Authors: Peter S. Finley and Jeffrey J. Fountain
H. Wayne Huizenga College of Business and Entrepreneurship, Nova Southeastern University, Fort Lauderdale, FL, USA
Peter S. Finley, Ph.D.
Carl DeSantis Building
3301 College Avenue
Fort Lauderdale, FL 33314
Peter S. Finley, Ph.D., is an Associate Professor of Sport and Recreation Management with the H. Wayne Huizenga College of Business and Entrepreneurship at Nova Southeastern University. His research interests include issues in college and youth sports.
Jeffrey J. Fountain, Ph.D., is an Associate Professor of Sport and Recreation Management with the H. Wayne Huizenga College of Business and Entrepreneurship at Nova Southeastern University. His research interests include issues in college sports, with a focus on financial issues and economic issues.
College Selection of Female Student-Athletes: Are the Factors Stable Over Time?
Purpose: This study aimed to apply means-end theory to determine whether the factors that drive college selection by female student-athletes were stable over an extended time at one university. Methods: Semi-structured interviews were conducted by two researchers with a population of 25 NCAA Division II female student-athletes at one university. Results: It was determined that eight attributes, eight consequences, and four values that were previously identified continued to be important drivers of college selection, suggesting that the criteria upon which college selection hinges are highly stable. Two additional factors emerged; the team itself and the opportunity to have personal improvement outside of sports were identified variables in the college selection process for this population. Conclusions: Previous research on college selection of student-athletes lacks any empirical replication or confirmation studies that examine a similarly defined population at the same university, as researchers instead sample different populations or apply different methods or surveys in each study. This research, by establishing the constancy of the factors, can be used by practitioners as they implement strategies for successful recruitment efforts and base those efforts on appealing to the values of the recruits. Applications in Sport: It is vital to recognize how prospective student-athletes choose to matriculate to a given university. Most notably, understanding that satisfying the values of achievement, belonging, fun and enjoyment, and security are as key to college selection as they were over a decade ago is essential and can assist coaches and recruiters in using their time and resources more efficiently as they work to attract prospects that best fit their programs.
Keywords: student-athlete recruitment, NCAA Division II, means-end theory
Recruiting of the highest quality student-athletes is the lifeblood of college sports. The quality of the players who matriculate to a program is likely a limiting or driving factor on the later success of teams. Few factors will contribute more to the success of college teams than the ability to attract and retain the best talent available, making an increased understanding of how to recruit more efficiently worthy of academic attention (19). According to Klenosky, Templin, and Troutman (15), “the competition to recruit talented student-athletes is often as fierce between universities as the actual contests between the schools’ athletic teams” (p. 95). It is, then, not surprising that the recruitment aspect of a coach’s duties can comprise 10-20 percent of their daily work time (8).
As research into college selection by student-athletes gained traction in the academic community, a wide variety of factors emerged as important, representing various populations and research participants. Among the criteria that student-athletes considered were the opportunity to play (9,16,27), academic factors (2,4,6,9,20,25,27), the amount of scholarship offered (5,24,28), the reputation and relationship with the head coach of the team (4,20,27), the coaching staff (12,14), and level of athletic competition (13). Differences did emerge when comparing athletes by NCAA Division. For example, baseball players in Division III were more likely to emphasize academics as compared to Division I or II players (21), and Division II and III lacrosse players valued academics more than Division I players (22).
Research also showed that instead of limiting themselves to just the offerings of the college itself, some prospects consider post-collegiate life in their decision-making. Huffman and Cooper (11) found that some players at Football Bowl Subdivision (FBS) schools identified the opportunity to have a good career off the gridiron as the most important criteria in college selection. Similarly, and perhaps because a professional career in softball seems somewhat improbable, academic factors weighed heavily in a study of community college softball players (29).
A shortcoming of the quantitative approach to college-selection studies is that the respondents often cite many variables as important, and the resulting list of criteria that influenced their decision is a long list of factors without any importance or weight to each. To address the relative importance of these many factors, Chard and Potwarka (3) brought an interesting approach to examining the weight of each variable. In a study of Canadian student-athletes at one university, they applied Priority Theory, which suggests that criteria and sub-criteria can be prioritized (26), and through the application of the Analytical Hierarchy Process (AHP), they determined the weight of criteria relative to other criteria. Among this population, the most important influence was that the college had the desired academic program, and that was almost twice as significant as the reputation of the school, and over twice as important as scholarship value, athletic facilities, chance to win, and the reputation of the head coach (3).
