, 2006). If someone scores high on the strategic dimension they are very likely to score highly on being inventive (r = 0.49), insightful (r = 0.44), dynamic (r = 0.41), striving (r = 0.41), and empowering (r = 0.40) and are likely to be low on compliant (r = -0.38). Insightful Dimension The insightful dimension is composed of the discerning, seeking improvement, and intuitive facets. More than half of the benchm ark group scored highly in the insightful dimension making this a frequent attribute. High scorers cons ider themselves very quick at getting to the core of a problem; have a constant need to improve things and be lieve they are good at identifying ways in which things can be improved; very much trust their intuition about whether 98

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things will work (Saville, 2006). If someone sc ores high on the insightful dimension they are very likely to score highly on stra tegic (r = 0.44) and i nventive (r = 0.41). Practically-Minded Dimension The practically minded dimension is composed of being practical, learning by doing, and common sense focused facets. More half of the benchmark group scored highly in the practically minded dimension making this a frequent attri bute. High scorers are ve ry oriented towards practical work; enjoy, and consider themselves good at, practical tasks; mu ch prefer to learn by doing; like to apply common sense (Saville, 2006). There are no correlations with other dimensions. Learning Oriented Dimension The learning oriented dimension is composed of open to learning, learning by reading, and quick learning facets. More than half of the benchmark group scored highly in the learning oriented dimension making this a frequent at tribute. High scorers are motivated by, and actively seek opportunities for learning new things; enjoy, and believe they learn a great deal through reading; consider themselves to be ve ry quick learners (Saville, 2006). If someone scores high on the learning orient ed dimension they are very likely to score highly on being abstract (r = 0.51). Younger peopl e tend to report higher scor es (Saville, 2006) on being learning oriented (SD diff 0.36). Analytical Dimension The analytical dimension is composed of problem solving, analyzing information, and probing facets. More than half of the benchmark group scored highly in th e analytical dimension making this a frequent attribute. High scorers see problem solving as one of their strengths; enjoy, and consider themselves good at, analyzing information; see themselves as having a great 99

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deal of curiosity; are good at asking probing que stions (Saville, 2006). If someone scores high on the analytical dimension they are very likely to score highly on bei ng rational (r = 0.50) and abstract (r = 0.48). Factual Dimension The factual dimension is composed of written communication, logical, and fact finding facets. More than half of the benchmark group scored highly in the factual dimension making this a frequent attribute. Hi gh scorers consider that they co mmunicate well in writing; readily understand the logic behind an argument; go to some lengths to ensure that they have all the relevant facts (Saville, 2006). There are no correlations with other dimensions. Rational Dimension The rational dimension is composed of numb er fluency, technology aware, and objective facets. More than half of the benchmark group scored highly in the rational dimension making this a frequent attribute. Hi gh scorers are very comfortable working with numerical data, are interested in, and regard themse lves as well versed in informa tion technology; rely heavily on facts and hard, objective data in making decisi ons (Saville, 2006). If someone scores high on the rational dimension they are very likely to score highly on bei ng analytical (r = 0.50). Males report higher scores than female s (SD diff = 0.58) (Saville, 2006). The Influence Cluster The influence cluster (see Figure A-2) is composed of leadership, impact, and communication sections and purposeful, dire cting, empowering, convincing, challenging, articulate, self promoting, inter active, and engaging dimensions. 100

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Purposeful Dimension The purposeful dimension is composed of deci sive, making decisions, and definite facets. More than half of the benchmark group scored hi ghly in the purposeful dimension making this a frequent attribute. High scorers are very comfortable making quick decisions; relish the responsibility for, and are prepared to make, big decisions; hold definite opinions on most issues and rarely change their mind (Saville, 2006). If someone scores high on the purposeful dimension they are very likely to score highly on being dire cting (r = 0.50), convincing (r = 0.45), and dynamic (r = 0.45), likely to score low on being involving (r = 0.30), and very likely to score low on being compliant (r = -0.40). Males (SD diff = 0.47) and older people (SD diff = 0.31) report higher scores (Saville, 2006). Directing Dimension The directing dimension is composed of leadership oriented, control seeking, and coordinating people facets. About half of the be nchmark group scored highly in the directing dimension making this a common attribute. High sc orers definitely want to take the lead and see leadership as one of their ke y strengths; are very much inclin ed to take control of things; enjoy, and believe they are good at, coordinating people (Saville, 2006). If someone scores high on the directing dimension they are very likely to score highly on be ing empowering (r = 0.55), purposeful (r = 0.50), dynamic (r = 0.47), convincing (r = 0.42), and enterprising (r = 0.40), but moderately likely to score lo w on being compliant (r = -0.31). Empowering Dimension The empowering dimension is composed of mo tivating others, inspiring, and encouraging facets. Less than half of the benchmark group scored highly in the empowering dimension making this a less usual attrib ute. High scorers attach importa nce to being able to motivate 101

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other people and consider themselves adept at finding ways to do this; want, and believe they are able to, to be inspirational to others; go out of their way to encourage others (Saville, 2006). If someone scores high on the empowering dimension th ey are very likely to score highly on being directing (r = 0.55) and strategi c (r = 0.40), likely to score low on being compliant (r = -0.30). Convincing Dimension The convincing dimension is composed of pe rsuasive, negotiative, and asserting views facets. About half of the benchmark group scor ed highly in the convincing dimension making this a common attribute. High sc orers are eager to bring peopl e round to their point of view and see themselves as very persuasive; want to ge t the best deal and believe they negotiate well; are determined to make people listen to their vi ews and put their point across forcibly (Saville, 2006). If someone scores high on the convincing dime nsion they are very likely to score highly on challenging (r = 0.55), enterprising (r = 0.47), pur poseful (r = 0.45), and directing (r = 0.42), but are moderately likely to score low on be ing compliant (r = -0.30). Males report higher scores (SD diff = 0.39) (Saville, 2006). Challenging Dimension The challenging dimension is composed of ch allenging ideas, prepared to disagree, and argumentative facets. About half of the benchmark group scored highly in the challenging dimension making this a common attribute. High scorers frequently challenge other peoples ideas; want people to know when they di sagree with them and are open in voicing disagreements; really enjoy arguing with peopl e and regularly get involved in arguments (Saville, 2006). If someone scores high on the ch allenging dimension they are moderately likely to score low on being co mpliant (r = -0.31). 102

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Articulate Dimension The articulate dimension is composed of giving presentations, el oquent, and socially confident facets. More than half of the be nchmark group scored highly in the articulate dimension making this a frequent attribute. High scorers enjoy, and believe they are good at, giving presentations; enjoy explaining things and consider that they do this well; enjoy meeting and are confident with new people (Saville, 2006). There are no correlations with other dimensions. Self-Promoting Dimension The self-promoting dimension is composed of immodest, attention seeking, and praise seeking facets. About half of the benchmar k group scored highly in the self-promoting dimension making this a common attribute. High scorers want people to know about their successes and go to some lengths to bring their achievements to othe rs attention; like to be, and often find themselves, the center of attention; have a strong need for praise and seek praise when they have done well (Saville, 2006). If someone scores high on the self-promoting dimension they are very likely to score highly on bei ng interactive (r = 0.43). Ov erall there is a low average self-rating on self-promoti ng. This indicates that in gene ral this is not seen as a particularly desirable charac teristic (Saville, 2006). Interactive Dimension The interactive dimension is composed of networking, talkative, and lively facets. More than half of the benchmark group scored highly in the interactive dimension making this a frequent attribute. High scorers attach a hi gh degree of importance to networking and believe they network very well; are extremely talkative; c onsider themselves to be very lively (Saville, 103

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2006). If someone scores high on the interactive di mension they are very likely to score highly on engaging (r = 0.58) and self-promoting (r = 0.43). Engaging Dimension The engaging dimension is composed of establishing rapport, fr iendship seeking, and initial impression facets. About half of the benchmark group scored highly in the engaging dimension making this a common attribute. Hi gh scorers very quickly establish rapport with people; have limited interest in making new frie nds; are unlikely to make strong first impression (Saville, 2006). If someone scores high on the en gaging dimension they are very likely to score highly on interactive (r = 0.58). The Adaptability Cluster The adaptability cluster (see Figure A-3) is composed of support, resilience, and flexibility sections and invol ving, attentive, accepting, resolving, self assured, composed, receptive, positive, and change oriented dimensions. Involving Dimension The involving dimension is composed of team oriented, democratic, and decision sharing facets. More than half of the benchmark group sc ored highly in the involving dimension making this a frequent attribut e. High scorers believe they work we ll, and enjoy being in a team; take full account of other peoples view s; go to considerable lengths to include others in the final decision (Saville, 2006). If someone scores high on the involving dimension they are very likely to score highly on accepting (r = 0.53) and attentiv e (r = 0.51), but moderately likely to score low on being purposeful (r = -0.30). 104

