Effects of Recruiter Characteristics on Recruiting Effectiveness in Division I Women's Soccer Marshall J

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2011 Recruiting in College Sports: Effects of Recruiter Characteristics on Recruiting Effectiveness in Division I Women's Soccer Marshall J. Magnusen

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COLLEGE OF EDUCATION

RECRUITING IN COLLEGE SPORTS: EFFECTS OF RECRUITER

CHARACTERISTICS ON RECRUITING EFFECTIVENESS

IN DIVISION I WOMEN‘S SOCCER

MARSHALL J. MAGNUSEN

A Dissertation submitted to the Department of Sport Management in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Degree Awarded: Fall Semester, 2011

Marshall James Magnusen defended this dissertation on August 2, 2011.

The members of the supervisory committee were:

Michael Mondello Professor Directing Dissertation

Gerald R. Ferris University Representative

Yu Kyoum Kim Committee Member

Pamela L. Perrewé Committee Member

The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with university requirements.

I dedicate this to my wife.

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ACKNOWLEDGEMENTS

The completion of this dissertation would not have been possible without the tremendous assistance from my committee. These individuals have been my stalwart supporters. I am truly honored to have learned so much from them during my time at the Florida State University. Much thanks to my primary advisor, Dr. Michael Mondello. I am indebted for his advice, encouragement, and support. Next, I would like to give special thanks to the dynamic duo of Drs. Ferris and Perrewé. Both of these individuals have been attentive advisors, guides, and ardent supporters. Without them, I would not have been able to get through the most challenging days of my dissertation process. I would also like to thank Dr. Kim. He has been most helpful, accommodating, and insightful. I remain in awe of his work ethic; it served as a constant reminder that I should remain diligent and never lose sight of the task at hand. Additional thanks are in order for the support I received from the College of Education and the Sport Management Program. Under the guidance of Dr. James, the program at FSU has evolved into the best in the country. Finally, for my wife…words cannot express my wholehearted appreciation of your patience and sacrifice. Above all, your devotion and dedication allowed me to endure this doctoral process. Thank you.

TABLE OF CONTENTS

List of Tables ...... viii

List of Figures ...... ix

Abstract ...... x

1. CHAPTER ONE ...... 1 1.1 Recruiting and Intercollegiate Athletics ...... 3 1.1.1 Student-Athlete Selection Decision Criteria ...... 3 1.1.2 Qualitative Inquiry and Recruiting Student Athletes ...... 7 1.2 Statement of Problem ...... 8 1.3 Purpose and Intended Contributions of the Research ...... 12 1.4 Research Questions ...... 12 1.5 Organization of the Study ...... 13

2. CHAPTER TWO ...... 14 2.1 Theoretical Foundations...... 16 2.2 Recruiter Characteristics ...... 18 2.2.1 Recruiter Function ...... 20 2.2.2 Recruiter Personality and Behavioral Traits ...... 20 2.2.3 Recruiter Demographics ...... 22 2.3 Context Factors ...... 22 2.3.1 Recruit Category ...... 24 2.3.2 Athletic Category ...... 25 2.3.3 Academic Category ...... 29 2.3.4 External Category ...... 30 2.4 Recruit and Influential Agent Fit Perceptions ...... 35 2.4.1 Overview of Fit Perceptions ...... 36 2.4.2 Recruit and Influential Agent Fit Interaction ...... 38 2.5 Recruiting Outcomes ...... 39 2.5.1 Job Pursuit Intentions ...... 40 2.5.2 Job-Organization Attraction...... 40 2.5.3 Acceptance Intentions ...... 41 2.5.4 Job Choice Decisions ...... 42 2.6 Research Model and Hypothesis Development ...... 43 2.7 Theoretical Foundations of the Research Model ...... 45 2.8 Recruiter Political Skill and Recruiting Effectiveness...... 48 2.8.1 Defining Political Skill ...... 49 2.8.2 Dimensions of Political Skill ...... 50 2.8.3 Distinctiveness of Political Skill ...... 52 2.8.4 Dispositional and Personal Ability Antecedents of Political Skill ...... 53

2.8.5 Direct and Interaction Effects of Political Skill ...... 53 2.8.6 Impact of Recruiter‘s Political Skill on Recruiting Effectiveness ...... 55 2.9 Recruiter Personality and Recruiting Effectiveness ...... 56 2.9.1 Overview of the Big Five Personality Dimensions...... 57 2.9.2 Proactive Personality: A Comparison and Cause for Exclusion ...... 60 2.9.3 Impact of Recruiter Personality on Recruiting Effectiveness ...... 62 2.10 Recruiter Behavioral Integrity and Recruiting Effectiveness ...... 62 2.10.1 Defining Behavioral Integrity ...... 62 2.10.2 Differentiating Behavioral Integrity and Reputation ...... 63 2.10.3 Outcomes of Behavioral Integrity ...... 63 2.10.4 Impact of Recruiter Behavioral Integrity on Recruiting Effectiveness ...... 64 2.11 Recruiter Performance Reputation and Recruiting Effectiveness ...... 64 2.11.1 Clarification and Distinctiveness of Reputation ...... 65 2.11.2 Overview of Organizational Reputation ...... 66 2.11.3 Overview of Personal Reputation ...... 70 2.11.4 Impact of Performance Reputation on Recruiting Effectiveness ...... 72 2.12 Research Hypotheses ...... 73

3. METHOD ...... 75 3.1 Research Design...... 75 3.2 Participants and Procedures ...... 75 3.2.1 Sampling ...... 75 3.2.2 Participants ...... 75 3.2.3 Procedures ...... 76 3.3 Measures ...... 77 3.3.1 Political Skill ...... 77 3.3.2 Big Five Personality ...... 77 3.3.3 Behavioral Integrity ...... 78 3.3.4 Performance Reputation...... 78 3.3.5 Recruiting Effectiveness (Outcome) ...... 79 3.4 Analysis...... 80

4. RESULTS ...... 82 4.1 Descriptive Statistics ...... 82 4.2 Multiple Regression Statistics...... 88

5. DISCUSSION ...... 94 5.1 Conceptual and Theoretical Implications ...... 99 5.2 Managerial Implications ...... 100 5.3 Limitations and Future Research Directions ...... 101 5.4 Summary ...... 106

Appendix ...... 107 A. Consent to Participate ...... 107 B. Letter of Assistance ...... 110

C. Head Coach (Recruiter) Questionnaire ...... 112

REFERENCES ...... 122 BIOGRAPHICAL SKETCH ...... 149

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LIST OF TABLES

1.1 Student-Athlete College Selection Factors ...... 4

4.1 Head Women‘s Soccer Coaches‘ Athletic Conference Distribution ...... 83

4.2 Descriptive Statistics for Recruiter (Head Coach) Political Skill ...... 84

4.3 Descriptive Statistics for Recruiter (Head Coach) Personality ...... 85

4.4 Descriptive Statistics for Recruiter (Head Coach) Behavioral Integrity ...... 87

4.5 Descriptive Statistics for Recruiter (Head Coach) Performance Reputation ...... 87 Characteristics………………………………………………………………….114

4.6 Descriptive Statistics for Recruiting Outcome (Total Quality) ...... 87

4.7 Correlations of Recruiter Predictors and Recruiting Effectiveness ...... 90

4.8 Mean (M), Standard Deviation (SD), and Reliability (α) of Recruiter Characteristics ...... 91

4.9 Regression Analysis for Recruiter Predictors on Recruiting Effectiveness ...... 93

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LIST OF FIGURES

2.1 Recruiter-centered Model of Recruiting Effectiveness in College Sports ...... 16

2.2 Context Categories and Key Factors ...... 24

2.3 Recruit – Influential Agent Fit Interaction ...... 39

2.4 Direct Effects of Recruiter Characteristics on Recruiting Effectiveness ...... 44

ABSTRACT

A multitude of studies have examined key factors influencing college or university selection by student-athletes. Much less attention, however, has been given to the roles of athletic recruiters and how their qualities and characteristics impact recruiting outcomes. Therefore, the purpose of this investigation was to examine the impact of recruiter (head coach) characteristics on recruiting effectiveness (total quality of recruits signed) in the context of NCAA Division I women‘s soccer. Recruiter characteristics included in this study were political skill, the Big Five personality dimensions (i.e., extraversion, agreeableness, conscientiousness, neuroticism, openness), behavioral integrity, and two performance reputation characteristics (i.e., head coach career record and final team NCAA rank). Over 130 (N = 131) head women‘s soccer coaches participated in this study. The direct effect of these nine predictor variables on the outcome of total quality of recruits signed (recruiting effectiveness) was assessed using multiple regression analysis. It was determined from the results that six of the nine recruiter characteristics (i.e., political skill, agreeableness, neuroticism, behavioral integrity, career record, and NCAA rank) had a significant impact on recruiting effectiveness.

CHAPTER ONE INTRODUCTION

One of the most important processes to the long-term success of an organization and its ability to achieve a sustained competitive advantage is the recruitment and training of premium talent (Barney, 1991; Becker & Huselid, 1998; Crook, Todd, Combs, Woehr, & Ketchen, 2011; Hegarty, 1995; Huselid, 1995). Over twenty years ago, Schneider (1987) argued this very point with the profound yet simple observation that people are the heart of successful organizations. Even though he did not have intercollegiate athletics in mind at the time, no place may his perspective be put on greater public display than the spectacle of National Collegiate Athletic Association (NCAA) sports in the United States (US). The recruiting of student-athletes in the US has been both a topic of interest as well as heated debate since the early 1900s. Today, recruiting is a media event. ESPN, for example, provided multiplatform coverage of the 2010 and 2011 National Letter of Intent Signing days for high school athletes with live blogging, full simulcast on ESPN360.com, and a two-set live studio show called: ESPNU Recruiting Insider: National Signing Day Presented by Under Armour. Nearly 100 years ago, recruiting was not a media spectacle; however, it was still a topic of heated debate. In 1929 the Carnegie Foundation for the Advancement of Teaching published a report that included a section classifying colleges and universities according to their degree and kind of athlete recruiting and subsidizing. This section provided an interesting, if not sobering look into the earliest days of competitive American sports. The report included estimates that one in seven college athletes received subsidization in the form of either a loan, scholarship, or some form of favorable arrangement for the athlete. Included in the report were several suggestions, one of which was the abolishment of recruiting from high schools. This suggestion went unheeded, and high school and college sports in the US have boomed into thriving multi-billion dollar sport industries. To illustrate this point, consider the following examples:  By in large, athletic facilities have been viewed as a great recruiting tool (Broughton, 2009), and from mid-1990 – 2005, campuses in the US spent over $15 billion on sports facilities (King, 2005).

 According to a financial report from the Chronicle of Higher Education, in a span of ten years (i.e., 1997 – 2007), almost half of all National Collegiate Athletic Association Division I (NCAA DI) athletic departments doubled or tripled their recruiting budgets. Furthermore, in 2007, the median football bowl series (FBS) football program spent nearly $650,000 on recruiting (Sander, 2008).  The high school and college athletics recruiting website and sports network, Rivals.com, was sold to Yahoo for around $100 million dollars (Duncan, 2007). A competing site, Scout.com, was sold to Fox Interactive Media, Inc. for around $60 million in 2005. Overall, anecdotal evidence, embedded journalistic accounts (e.g., Lewis, 2007; Feldman, 2007), and sport media reports (e.g., blogs, sport-related talk radio, print news coverage, television coverage on ESPN and Fox Sports) coalesce with theory and research evidence (e.g., Berkson, Ferris, & Harris, 2002; Berkson, Harris, & Ferris, 1999; Breaugh & Starke, 2000; Klenosky, Templin, & Troutman, 2001) into a collective message that recruiting effectiveness is most likely the product of some sort of combination of recruiter, recruit, organizational, job, and external (i.e., those factors, such as media attention, that are largely out of the control of individuals and organizations) characteristics. Incidentally, the significance of these areas is comparatively unknown, especially in the extant sport management literature. This is because most of the relevant sport-based scholarly literature has focused on student-athlete selection criteria (i.e., survey research about the factors student-athletes recall as most salient to their commitment decisions). Little orderly research has been conducted in the sport management discipline about recruiting and the multitude of factors that may have a significant impact on recruiting effectiveness (i.e., the quality as well as the quantity of recruits signed in the annual intercollegiate athletics recruiting cycle). This lack of research is surprising, especially in light of the vast amount of time, energy, and resources expended on recruiting student-athletes (e.g., Funk, 1991; Sander, 2008). In addition to surprising, it is also regrettable considering how recruiting effectiveness in a tight labor market is particularly applicable to contemporary athletic departments due to widespread financial turmoil in higher education and the pervasiveness of budget cuts –recruiting budgets being no exception (e.g., Schlabach, 2009; Viera, 2009). Thus, because athletic programs throughout the US have had to rethink their approach to

. finding athletes, the argument is made that in parallel, so too should the field of sport management rethink the state of the extant recruiting literature found within the discipline. Recruiting is more than just an applied area of inquiry; it is an established and valid area of serious academic query that dates back decades. What is therefore required is a line of sport management research that is focused on the advancement of both theory and empirical evidence as it pertains to recruiters, student-athletes, and the recruitment process as a whole. To this end, the subsequent content in this chapter is organized in the following manner. Provided first is a brief overview of the sport-based recruiting literature. Discussed thereafter are the problem statement, study purpose, and intended research contributions. Also explained are the underlying research questions that frame this scholarly inquiry. Recruiting and Intercollegiate Athletics In the field of management, a sizeable recruitment literature base has amassed in the decades following the seminal recruiting research of Alderfer and McCord (1970), which was the first study to empirically link recruiters to job-related outcomes (i.e., recruit‘s job intentions). Be that as it may, the recruitment literature is far from complete. In fact, several comprehensive reviews (e.g., Barber, 1998; Breaugh, 1992; Breaugh & Starke, 2000; Rynes, 1991; Wanous, 1992) have highlighted how recruitment scholars still have lingering concerns and frustration with the lack of more significant ―progress in understanding the recruitment process‖ (Breaugh & Starke, p. 406). Although it has not been noted quite so plainly in the sport-based literatures, the same concerns extend to the study of recruiting in intercollegiate athletics, if not more so because of the limited amount of scholarly attention this area has received. Student-Athlete Selection Decision Criteria Of the handful of peer-reviewed studies that have been published in academic journals or books (thus excluding unpublished master‘s theses and doctoral dissertations), most have been survey studies designed to ascertain the important choice factors of student-athletes. The recurring focus by researchers has been cross-sectional survey studies designed to identify subjective and objective factors impacting student-athletes‘ university selection decisions. Although the sport teams involved and exact research goals (e.g., comparing male and female student-athletes, comparing different NCAA divisions) benefit from a limited amount of diversity, the underlying objectives of these studies remains unchanged (i.e., identifying student- athlete selection decision factors).

Presented in Table 1.1 is a representative, but not exhaustive list of published studies that have empirically examined student-athlete selection factor/recruitment. For example, Letawsky Schneider, Pedersen, and Palmer (2003) assessed the college choice factors of NCAA Division I (DI) student-athletes and then compared their findings to college choice factors of non-athletes. The top three most influential factors for student-athletes were the degree-program options, head coach, and academic support services (first to third respectively). More recently, Pauline (2010) examined factors influencing male and female lacrosse players across NCAA DI, II, and III competitive levels. Key factors included career opportunities after graduation, academic reputation, social environment, and the head coach‘s personality/coaching style.

Table 1.1 Student-Athlete College Selection Factors

Authors Publication Sample Instrumentation Key Findings Mathes and Journal of 231 student- Student-Athlete Head coach and Gurney College athletes of Recruitment academics rated ―above (1985) Student revenue and non- Decision-Making average‖ in terms of Personnel revenue sports Survey (SARDS) importance. Doyle and Research 605 baseball and Simulated choice The most important Gaeth (1990) Quarterly softball NCAA task survey with a factors were the for Exercise Division I set of scholarship amount, and Sport recruits hypothetical athletic team, athletic programs atmosphere, location, described in terms and academic program. of researcher identified factors. Gabert, Hale, College 246 student- Student Athletes The most influential and Montalvo Admissions athletes from College Choice factor was head coach (1999) NCAA Division Profile Scale (athletic environment I, II, and NAIA (SACCPS) factor). Other results institutions (5 varied by competitive institutions total) level. Letawsky, College 126 student- Intercollegiate The top factors were Schneider, Student athletes Student-Athlete degree-program options, Pedersen, and Journal representing Questionnaire head coach, academic Palmer (2003) almost all first- (ISAQ) support services, type of year athletes community in which the from an NCAA campus is located, and DI institution school‘s sport traditions.

Table 1.1 – continued Student-Athlete College Selection Factors

Authors Publication Sample Instrumentation Key Findings Judson, International 245 incoming Self-designed For revenue and non- James, and Journal of scholarship and survey revenue generating Aurand Sport non-scholar sports, the top factor (2005) Management student-athletes was level of athletic on 20 competition. Important intercollegiate as well were academic athletic teams at reputation and desired 2 NCAA DI major offered. For universities (1 scholarship athletes, the major and 1 mid- most important factor major). was level of athletic competition. For non- scholarship athletes it was desired major offered. Also, it was reported that student- athlete selection criteria do not significantly differ between mid- major and major athletic conferences. Goss, Journal of 229 student- Student Athletes The top factor was the Jubenville, Marketing athletes from College Choice degree program offered. and Orejan for Higher NAIA and Profile Scale The second most (2006) Education NCAA DIII (SACCPS) influential factor was institutions (6 opportunity to play. The institutions total) third factor was head coach. Also, academic support services was reported as the fourth most influential factor. Kankey and The Smart 196 softball Self-designed The most highly rated Quarterman Journal student-athletes survey based on factors were availability (2007) from 10 NCAA Forseth (1987), of major or academic Division I Mathes and program, head coach, institutions in Gurney (1985), career opportunities Ohio and Reynaud after graduation, and (1998) social atmosphere of the team (not of the university/campus).

Table 1.1 – continued Student-Athlete College Selection Factors

Authors Publication Sample Instrumentation Key Findings Pauline, Book 320 collegiate Influential Winning programs was Pauline, and Chapter baseball Factors Survey the most influential Stevens students-athletes for Student- factor, followed by (2007) from 4 schools Athletes (IFSSA) opportunity to play and from each baseball specific NCAA Division facilities. Also, financial (I, II, and III) aid was found to be particularly important to DII as was academic strength to DIII. Pauline ICHPER-SD 792 male and Influential Top ranked factor was (2010) Journal of female NCAA Factors Survey career opportunities. Research lacrosse student- for Student Additional factors of athletes across Athletes – importance included NCAA DI, DII, Revised academic and overall and DIII (IFSSAR) reputation, major of competitive interest, social levels environment, and head coach‘s personality/ coaching style. Males were found to place greater importance on athletic/coaching staff factors than females. Differences were also reported between each competitive level. For example, DII and DIII lacrosse players reported academic factors to be more influential in their selection process than their DI counterparts.

On the whole, student-athlete selection decision factors have generally fallen into one of three overarching categories: (a) academic factors (i.e., university reputation, existence of preferred major), (b) athletic factors (i.e., opportunity to play, head coach personality, scholarship availability), and (c) social atmosphere factors (i.e., university/campus atmosphere,

. team social atmosphere). Although not detailed in Table 1, factors falling into one these three broad categories are also a recurring pattern in unpublished master‘s theses and doctoral dissertations about student-athlete choice factors (e.g., Forseth, 1987; Reynaud, 1998; Slabik, 1995; Widdison, 1982). In particular, after surveying almost 500 Division I volleyball players, Reynaud reported the top five factors were: (a) scholarship offer, (b) academic reputation, (c) head coach, (d) existence of preferred academic major, and (e) current roster of players. Furthermore, many of the factors frequently selected by student-athletes have also been selected by non student-athletes. Economic, educational, and social factors have all been found to be influential in students‘ decisions to attend a particular university (Canale, Dunlap, Britt, and Donahue, 1996; Dixon & Martin, 1991; Hossler, Schmit, & Vesper, 1999). Also interesting is that intercollegiate athletic success, such as a national championships in high-profile sports like football and basketball, has been linked (albeit limitedly) to short-term increases in the number of student applications to the university of the championship team (Murphy & Trandel, 1994; Pope & Pope, 2009; Toma & Cross, 1998). Coined by the media as ―the Flutie Effect‖, exploring the uptick in the quantity and quality of student applications after a championship (or high-profile) season gained national exposure after Boston College quarterback Doug Flutie won the Heisman Trophy in 1984, and it was alleged applications to the school rose by 30% the following year. The impact of the Flutie Effect has been primarily anecdotal, although there is evidence supportive of the phenomenon. Notably, Pope and Pope (2009) reported that success in basketball and football significantly increased the quantity of applications (2 – 8%) of universities with top 20 athletic programs (in these two respective sports). Qualitative Inquiry and Recruiting Student-Athletes Most of the research about student-athlete selection decisions has been grounded in quantitative research methods. Even so, there are rare exceptions to the cross-sectional approaches so often employed in sport management recruiting research. One exception was a means-end investigation of student-athlete school choice conducted by Klenosky et al. (2001). Instead of focusing on the extent to which specific factors were important in students‘ school- choice decisions, they ―focused on examining the means-end relationships that link the attributes to desired benefits and higher level personal values, thus providing a perspective for understanding how and why attributes are perceived as important‖ (Klenosky et al., p. 104).

More precisely, after interviewing 27 football bowl series (FBS) football players, the researchers reported the most important predictor of school choice was the coaching staff because it provided the student-athlete with an opportunity to develop, participate in athletic competition, and feel comfortable with the school. In addition to Klenosky et al. (2001), a more contemporary exception is a study by Fondren (2010). Her study, which was grounded in a sociological approach to recruiting, considered the identity and history of the University of Mississippi (Ole Miss Rebels) and how rivals of Ole Miss engage in negative recruiting by highlighting the school‘s history steeped in Southern Confederacy (i.e., the stigma of a racist past). After conducting in-depth interviews with both coaches and recruits (including those who accepted as well as turned down offers), Fondren reported several key findings about what specific types of negative recruiting techniques are used against Ole Miss. Examples included: Ole Miss has a racist past, still has strained race relations, and represents an ―elitist university catering to upper-middle class whites‖ (Fondren, p. 171). Yet, despite this past, the Rebels still have been able to recruit talented athletes. This result lends support to the notion that the coaches and administrators for Ole Miss do an effective job of countering such negative tactics through a variety of approaches, including coping and empowering strategies (Fondren). Statement of the Problem Taken as a whole, the body of literature on intercollegiate athletic recruiting is comparatively small and largely uniform in that the focus of these studies is most commonly student-athlete selection criteria among different sports and competitive levels. Thus, there are several problems facing the study of recruiting in both the business and sport management literatures. What follows is an explanation of several of these research limitations. One area that merits more extensive scholarly consideration from sport scholars is addressing the lack of an overarching conceptual framework guiding student-athlete research. Indeed, there is a lack of a comprehensive conceptual guide that provides sport management researchers with a detailed presentation of the various factors (i.e., recruiter, recruit, organizational, job, and external) that may independently as well as jointly affect recruiting effectiveness. The current arrays of sport-based studies are revealing and important research contributions helping to advance the study of recruiting and student-athlete selection decisions in college athletics. At the same time, however, research in this area would still benefit greatly from

. the creation of a detailed and wide-ranging framework (as seen in the business literature with Breaugh, 1992; Breaugh & Starke, 2000; Rynes, 1991) that could guide future scholarly investigations about recruiting in college athletics. A second limitation with the extant literature is the lack of in-depth exploration of individual aspects of the overall recruiting process (i.e., role of the recruiter) and how they impact specific recruiting outcomes such as organization attraction, acceptance intentions, and university choice. The main objective of most of the aforementioned student-athlete studies (e.g., Judson et al., 2005; Letawsky et al., 2005; Pauline et al., 2007; Pauline, 2010) was identifying specific factors (e.g., athletic scholarship, degree-options, playing time, academic reputation) that are important to student-athletes‘ selection decisions. In contrast, minimal attention has been paid to extensively examining the impact of specific factors, such as recruiters and ―why‖ and ―how‖ they are influential in student-athletes‘ decision-making processes. Incidentally, this limitation holds true for both the sport and mainstream management and personnel psychology disciplines (Breaugh & Starke, 2000; Chapman, Uggerslev, Carroll, Piasentin, & Jones, 2005). Lending support to this assertion is that in the most current meta- analytic review of the correlates of recruiting outcomes, both job and organization characteristics were important predictors of recruiting outcomes, but ―who does the recruiting appears not to be important‖ (Chapman et al., p. 938). Thus, along with the absence of a basic conceptualization of recruiting effectiveness in college sports, there are several key problems with the research literature that explicitly pertains to recruiters and their impact on recruiting effectiveness. One, compared to the recruiting literature as whole, little is known about recruiters and the mechanisms through which they achieve recruiting effectiveness. Several conceptual arguments have been articulated. For instance, the reputation/information framework (Berkson et al., 2002) positioned organizational reputation as a key source of information for recruits. The researchers then argued that recruiters would combine persuasive communication and organizational reputation information to positively influence job candidates during the recruitment interview process. Yet, as it stands currently, the limited array of empirical research in existence points to recruiters not having a large impact on actual job choices (Chapman et al., 2005; Rynes, 1991). Two, only a handful of recruiter characteristics have been examined, and of these factors only two have typically explained much variance in dependent variables (i.e., recruiter affect,

. such as warmth and personableness, and informativeness; Breaugh & Starke, 2000; Rynes, 1991). Even then, the impact of these factors may be limited, at best, to the early stages of the recruitment process (e.g., campus interview) and individuals‘ attraction to an organization (Powell, 1984; Rynes & Miller, 1983; Taylor & Bergmann, 1987). In other words, these factors are not likely to have significant impact on recruits‘ actual job decisions. Hence (Rynes, p. 413): The pattern is clear: Recruiter behaviors have moderate effects on overall impressions of the recruiter, but small or nonsignificant effects on intentions to pursue or accept job offers. Moreover, this is true even at the point at which the recruiter would be expected to have maximal impact—immediately following the recruitment interview.

