The differing roles of success drivers across sequential channels: An application to the motion picture industry

  • Thorsten Hennig-Thurau
  • Mark B. Houston
  • Gianfranco Walsh


In several product categories, it is typical to release products sequentially to different markets and customer segments. Conventional knowledge holds that the roles of various product success drivers do not differ significantly across these sequential channels of distribution. The authors examine sequential distribution channels within the motion picture industry and develop a model that proposes that such differences exist between a primary (short- and long-term theatrical box office) and a sequential (video rental) channel. The authors test their model with a sample of 331 motion pictures released in theaters and on video during 1999–2001 using partial least squares. Results reveal differences in the impact of success factors across channels. For example, cultural familiarity enhances box office success but relates negatively to video rental success, and distribution intensity and date of release enhance box office outcomes but have no impact on rental revenues.


sequential distribution channels partial least squares motion picture success cognitive categorization information economics 


  1. ACNielsen. 2001. “New ACNielsen EDI Study Reveals Preferences of Movie-Goers.” Scholar
  2. Basuroy, Suman, Subimal Chatterjee, and S. Abraham Ravid. 2003. “How Critical Are Critical Reviews? The Box Office Effects of Film Critics, Star Power, and Budgets.”Journal of Marketing 67 (October): 103–117.CrossRefGoogle Scholar
  3. —, Kalpesh Kaushik Desai, and Debabrata Talukdar. 2006. “An Empirical Investigation of Signaling in the Motion Picture Industry.”Journal of Marketing Research 43 (May): 287–295.CrossRefGoogle Scholar
  4. Bettman, James R. 1973. “Perceived Risk and Its Components: A Model and Empirical Test.”Journal of Marketing Research 10 (May): 184–190.CrossRefGoogle Scholar
  5. 2005. “Yearly Box Office.” http://www.boxofficempjo .com/yearly.Google Scholar
  6. Campbell, Margaret C. and Ronald C. Goodstein. 2001. “The Moderating Effect of Perceived Risk on Consumers’ Evaluations of Product Incongruity: Preference for the Norm.”Journal of Consumer Research 28 (December): 439–449.CrossRefGoogle Scholar
  7. Childs, Richard B. 1992. “Home Video.” InThe Movie Business Book. Ed. Jason E. Squire. New York: Fireside, 328–338.Google Scholar
  8. Chin, Wynne W. 1998. “The Partial Least Square Approach to Structural Equations Modeling.” InModern Methods for Business Research. Ed. George A. Marcoulides. Mahwah, NJ: Lawrence Erlbaum, 295–336.Google Scholar
  9. Chin, Wynne W. 2000. “Frequently Asked Questions-Partial Least Squares & PLS-Graph. Home Page.” Scholar
  10. —. 2001.PLS-Graph User’s Guide Version 3.0. Houston, TX: Soft Modeling.Google Scholar
  11. Cohen, Joel B. and Kunal Basu. 1987. “Alternative Models of Categorization: Toward a Contingent Processing Framework.”Journal of Consumer Research 13 (March): 455–472.CrossRefGoogle Scholar
  12. Conchar, Margy P., Melvin R. Crask, and George M. Zinkhan. 2005. “Market Valuation Models of the Effect of Advertising and Promotional Spending: A Review and Meta-Analysis.”Journal of the Academy of Marketing Science 33 (Fall): 445–460.CrossRefGoogle Scholar
  13. —, George M. Zinkhan, Cara Peters, and Sergio Olavarrieta. 2004. “An Integrated Framework for the Conceptualization of Consumers’ Perceived-Risk Processing.”Journal of the Academy of Marketing Science 32 (Fall): 418–436.CrossRefGoogle Scholar
  14. Dana, James D., Jr. and Kathryn E. Spier. 2001. “Revenue Sharing and Vertical Control in the Video Rental Industry.”Journal of Industrial Economics 49 (September): 223–245.Google Scholar