Another potential shortcoming of the college selection literature as it is applied to student-athletes is that it does not often yield recommendations for better recruitment. One study that did address recruitment used 291 surveys of community college softball players to determine that the most salient issues guiding their college selection were head coach, availability of program or major, the social atmosphere of the team, career opportunities after graduation, and the cost of tuition (29). Vermillion and Stoldt recommended that coaches use the results of the study to 1) recognize that softball players are multifaceted and their other identities must be recognized, as softball is not their singular focus, 2) when recruiting the athletic personnel should emphasize team chemistry, academic and overall reputations of the school, support networks, both physical and social, the experience the prospect will have while there and how that will contribute to post-collegiate careers, and 3) that the prospects should be integrated with other academic and social groups during campus visits (29).
Finally, a shortcoming in all the college selection literature is that no researchers have ever returned to a similarly defined population at the same university to determine whether the factors of college selection are stable over time. This research sought to address that gap in the literature.
Application of Means-End Theory
Developed by Gutman (10), means-end theory is designed to allow researchers to use semi-structured interviews to delve into consumer-choice decision-making at a deeper level than simply determining the superficial factors that were important when selecting from several options. It is in the process of guiding the participant through the levels of choice, from the attribute of an item to the positive consequences of selecting that item to the personal value that will be satisfied by that item that the researcher gets to an answer to the question “why” and not just “which.” For example, the location of a university could be important for selecting to attend a college, which can be understood as “which” criteria mattered at the time of selection. Standard survey data will record location as important if enough participants rate it highly. However, means-end theory goes deeper to determine “why” location was important, what consequence was there for selecting a school in that location, and ultimately what value was likely to be met through that choice.
Laddering technique is utilized to guide the interviewee, typically through the question, “Why was that important to you?” This allows the researcher to delve into deeper meanings behind the criteria of that the interviewees said guided their consumer choice. In the case of college selection interviews, laddering technique would be applied by asking the subject what criteria led them to select one college over another. From the responses, such as “location,” the interviewer would ask, “Why was location important to you?” The response could be, “The location allowed me to play my sport year-round.” The next question would be, “Why is it important to play your sport year-round?” The response that doing so would allow the subject to improve and pursue championships would reveal that the importance of location was tied to the value of achievement. Another subject might also say that location mattered, but because it was about being close to the beach, which in turn promised a fun and enjoyable college experience. While both subjects responded that location mattered, it was to satisfy very different values. To one respondent, location satisfied an achievement value, while to the other it satisfied a value of fun and enjoyment in life.
Klenosky, Templin, and Troutman (15) applied means-end theory to the college selection of 27 NCAA Division I football players. Through interviews the researchers demonstrated that an examination on college selection factors could move beyond surveys to explore the underpinning values. It was determined that the players selected the university for such attributes as facilities, the coach, the schedule, and academics. Utilizing means-end, the researchers found these attributes linked to such consequences as getting a “good” job, personal improvement as a player, playing on television, and feeling comfortable. As the interviewers probed deeper into why these consequences were important, they learned that in the minds of the players, each were tied to the four values of 1) feeling secure (Security), 2) a sense of achievement (Achievement), 3) a sense of belonging (Belonging), and 4) having a fun and enjoyable experience (Fun and Enjoyment).
Finley and Fountain (7) applied means-end theory, via the same methodology, to understanding the college selection of female student-athletes at a Division II university. An important finding was that, while the participants in the study were quite different than the Division I football players (15), the four values that underpinned the college selection process were the same; Achievement, Belonging, Fun and Enjoyment, and Security.