Moreover, the method in which recruiters have been assessed by researchers lacks consistency, which leads to a third problem for examining the impact of recruiters on recruiting outcomes. Three, there is a lack of well-established and diverse scales to measure recruiter characteristics. Multiple studies have included unique scales which the respective researchers either created or adapted to measure recruiter characteristics pertinent to the specific focus of their study (e.g., Liden & Parson, 1986; Schreurs, Derous, Witte, Proost, Andriessen, & Glabeke, 2005; Schmitt & Coyle, 1976; Turban & Dougherty, 1992). Other researchers have inconsistently (in terms of the number of factors incorporated from past research) adapted Schmitt and Coyle‘s scale of recruiter perceptions (e.g., Harris & Fink, 1987; Liden & Parson, 1986; Turban & Dougherty). Additionally, and in contrast to the aforementioned examples, many of the recruiter- focused studies have incorporated non-survey based methods to ascertain recruiter characteristics and their impact on job seekers. For instance, both Weilbaker and Merritt (1992) and Wiles and Shapiro (2004) compared recruiters‘ perceptions of what job characteristics are important to students (relative to the respective university where they recruited students) to what the students actually rated as the most important job characteristics. Rynes and Miller (1983) conducted videotaped versions of simulated campus interviews for a job position wherein they manipulated recruiter affect (e.g., frequent or infrequent smiling and nodding) and knowledge (e.g., amount of information provided). Also, Harris and Fink (1987) and Schmitt and Coyle (1976) described how, in the absence of preinterview-postinterview studies, it is difficult to determine the causal effects of a recruiter on a recruiting outcome. Thus, though the mixture of quantitative, qualitative, and experimental methods represented in the literature is interesting, it is also problematic. Essentially, because the

. recruiting literature in both the sport and mainstream management literatures lacks an established, definitive, and consistent approach to both defining and evaluating recruiter characteristics, this area of inquiry holds serious challenges for researchers. One challenge in particular is the difficulty of comparing research results and then drawing parallels between different studies and recruiting research in different disciplines. Four, even if the assumption is made that a key reason the recruiting literature leads researchers to take the position that recruiters have a limited impact on actual job choices is the absence of sufficient academic investigations (e.g., less than five studies have investigated recruiter personableness), there is still another serious concern for sport-based recruiting studies. This concern is the limited generalizeability of the findings from studies about recruiters in the business literature to a sport management context. One reason there may be a lack of generalizability is the job functions of the recruiters represented in most of the existing mainstream business studies have been a campus recruiter, not upper-level management or executives (Rynes, 1991). Another reason is the main foci of existing studies have been primarily college campus recruiters and their characteristics and how they interact with individuals close to or possessing college degrees at the undergraduate or graduate levels. Rynes, Heneman, and Schwab (1980) also noted how male business and engineering students are overrepresented as research subjects. Over twenty years later, this still appears to hold true as several contemporary studies (e.g., Becker, Connolly, & Slaughter, 2010; Turban & Cable, 2003) echo this previous observation. Thus, the job applicants (or recruits) typically studied have been individuals looking to become business professionals, men and women about to embark on the post-university experience, and they are interacting with campus recruiters, not high-level organizational members such as chief executive officers (CEOs). In distinct contrast, athletic recruiters are typically head or assistant or coaches who could be considered as more equivalent to business executives than traditional campus recruiters. Athletic recruiters are also interacting with high school students still under the care of parents or guardians. These young men and women are about to start their university experience; they are not college graduates whose university experience has ended. Also, whereas campus recruiters are ―unlikely to play an important future role in applicants‘ daily work lives‖ (Rynes, 1991, p. 414), athletic coaches (especially head coaches) are the gate keepers of a student-athletes future

. in college sports. Finally, how a business organization recruits is usually dictated by a board, executives, or management personnel. Each organization has a unique approach to recruiting, one not governed by an outside body of officials. In contrast, recruiting in intercollegiate athletics (at least at the NCAA DI – DIII levels) is regulated by a national organization (NCAA) that is not directly tied to any one specific institution. For example, the NCAA has restrictions regarding when and how frequently coaches may interact with student-athletes that applies to all institutions. Consequently, the applicability between business-based recruiter research and recruiters in college sports should be viewed with caution pending further investigation. Purpose and Intended Contributions of the Research Clearly, there are several limitations with the recruiting literature, and exploration of each would greatly contribute to the advancement of sport management studies. Therefore, the purpose of this study is two-fold: (a) the development of a conceptual framework (with particular reference to the role of the recruiter) that can be used to guide recruiting research in intercollegiate athletics and (b) empirically investigating the affects of recruiter characteristics on recruiting effectiveness. This two-fold approach provides a needed shift away from research focused solely on student-athlete college choice criteria and provides a fresh perspective to this area of study, especially with regard to sport management and the significance of athletic coach recruiters on student-athlete selection decisions. By addressing several of the aforementioned limitations of the recruiting literature, this study targets numerous areas for potential contributions. These areas include: (a) the development of conceptual model that includes the recruiting process as well as the factors contributing to recruiting effectiveness in college sports, (b) explanation of the role of athletic recruiters and their impact on recruiting effectiveness in college sports, and (c) empirical examination of recruiter characteristics and how they impact recruiting effectiveness in college sports. By addressing each of these areas, this study will not only answer its own research questions, but also provide a more detailed answer to a fundamental question posed by Breaugh and Starke (2000): How do we (the respective organization) improve recruitment effectiveness? Research Questions Serving to guide this study are two underlying research questions. The first question pertains to recruiting effectiveness as a whole, while the second question is focused on recruiters. RQ1: What leads to recruiting effectiveness in NCAA DI college soccer?

RQ2: What recruiter characteristics lead to recruiting effectiveness in NCAA DI college soccer? Organization of the Study In order to complete the objectives of this dissertation in an orderly process, this research study is organized in the following manner. Chapter 2 begins with a graphical representation of the proposed conceptual model of the factors and process leading to recruiting effectiveness in college sports. Once the requisite conceptualization of recruiting effectiveness in college sports is explained, the reader is then introduced to the research model. This model represents what will be precisely examined in this dissertation. Each aspect of this model is explained and it is accompanied by the development of specific hypothesis. Chapter 3 details the design of the inquiry used to test the hypothesized relationships. This chapter includes the statistical methodology, research measures, and data analysis techniques. Chapter 4 provides the research results. Chapter 5 includes a summary of these results and a discussion of the theoretical, practical, and managerial implications of the findings. Also provided in this chapter are study limitations and suggestions for future research. Lastly, the appendices include survey measures and supporting materials used in data collection.

CHAPTER TWO LITERATURE REVIEW

The process (or framework) guiding many of the sport management studies about intercollegiate athletics recruiting is not so much a recruiting effectiveness framework, but a student-athlete selection decision criteria framework. Essentially, the majority of sport management studies focused on student-athlete recruiting appear to be more aligned with the approaches proposed by Hossler and Gallagher (1987) than mainstream business models about the overall organizational recruitment process and/or specific aspects of this process (see Barber, 1998; Breaugh & Starke, 2000; Rynes, 1991). Student-choice models (e.g., Hossler & Gallagher, 1987; Jackson, 1982) are centered on students and their college choice processes. Although these models can be used to inform how universities approach the recruitment of students, the main focus is the student‘s selection process. Models such as these investigate student decisions in order to better inform universities about their target markets and how these individuals evaluate various college choice predictors (Sevier, 1996). These models are not primarily concerned with the role of recruiters and the overall recruiting process; in this regard, student choice models are one-sided, as they are solely focused on student choice criteria. Hossler and Gallagher (1987), for example, proposed a three-stage model of the college selection process that included predisposition, search, and choice stages. The first stage is the predisposition stage; this is when individuals decide what path they want to pursue, such as continuing their education or joining the workforce. The final stage is the choice stage; this reflects the decision by the individual to pursue specific options (i.e., submitting applications to select universities). Between these two stages is the search stage. This is when the greatest amount of interaction between the student and university takes place because this stage is when students weigh their options (i.e., evaluate university selection criteria) and universities seek out specific individuals. Of these three stages, the search stage in particular has been the starting point for most sport management studies centered on student-athlete selection decision criteria. This focus is understandable considering the primary objective of most of these studies has been identifying student-athlete selection decision factors. Be that as it may, the combination of identifying key

. factors along with exploring the underlying processes through which athletic recruiters go through to recognize and recruit key individuals has been largely absent in the scholarly sport- based literature. Identifying student-athlete selection criteria is useful, if not necessary, but it represents only one facet of recruiting. Hence, a broader scope of research is required because selection decision predictors (alone) do not fully explain recruiting effectiveness in college sports, nor do they provide adequate explanation about how athletic coaches‘ (recruiters) attract, court, and actually sign marquee student-athletes to their athletic program. Therefore, what is proposed in this dissertation is a model developed from the belief that athletic recruiters (athletic coaching staff) and their characteristics are central to achieving positive recruiting outcomes. Previous sport-based recruiting studies have been largely centered on identifying the factors most important to student-athletes‘ college choice decisions. Even though a variety of selection decision factors are incorporated into the proposed conceptual model, identifying them is not the primary objective. Instead, the final product of the proposed model is recruiting outcomes. Recruiter characteristics as well as other selection decision predictors (i.e., context factors) are included, but they are framed within the recruiting process. That is, the proposed model explores one way in which selection-decision factors, with particular reference to recruiter characteristics, may ultimately lead to positive recruiting outcomes such as university attraction, acceptance intentions, and scholarship-offer acceptance. The proposed conceptual model is presented in Figure 2.1. This figure provides a recruiting template to serve as both an introduction and general guide for research addressing matters of recruiting effectiveness in college sports. The generation of the model is based on the relevant sport and management literatures, as well as being supplemented by media and anecdotal accounts of recruiting in intercollegiate athletics. What follows is a brief overview of the model.

Context

Recruiter Recruit Recruit – Recruiting Characteristics FIT Influential Outcomes Perceptions Agent FIT Interaction

Influential Agent FIT Perceptions

Figure 2.1: Recruiter-centered model of recruiting effectiveness in college sports

Proposed within the model is that recruiter characteristics (e.g., personality factors, social effectiveness constructs) affect both recruits‘ fit perceptions and influential agents‘ fit perceptions. Recruits are student-athletes and influential agents are individuals such as parents, guardians, and/or high school coaches who have a significant and positive role in a recruit‘s life. Context factors (e.g., university academic rank, campus atmosphere, location) moderate the recruiter characteristics – recruit fit perceptions and recruiter characteristics – influential agent fit perceptions relationships. Next, recruit fit perceptions have an impact on the recruit – influential agent fit interaction; this relationship is also thought to be moderated by influential agents‘ fit perceptions. The recruit – influential agent fit interaction, which is illustrated in Figure 2.3, and is located in the appropriate section of the literature review, leads to recruiting outcomes such as attraction, acceptance intentions, and actual university choice decisions. In the following sections, the relevant theoretical frameworks and research evidence are used to support the proposed linkages in the conceptual model. Discussed thereafter is a subset model (Figure 2.4) that will be the specific focus of this study. Thus, two models are described in this dissertation: a broader conceptual model and a testable research model. Theoretical Foundations A multitude of theoretical approaches have been incorporated into studies focused on recruiting and student-athlete selection criteria. For example, researchers approaching student-

. athlete college choices with an economic model (e.g., Hossler, Braxton, & Coopersmith, 1989; Kotler & Fox, 1985) will center their study on the student-athlete‘s financial considerations and the cost-benefit process. On the other hand, a status attainment-based model (e.g., Paulsen, 2001) will cause researchers to view the end result/opportunity to achieve a desired status as the key predictor in college choice decisions. All together, the various theoretical perspectives found in the scholarly literature highlight the complexity of recruiting and student-athlete college choice decisions as well as how selection criteria (alone) are insufficient indicators of the underlying process that may eventually lead to student-athlete job/scholarship offer acceptance and recruiting effectiveness for recruiters. Thus, it is unlikely that a single theory can completely capture the various nuances of the recruiting process explored in the proposed conceptual model. What is therefore incorporated into this study is an integrative theoretical perspective composed of two established theories: (a) job choice theory (Behling, Labovitz, & Gainer, 1968), which is the combination of objective, subjective, and critical contact theories and (b) balance theory (Heider, 1958). Together, these theories provide an explanation about how both selection- decision criteria and the recruit – influential agent interactions contribute to recruiting outcomes. Provided next are explanations of each of these theoretical foundations. With regard to job choice theory (Behling et al., 1968), the objective theory component is grounded in the position that recruits are economically driven (i.e., scholarship opportunity, benefits, location, job responsibilities). Subjective theory frames recruits as being psychologically driven and affected more by their desire to fulfill psychological needs than their desire for additional economic rewards (e.g., recruits with a high level of team/school identification will seek out environments that are most conducive to their particular psychological needs). Finally, according to critical contact theory, there is more to the decision making process of student-athletes than economic and psychological needs. Recruits are also likely to make decisions based in part on recruiter characteristics and their interactions with the recruiter and the information this individual provides to them (Young, Rinehart, & Place, 1989). Each aspect of job choice theory (Behling et al., 1968) is represented in Figure 2.1. Context moderators coincide with subjective factors theory. Selection decision factors such as recruit fit perceptions have origins in objective factors theory. Moreover, the implicit role of the recruiter in the entire recruiting process along with the explicit focus of the model on recruiter characteristics has roots in critical contact theory.

Additionally, balance theory (Heider, 1958) provides a theoretical rationale about how the recruit – influential agent relationship impacts recruiting outcomes. Balance theory contends that individuals attempt to maintain a sense of balance in their day-to-day lives. This means they strive to attain ―a harmonious state, one in which the entities comprising the situation and the feelings about them fit together without stress‖ (Heider, p. 180). This has also been referred to as ―cognitive consistency‖ (Heider, p. 201). With regard to the proposed recruit – influential agent fit interaction, the involved parties are believed to need to reconcile their feelings toward the recruiter‘s characteristics. In doing so, the respective individuals are able to remedy an imbalanced state, transforming it into a balanced state in each of their minds. This unified position will then have an impact on recruiting outcomes. Attempts to achieve cognitive consistency can take place in a variety of different ways. For instance, if recruits‘ perceptions differ from the perceptions of their influential agents, the recruits may change their opinions of the influential agents (i.e., less credible in this particular situation). Despite having respect for these individuals, this is done by recruits in order to bring balance to their positions. The recruits may also attribute more value to recruiter characteristics. This is done to increase harmony between the recruiter‘s characteristics and the recruits‘ fit perceptions. However, because recruits and influential agents have strong ties (otherwise these individuals would not be influential agents), there is presumed to be a strong expectation to achieve some semblance of harmony between these individuals and their views. This, combined with the fact the recruits are high school student-athletes about to make what may be their first major life choice, lends greater support to the notion these individuals will more likely come to a state of balance about recruiter characteristics that does not involve diminishing the credibility and worth of either parties‘ opinions. Recruiter Characteristics Lanning (1979) remarked ―an athletic program is always a reflection, and sometimes an extension, of the personality of the coach‖ (p. 263). It should therefore come as no surprise that one of the most identified and influential characteristics impacting student-athlete university choice decisions are the coaches, with particular attention to the head athletic coach. In a study about Big 12 men‘s basketball student-athletes, it was reported that the athletes‘ relationships with the head coach was the most influential factor, reputation of the head coach was 3rd, head coach‘s style of play was 5th, and the student-athletes‘ relationships with the assistant coach(s)

. was 6th (Croft, 2008). Additionally, Gabert and colleagues (1999) surveyed athletes from several different competitive levels (NCAA DI, DII, and NAIA) and found that across levels, head coach was marked as the most influential factor of student-athletes‘ college choice decisions. Collectively, a plethora of researchers have reported similar findings (e.g., Adler & Adler, 1991; Cook, 1994; Cooper, 1996; Goss et al., 2006; Kankey & Quarterman, 2007; Letawsky et al., 2003; Mathes & Gurney, 1985; Pauline, 2010; Reynaud, 1998; Slabik, 1995; Stotlar, 1976; Swaim, 1983; Widdison, 1982). With specific consideration to the role of the coach as a recruiter, however, few if any sport-based studies have focused on recruiter/coach characteristics and how they precisely impact recruiting outcomes. Indeed, as it was noted in Chapter 1, minimal attention has been paid to two key areas. One area is the identification of specific recruiter/coach characteristics that are likely to have a significant impact on recruiting outcomes and what these factors actually impact (e.g., fit perceptions). A second area is an explanation of the process through which these characteristics have an impact as well as the degree to which they are responsible for this impact. Thus, for the purposes of this study, much of what is known about recruiter characteristics is drawn from the relevant management and personnel psychology literatures. In human resource management (HRM), the untested yet widely held belief for much of the twentieth century was recruiters could sway (either positively or negatively) a job applicant‘s decision to accept a career opportunity (Rynes, 1991). Indeed, it was not until the seminal piece by Alderfer and McCord (1970) that recruiters were empirically linked to recruitment outcomes such as organization attractiveness and job intentions. Nevertheless, forty years have passed since the article by Alderfer and McCord first appeared, and a multitude of studies have been published—though rarely in sport management—about various recruiter factors and how they affect recruiting outcomes (e.g., likelihood of offer acceptance, trust in the recruiter; Rynes & Miller, 1983; Schuler & Jackson, 1987). Presently, even though recruiters are generally viewed as having an impact on recruiting outcomes (Barber, 1998; Breaugh & Starke, 20000), the extent to which they have an impact as well as the specific characteristics contributing to this impact remain less clear. Taken as a whole, research results have been mixed. Indeed, still lacking in the literature is a consensus opinion as to whether or not recruiter characteristics (separate or in combination with job attributes) impact factors such as job attractiveness, an applicant‘s willingness to pursue a job,

. and actual job-choice decisions (e.g., Chapman et al., 2005; Harris & Fink, 1987; Mahony, Mondello, Hums, & Judd, 2006; Powell, 1984; Rynes, Bretz, & Gerhart, 1991; Rynes & Miller, 1983; Wanous & Colella, 1989). In several studies recruiter characteristics were reported to significantly influence recruiting outcomes, such as recruits‘ perceptions of job-organization attractiveness and intentions to attend a second interview (Powell, 1984; Rynes et al., 1991; Rynes & Miller, 1983). Notably, in a longitudinal study with structured interviews, Rynes and colleagues observed recruiters may be particularly impactful on recruiting outcomes if they are perceived by individuals (particularly those lacking sufficient information about the organization) as being ―symbolic of broader organizational characteristic (p. 487). Yet, in other cases (e.g., Harris & Fink, 1987; Schmitt & Coyle, 1976), even when job attributes were controlled for, no significant relationship was found between recruiters and applicants‘ job choice intentions. With this in mind, what follows in this section is an overview of the recruiting literature, with particular attention to recruiters and their impact on recruiting outcomes. Several recruiter characteristics have been repeatedly studied as possible factors that may significantly influence recruiting outcomes. These include: recruiter function, recruiter personality and behavioral traits, and recruiter demographics. Each is discussed in the ensuing sections. Recruiter Function One characteristic that may impact recruiting effectiveness is recruiter function. In other words, identifying whether the individual is a line recruiter (i.e., a non-HR employee, such as an engineer recruiting an engineer) or a personnel recruiter (i.e., an HR employee, such as a personnel specialist). This particular area has been rarely examined in the recruiting literature (Harris & Fink, 1987; Fisher, Ilgen, & Hoyer, 1979; Taylor & Bergmann, 1987), and it has not been linked to actual job-choice decisions. Nevertheless, Taylor and Bergmann reported higher company attractiveness rating among individuals interviewed by a line, rather than a personnel recruiter. Recruiter Personality and Behavioral Traits Under various, but similar labels, several recruiter personality and behavioral traits have been studied in the extant management literature. These include: (a) credibility (e.g., Coleman & Irving, 1997; Connerley, 1997; Connerley & Rynes, 1997; Fisher et al., 1979; Harris & Fink, 1987; Schreurs et al., 2005; Taylor & Bergmann, 1987), (b) job knowledge/job informativeness

(e.g., Liden & Parson, 1986; Macan & Dipboye, 1990; Powell, 1991; Schmitt & Coyle, 1976; Schreurs et al.; Taylor & Bergmann, 1987; Turban & Dougherty, 1992; Weilbaker & Merritt, 1992; Wiles & Spiro, 2004), (c) personableness (e.g., Connerley & Rynes, 1997; Liden & Parson; Rynes, 1991; Maurer, Howe, & Lee, 1992; Rynes et al., 1991; Schmitt & Coyle; Schreurs et al.; Weilbaker & Merrit), and (d) trustworthiness (e.g., Coleman & Irving, 1997). Of these factors, recruiter informativeness and affect (commonly labeled as personableness) appear to have the greatest impact on recruiting outcomes (Breaugh & Starke, 2000; Chapman et al., 2005). Notably, in their meta-analysis, Chapman and colleagues reported that ―among the recruiter characteristics, recruiter personableness was a particularly strong predictor of job pursuit intentions‖ (p. 935); however, it was less strongly related to organizational attraction, job acceptance intentions, and job choice. Lending anecdotal credence to the potential importance of these characteristics in a sport setting is an exchange between a football coach and athlete in the book, Meat Market. In the book, author Bruce Feldman detailed a 2005 exchange between then Ole Miss Head Football Coach Orgeron and Jerrell Powe, a five-star defensive tackle. In this example, Coach Orgeron appears to serve as what Sevier (1996) described as a ―champion‖. Sevier argued universities need an individual (a champion) who takes control of marketing the institution to students; this is someone who ―gather resources, mediates between different power and organizational structures on campus, and leads‖ (p. 15). In this specific example, Coach Orgeron appeared to take the mantle of an Ole Miss champion. One of the problems with Powe was not his athletic ability, but his poor academic performance. Therefore, when recruiting Powe, Coach Orgeron brought more than his trademark energy, he also brought an exceedingly detailed academic plan for how Powe could become eligible to play football for the Rebels of Ole Miss. This made quite an impression on Powe, who commented after his conversation with Orgeron: ―I knew I could become a better player if he coach me…He told me no matter what, he would stick with me, and that‘s when I fell in love with him‖ (Feldman, 2007, p. 159). Essentially, Orgeron recognized Powe‘s limitations and marketed a plan of action to him that would allow him to both improve his academic standing and compete eventually in intercollegiate football. Also impacted by Orgeron‘s presentation was an influential agent, a man who had taken on the role of a father figure in Powe‘s life. His name was Joe Barnett. He was the father of one

. of Powe‘s friends and he helped to guide Powe through the reruiting process. He, too, was impressed and remarked: ―It was incredible…He treated Jerrell like it was a job interview more than just some recruiting pitch. And he talked straight to him‖ (Feldman, 2007, p. 159). Though this observation lacks empirical confirmation, recruiter affect as well as informativeness (specific to the needs of a particular student-athlete) may indeed have an impact on recruiting outcomes. Recruiter Demographics Recruiter demographics also represent an area receiving considerable attention in the recruiting literature. Essentially, three key areas of demographic research have manifested in the literature. These areas include: (a) age (e.g., Alderfer & McCord, 1970; Cable & Judge, 1996; Hilgert & Eason, 1968; Rogers & Sincoff, 1978), (b) race (e.g., Cable & Judge; Thomas & Wise, 1999; Wyse, 1972), and (c) gender (e.g., Barber & Roehling, 1993; Cable & Judge; Hardin, Reding, & Stocks, 2002; Connerley, 1997; Connerley & Rynes, 1997; Harris & Fink, 1987; Taylor & Bergmann, 1987; Turban & Dougherty, 1992). With regard to age, though several studies have included it as a recruiter characteristic that may impact recruiting outcomes, one notable point to consider when evaluating this factor is that it may not have a significant influence because other factors (such as knowledge) may overshadow its impact (Marks, 1967). As for race, Wyse‘s (1972) examination came out shortly after the seminal work by Alderfer and McCord (1970); this study provided evidence that recruiter race had no impact on white applicants, whereas black applicants preferred a black recruiter. Likewise, Thomas and Wise (1999) observed that firms with minority recruiters may be more attractive to minority job applicants. For gender, a relatively recent study by Hardin and colleagues (2002) did not find a relationship between recruit/applicant gender, recruiter gender, and the rating the recruiter assigned to the possible new employee. In general, studies focused on the impact of the demographic characteristics of the recruiter and applicant‘s acceptance decisions (not level of attraction) are inconsistent, and consequently, there is not enough research evidence to conclude that recruiter demographics significantly impact applicant job choice (Barber, 1998; Chapman et al., 2005; Rynes, 1991). Context Factors In her model for future recruitment research, Rynes (1991) included recruitment context as an area whose factors, such as external environment, may impact recruitment activities and decisions, recruitment processes, and recruitment outcomes. In this study, context refers to the

. circumstances and conditions that are applicable to a specified event (i.e., recruiting). As illustrated in Figure 2.1., context factors are thought to have an impact on the relationships between recruiter characteristics and recruit fit perceptions as well as recruiter characteristics and influential agent fit perceptions. Certain context factors may significantly change the nature of the relationships between these variables. University academic ranking, for example, may alter the relationship between a recruiter characteristic such as knowledgeableness and recruit and influential agent fit perceptions. More precisely, the association between recruiter knowledgeableness and fit perceptions may get stronger when university academic ranking increases (and vice-versa). Therefore, in this section, context factors are organized into the following overarching categories: (a) recruit, (b) athletic, (c) academic, and (d) external. Each of these categories and the corresponding factors are presented in Figure 2.2. The recruit category pertains to factors such as student-athlete gender that may facilitate conditions that impact recruiting outcomes. The athletic category houses factors that are connected to student-athletes‘ athletic experiences (e.g., scholarship availability, opportunity to play, team climate, athletic conference). The academic category houses factors that are connected to student-athletes‘ academic/university experiences (e.g., availability of major, university academic rank, campus atmosphere). Even though athletic programs are technically part of a school, these two categories have been separated. The rationale for this separations stems from the belief that although the academic and athletic aspects of a school are not mutually exclusive, they are nevertheless distinct aspects of student-athletes‘ college experiences. Finally, the external conditions category includes factors that designated as primarily out of the control of individuals or organizations (e.g., economy, school location, weather).

Recruit Athletic Academic External

• Competitive • Opportunity to • Availability of • Economic Skill Level Play Desired Academic Conditions Major • Gender • Athletic • Scandals and Scholarship • Academic Sanctions • Sport Played Reputation • School Location • Career Opportunities • Weather/Climate After Graduation

Figure 2.2: Context categories and key factors

Recruit Category The combination of anecdotal evidence, personal experience in intercollegiate athletics at various levels, and research findings provide evidence that points to athlete competitive skill level (i.e., anticipated level of NCAA competition), gender, and sport played (i.e., football, soccer) all having the potential to change the nature of the relationship between recruiter characteristics and fit perceptions. Each of these recruit-oriented areas is discussed next. Competitive skill level. The scope of the extant literature is fairly diverse in that a variety of competitive levels, not just DI, have been explored, often times simultaneously (e.g., Cooper, 1996; Gabert et al., 1999; Goss et al., 2006; Elliott, 1995; Pauline, 2010; Pauline et al., 2007; Ulferts, 1992). In particular, Cooper conducted a study which included almost 40 schools and over 200 athletes from community colleges, junior colleges, and also National Association of Intercollegiate Athletics (NAIA) and NCAA DI schools. Prior to this example, Gabert and colleagues also compared student-athletes from multiple competitive levels, including DI, DII, DIII, and NAIA schools. After the factor of head coach (the most influential factor reported by student-athletes), they noted student-choice criteria varied by competitive level. Additionally, in study by DuMond, Lynch, and Platania (2008), wherein they developed an economic model to evaluate the college choice decisions of sought-after student-athletes, the

. researchers reported the most important factor to top DI football recruits was the location of the school (i.e., its distance to their home). Gender. Along with competitive level, there is evidence that influential factors may vary depending on the gender of the student-athlete. Incidentally, these results have been mixed. Mathes and Gurney (1985), for example, reported no significant differences between male and female student-athletes. Also, no significant gender differences were found in a study by Doyle and Gaeth (1990); they compared student-athletes from the sports of baseball and softball. Yet, in a more recent study by Pauline (2010), male lacrosse players were found to rate athletic factors as more influential than female lacrosse players. Furthermore, female lacrosse players rated academic factors as more influential than their male counterparts. Sport played. A small variety of sports and sport types have also been studied. Most frequently studied are sports such as football (Johnson, 1972; Klenosky et al., 2001; Letawsky et al., 2003; Stotlar, 1976), men‘s and women‘s basketball (Cooper, 1996; Croft, 2008; Elliott, 1995; Heilman, 1988; Hess, 1988; Moffitt, 1982; Speer, 1992; Swaim, 1983; Ulferts, 1992), baseball and softball (Doyle & Gaeth, 1990; Kankey and Quarterman, 2007; Pauline et al., 2007), and volleyball (Reynaud, 1998; Widdison, 1982). For example, Walker (2002) conducted a research study of all 49 freshman student-athletes at a Southeastern Conference (SEC) university. He found, regardless of sport affiliation or athlete gender, the coaching staff was an important influence on student-athletes‘ school choice decisions. Athletic Category Despite the limitations of the sport literature (as it pertains to recruiting), several athletic factors have been found to have a significant influence on student-athletes‘ college selection decisions. What follows in this section is a collection of the most consistently identified influential factors. Namely: job characteristics. This includes both an opportunity to play and scholarship information. Each factor is presented in light of research evidence, and when appropriate, supplemented with anecdotal evidence and media reports. Additionally, several factors that have been reported as important (but not a top factor) or infrequently studied are also discussed at the end of this section. Job characteristics. In line with objective factors theory (Behling et al., 1968), another key area contributing to recruiting outcomes are job characteristics, primarily the type of work, pay, and opportunities for compensation and advancement (Chapman et al., 2005; Jurgensen,

