Journal of Cultural Economics

, Volume 39, Issue 1, pp 15–41 | Cite as

When does it make sense to do it again? An empirical investigation of contingency factors of movie remakes

  • Björn Bohnenkamp
  • Ann-Kristin Knapp
  • Thorsten Hennig-Thurau
  • Ricarda Schauerte
Original Article

Abstract

A substantial number of current Hollywood productions are remakes of earlier motion pictures. This research investigates the economic implications of this strategy. It develops a conceptual framework of brand extension success in the movie industry that builds upon the sensations and familiarity that a movie offers and uses this framework to illustrate how remakes differ from other movie brand extensions (e.g., sequels). The sensations-familiarity framework is complemented by a contingency model that identifies factors which influence revenues and risk of movie remakes. Using a dataset of 207 remakes released in North American theaters between 1999 and 2011 and a matched sample of other movies, the authors find that, on average, remakes do not increase revenues but do reduce financial risk. The authors also provide evidence of the contingency role of several factors, including the original movie’s awareness and image and the relationship between the original movie and the remake. These insights should be valuable for the movie industry, as they can guide movie producers in their selection of movie brands that, if remade, should be more successful at the box office than the “average” movie remake.

Keywords

Remakes Motion pictures Brand extension 

References

  1. Aaker, D. A., & Keller, K. L. (1990). Consumer evaluations of brand extensions. Journal of Marketing, 54(1), 27–41.CrossRefGoogle Scholar
  2. Basuroy, S., & Chatterjee, S. (2008). Fast and frequent: Investigating box office revenues of motion picture sequels. Journal of Business Research, 61(1), 798–803.CrossRefGoogle Scholar
  3. Basuroy, S., Chatterjee, S., & Ravid, S. A. (2003). How critical are critical reviews? The box office effects of film critics, star power, and budgets. Journal of Marketing, 67(4), 103–117.CrossRefGoogle Scholar
  4. Bazin, A. (1951). A propos des reprises. Cahiers du Cinéma, 1(5), 52–56.Google Scholar
  5. Boxofficemojo. (2013). All time box office. Accessed December 23, 2013 from http://boxofficemojo.com/alltime/world/.
  6. Chang, B. H., & Ki, E. J. (2005). Devising a practical model for predicting theatrical movie success: Focusing on the experience good property. Journal of Media Economics, 18(4), 247–269.CrossRefGoogle Scholar
  7. Dacin, P. A., & Smith, D. C. (1994). The effect of brand portfolio characteristics on consumer evaluations of brand extensions. Journal of Marketing Research, 31(2), 229–242.CrossRefGoogle Scholar
  8. Dhar, T., Sun, G., & Weinberg, C. B. (2012). The long-term box office performance of sequel movies. Marketing Letters, 23(1), 13–29.CrossRefGoogle Scholar
  9. Eliashberg, J., & Sawhney, M. S. (1994). Modeling goes to Hollywood: Predicting individual differences in movie enjoyment. Management Science, 40(9), 1151–1173.CrossRefGoogle Scholar
  10. Elliott, C., & Simmons, R. (2008). Determinants of UK box office success: The impact of quality signals. Review of Industrial Organization, 33(2), 93–111.CrossRefGoogle Scholar
  11. Fellman, D. R. (2006). Theatrical distribution. In J. S. Squire (Ed.), The movie business book (pp. 362–374). Maidenhead: Open University Press.Google Scholar
  12. Friedman, R. G. (2006). Motion picture marketing. In J. S. Squire (Ed.), The movie business book (pp. 282–299). Maidenhead: Open University Press.Google Scholar
  13. Gelder, K. (2004). Popular fiction. The logics and practices of a literary field. New York: Routledge.Google Scholar
  14. Gemser, G., Leenders, M. A. A. M., & Weinberg, C. B. (2012). More effective assessment of market performance in later stages of the product development process: The case of the motion picture industry. Marketing Letters, 23(4), 1019–1031.CrossRefGoogle Scholar
  15. Green, M. C., Brock, T. C., & Kaufman, G. F. (2004). Understanding media enjoyment: The role of transportation into narrative worlds. Communication Theory, 14(4), 311–327.CrossRefGoogle Scholar
  16. Heckman, J. J., Ichimura, H., & Todd, P. E. (1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training program. Review of Economic Studies, 64(4), 605–654.CrossRefGoogle Scholar
  17. Heckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an econometric evaluation estimator. The Review of Economic Studies, 65(2), 261–294.CrossRefGoogle Scholar
  18. Hennig-Thurau, T., Houston, M. B., & Heitjans, T. (2009). Conceptualizing and measuring the monetary value of brand extensions: The case of motion pictures. Journal of Marketing, 73(6), 167–183.CrossRefGoogle Scholar
  19. Hennig-Thurau, T., Houston, M. B., & Sridhar, S. (2006a). Can good marketing carry a bad product? Evidence from the motion picture industry. Marketing Letters, 17(3), 205–219.CrossRefGoogle Scholar
