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«IMPACT OF MARKET DEMAND AND GAME SUPPORT PROGRAMS ON CONSUMPTION LEVELS OF PROFESSIONAL TEAM SPORT SPECTATORS AS MEDIATED BY PERCEIVED VALUE By ...»

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IMPACT OF MARKET DEMAND AND GAME SUPPORT PROGRAMS ON

CONSUMPTION LEVELS OF PROFESSIONAL TEAM SPORT SPECTATORS AS

MEDIATED BY PERCEIVED VALUE

By

KUN-WUNG BYON

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL

OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

© Kun-wung Byon To my family

ACKNOWLEDGMENTS

I would like to show my deepest appreciation to my advisor, Dr. James J. Zhang for his endless support throughout my course of study in the Ph D. program. I would not have been able to complete my dissertation without his patience, encouragement, insight, and support. Also, I want to thank the members of my committee (Dr. Connaughton, Dr. Ko, Dr. Kim, and Dr. Lutz) for their guidance and constructive advice. Many thanks also go to my Ph. D program colleagues who encouraged me during this arduous process. Most importantly, I thank my lovely wife, Young-woo, and my precious son and daughter, Connor and Kaylee, for their endless love and unselfish sacrifice. I love them all! Also, I would like to thank my entire family in Korea for their support and encouragement during my 6 years of education in the U.S. Above all else, I want to thank God, Jesus Christ, who strengthens me whenever and wherever.

TABLE OF CONTENTS

page ACKNOWLEDGMENTS

LIST OF TABLES

LIST OF FIGURES

LIST OF TERMS

ABSTRACT

CHAPTER 1 INTRODUCTION

Statement of Problem

Hypothesized Research Model

Significance of the Study

Delimitations

Limitations

2 LITERATURE REVIEW

Sport Spectator Consumption

Definition of Sport Spectator Consumption

Measurement of Behavioral Intentions

Overview of the Proposed Dimensions of Spectator Behavioral Intentions

Repatronage intentions

Recommending to others intentions

Service Quality

Definition of Service Quality

Significance of Examining Service Quality

Measurement of Service Quality

Overview of the Proposed Spectator Service Quality

Market Demand (Core Service Quality)

Proposed Dimensions of Market Demand (Core Service Quality)

Home team

Opposing team

Love of professional team sport

Economic consideration

Game promotion

Schedule convenience

Spectator Game Support Programs (Peripheral Service Quality)

Proposed Dimensions of Spectator Game Support Programs (Peripheral Service Quality)

Ticket service

Game amenities

Stadium service

Stadium accessibility

Perceived Value

Definition of Perceived Value

Importance of Examining Perceived Value

Measurement of Perceived Value

Overview of the Proposed Dimensions of Perceived Value

Perceived Value for the Cost

Relationship among Perceived Value, Service Quality, and Behavioral Intentions.......77 Summary

3 METHODOLOGY

Participants

Measurement

Market Demand

Game Support Programs

Perceived Value

Behavioral Intentions

Demographic Information

Procedures

Data Analyses

4 RESULTS

Descriptive Statistics

Exploratory Factor Analyses

Market Demand

Game Support

Perceived Value for the Cost

Behavioral Intentions

Measurement Models: Confirmatory Factor Analyses

Market Demand

Game Support Programs

Perceived Value for the Cost

Behavioral Intentions

Structural Model

5 DISCUSSION

Measurement Properties

Hypotheses Testing

Additional Suggestions

APPENDIX A INFORMED CONSENT AND QUESTIONNAIRE

LIST OF REFERENCES

BIOGRAPHICAL SKETCH

–  –  –

4-1 Frequency distributions for the sociodemographic variables (N = 453)

4-2 Descriptive statistics for the market demand variables (N = 453)

4-3 Descriptive statistics for the game support programs variables (N = 453)

4-4 Descriptive statistics for the perceived value for the cost variables (N = 453)...............146 4-5 Descriptive statistics for the behavioral intentions variables (N = 453)