1978; Osborn, 1990; Rynes & Miller, 1983). The meta-analyses by Chapman and colleagues underscored that applicant attraction is significantly impacted by what is being offered by the organization. Relative to sports and student-athletes, two job characteristics (so to speak, as participating in college sports is not a job in the traditional sense found in the mainstream management literature) have been identified repeatedly as influential factors in student-athletes‘ school selection decisions. The first factor is the opportunity to play. A multitude of studies have found this factor to be a top influencer. A representative list of these studies includes: Forseth (1987), Goss et al. (2006), Johnson (1972), Konnert and Giese (1987), Pauline et al. (2007), Slabik (1995), Stotlar (1976), and Widdison (1982). In particular, Goss and colleagues reported this was the second most important factor among small-college student-athletes (i.e., DIII and NAIA). It should also be noted that although opportunity to play has been frequently observed in the extant literature, the dichotomy between opportunity to play versus opportunity to play at the desired sport position has not been examined. Moreover, only one study reported the opportunity to play in a specific sporting event as important. Specifically, Croft (2008) found that the opportunity to play in the NCAA tournament was the 2nd most important factor among Big 12 men‘s basketball student-athletes. In addition the opportunity to play, another key job characteristic that has been identified pertains to athletic scholarships, a factor which runs ostensibly parallel with the topics of financial compensation and salary discussed in the management literature. Collectively, Doyle and Gaeth (1990), Elliott (1995), Reynaud (1998), Ulferts (1992), and Widdison (1982) have all noted this to be a top factor. Both Reynaud and Widdison reported this to be one of the most influential reasons volleyball players selected a college or university. Ulferts also found this to be an important factor. In fact, Ulferts indicated availability of an athletic scholarship was one of the top three reasons for student-athletes to attend a particular school. Additional factors. Apart from the aforementioned factors, there are several additional athletic factors that are important to student-athletes and may therefore impact recruiting outcomes. These factors include: (a) athletic conference, (b) athletic facilities, (c) athletic traditions, (d) team performance, and (e) social atmosphere. In following, each of these factors is briefly reviewed. To begin, only a couple studies have indicated athletic conference to be a key factor

. influencing student-athlete decisions. Croft (2008) reported this to be the fourth most important factor among Big 12 men‘s basketball student-athletes. In addition, DuMond et al. (2008) reported that for NCAA DI football recruits, whether or not a school is in a Bowl Championship Series (BCS) conference does significantly impact school choice decisions. To put this latter study in perspective, NCAA DI football includes conferences that are automatic qualifiers (AQ) and non-automatic qualifiers (Non-AQ). The AQ conferences represent the athletic conferences whose football champions receives an automatic bid to one of the five Bowl Championship Series (BCS) bowl games, events typically associated with greater prestige and financial payouts to the respective conferences. Presently (as of 2011), the six AQ conferences are the Atlantic Coast Conference (ACC), Big 12, Big East, Big Ten, Pacific-10 Conference (PAC -0), and the Southeastern Conference (SEC). Non-AQ conferences, such as the Western Athletic Conference (WAC), are not guaranteed to send their football champion to a BCS bowl game, regardless of whether or not their record and rank is superior to that of a champion from an AQ conference. Therefore, even though it has not been thoroughly studied by sport scholars, athletic conference may impact recruiting outcomes, especially for DI football. Consider how both the University of Utah and Texas Christian University (TCU) announced during the 2010 season they were leaving the Mountain West Conference (MWC), a non-AQ, to join the PAC-10 and Big East respectively. Utah joins the PAC-10 in the 2011-2012 school year whereas TCU joins the Big East in the 2012-2013 school year. When speaking of the move, TCU Head Football Coach Gary Patterson ostensibly confirmed the results of DuMond et al. (2008) when he said: ―I‘ll say this, we don‘t seem to get bored around this place…The one last mark people have held against in recruiting is that we were not an automatic qualifier. Not that‘s been erased‖ (Durrett, 2010). Another potentially important factor that has received limited scholarly attention is athletic facilities. With the exception of DuMond et al. (2008), who reported stadium age and the size of a sport team‘s stadium positively impacted recruiting outcomes, this factor has received minimal support (e.g., Goss et al., 2006; Pauline et al., 2007) as an influential factor for student- athletes. Be that as it may, a strong body of anecdotal evidence and media reports provides substantiation that this factor is important, at least in the minds of university and athletic department officials. Indeed, in the past two decades, billions have been spent on sports facilities in

. intercollegiate athletics (King, 2005). This, in part, may be the consequence of university decision-makers viewing these sport monoliths as beneficial to athletics and the recruiting of top student-athletes. For instance, Virginia Tech Associate Athletic Director Tom Gabbard remarked: ―The folks you see building new facilities around the country know what a great recruiting tool they can be‖ (Broughton, 2009, p.24a). In addition to this statement, there is also this example from the early 90s (King, p. 19): When Tommy Frazier visited the University of Nebraska on a football recruiting trip in the winter of 1992, he was wowed by the expanse of the 30,000 square-foot weight room and the sprawl of a 3 million dollar indoor practice field that put the Cornhuskers a decade ahead of most programs.

Hence, though other factors may overshadow the influence of athletic facilities, such structures may still have a noticeable impact on recruiting outcomes (or at least give key personnel the impression of having a significant impact on recruiting outcomes). Athletic traditions have also been observed as influential factors for student-athletes. Ulferts (1992) noted the basketball program and its athletic traditions was one of the top three reasons for student-athletes to attend a particular school. Both Elliot (1995) and Letawsky et al. (2003) reported this to be a top five influential factor (second and third respectively), while Goss et al. (2006) placed this factor in the top 10 (i.e., the 9th most important factor). Next, and though it may come as a surprise, athletic team performance has rarely been noted as an influential factor by student-athletes. For instance, DuMond et al. (2008) reported that the final Associated Press (AP) ranking of a specific school in the previous year of competition did significantly impact the decisions of football student-athletes. Otherwise, apart from Doyle and Gaeth (1990) and Pauline et al. (2007), winning program has not been identified as a top factor. This may stem from the complexity of how athletic performance, team record, and even team rankings are perceived by student-athletes. To illustrate this point, consider the following football comparison between TCU and the University of Texas (UT-Austin). The Horned Frogs of TCU finished the 2010 season ranked third in the nation, beat the fifth ranked Wisconsin Badgers in the Rose Bowl, and ended their season 12-0. In spite of being the number two ranked team in the country, they were unlikely to achieve a top 25 recruiting class. The Long Horns of Texas finished the same season with a 5-7 overall record and failed to make a bowl game. Yet, going into February 2nd (the official signing day), Texas boasted the top recruiting class in the country according to Rivals.com, which is largely recognized as the most

. complete source of NCAA recruiting information, especially with regard to football recruits and football program recruiting class rankings. In the end, Texas finished third, behind only Florida State University (FSU) and the University of Alabama who were second and first respectively. The University of Miami, another school coming off a disappointing football season, may help to put this seeming recruiting paradox in perspective. After losing the Hyundai Sun Bowl matchup against Notre Dame, and finishing their season 7-6, Miami‘s interim head coach Jeff Stoutland remarked: ―You can [look at it] both ways…You might want to come to Miami now because you can say, ‗I can come there and help your school. I don‘t have to sit around and wait a couple years.‘ That‘s how I look at it.‖ (Degnan, 2011). Thus, the impact of team performance on student-athlete choice decisions is most likely multi-faceted and interconnected to a variety of factors including athletic traditions, athletic conference, athletic opportunities, and sport-type. Lastly, several researchers have found evidence that social atmosphere has a significant impact on student-athlete selection decisions. Of note, Reynaud (1998) listed this as the fifth most important factor. Kankey and Quarterman (2007) found this to be the fourth most important factor influencing student-athlete selection decisions. Doyle and Gaeth (1990) and Pauline (2010) also noted this was an important factor. Finally, if this factor is indeed influential, it may be especially so during the campus visit. This is because recruits are immersed in the culture of the athletic team during the campus visit, which is done for the specific purpose of creating enhanced levels of familiarity and comfort (Grandillo, 2003). Academic Category Along with athletics, a third key category impacting recruiting outcomes encapsulates factors that are representative of organizational characteristics. In this case, these factors pertain to specific characteristics of institutions of higher education. Therefore, what follows in this section is a collection of key factors that have been repeatedly found to have an impact on student-athletes and their school choice decisions. Specifically: (a) academic major/degree program offered, (b) academic reputation, and (c) career opportunities after graduation. Note as well, though factors such as academic support services and on-campus dorms have been identified by student-athletes as influential, these factors (as well as others) were not included because they have rarely been noted as a top factor. For instance, only seldom have on- campus dorms been noted as an influential factor, and even then, only moderately (e.g., Goss et al., 2006). Also, though several studies (e.g., Gabert et al., 1999; Goss et al.; Letawasky et al.,

2003) found academic support services to be an important factor, only Goss et al. reported it to be in the top five (behind degree program offered, opportunity to play, and head coach). Academic major. Multiple studies have included findings about the availability of a desired academic major to represent a top factor influencing student-athletes‘ decisions about which school to attend. Indeed, several studies (e.g., Kankey & Quarterman, 2007; Letawsky et al., 2003; Pauline, Pauline, & Allen, 2008) reported this to be the most highly rated factor for student-athletes. Additionally, Judson and colleagues (2005) as well as several others (e.g., Goss et al., 2006; Mathes & Gurney, 1985; Pauline, 2010; Reynaud, 1998; Swaim, 1983; Widdison, 1982) each reported the availability of a desired academic major to be a top factor. Academic reputation. Along with the availability of a desired academic major, another key factor regularly observed by researchers is academic reputation. In fact, this has been reported as a top five factor in multiple studies over the past several decades (e.g., Elliott, 1995; Judson et al., 2005; Mathes & Gurney, 1985; Pauline, 2010; Pauline et al.., 2008; Reynaud, 1998; Swaim, 1983; Ulferts, 1992). In particular, Pauline conducted a recent study that included almost 1,000 lacrosse players from across three levels of intercollegiate athletic competition (i.e., DI – DIII). He reported this factor was tied with career opportunities upon graduation for being the most influential factor. By and large, academic reputation has been found to be a factor of noticeable importance to student-athletes. There is, however, limited evidence to contrary. Indeed, in distinct contrast to the aforementioned studies, academic standing (which can be considered as one aspect of academic reputation) was found to provide only a minor bump in recruiting outcomes for DI football student-athletes (Dumond et al., 2008). Career opportunities after graduation. Another factor that has frequently received a high rating of importance by student-athletes is career opportunities after graduation. Both Kankey and Quarterman (2007) and Swaim (1983) reported it as one of the most important factors. Also, Pauline (2010) found it to be the most important factor (tied with academic reputation). More precisely, on a 5-point Likert-type scale, the mean score for career opportunities was 3.99. External Category External characteristics, as defined for the purposes of this study, are those factors largely out of the control of recruiters and their respective schools. This area, though likely important to

. recruiting outcomes, has been discussed only on rare occasions in the extant sport management literature. As a result, there is little to no empirical evidence to inform the extent to which these factors may impact student-athletes and the recruiting process. This area is nevertheless thought to hold great potential for informing scholarly understanding of the recruiting process in college athletics, and it therefore warrants exploration. Hence, based in large part on anecdotal evidence and media accounts, several external factors are discussed. These include economic conditions, scandals and sanctions, school location, and weather/climate. Economic conditions. One external characteristic that may influence student-athletes is the economy, especially if it is combined with the factor of school location. To lend anecdotal support of this point, consider the following example. In 2009, a top football prospect was asked by the media why he chose the University of Virginia (UVA) over schools such as Ohio State University (OSU) and the University of Tennessee-Knoxville, both of which are schools with superior football programs. In response, the recruit noted how, given the current state of the US economy, he was concerned about his family‘s ability to travel and watch him play football (Viera, 2009). Hence, he selected the school that was close enough to home so that his family could watch him play without financially burdening them. Economic conditions may also overshadow other context factors. That is to say, for athletes in need of financial assistance, economic conditions may take precedence over factors like athletic and academic reputations. Accordingly, economic factors may influence how recruiter characteristics are viewed and alter recruit and influential agent fit perceptions. Scandals and sanctions. In recent years, 2010 stands out as a banner year for high- profile college sport scandals. Notably:  Auburn quarterback and 2010 Heisman Trophy winner, Cam Newton, was under investigation following claims by a Mississippi State booster that Newton‘s father wanted to exchange his son‘s commitment to the school for close to $200,000 (Associated Press, 2010).  In similarity to an academic scandal that rocked Florida State University (FSU) athletics in 2009, the University of North Carolina at Chapel Hill (UNC-Chapel Hill) faced similar challenges at the start of the 2010 football season as the NCAA investigated claims of possible academic misconduct (Barnhart, 2010).

 The storied athletics program of the University of Southern California (USC) experienced the NCAA throwing the book at them in 2010 for a lack of institutional control and numerous improper benefits to former basketball player O.J. Mayo and football player Reggie Bush. Not only did Reggie Bush, a former star football player with the Trojans, forfeit his 2005 Heisman Trophy, but the Trojans lost 30 football scholarships over three years and a two-year bowl ban (ESPN.com News Service, 2010).  University of Louisville Head Basketball Coach Rick Pitino‘s extortion trial. After a tryst with Karen Cunagin Sypher in August of 2003, the married father of five had no choice but to go public (and eventually to court) with the sexual encounter after Sypher attempted to extort $10 million from the coach (McShane, 2009). Regarding the USC scandal, men‘s basketball coach Kevin O‘Neill remarked: ―We can‘t control people 24 hours a day…That‘s all there is to it. You cannot control people from the outside. You cannot control agents. You cannot control runners. Those kinds of things get away from you sometimes because you have no way of knowing‖ (ESPN.com News Services, 2010). Be that as it may, athletic governing bodies such as the NCAA can still impose severe penalties, which, in both the short- and long-term, may have significant ramifications for achieving positive recruiting outcomes. Indeed, in a football study by DuMond et al. (2008), both the current number of scholarship reductions a school faces for violating NCAA rules as well as whether or not the school is under a ―bowl ban‖ were noted as significant factors influencing student-athlete‘s school choice decisions. Several additional examples of the impact of NCAA penalties are Southern Methodist University (SMU), the University of Alabama, and the University of Miami. Each of these institutions has been hit hard by athletic scandals, but of the three, none were hit harder than SMU. In fact, the long-term impact of the punishments imposed on SMU by NCAA in the late- 80s may have helped save Alabama and Miami from similar fates (Prisbell, 2007). That is to say, as J. Brent Clark (former NCAA investigator) reflected: ―Because of the SMU experience, the NCAA realizes it‘s too severe a penalty for the institution to recover from‖ (Prisbell). In 1987, the SMU football program was the first (and so far only) program to receive the NCAA ―death penalty‖ after its booster‘s funneled money to players. Several aspects of the penalty included the loss of 55 scholarships over four years, no off-campus recruiting until August 1988, and only being able to hire five full-time assistant coaches until August 1989

(McNabb, 1987). This penalty was, for all intents and purposes, a ―death blow‖ to the SMU Mustangs, which after 20 years is still struggling to regain a fracture of its former prominence (Dufresne, 2005). Accordingly, one external characteristic that holds the potential to significantly impact recruit and influential agent perceptions is scandals and sanctions. School location. Several studies (e.g., Doyle & Gaeth, 1990; Gabert et al., 1999; Pauline, 2010; Widdison, 1982) have provided mixed evidence supportive of the notion that school location is an important selection-decision factor. Widdison found this to be one of the most influential reasons for a volleyball player to select college or university. Similarly, Gabert et al. reported that DII student-athletes considered this to be a critical factor. Both Goss et al. and Pauline, however, reported this factor was moderately important, but not a top factor. Conversely, in an economic study by DuMond et al. (2008), it was reported that for heavily recruited football players from BCS-conference schools, school location (specifically, distance from home) was the most important factor for selecting a particular school. When speaking to Sports Illustrated about his study, Dumond remarked that (generally speaking), top recruits look for ―a place that is in a BCS conference with a big stadium that is close enough that they can be seen by family and friends‖ (Staples, 2009). With respect to football, he and his colleagues may have a point. Notably, Signing Day 2011 found the Florida State Seminoles with 21 football prospects from the state, including six of Rivals.com top 20 Sunshine State prospects. Thus, when it comes to recruiter characteristics, the location of the school may change the nature of the relationship between this variable and the fit perceptions of recruits and influential agents. Weather/climate. Another external factor that may impact recruiting outcomes is the weather and/or the general climate of a particular school. Even though it has not been specifically linked to recruiting outcomes, weather conditions may nevertheless impact recruiting outcomes. The University of Minnesota, for example, was covered in almost 20 inches of snow just before Christmas. The same snow fall covering the Golden Gopher‘s open-air TCF Bank Stadium also collapsed the Teflon roof of the National Football League‘s (NFL) Minnesota Vikings‘ Metrodome. Thus, though this extreme amount of snow is not an annual occurrence, such weather conditions may, at least temporarily, impact the perceptions recruits and influential agents have of a particular recruiter and his/her institution. Additionally, long before the Michael Vick dog fighting saga unfolded, he was a high school star looking to play DI college football. Several schools pursued Vick, but in the end he

. selected Virginia Tech. One school in particular that pursued Vick heavily was Syracuse. Yet, as several news articles reported (e.g., Minium, 1999; White, 1999), Vick did not want to: (a) be the next Donovan McNabb (an ex-Syracuse football player) and (b) play football surrounded by mounds of snows and blasted by chilling winds off Lake Ontario. In fact, one reporter observed ―mother nature worked in Tech‘s favor, too‖ (White, p. D1). In other words, Vick enjoyed his time at Syracuse, including the time he was able to spend with Donovan McNabb, but at the end of the day ―it was too cold‖ and he ―got sick.‖ On the other hand, Ohio State University quarterback, Terrelle Pryor weighed mostly Northern options, such as Michigan and Penn State, because playing football in the cold was ―closer to reality in the NFL one day if I make it there. It‘s a whole different ballgame…I think you need to be familiar with it as you go on…I thought through all that stuff‖ (Wieberg, 2010). Conversely, Florida State‘s Head Football Coach Jimbo Fisher has warned southern players, especially skill-position players, from venturing out of the Sun Belt. Jimbo was quoted as saying (Staples, 2009): I don't know if we ever said, 'You'll freeze.' But the landscape of playing, especially if you're a skill guy, is not as conducive as it is in The South…The weather can prohibit you from using all your skills at times and prevent you from getting the numbers and recognition and things you want. I think it is a significant difference.

Also, and in tandem with the previous two examples, the sports media has taken note of the weather and attempted to link it to differences in athletic success. In a relatively recent issue of USA Today, the following was written (Wieberg, 2010): Draw a line East Coast to West — along the 37th or 38th parallel, generally accepted as the boundary of the nation's Sun Belt — and south of it lie the programs that own 11 national titles in the 12-year era of the Bowl Championship Series. North of it sits Ohio State, the lonely exception in 2002.

Specific to football recruiting, the following observations were made. From 2002-2010, a majority of Rivals.com‘s annual top 100 prospects came from the Sun Belt region and chose schools in the Sun Belt. Furthermore, during this same time period, over 25% of the top 100 student-athlete prospects from northern states chose warm-weather colleges (Wieberg). Ultimately, the impact of weather and climate on recruits and influential agents is likely to be mixed, if not cyclical. Recruits from cold weather states may not mind snow and chilling winds, just as recruits from warm weather states may not mind scorching heat and humidity.

Also, if the Big Ten and other cold weather conference regain places of prominence in college sports, with particular reference to football, then a shift may occur and more Sun Belt athletes could migrate north. Weather and climate may also be eclipsed by other, more dominant context factors such as academic reputation and availability of academic major. If an athletic coach from Columbia University, for example, is recruiting a student-athlete, the impact of the snow, ice, and biting winter winds of New York may be overshadowed by the school‘s top-10 U.S. News and World Report national university ranking. Overall, this external factor remains an interesting, if not potentially significant recruiting factor that could impact recruits‘ and influential agents‘ perceptions of the recruiter and their fit perceptions. Recruit and Influential Agent Fit Perceptions The proposed conceptual model presented in Figure 2.1 includes recruit and influential agent fit perceptions as well as the interaction between these individuals and their fit perceptions. Fit is generally thought to represent how individuals interpret ―characteristics of the job, organization, and recruiter in light of their needs and values‖ (Chapman et al., 2005, p. 929). The concept of fit aligns with subjective factors theory because decisions made by an individual (e.g., student-athlete) are ―not based upon weighting of objective factors in a pattern which is fairly consistent from individual to individual, but rather is made on a highly personal basis‖ (Behling et al., 1968, p. 17). What follows in this section is a rationale for including recruit fit perceptions, influential agent fit perceptions, and the interaction between the two. An overview specific to the concept of fit is then provided in the next section. The recruit is the recruiter‘s target, and therefore the extent to which the target individual perceives a strong fit should serve to increase the probability of a positive recruiting outcome. However, unlike most college graduates, high school student-athletes are unique because they are not adults. Instead, they are individuals under the care of parents, family members, or legal guardians. Thus, athletic recruiters may have to do more than simply influence recruits. These individuals may also have to ―sell‖ themselves and their university to important individuals in the student-athlete‘s life (i.e., influential agents), such as family members, friends, and high school coaches. To some extent, athletic recruiters may even be required to recruit the student- athlete and influential agents in hopes of positively influencing both, and getting the latter (influential agent) to turn into an advocate on their behalf. Within the extant scholarly and popular press literatures, several influential agents in

. particular have been found to impact recruit predictors (e.g., fit perceptions), which may in turn impact recruiting outcomes. These agents include parents, high school coaches, and even other recruits/peers (Bissinger, 1990; Croft, 2008; Feldman, 2007; Hu & Hossler, 2000; Lewis, 2007; Newberg, 2010; Widdison, 1982). Moreover, their impact depends largely on the strength of the relationship between themselves and the student-athletes. This means the greater the strength of the relationship between a student-athlete and an influencing agent, the greater the likelihood this individual will have an impact on recruit predictors and recruiting outcomes. Therefore, even though this area has not been investigated extensively in the sport management literature, it is included in the conceptual model of recruiting effectiveness in college sports to provide a more nuanced understanding of how recruiter characteristics unfold in the recruiting process. In other words, recruiting in college sports may require recruiters to efficiently split time between the recruit and influential agents if they are to secure positive recruiting outcome. Overview of Fit Perceptions Fit is thought to be an ―elusive‖ construct (Judge & Ferris, 1992). This elusiveness is largely the consequence of an overabundance of research diversity in both measures and conceptualizations of the concept (Edwards, Caplan, & Harrison, 1998; Kristof, 1996; Kristof- Brown, Zimmerman, & Johnson, 2005). In short, even though ―‗person-environment congruence‘ refers to the degree of fit or match between the two sets of variables…what exactly constitutes a fit or match is not totally clear‖ (Muchinsky & Monahan, 1987, p. 268-269). Furthermore, when evaluating fit, it may also be important to consider the recruitment targets. That is, ―for certain key positions or for positions that are difficult to fill, it may still be beneficial to engage in highly targeted recruitment processes to maximize fit, but the gains of such practices may be smaller for positions that have numerous vacancies‖ (Chapman et al., 2005, p. 938). Of the two, the former is more relevant to recruiters in the realm of intercollegiate athletics. The reasons being: the restricted number of scholarships allowed by the NCAA per year and the limited amount of athletic department financial resources that are allotted to recruiting student-athletes per year. Hence, athletic recruiting is firmly grounded in maximizing fit. When reflecting on the body work surrounding the concept of fit, Schneider (2001) remarked that ―of all the issues in psychology that have fascinated scholars and practitioners

. alike, none has been more pervasive than the one concerning the fit of person and environment‖ (p. 141).Thus, in spite of these challenges associated with studying fit, the concept has nevertheless received extensive scholarly attention (e.g., Ekehammer, 1974; Kristof-Brown & Stevens, 2001; Parson, 1909; O‘Reilly, Chatman, & Caldwell, 1991; Silva, Hutcheson, & Wahl, 2010; Turban, Lau, Ngo, Chow, & Si, 2001). During this span of time, various types of fit (e.g., person-vocation, person-job, person-group, and person-organization are just a few) have been addressed by researchers and thought to represent subtypes of fit tied to an overarching person-environment (PE) interaction (Law, Wong, & Mobley, 1998). Of these different types of fit, three are particularly relevant to present discussion of recruiters, recruits, influential agents, and recruiting outcomes in college sports. These three types of fit include: (a) person-job fit, (b) person-organization fit, and (c) person-recruiter fit. In following is a discussion of each type of fit based on the scholarly literature. Person-job (PJ) fit. Whereas person-vocation (PV) fit is generally matching an individual to a specific vocational choice (e.g., mechanic, engineer, radio broadcaster), PJ fit is more exact. Indeed, the focus is on the relationship between a person‘s characteristics and the specific job-related or work tasks required of them (Kristoff-Brown et al., 2005). Person-job fit can also be further conceptualized (Edwards, 1991) as: (a) individual characteristics matching job requirements and (b) individual needs and preferences being commensurate with the job being performed. According to Chapman et al. (2005), PJ fit was found to have a moderate relationship with job-organization attraction. Once hired, it is also likely to have a strong correlation with job satisfaction and organizational commitment (Kristoff-Brown et al.). Person-organization (PO) fit. Quite simply, PO fit is the ―compatibility between people and the organization in which they work‖ (Kristof, 1996, p. 1). The more pronounced the parallels are between individuals‘ goals, personalities, and values and their organizations‘ goals, personalities, and values, the greater the probability of success for these individuals within their respective organizations (Chatman, 1989; Ryan & Schmitt, 1996; Vancouver & Schmitt, 1991). In comparison to PR fit (person-recruiter fit), PO fit is a significantly stronger predictor of recruiting outcomes, including both job-organization attraction and acceptance intentions (Chapman et al., 2005). Also, once hired, PO fit is likely to have a strong relationship to both job satisfaction and organizational commitment (Kristof-Brown et al., 2005). Person-recruiter (PR) fit. Even though PR fit was found to be a weaker predictor than

PO fit and PJ fit (Chapman et al., 2005), this type of fit may still be of great importance early-on and late in the recruiting process, especially in a college sport setting. Insofar as the recruiter in college sports typically doubles as the actual athletic coach, PR fit may function as a more significant predictor of recruiting outcomes in sport than is usually reported in the management literature. Both PJ fit and PO fit are important, however, the connection and fit student-athletes have with a recruiter/coach may be even more important because this individual can directly impact their college athletic career (e.g., field position, playing time). In contrast, many of the studies (e.g., Connerley & Rynes, 1997; Harris & Fink, 1987; Wiles & Spiro, 2004) focused on the impact of recruiters on recruiting outcomes have studied college campus recruiters, who, despite being valued organizational members, may have little to no impact on the recruit‘s day- to-day life if hired by the organization. Recruit and Influential Agent Fit Interaction Explored in the proposed conceptual model (Figure 2.1) are the roles of both student- athletes (recruits) as well as influential agents. An illustrated explanation of recruits‘ and influential agents‘ fit perceptions is presented in Figure 2.3. This figure includes four possible interactions. In sum, if the influential agents and recruits both have negative perceptions of the recruiter‘s characteristics, this is likely to lead to negative recruiting outcomes (e.g., lack of attraction, rejection of scholarship offer). Conversely, if the influential agents and recruits both have positive perceptions of the recruiter‘s characteristics, this is likely to lead to positive recruiting outcomes (e.g., attraction to the coach and sport team, verbal commitment, acceptance of scholarship offer). If the recruit has positive perceptions but the influential agent has negative perceptions (or vice-versa), this is likely lead to debate between the two parties. In line with balance theory, it is anticipated that the recruit and influential agent will eventually come to a position of mutual agreement (i.e., both have positive perceptions or both have negative perceptions) in order to reestablish relational harmony.