Purpose of the Study
As it pertains to student-athletes, currently lacking in the college-selection research is any form of empirical replication of previous work. Every piece of scholarly production stands as a one-off, with little evidence that factors remain consistent over time for similar populations. This research sought to make a unique contribution to the literature by replicating a student-athlete college selection study. The researchers replicated Finley and Fountain’s (7) means-end study of female student-athletes at the same NCAA Division II university. The researchers sought to determine whether the attributes, consequences, and values that guided college selection over a decade ago would be consistent with current student-athletes despite significant changes at the university in both the athletic and academic domains.
Utility of Replication
While replication studies get less attention because they do not necessarily present new knowledge (17), they are valuable for increasing transparency in research, including through empirical replication, in which a previous study’s procedures are repeated with a new population (1). Perhaps most important is to embrace that knowledge does not come only from testing a new theory, designing and using new surveys, or inventing a new construct. Rather, knowledge grows through confirmation (23).
Significant University Changes (2008-present)
At the time of data collection of the Finley and Fountain (7) study, the university utilized in the study had an athletic reputation that could best be described as underperforming. In the decade following the 2008 study, the university made a clear commitment to athletic achievement, best substantiated by the athletic department’s budget, which more than tripled from an annual budget of $3.7 million to over $12.8 million. To account for inflation because of the time difference, both annual budgets were adjusted to 2008 dollars using the CPI Index. Even after accounting for inflation, there was an increase of $8.5 million to the annual athletic department’s operating budget. In addition to the increase in the operating budget for athletics, the university’s financial commitment to building state-of-the-art athletic facilities was also significant; this included a new arena for basketball and volleyball, with a seating capacity of over 5,000, building a new aquatics facility with long-course swimming lanes and a diving well, new tennis courts, a strength, and conditioning facility dedicated to athletics, and purchasing a private golf course with a practice facility complete with a range, practice holes, and swing-monitoring technology. The number of teams offered increased, as track and field and swimming and diving squads were added in recent years.
With the financial commitment came on-field success. Overall, the athletic programs showed steady improvement in the rankings for the Learfield IMG College Director’s Cup, which are based on the total performance across the athletic department in NCAA-level competition. After never appearing in the top twenty universities between and 2006 and 2012, the university finished in the Top 20 three times from 2013 to 2017 (peaking at 9th). Prior to 2008, the university never won a conference or NCAA championship in any sport, for men or women. Over the next decade, the athletic teams won a combined 32 titles at the conference level (22 by women’s teams across six different sports) and added eight NCAA National Championships (five by women’s teams). Further, the head coach of every sport had been replaced since the 2008 study, with a clear shift in philosophy from hiring locally, sometimes from the high school ranks, to conducting national searches and hiring coaches with clear records of success at the NCAA level. Most had led college teams to conference, regional, and often national-level success, producing All-Americans, and often having earned accolades from their peers through “Coach of the Year” recognitions.
It is also noteworthy that over the last thirteen years, the university took strides toward earning national recognition academically by raising undergraduate admission standards, creating substantial academic scholarship programs to attract high-achieving prospects, creating dual admission programs that reserved graduate school seats in medicine, law, and business, and recruited heavily from preeminent private high schools. In this period, the university climbed the U.S. News and World Report rankings from “Rank Not Published” into the top 200 National Universities in several years of the rankings.
The research questions were developed to account for the length of time that had passed between studies, that the population will constitute completely new student-athletes, that the university’s athletic department had undergone significant and measurable changes yielding higher levels of achievement. The findings provide the first confirmation study on the topic of college selection among student-athletes. The results can be applied directly to athletic departments by addressing the question asked by Magnusen, et al., (18), “How do athletic departments improve recruitment effectiveness?” (p. 1266).
RQ1: Will participants identify similar attributes, consequences, and values underpinning their college selection process as a similarly defined population did in 2008, despite significant changes to the university?
RQ2: Will new attributes, consequences, and values emerge as important in the college selection process among this population, as compared to in 2008?
Replicating the previous study (7), the new population also consisted of 25 female student-athletes at the same NCAA Division II university, represented the complete athletic offerings for the university, with at least one participant per sport. This included the sports offered in 2008, basketball, cross country, golf, rowing, soccer, softball, tennis, and volleyball, along with the two sports added in subsequent years, which were track and field and swimming.
