Segmentation by Motivational Factors of Fantasy Football Consumers and Differences Among Segments

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Market segmentation and consumer motivation are among the most important concepts utilized in the prediction and explanation of consumer behavior. Although fantasy sports consumption has shown a remarkable growth in recent years, there has been limited research on the characteristics of participants of this activity, motivational factors influencing participation, and the effects of these factors on consumer behavior and preferences. For this purpose, we aimed to reveal the motives of fantasy football consumers, to comprise motivational market segments, and to show the potential differences between the segments in terms of experience. In the present study, we used non-hierarchical clustering (K-mean analysis) and hierarchical clustering (Ward cluster algorithm) analyses to determine the number of segments. In addition, we analyzed the potential differences between segments using ANOVA and chi-square analyses. As a result, we found that fantasy football consumers were classified into three different segments (loyal gamblers, hedonists, and casual players) with a motivational basis for the different behavioral responses. According to difference analysis, the consumers who are in different segments were found to be statistically different in terms of consumption behavior and experiential characteristics. The theoretical and practical effects of the study results were evaluated for academicians and practitioners.

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  • Altunisik R. Coskun R. Bayraktaroglu S. & Yildirim E. (2012). Sosyal bilimlerde arastirma yontemleri [Research Methods in Social Sciences]. Sakarya: Sakarya Publishing.

  • Armstrong G. & Kotler P. (2000) Marketing: An Introduction. Upper Saddle River NJ: Prentice Hall Inc.

  • Billings A.C. & Ruihley B.J. (2013). Why we watch why we play: The relationship between fantasy sport and fanship motivations. Mass Commun. Soc. 16(1) 5-25. DOI: 10.1080/15205436.2011.635260.

  • Buyukozturk S. (2016). Sosyal bilimler icin veri analizi el kitabi [Data Analysis Handbook for Social Sciences]. Ankara: Pegema Publishing.

  • Comeau T.O. (2007). Fantasy football participation and media usage. Unpublished doctoral dissertation University of Missouri Columbia MO.

  • Dhurup M. & Dlodlo N. (2013). To play or not to play! Online fantasy football consumption motives and the relationship with attitude and future behavioural intentions. Mediterranean Journal of Social Sciences 4(14) 201-211. DOI: 10.5901/mjss.2013.v4n14p201.

  • Dimisa A. (2016 Nov 4). The popularity of fantasy sports continues to grow. Retrieved November 30 2017 from

  • Dixon A.W. Backman S. Backman K. & Norman W. (2012). Expenditure-based segmentation of sport tourists. Journal of Sport & Tourism 17(1) 5-21. DOI: 10.1080/14775085.2011.635017.

  • Duman C. Taskin E. Gokce Z. & Zobar L. (2015). Clustering consumers through their football involvement levels and differences between clusters. Journal of ONERI 11(43) 71-88. DOI: 10.14783/od.v11i43.5000070103.

  • Dwyer B. & Drayer J. (2010). Fantasy sport consumer segmentation: An investigation into the differing consumption modes of fantasy football participants. Sport Marketing Quarterly 22(1) 33-47.

  • Dwyer B. & Kim Y. (2011). For love or money: Developing and validating a motivational scale for fantasy football participation. J. Sport Manage 25(1) 70-83. DOI: 10.1123/jsm.25.1.70.

  • Dwyer B. (2013). The impact of game outcomes on fantasy football participation and National Football League media consumption. Sport Marketing Quarterly 22(1) 33-47.

  • Dwyer B. Shapiro S.L. & Drayer J. (2011). Segmenting motivation: An analysis of fantasy baseball motives and mediated sport consumption. Sport Marketing Quarterly 20 129-137.

  • Eskiler E. Demirhan O. & Soyer F. (2017). Turkish validity and reliability study of “motivational scale for fantasy football participation.” Journal of Physical Education and Sports Sci 11(2) 159-169.

  • Eskiler E. Ozmen M. & Uzkurt C. (2011). The relationship of knowledge management market orientation and marketing innovation: A research on furniture industry. Eskisehir Osmangazi University Journal of Economics and Administrative Sciences 6(1) 31-69.

