Skip to main content
SpringerLink
Log in

Adapting to succeed? Leveraging the brand equity of best sellers to succeed at the box office

  • Original Empirical Research
  • Published:
Journal of the Academy of Marketing Science Aims and scope Submit manuscript

Abstract

Many movies are based on best-selling novels. While book adaptation is an often used strategy in the motion picture industry, it has received little academic attention. Using a multi-method approach, this research investigates the drivers behind the success of book-based movies. In Study 1, we analyze over 700 movies and find that book-based movies perform better at the box office on the opening weekend than non-book movies. However, this superior performance dissipates after the opening weekend. Further, the opening weekend performance of book-based movies is positively driven by book equity, book-movie similarity, and recency between the book’s peak equity and movie release. After the opening weekend, many of these book-related variables cease to have an impact, and the effect of movie-related variables (e.g., reviews) increases. Because Study 1 documents that book-movie similarity positively impacts the movie’s performance, contrary to prior findings that content similarity has negative or null impact on performance of a movie sequel, we undertake a second study to reconcile the discrepancy. Study 2 finds that content similarity results in satiation and therefore hampers the movie success for sequels; however, when a movie is adapted from a book, due to experiential modality change (i.e., from book format to film format rather than film to film), content similarity increases the movie’s chance of success.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. As a robustness check, we also collected a sample of 144 non-book movies between 2000 and 2006 and re-estimated the related models. The results remain the same except for minor changes in magnitude of coefficients. We would like to thank an anonymous reviewer for suggesting this robustness check analysis.

  2. Another option would be to use total gross as the dependent variable and have opening weekend gross as an explanatory variable, but that method is inferior to our approach, as it gives rise to concerns of multicolinearity.

  3. We would like to thank an anonymous reviewer for suggesting this operationalization of the equity variable.

  4. We have conducted robustness checks with two different arbitrary rank assignments to books that have never made any best-selling list—500 and 10,000—and our results remain the same (except for change in the magnitudes of coefficients).

  5. Another possible instrumental variable for similarity can be whether the name of the book and movie are the same. However, in our dataset, only two movies (out of 482) had names that differed from the names of the books upon which they were based.

References

  • Aaker, D. A., & Keller, K. L. (1990). Consumer evaluations of brand extensions. Journal of Marketing, 54(1), 27–41.

    Article  Google Scholar 

  • Ainslie, A., Drèze, X., & Zufryden, F. (2005). Modeling movie life cycles and market share. Marketing Science, 24(3), 508–517.

    Article  Google Scholar 

  • Basuroy, S., Chatterjee, S., & Abraham Ravid, S. (2003). How critical are critical reviews? The box office effects of film critics, star power and budgets. Journal of Marketing, 67(4), 103–117.

    Article  Google Scholar 

  • Basuroy, S., Desai, K. K., & Talukdar, D. (2006). An empirical investigation of signaling in the Motion Picture Industry. Journal of Marketing Research, 43(2), 287–295.

    Article  Google Scholar 

  • Broniarczyk, S. M., & Alba, J. W. (1994). The importance of the brand in brand extension. Journal of Marketing Research, 31(2), 214–228.

    Article  Google Scholar 

  • Brown, T. J., & Dacin, P. A. (1997). The company and the product: corporate associations and consumer product responses. Journal of Marketing, 61(1), 68–84.

    Article  Google Scholar 

  • Caminal, R., & Vives, X. (1996). Why market shares matter: an information-based theory. Rand Journal of Economics, 27, 221–239.

    Article  Google Scholar 

  • Chevalier, J. A., & Goolsbee, A. (2003). Measuring prices and price competition online: Amazon.com and BarnesandNoble.com. Quantitative Marketing and Economics, 1(2), 203–222.

    Article  Google Scholar 

  • Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: online book reviews. Journal of Marketing Research, 43(9), 345–354.

    Article  Google Scholar 

  • Crowder, R. G. (1976). Principles of learning and memory. Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  • Czeller, S. (2003). Consumer attitude towards brand extensions: an integrative model and research propositions. International Journal of Research in Marketing, 20(1), 97–115.

    Article  Google Scholar 

  • De Vany, A., & Walls, W. D. (1999). Uncertainty in the movie industry: does star power reduce the terror of the box office? Journal of Cultural Economics, 23(4), 285–318.

    Google Scholar 

  • De Vany, A., & Walls, W. D. (2002). Does Hollywood make too many r-rated movies? Risk, stochastic dominance and the illusion of expectation. Journal of Business, 75(3), 425–451.

    Article  Google Scholar 

  • Elberse, A. (2007). The power of stars: do star actors drive the success of movies? Journal of Marketing, 71(4), 102–120.

    Article  Google Scholar 

  • Elberse, A., & Eliashberg, J. (2003). Demand and supply dynamics for sequentially released products in international markets: the case of motion pictures. Marketing Science, 22(3), 329–354.

    Article  Google Scholar 

  • Eliashberg, J., & Shugan, S. M. (1997). Film critics: influencers or predictors? Journal of Marketing, 61(2), 68–78.

    Article  Google Scholar 

  • Feldman, J. M., & Lynch, J. G. (1988). Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology, 73(3), 421–435.

    Article  Google Scholar 

  • Friedman, R. G. (1992). Motion picture marketing. In J. E. Squire (Ed.), The movie business book (3rd ed., pp. 282–299). New York: Fireside.