To replicate the previous study, identical procedures were used in the interviewing process. This included 1) conducting the semi-structured interviews in a small faculty library to ensure a quiet and non-threatening environment, 2) quickly establishing the student-athlete as the only expert regarding her college selection, 3) reiterating that there were no right or wrong answers, 4) exhibiting curiosity about their responses while demonstrating judgment-free listening, 5) the researchers met with each student-athlete one at a time, and 6) consent forms were reviewed and signed by all participants, all of whom were adults.
The process of creating means-end chains was also identical to the previous study. This included 1) two researchers taking separate notes, which were then compared immediately after each interview, and 2) each interviewee was asked to list the colleges that they seriously considered as they made their final college selection. Subjects were then asked to list as many factors as they felt were important to distinguish their selected college from those that they chose not to attend, 3) the researchers then utilized the laddering technique, as described above, to delve into the question, “Why was that important to you?” The interviewers moved from the list of attributes to the perceived consequences, and finally to the value that was met by each attribute, and 4) means-end chains were created immediately after each interview, with researchers referring to their own notes, and discrepancies were jointly resolved with an emphasis on using keywords and phrases used by the student-athletes. Attributes that did not lead to a completed means-end chain were removed from consideration. Interviews generally lasted around fifteen minutes.
In total, 109 means-end chains were created, an average of 4.36 per participant. Coding the means-end chains revealed nine attributes cited as important in the college selection process of NCAA Division II female student-athletes. These attributes led to nine consequences, which, in turn, led to four values.
Using the coded data, an Implication Matrix (IM) was constructed (See Table 1) to summarize the connections between attributes, consequences, and values. The Implication Matrix provides the number of chains created through the interviews and shows how they linked to each attribute, consequence, or value. Location, for example, started 24 different means-end chains. The number of chains can be greater than the number of participants in the study. One participant could have selected location for two completely different reasons, which would produce two different means-end chains, one that initiated a chain that had to do with nightlife and beaches, leading to the value fun and enjoyment, and another chain that had to do with athletic performance and year-round participation opportunities and then to the value of achievement. The coding in the Implication Matrix represents the data of all 109 chains. From this Implication Matrix, it can be seen how strong connections were between attributes, consequences, and values. For example, of the 11 chains that began with the attribute of scholarship value, ten linked to the consequence of financial comfort, and one linked to feeling valued. Those linkages then connected to the values of achievement (four times) and security (seven times). The Implication Matrix was then used to build a traditional Hierarchical Value Map (HVM).
Table 1: Implication Matrix for female student-athletes’ college selection (Chains)
|A2 Scholarship value||11||0||10||0||0||0||0||1||0||0||0||4||7||0|
|A3 Academic program||16||1||2||0||12||0||0||0||0||1||4||8||3||1|
|A4 Coach’s reputation||17||4||0||0||0||6||0||6||0||1||3||9||1||4|
|A6 Friend on the team||1||0||0||0||0||0||1||0||0||0||0||0||0||1|
|A7 School factors||13||9||0||0||0||0||0||2||0||2||3||4||2||4|
|A8 Open spot||2||0||0||0||0||2||0||0||0||0||0||2||0||0|
|A9 Team factors||15||4||0||0||0||7||0||2||2||0||3||9||0||3|
|C1 Feel comfort||25||–||–||–||–||–||–||–||–||–||8||5||6||6|
|C2 Financial comfort||12||–||–||–||–||–||–||–||–||–||0||4||8||0|
|C4 Get a good job||13||–||–||–||–||–||–||–||–||–||4||7||2||0|
|C5 Can improve||30||–||–||–||–||–||–||–||–||–||4||26||0||0|
|C6 Friends & family||3||–||–||–||–||–||–||–||–||–||0||0||2||1|
|C7 Feel valued||12||–||–||–||–||–||–||–||–||–||1||5||0||6|
|C8 Playing time||2||–||–||–||–||–||–||–||–||–||1||1||0||0|
|C9 Personal improvement||5||–||–||–||–||–||–||–||–||–||1||4||0||0|
|V1 Fun and enjoyment||26||8||0||7||4||4||0||1||1||1||–||–||–||–|
The construction of a readable Hierarchical Value Map requires researchers to determine a cut-off value to demonstrate how frequently a connection had to be made to warrant the graphic representation of a line showing a connection. Although all connections can be determined via the Implication Matrix, the Hierarchical Value Map reduces clutter by eliminating connections made sparingly. In transferring the data from the IM to the HVM, the researchers selected a cut-off level of five chains. The more frequently an association was made, the thicker the lines appear, and various shades were used to make the frequency of association more apparent, with thin grey lines representing fewer associations than those lines presented in thick black ink.