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Attentive Dimension The attentive dimension is composed of empathic, listening, and psychologically-minded facets. About half of the benchmark group scored highly in the attentive dimension making this a common attribute. High scorers attach importance to, and believe they are good at, understanding how others are feeling; regard themselves as good lis teners; are interested in, and consider themselves adept at, understanding why people behave as they do (Saville, 2006). If someone scores high on the attentive dimension they are very likely to score highly on being accepting (r = 0.53), involving (r = 0.51), and resolv ing (r = 0.46). Females report higher scores than males (SD diff = 0.45) (Saville, 2006). Accepting Dimension The accepting dimension is composed of trusti ng, tolerant, and considerate facets. About half of the benchmark group scored highly in the accepting dimension making this a common attribute. High scorers are very trusting of pe ople; are tolerant; place great emphasis on being considerate towards other people (Saville, 2006). If someone scores high on the accepting dimension they are very likely to score highly on being involvi ng (r = 0.53) and attentive (r = 0.52). Resolving Dimension The resolving dimension is composed of c onflict resolution, handling angry people, and handling upset people facets. About half of th e benchmark group scored highly in the resolving dimension making this a common attribute. Hi gh scorers quickly re solve disagreements; consider themselves effective at calming angry people down; believe they cope well with people who are upset (Saville, 2006). If someone scores high on the resolving dimension they are very likely to score highly on being attentive (r = 0.46). 105

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Self-Assured Dimension The self-assured dimension is composed of self-confident, self-val uing, and self-directing facets. More than half of the benchmark group scored highly in the inventive dimension making this a frequent a ttribute. High scorers are self-confident; feel very positive about themselves; have a strong sense of their own worth; feel in control of their own future (Saville, 2006). There are no correlations with other dimensions. Composed Dimension The composed dimension is composed of cal m, poised, and copes with pressure facets. About half of the benchmark group scored high ly in the composed dimension making this a common attribute. High scorers are calm; see little point in worrying, before important events; rarely get anxious during important even ts; work well under pressure (Saville, 2006). If someone scores high on the composed dimension th ey are very likely to score highly on being change oriented (r = 0.43) and moderately likely to score lo w on being compliant (r = -0.39). Males report higher scores than females (SD diff 0.34) (Saville, 2006). Receptive Dimension The receptive dimension is composed of receptive to feedback, open to criticism, and feedback-seeking facets. More than half of th e benchmark group scored highly in the receptive dimension making this a frequent attribute. High scorers respond well to feedback from others; encourage people to criticize thei r approach; actively s eek feedback on their performance (Saville, 2006). There are no correla tions with other dimensions. Younger people report higher scores (SD diff 0.32) (Saville, 2006). 106

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Positive Dimension The positive dimension is composed of op timistic, cheerful, and buoyant facets. About half of the benchmark group scored highly in the positive dimension making this a common attribute. High scorers are optimistic; are very cheerful; recover quickly from setbacks (Saville, 2006). There are no correlations with other dimensions. Change Oriented Dimension The change oriented dimension is composed of accepting challenges, accepting change, and tolerant of uncertainty f acets. About half of the benchmark group scored highly in the change oriented dimension making this a common attribute. Hi gh scorers enjoy new challenges and adapt readily to new situations; are positive about and co pe well with change; cope well with uncertainty (S aville, 2006). If someone scores high on the change oriented dimension they are very likely to score highly on being composed (r = 0.43). The Delivery Cluster The delivery cluster (see Figure A-4) is composed of struct ure, drive and implementation sections and organized, principl ed, activity oriented, dynamic, striving, enterprising, meticulous, reliable, and compliant dimensions. Organized Dimension The organized dimension is composed of self organized, planning, a nd prioritizing facets. Less than half of the benchmark group scored hi ghly in the organized dimension making this a less usual attribute. High scor ers are well organized; attach importance to planning; make effective plans; establish clear priorities (Saville, 2006). If someone scores high on the organized dimension they are very likely to score highly on being reliable (r = 0.60), meticulous (r = 0.50), and compliant (r = 0.42). 107

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Principled Dimension The principled dimension is composed of proper, discreet, and honoring commitments facets. About half of the benchmark group scored highly in the principled dimension making this a common attribute. High scorers are concerned with ethical matters and believe they behave in an ethical fashion; consider maintaining c onfidentiality to be among their key strengths and can be relied upon to be discreet; view themse lves as honoring the commitments they have agreed to (Saville, 2006). There are no correlat ions with other dimensions. There is a high average self-rating on principled. This indicates people generally consider this as a highly desirable characteristic (Saville, 2006). Activity-Oriented Dimension The activity oriented dimension is composed of quick working, busy, and multi-tasking facets. About half of the benchmark group scor ed highly in the activity oriented dimension making this a common attribute. High scorers wor k at a fast pace; work well when busy; cope well with multi-tasking (Savil le, 2006). There are no correla tions with other dimensions. Females report higher scores than males (SD diff = 0.51) (Saville, 2006). Dynamic Dimension The dynamic dimension is composed of energe tic, initiating, and action oriented facets. More than half of the benchmark group scored highly in the dynamic dimension making this a frequent attribute. High scorer s consider themselves to be very energetic; see themselves as impatient to get things started and good at starting things o ff; are focused on making things happen (Saville, 2006). If someone scores high on the dynamic dimension they are very likely to score highly on being directing (r = 0.47), purposeful (r = 0.45), striving (r = 0.42), 108

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enterprising (r = 0.42), and strategic (r = 0.41), but moderately likely to be low on compliant (r = -0.37). Striving Dimension The striving dimension is composed of ambiti ous, results driven, and perservering facets. More than half of the benchmark group scored highly in the striving dimension making this a frequent attribute. High scorers see themselves as very ambitious and want to be successful; attach great importance to achieving outstanding results and believe they do so; are very persevering and keep going no matter what (Sav ille, 2006). If someone scores high on the striving dimension they are very likely to sc ore highly on being enterprising (r = 0.53), dynamic (r = 0.42), and strategic (r = 0.41). Males report higher scores (S D diff = 0.39) (Saville, 2006). Enterprising Dimension The enterprising oriented dimension is compos ed of competitive facets About half of the benchmark group scored highly in the enterprising dimension making this a common attribute. High scorers regard themselves as highly competit ive, with a strong need to win; believe they are good at, and derive real satisfaction from, identifying business opportun ities; see themselves as very sales oriented (Saville, 2006). If so meone scores high on the enterprising dimension they are very likely to score highly on stri ving (r = 0.53), convincing (r = 0.47), dynamic (r = 0.42), and directing (r = 0.40), and moderately likely to score low on compliant (r = -0.30). Males score more highly than fe males (SD diff = 0.70) (Saville, 2006). Meticulous Dimension The meticulous dimension is composed of qua lity oriented, thorough, and detailed facets. Less than half of the benchmark group scored hi ghly in the meticulous dimension making this a less usual attribute. High scorers regard themse lves as perfectionists; ensure a high level of 109