  20. Hennig-Thurau, T., Houston, M. B., & Walsh, G. (2006b). The differing roles of success drivers across sequential channels: An application to the motion picture industry. Journal of the Academy of Marketing Science, 34(4), 559–575.CrossRefGoogle Scholar
  21. Hennig-Thurau, T., Walsh, G., & Wruck, O. (2001). An investigation into the factors determining the success of service innovations: The case of motion pictures. Academy of Marketing Science Review, 6, 1–23.Google Scholar
  22. Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: Emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92–101.CrossRefGoogle Scholar
  23. Ho, J. Y. C., Dhar, T., & Weinberg, C. B. (2009). Playoff payoff: Super Bowl advertising for movies. International Journal of Research in Marketing, 26, 168–179.CrossRefGoogle Scholar
  24. Joshi, A., & Mao, H. (2012). Adapting to succeed? Leveraging the brand equity of best sellers to succeed at the box office. Journal of the Academy of Marketing Science, 40(4), 558–571.CrossRefGoogle Scholar
  25. Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1–22.CrossRefGoogle Scholar
  26. Knapp, A.-K., Hennig-Thurau, T., & Mathys, J. (2014). The importance of reciprocal spillover effects for the valuation of bestseller brands: Introducing and testing a contingency model. Journal of the Academy of Marketing Science, 42(2), 205–221.CrossRefGoogle Scholar
  27. Maltin, L. (2013). Leonard Maltin’s 2014 Movie Guide. New York: Signet.Google Scholar
  28. Marshall, P., Dockendorff, M., & Ibanez, S. (2013). A forecasting system for movie attendance. Journal of Business Research, 66(10), 1800–1806.CrossRefGoogle Scholar
  29. Mendelson, S. (2013). ‘Robocop’ and the problem with remakes. Forbes, July 11. Accessed December, 05 2013 from http://www.forbes.com/sites/scottmendelson/2013/11/07/trailer-talk-robocop-and-the-problem-with-remakes/.
  30. Palia, D., Ravid, S. A., & Reisel, N. (2008). Choosing to cofinance: Analysis of project-specific alliances in the movie industry. The Review of Financial Studies, 22(2), 483–511.Google Scholar
  31. Paternoster, R., Brame, R., Mazerolle, P., & Piquero, A. (1998). Using the correct statistical test for the equality of regression coefficients. Criminology, 36(4), 859–866.CrossRefGoogle Scholar
  32. Ravid, S. A. (1999). Information, blockbusters, and stars: A study of the film industry. Journal of Business, 72(4), 463–492.CrossRefGoogle Scholar
  33. Ravid, S. A., & Basuroy, S. (2004). Beyond morality and ethics: Executive objective function, the R-rating puzzle, and the production of violent films. Journal of Business, 77(2), 155–192.CrossRefGoogle Scholar
  34. Reddy, S. K., Holak, S. L., & Bhat, S. (1994). To extend or not to extend: Success determinants of line extensions. Journal of Marketing Research, 31(2), 243–262.CrossRefGoogle Scholar
  35. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.CrossRefGoogle Scholar
  36. Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39(1), 33–38.Google Scholar
  37. Rubin, D. B. (1973). The use of matched sampling and regression adjustment to remove bias in observational studies. Biometrics, 29(1), 185–203.CrossRefGoogle Scholar
  38. Smith, H. L. (1997). Matching with multiple controls to estimate treatment effects in observational studies. Sociological Methodology, 27(1), 325–353.CrossRefGoogle Scholar
  39. Smith, J. A., & Todd, P. E. (2001). Reconciling conflicting evidence on the performance of propensity-score matching methods. American Economic Review, 91(2), 112–118.CrossRefGoogle Scholar
  40. Sood, S., & Drèze, X. (2006). Brand extensions of experiential goods: Movie sequel evaluations. Journal of Consumer Research, 33(3), 352–360.CrossRefGoogle Scholar
  41. Thompson, C. J., Pollio, H. R., & Locander, W. B. (1994). The spoken and the unspoken: A hermeneutic approach to understanding the cultural viewpoints that underlie consumers’ expressed meanings. Journal of Consumer Research, 21(3), 432–452.CrossRefGoogle Scholar
  42. Verevis, C. (2006). Film remakes. Edinburgh: Edinburgh University Press.Google Scholar
  43. Völckner, F., & Sattler, H. (2006). Drivers of brand extension success. Journal of Marketing, 70(2), 18–34.CrossRefGoogle Scholar
  44. Wallace, W. T., Seigerman, A., & Holbrook, M. B. (1993). The role of actors and actresses in the success of films: How much is a movie star worth? Journal of Cultural Economics, 17, 1–27.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Björn Bohnenkamp
    • 1
  • Ann-Kristin Knapp
    • 2
  • Thorsten Hennig-Thurau
    • 2
    • 3
  • Ricarda Schauerte
    • 2
  1. 1.Karlshochschule International UniversityKarlsruheGermany
  2. 2.Marketing Center MuensterUniversity of MuensterMuensterGermany
  3. 3.Cass Business SchoolCity University LondonLondonUK

Personalised recommendations