Consistent with the work of Klenosky, Templin, and Troutman (15) and Finley and Fountain (7), the HVM (see Figure 1) has the following structure: 1) The values are presented at the top to indicate their abstract nature, in triangles and with all capital letters, 2)The consequences are represented in the middle, in circles and beginning with a capital letter, and 3) the attributes are at the bottom, indicative of being just the beginning point for decision making, in rectangles and with all lower-case letters. The first number within each shape represents the number of participants who mentioned that concept, followed by a number in parenthesis indicating how many times that concept was mentioned in total; again, allowing for a single concept to be mentioned more than once by a single participant.
While the focus of this study is qualitative in nature, the data does provide an overview of the differences between 2008 and the current results. While both studies had 25 NCAA Division II female student-athletes, the current data resulted in 32 additional means-end chains. In 2008 the 25 participants averaged 3.08 chains for a total of 77, whereas the current participants averaged 4.36 chains for a total of 109.
Research Question One
There was tremendous stability of the factors of college selection over an extended period, with all eight attributes, eight consequences, and four values from the 2008 study emerging through the interviews again.
Research Question Two
There were two new factors of college selection that emerged through the current research. One was an additional attribute, called team factors, and the other an additional consequence, called personal improvement. There were no new values that were found.
Table 2; Difference between 2008 and Current research findings
|From||2008* N (Chains)||Current N (Chains)||Difference|
|Difference in Chains|
|A1 Location||22 (30)||19 (24)||-3||-6|
|A2 Scholarship value||16 (16)||11 (11)||-5||-5|
|A3 Academic programs||7 (7)||15 (16)||+8||+9|
|A4 Coach’s reputation||7 (7)||13 (17)||+6||+10|
|A5 Facilities||6 (6)||9 (10)||+3||+4|
|A6 Friend on the team||4 (4)||1 (1)||-3||-3|
|A7 School factors||4 (4)||11 (13)||+7||+9|
|A8 Open spot||3 (3)||2 (2)||-1||-1|
|A9 Team factors||N/A||13 (15)||+13||+15|
|C1 Feel comfort||15 (16)||18 (25)||+3||+9|
|C2 Financial comfort||14 (14)||12 (12)||-2||-2|
|C3 Adventure||12 (12)||7 (7)||-5||-5|
|C4 Get a good job||9 (9)||13 (13)||+4||+4|
|C5 Can improve||8 (10)||18 (30)||+10||+20|
|C6 Friends & family||7 (8)||3 (3)||-4||-5|
|C7 Feel valued||5 (5)||11 (12)||+6||+7|
|C8 Playing time||3 (3)||2 (2)||-1||-1|
|C9 Personal improvement||N/A||4 (5)||+4||+5|
|V1 Fun & enjoyment||20 (27)||18 (26)||-2||-1|
|V2 Achievement||14 (21)||23 (52)||+9||+31|
|V3 Security||13 (22)||12 (18)||-1||-4|
|V4 Belonging||5 (7)||11 (13)||+6||+6|
The findings for the attribute variables did indicate that the attributes cited by NCAA Division II female student-athletes were similar in the college selection process to the female student-athletes in 2008, with all eight of the previously identified attributes being mentioned again. However, the current study also produced a new, ninth attribute. The researchers labeled the newly discovered attribute “team factors,” and it was typically mentioned regarding the team having a history of success and a promising future and that the student-athlete saw herself fitting in and being successful with the team. It was mentioned by thirteen participants, and it initiated 15 means-end chains. The new attribute accounted for 15 of the 32 additional means-end chains. The remaining eight attributes saw differences in the number of means-end chains they initiated. For example, academic programs, coach, and school factors all saw considerable increases in the number of participants mentioning the attribute as well as several more means-end chains initiated. Conversely, the four attributes of location, scholarship, a friend on the team, and an open spot all saw declines in the number of participants mentioning them, and a reduction in the number of mean-end chains initiated.