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quality; want things done properly and consider themselves very thorough in their approach; see themselves as highly attentive to detail (Saville, 2006). If someone scores high on the meticulous dimension they are very likely to score highly on being organized (r = 0.50), reliable (r = 0.48), and compliant (r = 0.42). Reliable Dimension The reliable dimension is composed of mee ting deadlines, finishing tasks, and punctual facets. About half of the benchmark group scored highly in the reliable dimension making this a common attribute. High scorers are conscien tious about meeting deadlines; believe they rarely leave things unfinished; consider themselves highly punct ual (Saville, 2006). If someone scores high on the reliable dimension they are very likely to score highly on being organized (r = 0.60), meticulous (r = 0.48), and compliant (r = 0.47). Compliant Dimension The compliant dimension is composed of rule bound, following procedures, and risk averse facets. Less than half of the benchmar k group scored highly in the change oriented dimension making this a less usual attribute. High scorers need to have rules and adhere strictly to them; like to follow set procedures; an d regard themselves as decidedly risk averse (Saville, 2006). If someone scores high on the comp liant dimension they are very likely to score highly on being reliable (r = 0.43), organized (r = 0.42), and meticul ous (r = 0.42) and moderately likely to score low on being compos ed (r = -0.39), strategi c (r = -0.38), dynamic (r = -0.37), directing (r = -0.31), ch allenging (r = -0.31), empowering (r = -0.30), convincing (r = 0.30), and enterprising (r = -0.30). Females report higher scores than males (SD diff = 0.40) (Saville, 2006). 110

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Cluster Section Dimension Facets Inventive Creative, original, radical Vision Abstract Conceptual, theoretical, learning by thinking Strategic Developing strategy, visionary, forward thinking Insightful Discerning, seeking improvement, intuitive Thought Judgment Practically Minded Practical, learning by doing common sense focused Learning Oriented Open to learning, learning by reading, quick learning Analytical Problem solving, analyzing information, probing Evaluation Factual Written communication, logical, fact finding Rational Number fluency, technology aware, objective Figure A-1 The thought cluster, sections and dimensions. Cluster Section Dimension Facets Purposeful Decisive, making decisions definite Leadership Directing Leadership oriented, control seeking, coordinating people Empowering Motivating others, inspiring, encouraging Convincing Persuasive, negotiative, asserting views Influence Impact Challenging Challenging ideas, prepared to disagree, argumentative Articulate Giving presentations, eloquent, socially confident Self promoting Immodest, attention seeking, praise seeking Communication Interactive Networking, talkative, lively Engaging Establishing rapport, friendship seeking, initial impression Figure A-2. The influence cluste r, sections and dimensions. 111

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Cluster Section Dimension Facets Involving Team oriented, democratic, decision sharing Support Attentive Empathic, listening, psychologically minded Accepting Trusting, tolerant, considerate Resolving Conflict resolution, handling angry and upset people Adaptability Resilience Self assured Self-confident, self-valuing, self-directing Composed Calm, poised, copes with pressure Receptive Receptive to feedback, open to criticism, feedback seeking Flexibility Positive Optimistic, cheerful, buoyant Change oriented Accepting challenges, accepting change, tolerant of uncertainty Figure A-3. The adaptability clus ter, sections and dimensions. Cluster Section Dimension Facets Organized Self organized, planning, prioritizing Structure Principled Proper, discreet, honoring commitments Activity oriented Quick working, busy, multi-tasking Dynamic Energetic, initiating, action oriented Delivery Drive Striving Ambitious, results driven, perservering Enterprising Competitive, enterpreurial, selling Meticulous Quality oriented, thorough, detailed Implementation Reliable Meeting deadlines, finishing Tasks, punctual Compliant Rule bound, following Procedures, risk averse Figure A-4. The delivery cluste r, sections and dimensions. 112

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APPENDIX B DESCRIPTIVE STATISTICS Table B-1. Executive Summary-Aggregate (n=168) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Thought Vision 6.96 1.74 1 -0.081 -0.738 Judgment 6.57 1.73 5 -0.309 0.017 Evaluation 6.42 1.93 6 -0.246 -0.611 Influence Leadership 6.69 1.63 3 -0.445 0.556 Impact 5.47 1.84 10 0.230 -0.440 Communication 4.89 1.83 12 -0.008 -0.238 Adaptability Support 5.46 2.10 11 -0.250 -0.390 Resilience 5.77 1.79 8 -0.185 0.054 Flexibility 5.94 1.85 7 -0.190 -0.205 Delivery Structure 6.73 1.75 2 -0.507 0.534 Drive 6.68 1.91 4 -0.267 -0.385 Implementation 5.62 1.85 9 -0.141 -0.317 Ratings acquiescence 6.79 1.86 -0.521 0.214 Consistency of rankings 5.63 1.82 -0.070 -0.187 Motive-talent agreement 5.24 1.90 -0.144 -0.384 Normative-ipsative agreement 4.92 2.09 -0.350 -0.832 113

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Table B-2. Psychometric Pr ofile-Aggregate (n=168) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Inventive 6.45 1.74 10 0.01 -0.50 Abstract 6.40 1.70 12 -0.14 -0.02 Strategic 7.35 1.94 2 -0.55 -0.42 Insightful 6.90 1.56 4 -0.29 -0.33 Practically minded 5.83 1.92 22 -0.50 -0.08 Learning oriented 6.15 1.63 18 -0.38 -0.65 Analytical 6.85 1.93 8 -0.38 -0.33 Factual 6.29 1.97 15 -0.46 -0.08 Rational 5.99 1.95 20 -0.18 -0.65 Purposeful 6.21 1.85 17 -0.23 -0.34 Directing 6.88 1.65 6 -0.60 0.75 Empowering 6.37 1.77 14 -014 -0.00 Convincing 5.41 1.86 29 0.32 -0.22 Challenging 4.72 1.95 36 0.69 0.34 Articulate 6.47 1.84 9 -0.29 -0.36 Self promoting 4.73 1.80 35 0.93 0.79 Interactive 5.36 1.90 32 -0.07 -0.46 Engaging 4.97 1.84 34 -0.27 -0.48 Involving 5.54 2.17 28 -0.20 -0.50 Attentive 5.40 2.05 31 -0.21 -0.43 Accepting 5.77 1.84 25 -0.40 -0.24 Resolving 5.11 1.78 33 -0.03 0.05 Self-assured 6.45 1.63 10 -0.10 0.14 Composed 5.73 1.85 26 -0.08 -0.53 Receptive 5.69 1.86 27 -0.24 -0.12 Positive 7.73 1.95 1 -0.31 -0.51 Change oriented 6.29 1.83 15 -0.33 -0.19 Organized 6.40 1.72 12 -0.48 -0.05 Principled 6.86 1.58 7 -0.68 0.46 Activity oriented 6.01 1.75 19 -0.25 -0.01 Dynamic 6.89 1.97 5 -0.34 -0.10 Striving 7.02 1.72 3 -0.44 -0.36 Enterprising 5.80 1.95 24 -0.08 -0.58 Meticulous 5.83 1.87 22 -0.24 -0.61 Reliable 5.84 1.78 21 -0.39 -0.23 Compliant 5.39 1.81 30 0.23 -0.42 114

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Table B-3. Competency Potent ial Profile-Aggregate (n=168) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achieving success 6.95 1.81 5 -0.49 -0.16 Adjusting to change 6.57 1.77 7 -0.54 0.20 Communicating with people 5.27 1.90 12 -0.13 -0.16 Creating innovation 7.05 1.74 2 -0.07 -0.85 Evaluating problems 7.05 1.82 2 -0.30 -0.56 Executing assignments 5.70 1.85 10 -0.14 -0.34 Making judgments 7.07 1.58 1 -0.58 0.83 Presenting information 6.28 1.68 8 -0.39 -0.01 Projecting confidence 6.23 1.78 9 -0.42 0.10 Providing leadership 6.83 1.65 6 -0.66 0.72 Providing support 5.61 2.04 11 -0.45 -0.12 Structuring tasks 6.96 1.74 4 -0.60 0.75 Table B-4. Entrepreneurial Pote ntial Summary-Aggregate (n=168) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Getting in the zone 6.99 1.81 2 -0.63 0.06 Seeing possibilities 7.49 1.67 1 -0.51 -0.15 Creating superior opportunities 6.77 1.77 5 -0.37 -0.15 Staying in the zone 6.94 1.63 3 -0.58 0.35 Opening up to the world 6.17 1.83 6 -0.42 -0.004 Building capacity 6.74 1.74 4 -0.41 0.27 115