Influential Agent (+) Influential Agent (+) Recruit (-) Recruit (+)

Perceptions of Recruiter Characteristics Influential Agents Influential Agent (-) Influential Agent (-) Recruit (-) Recruit (+)

Recruit

Figure 2.3: Recruit-influential agent fit interaction

Recruiting Outcomes In Figure 2.1, the general term of recruiting outcome was used to indicate the product of the recruit – influential agent fit interaction (see Figure 2.3). The desired recruiting outcome is a student-athlete selecting a recruiter‘s school. However, this result is not a guaranteed outcome of a positive recruit and influential agent fit interaction. Therefore, what is discussed in this section is the four most frequently studied recruiting outcomes, and when available, how they specifically interact with fit perceptions. Even though the labels of recruiting outcome variables may be inconsistently applied in the literature, there are four recurring outcome variables that have been identified (Chapman et al., 2005). These four recruiting outcomes include: (a) job pursuit intentions, (b) job- organization attraction1, (c) acceptance intentions, and (d) job choice decisions. Implicit with these outcomes is the logical progression that attraction leads to intentions, which then leads to an actual decision (Ajzen, 1985; Ajzen & Fishbein, 1980). However, this progression is not always clear-cut. Indeed, ―relationships between recruiting predictors and job choice are neither

1 In the management literature the focus is primarily on business organizations, not institutions of higher learning. Accordingly, unless the organization in a specific study was a university, the term organization is used in this section to reflect the terminology of the original research. 39

. direct nor predicted by a fully mediated model in which a given predictor relates to attraction attitudes, which leads to acceptance intentions and, in turn, job-choice‖ (Chapman et al., p. 940). In place of these relationships, two partial mediation models including attraction attitudes and intentions were found to better explain the relationships between selection decision criteria and the recruiting outcome of job choice. For example, recruiter characteristics and fit perceptions were reported to predict job choice outcomes through an attraction attitudes model whereas job-organizational characteristics found the best fit with an intentions mediated model (Chapman et al., 2005). Each of the four key recruiting outcomes as well as the noted predictors of each specific outcome is reviewed next. Job Pursuit Intentions The recruiting outcome of job pursuit intentions describes the intent of an individual to pursue a particular job. The outcomes of job pursuit intentions has included ―all outcome variables that measured a person‘s desire to submit an application, attend a site visit or second interview, or otherwise indicate a willingness to enter or stay in the applicant pool without committing to a job choice‖ (Chapman et al., 2005, p. 929). According to Chapman et al., as well as Jurgensen (1987) and Turban, Eyring, and Campion (1993), two particularly strong predictors of job pursuit intentions are linked to job-organization characteristics. The job characteristic found to be most significant was the type of work (p = .52). The organizational characteristic found to be the most significant was the image of the organization (p = .51). In addition, recruiter personableness was also found to be a strong predictor of job pursuit intentions (p = .50). Job-Organization Attraction The recruiting outcome of job-organization attraction refers to an individual‘s all- encompassing evaluation of a specific job and/or organization (Chapman et al., 2005). In their meta-analyses, Chapman and colleagues collapsed the three most frequently represented variations of job-organization attraction (e.g., Macan & Dipboye, 1990; Saks, Weisner, & Summers, 1994; Smither, Reilly, Millsap, Pearlman, & Stoffey, 1993) into a single category. For example: (a) ―How attractive is the job to you?‖ (Saks et al.), (b) ―How much would you like to work for this company?‖ (Macan & Dipboye), and (c) ―[This organization] is one of the best employers to work for‖ (Smither et al.). Of the recruiting outcome predictors identified by Chapman et al. (2005), perceived work environment and organizational image (i.e., organizational characteristics) were both reported as

. having a significant relationship with job-organization attraction. What is more, perceived work environment had the strongest relationship (p = .60) compared to all other predictors with job- organization attraction. In comparison, recruiter characteristics only had medium effect sizes, with personableness being strongest (p = .42). Hence: ―applicants may rely less on signals from recruiters as more information about job and organizational characteristics become available‖ (Chapman et al., p. 935). Acceptance Intentions In the scholarly literature, when actual job choice decisions are not able to be determined by researchers, the likelihood of accepting a job if offered (i.e., acceptance intentions) is often used as the dependent variable. Judge and Cable (1997), for example, studied job applicants‘ perceived fit with an organization and found this factor significantly predicted acceptance intentions incremental to the attractiveness of job attributes. Chapman et al. (2005) also reported the variable of acceptance intentions was ―the best available proxy variable for actual job choice‖ (p. 940). Nonetheless, using intentions in place of actual behavioral outcomes is not without limitations. Behavioral intention models take the stance the population being studied holds to the belief they can control what happens in the future, places values in what might be done in the future, and views future events in probabilistic thinking (i.e., probable versus improbable instead of view events with uncertainty; Cote & Tansuhaj, 1989). As a result, and in line with theories of reasoned action and planned behavior (Ajzen, 1985; Ajzen & Fishbein, 1980), actual behaviors are thought to be preceded by behavioral intentions. This progression, though not without fault and scholarly criticism (e.g., Manski, 1990), is supported by a sizeable and cross-disciplinary body of literature (e.g., Armitage & Conner, 2001; Hagger, Chatzisarantis, & Biddle, 2002; Judge & Cable, 1997; Pelling & White, 2009; Peslak, Ceccucci, & Sendall, 2010; Shimp & Kavas, 1984; Tarkiainen & Sundqvist, 2005) that is generally supportive of behavioral intentions acting as a precursor to actual behavior. Thus, in line with the statement by Chapman and colleagues (2005), intentions appear to be a suitable alternative for situations that prevent the assessment of actual behaviors. Overall, job and organizational characteristics have been reported as the strongest predictors of acceptance intentions (Chapman et al., 2005; Judge & Cable, 1997). Also, in the later stages of the recruitment process, person-job fit may be a stronger predictor of acceptance

. than other types of fit, such as person-recruiter fit (Chapman et al.). This generalized finding is similar to the position taken by Barber (1998). He held later events may be more significant to individuals‘ job choice intentions than early events, such as those taking place during initial face- to-face to meetings between the recruiter and job applicant. Job Choice Decision Job choice simply refers to the choice made by an individual about whether or not to accept a job offer. In the management literature, recruiting predictors have not been found to have a large or even moderate direct impact on job choice (Chapman et al., 2005). In following are several explanations as to why this might be the case. One explanation is the relationship between recruiting predictors (e.g., job-organization characteristics) and job choice may be partially mediated by attraction attitudes and acceptance intentions. Judge and Cable (1997) noted the relationship between predictors, such as organizational characteristics, and job choice is most likely not direct. Instead, it may be mediated by other factors (e.g., knowledge of job-organization; Chapman, Uggerslev, & Webster, 2003). Thus, as was the case with Chapman et al. (2005), a direct effects model may be a poor fit. A second explanation is a statistical issue in that point-biserial correlations are typically used to calculate the effect sizes of job choice decisions. Unfortunately, ―point-biserial correlations are limited by the distributions of both the dichotomous and continuous variables and in the most typical cases will have ceilings well below .80, and, thus, comparing the effect sizes for job choice and other outcome variables should be done with caution‖ (Chapman et al., 2005, p. 936). A third explanation is job-choice is not a one-way street, but instead requires a commitment from both the individual looking for a job and the employer looking to fill a job vacancy (Chapman et al.). That is, an offer must be made and then that offer must be accepted. In the sport management literature, at least as it pertains to student-athletes, most of the studies (e.g., Gabert et al., 1999; Letawsky et al., 2003; Judson et al., 2005; Pauline, 2010; Pauline et al., 2007) are based on participant recall and utilize questionnaires to ascertain which recruiting predictors most impacted student-athletes‘ choice decisions. Comments by Schwab, Rynes, and Aldag (1987), however, highlight problems with cross-sectional questionnaire research so often employed with student-athlete university selection research. Specifically, ―demand characteristics (in questionnaire rating research) may cause subjects to provide

. expectancy, instrumentality, and valence estimates for multiple attributes, even though they do not actually make their decisions on the basis of those attributes‖ (Schwab et al., p. 155). Furthermore, in the case of recruiters, unless there is a pre- and post-interaction study, it is difficult to determine a causal effect for a recruiting predictor (i.e., recruiter) on a recruiting outcome (i.e., job choice), in addition to being a difficult to control for extraneous variables (Harris & Fink, 1987; Schmitt & Coyle, 1976). To this end, determining a causal effect for specific recruiting predictors on job choice is clearly a challenge, both practically as well as methodologically. Hence, a proxy, such as acceptance intentions (though it is not without its own limitations as a dependent variable), may be the more realistic option available to a majority of recruiting-focused scholars (Chapman et al., 2005). Research Model and Hypothesis Development Over two decades ago, Schmitt and Schneider (1983) observed how the scholarly literature addressing organizational selection practices and the respective organizational outcomes was underdeveloped. In response, Schuler and Jackson (1987) detailed how to connect competitive strategies with HRM. They compiled HRM practices into five basic categories, the second of which was recruitment and selection (i.e., organizational staffing). More recently, in their review, Breaugh and Starke (2000) updated the contribution made by Schuler and Jackson, and developed an organizing framework of the recruitment process ―in order to stimulate the type of research that has been called for in previous reviews‖ (p. 430). Their model, which detailed the broad organizational process through which recruiting outcomes may be achieved, included five stages: (a) recruitment objectives, (b) strategy development, (c) recruitment activities, (d) intervening/process variables, and (e) recruitment results. In the Breaugh and Starke (2000) model, recruitment objectives (e.g., retention rate, cost of filling jobs, quality of applicants, etc.) are believed to lead to strategy development (e.g., whom to recruit? when to recruit?), which then leads to recruitment activities (e.g., recruitment sources, recruiters, and recruitment message). Between recruitment activities and the final stage of recruitment results (e.g., comparison of outcomes to the objectives), Breaugh and Starke added intervening/process variables (e.g., applicant attention, comprehension, interest). These variables were added to provide a mechanism to more effectively explain why recruitment activities result in particular recruitment outcomes.

Each of the areas described in the Breaugh and Starke (2000) model is undoubtedly important. Yet, for the purposes of this dissertation, the focus of this section is directed toward the third stage (i.e., recruitment sources, recruiters, recruitment messages), with particular attention being paid to recruiter characteristics and their impact on recruiting effectiveness in college sports. By way of the first conceptual model (Figure 2.1), recruiter characteristics contribute to recruiting outcomes through the interaction of recruit and influential agent fit perceptions. With this in mind, a testable research model (Figure 2.4) was developed; this model explores the direct effects of recruiter characteristics on recruiting effectiveness in college sports.

Recruiter Social Effectiveness

Political Skill

Recruiter Personality

Extraversion

Agreeableness Recruiting

Conscientiousness Effectiveness

Neuroticism Total Quality of Recruits Signed Openness

Recruiter Behavioral Integrity

Recruiter Performance Reputation

Career Record

Final NCAA Rank

Figure 2.4: Direct effects of recruiter characteristics on recruiting effectiveness

Theoretical Foundations of the Research Model To support the proposed recruiter research model (Figure 2.4), several key theories are brought together to explain the impact of each recruiter characteristic on recruiting effectiveness. At the heart of this study is the importance of interpersonal relationships and the premise that recruiter characteristics impact recruiting outcomes, with particular attention to the selection decisions of student-athletes (i.e., job choice). To this end, several recruiter characteristics are identified. More specifically, what follows in this section is an overview of the theoretical rationale lending support for the proposed relationships between recruiting predictors and recruiting effectiveness. One proposed predictor of recruiting effectiveness is the social effectiveness construct of political skill. This concept has been defined as ―the ability to effectively understand others at work and to use such knowledge to influence others to act in ways that enhance one‘s personal and/or organizational objectives‖ (Ferris, Treadway, Kolodinsky, Hochwarter, Kacmar, Douglas, & Frink, 2005, p. 127). In line with this construct, a political skill perspective provides one possible explanation as to how certain recruiters may have a better chance at achieving recruiting effectiveness than others. This is because political skill represents ―a comprehensive pattern of social competencies, with cognitive, affective, and behavioral manifestations, which have both direct effects on outcomes, as well as moderating effects on predictor – outcome relationships‖ (Ferris, Treadway, Perrewé, Brouer, Douglas, & Lux, 2007, p. 291). Essentially, the relevance of political skill theory to recruiting effectiveness is this. Political skill consists of four dimensions; these dimensions include social astuteness, interpersonal influence, networking ability, and apparent sincerity. Recruiters who possess political skill should therefore be able to more skillfully evaluate and then adapt to their recruiting context, make connections, and come across as authentic and sincere when interacting with recruits and influential agents. In other words, recruiters who possess political skill ―combine social astuteness with the capacity to adjust their behavior to different and changing situational demands in a manner that appears to be sincere, inspires support and trust, and effectively influences and controls the responses of others‖ (Ferris, Treadway et al., 2007, p. 291-292). Accordingly, the characteristic of political skill may have direct effect on recruiters‘ ability to sign a greater quantity and quality of recruits than other, less politically skilled recruiters.

Along with political skill, the Big Five personality dimensions (i.e., extraversion, agreeableness, conscientiousness, neuroticism, openness) are also thought to impact recruiting outcomes. Personality theory guides this particular factor and its relevance to recruiting effectiveness. When explaining personality theory, the following generalization was made by Hogan and Shelton (1998, p. 130): Personality theories have two major jobs to do. On the one hand, they analyze the nature of human nature and tell us about the universal features of human performance. On the other hand, they tell us about individual differences and define the major dimensions or parameters of human performance.

Furthermore, though it was acknowledged by Hogan and Shelton that personality can be thought of as the sum of a person‘s most important traits, these authors added that the ―various dimensions of personality are related to individual differences in peoples‘ desires to get along and get ahead, and job performance ratings reflect their relative success in doing so‖ (p. 140). Accordingly, because one of the fundamental goals of a recruiter is to establish positive relationships with both recruits and influential agents, personality factors may therefore have strong potential to positively contribute to recruiting outcomes. Even though minimal attention has been paid to the impact of recruiter personality on recruiting effectiveness (Chapman et al., 2005), recruiter personality characteristics (as signaled by the recruiter) may nevertheless have an impact on recruiting outcomes. Next, with regard to behavioral integrity, the potential impact of this factor on recruiting outcomes can be understood through role theory. The concept of behavioral integrity is grounded in the premise of word-deed alignment. Correspondingly, role theory is grounded in the basic idea business environments are not dynamic; instead, they are manufactured social settings that have a variety of mechanisms in place to promote reliable, conventional behavior by its members (Katz & Kahn, 1978). In other words, the focus of role theory is on routine or patterned social behaviors and the general expectations (by social participants) for adherence to characteristic social behaviors by performers. Another word for these expected behaviors is ―roles‖ (Biddle, 1986), and how behavioral integrity could impact recruiting effectiveness is as relatively straightforward premise. In short, there is likely to be a strong expectation for consistency between what a recruiter says and what a recruiter actually does. It is unlikely recruits and influential agents expect unreliable behavior from a recruiter, especially a recruiter whose organization is high on the list

. of potential schools to for a student-athlete to attend. Hence, recruiters who have high levels of behavioral integrity are likely to have an advantage in recruiting high quality student-athletes over those recruiters who violate expected recruiter roles. Finally, signaling theory (Spence, 1973) provides a logical foundation for explaining the impact of recruiter performance reputation characteristics on recruiting outcomes. This theory is relevant to the present study because one point that is evident from critical contact theory (Behling et al., 1968) is recruit uncertainty. That is, recruits (student-athletes) may have information gaps (in varying degrees) about a particular job and organization (in this case a university); this causes them to have uncertainty. Recruits may also lack the ability and/or motivation to gather information and become more knowledgeable about an organization (Larsen & Phillips, 2002). As a result, recruits may look to recruiters to remove the uncertainty and remedy their situation. More precisely, recruiters may directly inform recruits (e.g., provide information about job duties) or impression manage and send signals (cues) to recruits that provide a clearer picture of both observed, but not fully understand characteristics, and unobservable characteristics (Rynes, 1991). Essentially, the recruit views the recruiter as ―symbolic of broader organizational characteristics‖ (Rynes et al., 1991, p. 487). This has been described as signaling (Rynes et al.; Rynes & Miller, 1983; Spence, 1973). Signaling theory is grounded in economics perspective to the job market (see Spence, 1973 for an introduction to this area). Over the past several decades, however, signaling theory has been adapted in greater detail to recruiters and recruiting in the HRM literature (see Rynes et al., 1991; Rynes & Miller, 1983). When developing his theory, Spence‘s aim was two-fold. One, ―outline a conceptual apparatus within which the signaling power of education, job experience, race, sex, and a host of other observable, personal characteristics can be determined‖ (Spence, p. 356). Two, ascertain the extent to which the respective job markets account for information and whatever potential signals are sent. In this dissertation, signaling is interwoven with theories about political skill, personality, and behavioral integrity to explain how several recruiter performance reputation characteristics could impact recruiting effectiveness. Prior to Spence (1973), the concept of signaling had been discussed in the scholarly literature (e.g., Behling et al., 1968; Gerstner, 1966), but it had not been so formally outlined. Since that time, however, several researchers have linked signaling theory, either conceptually or

. through research evidence, to the role of recruiters and recruiting outcomes (e.g., Berkson et al., 2002; Chapman et al., 2005; DeBell, Montgomery, McCarthy, & Lantheir, 1998; Kreps & Wilson, 1982; Rynes, 1991; Rynes et al., 1991; Rynes & Miller, 1983). For instance, Rynes and colleagues found strong evidence for signaling theory when they reported (p. 514): recruitment experiences have stronger signaling value when little is known about the organization prior to a job search, when organizational representatives are in the same functional area as the applicant, and when experiences occur during the site visit as opposed to the campus interview.

Therefore, in line with assertions by Rynes, a prepared recruiter (i.e., recruiter preparedness) may indeed signal organizational efficiency. In sum, signaling (as a mechanism of social influence) has been repeatedly argued as a possible explanation for the role of recruiters in the recruiting process (Berkson et al., 2002; Breaugh & Starke, 2000; Chapman et al., 2005; Rynes, 1991; Rynes et al., 1991). Therefore, in this study, it seems appropriate to suggest that signaling theory informs how recruiter performance reputation characteristics (e.g., head coach‘s career record) are perceived by recruits, which may then lead to positive recruiting outcomes. Recruiter Political Skill and Recruiting Effectiveness Politics is about both influence and those who influence, and for centuries scholars have discussed in varying degrees the existence and role of politics in society. The famous philosopher Aristotle commented that mankind is, by its very nature, filled with political animals. Before him, Plato, in his most widely disseminated writing, The Republic, wrote (Plato & Allen, 2006, p. 26): The greatest penalty for refusing to rule is to be ruled by an inferior. It is fear of that, I think, that causes good men to rule, when they do, and they enter an office not because they think they are going to something good or a thing to be enjoyed, but because they think it a necessity, and they have no one as good or better than themselves to turn it over to.

Since the times of Plato and Aristotle, however, scholarly interest in politics has extended far beyond the halls of the School of Athens. Within the past 100 years the study of and publishing about politics has included a variety of areas, one of which is business firms and the behaviors of individuals and groups within these organizations. This refers to organizational politics, which has been defined as ―a subjective state in which organizational members perceive themselves or others as intentionally

. seeking selfish ends in an organizational context when such ends are opposed to those of others‖ (Gandz & Murray, 1980, p. 248). Generally, organizations have come to be viewed as inherently political arenas (e.g., Burns, 1961; Krackhardt, 1990; Mintzberg, 1983; Pfeffer, 1981). In the political arena, personal, group, and organizational success may be contingent upon the ability of individuals within these organizations to successfully pilot through their respective political environments. This has sparked interest in three distinct but interrelated areas of political research within business organizations: (a) political behavior, (b) political perceptions, and (c) political skill (Ferris & Hochwarter, 2011; Ferris & Kacmar, 2002). To a much lesser extent, a fourth area, political will (Mintzberg, 1983; Treadway, Hochwarter, Kacmar, & Ferris, 2005), which is an individual‘s willingness to expend energy and time in the pursuit of specific political goals, could also be included in this list. Of these various areas, political skill is the most salient area of organizational politics research to this dissertation. Therefore, from this point, the review of political skill and how it is relevant to recruiters progresses in the following fashion. First, political skill is defined and the dimensions of political skill are explained. Outlined next is the distinctiveness of political skill as a recruiter characteristic. This precedes a discussion of the antecedents and the direct and interaction effects of political skill. Explored in closing is a more detailed explanation of how recruiter political skill may contribute to recruiting effectiveness. Defining Political Skill Political behavior refers to the actual behaviors of individuals (the ―what‖). Political perceptions represent how the actions of an individual are perceived and subjectively interpreted by others. More specifically, how organizational politics are perceived ―involves an individual‘s attribution to behaviors or self-serving intent, and is defined as an individual‘s subjective evaluation about the extent to which the work environment is characterized by co-workers and supervisors who demonstrate such self-serving behavior‖ (Ferris, Harrell-Cook, & Dulebohn, 2000, p. 90). The final area is political skill, which is more than just the method of behavior, it is also the style. In other words, a ‗how to‘ construct (Ferris, Davidson, & Perrewé, 2005). This concept represents the only social effectiveness construct that has been ―explicitly developed to assess an employee‘s ability to recognize and then navigate the political realm of interpersonal relationships‖ (Treadway, Breland, Adams, Duke, & Williams, 2010, p. 139). Once again, political skill has been defined as: ―the ability to effectively understand others at work and to use

. such knowledge to influence others to act in ways that enhance one‘s personal and/or organizational objectives‖ (Ferris, Treadway et al., 2005, p. 127). Furthermore, even though political skill is thought to overlap with personality traits and social effectiveness constructs (e.g., emotional intelligence, social savvy, interpersonal social skill), it is a distinct construct (see Ferris, Perrewé, & Douglas, 2002 for a thorough review). For instance, social skill has been defined as the ―ability to perceive interpersonal or social cues, integrate these cues with current motivations, generate responses, and enact responses that will satisfy motives and goals‖ (Norton & Hope, 2001, p. 60). Peled (2000), however, when discussing the art of politicking for success, made a key—but not empirically tested—distinction between these two concepts. Specifically: ―political skills refer to the manager‘s ability to manipulate his/her inter-personal relationships with employees, colleagues, clients, and supervisors to ensure the ultimate success of the project‖ (Peled, p. 27). In slight contrast, even though inter-personal social skills ―refer to the ease and comfort of communications between these leaders [project leaders] and their employees, peers, superiors, and clients‖ (Peled, p. 27), such skills were not believed to explain project success. This is because social skill, unlike political skill, was not thought to include interpersonal influence capabilities. Dimensions of Political Skill When first attempting to measure political skill, Ferris, Berkson, Kaplan, Gilmore, Buckley, and Witt (1999) proposed a one-dimensional scale of political skill. Subsequent research has brought forth a multidimensional approach to the concept. This advancement has greatly improved upon limitations of a uni-dimensional approach (e.g., Ferris, Treadway et al., 2005; Ferris, Davidson et al., 2005). In their seminal work on political skill, Ferris, Treadway et al. (2005) published an 18- item questionnaire called the Political Skill Inventory (PSI). They reported the construct of political skill consists of four distinct, but moderately-related dimensions. These four dimensions include: (a) social astuteness, (b) interpersonal influence, (c) networking ability, and (d) apparent sincerity. All four dimensions are discussed next. Social astuteness. This dimension reflects high self-awareness and a keen, if not ingenious understanding of what is required in order to be accepted in various social situations (Goffee & Jones, 2005). It is also being keenly aware of the behaviors of others and how best to respond in order to achieve the desired personal and/or organizational objectives regardless of

. the social circumstances (Ferris, Treadway et al., 2007; Pfeffer, 1992). Moreover, for individuals low in political skill, organizational politics can lead to depressive symptoms (Brouer, Ferris, Hochwarter, Laird, & Gilmore, 2006). However, because politically skilled individuals are socially astute, they may perceive their environments as less stressful because they know how to effectively manage the particular political circumstances within their work environment. Interpersonal influence. This dimension of political skill describes a pleasant and persuasive personal style and ability to appear unpretentious and compelling. Individuals who have interpersonal influence possess a heightened level of interpersonal flexibility that ultimately enables them to more effectively exert sway over other individuals (Ferris, Treadway et al., 2007; Pfeffer, 1992) and achieve their desired goals. Essentially, through a heightened ability to calibrate their behaviors based on the context of the interaction as well as the person with whom they are interacting, politically skilled individuals are able to engage in more successful influence attempts (Harris, Kacmar, Zivnuska, & Shaw, 2007; Treadway, Ferris, Duke, Adams, & Thatcher, 2007). Networking ability. Individuals who are skilled networkers display an impressive capacity to initiate, develop, and also maintain relationships with a diverse group of contacts. Networking ability is often times essential to career success, especially in the realm of influencing political decisions (Watkins & Bazerman, 2003). Politically skilled individuals are therefore more likely to be successful in the workplace because they have the ability to capitalize on advantageous work opportunities (Ferris, Treadway et al., 2007). Individuals high in political skill are proficient networkers, able to more quickly and efficiently build productive work alliances and coalitions, and thereby have greater access to the resources necessary to reach individual and personal objectives (Pfeffer, 1992). Yet, as Treadway, Breland et al. (2010) observed, even though ―the possession of political skill is an asset to all employees, it does not, in and of itself indicate that individuals will engage in networking behaviors‖ (p. 144). In short, these individuals must want to engage in networking. Apparent sincerity. This dimension of political skill describes individuals who are forthright, and who display high levels of genuineness, authenticity, and sincerity (Ferris, Davidson et al., 2005; Ferris, Treadway et al., 2007). Apparent sincerity is important because, as both Bolino (1999) and Jones (1990) suggested, influence attempts are more likely to result in a successful outcome when the actor executing the influence attempt is perceived by others as

―real‖ and without ulterior motives. Essentially, ―this dimension of political skill strikes at the very heart of whether influence attempts will be successful, because it focuses on the perceive intentions of the behavior in question. And perceived intentions or motives are what shape the whole response‖ (Ferris, Davidson, et al., p. 11). Thus, even though political skill represents a form of manipulation, it is understated, subtle, and in stark contrast to the negative connotations of Machiavellian political behaviors. This latter point in particular is briefly elaborated upon in the following paragraph. A ―High Mach‖ (Christie and Geis, 1970) seeks as much power as possible and will stop at nothing to both gain power and then maintain control of this acquired power. Whereas a politically skilled individual will likely engage in helping behaviors and genuine interpersonal interactions, this is not the case for a High Mach (Dahling, Whitaker, & Levy, 2009; Wolfson, 1981). Instead, such individuals will seek their goals through deceitful and more direct manipulation techniques and react with hostility to opposition to their manipulation tactics (Geis, 1978; Hunt & Chonko, 1984). Thus, there is a clear distinction between politically skilled individuals and those individuals who engage in Machiavellian political behaviors. Distinctiveness of Political Skill Since the PSI (Ferris, Treadway et al., 2005) was first published, several studies have provided considerable evidence for the cross-cultural generalizability of the construct outside of North America (e.g., Blickle, Meurs, Zettler, Solga, Noethen, Kramer, & Ferris, 2008; Lvina, Johns, & Bobrova, 2009). There is also ample support for the construct and factorial validity of political skill (i.e., is it related to similar constructs and unrelated to different constructs; Ferris, Treadway et al., 2007: Ferris, Blickle, Schneider, Kramer, Zettler, Solga, Noethen, & Meurs, 2008). For example, political skill is unrelated to general mental ability (GMA), which includes fluid (reasoning ability) and crystallized intelligence (common understanding of real world issues; Ferris, Treadway et al., 2005). Additionally, the construct of political skill is related to but distinct from concepts such as political savvy (Chao, O‘Leary-Kelly, Wolf, Klein, & Gardner, 1994) and social competency constructs like emotional intelligence (EI; Goleman, 1995; 1998). In particular, political savvy ―suggests adeptness at the intuitive aspects of politics in organizations (Ferris, Treadway et al., 2007, p. 293); it was found to be moderately related to political skill (r = .47; Ferris, Treadway et al., 2005). Also, emotional intelligence is emotion-based interpersonal interactions and though it

. also has a modest relationship (r = .53) to political skill, political skill includes knowledge and interpersonal skills that exceed emotion (Ferris, Treadway et al., 2005). Dispositional and Personal Ability Antecedents to Political Skill Several studies have provided information about the antecedents of political skill in organizations (e.g., Ferris, Treadway et al., 2007; Liu, Ferris, Zinko, Perrewe, Weitz, & Xu, 2007). Notably, Ferris, Treadway and colleagues developed a conceptualization of five antecedents to the four dimensions of political skill based on previous empirical evidence. These antecedents (categorized as themes) included: perceptiveness (i.e., self-monitoring and conscientiousness), control (i.e., locus of control and self-efficacy), affability (i.e., extraversion, agreeableness, and positive affectivity), active influence (i.e., proactive and action-state), and developmental experiences (i.e., role modeling and mentoring). Antecedents to interpersonal influence, for example, were conceptualized as control, affability, and active influence. Further, as noted by the category of development experiences, even though certain individuals may be more naturally politically skilled than others, political skill is nevertheless a trainable skill (Blass & Ferris, 2007; Ferris, Davidson et al., 2005; Ferris, Treadway et al, 2007). For instance, social astuteness can be developed through leadership training programs and videotaped role-playing with feedback (Blass & Ferris; Ferris, Davidson, et al.). Moreover, in the case of interpersonal influence, one antecedent may be mentoring, given how (Ferris, Davidson et al., p. 44): At its best, mentoring involves the informal training and development of what, when, and with whom to things in the work environment, along with building the perceptive, interpersonal, and social effectiveness competencies that round out political skill.

