Browsing by Author "Tourism, Conventions and Event Management, School of Physical Education and Tourism Management"

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    Ticket Sales Outsourcing Performance Measures Using Balanced Scorecard and Analytic Hierarchy Process Combined Model
    (FiT, 2017-06) Lee, Seungbum; Brownlee, Eric; Kim, Yongjae; Lee, Soonhwan; Tourism, Conventions and Event Management, School of Physical Education and Tourism Management
    Outsourcing ticket sales operations to the service provider is becoming popular in intercollegiate sport in the US. While much has been reported about ticket sales outsourcing, there is a major lack of understanding in the literature as to how the service provider’s performance is measured by the athletic department. To fill important gaps in the sport marketing literature, this study employed the Balanced Scorecard (BSC) and Analytic Hierarchy Process (AHP) combined model using one NCAA Division I athletic department to understand performance measure metrics. The result of the AHP showed that Financial (WF = 0.487) is the most important performance measure within the domain level, followed by Customer (WC = 0.343), Business Process (WB = 0.091), and Learning & Growth (WL = 0.078). Global weights indicated that Cost-Saving (WFC = 0.223) is the most important factor, which implies that cost-driven outsourcing is a primary motivation for ticket sales outsourcing. Theoretical and practical implications of the analyses are also provided.
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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.