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Effective Demand Lifting through Pre-Launch Movie Marketing Activities

  • Received : 2015.12.28
  • Accepted : 2016.04.11
  • Published : 2016.10.31

Abstract

The purpose of this paper is to examine empirically how to balance advertising expenditure before and after launch with regard to the direction of word of mouth in the motion picture industry. The vector auto-regression model is applied to assess the dynamic impact of advertising and word of mouth on sales. Empirical data, including advertising, word of mouth, and sales (the number of entries) of 83 movies are used for analysis. The research results show that for a movie having more positive word of mouth in the pre- and post-launch periods, it is worthwhile to spend the advertising budget in the pre-launch period only and to spare it in post-launch period. However, it is worthwhile to spare the advertising budget in the pre-launch period for movies having less positive word of mouth before and after launch, and to concentrate spending in post-launch period instead. Mangers who handle products and services facing shortened lifecycles, such as games, eBooks, and digital music contents, need to check the quality of pre-launch word of mouth for their advertising budget decisions in the pre- and post-launch periods and spend more of the advertising budget in the post- (pre-) launch period if pre-launch word of mouth is negative (positive). For products and services with a shortened lifecycle, it is recommended to spend more of the advertising budget in the post- (pre-) launch period if pre-launch word of mouth is negative (positive).

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A5A8024569)

References

  1. Anand, B., and Shachar, R. (2004), "Advertising the matchmaker," working paper, Harvard University Cambridge.
  2. Babutsidze, Z. (2011), "Advertising and WordOf-Mouth in Motion Picture Industry," working paper, OFCE Sciences Po and SKEMA Business School.
  3. Bemmaor, A. C. (1994), "Modeling the diffusion of new durable goods: Word-of-mouth effect versus consumer heterogeneity," In Laurent, G., Lilien, G. L., and Pras, B. (Eds.), Research Traditions in Marketing, 201-223.
  4. Burmester, A. B., Becker, J. U., van Heerde, H. J., and Clement, M. (2015), "The Impact of Pre- and Post-launch Publicity and Advertising on New Product Sales," International Journal of Research in Marketing, 32 (4), 408-417.
  5. Caves, R. E. (2001), "Creative Industries: Contracts Between Art and Commerce," Cambridge, MA: Harvard University Press.
  6. Chevalier, J. A., and Mayzlin, D. (2006), "The effect of word of mouth on sales: Online book Reviews," Journal of Marketing Research, 43 (3), 345-54.
  7. Chintagunta, P. K., Gopinath, S., and Venkataraman, S. (2010), "The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets," Marketing Science, 29 (5), 944-57.
  8. Clark, C. R., Doraszelski, U., and Draganska, M. (2009), "The effect of advertising on brand awareness and perceived quality: An empirical investigation using panel data," Quantitative Marketing and Economics, 7, 20736.
  9. Dekimpe, M. G., and Hanssens, D. M. (1995), "The persistence of marketing effects on sales," Marketing Science, 14 (1), 1-21.
  10. Dellarocas, C., Zhang, X. Q. and Awad, N. F. (2007), "Exploring the value of online product reviews in forecasting sales: The case of motion pictures," Journal of Interactive Marketing, 21 (4), 23-45.
  11. Elberse, A. and Anand, B. N. (2007), "The effectiveness of pre-release advertising for motion pictures: An empirical investigation using a simulated market," Information Economics and Policy, 19 (3-4), 319-43.
  12. Godes, D. and Mayzlin, D. (2004), "Using online conversations to study word-of-mouth communication," Marketing Science, 23 (4), 545-60.
  13. Gopinath, S., Chintagunta, P. K. and Venkataraman, S. (2013), "Blogs, Advertising, and Localmarket Movie Box Office Performance," Management Science, 59 (12), 2635-2654.
  14. Joshi, A. and Hanssens, D. M. (2009), "Movie advertising and the stock market valuation of studios: A case of Great Expectations?," Marketing Science, 28 (2), 239-50.
  15. Joshi, A. and Hanssens, D. M. (2010), "The direct and indirect effects of advertising spending on firm value," Journal of Marketing, 74 (1), 20-33.
  16. Liu, Y. (2006), "Word of mouth for movies: Its dynamics and impact on box office revenue," Journal of Marketing, 70 (3), 74-89.
  17. Narayanan, S., Manchanda, P. and Chintagunta, P. K. (2005), "Temporal differences in the role of marketing communication in new product categories," Journal of Marketing Research, 42, 278-90.
  18. Oliver, R. L. (1980), "A cognitive model of the antecedents and consequences of satisfaction decisions," Journal of Marketing Research, 17, 460-9.
  19. Onishi, H. and Manchanda, P. (2012), "Marketing activity, blogging and sales," International Journal of Research in Marketing, 29 (3), 221-234.
  20. Ottenbacher, M. C. and Harrington, R. F. (2010), "Strategies for achieving success for innovative versus incremental new services," Journal of Services Marketing, 24 (1), 3-15.
  21. Pauwels, K. (2004), "How dynamic consumer response, competitor response, company support, and company inertia shape longterm marketing effectiveness," Marketing Science, 23 (4), 596-610.
  22. Pauwels, K., Silva-Risso, J., Srinivasan, S. and Hanssens, D. M. (2004), "New Products, Sales Promotions, and Firm Value: The Case of the Automobile Industry," Journal of Marketing, 68 (4), 142-156.
  23. Pauwels, K. and Weiss, A. (2008), "Moving from free to fee: How online firms market to change their business model successfully," Journal of Marketing, 72 (3), 14-31.
  24. Rennhoff, A. D. and Wilbur, K. C. (2011), "The Effectiveness of Post-release Movie Advertising," International Journal of Advertising, 30 (2), 305-328.
  25. Schonfeld and Associates. (2006), "Advertising Ratios and Budgets," Schonfeld and Associates Inc.
  26. Song, T. H., Kim, J. and Ko, W. (2009) "ReConsidering Aggregated Data Bias by Extending Koyck Model," Journal of the Korean Operations Research and Management Science Society, 34 (2), 91-100.
  27. Srinivasan, S., Pauwels, K., Hanssens, D. M. and Dekimpe, M. G. (2004), "Do promotions benefit manufacturers, retailers, or both?," Management Science, 50 (5), 617-629.
  28. Xiong, G. and Bharadwaj, S. (2014), "Prerelease Buzz Evolution Patterns and New Product Performance," Marketing Science, 33 (3), 401-421.
  29. Zufryden, F. S. (1996), "Linking advertising to box office performance of new film releases - A marketing planning model," Journal of Advertising Research, 36, 29-41