4-6 Factor pattern matrix for the market demand variables: alpha factoring with promax rotation using first half data (n = 231)

4-7 Factor pattern matrix for the game support programs variables: alpha factoring with promax rotation using first half data (n = 231)

4-8 model fit comparison between the six-factor model and five-factor model of market demand using second half data (n = 222)

4-9 Model fit comparison between the five-factor model, four-factor model, and threefactor model of game support programs using second half data (n = 222)

4-10 Model fit comparison between the five-item model and three-item model of perceived value for the cost using second half data (n = 222)





4-11 Model fit comparison between the ten-item model and five-item model of behavioral intentions using second half data (n = 222)

4-12 Overall model fit indices for the measurement model of hypothesized structural model using second half data (n = 222)

4-13 Interfactor correlations from the confirmatory factor analysis of the market demand using second half data (n = 222)

4-14 Interfactor correlations from the confirmatory factor analysis of the game support programs using second half data (n = 222)

4-15 Interfactor correlations, construct reliability, and average variance extracted from the confirmatory factor analysis of the hypothesized structural model using second half data (n = 222)

4-16 Indicator loadings, critical ratios, cronbach’s alpha, construct reliability, average variance extracted for the market demand using second half data (n = 222)..................158 4-17 Indicator loadings, critical ratios, cronbach’s alpha, construct reliability, average variance extracted for the game support programs using second half data (n = 222).....159 4-18 Indicator loadings, critical ratios, cronbach’s alpha, construct reliability, average variance extracted for the perceived value for the cost using second half data (n = 222)

4-19 Indicator loadings, critical ratios, cronbach’s alpha, construct reliability, average variance extracted for the behavioral intentions using second half data (n = 222)..........161 4-20 Maximum likelihood standardized loadings (β), critical ratios (cr), standard errors (se), and t-values for the hypothesized structural model using second half data (n = 222)

–  –  –

1-1 Conceptual framework of market demand, game support programs, perceived value, and behavioral intentions

1-2 Six dimensions of market demand

1-3 Four dimensions of game support programs

1-4 Uni-dimension of perceived value

1-5 Two dimensions of behavioral intentions

1-6 Proposed structural relationships among market demand, game support, perceived value for the cost, and behavioral intentions

4-1 First-order confirmatory factor analysis for market demand

4-2 First-order confirmatory factor analysis for game support programs

4-3 First-order confirmatory factor analysis for perceived value for the cost

4-4 First-Order confirmatory factor analysis for behavioral intentions

4-5 Tested structural model

4-6 Tested structural model

–  –  –

Behavioral Intentions Behavioral intentions as indications of an individual’s willingness toward a given task (Ajzen, 2005).

–  –  –

IMPACT OF MARKET DEMAND AND GAME SUPPORT PROGRAMS ON

CONSUMPTION LEVELS OF PROFESSIONAL TEAM SPORT SPECTATORS AS

MEDIATED BY PERCEIVED VALUE

–  –  –

Chair: James J. Zhang Major: Health and Human Performance The purpose of this study was to examine the structural relationship of market demand variables and game support programs to the consumption of professional team sport games while taking into consideration the mediating influence of perceived value. This study simultaneously incorporated market demand (core service) and game support (peripheral service) factors into one study and examined their direct and indirect relationships with game consumption behaviors.