  15. De Vany, Arthur and W. David Walls. 1999. “Uncertainty in the Movie Industry: Does Star Power Reduce the Terror of the Box Office?”Journal of Cultural Economics 23 (4): 285–318.CrossRefGoogle Scholar
  16. Diamantopoulos, Adamantios and Heidi M. Winklhofer. 2001. “Index Construction With Formative Indicators: An Alternative to Scale Development.”Journal of Marketing Research 38 (May): 269–277.CrossRefGoogle Scholar
  17. Donahue, Suzanne Mary. 1987.American Film Distribution: The Changing Marketplace. Ann Arbor: University of Michigan Research Press.Google Scholar
  18. Elberse, Anita and Jehoshua Eliashberg. 2003. “Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures.”Marketing Science 22 (Summer): 329–354.CrossRefGoogle Scholar
  19. Eliashberg, Jehoshua and Steven M. Shugan. 1997. “Film Critics: Influencers or Predictors?”Journal of Marketing 61 (April): 68–78.CrossRefGoogle Scholar
  20. Faber, Ronald J. and Thomas C. O’Guinn. 1984. “Effect of Media Advertising and Other Sources on Movie Selection.”Journalism Quarterly 61 (Summer): 317–377.Google Scholar
  21. Fornell, Claes and Fred L. Bookstein. 1982. “Two Structural Equations Models With Unobservable Variables and Measurement Error.”Journal of Marketing Research 18 (November): 39–50.Google Scholar
  22. —, and David L. Larcker. 1981. “Evaluating Structural Equation Models With Unobservable Variables and Measurement Error.”Journal of Marketing Research 18 (February): 39–50.CrossRefGoogle Scholar
  23. Hair, Joseph F., Jr., Rolph E. Anderson, Ronald L. Tatham, and William C. Black. 1998.Multivariate Data Analysis. 5th ed. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  24. Hennig-Thurau, Thorsten, Gianfranco Walsh, and Oliver Wruck. 2001. “An Investigation Into the Success Factors Determining the Success of Service Innovations: The Case of Motion Pictures.”Academy of Marketing Science Review. Scholar
  25. hennig06-01.html. Hettrick, Scott. 2001. “Raise the Rent.”Video Business. http://www Scholar
  26. Horovitz, Bruce. 2003. “Sit Down Meals Give Way to Days of Grazing.”USA Today. Scholar
  27. Jarvis, Cheryl Burke, Scott B. MacKenzie, and Philip M. Podsakoff. 2003. “A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research.”Journal of Consumer Research 30 (September): 199–218.CrossRefGoogle Scholar
  28. Jedidi, Kamel, Robert E. Krider, and Charles B. Weinberg. 1998. “Clustering at the Movies.”Marketing Letters 9 (November): 393–405.CrossRefGoogle Scholar
  29. Kaplan, Leon B., George J. Szybillo, and Jacob Jacoby. 1974. “Components of Perceived Risk in Product Purchase.”Journal of Applied Psychology 59 (June): 287–291.CrossRefGoogle Scholar
  30. Kirmani, Amna and Akshay R. Rao. 2000. “No Pain, No Gain: A Critical Review of the Literature on Signaling Unobservable Product Quality.”Journal of Marketing 64 (April): 66–79.CrossRefGoogle Scholar
  31. Krider, Robert E. and Charles B. Weinberg. 1998. “Competitive Dynamics and the Introduction of New Products: The Motion Picture Timing Game.”Journal of Marketing Research 35 (February): 1–15.CrossRefGoogle Scholar
  32. Lehmann, Donald R. and Charles B. Weinberg. 2000. “Sales Through Sequential Distribution Channels: An Application to Movies and Videos.”Journal of Marketing 64 (July): 18–33.CrossRefGoogle Scholar
  33. Levin, Aron M., Irwin P. Levin, and C. Edward Heath. 1997. “Movie Stars and Authors as Brand Names: Measuring Brand Equity in Experiential Products.” InAdvances in Consumer Research, Vol. 24. Eds. Merrie Brucks and Debbie Maclnnis. Provo, UT: Association of Consumer Research, 175–181.Google Scholar
  34. Litman, Barry R. 1983. “Predicting Success of Theatrical Movies: An Empirical Study.”Journal of Popular Culture 16 (Spring): 159–175.CrossRefGoogle Scholar