The findings for the consequences variables also indicated consistency, with all eight consequences from the 2008 study being mentioned again. However, like the results of the attributes, one new consequence variable also emerged. The researchers labeled the newly discovered consequence “personal improvement.” This new consequence was distinct from the consequence “can improve,” which was strictly about getting measurably better in one’s sport, whether that be better scores, faster times, or a greater chance to play at a higher level. The new consequence of personal improvement, mentioned by four participants, dealt with being a more mature person, experiencing personal growth, and taking on a challenge through the college experience. It was about personal transformation in ways that were separate from athletic improvement. The biggest difference in consequence variables between 2008 and the current research was seen in the consequence can improve, which saw ten additional participants mention it, resulting in an additional 20 means-end chains. The consequences of feel comfortable, feel valued, and getting a good job also saw more participants and means-end chains. The consequences of financial comfort, adventure, friends and family, and playing time saw reduced mentions by participants and a decline in means-end chains.
The findings for the values that underpin the selection of a college also showed consistency, with all four variables (achievement, belonging, fun and enjoyment, and security) repeating as the only values to which every means-end chain finished. The most noteworthy difference between the 2008 and current populations was the large increase in the number of participants and means-end chains leading to achievement as a value that would be satisfied by choosing the university. Nine additional participants mentioned achievement, and 31 additional means-end chains concluded with that value. Six additional participants mentioned belonging, while both fun and enjoyment and security saw slight decreases in the number of mentions and means-end chains.
The goal of this research was to determine whether there was consistency in the attributes, consequences, and values that guided the college selection of NCAA Division II female student-athletes at one university, even with the substantial financial investment in athletics and the emphasis on increasing the university’s academic profile. The results of the study clearly showed that while one new attribute and one new consequence emerged, the original variables all still factored into the college selection process of the participants. Most importantly, all the means-end chains continued to lead to the same four values: achievement, belonging, fun and enjoyment, and security.
Many of the differences between 2008 and current results logically coincide with the changes to the athletic department and the university. Achievement was the value that the current student-athletes most wanted to satisfy as they made their college selection. This emergence stands in contrast to 2008, when the athletic programs were rather mediocre, and the participants were more interested in satisfying the value of having a fun and enjoyable experience. In the 2008 study, one of the most common means-end chains linked location to the consequence of adventure and on to the value of fun and enjoyment. All three of those variables were mentioned by fewer participants in this study. The greatest change was the number of participants that had chains lead to the achievement value, which increased from 14 to 23 participants and from 21 to 52 chains. It stands to reason that the coaching staff would recruit prospects with this value, and it ties strongly to the consequence of improvement in the sport. The results also clearly show a shift toward athletes wanting to improve in their sport, feel comfortable, and feel valued. The desire to improve fits the athletic department’s agenda of having greater success at all levels of competition and would validate the expenditures the athletic department had made. Further, the current coaches were likely actively recruiting prospects who show a strong desire for improvement within the sporting context. Similarly, the emphasis on recruiting high-achieving prospects in general, combined with the changing academic profile of the university, likely explains the slight increase in the consequence of getting a good job after graduation.
The focus on academic reputation would seem to be the best explanation for the increased attention to the attributes of the school and academics as factors driving college selection. Given the hiring practices of the athletic department, to bring in coaches with histories of success and then their impact at the university, the increase in attention to the coach as a factor is not surprising and would be considered a desirable outcome for the university. However, given the tremendous financial investment in athletic facilities, it was interesting to see that the attribute of facilities only saw a modest gain in importance. Only three more participants mentioned facilities than had in 2008.