    Google Scholar 

  • Hellofs, L. L., & Jacobson, R. (1999). Market share and customers’ perceptions of quality: when can firms grow their way to higher versus lower quality? Journal of Marketing, 63(1), 16–25.

    Article  Google Scholar 

  • Joshi, A. M., & Hanssens, D. M. (2009). Movie advertising and the stock market valuation of studios: a case of ‘Great Expectations? Marketing Science, 28(2), 239–250.

    Article  Google Scholar 

  • Kent, R. J., & Allen, C. T. (1994). Competitive interference effects in consumer memory for advertising: the role of brand familiarity. Journal of Marketing, 58(3), 97–105.

    Article  Google Scholar 

  • Klink, R. R., & Smith, D. C. (2001). Threats to the external validity of brand extension research. Journal of Marketing Research, 38, 326–335.

    Article  Google Scholar 

  • Krider, R. E., Li, T., Liu, Y., & Weinberg, C. B. (2005). The lead-lag puzzle of demand and distribution: a graphical method applied to movies. Marketing Science, 24(4), 635–645.

    Article  Google Scholar 

  • Lampel, J., & Shamsie, J. (2000). Critical push: strategies for creating momentum in the motion picture industry. Journal of Management, 26, 233–257.

    Article  Google Scholar 

  • Lynch, J. G., Harmorstein, H., & Weigold, M. F. (1988). Choices from sets including remembered brands: use of recalled attributes and prior overall evaluations. Journal of Consumer Research, 15, 169–184.

    Article  Google Scholar 

  • Mao, H., & Krishnan, H. S. (2006). Effects of prototype and exemplar fit on brand extension evaluations: a two-process contingency model. Journal of Consumer Research, 33(1), 41–49.

    Article  Google Scholar 

  • Martin, D. (2009). ‘Harry Potter’ countdown: Steve Kloves on a ‘Haunting Moment’ in ‘Half Blood Prince.’ Los Angeles Times Hero Complex Blog (June 17), (accessed December 9, 2009).

  • McCarthy, M. S., Heath, T. B., & Milberg, S. J. (2001). New brands versus brand extensions, attitudes versus choice: experimental evidence for theory and practice. Marketing Letters, 12(1), 75–90.

    Article  Google Scholar 

  • MPAA (2008). “2008 Theatrical Market Statistics,” (accessed December 9, 2009).

  • Neelamegham, R., & Chintagunta, P. (1999). A Bayesian model to forecast new product performance in domestic and international markets. Marketing Science, 18(2), 115–136.

    Article  Google Scholar 

  • Park, C. W., Milberg, S., & Lawson, R. (1991). Evaluation of brand extensions: the role of product feature similarity and brand concept consistency. Journal of Consumer Research, 18, 185–193.

    Article  Google Scholar 

  • Redden, J. P. (2008). Reducing satiation: the role of categorization level. Journal of Consumer Research, 34(5), 624–634.

    Article  Google Scholar 

  • Rolls, B. J., Rolls, E. T., Rowe, E. A., & Sweeney, K. (1981). Sensory specific satiety in man. Physiology and Behavior, 27(1), 137–142.

    Article  Google Scholar 

  • Rosenthal, M. (2009). “Amazon Sales Rank for Books,” (December 16, 2009).

  • Sansone, C., Weir, C., Harpster, L., & Morgan, C. (1992). Once a boring task always a boring task? Interest as a self-regulatory mechanism. Journal of Personality and Social Psychology, 63(3), 379–390.

    Article  Google Scholar 

  • Schnapp, M., & Allwine, T. (2001). “Mining of Book Data from Amazon.com,” Presentation at the UCB/SIMS Web mining conference.

  • Shiv, B., & Huber, J. (2000). The impact of anticipating satisfaction on consumer choice. Journal of Consumer Research, 27(2), 202–216.

    Article  Google Scholar 

  • Sood, S., & Drèze, X. (2006). Brand extensions of experiential goods: movie sequel evaluations. Journal of Consumer Research, 33(3), 352–360.

    Article  Google Scholar 

  • Zufryden, F. (1996). Linking advertising to box-office performance of new film releases—a marketing planning model. Journal of Advertising Research, 36(4), 29–41.

    Google Scholar 

Download references

Acknowledgement

Both authors would like to thank Raj Echambadi, Shanker Krishnan, Xiaojing Yang and participants of the Marketing Science Conference in Vancouver for comments on a previous version of the draft and Ngan N. Chau for help with data collection. All remaining errors are our own.

Author information

Authors and Affiliations

  1. University of Central Florida, Orlando, FL, USA

    Amit Joshi & Huifang Mao

  2. Department of Marketing, College of Business Administration, P.O. Box 161400, Orlando, FL, 32816-1400, USA

    Amit Joshi

Authors
  1. Amit Joshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Huifang Mao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amit Joshi.

Appendix 1: Movie Posters Leveraging Book Equity

Appendix 1: Movie Posters Leveraging Book Equity

figure a

Rights and permissions

Reprints and permissions

About this article

Cite this article

Joshi, A., Mao, H. Adapting to succeed? Leveraging the brand equity of best sellers to succeed at the box office. J. of the Acad. Mark. Sci. 40, 558–571 (2012). https://doi.org/10.1007/s11747-010-0241-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11747-010-0241-2

Keywords

Search

Navigation