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Table B-5. Entrepreneurial Pote ntial Profile-Aggregate (n=168) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achievement drive 7.29 1.70 2 -0.55 -0.17 Compelling vision 6.28 1.68 16 -0.09 -0.01 Energy 6.93 1.84 4 -0.61 0.52 Action oriented 6.51 1.95 13 -0.52 -0.09 Big picture 7.48 1.71 1 -0.54 -0.25 Options thinking 6.81 1.65 5 -0.15 -0.63 Savvy 7.23 1.73 3 -0.93 0.83 Problem seeking 5.84 1.93 19 -0.30 -0.48 Synthesis 6.58 1.83 11 -0.35 -0.23 Problem solving 6.60 1.58 10 -0.24 -0.27 Delighting customers 5.77 1.87 20 -0.04 -0.61 Focus 6.77 1.74 6 -0.43 0.21 Positive mindset 6.63 1.72 9 -0.78 0.63 Self-determining 6.74 1.71 7 -0.35 -0.08 Persistence 6.52 1.81 12 -0.39 0.18 Expressing passion 6.16 1.72 17 -0.20 -0.01 Purposeful networking 5.69 1.93 21 -0.26 -0.26 Creating partnerships 6.32 1.85 15 -0.44 -0.01 Building up the team 6.41 1.82 14 -0.46 0.19 Experiential learning 6.11 1.63 18 -0.22 0.05 Staying on track 6.73 1.77 8 -0.29 -0.07 116

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Table B-6. Executive Summary-Doctorates (n=40) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Thought Vision 7.68 1.37 1 0.01 -1.05 Judgment 6.18 1.83 7 -0.43 0.12 Evaluation 6.13 1.82 8 -0.06 -0.22 Influence Leadership 7.35 1.62 2 -0.29 -0.46 Impact 5.68 1.74 10 0.02 -0.78 Communication 4.85 1.84 12 0.12 0.30 Adaptability Support 6.13 1.98 8 -0.15 -0.47 Resilience 6.33 1.68 6 0.24 -0.78 Flexibility 6.38 1.67 5 -0.57 1.03 Delivery Structure 6.83 1.83 4 -0.97 1.44 Drive 7.00 1.73 3 -0.69 0.13 Implementation 5.20 1.72 11 -0.55 -0.36 Ratings acquiescence 7.28 1.80 ---1.23 2.02 Consistency of rankings 5.55 1.82 --0.03 -0.98 Motive-talent agreement 5.08 1.86 ---0.11 -0.36 Normative-ipsative agreement 4.05 1.88 ---0.25 -1.22 117

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Table B-7. Executive SummaryNon-Doctorates (n=128) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Thought Vision 6.73 1.77 1 0.03 -0.78 Judgment 6.69 1.67 3 -0.22 -0.17 Evaluation 6.51 1.95 5 -0.31 -0.67 Influence Leadership 6.48 1.58 6 -0.59 0.84 Impact 5.41 1.86 10 0.30 -0.33 Communication 4.90 1.82 12 -0.05 -0.41 Adaptability Support 5.25 2.08 11 -0.27 -0.45 Resilience 5.60 1.78 9 -0.28 0.08 Flexibility 5.80 1.88 7 -0.07 -0.37 Delivery Structure 6.70 1.72 2 -0.34 0.22 Drive 6.59 1.95 4 -0.15 -0.44 Implementation 5.75 1.87 8 -0.07 -0.42 Ratings acquiescence 6.64 1.84 ---0.33 -0.02 Consistency of rankings 5.65 1.81 ---0.10 0.07 Motive-talent agreement 5.29 1.90 ---0.16 -0.39 Normative-ipsative agreement 5.20 2.06 ---0.46 -0.70 118

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Table B-8. Psychometric Pr ofile-Doctorates (n=40) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Inventive 6.98 1.37 6 0.28 -0.91 Abstract 6.63 1.46 12 0.14 -0.32 Strategic 8.30 1.38 1 -0.78 0.57 Insightful 6.83 1.56 9 -0.10 -0.10 Practically minded 5.23 2.08 31 -0.25 -0.63 Learning oriented 6.03 1.67 20 -0.43 -0.43 Analytical 6.98 1.74 6 -0.53 -0.01 Factual 6.15 1.71 19 -0.83 1.37 Rational 5.58 1.79 28 0.10 -0.12 Purposeful 6.63 2.03 12 -0.23 -0.92 Directing 6.98 1.64 6 -0.17 -0.20 Empowering 7.43 1.39 2 -0.01 -1.09 Convincing 5.73 1.57 24 -0.13 -0.50 Challenging 4.88 1.93 34 0.70 0.15 Articulate 6.75 1.81 10 -0.25 -0.81 Self promoting 4.65 1.89 36 0.82 0.69 Interactive 5.45 1.83 30 0.18 -0.25 Engaging 4.80 1.58 35 0.03 0.56 Involving 6.33 2.10 15 -0.46 -0.41 Attentive 5.80 1.81 23 -0.16 -0.24 Accepting 6.20 1.75 17 -0.08 -0.60 Resolving 5.63 1.53 27 -0.20 -0.46 Self-assured 6.45 1.67 14 -0.54 1.36 Composed 6.33 1.79 15 0.05 -0.51 Receptive 5.65 1.48 26 -0.36 1.16 Positive 6.20 1.50 17 -0.25 -0.76 Change oriented 6.68 1.86 11 -0.50 -0.19 Organized 6.50 1.75 13 -0.56 -0.18 Principled 7.00 1.47 5 -0.86 0.06 Activity oriented 5.90 1.77 22 -0.50 0.41 Dynamic 7.13 1.86 4 -0.44 0.11 Striving 7.20 1.66 3 -0.22 -0.92 Enterprising 5.95 1.84 21 -0.36 -0.67 Meticulous 5.53 1.92 29 -0.28 -0.77 Reliable 5.70 1.82 25 -0.15 -0.87 Compliant 4.98 1.52 33 0.00 -0.63 119

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Table B-9. Psychometric Profile-Non-Doctorates (n=128) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Inventive 6.28 1.81 13 0.08 -0.57 Abstract 6.32 1.76 12 -0.15 -0.07 Strategic 7.05 1.99 1 -0.38 -0.65 Insightful 6.88 1.55 3 -0.35 0.13 Practically minded 6.02 1.82 20 -0.55 -0.05 Learning oriented 6.19 1.61 14 -0.36 -0.02 Analytical 6.80 1.98 7 -0.33 -0.43 Factual 6.33 2.04 10 -0.40 -0.37 Rational 6.12 1.97 16 -0.28 -0.70 Purposeful 6.09 1.76 17 -0.31 -0.12 Directing 6.85 1.65 4 -0.74 0.99 Empowering 6.04 1.74 19 -0.05 0.19 Convincing 5.31 1.94 30 0.44 -0.15 Challenging 4.67 1.96 36 0.69 0.40 Articulate 6.38 1.83 9 -0.31 -0.25 Self promoting 4.75 1.76 35 0.98 0.81 Interactive 5.34 1.92 29 -0.14 -0.53 Engaging 5.02 1.91 33 -0.34 -0.65 Involving 5.29 2.13 31 -0.14 -0.44 Attentive 5.23 2.10 32 -0.17 -0.53 Accepting 5.63 1.84 25 -0.47 -0.27 Resolving 4.95 1.83 34 0.07 0.16 Self-assured 6.45 1.61 8 0.05 -0.30 Composed 5.54 1.82 27 -0.12 -0.65 Receptive 5.70 1.96 24 -0.22 -0.37 Positive 5.58 2.05 26 -0.22 -0.63 Change oriented 6.16 1.81 15 -0.30 -0.14 Organized 6.33 1.71 11 -0.46 0.01 Principled 6.82 1.61 5 -0.62 0.53 Activity oriented 6.05 1.74 18 -0.16 -0.16 Dynamic 6.82 2.00 5 -0.30 -0.16 Striving 6.97 1.74 2 -0.50 -0.26 Enterprising 5.76 1.98 23 0.00 -0.55 Meticulous 5.92 1.85 21 -0.22 -0.59 Reliable 5.88 1.76 22 -0.46 0.03 Compliant 5.52 1.87 28 0.21 -0.52 120