APPLICATIONS IN SPORT
As college selection research advances, there should be a connection between theory and practice that contributes to successful athletic department’s recruiting strategies. To that end, it is recommended that in the recruitment process, the athletic department personnel move beyond discussing the attributes of the university, the athletic programs, the teams, and the facilities. Coaches, administrators and admission counselors should help the prospect understand how those attributes will satisfy the values of wanting to achieve, belong, have fun and feel secure. For example, a traditional campus tour would include showing the prospect the athletic facilities; the weights and training rooms, locker rooms, and the competition space (whether that be an arena, a field, court, pool, etc.). However, based on these means-end studies, it would be a much richer and more meaningful experience to then explain how that space contributes to a fun experience, or how it can be utilized to help the athlete improve in their sport, and ultimately how training and playing in that space leads to greater achievement for the player and the team. Similarly, in anticipating a recruitment opportunity, the coach could focus on what he or she can do to make the athlete see that they will feel a sense of belonging, perhaps through conversations about the team’s traditions, lifelong friendships that athletes create, structured mentorship programs between older and younger athletes, and so forth. The coaches should consider how to demonstrate that student-athletes feel secure, which goes well beyond issues such as campus security, blue-box alarm systems, and buzzing into secure spaces with an identification card. To emphasize how the athletic program contributes to a sense of family and togetherness, coaches may explain how many student-athletes stay for four or more years to underscore a consistent, nurturing environment and how student-athletes find financial security through post-graduate job placement. In every aspect of the campus visit, those with recruiting responsibility should be considering how they are addressing the values that underpin college selection and not merely the attributes of the campus and program.
Limitations and Future Research
This study is not without limitation. First, as with any interview-based research, the information gleaned from the participants is filtered through the interviewers, coded, and reduced to usable data. In this process, it will inherently lose a degree of its richness. Every effort was made to take notes separately and to reconcile the interviewers’ differing perceptions fairly to best reflect the intended meanings of the participants. Second, this is one study of one relatively small population at one university. Further research that employs means-end interviewing among other populations (males, for example) in other contexts (NCAA Divisions, regions of the country, etc.) will add to the body of knowledge in this area. Third, the study depends on an accurate memory of the participants, as they attempt to return to the moment that they selected one college over others and to know and truthfully explain the most meaningful attributes that created differentiation between those options. Then the participants must be willing to truthfully explore what they anticipated were consequences of those attributes and what values they hoped to satisfy. For many participants this asked them to explore their own values in deeper ways than they likely had previously considered. Future studies should replicate this methodology with new populations of student-athletes to verify or refute that there are four known values that underpin the college selection process.
- Aguinis H., & Solarino, A.M. (2019). Transparency and replicability in qualitative research: The case of interviews with elite informants. Strategic Management Journal, 40(8), 12911315. https://doi.org/10.1002/smj.3015
- Bukowski, B.J. (1995). Influences on student college choice for minority and non-minority athletes at a Division III institution (Doctoral dissertation, University of Wisconsin, Madison, WI). Dissertation Abstracts International, 56(7), 126.
- Chard, C.R., & Potwarka, L.R. (2017). Exploring the Relative Importance of Factors That Influence Student-Athletes’ School-Choice Decisions: A Case Study of One Canadian University. Journal of Intercollegiate Sport, 10(1), 22-43. https://doi.org/10.1123/jis.2016-0014
- Cook, T. (1994). Factors female freshmen student-athletes use in deciding between a NJCAA college and a NAIA college. Unpublished master’s thesis, University of Kansas, Lawrence, KS.
- Doyle, C.A., & Gaeth, G.J. (1990). Assessing the Institutional Choice Process of Student-Athletes. Research Quarterly for Exercise and Sport, 61(1), 85–92. https://doi.org/10.1080/02701367.1990.10607482
- Finley, P.S., & Fountain, J.J. (2008). An application of means-end theory to analyze the college selection process of female athletes at an NCAA Division II–university. The Sport Journal, 11(2). Available for download at https://thesportjournal.org
- Feldman, B. (2009, Sept. 7). Recruiting’s importance keeps growing. ESPN. Retrieved from https://www.espn.com/collegesports/recruiting/football/columns/story?columnist=feldman_bruce&id=4453458
- Forseth, E. (1987). Factors influencing student-athletes’ college choice at evangelical, church supported NAIA institutions in Ohio (Doctoral dissertation, The Ohio State University, Columbus, Ohio). Dissertation Abstracts International, 48(01), 172.
