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Brand Equity, Efficiency and Valuation of Professional Sports Franchises: The Case of Major League Baseball

Author

Listed:
  • Srinivas K. Reddy

    (Professor of Marketing, Singapore Management University,)

  • Antonie Stam

    (Leggett & Platt Distinguished Professor of Information Systems, University of Missouri-Columbia)

  • Per J. Agrell

    (Associate Professor, CORE, Louvain-la-Neuve, Belgium.)

Abstract

Values of professional sports franchises have outpaced even investment returns in recent bull markets. Financial World found the value of professional teams like the Dallas Cowboys, Miami Dolphins and the NY Yankees to exceed $200 million each. In 1996, the average estimated value of Major League Baseball (MLB) teams was $134 million, and most showed double-digit growth in value, although 13 of the 26 teams were in the red. Our research proposes a model to determine the value of a professional sports franchise, by treating the franchise as a brand whose value is enhanced by its key attributes. This approach is appropriate because each franchise represents a single brand firm. Our model takes into account equity enhancing factors like the franchise longevity, historical performance, the number of marquee/award-winning roster players, and market factors such as market size, competition and franchise efficiency. We determine the extent to which a franchise is managed efficiently with respect to inputs like investments in players (player costs) and outputs such as franchise revenue and team performance (win-loss ratio). Using data from 1990-1995 to illustrate our model, we are able to determine (1) the brand equity of MLB franchises, (2) how efficiently each team is managed, and (3) the contribution of marketing factors like brand equity, market size, competition, as well as efficiency, to franchise value. While this paper focuses on MBL, the methodology can easily be extended to other professional sports.

Suggested Citation

  • Srinivas K. Reddy & Antonie Stam & Per J. Agrell, 2015. "Brand Equity, Efficiency and Valuation of Professional Sports Franchises: The Case of Major League Baseball," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 5(1), pages 63-89, January.
    • Handle: RePEc:mir:mirbus:v:5:y:2015:i:1:p:63-89
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    References listed on IDEAS

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    1. Michael R. Butler, 1995. "Competitive Balance in Major League Baseball," The American Economist, Sage Publications, vol. 39(2), pages 46-52, October.
    2. Ali, Agha Iqbal & Lerme, Catherine S. & Seiford, Lawrence M., 1995. "Components of efficiency evaluation in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 80(3), pages 462-473, February.
    3. Dan Horsky & Paul Nelson, 1996. "Evaluation of Salesforce Size and Productivity Through Efficient Frontier Benchmarking," Marketing Science, INFORMS, vol. 15(4), pages 301-320.
    4. Lawrence M. Kahn, 1993. "Managerial Quality, Team Success, and Individual Player Performance in Major League Baseball," ILR Review, Cornell University, ILR School, vol. 46(3), pages 531-547, April.
    5. Glenn Knowles & Keith Sherony & Mike Haupert, 1995. "Baseball Attendance and Outcome Uncertainty: Reply," The American Economist, Sage Publications, vol. 39(2), pages 88-89, October.
    6. Telser, L G, 1995. "The Ultimatum Game and the Law of Demand," Economic Journal, Royal Economic Society, vol. 105(433), pages 1519-1523, November.
    7. John M. Murphy, 1992. "Assessing the Value of Brands," Palgrave Macmillan Books, in: John M. Murphy (ed.), Branding: A Key Marketing Tool, edition 0, chapter 19, pages 184-197, Palgrave Macmillan.
    8. Maindiratta, Ajay, 1990. "Largest size-efficient scale and size efficiencies of decision-making units in data envelopment analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 57-72.
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Keller, Kevin Lane, 2003. "Brand Synthesis: The Multidimensionality of Brand Knowledge," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 29(4), pages 595-600, March.
    11. Whitney, James D, 1988. "Winning Games versus Winning Championships: The Economics of Fan Interest and Team Performance," Economic Inquiry, Western Economic Association International, vol. 26(4), pages 703-724, October.
    12. Charles E. Zech, 1981. "An Empirical Estimation of a Production Function: The Case of Major League Baseball," The American Economist, Sage Publications, vol. 25(2), pages 19-23, October.
    13. Thomas H. Bruggink, 1993. "National Pastime to Dismal Science: Using Baseball to Illustrate Economic Principles," Eastern Economic Journal, Eastern Economic Association, vol. 19(3), pages 275-294, Summer.
    14. Clement, Robert C & McCormick, Robert E, 1989. "Coaching Team Production," Economic Inquiry, Western Economic Association International, vol. 27(2), pages 287-304, April.
    15. Glenn Knowles & Keith Sherony & Mike Haupert, 1992. "The Demand for Major League Baseball: A Test of the Uncertainty of Outcome Hypothesis," The American Economist, Sage Publications, vol. 36(2), pages 72-80, October.
    16. Gramlich, Edward M., 1994. "A natural experiment in styles of capitalism: Professional sports," The Quarterly Review of Economics and Finance, Elsevier, vol. 34(2), pages 121-130.
    17. Bruce Bukiet & Elliotte Rusty Harold & José Luis Palacios, 1997. "A Markov Chain Approach to Baseball," Operations Research, INFORMS, vol. 45(1), pages 14-23, February.
    18. Paul M. Sommers & Noel Quinton, 1982. "Pay and Performance in Major League Baseball: The Case of the First Family of Free Agents," Journal of Human Resources, University of Wisconsin Press, vol. 17(3), pages 426-436.
    19. Ladd Kochman & Ravija Badarinathi, 1995. "Baseball Attendance and Outcome Uncertainty: A Note," The American Economist, Sage Publications, vol. 39(2), pages 87-87, October.
    20. Christopher Zappe & William Webster & Ira Horowitz, 1993. "Using Linear Programming to Determine Post-Facto Consistency in Performance Evaluations of Major League Baseball Players," Interfaces, INFORMS, vol. 23(6), pages 107-113, December.
    21. Doyle, JR & Green, RH, 1991. "Comparing products using data envelopment analysis," Omega, Elsevier, vol. 19(6), pages 631-638.
    22. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    23. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    24. Timothy Anderson & Gunter Sharp, 1997. "A new measure of baseball batters using DEA," Annals of Operations Research, Springer, vol. 73(0), pages 141-155, October.
    25. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    26. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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    More about this item

    Keywords

    Brand equity; data envelopment analysis; efficiency analysis; sports franchises.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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