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Table B-10. Competency Pr ofile-Doctorates (n=40) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achieving success 7.03 1.78 5 -0.59 -0.42 Adjusting to change 6.98 1.64 7 -1.13 2.59 Communicating with people 5.33 1.81 12 -0.11 0.15 Creating innovation 7.60 1.36 1 0.15 -0.99 Evaluating problems 7.00 1.69 6 -0.22 0.12 Executing assignments 5.53 1.83 11 -0.48 -0.09 Making judgments 7.03 1.86 4 -0.52 0.52 Presenting information 6.63 1.53 9 -0.62 0.45 Projecting confidence 6.83 1.51 8 -0.13 0.15 Providing leadership 7.30 1.63 2 -0.45 0.02 Providing support 6.45 1.67 10 0.23 -0.55 Structuring tasks 7.20 1.79 3 -1.29 1.89 Table B-11. Competency Potential Profile-Non-Doctorates (n=128) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achieving success 6.92 1.81 3 -0.46 -0.08 Adjusting to change 6.44 1.79 7 -0.38 -0.19 Communicating with people 5.25 1.92 12 -0.13 -0.24 Creating innovation 6.88 1.80 4 0.01 -0.96 Evaluating problems 7.07 1.85 2 -0.33 -0.71 Executing assignments 5.76 1.85 10 -0.04 -0.47 Making judgments 7.08 1.48 1 -0.59 0.74 Presenting information 6.17 1.71 8 -0.32 -0.09 Projecting confidence 6.05 1.81 9 -0.42 -0.06 Providing leadership 6.68 1.62 6 -0.78 0.88 Providing support 5.34 2.06 11 -0.49 -0.40 Structuring tasks 6.76 1.70 5 -0.39 0.60 Table B-12. Entrepreneurial Poten tial Summary-Doctorates (n=40) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Getting in the zone 7.30 1.82 2 -0.67 -0.19 Seeing possibilities 8.00 1.40 1 -0.50 0.27 Creating superior opportunities 7.15 1.92 5 -0.75 0.55 Staying in the zone 7.48 1.66 4 -0.55 -0.06 Opening up to the world 6.65 1.65 6 -0.43 -0.03 Building capacity 7.03 1.88 3 -0.53 0.06 121

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Table B-13. Entrepreneurial Potentia l Summary-Non-Doctorates (n=128) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Getting in the zone 6.89 1.79 2 -0.63 0.15 Seeing possibilities 7.33 1.72 1 -0.44 -0.32 Creating superior opportunities 6.65 1.71 4 -0.26 -0.35 Staying in the zone 6.77 1.58 3 -0.68 0.50 Opening up to the world 6.02 1.86 6 -0.39 -0.04 Building capacity 6.65 1.69 4 -0.40 0.40 Table B-14. Entrepreneurial Poten tial Profile-Docto rates (n=40) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achievement drive 7.48 1.67 2 -0.45 -0.52 Compelling vision 6.83 1.50 11 0.17 -0.59 Energy 7.40 1.79 3 -0.82 0.83 Action oriented 6.48 2.16 17 -0.50 -0.40 Big picture 8.10 1.36 1 -0.60 0.44 Options thinking 7.38 1.28 4 -0.22 -1.14 Savvy 7.35 1.75 5 -1.01 0.73 Problem seeking 6.48 1.75 17 -0.63 0.17 Synthesis 6.75 1.64 13 -0.41 -0.27 Problem solving 6.75 1.55 13 -0.39 0.18 Delighting customers 5.80 2.09 20 -0.15 -0.81 Focus 7.13 1.75 7 -0.11 -0.97 Positive mindset 7.03 1.29 10 0.16 -0.81 Self-determining 7.13 1.71 7 -1.25 2.39 Persistence 7.05 1.79 9 -0.76 1.44 Expressing passion 6.80 1.42 12 -0.75 1.64 Purposeful networking 6.08 1.69 19 -0.49 0.19 Creating partnerships 6.63 1.80 16 -0.49 -0.11 Building up the team 7.30 1.49 6 -0.16 -0.81 Experiential learning 5.53 1.86 21 -0.16 0.00 Staying on track 6.65 1.98 15 -0.38 -0.41 122

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Table B-15. Entrepreneurial Potentia l Summary-Non-Doctorates (n=128) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achievement drive 7.23 1.70 2 -0.57 -0.11 Compelling vision 6.11 1.70 17 -0.09 0.01 Energy 6.78 1.84 4 -0.57 0.52 Action oriented 6.52 1.88 10 -0.52 0.00 Big picture 7.29 1.76 1 -0.44 -0.46 Options thinking 6.63 1.71 7 -0.02 -0.65 Savvy 7.20 1.72 3 -0.91 0.88 Problem seeking 5.64 1.94 20 -0.19 -0.53 Synthesis 6.52 1.88 10 -0.31 -0.26 Problem solving 6.55 1.59 9 -0.19 -0.38 Delighting customers 5.76 1.80 19 0.01 -0.56 Focus 6.66 1.72 6 -0.56 0.50 Positive mindset 6.50 1.82 12 -0.79 0.35 Self-determining 6.62 1.69 8 -0.08 -0.32 Persistence 6.36 1.78 13 -0.30 -0.04 Expressing passion 5.96 1.76 18 -0.02 -0.09 Purposeful networking 5.56 1.98 21 -0.17 -0.34 Creating partnerships 6.23 1.85 15 -0.42 0.02 Building up the team 6.13 1.82 16 -0.45 0.16 Experiential learning 6.30 1.51 14 -0.07 -0.32 Staying on track 6.76 1.70 5 -0.23 0.02 123

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Table B-16. Executive Summary-Entrepreneurial School Leaders (n=33) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Thought Vision 7.18 1.93 1 -0.38 -0.57 Judgment 6.52 1.81 4 -0.61 0.03 Evaluation 5.67 2.11 9 0.23 -0.86 Influence Leadership 7.18 1.57 1 -0.73 0.39 Impact 5.36 1.82 12 -0.01 -1.08 Communication 5.39 2.03 11 -0.02 -0.73 Adaptability Support 5.91 1.76 7 -0.13 -0.84 Resilience 5.73 1.42 8 -0.53 -0.25 Flexibility 6.03 1.75 6 -0.56 0.35 Delivery Structure 6.21 2.00 5 -0.50 0.17 Drive 6.61 2.04 3 -0.53 0.04 Implementation 5.42 1.89 10 0.32 -0.37 Ratings acquiescence 6.88 1.63 --0.03 -0.89 Consistency of rankings 5.82 1.60 --0.12 0.34 Motive-talent agreement 4.91 1.93 ---0.12 -0.40 Normative-ipsative agreement 4.94 2.12 ---0.17 -0.90 124

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Table B-17. Executive Summary-Non-Entrepreneurial School Leaders (n=135) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Thought Vision 6.90 1.67 1 0.00 -0.80 Judgment 6.58 1.70 6 -0.22 -0.01 Evaluation 6.60 1.83 5 -0.33 -0.41 Influence Leadership 6.57 1.62 7 -0.39 0.70 Impact 5.50 1.83 10 0.29 -0.31 Communication 4.76 1.62 12 -0.08 -0.14 Adaptability Support 5.35 1.83 11 -0.22 -0.42 Resilience 5.79 1.75 9 -0.15 -0.03 Flexibility 5.92 2.15 8 -0.11 -0.30 Delivery Structure 6.85 1.86 2 -0.42 0.43 Drive 6.70 1.87 3 -0.18 -0.57 Implementation 5.67 1.83 4 -0.26 -0.24 Ratings acquiescence 6.77 1.90 ---0.59 0.29 Consistency of rankings 5.58 1.86 ---0.08 -0.31 Motive-talent agreement 5.32 1.88 ---0.14 -0.39 Normative-ipsative agreement 4.92 2.07 ---0.40 -0.82 125

