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The Lead-Lag Puzzle of Demand and Distribution: A Graphical Method Applied to Movies

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  • Robert E. Krider

    (Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6 Canada)

  • Tieshan Li

    (Sauder School of Business, University of British Columbia, Vancouver, BC V6T 1Z2 Canada)

  • Yong Liu

    (Whitman School of Management, Syracuse University, Syracuse, New York 13244)

  • Charles B. Weinberg

    (Sauder School of Business, University of British Columbia, Vancouver, BC V6T 1Z2 Canada)

Abstract

Understanding the lead-lag relationship between distribution and demand is an important and challenging issue for all marketers. It is particularly challenging in the movie industry, where the very short lifespan and decaying revenue and exhibition patterns of motion pictures means that the associated time series are short and nonstationary, rendering existing econometric methods unreliable. We propose an alternate method that uses state-space diagrams to determine lead-lag relationships. Straightforward to apply and interpret, it takes advantage of the eye’s ability to see patterns that algebra-based formulations cannot easily recognize. A number of validation tests are provided to illustrate the usefulness and limitations of the method. We study the weekly data for 231 major movies released in 2000–2001. While econometric methods do not provide consistent results, the graphical method of visually inferred causality clearly shows a pattern that demand leads distribution for most movies. In other words, the dominant industry pattern is one of movie exhibitors monitoring box office sales and then responding with screen allocation decisions. The managerial implications of these findings are discussed.

Suggested Citation

  • Robert E. Krider & Tieshan Li & Yong Liu & Charles B. Weinberg, 2005. "The Lead-Lag Puzzle of Demand and Distribution: A Graphical Method Applied to Movies," Marketing Science, INFORMS, vol. 24(4), pages 635-645, April.
    • Handle: RePEc:inm:ormksc:v:24:y:2005:i:4:p:635-645
    DOI: 10.1287/mksc.1050.0149
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    1. Sha Yang & Vishal Narayan & Henry Assael, 2006. "Estimating the Interdependence of Television Program Viewership Between Spouses: A Bayesian Simultaneous Equation Model," Marketing Science, INFORMS, vol. 25(4), pages 336-349, July.
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    3. Robert Krider & Tieshan Li & Yong Liu & Charles Weinberg, 2008. "Demand and distribution relationships in the ready-to-drink iced tea market: A graphical approach," Marketing Letters, Springer, vol. 19(1), pages 1-12, March.
    4. Divakaran, Pradeep Kumar Ponnamma & Palmer, Adrian & Søndergaard, Helle Alsted & Matkovskyy, Roman, 2017. "Pre-launch Prediction of Market Performance for Short Lifecycle Products Using Online Community Data," Journal of Interactive Marketing, Elsevier, vol. 38(C), pages 12-28.
    5. Clement, Michel & Wu, Steven & Fischer, Marc, 2014. "Empirical generalizations of demand and supply dynamics for movies," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 207-223.
    6. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    7. I. Robert Chiang & Jhih‐Hua Jhang‐Li, 2020. "Competition through Exclusivity in Digital Content Distribution," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1270-1286, May.
    8. Xinlei Chen & Yuxin Chen & Charles Weinberg, 2013. "Learning about movies: the impact of movie release types on the nationwide box office," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(3), pages 359-386, August.
    9. Steven M. Shugan, 2006. "—Antibusiness Movies and Folk Marketing," Marketing Science, INFORMS, vol. 25(6), pages 681-685, 11-12.
    10. Amit M. Joshi & Dominique M. Hanssens, 2009. "Movie Advertising and the Stock Market Valuation of Studios: A Case of “Great Expectations?”," Marketing Science, INFORMS, vol. 28(2), pages 239-250, 03-04.
    11. Harald Van Heerde & Kristiaan Helsen & Marnik G. Dekimpe, 2007. "The Impact of a Product-Harm Crisis on Marketing Effectiveness," Marketing Science, INFORMS, vol. 26(2), pages 230-245, 03-04.
    12. Robert E. Krider, 2006. "—Research Opportunities at the Movies," Marketing Science, INFORMS, vol. 25(6), pages 662-664, 11-12.
    13. Fernanda Gutierrez-Navratil & Victor Fernandez-Blanco & Luis Orea & Juan Prieto-Rodriguez, 2014. "How do your rivals’ releasing dates affect your box office?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 38(1), pages 71-84, February.
    14. Koen Pauwels & Shuba Srinivasan & Philip Hans Franses, 2007. "When Do Price Thresholds Matter in Retail Categories?," Marketing Science, INFORMS, vol. 26(1), pages 83-100, 01-02.
    15. Dinesh Ramdas Pai & Siddharth Bhatt, 2023. "Is suggestive selling effective in increasing sales? Investigating its role in store promotion strategy using retail chain data from the U.S," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(1), pages 32-40, March.
    16. Jordi McKenzie, 2009. "Revealed word-of-mouth demand and adaptive supply: survival of motion pictures at the Australian box office," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(4), pages 279-299, November.
    17. Angela Liu & Yong Liu & Tridib Mazumdar, 2014. "Star power in the eye of the beholder: A study of the influence of stars in the movie industry," Marketing Letters, Springer, vol. 25(4), pages 385-396, December.
    18. Steven M. Shugan, 2007. "—Causality, Unintended Consequences and Deducing Shared Causes," Marketing Science, INFORMS, vol. 26(6), pages 731-741, 11-12.
    19. Charles B. Weinberg, 2006. "—Research and the Motion Picture Industry," Marketing Science, INFORMS, vol. 25(6), pages 667-669, 11-12.
    20. Ataman, B.M., 2007. "Managing brands," Other publications TiSEM 462dcbba-2ac1-46d1-a61c-f, Tilburg University, School of Economics and Management.
    21. Chakravarty, Anindita & Liu, Yong & Mazumdar, Tridib, 2010. "The Differential Effects of Online Word-of-Mouth and Critics' Reviews on Pre-release Movie Evaluation," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 185-197.
    22. Antonis A. Michis, 2023. "Retail distribution evaluation in brand-level sales response models," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 366-378, September.
    23. Anthony Koschmann & Yi Qian, 2020. "Latent Estimation of Piracy Quality and its Effect on Revenues and Distribution: The Case of Motion Pictures," NBER Working Papers 27649, National Bureau of Economic Research, Inc.
    24. Steven M. Shugan, 2006. "Editorial: Save Research—Abandon the Case Method of Teaching," Marketing Science, INFORMS, vol. 25(2), pages 109-115, 03-04.
    25. Tirtha Dhar & Guanghui Sun & Charles Weinberg, 2012. "The long-term box office performance of sequel movies," Marketing Letters, Springer, vol. 23(1), pages 13-29, March.

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