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A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions

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  • Eelco Kappe

    (Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Ashley Stadler Blank

    (Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Wayne S. DeSarbo

    (Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

Abstract

Game attendance resulting from ticket sales is the single largest revenue stream for Major League Baseball (MLB) teams. We propose a general multiple distributed lag framework following the Koyck family of models for estimating MLB attendance drivers and focus specifically on the differential direct and carryover effects of in-game promotions. By setting various model constraints, the proposed framework incorporates different forms of serial correlation and promotion-specific dynamic effects. Using information model-selection heuristics, we select an optimal model of attendance drivers for the Pittsburgh Pirates' 2010--2012 MLB seasons. We demonstrate that our newly proposed model with an unrestricted serial correlation structure performs best. We find that although kids promotions have the highest direct effect on attendance, giveaway and entertainment promotions have substantial carryover effects and the largest total effects. We use our results to optimize the Pirates' promotional schedule and find that a reallocation of resources across promotional categories can increase profits between 39% and 88%.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1856 . This paper was accepted by Eric Bradlow, special issue on business analytics .

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ormnsc:v:60:y:2014:i:6:p:1489-1510
    DOI: 10.1287/mnsc.2013.1856
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    as
    1. Peles, Yoram, 1971. "Rates of Amortization of Advertising Expenditures," Journal of Political Economy, University of Chicago Press, vol. 79(5), pages 1032-1058, Sept.-Oct.
    2. Baimbridge, Mark & Cameron, Samuel & Dawson, Peter, 1996. "Satellite Television and the Demand for Football: A Whole New Ball Game?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 43(3), pages 317-333, August.
    3. Carter Richard A. L. & Zellner Arnold, 2004. "The ARAR Error Model for Univariate Time Series and Distributed Lag," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(1), pages 1-44, March.
    4. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    5. MacKinnon, James G. & White, Halbert & Davidson, Russell, 1983. "Tests for model specification in the presence of alternative hypotheses : Some further results," Journal of Econometrics, Elsevier, vol. 21(1), pages 53-70, January.
    6. Zellner, Arnold & Geisel, Martin S, 1970. "Analysis of Distributed Lag Models with Application to Consumption Function Estimation," Econometrica, Econometric Society, vol. 38(6), pages 865-888, November.
    7. Winer, Russell S, 1979. "An Analysis of the Time-varying Effects of Advertising: The Case of Lydia Pinkham," The Journal of Business, University of Chicago Press, vol. 52(4), pages 563-576, October.
    8. Stephen Allan, 2004. "Satellite television and football attendance: the not so super effect," Applied Economics Letters, Taylor & Francis Journals, vol. 11(2), pages 123-125.
    9. Moshe Givon & Dan Horsky, 1990. "Untangling the Effects of Purchase Reinforcement and Advertising Carryover," Marketing Science, INFORMS, vol. 9(2), pages 171-187.
    10. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2005. "Evaluating the effect of education on earnings: models, methods and results from the National Child Development Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 473-512, July.
    11. Lorna Gifis & Paul Sommers, 2006. "Promotions and Attendance in Minor League Baseball," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 34(4), pages 513-514, December.
    12. Gerard J. Tellis & Philip Hans Franses, 2006. "Optimal Data Interval for Estimating Advertising Response," Marketing Science, INFORMS, vol. 25(3), pages 217-229, 05-06.
    13. Andrew Welki & Thomas Zlatoper, 1999. "U.S. professional football game-day attendance," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 27(3), pages 285-298, September.
    14. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2004. "Role of Forgetting in Memory-Based Choice Decisions: A Structural Model," Quantitative Marketing and Economics (QME), Springer, vol. 2(2), pages 107-140, June.
    15. Herrington, J. Duncan & Dempsey, William A., 2005. "Comparing the Current Effects and Carryover of National-, Regional-, and Local-Sponsor Advertising," Journal of Advertising Research, Cambridge University Press, vol. 45(1), pages 60-72, March.
    16. Nerlove, Marc, 1958. "Distributed Lags and Demand Analysis for Agricultural and Other Commodities," Technical Resources 316559, United States Department of Agriculture, Agricultural Marketing Service, Transportation and Marketing Program.
    17. Antonio G. Chessa & Jaap M. J. Murre, 2007. "A Neurocognitive Model of Advertisement Content and Brand Name Recall," Marketing Science, INFORMS, vol. 26(1), pages 130-141, 01-02.
    18. 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.
    19. J. Myles Shaver, 1998. "Accounting for Endogeneity When Assessing Strategy Performance: Does Entry Mode Choice Affect FDI Survival?," Management Science, INFORMS, vol. 44(4), pages 571-585, April.
    20. Kristian S. Palda, 1964. "The Measurement of Cumulative Advertising Effects," The Journal of Business, University of Chicago Press, vol. 38, pages 162-162.
    21. Robert J. Lemke & Matthew Leonard & Kelebogile Tlhokwane, 2010. "Estimating Attendance at Major League Baseball Games for the 2007 Season," Journal of Sports Economics, , vol. 11(3), pages 316-348, June.
    22. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    23. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    24. Elise M. Beckman & Wenqiang Cai & Rebecca M. Esrock & Robert J. Lemke, 2012. "Explaining Game-to-Game Ticket Sales for Major League Baseball Games Over Time," Journal of Sports Economics, , vol. 13(5), pages 536-553, October.
    25. Wesley Hartmann, 2006. "Intertemporal effects of consumption and their implications for demand elasticity estimates," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 325-349, December.
    26. McDonald, Mark & Rascher, Daniel, 2000. "Does Bat Day Make Cents? The Effect of Promotions on the Demand for Major League Baseball," MPRA Paper 25739, University Library of Munich, Germany.
    27. Thomas C. Boyd & Timothy C. Krehbiel, 2006. "An Analysis of the Effects of Specific Promotion Types on Attendance at Major League Baseball Games," American Journal of Business, Emerald Group Publishing, vol. 21(2), pages 21-32.
    28. Roland T. Rust & Duncan Simester & Roderick J. Brodie & V. Nilikant, 1995. "Model Selection Criteria: An Investigation of Relative Accuracy, Posterior Probabilities, and Combinations of Criteria," Management Science, INFORMS, vol. 41(2), pages 322-333, February.
    29. Ralph Breuer & Malte Brettel & Andreas Engelen, 2011. "Incorporating long-term effects in determining the effectiveness of different types of online advertising," Marketing Letters, Springer, vol. 22(4), pages 327-340, November.
    30. 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.
    31. David B. Montgomery & Alvin J. Silk, 1972. "Estimating Dynamic Effects of Market Communications Expenditures," Management Science, INFORMS, vol. 18(10), pages 485-501, June.
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