A questionnaire that measured market demand of professional team sport games, game support programs, perceived value, consumption intentions, and sociodemographics was responded by a total of 453 research participants at various metropolitan areas and locations, following a community intercept sampling approach (Brenner, 1996). The data set was randomly split into two halves: one for exploratory factor analyses and the other for confirmatory factor analyses and tests of structural relationships among these sets of variables. As a result of the factor analyses, five factors were confirmed for the market demand variables including Home Team, Opposing Team, Game Promotion, Economic Consideration, and Schedule Convenience. A three-factor model of game support programs was generated that consisted of Game Amenities, Ticket Service, and Venue Quality. Furthermore, a unidimensional model was derived for the perceived value (i.e., Perceived Value for the Cost) and consumption intentions (Behavioral Intentions) sections from the factor analyses, respectively. All measures displayed good psychometric properties in terms of validity and reliability. In the structural relationship analyses, Home Team, Opposing Team, Game Promotion, Game Amenities, and Perceived Value for the Cost were found to be significantly related to Behavioral Intentions for professional team sport games. Venue Quality was the only factor that was found to have an indirect relationship with Behavioral Intentions through Perceived Value for the Cost. The findings of this study revealed the importance for professional sport teams to build a strong and high-quality home team, highlight the merits and competitiveness of both home and opposing teams in their game promotions, adopt multiple means of marketing campaigns, formulate exciting entertainment elements for pre-game, during-game, and post-game shows, and price game tickets in a reasonable manner to ensure consumer affordability.

–  –  –

According to Shank (2005), game attendance is the most traditional and important form of sport consumption behavior in spectator sport, which is defined as any live sport event that is played in front of spectators. Examples of spectator sport include, but are not limited to, baseball, basketball, football, and ice hockey. Spectator sport is distinguished from participant sport in two aspects. First, the main activity and motivation for spectators in a sport event lie in watching a sport competition; whereas, the main activity and motivation for a participant sport is the actual playing of the sport. Second, spectator sport requires some type of confined facilities (e.g., stadium, arena, gym, or field), where spectators can watch the athletic performance and competition. Nevertheless, a chaste participant sport such as hunting does not necessarily require any venue for paid spectators (Shank, 2005).

Chelladurai (1999) classified the sport industry into three segments: (a) sport economic activities, (b) spectator sports, and (c) participant sports. This researcher noted that spectator sport had been the fastest growing segment within the sport industry and further estimated that this sector alone was a $50 billion industry in terms of annual business transactions. Other researchers have also recognized the continued growth of spectator sport in North America by pointing out that spectator sport has become an increasingly important type of leisure behaviors of Americans (Ross & James, 2006; Trail, Anderson, & Fink, 2005). The rapid and vast growth of professional sport teams in North America is also evidence of the immense interest in spectator sports. According to Frank (2000), 67% of the U.S. population referred to themselves as fans of the National Football League (NFL), 62% of the U.S. population indicated that they were rooting for Major League Baseball (MLB), and 54% reported that they were National Basketball Association (NBA) fans. Masteralexis, Barr, and Hums (2008) indicated that as of 2007, a total of 149 franchise teams belong to the five major professional sport leagues: MLB, NFL, NBA, the National Hockey League (NHL), and Major League Soccer (MLS). This figure does not include teams in less-prominent professional sport leagues such as the Arena Football League (AFL), Women’s National Basketball Association (WNBA), and many other major and minor league teams. The augmentation of spectator sports has been also confirmed through attendance and media viewership rates. In the year of 2003-2004, approximately 476 million people attended spectator sport events in North America. In 2003, NFL games were played in front of more than 17 million fans that attended games at 95% of stadium capacity on average. A similar trend has been observed in international competitions as well; for example, the 2002 World Cup soccer tournament in Korea and Japan was televised to over 200 countries during 30 days of competition, drawing approximately 28.2 billion cumulative viewers (Hyundai Economic Institute, 2002). Brandt (2004) reported that approximately 137 million television viewers watched the 2004 Super Bowl. The same phenomenon is also true in Division I men’s basketball and football, which are considered to be the two main revenue producers for collegiate athletic departments (Fulks, 2003). In 2005, nearly 1.3 million people watched March Madness college men’s basketball games online (Rein, Kotler, & Shields, 2006). According to Fulks, the average percentages that Division-I men’s basketball and football contributed to the income of Division I athletic programs in 2003 were 70% ($13 million) and 23% ($4.3 million), respectively.



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