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Table B-18. Psychometric Profile-Entre preneurial School Leaders (n=33) mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Inventive 6.70 1.75 7 -0.52 -0.60 Abstract 6.27 2.02 12 -0.37 -0.03 Strategic 7.55 2.22 1 -0.69 -0.53 Insightful 7.00 1.60 4 -0.81 1.21 Practically minded 5.55 2.19 29 -0.31 -0.93 Learning oriented 6.12 1.63 15 -0.79 0.16 Analytical 6.06 2.15 17 0.16 -0.63 Factual 6.06 2.03 17 -0.26 -0.54 Rational 5.06 2.10 33 0.25 -0.41 Purposeful 6.15 2.05 14 -0.46 -0.79 Directing 7.21 1.47 3 -0.77 0.81 Empowering 7.24 1.46 2 -0.13 -1.06 Convincing 5.09 1.76 34 0.09 -0.57 Challenging 4.70 2.07 36 0.39 -0.25 Articulate 6.64 1.87 7 -0.57 -0.12 Self promoting 5.61 1.98 26 0.76 -0.28 Interactive 5.58 2.09 27 -0.05 -0.36 Engaging 5.21 1.63 32 -0.34 -0.57 Involving 6.00 2.07 19 -0.08 -0.41 Attentive 5.76 1.58 22 0.08 -0.27 Accepting 6.12 1.43 15 -0.34 -0.87 Resolving 4.88 1.51 35 0.26 -0.09 Self-assured 6.55 1.74 9 -0.11 0.06 Composed 5.70 1.91 23 0.07 -0.66 Receptive 5.79 1.75 21 -0.01 -0.84 Positive 5.97 1.78 20 -1.01 0.30 Change oriented 6.36 2.04 10 -0.56 0.11 Organized 6.15 1.96 13 -0.19 -0.55 Principled 6.36 1.92 10 -0.78 0.44 Activity oriented 5.58 1.91 27 -0.17 -1.07 Dynamic 6.85 2.11 6 -0.54 -0.29 Striving 7.00 1.76 4 -0.27 -0.54 Enterprising 5.67 2.03 25 -0.26 -0.64 Meticulous 5.48 1.94 30 0.12 -0.94 Reliable 5.70 1.93 23 -0.48 -0.29 Compliant 5.24 1.60 31 0.32 -0.35 126

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Table B-19. Psychometric Profile-Non-Entr epreneurial School Leaders (n=135) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Inventive 6.39 1.73 12 0.13 -0.39 Abstract 6.42 1.61 9 0.01 -0.26 Strategic 7.30 1.86 1 -0.52 -0.40 Insightful 6.84 1.55 6 -0.16 -0.19 Practically minded 5.90 1.84 21 -0.53 0.02 Learning oriented 6.16 1.63 17 -0.28 -0.20 Analytical 7.04 1.82 2 -0.49 -0.08 Factual 6.34 1.95 13 -0.51 0.07 Rational 6.21 1.84 16 -0.22 -0.71 Purposeful 6.23 1.79 15 -0.14 -0.22 Directing 6.80 1.68 7 -0.55 0.72 Empowering 6.16 1.77 17 -0.07 0.14 Convincing 5.49 1.88 28 0.35 -0.21 Challenging 4.73 1.92 35 0.78 0.51 Articulate 6.43 1.82 8 -0.22 -0.40 Self promoting 4.51 1.68 36 0.93 1.03 Interactive 5.31 1.84 31 -0.11 -0.55 Engaging 4.91 1.88 34 -0.23 -0.50 Involving 5.42 2.18 30 -0.22 -0.57 Attentive 5.27 2.14 32 -0.18 -0.58 Accepting 5.68 1.91 27 -0.34 -0.32 Resolving 5.16 1.84 33 -0.10 0.04 Self-assured 6.42 1.60 9 -0.11 0.15 Composed 5.73 1.83 24 -0.12 -0.49 Receptive 5.67 1.88 25 -0.28 -0.01 Positive 5.67 1.99 25 -0.17 -0.59 Change oriented 6.27 1.78 14 -0.26 -0.35 Organized 6.42 1.65 9 -0.56 0.13 Principled 6.99 1.46 4 -0.44 -0.41 Activity oriented 6.12 1.69 19 -0.22 0.37 Dynamic 6.90 1.94 5 -0.27 -0.06 Striving 7.03 1.71 3 -0.49 -0.31 Enterprising 5.84 1.93 23 -0.02 -0.59 Meticulous 5.91 1.85 20 -0.33 -0.45 Reliable 5.87 1.74 22 -0.34 -0.26 Compliant 5.43 1.85 29 0.21 -0.47 127

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Table B-20. Competency Potential Profile -Entrepreneurial School Leaders (n=33) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achieving success 6.94 1.87 4 -0.85 0.47 Adjusting to change 6.88 1.74 5 -1.10 1.84 Communicating with people 5.70 2.07 11 0.04 -0.32 Creating innovation 7.21 1.85 2 -0.37 -0.53 Evaluating problems 6.45 1.84 7 0.13 -0.73 Executing assignments 5.42 2.02 12 0.25 -0.27 Making judgments 7.06 1.43 3 -1.03 2.89 Presenting information 6.45 1.56 7 0.04 -1.33 Projecting confidence 6.21 1.53 9 -0.86 0.17 Providing leadership 7.24 1.60 1 -0.76 0.30 Providing support 6.09 1.66 10 -0.66 -0.44 Structuring tasks 6.67 1.75 6 -0.60 0.25 Table B-21. Competency Potential Profile-N on-Entrepreneurial School Leaders (n=135) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achieving success 6.95 1.79 4 -0.39 -0.35 Adjusting to change 6.49 1.77 7 -0.41 -0.06 Communicating with people 5.15 1.83 12 -0.23 -0.23 Creating innovation 7.01 1.70 2 0.01 -0.94 Evaluating problems 7.20 1.77 1 -0.41 -0.38 Executing assignments 5.77 1.80 10 -0.24 -0.32 Making judgments 7.07 1.61 3 -0.50 0.48 Presenting information 6.24 1.70 8 -0.46 0.15 Projecting confidence 6.24 1.83 8 -0.36 -0.04 Providing leadership 6.73 1.64 6 -0.66 0.85 Providing support 5.49 2.10 11 -0.37 -0.16 Structuring tasks 6.91 1.73 5 -0.60 0.89 Table B-22. Entrepreneurial Potential Summ ary-Entrepreneurial Sc hool Leaders (n=33) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Getting in the zone 7.06 1.92 2 -1.11 0.98 Seeing possibilities 7.73 1.66 1 -0.32 -0.73 Creating superior opportunities 6.39 1.84 6 -0.56 0.07 Staying in the zone 7.03 1.60 3 -0.71 1.33 Opening up to the world 6.45 1.84 5 -0.22 -0.64 Building capacity 7.03 1.38 3 -0.81 1.09 128

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Table B-23. Entrepreneurial Potential Summ ary-Entrepreneurial Sc hool Leaders (n=33) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Getting in the zone 6.97 1.78 2 -0.48 -0.23 Seeing possibilities 7.43 1.68 1 -0.55 -0.05 Creating superior opportunities 6.86 1.74 4 -0.30 -0.31 Staying in the zone 6.92 1.63 3 -0.55 0.13 Opening up to the world 6.10 1.82 6 -0.48 0.12 Building capacity 6.67 1.81 5 -0.32 0.11 Table B-24. Entrepreneurial Potential Prof ile-Entrepreneurial Sc hool Leaders (n=33) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achievement drive 7.33 1.59 2 -0.60 0.45 Compelling vision 6.55 1.63 13 0.13 -0.12 Energy 6.82 2.08 8 -1.01 0.63 Action oriented 6.61 2.09 12 -0.85 -0.08 Big picture 7.76 1.71 1 -0.50 -0.82 Options thinking 7.00 1.81 5 -0.37 0.09 Savvy 7.21 1.45 3 -1.20 3.14 Problem seeking 5.91 1.88 19 -0.28 -0.90 Synthesis 6.06 1.86 17 -0.23 -0.09 Problem solving 6.42 1.61 14 -0.45 -0.61 Delighting customers 5.64 2.16 21 0.09 -0.76 Focus 6.73 1.90 10 -0.33 -0.86 Positive mindset 6.67 1.59 11 -1.30 2.73 Self-determining 6.85 1.42 6 0.27 0.08 Persistence 6.39 1.46 15 -0.70 0.74 Expressing passion 6.85 1.65 6 0.00 -0.83 Purposeful networking 6.03 2.18 18 -0.41 -0.34 Creating partnerships 6.21 1.98 16 -0.44 -0.83 Building up the team 7.09 1.44 4 -0.52 0.94 Experiential learning 5.85 1.56 20 0.06 -0.65 Staying on track 6.76 1.79 9 -0.68 1.45 129

