IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v24y2005i4p635-645.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1050.0149
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1050.0149?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. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    2. Thornton, Daniel L & Batten, Dallas S, 1985. "Lag-Length Selection and Tests of Granger Causality between Money and Income," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 17(2), pages 164-178, May.
    3. 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.
    4. Ramya Neelamegham & Pradeep Chintagunta, 1999. "A Bayesian Model to Forecast New Product Performance in Domestic and International Markets," Marketing Science, INFORMS, vol. 18(2), pages 115-136.
    5. Judith A. Chevalier & Dina Mayzlin, 2003. "The Effect of Word of Mouth on Sales: Online Book Reviews," NBER Working Papers 10148, National Bureau of Economic Research, Inc.
    6. Vincent R. Nijs & Marnik G. Dekimpe & Jan-Benedict E.M. Steenkamps & Dominique M. Hanssens, 2001. "The Category-Demand Effects of Price Promotions," Marketing Science, INFORMS, vol. 20(1), pages 1-22, September.
    7. Shuba Srinivasan & Koen Pauwels & Dominique M. Hanssens & Marnik G. Dekimpe, 2004. "Do Promotions Benefit Manufacturers, Retailers, or Both?," Management Science, INFORMS, vol. 50(5), pages 617-629, May.
    8. Hsiao, Cheng, 1982. "Autoregressive modeling and causal ordering of economic variables," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 243-259, November.
    9. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    10. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    11. Jehoshua Eliashberg & Sanjeev Swami & Charles B. Weinberg & Berend Wierenga, 2001. "Implementing and Evaluating SilverScreener: A Marketing Management Support System for Movie Exhibitors," Interfaces, INFORMS, vol. 31(3_supplem), pages 108-127, June.
    12. Peter S. Fader & Bruce G. S. Hardie & Chun-Yao Huang, 2004. "A Dynamic Changepoint Model for New Product Sales Forecasting," Marketing Science, INFORMS, vol. 23(1), pages 50-65, October.
    13. van den Bulte, C. & Stremersch, S., 2003. "Contagion and heterogeneity in new product diffusion: An emperical test," ERIM Report Series Research in Management ERS-2003-077-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
    15. Prasad A. Naik & Kalyan Raman & Russell S. Winer, 2005. "Planning Marketing-Mix Strategies in the Presence of Interaction Effects," Marketing Science, INFORMS, vol. 24(1), pages 25-34, June.
    16. Leonard M. Lodish & Magid M. Abraham & Jeanne Livelsberger & Beth Lubetkin & Bruce Richardson & Mary Ellen Stevens, 1995. "A Summary of Fifty-Five In-Market Experimental Estimates of the Long-Term Effect of TV Advertising," Marketing Science, INFORMS, vol. 14(3_supplem), pages 133-140.
    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. 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.
    2. 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.
    3. 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.
    4. Sumit Raut & Sanjeev Swami & Eunkyu Lee & Charles B. Weinberg, 2008. "How Complex Do Movie Channel Contracts Need to Be?," Marketing Science, INFORMS, vol. 27(4), pages 627-641, 07-08.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Steven M. Shugan, 2007. "—Causality, Unintended Consequences and Deducing Shared Causes," Marketing Science, INFORMS, vol. 26(6), pages 731-741, 11-12.
    11. Charles B. Weinberg, 2006. "—Research and the Motion Picture Industry," Marketing Science, INFORMS, vol. 25(6), pages 667-669, 11-12.
    12. Ataman, B.M., 2007. "Managing brands," Other publications TiSEM 462dcbba-2ac1-46d1-a61c-f, Tilburg University, School of Economics and Management.
    13. 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.
    14. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    15. 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.
    16. 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.
    17. Steven M. Shugan, 2006. "—Antibusiness Movies and Folk Marketing," Marketing Science, INFORMS, vol. 25(6), pages 681-685, 11-12.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Steven M. Shugan, 2006. "Editorial: Save Research—Abandon the Case Method of Teaching," Marketing Science, INFORMS, vol. 25(2), pages 109-115, 03-04.
    24. Robert E. Krider, 2006. "—Research Opportunities at the Movies," Marketing Science, INFORMS, vol. 25(6), pages 662-664, 11-12.
    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.

    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. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    2. Jehoshua Eliashberg & Anita Elberse & Mark A.A.M. Leenders, 2006. "The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions," Marketing Science, INFORMS, vol. 25(6), pages 638-661, 11-12.
    3. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    4. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
    5. Katherine Goff Inglis & Saeed Zolfaghari, 2017. "A Review of Scheduling Problems and Research Opportunities in Motion Picture Exhibition," Interfaces, INFORMS, vol. 47(2), pages 175-187, April.
    6. C F Elliott & R Simmons, 2007. "Determinants of UK box office success: the impact of quality signals," Working Papers 584026, Lancaster University Management School, Economics Department.
    7. Deepa Chandrasekaran & Gerard J. Tellis, 2008. "Global Takeoff of New Products: Culture, Wealth, or Vanishing Differences?," Marketing Science, INFORMS, vol. 27(5), pages 844-860, 09-10.
    8. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    9. repec:lan:wpaper:1090 is not listed on IDEAS
    10. Koen Pauwels & Dominique M. Hanssens, 2007. "Performance Regimes and Marketing Policy Shifts," Marketing Science, INFORMS, vol. 26(3), pages 293-311, 05-06.
    11. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    12. Vincent R. Nijs & Shuba Srinivasan & Koen Pauwels, 2007. "Retail-Price Drivers and Retailer Profits," Marketing Science, INFORMS, vol. 26(4), pages 473-487, 07-08.
    13. 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.
    14. Bogomolova, Svetlana & Szabo, Marietta & Kennedy, Rachel, 2017. "Retailers' and manufacturers' price-promotion decisions: Intuitive or evidence-based?," Journal of Business Research, Elsevier, vol. 76(C), pages 189-200.
    15. Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.
    16. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    17. Kim, Taegu & Hong, Jungsik & Kang, Pilsung, 2015. "Box office forecasting using machine learning algorithms based on SNS data," International Journal of Forecasting, Elsevier, vol. 31(2), pages 364-390.
    18. Ailawadi, Kusum L. & Beauchamp, J.P. & Donthu, Naveen & Gauri, Dinesh K. & Shankar, Venkatesh, 2009. "Communication and Promotion Decisions in Retailing: A Review and Directions for Future Research," Journal of Retailing, Elsevier, vol. 85(1), pages 42-55.
    19. van Everdingen, Y.M. & Fok, D. & Stremersch, S., 2008. "Modeling Global Spill-Over of New Product Takeoff," ERIM Report Series Research in Management ERS-2008-067-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    21. repec:lan:wpaper:1176 is not listed on IDEAS
    22. Delre, S.A. & Jager, W. & Bijmolt, T.H.A. & Janssen, M.A., 2007. "Targeting and timing promotional activities: An agent-based model for the takeoff of new products," Journal of Business Research, Elsevier, vol. 60(8), pages 826-835, August.

    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:ormksc:v:24:y:2005:i:4:p:635-645. 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.