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Rise and fall of stars: Investigating the evolution of star status in professional team sports

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  • Yang, Yupin
  • Shi, Mengze

Abstract

This article describes an empirical study of the rise and fall of star athletes, using data from the National Basketball Association (NBA) from 1987 to 2008. We measure star status by the number and share of all-star votes, and we apply both Tobit regression and hazard models to investigate the determining factors for star status. We find that the attainment of star status begins with the athlete's exceptional individual performance. We also find that having won a championship in the past can have a long-lasting effect on a player's popularity. The popularity of an athlete depends on his team in two ways: the attainment of star status is associated with strong team performance, and star teammates can reinforce each other's popularity. Interestingly, whereas stars can move from a losing team to a winning team to extend their star life, a team change can be very risky for new stars. Our results also suggest that teams with a large fan base, winning records, and star players should leverage these assets in attracting and retaining star players.

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  • Yang, Yupin & Shi, Mengze, 2011. "Rise and fall of stars: Investigating the evolution of star status in professional team sports," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 352-366.
    • Handle: RePEc:eee:ijrema:v:28:y:2011:i:4:p:352-366
    DOI: 10.1016/j.ijresmar.2011.05.004
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    1. Meyer, Bruce D, 1990. "Unemployment Insurance and Unemployment Spells," Econometrica, Econometric Society, vol. 58(4), pages 757-782, July.
    2. Dipak C. Jain & Naufel J. Vilcassim, 1991. "Investigating Household Purchase Timing Decisions: A Conditional Hazard Function Approach," Marketing Science, INFORMS, vol. 10(1), pages 1-23.
    3. Pradeep K. Chintagunta, 1998. "Inertia and Variety Seeking in a Model of Brand-Purchase Timing," Marketing Science, INFORMS, vol. 17(3), pages 253-270.
    4. Venkatesh Shankar & Pablo Azar & Matthew Fuller, 2008. "—: A Multicategory Brand Equity Model and Its Application at Allstate," Marketing Science, INFORMS, vol. 27(4), pages 567-584, 07-08.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. Peter N. Golder & Gerard J. Tellis, 1997. "Will It Every Fly? Modeling the Takeoff of Really New Consumer Durables," Marketing Science, INFORMS, vol. 16(3), pages 256-270.
    7. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
    8. Kristiaan Helsen & David C. Schmittlein, 1993. "Analyzing Duration Times in Marketing: Evidence for the Effectiveness of Hazard Rate Models," Marketing Science, INFORMS, vol. 12(4), pages 395-414.
    9. R. Venkatesh & Vijay Mahajan, 1997. "Products with Branded Components: An Approach for Premium Pricing and Partner Selection," Marketing Science, INFORMS, vol. 16(2), pages 146-165.
    10. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    11. Peter N. Golder & Gerard J. Tellis, 2004. "Growing, Growing, Gone: Cascades, Diffusion, and Turning Points in the Product Life Cycle," Marketing Science, INFORMS, vol. 23(2), pages 207-218, December.
    12. Rosen, Sherwin, 1981. "The Economics of Superstars," American Economic Review, American Economic Association, vol. 71(5), pages 845-858, December.
    13. Vanhuele, Marc & Dekimpe, Marnik G. & Sharma, Sunil & Morrison, Donald G., 1995. "Probability Models for Duration: The Data Don't Tell the Whole Story," Organizational Behavior and Human Decision Processes, Elsevier, vol. 62(1), pages 1-13, April.
    14. Yupin Yang & Mengze Shi & Avi Goldfarb, 2009. "Estimating the Value of Brand Alliances in Professional Team Sports," Marketing Science, INFORMS, vol. 28(6), pages 1095-1111, 11-12.
    15. Hausman, Jerry A & Leonard, Gregory K, 1997. "Superstars in the National Basketball Association: Economic Value and Policy," Journal of Labor Economics, University of Chicago Press, vol. 15(4), pages 586-624, October.
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    Cited by:

    1. Scott M. Kaplan, 2022. "Putting a price on popularity: Evidence from superstars in the National Basketball Association," Economic Inquiry, Western Economic Association International, vol. 60(3), pages 1357-1381, July.
    2. Eelco Kappe & Ashley Stadler Blank & Wayne S. DeSarbo, 2014. "A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions," Management Science, INFORMS, vol. 60(6), pages 1489-1510, June.
    3. Hofmann, Julian & Schnittka, Oliver & Johnen, Marius & Kottemann, Pascal, 2021. "Talent or popularity: What drives market value and brand image for human brands?," Journal of Business Research, Elsevier, vol. 124(C), pages 748-758.
    4. Foutz, Natasha Zhang, 2017. "Entertainment Marketing," Foundations and Trends(R) in Marketing, now publishers, vol. 10(4), pages 215-333, October.
    5. Daniel H. Weinberg, 2016. "Talent Recruitment and Firm Performance," Journal of Sports Economics, , vol. 17(8), pages 832-862, December.

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