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Table B-25. Entrepreneurial Potential Profile -Non-Entrepreneurial School Leaders (n=135) Mean Std. Rank Skewness Kurtosis Dev. (Pearson) (Pearson) Achievement drive 7.27 1.72 2 -0.53 -0.31 Compelling vision 6.21 1.69 16 -0.14 -0.02 Energy 6.96 1.78 4 -0.44 0.30 Action oriented 6.49 1.91 13 -0.42 -0.08 Big picture 7.41 1.70 1 -0.55 -0.12 Options thinking 6.76 1.61 6 -0.10 -0.90 Savvy 7.24 1.79 3 -0.89 0.50 Problem seeking 5.82 1.94 19 -0.30 -0.39 Synthesis 6.70 1.80 9 -0.37 -0.25 Problem solving 6.64 1.57 10 -0.18 -0.22 Delighting customers 5.80 1.79 20 -0.07 -0.62 Focus 6.79 1.70 5 -0.46 0.58 Positive mindset 6.61 1.76 11 -0.68 0.27 Self-determining 6.71 1.77 8 -0.41 -0.03 Persistence 6.56 1.88 12 -0.37 0.03 Expressing passion 5.99 1.69 18 -0.26 0.07 Purposeful networking 5.60 1.85 21 -0.25 -0.25 Creating partnerships 6.35 1.81 14 -0.43 0.25 Building up the team 6.24 1.86 15 -0.37 0.04 Experiential learning 6.18 1.64 17 -0.30 0.24 Staying on track 6.73 1.77 7 -0.19 -0.45 130

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APPENDIX C FISHERS LSD CONTRASTS Table C-1. Entrepreneurial Potential Summary Contrasts Diff. Pr. > Diff Sign. Seeing possibilities vs Opening up to the world 1.32 < 0.0001 Yes Seeing possibilities vs Build ing capacity 0.75 < 0.0001 Yes Seeing possibilities vs Creating s uperior opportunities 0.72 0.000 Yes Seeing possibilities vs Staying in the zone 0.55 0.004 Yes Seeing possibilities vs Getting in the zone 0.50 0.008 Yes Getting in the zone vs Opening up to the world 0.82 < 0.0001 Yes Getting in the zone vs Building capacity 0.25 0.187 No Getting in the zone vs Creating superior opportunities 0.22 0.245 No Getting in the zone vs Staying in the Zone 0.05 0.801 No Staying in the zone vs Opening up to the world 0.77 < 0.0001 Yes Staying in the zone vs Building capacity 0.20 0.285 No Staying in the zone vs Creating superior opportunities 0.17 0.362 No Creating superior opportunities vs Opening up to the world 0.60 0.002 Yes Creating superior opportunities vs Building capacity 0.03 0.875 No Building capacity vs Opening up to the world 0.57 0.003 Yes (critical value = 1.96) Table C-2. Entrepreneurial Potential Profile Contrasts Diff. Pr. > Diff Sign. Big picture vs Purposeful networking 1.80 <0.0001 Yes Big picture vs Delighting customers 1.71 <0.0001 Yes Big picture vs Problem seeking 1.64 <0.0001 Yes Big picture vs Experiential learning 1.37 <0.0001 Yes Big picture vs Expressing passion 1.32 <0.0001 Yes Big picture vs Compelling vision 1.20 <0.0001 Yes Big picture vs Creating partnerships 1.16 <0.0001 Yes Big picture vs Building up the team 1.08 <0.0001 Yes Big picture vs Action oriented 0.97 <0.0001 Yes Big picture vs Persistence 0.96 <0.0001 Yes Big picture vs Synthesis 0.90 <0.0001 Yes Big picture vs Problem solving 0.88 <0.0001 Yes Big picture vs Positive mindset 0.86 <0.0001 Yes Big picture vs Staying on track 0.75 0.00 Yes Big picture vs Self-determining 0.74 0.00 Yes Big picture vs Focus 0.71 0.00 Yes Big picture vs Options thinking 0.68 0.00 Yes Big picture vs Energy 0.55 0.00 Yes Big picture vs Savvy 0.25 0.20 No Big picture vs Achievement drive 0.20 0.31 No (critical value = 1.96) 131

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Table C-2 (continued) Diff. Pr. > Diff Sign. Achievement drive vs Purposeful networking 1.60 <0.0001 Yes Achievement drive vs Delighting customers 1.52 <0.0001 Yes Achievement drive vs Problem seeking 1.45 <0.0001 Yes Achievement drive vs Experien tial learning 1.17 <0.0001 Yes Achievement drive vs Expressing passion 1.12 <0.0001 Yes Achievement drive vs Compelling vision 1.01 <0.0001 Yes Achievement drive vs Creating partnerships 0.96 <0.0001 Yes Achievement drive vs Building up the team 0.88 <0.0001 Yes Achievement drive vs Action Oriented 0.77 <0.0001 Yes Achievement drive vs Persistence 0.76 <0.0001 Yes Achievement drive vs Synthesis 0.71 0.00 Yes Achievement drive vs Problem solving 0.68 0.00 Yes Achievement drive vs Positive mindset 0.66 0.00 Yes Achievement drive vs Staying on track 0.55 0.00 Yes Achievement drive vs Self-determining 0.55 0.00 Yes Achievement drive vs Focus 0.51 0.01 Yes Achievement drive vs Options thinking 0.48 0.01 Yes Achievement drive vs Energy 0.36 0.06 No Achievement drive vs Savvy 0.05 0.78 No Savvy vs Purposeful networking 1.15 <0.0001 Yes Savvy vs Delighting customers 1.46 <0.0001 Yes Savvy vs Problem seeking 1.39 <0.0001 Yes Savvy vs Experiential learning 1.12 <0.0001 Yes Savvy vs Expressing passion 1.07 <0.0001 Yes Savvy vs Compelling vision 0.95 <0.0001 Yes Savvy vs Creating partnerships 0.91 <0.0001 Yes Savvy vs Building up the team 0.83 <0.0001 Yes Savvy vs Action oriented 0.72 0.00 Yes Savvy vs Persistence 0.71 0.00 Yes Savvy vs Synthesis 0.65 0.00 Yes Savvy vs Problem solving 0.63 0.00 Yes Savvy vs Positive mindset 0.61 0.00 Yes Savvy vs Staying on track 0.50 0.01 Yes Savvy vs Self-determining 0.49 0.01 Yes Savvy vs Focus 0.46 0.02 Yes Savvy vs Options thinking 0.43 0.03 Yes Savvy vs Energy 0.30 0.12 No (critical value = 1.96) 132

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Table C-2 (continued). Diff. Pr. > Diff Sign. Energy vs Purposeful networking 1.24 <0.0001 Yes Energy vs Delighting customers 1.16 <0.0001 Yes Energy vs Problem seeking 1.09 <0.0001 Yes Energy vs Experiential learning 0.82 <0.0001 Yes Energy vs Expressing passion 0.77 <0.0001 Yes Energy vs Compelling vision 0.65 0.00 Yes Energy vs Creating partnerships 0.61 0.00 Yes Energy vs Building up the team 0.52 0.01 Yes Energy vs Action oriented 0.42 0.03 Yes Energy vs Persistence 0.40 0.04 Yes Energy vs Synthesis 0.35 0.07 No Energy vs Problem solving 0.33 0.09 No Energy vs Positive mindset 0.30 0.12 No Energy vs Staying on track 0.20 0.31 No Energy vs Self-determining 0.19 0.32 No Energy vs Focus 0.15 0.42 No Energy vs Options thinking 0.13 0.52 No Options thinking vs Purposeful networking 1.12 <0.0001 Yes Options thinking vs Delighting customers 1.04 <0.0001 Yes Options thinking vs Problem seeking 0.96 <0.0001 Yes Options thinking vs Experien tial learning 0.69 0.00 Yes Options thinking vs Expressing passion 0.64 0.00 Yes Options thinking vs Compelling vision 0.52 0.01 Yes Options thinking vs Creating partnerships 0.48 0.01 Yes Options thinking vs Building up the team 0.40 0.04 Yes Options thinking vs Action oriented 0.29 0.13 No Options thinking vs Persistence 0.28 0.15 No Options thinking vs Synthesis 0.23 0.24 No Options thinking vs Problem solving 0.20 0.29 No Options thinking vs Positive mindset 0.18 0.35 No Options thinking vs Stayi ng on track 0.07 0.71 No Options thinking vs Self-determining 0.07 0.73 No Options thinking vs Focus 0.03 0.88 No (critical value = 1.96) 133