Therefore, regardless of an individual‘s starting level of political skill, this is an area that can be enhanced through focused effort and various training methods and supervision/mentoring. Direct and Interaction Effects of Political Skill Direct effects. Political skill has been shown to positively impact team and managerial performance (Ahearn, Ferris, Hochwarter, Douglas, & Ammeter, 2004: Semadar, Robins, & Ferris, 2006) in addition to task and job performance (Blickle, Frölich, Ehlert, Pirner, Dietl, Hanes, & Ferris, 2011; Jawahar, Meurs, Ferris, & Hochwarter, 2008). Political skill has also been found to have both direct and interaction effects on influence tactic selection and execution (Ferris, Treadway et al., 2007; Kolodinsky, Treadway, & Ferris, 2007). For instance, Kolodinsky

. et al. reported political skill directly related to usage of the rationality influence tactic in HR decisions and actions. Additional direct effects include: improved leader self-efficacy (Douglas & Ammeter, 2004), work outcomes (Kolodinsky, Hochwarter, & Ferris, 2004; Smith, Plowman, Duchon, & Quinn, 2009), career prospects (Wei, Liu, Chen, & Wu, 2010), and career-related outcomes, such as total promotion, career satisfaction, life satisfaction, and perceived external mobility (Breland, Treadway, Duke, & Adams, 2007; Ferris, Rogers, Blass, & Hochwarter, 2009; Todd, Harris, Harris, & Wheeler, 2009). Interaction effects. In addition to the growing number of studies that have reported a direct effect, a multitude of studies have included evidence of strong interaction effects, especially with regard to the role of political skill in stressor- and strain-outcome relationships (e.g., Meurs, Gallagher, & Perrewé, 2010). Markedly, political skill has been found to moderate the following related relationships: role conflict-physiological strain (Perrewé, Zellars, Ferris, Rossi, Kacmar, & Ralston, 2004), role conflict-burnout (Jawahar et al., 2008), role overload- strain (Perrewé, Zellars, Rossi, Ferris, Kacmar, Liu, Zinko, & Hochwarter, 2005), negative affectivity-strain (Zellars, Perrewé, Rossi, Tepper, & Ferris, 2008), and perceived entitlement behavior-strain (Hochwarter, Summers, Thompson, Perrewé, & Ferris, 2010). Furthermore, political skill has been reported to have interactive effects between felt accountability-job tension effects on job performance ratings (Hochwarter, Ferris, Gavin, Perrewé, Hall, & Frink, 2007; Gallagher & Laird, 2008), personality and job performance relationships (Blickle, Meurs et al., 2008; Blickle, Wendel, & Ferris, 2010), and social stressors and the effect of political decision making on both job and career satisfaction (Harris et al., 2007). Political skill may also moderate the relationship between self- and supervisor-reported employee ingratiation (Treadway et al., 2007), and moderate the positive relationship between employee rationality and supervisor perceptions (Kolodinsky et al., 2007). What is more, political skill may aid individuals in their ability to circumvent unfavorable dyadic relationships. That is, political skill may serve as a significant moderator of the relationship between demographic dissimilarity – LMX quality (Brouer et al., 2009). Political skill may even serve to mediate the relationship between self-efficacy and hierarchical position attained (Ferris, Blickle et al., 2008). Finally, performance has been linked to career success and power. Yet, this link is inconsistent; in fact, many high performing individuals are unable to leverage work performance

. into increased influence and success (Treadway, Breland, Cho, Yang, & Duke, 2009). Nevertheless, when the relationship between performance and power was moderated by political skill, Treadway and colleagues reported that high performers were more likely than low performers to convert performance into workplace power, which was defined as ―the possibility of imposing one‘s own will upon the behavior of other persons‖ (Weber, 1954, p. 323). Impact of Recruiter Political Skill on Recruiting Effectiveness The primary goal of this dissertation is to better understand recruiter characteristics and how they impact recruiting effectiveness in college sports. To this end, the social effectiveness construct of political skill was included in this study because it specifically refers to the capacity of an individual to successfully exercise influence over others. Politically skilled recruiters are presumed to be socially astute (i.e., they are shrewd socially) and able to effortlessly and effectively calibrate their behavior to the contextual demands of their specific situation. They are also savvy networkers, easily inspiring comfort, trust, and confidence in others. What is more, when engaging in influence attempts (Ferris, Treadway et al., 2007, p. 304): Individuals high in political skill know which particular type of influence tactic or strategy to employ in each situation. These individuals also know precisely how to execute a specific tactic or strategy in just the right way to demonstrate the desired effect, thus ensuring the success of the influence attempt.

This success is partly the consequence of these individuals‘ behaviors being perceived as a sincere, authentic, and genuine. Accordingly, recruiters who possess high levels of political skill should be able secure a greater number of high quality student-athletes. In short, recruiters who possess political skill should be better able to make connections with recruits and when they do, they should be able to more accurately evaluate their recruiting context. That is, these recruiters will be able to more precisely gauge the recruiting environment and key persons (i.e., recruit and their parents or guardians) and then calibrate their behaviors in ways that best fit with these factors. Politically skilled recruiters will also be able to more effectively compile, package, and transmit recruiting predictor information (Ferris, Treadway et al., 2007). Therefore, because politically skilled recruiters are socially astute as well as highly adept at developing and executing influence strategies, they will be able to identify and then masterfully present key information to recruits and their corresponding influential agents. This should then lead to positive recruiting outcomes such as signing a greater number of high-quality recruits.

Recruiter Personality and Recruiting Effectiveness As it was observed previously, recruiters have been researched for decades, but there exists only a short list of personality characteristics and behavioral traits that have been studied relative to recruiters in a recruiting context. Also, of the factors comprising this list, only two (i.e., informativeness and personableness) have been linked moderately to recruiting outcomes, particularly job pursuit intentions (Breaugh & Starke, 2000; Chapman et al., 2005; Rynes, 1991). Even then, there are several noted concerns about the impact of these factors on recruiting outcomes (Chapman et al.; Rynes & Barber, 1990; Rynes et al., 1991; Schwab et al., 1987). One concern is after reporting the link between recruiter personableness and job pursuit intentions (p = .50), Chapman and colleagues (2005) commented ―this large validity coefficient must be interpreted with caution because it was only based on three studies‖ (p. 935). A second concern is the importance of recruiter characteristics is also based on substantially different methodologies. In certain cases, cross-sectional questionnaire rating research has been employed, whereas other studies have been grounded in longitudinal, interview-based approaches to recruiters and the recruiting process (Schwab et al., 1987). Therefore, at least in terms of quantitative research, there is a lack of established and recruiter-specific scales to evaluate the impact of recruiter characteristics on recruiting outcomes. Also interesting is that of the recruiter characteristics receiving attention in the extant literature, almost no attention has been paid to the convergence of personality traits in the Big Five model (Barrick& Mount, 1991; Costa & McCrae, 1988; Digman, 1989, 1990; McCrae & Costa, 1987). Even so, a case can still be made that parallels exist. For instance, factors such as personableness and warmth are similar to the Big-Five category of agreeableness. The lone exception to this observation (at least to our knowledge) is a study by Dykeman and Dykeman (1996). Together, they examined the personality profiles of executive search recruiters (ESRs). The main goal of the Dykeman and Dykeman study was to compare and contrast the personality of ESRs from the general adult population. Of note was that on both extraversion and openness scales, ESRs reported higher than expected frequencies. Overall, veteran ESRs were ―described as: (a) secure, hardy, and generally relaxed even under stressful conditions, (b) extraverted, outgoing, active, and high spirited, (c) open to new experiences, and (d) dependable and moderately well organized‖ (Dykeman & Dykeman, p. 83). Practically, the authors noted one benefit of the recruiter profile they reported was the opportunity to improve fit

. between the recruiter and client as well as the recruiter and the personnel they are looking to hire for the specified business firm. What is ultimately evident from the information in this section (as well as what has been previously provided), is the existence of considerable challenges when attempting to link the impact of recruiter characteristics and traits on recruiting outcomes. Not only have a limited number of characteristics been studied, but those characteristics that have been studied have been examined infrequently and without considerable methodological uniformity. This should not preclude examining the impact of recruiter personality characteristics on recruiting outcomes, although it does mean there is not much research evidence (specific to recruiters) to guide this examination nor is there a large body of evidence to serve as a point of comparison with the findings of this study. With this in mind, the inclusion of recruiter personality characteristics provides several key contributions to both recruiting research and practice. First, one suggested course of action for future recruiting research has been to explore the possibility of individual differences amongst recruiters that may better explain recruiting effectiveness. According to Chapman et al. (2005), one of the areas ripe for examination is recruiter personality. Second, though the recruiter behavioral characteristic of warmth is distinct from a personality trait embodying a generalized and personalized tendency toward warmth, the recruit may not perceive a difference. Also, the latter personality factor may serve a similar function for recruiters in the way of signals. That is, athletic recruiter personality factors may send ―signals‖ to student-athletes, which could then be leveraged by recruiters to positively impact these recruits‘ perceptions toward both the recruiter and the recruiter‘s university. Therefore, what follows is a discussion of the Big Five personality factors and an explanation as to how they may impact recruiting effectiveness. Overview of the Big Five Personality Dimensions In the past several decades, multiple meta-analyses have been conducted about specific outcomes (e.g., job performance, job satisfaction, entrepreneurial intentions) and their link to the Big Five (e.g., Barrick & Mount, 1991; Clarke & Robertson, 2005; Giluk, 2009; Judge, Heller, & Mount, 2002; Larson, Rottinghuas, & Borgen, 2002; Thomas, Whitman, & Viswesvaran, 2010; Trapmann, Hell, Hirn, & Schuler, 2007; Zhao, Seibert, & Lumpkin, 2010). For example, the dimension of conscientiousness was reported to be a valid predictor of job performance, regardless of occupational group, therein providing evidence of importance to the

. accomplishment of work tasks in a variety of jobs (Barrick & Mount). Ultimately, given the long-standing prominence of personality research in both the management and psychology disciplines, the purpose of this section is not to collect, condense, and then re-communicate this massive wealth of information. Neither is the purpose of this section to engage in the scholarly taxonomic debate surrounding a five- or six-factor model (Digman, 1990) and exact dimensional labels (Costa & McCrae, 1992; Norman, 1963). This is not only unfeasible, but much of this information is irrelevant to a specific comprehension of recruiter personality and recruiting effectiveness. Therefore, what follows is a brief introduction to the five-factor model. This includes general overviews of each factor as well as how the Big Five is distinct from proactive personality, a factor which may also interact with political skill. The argued importance of the Big Five to recruiting effectiveness is articulated at the close of this section. Emergence of the Big Five. The early roots of a personality taxonomy primarily stem from works of McDougall (1932) and Cattell (1943, 1946), which were then improved upon over the next thirty years (see Borgatta, 1964; Norman, 1963; Tupes, 1957; Tupes & Christal, 1961). Most noticeably, Norman‘s work and initial personality factor labels (i.e., extraversion, emotional stability, agreeableness, conscientiousness, culture) stemmed what would in the future come to be called as the ―Big Five‖ (Goldberg, 1981). Since that time, there has been both agreement and debate about these broad dimensions, as well as concern about imprecise dimensional specifications (Briggs, 1989; Livneh &Livneh, 1989) and measurement instruments (see Digman, 1990 for a thorough overview). Eysenck (1991) stated (p. 786): ―Where we have literally hundreds of inventories incorporating thousands of traits, largely overlapping but also containing specific variance, each empirical finding is strictly speaking only relevant to a specific trait‖ (p. 786). Additionally, John (1989) observed that a key problem when studying personality is ―which Big Five?‖ or ―whose Big Five?‖. In other words, what is lacking is an adequate theoretical explanation of both the how and the why of personality. These observations serve to reinforce the fact that a host of challenges and academic debates exceeding the scope of this dissertation arise upon reviewing the personality literatures. Therefore, what is expressed in following is a presentation and overview of the approach to personality research that is employed in this dissertation. Herein, the Big Five is held to include the following dimensions: extraversion, agreeableness, conscientiousness, neuroticism, and

. openness. This perspective is grounded in the work of John, Donahue, and Kentle (1991) and their Big Five Inventory (BFI), and it was selected for three keys reasons. One, even though there is greater accord with respect to the number of dimensions than with the meaning of the dimensions, this does not preclude general agreement across studies (Digman, 1990). Thus, though the labels used to categorize the Big Five may vary (e.g., Neuroticism versus Emotional Stability), this has little to no bearing on the underlying nature of the personality factor. Two, the approach taken by John and colleagues has received modest, if not strong scholarly acceptance (John, Naumann, & Soto, 2008; John & Srivastava, 1999). Three, in terms of practicality, the BFI (in contrast to other personality measures such as Costa and McCrae‘s (1992) NEO questionnaires) provides for a succinct and accessible assessment of the five personality dimensions when time and participant interest levels are of concern. This perspective, with particular regard to the BFI, though addressed in the following paragraphs, is given more due diligence and methodological attention in Chapter 3. Big Five dimensions. In their book chapter, John and colleagues (2008) defined each of the Big Five dimensions in the following way. The definition ascribed to extraversion (dimension I) was ―an energetic approach toward the social and material world and includes traits such as sociability, activity, assertiveness, and positive emotionality‖ (John et al., p. 120). Extraverted individuals exemplify positive and outgoing characteristics. Agreeableness (dimension II) ―contrasts a prosocial and communal orientation toward others with antagonism and includes traits such as altruism, tender-mindedness, trust, and modesty‖ (John et al., p. 120). With regard to interpersonal interactions, agreeable individuals are likely to be patient, empathetic, and good listeners. The dimension of conscientiousness (dimension III) was referred to as ―social prescribed impulse control that facilitates task- and goal-directed behavior, such as thinking before acting, delaying gratification, following norms and rules, and planning, organizing, and prioritizing tasks‖ (John et al., p. 120). It may also extend to include meticulousness and a strong, if not an incessant desire to maintain an elevated performance standard. Neuroticism (dimension IV) on the other hand, ―contrasts emotional stability and even-temperedness with negative emotionality, such as feeling anxious, nervous, sad, and tense‖ (John et al., p. 120). Essentially, highly neurotic individuals are likely to have mood swings, impulsiveness, and display self-consciousness (Costa & McCrae, 1992). Finally, openness (dimension V) was described as ―the breadth, depth, originality, and complexity of an

. individual‘s mental and experiential life‖ (John et al., p. 120). In essence, open individuals have an affinity for new experiences and an elevated level of intellectual curiosity (McCrae & Costa, 1987). Proactive Personality: A Comparison and Cause for Exclusion Definition and distinctiveness. According to Bateman and Crant (1993), the ―prototypic proactive personality, as we conceive it, is one who is relatively unconstrained by situational forces, and who effects environmental change. Other people, who would not be so classified, are relatively passive - they react to, adapt to, and are shaped by their environments‖ (p. 105). In effect, proactive personality represents the dispositional tendencies of individuals to prompt change in an array of situations (Bateman & Crant). Furthermore, proactive personality is ―taking initiative in improving current circumstances or creating new ones‖ (Crant, 2000, p. 436). Proactive individuals should also ―have a greater sense of self-determination and self- efficacy in their work lives‖ (Seibert, Crant, & Kraimer, 1999, p. 418). Overall, when compared to the five-factor model, proactive personality has been found to demonstrate unique variance in criteria exceeding that of the Big Five personality factors (Crant & Bateman, 2000; Major, Turner, & Fletcher, 2006). In short, proactive personality captures both ―conceptually and empirically, some unique elements of personality not accounted for by the five-factor model‖ (Crant & Bateman, p. 66). For instance, proactive individuals are thought to exemplify a self-starting spirit and a strong motivation to learn (Frese, Fay, Hilburger, Leng, & Tag, 1997; Major et al.) that exceeds general extraversion. In support of this, Crant (1996) reported undergraduate and MBA students demonstrating proactive personalities were more positively correlated with entrepreneurship (i.e., intentions to own one‘s own business). Additionally, proactive individuals are future oriented, persistent, and effective at seizing existing opportunities as well as creating opportunities/favorable conditions to facilitate progress toward individual and/or organizational goals (Bateman & Crant; Crant, 1996, 2000; Parker, Williams, & Turner, 2006). Thus, proactive individuals possess more than just conscientiousness and openness because they identify and create opportunities, and they also tend to be relentless in their pursuit of achieving an identified objective (Crant, 2000). Outcomes associated with proactive personality. Though not as widely studied as the Big Five, proactive personality has been associated with a variety of positive organizational and individual outcomes (see Crant, 2000 for a comprehensive review). For instance, at the

. organizational level, proactive personality has been associated with organizational innovation (Parker, 1998) and group dynamics and team performance (Kirkman & Rosen, 1999). Research evidence also points to a relationship between proactive individuals and entrepreneurship (Crant, 1996) as well as career promotions and success (Seibert, Crant, & Kraimer, 1999; Seibert, Kraimer, & Crant, 2001; Fuller & Marler, 2009). Further, in a contemporary study by Greguras and Diefendorff (2010), they reported an indirect link between proactive personality and life satisfaction, in-role performance, and organizational citizenship behaviors (OCBs). Leadership is another area linked to proactive personality (e.g, Bateman & Crant, 1993; Crant & Bateman, 2000; Deluga, 1998). In a rather unique study, Deluga found a relationship between perceived American presidential proactivity and ratings of charismatic leadership and presidential performance. Exclusion of proactive personality. Along with the Big Five, proactive personality fits in well with the objective of this research, which is to better understand how recruiter characteristics impact recruiting effectiveness in college sport. For instance, from a dispositional approach, proactive personality is grounded in individuals‘ needs to understand and control their environments (White, 1959). In other words, as Bandura (1986) commented, ―people create environments and set them in motion as well as rebut them. People are foreactive, not simply counteractive‖ (p. 22). Also, as Crant (2000) observed, certain impression management techniques (e.g., ingratiation) are by their very nature proactive, which by extension suggests the individual may have a proactive personality. Incidentally, the inclusion of proactive personality alongside the Big Five may result in too much overlap with the social effectiveness construct of political skill. For instance, similar to political skill, proactive individuals are going to seek to understand their environments, network, and act in ways that may best contribute to the achievement of personal and/or organizational objectives. Yet, whereas proactive personality describes a general disposition toward these behaviors, it does not provide an explanation as to how these individuals execute these behaviors and successfully achieve their specified goals. The construct of political skill provides an explanation for more than just general desire to invoke change. It is a style and social effectiveness construct; thus, political skill explains both how and why a particular approach may be successful in achieving a desired outcome. Hence, given the likelihood of an interaction between proactive personality and political skill, the former was excluded from this study.

Impact of Recruiter Personality on Recruiting Effectiveness Minimal attention has been paid to the impact of recruiter personality on recruiting effectiveness (Chapman et al., 2005). Moreover, in a sport context, only rarely has head coach personality/style been noted as a moderately important predictor of student-athlete selection decision. Pauline et al. (2010), for example, listed it as the ninth most influential factor. Nevertheless, a point made by Wiggins and Trapnell (1996) provides an erudite and attractive explanation as to why a personality – recruiting effectiveness relationship could exist. What they argued was an underlying emphasis, if not focus, of the major personality dimensions on getting along and getting ahead. That is, these dimensions are either directly or indirectly linked to relationship development. Specifically (Wiggins & Trapnell, p. 134): Our own granting of conceptual priority to the first two factors the FFM [Ascendance and Agreeableness] is done so on the ground of their relative ‗purity‘ as lower order indicates of the highly abstract notions of agency and communion. On this view, the remaining dimensions of Conscientiousness, Neuroticism, and Openness/Intellect are viewed as dimensions that either facilitate (desirable) or interfere with (undesirable) the development and maintenance of agentic and communal enterprises within a social group. More radically, we assert that the interpenetration of agentic and communal concerns into the other three factors is so complete that manifestations of both can be identified within each of the factors.

Recruiter personality may therefore contribute to recruiting effectiveness because one inherent function of recruiters is to develop a strong and positive relationship with both recruits and relevant influential agents in order to get the recruit to commit to the recruiter‘s academic institution. Recruiter Behavioral Integrity and Recruiting Effectiveness Defining Behavioral Integrity Quite simply, behavioral integrity represents ―the perceived pattern or alignment between an actor‘s words and deeds‖ (Simons, 2002, p. 19). It is ―the consistency of an acting entity‘s words and actions‖ (Palanski & Yammarino, 2007). In this respect, behavioral integrity is value- neutral. In other words, the construct is not indicative of values or morality; instead, it demonstrates longitudinal word-deed consistency of a target individual (Palanski & Yammarino). Behavioral integrity is also thought to consist of several distinct attributes (Simons, 2002). First, it is subjective. In short, regardless of what target individuals think/perceive, their

. behavioral integrity is largely the consequence of how others perceive their word-deed alignment. In this respect, behavioral integrity is not so much what actually happens, but what is perceived as happening relative to what was said by an individual. Second, it is an ascribed trait. This means that with behavioral integrity there will inherently be some level of causal attribution with regard to the relevant behavior. Third, though it is more likely to be ascribed to individuals, behavioral integrity can also be directed toward organizations (of which a focal individual may be representative). For instance, scholarly explanations of behavioral integrity have included individuals as well as work teams (Palanski & Yammarino, 2009), as a positive relationship between team behavioral integrity and team trust has been reported (Palanski, Kahai, & Yammarino, 2011). Fourth, and in similarity to reputation, behavioral integrity is slow to develop but can be promptly lost in instances of word-deed misalignment (e.g., Barry Bond steroid scandal, Tiger Woods infidelity scandal). Differentiating Behavioral Integrity and Reputation In addition to behavioral integrity, another recruiter characteristic that is being examined in this study is recruiter performance reputation. Reputation is similar to but nevertheless distinct from the concept of behavioral integrity. One definition of behavioral integrity is ―the perceived pattern or alignment (or misalignment) between a target‘s words and deeds‖ (Simons, 2002, p. 19). Yet, whereas reputation is held to be the aggregate of opinions about a specific entity (Bromley, 1993; Frink, Hall, Perryman, Ranft, Hochwarter, Ferris, & Royle, 2008), behavioral integrity usually refers to an individual‘s perception of a target, with particular reference to word-deed alignement. Outcomes of Behavioral Integrity Several key consequences of behavioral integrity at the individual level have been reported in the extant scholarly literature. For example, Prottas (2008) linked behavioral integrity to outcomes such as absenteeism, well-being (health), and life satisfaction. Behavioral integrity has also been demonstrated to have a significant relationship with trust at both individual (Simons, Friedman, Liu & McLean-Parks, 2007) and team levels (Palanski et al., 2011) as well with OCBs (Dineen, Lewicki, & Tomlinson, 2006). Moreover, in the meta-analysis by Davis and Rothstein (2006), behavioral integrity was reported to have a strong and positive relationship with employees‘ job and leader satisfaction and their levels of organizational commitment.

Impact of Recruiter Behavioral Integrity on Recruiting Effectiveness When recruiters recruit student-athletes, they engage in social exchanges with both recruits and influential agents. According to social identity theory (SIT; Blau, 1964), during this process, recruiters will attempt to engage in exchanges that produces feelings of ―personal obligation, gratitude, and trust‖ (p. 94). Therefore, a key aspect of this social exchange process is the word-deed alignment of the recruiter. If this individual is perceived as saying one thing while doing another, this could result in distrust and a lack of satisfaction with the recruiter (as opposed to trust and a positive reciprocal exchange relationship). Moreover, word-deed misalignment during the recruiting process may signal to recruits and influential agents that there may also be misalignment once on the recruit is committed to team. For instance, recruits and influential agents may perceive the recruiter as saying a recruit will start for the team during his/her freshman year while at the same time also thinking the recruiter will not follow through with this statement (i.e., recruit will not start). To this end, it is not unreasonable to draw a relationship between recruiter behavioral integrity and positive recruiting outcomes. Recruiter Performance Reputation and Recruiting Effectiveness Embedded within the printed lines of the articles detailing the youthful exploits beneath the lights of Friday nights and the professional glories of any given Sunday is a word seemingly synonymous with a discussion of athletic competition. That word is reputation, an in its simplest form it represents the sum of opinions about an entity (e.g., person, organization; Bromley, 1993). Inside the hyper-scrutinized world of sports, where even victories may come with criticism if they are not stylistically satisfying to spectators, the facilitation and preservation of reputation has long been a point of interest and conversation in the US. Historical cases in point: the heralded sport rivalries between the Big Three football powers of Harvard, Yale, and Princeton from the late 1800s and early 1900s. Yet, when observed in the context of organizational behavior research, the study of reputation represents a relatively new area of academic inquiry, especially with regard to the similar but nevertheless distinct areas of organizational and personal reputation and their role in recruiting effectiveness. With particular reference to sport management, though student-athletes have reported coach and organizational reputation (such as university academic reputation) to be important factors influencing their university choice decisions (e.g., Croft, 2008; Elliot, 1995;

Judson et al., 2005; Mathes & Gurney, 1985; Reynaud, 1998), these areas have not otherwise been tested empirically. There is, as a result, a lack of extensive research findings to determine how various types of reputation precisely impact recruiting outcomes in college sports. With this limitation in mind, the role of reputation in recruiting effectiveness is developed in this section. First, the distinctiveness of reputation as a construct when compared to other constructs, such as a celebrity, is discussed. Next, organizational and personal reputations are differentiated from one another and discussed separately. Then, as it pertains to this dissertation, recruiter performance reputation is explored in light of recruiting effectiveness in college sports. Clarification and Distinctiveness of Reputation In the management literature, particularly studies focused on recruitment, it is not uncommon to see the term ―reputation‖ confused with terms such as ―identity‖, ―image‖, ―familiarity‖, and ―culture‖ (Cable & Turban, 2001; Berkson et al., 2002). For example, Ferris, Berkson and colleagues, in line with observations of Dutton, Dukerich, and Harquail (1994), noted the factors of ―reputation‖ and ―identity‖ to be distinct judgments of the same target. Identity pertains ―to the attributions made of an organization by its members and ―reputation‖ relates to the attributions made about the same organization by outsiders‖ (Berkson et al., p. 361). Moreover, though factors like image, culture, and familiarity may impact how job applicants and recruits perceive an organization (Gatewood, Gowan, & Lautenshlager, 1993; Kilduff & Krackhardt, 1994; Rynes, 1991), they are nevertheless distinct from the core concept of reputation (Cable & Turban). Corporate image, for instance, has been thought to represent a global or total impression an entity, such as a business firm, has on the minds of others (Dichter, 1985). Even though image has been used synonymously with reputation (e.g., Dowling, 1993), it is generally viewed as a related but distinct construct (e.g., Davies, Chun, da Silva, & Roper, 2004; Dutton et al., 1994) of which reputation may be a dimension (Barich & Kotler, 1991; Sung & Yang, 2008). More precisely, image has been viewed as an opinion formed independent of actual experience whereas reputation is ―something that is dependent upon actual experience of the organization‖ (Davies et al., p. 126). Reputation is also distinct from the constructs of ―celebrity‖ and ―legitimacy‖. Whereas ―celebrity is often a fleeting state driven by CEO – media exchanges, reputation is a more enduring trait fueled, in large part, by a history of interactions with various stakeholders‖

(Treadway, Adams, Ranft, & Ferris, 2009, p. 554-570). Additionally, several researchers have convincingly separated organizational legitimacy and reputation (e.g., Deephouse & Carter, 2005; Lawrence, 1998; Ruef & Scott, 1998). Notably, based on both theory and empirical evidence, Deephouse and Carter developed the following view (p. 332): Thus, we view legitimacy as the social acceptance resulting from adherence to regulative, normative or cognitive norms and expectations. In contrast, we view reputation as a social comparison among organizations on a variety of attributes, which could include these same regulative, normative or cognitive dimensions.