  35. Magiera, Marcy. 2004. “Rental Finishes Flat in 2004.” Dec. 30.Google Scholar
  36. Mandler, George. 1982. “The Structure of Value: Accounting for Taste.” InAffect and Cognition. Eds. Margaret S. Clark and Susan T. Fiske. Hillsdale, NJ: Lawrence Erlbaum, 3–36.Google Scholar
  37. McBride, Sarah, Peter Grant, and Merissa Marr. 2006. Movies May Hit DVD, Cable Simultaneously.”Wall Street Journal, January 4, p. B1.Google Scholar
  38. Metacritic. 2001. “The Official METASCORES FAQ List.” http://www Scholar
  39. Neelamegham, Ramya and Pradeep Chintagunta. 1999. “A Bayesian Model to Forecast New Product Performance in Domestic and International Markets.”Marketing Science 18 (2): 115–136.CrossRefGoogle Scholar
  40. Nelson, Philip. 1970. “Information and Consumer Behavior.”Journal of Political Economy 78 (2): 311–329.CrossRefGoogle Scholar
  41. Prag, Jay and James Casavant. 1994. “An Empirical Study of the Determinants of Revenues and Marketing Expenditures in the Motion Picture Industry.”Journal of Cultural Economics 18 (September): 217–235.CrossRefGoogle Scholar
  42. Prosser, Elise K. 2002. “How Early Can Video Revenues Be Accurately Predicted?”Journal of Advertising Research 42 (March/April): 47–55.Google Scholar
  43. Puig, Claudia. 2005. “Movies as You Like Them: Readers Sound Off on Theater Vs. Home.”USA Today, July 26, p. D1.Google Scholar
  44. Ratchford, Brian T. and Alan R. Andreasen. 1974. “A Study of Consumer Perceptions of Decisions.” InAdvances in Consumer Research, Vol. 1. Eds. Scott Ward and Peter Wright. Provo, UT: Association of Consumer Research, 334–345.Google Scholar
  45. Ravid, S. Abraham. 1999. “Information, Blockbuster, and Stars: A Study of the Film Industry.”Journal of Business 72 (October): 463–492.Google Scholar
  46. Rogers, Everett M. 1983.Diffusion of Innovations, 3d ed. New York: Free Press.Google Scholar
  47. Rust, Roland T. and Richard L. Oliver. 1994. “Service Quality: Insights and Managerial Implications From the Frontier.” InService Quality: New Directions in Theory and Practice. Eds. Roland T. Rust and Richard L. Oliver. Thousand Oaks, CA: Sage, 1–19.Google Scholar
  48. Sawhney, Mohanbir S. and Jehoshua Eliashberg. 1996. “A Parsimonious Model of Forecasting Gross Box-Office Revenues of Motion Pictures.”Marketing Science 15 (2): 113–131.CrossRefGoogle Scholar
  49. Slotegraaf, Rebecca J. and Peter R. Dickson. 2004. “The Paradox of a Marketing Planning Capability.”Journal of the Academy of Marketing Science 32 (Fall): 371–385.CrossRefGoogle Scholar
  50. Stone, M. 1974. “Cross-Validatory Choice and Assessment of Statistical Predictions.”Journal of the Royal Statistical Society 36 (1): 111–147.Google Scholar
  51. Swami, Sanjeev, Jehoshua Eliashberg, and Charles B. Weinberg. 1999. “SilverScreener: A Modeling Approach to Movie Screens Management.”Marketing Science 18 (3): 352–372.CrossRefGoogle Scholar
  52. Valenti, Jack. 2001. “How It All Began.” about/index.htm.Google Scholar
  53. Weinberg, Charles B. 2003. “Profits Out of the Picture: Research Issues and Revenue Sources Beyond the North American Box Office.” Working paper. University of British Columbia, Vancouver, Canada.Google Scholar
  54. Zinkhan, George M., Erich Joachimsthaler, and Thomas Kinnear. 1987. “Individual Differences and Marketing Decision Support System Usage and Satisfaction.”Journal of Marketing Research 24 (2): 208–214.CrossRefGoogle Scholar

Copyright information

© Academy of Marketing Science 2006

Authors and Affiliations

  • Thorsten Hennig-Thurau
    • 1
  • Mark B. Houston
    • 2
  • Gianfranco Walsh
    • 3
  1. 1.Bauhaus-University of WeimarGermany
  2. 2.University of Missouri-ColumbiaColumbiaUSA
  3. 3.University of Koblenz-LandauGermany

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