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Table C-2 (continued). Diff. Pr. > Diff Sign. Focus vs Purposeful networking 1.09 <0.0001 Yes Focus vs Delighting customers 1.01 <0.0001 Yes Focus vs Problem seeking 0.93 <0.0001 Yes Focus vs Experiential learning 0.66 0.00 Yes Focus vs Expressing passion 0.61 0.00 Yes Focus vs Compelling vision 0.49 0.01 Yes Focus vs Creating partnerships 0.45 0.02 Yes Focus vs Building up the team 0.37 0.06 Yes Focus vs Action oriented 0.26 0.17 No Focus vs Persistence 0.25 0.20 No Focus vs Synthesis 0.20 0.31 No Focus vs Problem solving 0.17 0.37 No Focus vs Positive mindset 0.15 0.44 No Focus vs Staying on track 0.04 0.83 No Focus vs Self-determining 0.04 0.85 No Self-determining vs Purposeful networking 1.05 <0.0001 Yes Self-determining vs Delighting customers 0.97 <0.0001 Yes Self-determining vs Problem seeking 0.90 <0.0001 Yes Self-determining vs Experiential learning 0.62 0.00 Yes Self-determining vs Expressing passion 0.58 0.00 Yes Self-determining vs Compelling vision 0.46 0.02 Yes Self-determining vs Creating partnerships 0.42 0.03 Yes Self-determining vs Building up the team 0.33 0.08 No Self-determining vs Action oriented 0.23 0.24 No Self-determining vs Persistence 0.21 0.27 No Self-determining vs Synthesis 0.16 0.41 No Self-determining vs Problem solving 0.14 0.48 No Self-determining vs Positive mindset 0.11 0.56 No Self-determining vs Staying on track 0.01 0.98 No Staying on track vs Purposeful networking 1.05 <0.0001 Yes Staying on track vs Delighting customers 0.96 <0.0001 Yes Staying on track vs Problem seeking 0.89 <0.0001 Yes Staying on track vs Experiential learning 0.62 0.00 Yes Staying on track vs Expressing passion 0.57 0.00 Yes Staying on track vs Compelling vision 0.45 0.02 Yes Staying on track vs Creating partnerships 0.41 0.03 Yes Staying on track vs Building up the team 0.33 0.09 No Staying on track vs Action oriented 0.22 0.25 No Staying on track vs Persistence 0.21 0.28 No Staying on track vs Synthesis 0.15 0.42 No Staying on track vs Problem solving 0.13 0.50 No Staying on track vs Positive mindset 0.11 0.58 No (critical value = 1.96) 134

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Table C-2 (continued). Diff. Pr. > Diff Sign. Positive mindset vs Purposeful networking 0.94 <0.0001 Yes Positive mindset vs Delighting customers 0.86 <0.0001 Yes Positive mindset vs Problem seeking 0.79 <0.0001 Yes Positive mindset vs Experiential learning 0.51 0.01 Yes Positive mindset vs Expressing passion 0.46 0.02 Yes Positive mindset vs Compelling vision 0.35 0.07 No Positive mindset vs Creating partnerships 0.30 0.12 No Positive mindset vs Building up the team 0.22 0.25 No Positive mindset vs Action oriented 0.11 0.56 No Positive mindset vs Persistence 0.10 0.60 No Positive mindset vs Synthesis 0.05 0.81 No Positive mindset vs Problem solving 0.02 0.90 No Problem solving vs Purposeful networking 0.92 <0.0001 Yes Problem solving vs Delighting customers 0.83 <0.0001 Yes Problem solving vs Problem seeking 0.76 <0.0001 Yes Problem solving vs Experiential learning 0.49 0.01 Yes Problem solving vs Expressing passion 0.44 0.02 Yes Problem solving vs Compelling vision 0.32 0.10 No Problem solving vs Creating partnerships 0.28 0.15 No Problem solving vs Building up the team 0.20 0.31 No Problem solving vs Action oriented 0.09 0.64 No Problem solving vs Persistence 0.08 0.69 No Problem solving vs Synthesis 0.02 0.90 No Synthesis vs Purposeful networking 0.89 <0.0001 Yes Synthesis vs Delighting customers 0.81 <0.0001 Yes Synthesis vs Problem seeking 0.74 0.00 Yes Synthesis vs Experiential learning 0.46 0.02 Yes Synthesis vs Expressing passion 0.42 0.03 Yes Synthesis vs Compelling vision 0.30 0.12 No Synthesis vs Creating partnerships 0.26 0.18 No Synthesis vs Building up the team 0.17 0.37 No Synthesis vs Action oriented 0.07 0.73 No Synthesis vs Persistence 0.05 0.78 No Persistence vs Purposeful networking 0.84 <0.0001 Yes Persistence vs Delighting customers 0.76 <0.0001 Yes Persistence vs Problem seeking 0.68 0.00 Yes Persistence vs Experiential learning 0.41 0.03 Yes Persistence vs Expressing passion 0.36 0.06 No Persistence vs Compelling vision 0.24 0.21 No Persistence vs Creating partnerships 0.20 0.29 No Persistence vs Building up the team 0.12 0.54 No Persistence vs Action oriented 0.01 0.95 No (critical value = 1.96) 135

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Table C-2 (continued). Diff. Pr. > Diff Sign. Action oriented vs Purposeful networking 0.83 <0.0001 Yes Action oriented vs Delighting customers 0.74 0.00 Yes Action oriented vs Problem seeking 0.67 0.00 Yes Action oriented vs Experien tial learning 0.40 0.04 Yes Action oriented vs Expressing passion 0.35 0.07 No Action oriented vs Compelling vision 0.23 0.23 No Action oriented vs Creating partnership 0.19 0.32 No Action oriented vs Building up the team 0.11 0.58 No Building up the team vs Purpos eful networking 0.72 0.00 Yes Building up the team vs Delighting customers 0.64 0.00 Yes Building up the team vs Problem seeking 0.57 0.00 Yes Building up the team vs Experi ential learning 0.29 0.13 No Building up the team vs Expr essing passion 0.24 0.21 No Building up the team vs Comp elling vision 0.13 0.52 No Building up the team vs Creating partnerships 0.08 0.67 No Creating partnerships vs Purpos eful networking 0.64 0.00 Yes Creating partnerships vs Deli ghting customers 0.55 0.00 Yes Creating partnerships vs Pr oblem seeking 0.48 0.01 Yes Creating partnerships vs Expe riential learning 0.21 0.28 No Creating partnerships vs Expr essing passion 0.16 0.41 No Creating partnerships vs Compelling vision 0.04 0.83 No Compelling vision vs Purposef ul networking 0.60 0.00 Yes Compelling vision vs Delighting customers 0.51 0.01 Yes Compelling vision vs Problem seeking 0.44 0.02 Yes Compelling vision vs Experien tial learning 0.17 0.39 No Compelling vision vs Expressing passion 0.12 0.54 No Expressing passion vs Purposef ul networking 0.84 0.01 Yes Expressing passion vs Delighting customers 0.39 0.04 Yes Expressing passion vs Problem seeking 0.32 0.10 No Expressing passion vs Experien tial learning 0.05 0.81 No Experiential learning vs Purpos eful networking 0.43 0.03 Yes Experiential learning vs Deli ghting customers 0.35 0.07 No Experiential learning vs Probl em seeking 0.27 0.16 No Problem seeking vs Purposeful networking 0.15 0.42 No Problem seeking vs Delighting customers 0.07 0.71 No Delighting customers vs Purposeful networking 0.08 0.67 No (critical value = 1.96) 136

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BIOGRAPHICAL SKETCH Matthew J.G. Basham received his baccalaure ate degree from Oakland University in Rochester, Michigan, in December 1990. He then attended the University of Florida for his masters degree and graduated in December 1993. Basham then began work in Tarpon Springs, Florida as a technical writer-pack aging engineer-training director. He then went to work for Pinellas County Schools, as a department head of computer electronics at the Pinellas Technical Education Center (vocational education cente r). After this, he began teaching at St. Petersburg College in computer electronics first as a faculty member and later as a program director. During his tenure at St. Petersburg College, Basham completed his doctorate from the University of Florida in August 2007. 153