Furthermore, Rindova, Pollack, and Hayward (2006) argued for the existence of three key distinctions between the intangible assets of celebrity, legitimacy, and reputation based on the categories of theoretical foundations, sociocognitive basis of the asset, and processes through which the asset is built. First, reputation is based in signaling theory, whereas legitimacy and celebrity are grounded in institutional theory and mass communication theories respectively (Rindova et al., 2006). Second, reputation describes the perceived ability of a firm (or individual) to generate value for relevant entities (i.e., stakeholders), whereas legitimacy is ―the generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within a social system‖ (Suchman, 1995, p. 573-574). Also, the basis of celebrity is the ―perceived potential to achieve important results and an attractive social identity‖ (Rindova et al., p. 54), instead of the perceived ability to create value for an organization. Third, reputation is built through strategic processes (e.g., financial performance, product quality). In contrast, legitimacy is developed through external validation (e.g., conformity to established norms, awards and third-party recognition), while celebrity is largely a media created product (e.g., portrayal or organizational activities, character development; Rindova et al.). Overview of Organizational Reputation Even though the study of reputation in the HRM literature has not received a considerable amount of scholarly attention in the academic journals until more recently, a small but nevertheless impressive research foundation has formed, mainly in regard to organizational reputation (e.g., Berkson et al., 1999; Berkson et al., 2002; Carter & Deephouse, 1999; Friedman, 2009; King & Whetten, 2008; Pfarrer, Pollock, & Rindova, 2010; Rindova, Williamson, & Petkova, 2010; Turban, Forret, & Hendrickson, 1998; Williamson, King, Lepak, & Sarma, 2010). Indeed, over the past thirty years researchers have developed diverse notions of

. what constitutes reputation, and these different notions stem from a wide variety of academic disciplines. What follows is a representative, but not exhaustive sample of all the possible definitions of reputation (see Rindova, Williamson, Petkova, & Sever, 2005; Walker, 2010 for excellent reviews of organizational reputation definitions and literature) and contemporary research issues about reputation (see Bergh, Ketchen, Boyd, & Bergh, 2010). Definitions and research advancements. From an institutional perspective, reputation has been defined in several different ways (Fombrun, 1996; Roberts & Dowling, 2002). Fombrun viewed it as stakeholders‘ knowledge and emotional reactions toward a specified firm. Additionally, Hannon and Milkovich (1996) defined organizational reputation as ―the collective judgments of an organization‘s overall character by groups of similarly interested and informed people that are based primarily on the past actions of the firm‖ (p. 408). For instance, employee layoffs, especially for a fledgling business firm, can result in negative organizational reputation (Flanagan & O‘Shaughnessy, 2005). Likewise, Fombrun (1996) summed up organizational reputation as ―a firm‘s overall appeal compared to other leading rivals‖ (p. 72). In line with marketing research, Shamsie (2003) described organizational reputation as ―the level of awareness that the firm has been able to develop for itself…as well as for its brands‖ (p. 199). Weiss, Anderson, & MacInnis (1999) viewed reputation as ―a global perception of the extent to which an organization is held in high esteem or regard‖ (p. 1078). Additionally, Milewicz and Herbig (1994) defined reputation as ―the estimation of the consistency over time of an attribute of an entity‖ (p. 41). In contrast to marketing theory, there are also economic and HRM theoretical perspectives to organizational reputation. Shapiro (1982) explored firm-specific reputation in a perfectly competitive environment but one with imperfect consumer information (i.e., product attributes are not perfectly observable prior to purchase). Thus, in line with his economic approach, ―reputation formation is a type of signaling activity: the quality of items produced in previous periods serves as a signal of the quality of those produced during the current period‖ (Shapiro, p. 659-660). With regard to HRM, reputation represents a specific and shared judgment of a business firm‘s philosophies, policies, and practices about managing organizational personnel (Hannon & Milkovich, 1996), which may indirectly improve the overall organizational (corporate) reputation (Friedman, 2009).

Additionally, Highhouse, Brooks, and Gregarus (2009) took a rather unique approach to examining the formation of corporate reputation. In contrast to the more traditional approaches to reputation, these researchers looked at reputation from an impression management (IM) perspective. First, they defined organizational reputation as a ―global (i.e., general), temporally stable, evaluative judgment about a firm that is shared by multiple constituencies‖ (Highhouse et al., p. 1482). Next, they explained the approach they took to studying reputation in the following manner (Highhouse et al., p.1483): based on the idea that although structurally different, both individuals and organizations share social objectives,‖ which enabled them to attempt ―to understand the self- presentation motives of corporations and how they manifest themselves in the impressions held about them by relevant constituents.

Overall, ―scholars tend to define organizational reputation either as specific assessments of a relevant attribute (e.g. ability to produce quality), as the economics perspective suggests, or as collective knowledge about and recognition of a firm, as the institutional perspective suggests‖ (Rindova et al., 2005, p. 1035). Moreover, in their comprehensive work on organizational reputation, Rindova et al. reviewed over 60 studies using the construct of organizational reputation and, in addition to proposing a general definition, they proposed the existence of two distinct organizational reputation dimensions. These dimensions (i.e., perceived quality and prominence) were based on signaling and institutional theories respectively. Perceived quality captures the degree to which stakeholders evaluate positively a specific attribute of an organization (e.g., production of quality products). The dimension of prominence was linked to the large-scale and collective recognition an organization received in its noted field. For instance, in the study by Rindova et al. (2005), prominence was measured by the number of recruiters that had nominated a particular school. That is, ―regardless of the individual reasons that led each recruiter to select a particular school, across the 1,600 recruiters who completed the survey, this nomination procedure captured the relative prominence of business schools among corporate recruiters as a stakeholder group‖ (Rindova et al., p. 1040). Finally, Barney (1991) took a resource-based view (RBV) and described organizational reputation as a proxy for a guarantee or formal contract. According to this line of thinking, reputation represents an intangible asset that is unique and can significantly contribute to organizational performance, and it is therefore also relevant at both the organizational and personal levels. Recently, Boyd, Bergh, and Ketchen (2010) confirmed the value of a RBV

. model when studying reputation and performance. In contrast to the two-stage approach taken by Rindova et al. (2005), they reported the reputation – performance relationship was strong when the interdependencies of reputation were considered jointly instead of separately. In other words, ―the determinants of reputation appear to have a synergy affect, where their integration creates more value than when the parts are considered separately‖ (Boyd et al., p. 603). Thus, in light of these two academic camps (i.e., Boyd et al., 2010; Rindova et al., 2005), there are several key points that can be taken away from the burgeoning reputation literature. One, to a limited extent, there is academic agreement on certain matters of reputation, such as a basic definition and the need for additional conceptual development about reputation as a strategic resource. Two, in spite of scholarly agreement on several issues, there is ultimately a lack of consensus on which approach best explains the manner in which organizational reputation impacts organizational performance. To this end, continued scholarly inquiry and debate is required to better understand the significance of organizational reputation, its dimensions, antecedents, outcomes, and operationalization. Outcomes of organizational reputation. Although by no means an extensive list compared to other management constructs, a variety of strategic benefits have still been linked to organizational reputation. Several potential benefits are increased firm profitability (Roberts & Dowling, 2002), reduced firm costs (Deephouse, 2000; Fombrun, 1996), the ability to change premium prices (Fombrun; Rindova et al., 2005), and positive customer behaviors, such as word- of-mouth (WOM) intentions (Hong & Yang, 2009). With particular reference to recruiting, organizational reputation may be linked to being seen as a more attractive employer (Highhouse, Zickar, Thorsteinson, Stierwalk, & Slaughter, 1999) as well as attracting larger and higher- quality applicant pools (Barber, 1998; Berkson et al., 2002; Fombrun; Turban & Cable, 2003; Williamson et al., 2010). Notably, Turban and Cable (2003) were the first to empirically test this previously untested proposition about applicant pools. After conducting a two study design, they reported firms with more positive reputations attracted larger applicant pools. There was also evidence, though not as strong, that firms with more positive reputations were able to interview a greater number of higher-quality applicants. Several months later, a similar study was published by Cable and Turban (2003). In this instance, organizational reputation was linked to job pursuit as well as job seekers‘ willingness to receive lower wages to join organizations with positive

. reputations. More recently, Williamson et al., (2010) also reported findings in an analogous vein wherein organizational reputation moderated the relationship between Website attributes and job applicant attraction levels. Overview of Personal Reputation Definition. Similar to the various definitions of organizational reputation, personal reputation has been defined differently according to discipline and research area. Once more, though this list is not is exhaustive, it still provides an adequate and diverse cross-section of the various perspectives of personal reputation. First, a rather basic, but direct approach to defining personal reputation was offered by Gladstone (1963); he linked personal reputation to competence. Similarly, Tsui (1984) suggested that in the case of managers, reputation is the consequence of meeting constituents‘ expectations with regard to performance and role- competency. Bromley (1993) on the other hand viewed personal reputation as the product of how others within the organization view this individual. Essentially, personal reputation was seen as ―a nucleus of interconnected impressions shared and expressed by a high proportion of members of a defined social network‖ (Bromley, p. 42). More specifically, from a social network perspective, personal reputation may be the result of an individual‘s network, or social group to which this individual belongs (Kilduff & Krackhardt, 1994). This approach in particular is frequently employed in the extant management-based reputation literature. As a consequence of these various approaches, Ferris, Blass, Douglas, Kolodinsky, and Treadway, (2003) sought to remove researcher confusion and devised a general and interdisciplinary view of personal reputation. Specifically: (Ferris, Blass et al., p. 215): perceptual identity formed from the collective perceptions of others, which is reflective of the complex combination of personal characteristics and accomplishments, demonstrated behavior, and intended images presented over some period of time observed directly or reported from secondary sources, which reduces ambiguity and unexpected future behavior.

In sum, personal reputation is how a particular community collectively judges the qualities and/or character of a specific individual. Together, the definitions for both organizational and personal reputation reflect what ultimately amounts to subjective perceptions and judgments of a particular entity by relevant entities, such as a local community and its members.

Development of personal reputation. Reputation forms over time and through the key processes of development and maintenance (Fombrun & Shanley, 1990). This evolution is both episodic and continual, wherein ―the continual processes of developing and maintaining a reputation are punctuated by episodic events‖ (Ferris, Blass et al., 2003, p. 228). With regard to the development of personal reputation—leader reputation in particular—Hall, Blass, Ferris, and Massengale (2004) proposed three categories that house the ―different qualities, features, and characteristics of individuals that combine to varying degrees based on context, and as such contribute to leader reputations‖ (p. 519). These categories included: (a) human capital, (b) social capital, and (c) leader style. What follows is a review of each of these categories. Human capital was described as the extent to which individuals improve their worth through the process of acquiring relevant knowledge and skills via educational and experiential means. In essence, ―human capital is the knowledge and skill that individuals have, which is the direct result of their investments in education and training‖ (Hall et al., 2004, p. 519). Next, at the individual level, social capital was viewed as ―the leveraging of one‘s human capital, personological capital (i.e., personal skills and abilities), and social networks‖ (Hall et al., p. 520). As for leader style, Hall and colleagues proposed that leaders who have a positively perceived leader style will be more likely to have a positive reputation. They contended in particular that ―political skill, as a component of leader style, is critical to reputation development through its capacity for the deliberate packaging of behavior, and the strong sense of adaptability in performance‖ (Hall et al., p. 523). For the development of reputation, routine behavior may be synonymous with reputation maintenance. Yet, for individuals to maintain their reputations, they must first be aware of the perceived reputation, and thereafter act in accordance with these perceptions while also taking into account that contexts regularly change and therefore reputation must be frequently recalibrated (Ferris, Blass et al., 2003). Additionally, individuals must actively engage in the defense of their reputation through situation-appropriate impression management behaviors (Greenberg, 1990). This, for example, might include apologies and/or excuses. To defend or enhance one‘s reputation, individuals may also develop advocates. In turn, advocates may influence less informed individuals to trust a particular peer or supervisor, thereby strengthening the focal individual‘s personal reputation (Wong & Boh, 2010).

Outcomes of personal reputation. In the mid-1980s, Tsui (1984) explored managerial reputation, although his efforts gained little notoriety until the end of the twentieth century. Indeed, it was not until more recently that there has been noticeable inquiry into reputation at the organizational and also personal level. Moreover, of these two areas, the latter has only just begun to generate more consistent and high-quality scholarly attention (e.g., Blass & Ferris, 2007; Ferris, Perrewé, Ranft, Zinko, Stoner, Brouer, & Laird, 2007; Hall et al., 2004; Johnson, Erez, Kiker, & Motowidlo, 2002; Kilduff & Krackhardt, 1994; Laird, Hochwarter, Ferris, Perryman, & Zinko, 2009; Ranft, Zinko, Ferris, & Buckley, 2006; Wong & Boh, 2010). Even though studies extending beyond the conceptual realm with regard to the outcomes of personal reputation remain exceedingly limited, what evidence does exist shows promise for this up-and-coming area of reputation research. Several promising findings include examples of positive leader reputation being linked to an increased likelihood of subordinate perceptions of leader competency (Gioia & Sims, 1983) and trust in the leader (Whitmeyer, 2000). Also, in a study by Bartol and Martin (1990), one implied finding was reputation for expertness impacted financial rewards. Personal reputation has also been reported to moderate a multitude of relationships. These relationships include political behavior – work outcomes relationships (Hochwarter et al., 2007), accountability – strain relationships (Laird et al., 2009), and organizational identification – cooperation relationships (Polzer, 2004). Of note, individuals who experienced perceived low levels of personal reputation were found to experience ―more job tension and depressed mood at work and less job satisfaction as felt accountability intensified‖ (Laird et al., p. 76). Impact of Performance Reputation on Recruiting Effectiveness Clearly evident from the research that has amassed about reputation is that it represents a complex and multi-faceted concept at both organization and personal levels. Indeed, an assorted variety of factors contribute to our wide-ranging understanding of reputation. Although personal reputation has not been explicitly examined in the sport-based recruiting/student-choice literature, several studies have provided evidence that team rank, team performance (i.e., win/loss record), and the reputation of the coaching staff may be somewhat influential in student-athletes‘ school decisions (e.g., Doyle & Gaeth, 1990; Pauline et al., 2007; Pauline, 2010). Therefore, in light of the focus of this dissertation, recruiter performance reputation was

. conceptualized as the factors of head coach career record and head coach final NCAA team ranking (from the previous season). These factors are based on objective information. As a consequence, they do not perfectly coincide with the provided definitions of personal reputation, which are grounded in subjective assessments from relevant individuals. Be that as it may, these two factors are nevertheless viewed as relevant proxies for performance reputation. Although they are not exact reflections of performance reputation, a coach‘s record and team ranking are most likely key factors contributing to how student-athletes and influential agents perceive a particular coach‘s performance (thereby contributing to performance reputation). Thus, performance reputation information is argued to potentially function as a signal to recruits and influential agents (Berkson et al., 2002). These signals then hold the potential to establish a positive (or negative) impression in the minds of recruits and influential agents about the recruiter (the respective coach). Hence, depending on the capabilities of the recruiter, performance reputation information can be championed with telling effect to enhance the likelihood of achieving positive recruiting outcomes. Research Hypotheses Accordingly, this dissertation includes the formulation of the following hypotheses:  Hypothesis 1: Recruiter political skill will have a positive and direct effect on the total quality of recruits signed.  Hypothesis 2: Recruiter personality will have a direct effect on the total quality of recruits signed. More specifically, recruiter extraversion will have a positive and direct effect on the total quality of recruits signed.  Hypothesis 3: Recruiter agreeableness will have a positive and direct effect on the total quality of recruits signed.  Hypothesis 4: Recruiter conscientiousness will have a positive and direct effect on the total quality of recruits signed.  Hypothesis 5: Recruiter neuroticism will have a negative and direct effect on the total quality of recruits signed.  Hypothesis 6: Recruiter openness will have a positive and direct effect on the total quality of recruits signed.

 Hypothesis 7: Recruiter behavioral integrity will have a positive and direct effect on the total quality of recruits signed.  Hypothesis 8: Recruiter performance reputation characteristics will have a direct effect on the total quality of recruits signed. More specifically, head coach (recruiter) career record will have a positive and direct effect on the total quality of recruits signed.  Hypothesis 9: Final team NCAA ranking (from the previous season) will have a positive and direct effect on the total quality of recruits signed.

CHAPTER THREE METHOD Driving this dissertation is the underlying goal of better understanding what leads to recruiting effectiveness in college sports, with particular reference to athletic recruiters and NCAA DI soccer. One problem with the current recruiting literature is the absence of scholarly attention in the realm of sports. Another issue is the lack of information (across both the sport and management disciplines) about recruiters, especially the impact of their characteristics on recruiting outcomes. Therefore, to explore the impact of recruiter characteristics on recruiting effectiveness in NCAA DI women‘s soccer, a quantitative research approach was employed in this dissertation. The outline of Chapter 3 is as follows: (a) research design, (b) participants and procedures, (c) measures, and (d) analysis. Research Design This study is a quantitative survey design. Even though a causal relationship cannot be determined, this study design still provides an opportunity to empirically confirm a relationship between recruiter characteristics and recruiting effectiveness. In other words, a quantitative approach allows for the testing of the interaction between the specified nine predictor variables and the outcome variable of total quality of recruits a recruiter was able to sign. Participants and Procedures Sampling According to Green (1991), when determining a minimum sample size to test both the R2 as well as significance tests on the regression slopes, the following general formulas should be used (respectively): (a) 50 + 8k, with k being equal to the number of IVs and (b) 104 + k, where k is equal to the number of IVs. Of the two formulas, the one that produces the largest value should then be used in the research study. Accordingly, because there are nine IVs included in the research model, a minimal sample size of 122 is recommended in order to reliably run a regression model. Participants At present, no systematic research has been conducted about the impact of recruiters on recruiting effectiveness in college sports. Essentially, little to nothing is known about how recruiter characteristics directly impact recruiting outcomes. As a result, there is a relatively non-

. existent sport-based research foundation to which the focus of the current study can be compared against. Be that as it may, there are still a preponderance of opportunities to study recruiting and recruiters across all college sports and competitive levels. Even so, for the purposes of this study, the initial sampling frame is head women‘s soccer coaches from all relevant NCAA DI universities. Only head coaches that were resident in their positions at the beginning of the data collection were included. Coaches were surveyed during the off-season (spring). There are several reasons why these sport coaches were selected for this study. One key reason is accessibility. Data collection took place during the spring. Because women‘s soccer was not in-season during the time of the data collection, the assumption held by the researcher was this would lead to a better response rate. Also, even though football is not a spring sport, football coaches were not selected based on the recommendations of senior faculty and previous research experience with this population (i.e., poor response rate from head coaches). A second reason pertained to existing connections within the soccer community. One challenge of survey research is getting adequate response rates, especially in a timely manner. Therefore, having existing contacts who are head women‘s soccer coaches provided an opportunity to increase survey response rates because these contacts vouched for the credibility of the researcher and the legitimacy of the study. In effect, the recommendation of the head coach (i.e., at Florida State University) served as an introduction that, at least in premise, established a sense of familiarity between the solicited head women‘s soccer coach and the unknown researcher that would otherwise fail to exist. Procedures A list of all NCAA DI head women‘s soccer coaches and contact information was compiled from both the official NCAA website (www.ncaa.org) and respective university and college athletic department websites. Each school was provided a code (i.e., 1, 2, 3…) to distinguish it from other institutions. This was necessary in order for the researcher to be able to subsequently link predictors, such as final 2010 NCAA rank to recruiting effectiveness. The personal identity of the participant was not required for participation in the study. Once this information was compiled, questionnaire packets were put together. Questionnaire packets consisted of the following: (a) letter of introduction to the study, (b) participant consent form, (c) questionnaire packet, and (d) a self-addressed stamped envelope (SASE). After one month, if less than 122 responses were received, a second round of mailing

. would have commenced. This step was not required because over 122 responses were received after the first mailing attempt. Once the questionnaire was completed, participants were directed to place the completed survey in the SASE and return it to the researcher. Upon receipt, the researcher transferred all data to an SPSS database stored in the researcher‘s secured, university office. This study required identifiers (e.g., university name, conference affiliation). However, once all the data were collected and matched, the identifiers were removed from the research records to ensure participant anonymity and answer confidentiality remain private. Measures In order to reflect the context of this dissertation, the measurement instruments required only minor modifications. These changes did not diminish item integrity. Note as well, the scales employed in this dissertation represented established scales. That is, each scale had previously demonstrated internal consistency reliabilities exceeding the recommended threshold of .70 (Nunnally, 1978). Political Skill Recruiter (head women‘s soccer coach) political skill was measured using the 18-item (α = .94) political skill inventory (PSI; Ferris, Treadway et al., 2005). This 18-item scale has been repeatedly reported as a valid and reliable instrument to assess an individual‘s level of political skill (e.g., Breland et al., 2007; Harvey, Harris, Harris, & Wheeler, 2007; Hochwarter et al., 2007; Semandar et al., 2006; Todd et al., 2009). The PSI includes the four-dimensions of political skill: social astuteness, interpersonal influence, networking ability, and apparent sincerity. All 18 items were measured on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Big Five Personality To measure the Big Five personality dimensions of recruiters, the Big Five Inventory (BFI; John et al., 1991) was used in this dissertation. The BFI is a 44-item measurement tool requiring participants to indicate on a 5-point Likert scale ranging from 1 (disagree strongly) to 5 (agree strongly) the extent to which they agree or disagree with a statement. In this study, all 44-items were measured on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). In this study, the BFI demonstrated alpha coefficients above .70 (.77 to .86).

Previously, the BFI has demonstrated acceptable reliability and validity evidence (Benet- Martinez & John, 1998; John & Srivastava, 1999). In particular, John and Srivastava (1999) reported, after conducting multiple samples across the US and Canada, alpha reliabilities of the BFI scales generally ranged from .75 to .90 (with an average above .80). Furthermore, after comparing the BFI to the NEO Five Factor Inventory (NEO-FFI; Costa & McCrae, 1992) and unipolar trait descriptive adjectives (TDA; Goldberg, 1992) questionnaires (both of which are established and frequently employed personality assessment tools), John and Srivastava reported the alpha scores for the BFI, TDA, and NEO-FFI were .83, .89, and .79 respectively. Their results also indicated that across all three instruments the Big Five can be satisfactorily measured with both convergent and discriminant validity. In the end, it was concluded if time is not an issue, the full NEO Personality Inventory, Revised (NEO PI-R; Costa & McCrae, 1992) is the best choice. Otherwise, the BFI is a shorter assessment that is just as efficient and effective as either the NEO-FFI or the TDA (John & Srivastava). This instrument (i.e., BFI) was designed to provide an efficient and flexible assessment of the five dimensions of personality not found in alternative instruments. For example, the NEO PI-R; (Costa & McCrae, 1992) consists of 240-items. The BFI also uses single adjectives as items; it does not use definitions or elaborations (John, 1989). Ultimately, this short scale is advantageous because, as Burisch (1984) observed, ―short scales not only save testing time, but also avoid subject boredom and fatigue (p. 219). Behavioral Integrity Recruiter behavioral integrity was assessed with a self-report version of an 8-item measured developed by (Simons et al., 2007). This instrument is focused on individual leaders, not work teams or organizations. The items are designed to assess the consistency between what is espoused and what is actually done. Items were scored on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Cronbach‘s alpha was acceptable (α = .92). Performance Reputation Women‘s soccer head coach performance reputation was assessed using two variables: head coach career record and NCAA rank (final ranking for the 2010 season). These two variables are thought to represents performance reputation characteristics of a head coach. Each was assessed using secondary data compiled by the researcher. Incidentally, because reputation

. is an external perception (held by another), each of these factors was thought to be a representative proxy for actual head coach performance reputation. That is, reputation is defined as subjective, but in this study it was measured using objective indicators of performance (i.e., winning percentage is neither perceptual nor malleable). Even so, both winning percentage and NCAA rank are likely to be key factors contributing to the formulation of subjective judgments of head women‘s soccer coaches. Career record. Head coach career record represented the respective coach‘s overall record as an NCAA DI head coach (i.e., winning percentage). This information was collected from official athletic department websites. To determine a coach‘s record, the standard NCAA formula was used: wins + ties / total # of games = winning percentage. Each win was worth one point whereas ties received half-a-point. NCAA rank. In addition to a head coach‘s winning percentage, another performance reputation characteristic was determined to be the rank of the coach‘s team. As the leader of the team, NCAA rank is reflection of the coach just as much as it is a reflection of the on-field performances of the student-athletes. In this study, 2010 women‘s soccer rank was assessed using the official NCAA final season rankings. This is based on the NCAA‘s ratings percentage index (RPI); it includes a ranking for each of the over 300 women‘s soccer teams competing in DI women‘s soccer. Recruiting Effectiveness (Outcome) Quality of recruits signed. Recruit total quality was determined in part through the following website: www.topdrawersoccer.com. This site is devoted to NCAA men‘s and women‘s intercollegiate soccer. Much like rivals.com, topdrawersoccer ranks athletes throughout the United States. International players are not rated on this site. The ranking criteria does not include a student-athelte‘s respective coach or parents; thus, the rankings are meant to be purely objective critiques of soccer players. Student-athletes are ranked from 1-star (fair) to 5-stars (best of the best). What follows is an explanation of the star ratings per the topdrawer website. Unrated athletes receive an NR (Not Rated); these individuals have either not been scouted by topdrawer or are not deemed ready enough to receive even a 1-star rating. A five-star (best of the best) soccer player is someone who ranks in the highest percentile of his/her peers and is coveted by coaches and scouts, pro and college alike. Such a player has a

. command of the technical, tactical, mental, and physical elements of the game. This also includes the emotional maturity required to handle success and be a good team member. A four-star (very strong) player represents one of the strongest players. This is someone who is always among the most exceptional footballers on the field. These players may be progressing toward a five-star ranking, and are still attracting a considerable amount of attention from recruiters. Three-star (strong) players are fairly strong in the technical, tactical, physical, and mental aspects of soccer. However, they are not currently as talented in these areas as their four- and five-star counterparts. Two-star (good) athletes represent talented players who need further development. They can still contribute to a game; yet, their limitations in key areas of skill development may inhibit their ability to make a consistent and significant impact on the field. One-star (fair) players are described as individuals who have not yet come into their own on the field. In short, they have unrealized potential that could lead to good things down the line. Presently though, these individuals lack the complete package of requisite technical, tactical, physical, and mental abilities that are one display with three-, four-, and five-star players. For the purposes of this dissertation, recruiter‘s (head women‘s soccer coaches) were asked to identify both the number and quality of the recruits they personally had a significant (primary) role in recruiting for the 2011-2012 women‘s soccer season. They were asked to base the quality of the recruit on the ranking system provided by topdrawersoccer. Then, to determine a head coach‘s overall recruiting effectiveness (total quality of recruiting class), the following formula was used: Total Quality = Star Total / Total Number of Recruits For example, if a head coach indicated he/she personally recruited two student-athletes with four-star ratings, the total quality for this coach would be four (i.e., 4 = 8/2). In contrast, if a head coach indicated he/she personally recruited five athletes with a two-star rating, this individual‘s total quality would be two (i.e., 2 = 10/5). Data Analysis The intent of regression analysis is to examine the relationship between an IV and a DV. Regression does not imply a causal relationship; instead, regression analysis reveals a relationship between an IV or IVs and a DV (Tabachnick & Fidell, 2001). Unlike a simple regression, multiple regression is an extension of bivariate regression and allows for the

. researcher to use two or more IVs (Stevens, 2002). The generalized formula for regression analysis takes the following form:

Y´ = A+ B1X1 + B2X2 + … + BkXk In this formula, Y´ is the predicted value of the DV. A is the Y intercept. The Xs represent each of the IVs. k represents the number of IVs. The Bs are the coefficients assigned to the IVs during the regression analysis. In terms of the different types of regression analysis, a standardized regression analysis allows the researcher to group predictors together and include them into the regression analysis in different steps as blocks (Aiken & West, 1991; Cohen, Cohen, West, & Aiken, 2003). Generally, in the first step, the most important or established predictors are entered (i.e., Block 1). Then, in the next step, factors lacking the same level or theoretical and/or empirical support are added (Block 2). This type of regression analysis was selected for the present study. Minimal attention has been paid to recruiter characteristics and how they impact recruiting effectiveness. This is particularly true in the sport management literature and it therefore inhibits the prescribing of recruiter predictor order based solely on previous research evidence. Accordingly, order of entry of the predictors was based on theory, logic, and how the items were evaluated (i.e., recruiter self-report data versus secondary data collected by the researcher). More specifically, self-report recruiter characteristics that had previously received even a small amount of theoretical or empirical support in the scholarly literatures were added in the first step (Block 1). In the second step, recruiter performance reputation characteristics were entered into the regression analysis (Block 2); these factors (i.e., career record and NCAA team rank) were generated from secondary data.

