Browsing by Subject "intercollegiate athletics"

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    Applying Holland's Vocational Choice Theory in Sport Management
    (Human Kinetics, 2017) Pierce, David; Johnson, James
    Holland’s (1997) vocational choice theory is used in vocational counseling to aid job seekers in finding occupations that fit their personality based on Holland’s RIASEC typology of personalities and work environments. The purpose of this research was to determine the Holland RIASEC profiles for occupations within the sport industry by having employees in intercollegiate athletics complete the Position Classification Inventory (Gottfredson & Holland, 1991). Results indicated the three-letter Holland code for the sport industry is SEC. The sport industry is dominated by the Social environment, evidenced by seven occupations possessing Social in the first letter of the profile and Social rating in the top two for all occupations. Seven occupations were primarily Social, three were Realistic, two were Enterprising, and two were Conventional. A MANOVA was also conducted to compare differences between occupational disciplines on the six Holland environments. Implications for sport industry occupations and the application of Holland’s theory are discussed.
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    Who should we hire?: Examining coaching succession in NCAA Division I women’s basketball
    (Sage, 2017-04) Pierce, David A.; Johnson, James E.; Krohn, Brian D.; Judge, Lawrence W.; Tourism, Conventions and Event Management, School of Physical Education and Tourism Management
    The purpose of this study was to evaluate the performance of newly hired coaches in relation to their predecessors, and utilize the analysis to provide guidance to decision makers in college athletic departments. This study examined 185 coaching changes in Division I women’s basketball in 16 conferences between 2000 and 2009. Data were collected from online sources including institutional websites, media guides, and media articles. Latent class analysis was employed to reduce the data to one item per factor. Factors included demographics, coaching ability, coaching experience, past team performance, hiring factors (coaching level change, inside/outside hire, interim, conference affiliation), and institutional factors (public/private, demographic market area, enrollment, budget, and National Association of Collegiate Directors of Athletics standings). Mixed models analysis was performed to identify which categories have a relationship with changes in the number of wins following a coaching change. Results suggest that past team performance was the strongest indicator of future performance after a coaching change.