- Gutman, J. (1982). A means-end chain model based on consumer categorization process. Journal of Marketing, 46(2), 60-72.
- Huffman, L.T., & Cooper, C.G. (2012). I’m taking my talents to… An examination of hometown socio-economic status on the college-choice factors of football student-athletes at a southeastern university. Journal of Issues in Intercollegiate Athletics, 5, 225-246. Available for download at http://csri-jiia.org
- Jordan, T.L., & Kobritz, J.I. (2011). University selection factors for Division II softball student athletes. Journal of Issues in Intercollegiate Athletics, 4, 428-440. Available for download at http://csri-jiia.org
- Judson, K.M., James, J.D., & Aurand, T.W., (2004). Marketing the university to student-athletes: Understanding university selection criteria. Journal of Marketing of Higher Education, 14(1), 23-40. https://doi.org/10.1300/J050v14n01_02
- Kankey, K., & Quarterman, J. (2007). Factors influencing the university choice of NCAA division I softball players. The SMART Journal, 3(2), 35–49. Available for download at http://ww.w.thesmartjournal.com/softball.pdf
- Klenosky, D.B., Templin, T.J., & Troutman, J.A. (2001). Recruiting student athletes: A means-end investigation of school-choice decision making. Journal of Sport Management, 15(2). https://doi.org/10.1123jsm.15.2.95
- Kulkarni, S. (2013, October 17). Why are replication studies so rarely published? Editage Insights. https://doi.org/10.34193/El-A-6230
- Magnusen, M.J., Kim, Y., Perrewe, P.L., & Ferris, G.R. (2014). A critical review and synthesis of student-athlete college-choice factors: Recruiting effectiveness in NCAA sports. International Journal of Sports Science and Coaching, 9(6), 1265-1286. https://doi.org/10.1260/1747-9518.104.22.1685
- Magnusen, M.J., Kim, J.W., McAllister, C.P., Perrewe, P.L., Ferris, G.R. (2018). She got game: Investigating how reputation can be leveraged to improve recruiting effectiveness in National Collegiate Athletic Association women’s basketball. International Journal of Sports Science and Coaching, 13(2), 179-185. https://doi: 10.1177/1747954117725928
- Mathes, S., & Gurney, G. (1985). Factors in student-athletes choice of colleges. Journal of College Student Personnel, 26(4), 327-333.
- Pauline, J., Pauline, G., & Stevens, A. (2004). Influential factors in the college selection process of baseball student-athletes. Journal of Contemporary Athletics, 1(2), 153-166.
- Pauline, J. (2010). Factors influencing college selection by NCAA Division I, II, and III lacrosse players. The ICHPER-SD Journal of Research in Health, Physical Education, Recreation, Sport & Dance, 5(2), 62.
- Polit, D.F., & Beck, C.T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47 (11): 1451-58.
- Popp, N., Pierce, D., & Hums, M.A. (2011). A comparison of the college selection process for international and domestic student-athletes at NCAA Division I universities. Sport Management Review, 14(2), 176–187. https://doi.org/10.1016/j.smr.2010.08.003
- Reynaud, C. (1998). Factors influencing prospective female volleyball student-athletes’ selection of an NCAA Division I university: Towards a more informed recruitment process (Doctoral dissertation, Florida State University, Tallahassee, FL.) Dissertation Abstracts International, 59(02), 445.
- Saaty, T.L. (2008). Decision making with the analytical hierarchy process. International Journal of Services Science, 1(1), 83-98. https://doi.org/10.1504/IJSSCI.2008.017590
- Slabik, S.L. (1995). Influences on college choice of student-athletes at National Collegiate Athletic Association Division III institutions. Unpublished doctoral dissertation, Temple University, Philadelphia, PA.
- Ulferts, L. (1992). Factors influencing recruitment of collegiate basketball players in institutions of higher education in the Midwest (Doctoral dissertation, University of North Dakota, Grand Forks, ND). Dissertation Abstracts International, 54(03), 770.
- Vermillion, M., & Stoldt, G.C. (2010). College choice factors influencing community college softball players. Journal of Coaching Education, 3(1).