CHAPTER FOUR RESULTS Descriptive Statistics According to list of NCAA rankings, there are currently 322 women‘s soccer programs competing in NCAA DI women‘s soccer. Therefore, 322 surveys were sent out to NCAA DI head women‘s soccer coaches. A total of 131 coaches responded (41% response rate). There were 88 male (67.2%) and 43 female (32.8%) respondents. In terms of ethnicity, 117 head coaches were Caucasian (89.3%) and 5 were African American (3.8%). Less than 10% of the participants indicated they were Asian American, Hispanic American, multiracial or another category (e.g., European, South American). The participants‘ average age was 41 (M = 40.97, SD = 7.41). Also, over fifty percent (54.4%) of the head coaches who participated in this study had 10 or more years of experience as a head coach. Finally, athletic conferences with at least five head soccer coaches participating included the Atlantic 10, Atlantic Coast Conference (ACC), Big 12, Big West, Horizon, Metro Atlantic, Mid-American, Southeastern Conference (SEC), Southern, Southland, Summit, and Sunbelt. Table 4.1 provides a complete list of the participating athletic conferences. In addition, descriptive statistics (M, SD) are provided for the independent and dependent variables. Table 4.2 includes the descriptive statistics for the factor and items of Political Skill. Table 4.3 provides the statistical information for Personality; this includes personality factor totals as well as the means and standard deviations for the items of each of the five personality dimensions (i.e., Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness). Table 4.4 and Table 4.5 include the descriptive statistics for Behavioral Integrity and the two Performance Reputation variables respectively. Table 4.6 includes the corresponding statistical information for the dependent variable, Total Quality (i.e., average star rating of signed recruits).

Table 4.1: Participating Head Women‘s Soccer Coaches‘ Athletic Conference Distribution

Conference Frequency Percent

American East 3 2.3

Atlantic 10 6 4.6

ACC 5 3.8

Atlantic Sun 3 2.3

Big 12 5 3.8

Big East 4 3.1

Big Sky 2 1.5

Big South 4 3.1

Big 10 4 3.1

Big West 7 5.3

Colonial 4 3.1

Conference USA 4 3.1

Great West 3 2.3

Horizon 5 3.8

Ivy League 1 .8

Metro Atlantic 6 4.6

Mid-American 6 4.6

Missouri Valley 3 2.3

Mountain West 3 2.3

Northeast 4 3.1

Ohio Valley (OVC) 2 1.5

Pacific 10 (Pac 10) 3 2.3

Patriot League 4 3.1

SEC 6 4.6

Southern 6 4.6

Southland 5 3.8

South Western 3 2.3

Summit 6 4.6

Sunbelt 6 4.6

West Coach 4 3.1

Western Athletic Conference (WAC) 4 3.1

Total 131 100

Table 4.2: Descriptive Statistics for Recruiter (Head Coach) Political Skill

Factor and items M SD Political Skill

I spend a lot of time networking with others. 5.22 1.37 I am able to make most people feel comfortable and at ease around me. 6.05 1.08 I am able to communicate easily and effectively with others. 6.02 1.03 It is easy for me to develop good rapport with most people. 6.07 1.10 I understand people very well. 5.80 1.01 I am good at building relationships with influential people. 5.40 1.07 I am particularly good at sensing the motivations and hidden agendas of 5.32 1.19 others. When communicating with others, I try to be genuine in what I say and do. 6.56 .78 I have developed a large network of colleagues and associates whom I can 5.44 1.33 call on for support when I really need to get things done. I know a lot of important people and I am well connected. 4.91 1.30 I spend a lot of time developing connections with others. 4.98 1.31 I am good at getting people to like me. 5.50 1.06 I believe it is important that people believe I am sincere in what I say and 6.56 .81 do. I try to show a genuine interest in other people. 6.35 .98 I am good at using my connections and networks to make things happen at 5.31 1.18 work. I have a good intuition or ―savvy‖ about how to present myself to others. 5.71 1.15 I always seem to instinctively know the right things to say or do to 5.25 1.08 influence others. I pay close attention to people‘s facial expressions. 5.65 1.16

Table 4.3: Descriptive Statistics for Recruiter (Head Coach) Personality

Factors and items M SD Extraversion

Is talkative 4.89 1.57 * Is reserved 4.32 1.72 Is full of energy 5.80 1.00 Generates lots of enthusiasm 5.76 1.01 * Tends to be quiet 4.47 1.81 Has an assertive personality 5.59 1.20 * Is sometimes shy, inhibited 4.53 1.65 Is outgoing, sociable 5.47 1.34 Agreeableness * Tends to find fault with others 4.45 1.50 Is helpful and unselfish with others 5.92 1.02 * Starts quarrels with others 5.67 1.53 Has a forgiving nature 5.40 1.35 Is generally trusting 5.94 1.18 * Can be cold and aloof 5.28 1.56 Is considerate and kind to most everyone 6.00 1.06 * Is sometimes rude to others 5.55 1.39 Likes to cooperate with everyone 5.91 .87 Conscientiousness

Does a thorough job 6.10 .81 * Can be somewhat careless 5.18 1.58 Is a reliable worker 6.53 .66 Tends to be disorganized* 5.53 1.52 * Tends to be lazy 6.18 1.10 Perseveres until the task is finished 5.94 .98 Does things efficiently 5.80 1.08 Makes plans and follows through with them 5.89 .94 * Is easily distracted 4.53 1.73 *Indicates reverse scored item.

Table 4.3: Descriptive Statistics for Recruiter (Head Coach) Personality – Continued

Factors and items M SD Neuroticism

Is depressed and blue 1.85 1.30 * Is relaxed, handles stress well 3.02 1.56 Can be tense 4.42 1.71 Worries a lot 3.96 1.85 * Is emotionally stable, not easily upset 2.66 1.37 Can be moody 3.40 1.74 * Remains calm in tense situations 2.47 1.08 Gets nervous easily 3.12 1.60 Openness

Is original, comes up with new ideas 5.50 1.03 Is curious about many different things 5.74 1.11 Is ingenious, a deep thinker 5.18 1.10 Has an active imagination 5.40 1.40 Is inventive 5.37 1.12 Values artistic, aesthetic experiences 4.99 1.42 * Prefers work that is routine 3.94 1.92 Likes to reflect, play with ideas 5.83 .94 * Has few artistic interests 4.21 1.68 Is sophisticated in art, music, or literature 3.59 1.73 *Indicates reverse scored item.

Table 4.4: Descriptive Statistics for Recruiter (Head Coach) Behavioral Integrity

Factor and items M SD Behavioral Integrity

There is a match between my words and actions. 6.40 .93 I deliver on my promises. 6.46 .64 I practice what I preach. 6.21 .76 I do what I say I will do. 6.44 .69 I conduct myself by the same values I talk about. 6.36 .69 I show the same priorities I describe. 6.29 .76 When I promise something, I can be certain that it will happen. 6.33 .79 If I say I am going to do something, I will. 6.49 .67

Table 4.5: Descriptive Statistics for Recruiter (Head Coach) Performance Reputation

Factor M SD Career Record .518 .13 NCAA Team Rank 155.11 89.47

Table 4.6: Descriptive Statistics for Recruiting Outcome (Total Quality)

Factor M SD Total Quality 2.54 1.31

Multiple Regression Statistics Two underlying research questions were proposed for this dissertation: (a) What leads to recruiting effectiveness in NCAA DI college soccer? and (b) What recruiter characteristics lead to recruiting effectiveness in NCAA DI college soccer? To address these questions, standardized multiple regression was employed to examine the primary significance of the recruiter characteristic IVs on the DV of Total Quality. This was done in steps, with participant response data (recruiter self-report data) being entered first (Block 1) and then secondary data about performance reputation predictors being entered second (Block 2). The IVs examined were

Political Skill, Personality (i.e., Extraversion, Agreeableness, Conscientiousness, Neuroticism,

Openness), Behavioral Integrity, and two performance reputation variables (i.e., Career Record and NCAA Rank (final 2010 ranking)). The DV was Total Quality (recruiting effectiveness).

One assumption for multiple regression pertains to sample size, and several different guidelines have been proposed. Stevens (2002) recommended 15 participants per predictor when conducted social science research whereas Tabachnick and Fidell (2001) provided the following formula: N > 50 +8m (where m = number of IVs). The present study included 9 predictors. The participants were 131 head women‘s soccer coaches, which is just under the number recommended by Stevens (i.e., 135). According to the formula provided by Tabchnick and Fidell, however, the minimum size requirement is 122; thus, the requirement was exceeded. Therefore, the assumption was determined to not be in violation. Prior to conducting the multiple regression analysis, the standardized predicted value with the standardized residuals on the scatterplot was observed. This was done to check the homogeneity of variance. In terms of the scatterplot, the cases were not centered about zero, but were instead grouped primarily in the upper right section of the graph. Thus, the homogeneity of variance assumption was violated. Also, normality of the data was assessed by inspecting the standardized residual on the histogram. This revealed a slight negative skew, although it was not deemed enough to violate the normality assumption. However, there were several possible outliers in the data.

In terms of data outliers, a Mahalanobis distance criterion was applied. The extracted critical chi-square (χ²) at =.001 for 9 df was 27.877. That is, if an item exceeded 27.877 it was deemed an outlier. As a result, three outliers among the cases were found. These three cases were examined and appeared to have a logically understandable and reasonable range of responses. Moreover, the exclusion of these cases did not significantly change the regression equation. Thus, no data was deleted from subsequent analysis. Next, a sensitivity analysis was conducted to check the multicollinearity among the nine IVs. In this analysis, Tolerance and VIF did not indicate multicollinearity. Tolerance values were all greater than .333 and VIF values were less than 3. Thus, both Tolerance and VIF values were found to be acceptable within their respective ranges. Correlations for the IVs and DV were also examined (Figure 4.7). Apart from the factors of Extraversion, Conscientiousness, and Openness, most of the correlations between the predictors and outcome variable were statistically significant. Most notably, the correlation between Political Skill and Total Quality was positive and high (r =.58). The correlation between NCAA Rank and Total Quality was negative and modestly correlated (r = -.40). Relatively modest correlations were also found between Agreeableness and Total Quality (r = .24), Neuroticism and Total Quality (r = -.30), and Career Record and Total Quality (r = .23). Furthermore, the correlation coefficients among the IVs ranged from low to high correlations (ranging from -.01 to -.58). However, this statement is somewhat misleading. That is, if the high (i.e., >.5) and anticipated correlation between Career Record and NCAA Rank (-.58) is excluded, the correlation coefficients among the remaining IVs are relatively low (< .2). Overall, this result also indicates an absence of multicollinearity, and further supports that examination of the data through standardized regression may be reliably undertaken. Cronbach‘s Alpha was used to assess the reliability of the scale items. As displayed in Table 4.8, Cronbach‘s Alpha values were .94 Political Skill, .86 Extraversion (Personality Dimension I), .81 Agreeableness (Personality Dimension II), .77 Conscientiousness (Personality Dimension III), .86 Neuroticism (Personality Dimension IV), .79 Openness (Personality Dimension V), and .92 Behavioral Integrity. The internal consistency of each of the factors was acceptable, having exceeded the recommended benchmark of .70 (Nunnally, 1978).

Table 4.7: Correlations of Recruiter Predictors and Recruiting Effectiveness

Total Political Extra- Agreeable Conscientious Neuroti- Open- Factor Integrity Record Rank Quality Skill version -ness -ness cism ness Political Skill .58** .94 α Extraversion .12 .42** .86 α Agreeableness .24** .38** .03 .81 α Conscientiousness .08 .13 .03 .29** .77 α Neuroticism -.30** -.23** -.09 -.45** -.26** .86 α Openness .14 .37** .25** .24** .04 -.25** .79 α Behavioral .18* .44** .06 .35** .32** -.12 .20* .92 α Integrity Career Record .23** .07 -.17 .08 -.05 -.01 .04 .13 1.000 NCAA Rank -.40** -.14 .05 -.17 .06 .09 .02 -.12 -.58** 1.000 Note: * p < .05. **p < .01. α = coefficient alpha

Table 4.8: Mean (M), Standard Deviation (SD), and Reliability (α) of Recruiter Characteristics

Scale M SD Cronbach α

Political Skill 5.67 .83 .94

Personality Extraversion 5.10 1.00 .86 Agreeableness 5.57 .82 .81 Conscientiousness 5.74 .71 .77 Neuroticism 3.11 1.10 .86 Openness 4.98 .80 .79

Behavioral Integrity 6.37 .61 .92

Table 4.9 shows the results of the standardized regression model. This analysis was employed to build a model for predicting Total Quality. In the first step, several predictors were blocked together: Political Skill, Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness, and Behavioral Integrity. Each of these predictors was a self-report recruiter characteristic. This model was statistically significant, F(7, 123)= 11.00, p < .001, with R2 at .39. The adjusted R2 (.35) indicated that more than a third of the variance in Total Quality was explained by the combination of these recruiter characteristics. Upon closer examination, however, only Political Skill demonstrated a significant unique effect, with Total Quality increasing with this particular recruiter characteristic. An estimation of the squared semipartial correlation (sr2 =.532) indicated that 28% of the unique variance in Total Quality was predicted by Political Skill (see Table 4.9 for a complete breakdown of each predictor‘s unique variance). Further, the size and direction of the relationships lends support to the notion that NCAA women‘s soccer head coaches (recruiters) who are more politically skilled are likely to recruit more highly ranked (higher quality) athletes for their teams than head coaches who have low levels of political skill. In the second block, two additional recruiting predictors were entered into the model: Career Record and NCAA Rank. Each of these two predictors represented coach performance reputation variables. These predictors were based on secondary data compiled by the researcher and described as performance reputation proxies because reputation, by definition, is a subjective

. evaluation of an entity by others (not objective criteria). Addition of these predictors significantly increased the fit of the model to the data, F(9, 121) = 12.15, p < .001. The adjusted R2 value increased from .35 to .44, which indicated a 9% change in explained variance. Thus, nearly half of the variance in Total Quality was accounted for by these nine predictors. As shown in Table 4.9, of the two coach performance reputation variables, only NCAA Rank had a statistically significant effect on the outcome of Total Quality. Next, to determine the amount of unique variance explained by the two significant predictors (i.e., Political Skill and NCAA Rank), semipartial correlation coefficients of the two predictors were calculated (.492 +(-.24)2 = .30). The sum of the two predictors (.30) is the amount of R2 attributable to these factors unique variablity while the remainder of the statistically insignificant predictors (.14) is the amount of R2 jointly contributed to shared variability. Furthermore, the size and direction of the Step 2 model relationships indicated there was a negative correlation (r = -.40) between NCAA Rank and Total Quality. This particular finding is explained in the following way. With rank, small (e.g., 1st or 2nd) is higher and therefore presumed to be more desired. Conversely, large (100th) is lower and therefore thought to be less desirable. Accordingly, what is indicated by this finding is that a smaller NCAA Rank (and thereby higher position in the NCAA ranking system) is associated with increased Total Quality. Overall, the results of the standardized regression analsysis indicate several key findings. First, one of the objectives of this study was to answer the following research question: What recruiter characteristics lead to recruiting effectiveness in NCAA Division I women‘s soccer? To this end, nine recruiter characteristics were evaluated and of the predictors, over half of the variance in Total Quality was predicted by Political Skill. Two, the coach performance reputation variable of NCAA Rank also contributed modestly to the prediction of Total Quality. The remaining recruiting predictors, however, added no further impact on Total Quality. Nevertheless, almost all of the proposed hypotheses were supported. That is, only three predictors (i.e., Extraversion, Conscientiousness, Openness) did not have a significent effect on the recruiting outcome of total quality. Therefore, hypotheses 2, 4, and 6 were not supported. All other hypotheses (i.e., H1, H3, H5, H7, H8, H9) were supported. An explanation of these findings will be discussed in the next chapter.

Table 4.9: Regression Analysis for Recruiter Predictors on Recruiting Effectiveness

Predictor B SE B β sr2 ∆Adjusted R2 Block 1 .35** Constant -0.01 1.42 Political Skill 1.11 0.15 .70** .28 Extroversion -0.20 0.10 -.16 .02 Agreeableness 0.02 0.14 .01 .01 Conscientiousness -0.01 0.14 -.01 .01 Neuroticism -0.14 0.10 -.11 .01 Openness -0.14 0.13 -.09 .01 Behavioral Integrity -0.25 0.18 -.12 .01 Block 2 .09** Constant 0.69 1.42 Political Skill 1.04 0.14 .66** .24 Extroversion -0.16 0.10 -.12 .01 Agreeableness -0.05 0.13 -.03 .01 Conscientiousness 0.08 0.14 .04 .01 Neuroticism -0.12 0.09 -.10 .01 Openness -0.09 0.12 -.06 .01 Behavioral Integrity -0.31 0.17 -.14 .01 Career Record 0.16 0.82 .02 .01 NCAA Rank -0.01 0.01 -.30** .06 Total R2 .44a N 131 Note: ** p <.001; Adjusted R2 = .35 for Step 1; ∆Adjusted R2 = .09 for Step 2 (p < .001). aUnique variability = .30; Shared variability = .14.

CHAPTER FIVE DISCUSSION

The main objective of this dissertation was two-fold. One objective was the development of a model of recruiting effectiveness in college sports, centered in particular on the role of recruiters. The second objective was to empirically test the relationship between recruiter characteristics and recruiting effectiveness. In this instance, recruiting effectiveness was evaluated as the total quality of the recruits signed by a recruiter (head women‘s soccer coach). To this end, nine hypotheses were tested. These hypotheses sought to examine the relationship between nine recruiter characteristics (i.e., political skill, extraversion, agreeableness, conscientiousness, neuroticism, openness, behavioral integrity, head coach career record, and head coach‘s final NCAA team rank) and the outcome variable of total quality. The hypotheses were largely support. Most notably, political skill was found to have a direct effect on total quality. NCAA team rank (a recruiter performance reputation characteristic) also had a direct effect on total quality. Additional direct effects were reported between the IVs of agreeableness, neuroticism, behavioral integrity, and career record and the DV of total quality. With these results in mind, this section is divided into several different areas. This section will begin with a discussion of the results. Second, the conceptual and theoretical implications of the results will be discussed. Explored next will be the practical applications of the results to athletic coaches (recruiters). In closing, the limitations of the study will be addressed; future research suggestions will also be provided. One point of discussion from Chapter 2, with particular reference to recruiters, was how the literature remains inconclusive when it comes to whether or not recruiter characteristics have a significant effect on recruiting outcomes. Presently, the general research consensus is that although recruiter characteristics may have an impact on job-organization attraction and a job applicant‘s willingness to pursue a job, such characteristics are unlikely to have a substantial effect on job choice decisions (Breaugh & Starke, 2000; Chapman et al., 2005; Rynes et al., 1991). The characteristic of personableness, for example, has demonstrated a strong relationship with the recruiting outcome of job pursuit intentions (Chapman et al.). Of the factors that have been examined though, minimal attention has been paid to social effectiveness constructs such as

. political skill. Hence, one noticeable finding from the present study was the relationship between political skill and the quality of the recruits the head women‘s soccer coaches were able to sign with their respective soccer teams (hypothesis 1). Recruiters with higher levels of political skill were found to have a higher total quality of recruits signed than recruiters with lower levels of political skill. This finding aligns with previous political skill theory and research evidence. Essentially, if recruiters are politically skilled, they are viewed as being perspicacious and shrewd socially, exceedingly competent networkers and coalition builders, persuasive and able to convince others of their positions, and believable and authentic in what they say and do. In the exact context of recruiting, Berkson et al. (2002) made a parallel statement of successful recruiters (though they did not explicitly state the construct of political skill) that aligns with the findings of this study. Notably, individuals (recruiters) who are socially aware, conscious of the changing nature of their recruiting environments, and persuasive in their interpersonal interactions with job candidates will be better able to elicit the desired response (i.e., job offer acceptance) from recruits. Even though influence tactics were not explicitly studied in this dissertation, past research evidence indicates politically skilled individuals are more effective in their influence attempts (Ferris, Treadway et al., 2007; Harris et al., 2007; Treadway et al., 2007). It is therefore likely in the present study that those recruiters who were more politically skilled were better able to have their influence tactics positively perceived by both recruits and influential agents. This in turn likely led to their ability to sign higher quality recruits. Furthermore, job applicants have been noted to have more positive impressions of a recruiter if the individual was genuine (Connerley & Rynes, 1997). Once again, this result, though not directly assessed in the present study, appears to be supported because politically skilled individuals are able to effectively engage in socially influence behaviors while at the same time being perceived as genuine and sincere. Therefore, even though it cannot be stated conclusive, it can be inferred that not all recruiters can give the impression to recruits they are truly concerned with their well-being. Moreover, not all recruiters can successful develop and then effectively execute influence attempts that lead to positive recruiting outcomes. In addition to political skill, a relationship between two of the Big Five personality factors and recruit total quality was also reported. Namely, agreeableness (hypothesis 3) was found to a have a positive and direct effect on recruiting class total quality (recruiting

. effectiveness). The factor of neuroticism was found to have a direct and negative effect on total quality (hypothesis 5). A recruiter who is agreeable ―contrasts a prosocial and communal orientation toward others with antagonism‖ (John et al., 2008, p. 120) whereas a neurotic recruiter ―contrasts emotional stability and even-temperedness with negative emotionality‖ (John et al., p. 120). Therefore, what is seemingly implicit from this result is recruiters who are more agreeable and less neurotic may be able to secure higher quality recruits than recruiters who are unpleasant and who lack modesty and even-temperedness. This may especially be the case when these two personality factors are combined with political skill. Hogan and Shelton (1998) noted that what is largely absent from the scholarly discussion of personality and organizational performance outcomes is the inclusion of social skill. What they meant by this was there needs to be, when discussing personality and performance outcomes, an explanation of some sort of mechanism that accounts for how a particular personality factor is portrayed to others. Thus, individuals who are politically skilled and highly agreeable may be better able to showcase their personality to others than individuals who are agreeable but lack political skill. This is because politically skilled individuals are more capable of assessing and understanding their social environments, as well as adapting how they maneuver through this environment to achieve personal and/or organizational objectives. Hence, it may be that even if a recruiter is neurotic, if they are also politically skilled, he/she may be able temper the negative effects of this personality factor to still achieve recruiting effectiveness. A positive and direct effect was also found between the factor of behavioral integrity and total quality (hypothesis 7). Even though the correlation for this relationship was low (< .2), the result still lends support to the notion that recruiter word-deed alignment is an important part of the process that leads to recruiting effectiveness. What this means, or what can be inferred, is that recruiters need to be calculated in what they say to recruits and influential agents. Recruiting high school student-athletes is not a one-shot deal. Instead, it is a process that unfolds over a series of years as the recruiter (head coach) watches the student-athlete develop throughout high school. Consequently, if recruiters are perceived as lacking behavioral integrity, this could jeopardize their ability to attract high quality recruits in both the present and future. Even if a recruit does not recognize the lack of recruiter behavioral integrity until it is too late (i.e., signed the letter of intent and will be attending the recruiter‘s school), this could still negatively impact the recruiter‘s ability to sign high quality recruits in the future. As it was

. previously noted, influential agents include parents, high school coaches, and other recruits/peers (Bissinger, 1990; Croft, 2008; Feldman, 2007; Hu & Hossler, 2000; Lewis, 2007; Newberg, 2010; Widdison, 1982). With respect to this latter influential agent (i.e., other recruits/peers), if a recruit (after signing) perceives a recruiter as lacking behavioral integrity (e.g., recruiter said I would have an opportunity to play my freshman year, but I didn‘t even get a chance), then this individual might convey this information to other recruits with whom he/she has a relationship. In time, a social network among recruits and influential agents could develop, which could then lead to the recruiter having an untrustworthy and unreliable reputation among up-and-coming student-athletes (Wong & Boh, 2010). Next, both performance reputation characteristics demonstrated a positive and direct effect with total quality (hypotheses 8 and 9). Of the two, the relationship between the recruiter performance reputation characteristic of NCAA team rank and recruiting effectiveness (hypothesis 9) had the stronger correlation with total quality. Head coaches (and coaching staff) are influential factors to student athletes (Letwasky et al., 2003; Pauline, 2010; Pauline et al., 2007), as is athletic team performance (Doyle & Gaeth, 1990; Pauline et al.). Therefore, even though team rank has not always been linked to recruiting outcomes (e.g., DuMond et al., 2008), this result is still interesting because of the role performance reputation characteristics may play in recruits‘ decisions. In addition to recruiters‘ political skill levels, performance reputation characteristics may send a signal to the sport marketplace. This reputation signal is information about the head coach and the athletic team and it may represent one of the most salient information links recruiters have to recruits (Berkson et al., 2002). What is more, the recruiter does not even need to be present for reputation characteristics to have an impact. Whereas the characteristic of political skill is strongest after being personally experienced, the impact of performance reputation characteristics can have a significant impact on recruits in the absence of the recruiter. In other words, the signal sent by this reputation characteristic is not limited by geophysical boundaries. For instance, a recruit from the state of California may be recruited by a head coach in the state of Florida. This recruit from California may observe a soccer team‘s final NCAA rank. This rank, a performance reputation characteristic of the coach, sends a signal about the coach‘s performance ability to the recruit. Hence, without meeting the coach, this reputation characteristic of the coach is having an impact on recruiting effectiveness.

