IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v60y2014i6p1489-1510.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2013.1856
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2013.1856?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Kristian S. Palda, 1964. "The Measurement of Cumulative Advertising Effects," The Journal of Business, University of Chicago Press, vol. 38, pages 162-162.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Moshe Givon & Dan Horsky, 1990. "Untangling the Effects of Purchase Reinforcement and Advertising Carryover," Marketing Science, INFORMS, vol. 9(2), pages 171-187.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lee, Ju-Yeon & Sridhar, Shrihari & Palmatier, Robert W., 2017. "The effect of firms' structural designs on advertising and personal selling returns," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 173-193.
    2. Melvin Woodley, 2021. "Decoupling the individual effects of multiple marketing channels with state space models," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 248-255, June.
    3. Jingnan Chen & Miguel A. Fonseca & Anthony Heyes & Jie Yang & Xiaohui Zhang, 2023. "How Much Will Climate Change Reduce Productivity in a High-Technology Supply Chain? Evidence from Silicon Wafer Manufacturing," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 86(3), pages 533-563, November.
    4. Steffen Q. Mueller, 2020. "Pre- and within-season attendance forecasting in Major League Baseball: a random forest approach," Applied Economics, Taylor & Francis Journals, vol. 52(41), pages 4512-4528, September.
    5. Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
    6. Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.
    7. Li, Yang & Liu, Feng, 2021. "Joint inventory and pricing control with lagged price responses," International Journal of Production Economics, Elsevier, vol. 241(C).
    8. Guitart, Ivan A. & Hervet, Guillaume, 2017. "The impact of contextual television ads on online conversions: An application in the insurance industry," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 480-498.
    9. Arindam Banerjee & Tanushri Banerjee, 2017. "Determinants of Analytics Process Adoption in Emerging Economies: Perspectives from the Marketing Domain in India," Vikalpa: The Journal for Decision Makers, , vol. 42(2), pages 95-110, June.
    10. Hervet, Guillaume & Guitart, Ivan A., 2022. "Increasing the effectiveness of display social media ads for startups: The role of different claims and executional characteristics," Journal of Business Research, Elsevier, vol. 153(C), pages 467-478.
    11. Scott D. Grimshaw & Jeffrey S. Larson, 2021. "Effect of Star Power on NBA All-Star Game TV Audience," Journal of Sports Economics, , vol. 22(2), pages 139-163, February.
    12. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
    2. Li, Yang & Liu, Feng, 2021. "Joint inventory and pricing control with lagged price responses," International Journal of Production Economics, Elsevier, vol. 241(C).
    3. Philip Hans Franses, 2021. "Marketing response and temporal aggregation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 111-117, June.
    4. Gunther Bensch & Jörg Peters, 2013. "Alleviating Deforestation Pressures? Impacts of Improved Stove Dissemination on Charcoal Consumption in Urban Senegal," Land Economics, University of Wisconsin Press, vol. 89(4), pages 676-698.
    5. Wagstaff, Adam & Yu, Shengchao, 2007. "Do health sector reforms have their intended impacts?: The World Bank's Health VIII project in Gansu province, China," Journal of Health Economics, Elsevier, vol. 26(3), pages 505-535, May.
    6. Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.
    7. Grant Allan & Graeme Roy, 2008. "Does Television Crowd Out Spectators?," Journal of Sports Economics, , vol. 9(6), pages 592-605, December.
    8. Black, Dan A. & Joo, Joonhwi & LaLonde, Robert J. & Smith, Jeffrey A. & Taylor, Evan J., 2015. "Simple Tests for Selection Bias: Learning More from Instrumental Variables," IZA Discussion Papers 9346, Institute of Labor Economics (IZA).
    9. Pohlmeier, Winfried & Seiberlich, Ruben & Uysal, Selver Derya, 2016. "A simple and successful shrinkage method for weighting estimators of treatment effects," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 512-525.
    10. Black, Dan A. & Joo, Joonhwi & LaLonde, Robert & Smith, Jeffrey A. & Taylor, Evan J., 2022. "Simple Tests for Selection: Learning More from Instrumental Variables," Labour Economics, Elsevier, vol. 79(C).
    11. Jeffery Borland, 2003. "Demand for Sport," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 19(4), pages 478-502, Winter.
    12. Breuer, Ralph & Brettel, Malte, 2012. "Short- and Long-term Effects of Online Advertising: Differences between New and Existing Customers," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 155-166.
    13. Alexander John Bond & Francesco Addesa, 2020. "Competitive Intensity, Fans’ Expectations, and Match-Day Tickets Sold in the Italian Football Serie A, 2012-2015," Journal of Sports Economics, , vol. 21(1), pages 20-43, January.
    14. Adam Cox, 2018. "Spectator Demand, Uncertainty of Results, and Public Interest," Journal of Sports Economics, , vol. 19(1), pages 3-30, January.
    15. Catherine C. Gropper & Benjamin C. Anderson, 2018. "Sellout, Blackout, or Get Out," Journal of Sports Economics, , vol. 19(3), pages 332-370, April.
    16. Hojun Sung & Brian M. Mills, 2018. "Estimation of game-level attendance in major league soccer: Outcome uncertainty and absolute quality considerations," Sport Management Review, Taylor & Francis Journals, vol. 21(5), pages 519-532, December.
    17. Michel Clement & Björn Christensen & Sönke Albers & Steffen Guldner, 2007. "Was bringt ein Oscar im Filmgeschäft? Eine empirische Analyse unter Berücksichtigung des Selektionseffekts," Schmalenbach Journal of Business Research, Springer, vol. 59(2), pages 198-220, March.
    18. Budzinski, Oliver & Feddersen, Arne, 2015. "Grundlagen der Sportnachfrage: Theorie und Empirie der Einflussfaktoren auf die Zuschauernachfrage," Ilmenau Economics Discussion Papers 94, Ilmenau University of Technology, Institute of Economics.
    19. Dominik Schreyer, 2019. "Football spectator no-show behaviour in the German Bundesliga," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4882-4901, September.
    20. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:60:y:2014:i:6:p:1489-1510. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.