  • Farquhar L.K. & Meeds R. (2007). Types of fantasy sports users and their motivations. J. Comput.-Mediat. Comm. 12(4) 1208-1228. DOI: 10.1111/j.1083-6101.2007.00370.x.

  • Funk D.C. (2002). Consumer-based marketing: The use of micro-segmentation strategies for understanding sport consumption. Int. J Sport Mark. Spo. 4(3) 39-64. DOI: 10.1108/IJSMS-04-03-2002-B004.

  • Greenberg M. & McDonald S.S. (1989). Successful needs/benefits segmentation: A user’s guide. J. Consum. Mark. 6(3) 29-36. DOI: 10.1108/EUM0000000002552.

  • Green-Demers I. Pelletier L.G. Stewart D.G. & Gushue N.R. (1998). Coping with the less interesting aspects of training: Toward a model of interest and motivation enhancement in individual sports. Basic Appl. Soc. Psych. 20(4) 251-261. DOI: 10.1207/s15324834basp2004_2.

  • Haley R.I. (1984). Benefit segments: Backwards and forwards. J. Advertising Res. 24(1) 19-25.

  • Indiana University Sports and Entertainment Academy Kelley School of Business. (2000). It’s football friends and fun but few women interested in sports fantasy leagues study finds. Retrieved November 30 2017 from releases/fantasy.htm

  • Islamoglu A.H. & Altunisik R. (2013). Tuketici davranislari [Consumer Behavior]. Istanbul: Beta Publications.

  • Ketchen Jr. D.J. & Shook C.L. (1996). The application of cluster analysis in strategic management research: An analysis and critique. Strategic Management Journal 441-458.

  • Kim C. & Korea S.Y.K. (1998). Segmentation of sport center members in Seoul based on attitudes toward service quality. J. Sport Manage. 12(4) 273-287. DOI: 10.1123/jsm.12.4.273.

  • Kotler P. & Armstrong G. (2011). Principles of Marketing. Upper Saddle River NJ: Prentice Hall Inc.

  • Kotler P. & Keller K.L. (2009). Marketing Management. Upper Saddle River NJ: Prentice Hall Inc.

  • Larkin B. (2015). An examination of fantasy sport participation motives and substitution versus attendance intention. Sport Marketing Quarterly 24(2) 120-133.

  • Mucuk İ. (2001). Pazarlama ilkeleri [Marketing Principles]. Istanbul: Turkmen Publishing.

  • Nakip M. (2006). Pazarlama arastirmalari teknikler ve uygulamalar [Marketing Research Techniques and Applications]. Ankara: Seckin Publications.

  • Pitts B.G. Fielding L.W. & Miller L.K. (1994). Industry segmentation theory and the sport industry: Developing a sport industry segment model. Sport Marketing Quarterly 3(1) 15-24.

  • Punj G. & Stewart D.W. (1983). Cluster analysis in marketing research: Review and suggestions for application. J. Marketing Res. 134-148. DOI: 10.2307/3151680.

  • Rohm A.J. Milne G.R. & McDonald M.A. (2006). A mixed-method approach for developing market segmentation typologies in the sports industry. Sport Marketing Quarterly 15(1) 29-39.

  • Ruihley B.J. (2010). The fantasy sport experience: Motivations satisfaction and future intentions. Unpublished doctoral dissertation Tennessee University Knoxville TN.

  • Shipman F.M. (2001). Blending the real and virtual: Activity and spectatorship in fantasy sports. Digital Arts and Culture 2001 Conference 26-28 April 2001 (pp. 1-9). Providence RI: Brown University.

  • Sport Business Group. (2013). The global sports media consumption report 2013. Retrieved November 30 2017 from

  • Tabachnick B.G. & Fidell L.S. (2012). Using Multivariate Statistics. Boston MA: Pearson.

  • Trail G.T. Fink J.S. & Anderson D.F. (2003). Sport spectator consumption behavior. Sport Marketing Quarterly 72(1) 8-17.

  • Tseng F.C. (2011). Segmenting online gamers by motivation. Expert Syst. Appl. 38(6) 7693-7697. DOI: 10.1016/j.eswa.2010.12.142.

  • Zeithaml V.A. Berry L.L. & Parasuraman A. (1996). The behavioral consequences of service quality. J. Marketing 60(2) 31-46. DOI: 10.2307/1251929.

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