Furthermore, when combined with political skill (i.e., a politically skilled recruiter who also has a strong performance reputation), recruiters may be especially successful in attracting a high quality recruiting class. This is because politically skilled recruiters will be better able to manage the presentation of salient performance reputation information. Both career record and rank impacted total recruit quality, and so without a politically skilled recruiter it may still influence student-athlete decisions. However, when combined with a politically skilled recruiter, these two performance reputation characteristics may be significantly more impactful on recruit‘s decisions to attend a particular school. As such, all of these recruiter characteristics are likely to be important recruiter-based predictors of recruiting effectiveness and should therefore be explored more fully in the future. Finally, in addition to what was reported as significant, it also interesting to explore what was insignificant (in terms of unique variance explained in the research model). In particular, even though over one-third of the research model was explained by recruiter political skill and performance reputation characteristics, this still leaves a large amount of variance unexplained. This means there are a multitude of factors not addressed in the current research model that need to be considered. Such factors are likely to include additional recruiter characteristics, academic/university characteristics, and external factors outside the control of the recruiter (e.g., school location). Several of these factors are discussed next. In terms of recruiter characteristics, given the impact of recruiter political skill, it would be useful to explore additional social effectiveness characteristics. Ego-resiliency, for example, is an interesting construct to consider in the future. This construct has been defined as ―the dynamic capacity of an individual to modify a characteristic level of ego-control, in either direction, as a function of the demand characteristics of the environmental context, so as to enhance system equilibrium‖ (Block & Kremen, 1996, p. 351). Those high in ego-resiliency are prone to positive affective outlooks and less likely to view changing circumstances with anxiety. Thus, along with political skill, ego-resiliency could be a beneficial social effectiveness characteristic for recruiters to possess. Further, because recruits are often times recruited by more than just the head coach, it would also be interesting to examine the combination of head coach and assistant coach characteristics. Alone, each coach may lack particular characteristics that could have a significant impact on recruits and influential agents. Together, the combination of head coach

. and assistant coach characteristics may fill those gaps and potentially create a unique ―composite recruiter‖ for the respective athletic team. Indeed, from a resource-based view (RBV), this could even create a recruiting competitive advantage not easily replicated by other athletic institutions. In effect, this competitive advantage could come from the approach to recruiting student-athletes that had developed over time among the coaching staff for a particular sport team. Additionally, both academic major availability and academic reputation have been repeatedly identified as influential factors, if not the most influential factors, when it comes time for student-athletes to select a school (e.g., Judson et al., 2005; Kankey & Quarterman, 2007; Letawsky et al., 2003; Mathes & Gurney, 1985; Pauline, 2010; Pauline et al., 2007; Reynaud, 1998; Ulferts, 1992). Thus, these factors are also likely to have a significant impact on recruit decisions about which college or university to attend. Finally, with regard to external characteristics, a key factor may be school location. DuMond et al. (2008) identified this as the most important predictor of student-athletes (NCAA DI football players). The degree to which this factor is important may vary outside of DI football, but it is still likely to be a key factor of importance to recruits regardless of competitive level or sport-type. Conceptual and Theoretical Implications One key implication from the findings is the usefulness of political skill and social influence theory to recruiting research in a sport context. The combination of these approaches appears to account for the development and delivery of influence strategies and tactics as well as the style of such efforts. When previously discussing social influence in interpersonal relationships, Jones (1990) noted the absence of a style construct that could explain the method or mechanism through which influence attempts would be made more successful. Hogan and Shelton (1998) made a similar point when discussing personality and performance outcomes. Hence, political skill may undoubtedly represent one missing piece to social influence theory. Further, in alignment with signaling theory (Spence, 1974), the present results appear to suggest that recruiter performance reputation characteristics may convey salient performance information to recruits. In cases where this information is effectively signaled to recruits (such as by a politically skilled recruiter), it may serve to distinguish the recruiter and the recruiter‘s institution in the eyes of student-athletes (recruits) and influential agents. Thus, the current findings also appear to advance the reputation/information framework developed by Berkson et al. (2002). In short, reputation characteristics are information links to recruits and can, when

. properly leveraged, positively impact recruit‘s perceptions of recruiters and their institutions. This can then have a significant impact on recruiting outcomes, with actual job choice decisions being the most desired outcome. Managerial Implications One of the main findings from this study was the direct effect of political skill on recruiting effectiveness. Politically skilled individuals combine social astuteness with the ability to make instant modifications to their behavior across shifting circumstances and environments (Ferris, Treadway et al., 2005). They do so in a genuine and sincere manner that inspires confidence, support, and conviction. This should therefore enable politically skilled recruiters to obtain greater access to key information, more quickly and easily develop wider and higher- quality social contacts, and have more flexible and productive social relationships (Ferris, Davidson et al., 2005; Treadway et al., 2005). Moreover, though it was not explicitly detailed in this study, individuals high in political skill are thought to be better able to select and successfully execute influence strategies and tactics (Ferris, Treadway et al., 2007; Harris et al., 2007). The practical value of this information to athletic coaches rests with the fact that political skill is trainable (Ferris, Davidson et al., 2005). That is, though certain individuals may be inherently more politically skilled than others, each dimension of political skill can still be improved upon with practice. Social astuteness can be improved with feedback. In the case of an assistant coach, for example, a head coach may be able to critique how the assistant coach interacts with a particular recruit and then provide this individual with detailed feedback after the fact. Interpersonal influence can be learned through mentoring, leadership training (e.g., developing improved communication skills), and behavioral modeling. With respect to this latter training tool, an assistant coach may watch a senior coach, model a particular skill, and then practice what was learned until it can be executed with ease. Networking ability can also be improved with training, and a great opportunity to connect with more coaches is at national conferences, especially conferences that cater to high school and club coaches (as these coaches oversee high school student-athletes). Lastly, apparent sincerity can be improved though communication training. A coach can learn how to more effectively convey empathy when speaking and better control their non-verbal body cues.

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Thus, in terms of precise practical applications, head and assistant athletic coaches could learn to become more politically skilled through diligent practice. This may be especially relevant to young and aspiring assistant coaches. If possible, these individuals should seek out a mentoring relationship with a more experienced and successful head coach. This head coach mentor (assuming he/she possesses a high level of political skill) could then advise and provide frequent behavioral feedback to the assistant coach. In doing so, the head coach may be able to help the assistant coach become more aware of the realm of college sports and how they should interact with high school coaches, other college coaches, recruits, and parents/guardians. Although not guaranteed, this could result in the assistant coach becoming more politically skilled, which may then contribute to the assistant coach having improved recruiting effectiveness. Limitations and Future Research Directions One limitation of the current study is the generalizeability of the findings. The sport consumers participating in this study were representative of one sport (women‘s soccer) and one competitive level (i.e., NCAA DI). Also, because there was violation of the regression assumptions (i.e., homeogeneity of variance), the findings may not be generalized beyond the sample. Nevertheless, the construct of political skill, for example, is thought to be a generalizeable concept that, if possessed, is applicable to multitude of contexts and situations (Ferris, Davidson et al., 2005). Therefore, the applications derived from the underlying nature of recruiter – recruit interactions and how recruiter political skill leads to recruiting effectiveness is likely to be both applicable and transferrable to sport and not-sport labor markets and organizations. A second limitation of the current study pertains to several of the recruiter characteristic constructs. Of the self-reported recruiter characteristics, political skill, agreeableness, neuroticism, and behavioral integrity had a significant direct effect on the outcome of total quality of signed recruits. Extraversion, conscientiousness, and openness did not have an impact. Nevertheless, it is quite likely these factors do have an impact on recruiting outcomes; however, this relationship may not be best explored through recruiter self-report data. Consider the factor of behavioral integrity, which, even though it was significant, still had a low correlation with total quality. Behavioral integrity is not an objective factor. Quite the contrary, behavioral integrity is subjective and can be influenced and altered by the target

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. individual, the perceivers, the environment, and also cognitive processes such as bias. Indeed, the true impact of behavioral integrity is not so much what the target individual does, but how the word-deed (mis)alignment is perceived by others (Simons, 2002). Thus, the reported relationship between behavioral integrity and recruiting effectiveness is not too surprising. That is to say, it is highly unlikely recruiters would indicate low levels of behavioral integrity, although there was enough variation to get a significant effect. Therefore, in the future, recruiter behavioral integrity and how it impacts student-athlete selection decisions should be assessed from the perspective of the student-athletes. As a point of comparison with student-athletes‘ perceptions, recruiters‘ behavioral integrity perceptions would still be worth assessing. Yet, as a standalone, self-report factor, the benefits to recruiting research may be quite limited. Along the same lines, self-report models of personality may also be problematic to researchers who seek to study recruiting through recruiter self-report questionnaires (regardless of whether or not a significant effect is found). Although recall is a useful means of data collection, it is not a perfect representation of the past, especially as it pertains to how we perceive ourselves (Neisser & Winograd, 1988). In short (Hogan & Shelton, 1998, p. 140): Our view is that what people do while responding to items on a questionnaire is the same as what they do during social interaction more generally—they tell others how they would like to be regarded in order to get along and get ahead. When they endorse items, they mean it—self-presentations‘ are usually sincere. Item endorsements are self- presentations, not self-reports, and consistencies in item endorsements represent consistencies in self-presentational behavior, both of which are guided by the same underlying identity.

Accordingly, what may instead be more beneficial for researchers is to explore the combination of recruiter personality and social effectiveness as viewed by recruits (as opposed to recruiters). Instead of viewing personality as purely a trait, it may also be beneficial to explore how personality is a both a reflection of motivation, identity, and reputation, and how a social effectiveness construct (e.g., social skill, political skill) may improve the personality – performance outcome relationship (Hogan & Shelton, 1998). Motivation pertains to whether or not there is a strong desire to establish positive interpersonal relationship and get ahead. Identity is ―personality from the inside—how we think about ourselves and how we want others to think about us‖ (Hogan & Shelton, p. 142). Conversely, reputation is ―personality from the outside— how others think about and evaluate our efforts to get along and get ahead‖ (Hogan & Shelton, p. 142). Finally, the inclusion of social effectiveness provides a bridge between personality and

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. performance outcomes. More precisely, ―social skill is what translates identity into successful reputation, social skill transforms motivation into accomplishment‖ (Hogan & Shelton, p. 143). Hence, an interesting extension of the current study would be to explore the relationship between recruits‘ perceptions of recruiter personality and social skill and various recruiting outcomes (e.g., job-organization attraction, acceptance intentions, school choice). An additional limitation of the current study is the outcome variable of total quality of recruiting class signed by a particular recruiter (head women‘s soccer coach). The findings from this study demonstrated a relationship between two recruiting predictors and the quality of recruits a head coach was able to sign. To incorporate an objective assessment of recruit quality into the study, the soccer recruiting and information site of www.topdrawersoccer.com was used. This site includes recruit rankings on a 1 – 5 star scale. Inherent limitations to this approach, however, include the following observations. One, though this soccer site is similar to football and basketball recruiting sites (i.e., www.rivals.com), the rankings are still based on individual assessments. Thus, the soccer recruit rankings are not beyond reproach and could be viewed differently by different coaches depending on how they evaluate soccer skill. Two, the outcome of total quality does not take into account the needs of each individual recruiter. In concept, a greater number of highly rated recruits are better than recruits with low ratings. Practically though, it comes down to recruiter preference and what a particular head coach needs for their team the next season. What is meant by preference is illustrated in the following example. Assume there is a recruit (Student-athlete X) who is the top soccer recruit in the country. Incidentally, this individual has a very poor academic track record. When recruiting, Head Coach A places a higher value on academics and recruit attitude than pure athletic skill. In contrast, Head Coach B places the highest value on soccer skill, with the lowest priority being academic ability. The recruit‘s first choice is Head Coach A; the second choice is Head Coach B. However, because Head Coach A prefers academics to pure athletics, this coach does not offer Student-athlete X a scholarship. As a result, this recruit signs with Head Coach B. Thus, even if Head Coach A is a spectacular recruiter, this individual may pass on a top recruit if the student- athlete does not meet the desired recruiting criteria. In addition to preference, there is also the issue of a head coach‘s needs for the following season. That is, even if a coach could easily sign an entire class of top-rated student-athletes, this individual may not do so if these individuals do not fill specific gaps in the coach‘s athletic team.

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For instance, a head coach may recruit a relatively unknown student-athlete (instead of pursuing highly rated players) if this individual is perceived as being able to fill a specific role for the team. Objective ranking systems such as topdrawersoccer and rivals cannot capture this type of information. In effect, a talented recruiter may be extremely satisfied with the quality of his/her recruiting class even if the total quality score of the recruiting class is low (based on objective rankings). Ultimately, this is a challenge not easily addressed in future studies. Even so, it is a point of consideration that should be kept in mind when assessing recruiting class quality and a recruiter‘s recruiting effectiveness. Limitations aside, what follows next in this section is a presentation of several research suggestions. First, there is limited evidence that recruiter characteristics have a direct effect on recruiting outcomes, especially the key outcome of job choice (Chapman et al., 2005). The results of this study are a modest exception. The most obvious explanation for results such as these is the relationship between recruiter characteristics and recruiting outcomes is more complex than a direct path. Indeed, when discussing this very point, Chapman and colleagues reported that the relationship between recruiter characteristics and recruiting outcomes is most likely explained by the following interactions. Recruiter characteristics impact recruit‘s levels of job-organization attraction (JOA). From there, the effect of JOA on job choice may be partially mediated by acceptance intentions. Therefore, one suggestion for future research centered on recruiter characteristics is to examine an attitudes mediated model such as the one reported by Chapman et al. (2005). Although it would not been an easily executed study, one approach to this type of model would be exploring the time sequencing of recruit‘s reactions to both recruiter characteristics and recruiters‘ influence strategies and tactics. This would be particularly beneficial to the study of recruiting in college sports because there is limited evidence available to inform scholars about which recruiter characteristics impact job choice. Moreover, no evidence has been provided to explain the mechanisms through which recruiter characteristics impact JOA. There is also no information present as to how long it takes for acceptance intentions to lead to job choice. Accordingly, sport researchers interested in recruiting would be well served to explore how to conduct episodic research in intercollegiate athletics. Second, a linked but nevertheless distinct area of future research would be comparing recruiters at different levels of NCAA competition. In effect, more precisely identifying the

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. nuances of the recruiting process that vary by competitive level and thereafter examining the causes for these variations. For instance, in the development of a multidimensional model of coaching satisfaction and dissatisfaction, Dixon and Warner (2010) interviewed fifteen DIII coaches from the sports of men‘s and women‘s soccer and basketball. When the interviews shifted toward recruiting, it was evident this was not viewed as an enjoyable aspect of the coaches‘ jobs (Dixon & Warner, p. 155): from a job preference perspective, recruiting was discussed as passionately as the ability to impact athletes; however, in the opposite direction. That is, as passionately as they spoke about enjoying the relationships with current recruits, they spoke with equal distaste about recruiting.

Such views of recruiting stand in seemingly obvious contrast to DI coaches (especially football coaches) who, at least anecdotally, appear to embrace the process (e.g., Feldman, 2007). One case in point is Joe Paterno, Penn State‘s Head Football Coach. Despite being 84 years old, in a recent interview he adamantly stated that ―there‘s no guarantee on anything, but I intend to be here, and I intend to work hard at recruiting‖ (Associated Press, 2011). It is therefore highly likely that recruiting and the roles of recruiters vary by both sport- type and competitive level. Thus, even though political skill is a generalizeable concept, it would be still be worthwhile to explore how it is executed by coaches for a variety of sports at each competitive level. In other words, interpersonal influence has a high probability of being an important factor for coaches at the DI – DIII levels. How interpersonal is enacted, on the other hand, may vary by competitive level, which opens the door for a multitude of research opportunities, especially as it pertains to influence tactics and strategies. Accordingly, a third research suggestion is to explore recruiter characteristics as well as recruiter influence tactics and strategies. An excellent theoretical starting point to guide such a study is the reputation/information framework (Berkson et al., 2002). Their framework, which was grounded in an organization-based recruitment perspective, explained ―how organizations may increase their attractiveness through promotion of reputation in the interview context‖ (Berkson et al., p. 360). Information is central to the framework because it was argued to be at the core of job applicant attraction to an organization. In addition to job attributes, organizational reputation was specified as a key source of information. Social influence tactics (such as persuasive speech) were then proposed as necessary mechanisms for effective information transmission. Indeed, carefully crafted influence behaviors were proposed to impact recruits by

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. heightening their perceptions of reputation and thereby making this information more salient. Taken as a whole, the Berkson et al. (2002) model highlights the important role of recruiters, their characteristics, and their influence practices on obtaining top talent in a tight labor market. This is exceedingly relevant to athletic recruiters as recruiting in college sports is a year-long process. Thus, exploring this model with the inclusion of specific recruiter characteristics (e.g., political skill) and influence tactics (e.g., rational persuasion, inspirational appeal) would be an interesting and practically useful recruiting research advancement for sport- based recruiting studies. Summary Despite being exceedingly important to the success of college sport teams, minimal attention has been paid to the antecedents of recruiting effectiveness in intercollegiate athletics. In particular, little to no attention has been paid the roles of recruiters and how their characteristics and behaviors lead to positive recruiting outcomes. This study therefore sought to achieve a two-fold objective. First, develop a conceptual framework that explores one possible explanation as to how recruiters achieve recruiting effectiveness. Two, empirically test select aspects of the proposed conceptual model. Accordingly, the direct effect of nine recruiter characteristics (i.e., political skill, extraversion, agreeableness, conscientiousness, neuroticism, openness, behavioral integrity, career record, and NCAA rank) on the outcome of total recruiting class quality was examined. Of these characteristics, political skill, agreeableness, neuroticism, behavioral integrity, head coach career record (performance reputation), and the final NCAA rank of the head coach‘s team (performance reputation) were found to have a significant direct effect on recruiting effectiveness. Thus, even though much still remains unknown about the impact of recruiter characteristics on recruiting outcomes, this study nevertheless provides preliminary research evidence that recruiter characteristics (especially political skill) may indeed be valuable characteristics for athletic coaches to possess while recruiting student-athletes.

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APPENDIX A CONSENT TO PARTICIPATE

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Office of the Vice President For Research Human Subjects Committee Tallahassee, Florida 32306-2742 (850) 644-8673 · FAX (850) 644-4392

APPROVAL MEMORANDUM

Date: 5/10/2011

To: Marshall Magnusen

From: Thomas L. Jacobson, Chair

Re: Use of Human Subjects in Research Recruiting Predictors Influences on Recruiting Effectiveness in College Sports: The Case of NCAA Division I Soccer

The application that you submitted to this office in regard to the use of human subjects in the proposal referenced above have been reviewed by the Secretary, the Chair, and one member of the Human Subjects Committee. Your project is determined to be Expedited per per 45 CFR § 46.110(7) and has been approved by an expedited review process.

The Human Subjects Committee has not evaluated your proposal for scientific merit, except to weigh the risk to the human participants and the aspects of the proposal related to potential risk and benefit. This approval does not replace any departmental or other approvals, which may be required.

If you submitted a proposed consent form with your application, the approved stamped consent form is attached to this approval notice. Only the stamped version of the consent form may be used in recruiting research subjects.

If the project has not been completed by 5/4/2012 you must request a renewal of approval for continuation of the project. As a courtesy, a renewal notice will be sent to you prior to your expiration date; however, it is your responsibility as the Principal Investigator to timely request renewal of your approval from the Committee.

You are advised that any change in protocol for this project must be reviewed and approved by the Committee prior to implementation of the proposed change in the protocol. A protocol change/amendment form is required to be submitted for approval by the Committee. In addition, federal regulations require that the Principal Investigator promptly report, in writing any unanticipated problems or adverse events involving risks to research subjects or others.

By copy of this memorandum, the Chair of your department and/or your major professor is reminded that he/she is responsible for being informed concerning research projects involving human subjects in the department, and should review protocols as often as needed to insure that the project is being conducted in compliance with our institution and with DHHS regulations.

This institution has an Assurance on file with the Office for Human Research Protection. The Assurance Number is FWA00000168/IRB number IRB00000446.

Cc: Michael Mondello, Advisor HSC No. 2011.6263

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APPENDIX B LETTER OF ASSISTANCE

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APPENDIX C HEAD COACH (RECRUITER) QUESTIONNAIRE

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Recruiter Political Skill

Instructions: Using the following 7-point scale, circle the number that best describes how much you agree with each statement about yourself.

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 1) I spend a lot of time and effort networking with 1 2 3 4 5 6 7 others. 2) I am able to make most people feel comfortable and at 1 2 3 4 5 6 7 ease around me. 3) I am able to communicate easily and 1 2 3 4 5 6 7 effectively with others. 4) It is easy for me to develop good rapport with most 1 2 3 4 5 6 7 people.

5) I understand people very well. 1 2 3 4 5 6 7

6) I am good at building relationships with 1 2 3 4 5 6 7 influential people. 7) I am particularly good at sensing the motivations 1 2 3 4 5 6 7 and hidden agendas of others. 8) When communicating with others, I try 1 2 3 4 5 6 7 to be genuine in what I say and do. 9) I have developed a large network of colleagues and associates whom I can call on for 1 2 3 4 5 6 7 support when I really need to get things done.

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Recruiter Political Skill (Continued From Previous Page)

Instructions: Using the following 7-point scale, circle the number that best describes how much you agree with each statement about yourself.

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 10) I know a lot of important people and I am well 1 2 3 4 5 6 7 connected. 11) I spend a lot of time developing connections with 1 2 3 4 5 6 7 others. 12) I am good at getting people to like me. 1 2 3 4 5 6 7

13) I believe it is important that people believe I 1 2 3 4 5 6 7 am sincere in what I say and do. 14) I try to show a genuine interest in other people. 1 2 3 4 5 6 7

15) I am good at using my connections and networks to 1 2 3 4 5 6 7 makes things happen at work. 16) I have good intuition or ―savvy‖ about 1 2 3 4 5 6 7 how to present myself to others. 17) I always seem to instinctively know the right things to 1 2 3 4 5 6 7 say or do to influence others. 18) I pay close attention to peoples‘ facial 1 2 3 4 5 6 7 expressions.

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Recruiter Personality

Instructions: Here are a number of characteristics that may or may not apply to you. Please write a number next to each statement to indicate the extent to which you agree or disagree with that statement.

I see myself as someone who…

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 1) Is talkative 1 2 3 4 5 6 7 2) Tends to find fault with others 1 2 3 4 5 6 7 3) Does a thorough job 1 2 3 4 5 6 7 4) Is depressed, blue 1 2 3 4 5 6 7 5) Is original, comes up with new ideas 1 2 3 4 5 6 7 6) Is reserved 1 2 3 4 5 6 7 7) Is helpful and unselfish w/ others 1 2 3 4 5 6 7 8) Can be somewhat careless 1 2 3 4 5 6 7 9) Is relaxed, handles stress well 1 2 3 4 5 6 7 10) Is curious about many different 1 2 3 4 5 6 7 things 11) Is full of energy 1 2 3 4 5 6 7 12) Starts quarrels with others 1 2 3 4 5 6 7 13) Is a reliable worker 1 2 3 4 5 6 7 14) Can be tense 1 2 3 4 5 6 7 15) Is ingenious, a deep thinker 1 2 3 4 5 6 7 16) Generates a lot of enthusiasm 1 2 3 4 5 6 7 17) Has a forgiving nature 1 2 3 4 5 6 7 18) Tends to be disorganized 1 2 3 4 5 6 7 19) Worries a lot 1 2 3 4 5 6 7

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I see myself as someone who…

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 20) Has an active imagination 1 2 3 4 5 6 7 21) Tends to be quiet 1 2 3 4 5 6 7 22) Is generally trusting 1 2 3 4 5 6 7 23) Tends to be lazy 1 2 3 4 5 6 7 24) Is emotionally stable, not easily 1 2 3 4 5 6 7 upset 25) Is inventive 1 2 3 4 5 6 7 26) Has an assertive personality 1 2 3 4 5 6 7 27) Can be cold and aloof 1 2 3 4 5 6 7 28) Perseveres until the task is finished 1 2 3 4 5 6 7 29) Can be moody 1 2 3 4 5 6 7 30) Values artistic, aesthetic 1 2 3 4 5 6 7 experiences 31) Is sometimes shy, inhibited 1 2 3 4 5 6 7 32) Is considerate and kind to almost 1 2 3 4 5 6 7 everyone 33) Does things efficiently 1 2 3 4 5 6 7 34) Remains calm in tense situations 1 2 3 4 5 6 7 35) Prefers work that is routine 1 2 3 4 5 6 7 36) Is outgoing, sociable 1 2 3 4 5 6 7 37) Is sometimes rude to others 1 2 3 4 5 6 7 38) Makes plans and follows through 1 2 3 4 5 6 7 with them 39) Gets nervous easily 1 2 3 4 5 6 7

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I see myself as someone who…

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 40) Likes to reflect, play with ideas 1 2 3 4 5 6 7 41) Has few artistic interests 1 2 3 4 5 6 7 42) Likes to cooperate with others 1 2 3 4 5 6 7 43) Is easily distracted 1 2 3 4 5 6 7 44) Is sophisticated in art, music, or 1 2 3 4 5 6 7 literature

Recruiter Integrity

Instructions: Using the following 7-point scale, circle the number that best describes how much you agree with each statement about yourself. Please, do not over think—respond instinctually.

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 1) There is a match between my words 1 2 3 4 5 6 7 and actions. 2) I deliver on my promises. 1 2 3 4 5 6 7 3) I practice what I preach. 1 2 3 4 5 6 7 4) I do what I say I will do. 1 2 3 4 5 6 7 5) I conduct myself by the same values 1 2 3 4 5 6 7 I talk about. 6) I show the same priorities that I 1 2 3 4 5 6 7 describe. 7) When I promise something, I can be certain that it will 1 2 3 4 5 6 7 happen. 8) If I say I am going to do something, I 1 2 3 4 5 6 7 will.

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Recruiter Affectivity

Instructions: The following section consists of a number of words that describe different feelings and emotions. In the space provided next to each word, indicate the degree to which you generally feel this way – that is, how you feel on the average. Please use the scale below.

Not At All / Never Rarely Occasionally Sometimes Frequently Usually Always

1 2 3 4 5 6 7

Please indicate to what extent you generally feel this way.

______interested ______irritable

______distressed ______alert

______excited ______ashamed

______upset ______inspired

______strong ______nervous

______guilty ______determined

______scared ______attentive

______hostile ______jittery

______enthusiastic ______active

______proud ______afraid

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Recruiting Outcomes – Perceived Effectiveness

Instructions: Using the following 7-point scale, circle the number that best describes how much you agree with each statement about yourself and your recruiting effectiveness this past year.

Not At All Slightly Somewhat Neutral Moderately Mostly Entirely 1) Overall, to what extent do you feel you performed your recruiting 1 2 3 4 5 6 7 job the way you would like it to be performed? 2) To what extent did you meet your expectations in your recruiter roles and 1 2 3 4 5 6 7 responsibilities? 3) To what extent would you change the manner in which you performed 1 2 3 4 5 6 7 your job recruiting this past year?

Recruiting Outcomes – Recruits Signed

Instructions: Per conversations with several DI-A soccer coaches, a comparable site to Rivals.com was noted as TopDrawerSoccer.com. This site includes a rating system ranging from 1-Star (Fair) to 5-Star (Best of the Best). Please tell us how many recruits YOU personally had a significant role in getting to commit (sign) to playing soccer for your team next season? Please provide a numeric response next to each appropriate category.

# of Recruits Receiving a “Not Rated” rating: ______

# of Recruits Receiving a 1-Star (Fair) rating: ______

# of Recruits Receiving a 2-Star (Good) rating: ______

# of Recruits Receiving a 3-Star (Strong) rating: ______

# of Recruits Receiving a 4-Star (Very Strong) rating: ______

# of Recruits Receiving a 5-Star (Best of the Best) rating: ______

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Recruiting Outcomes – Satisfaction

Instructions: Using the following 7-point scale, circle the number that best describes how much you agree with each statement about your recruiting satisfaction levels this past recruiting cycle.

Strongly Moderately Slightly Slightly Moderately Strongly Neutral Disagree Disagree Disagree Agree Agree Agree 1) I am satisfied with the success I had recruiting student- 1 2 3 4 5 6 7 athletes this past year. 2) I am satisfied with the progress I made toward meeting my 1 2 3 4 5 6 7 overall recruiting goals this past year. 3) I am satisfied with the progress I made toward meeting my goals 1 2 3 4 5 6 7 for recruit quality this past year. 4) I am satisfied with the progress I made toward meeting my recruiting goals 1 2 3 4 5 6 7 for career advancement this past year. 5) I am satisfied with the progress I made toward meeting my goals for developing 1 2 3 4 5 6 7 new recruiting skills this past year. 6) I am satisfied with the overall quality of the student- athletes I was able 1 2 3 4 5 6 7 to recruit this past year.

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Recruiter Demographics

1. Age:______

2. Gender (circle one): (a) Male (b) Female

3. Ethnicity (circle one):

(a) African American (b) Asian American (c) Caucasian

(d) Hispanic American (e) Native American Indian (f) Multiracial

Not Listed: ______

Coach, I completely recognize that surveys can be an inconvenience. I therefore

sincerely appreciate your time and energy in helping me to complete my dissertation!

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Ahearn, K.K., Ferris, G.R., Hochwarter, W.A., Douglas, C., & Ammeter, A.P. (2004). Leader political skill and team performance. Journal of Management, 30, 309-327.

Aiken, L., & West, S. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage Publications.

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl. & J. Beckmann (Eds.), Springer series in social psychology (pp. 11–39). Berlin: Springer.

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, CA: Prentice-Hall, Inc.

Alderfer, C. P., & McCord, C. G. (1970). Personal and situational factors in the recruitment interview. Journal of Applied Psychology, 54, 377-385.

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BIOGRAPHICAL SKETCH

In the fall of 2003, Marshall Magnusen completed his Bachelor of Science in Kinesiology and English Literature from Wheaton College (IL). He then went on to complete a Masters of Science in Kinesiology from Texas Christian University (TCU) in the spring of 2006. He enrolled in the Sport Management doctoral program at the Florida State University (FSU) in the fall of 2007. In both 2009 and 2010, he was awarded the Distinguished Doctoral Student Researcher of the Year award for the Sport Management program. The primary goal of his research is to explore the nature of work relationships and apply the social influence and effectiveness processes literatures to sport management, with particular attention being paid to influence strategies and tactics, political skill, recruiting, and reputation.

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