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The Effect of Rating Dispersion on Purchase of Experience Goods based on the Korean Movie Box Office Data

  • Received : 2019.01.07
  • Accepted : 2019.04.26
  • Published : 2019.04.30

Abstract

Online platforms often provide rating information to customers to relieve the uncertainty they encounter when purchasing experience goods. Prior research has focused mostly on the roles of rating volume and the valence of an average rating among the various possibilities. However, less frequently investigated is the effect of rating dispersion, which may be associated with uncertainty regarding how well a product fits a customer's personal preference, on new trials of experience goods. In this study, we examine the effect of rating dispersion on new trials of experience goods and identify the conditions which intensify or reduce the effect. Empirical analyses of movie box office sales data and online rating data reveal three interesting findings. First, movie sales decrease as movie ratings become increasingly dispersed. Second, the negative effect of rating dispersion on movie sales is more pronounced with more rating volume. Third, this negative effect weakens when additional information about a movie is available (i.e., higher average rating, greater star power, and time since its release). We discuss the academic and practical implications of our findings.

Keywords

References

  1. Bae, J., & Kim, B. D. (2013). Is the electronic word of mouth effect always positive on the movie?, Academy of Marketing Studies Journal, 17 (1), 61-78.
  2. Bakshy, E., Rosenn, I., Marlow, C., & Adamic, L. (2012). The role of social networks in information diffusion, In Proceedings of the 21st international conference on World Wide Web, 519-28. ACM.
  3. 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.
  4. Bei, L. T., Chen, E. Y., & Widdows, R. (2004). Consumers' online information search behavior and the phenomenon of search vs. experience products, Journal of Family and Economic Issues, 25 (4), 449-467.
  5. Bernoulli, J. (1713). Ars conjectandi. Impensis Thurnisiorum, fratrum.
  6. Bhardwaj, P. (2001). Delegating pricing decisions, Marketing Science, 20 (2), 143-169.
  7. Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior, Journal of Consumer Research, 14 (3), 350-362
  8. Chen, P. Y., Hong, Y., & Liu, Y. (2017). The value of multidimensional rating systems: Evidence from a natural experiment and randomized experiments, Management Science, 64 (10), 4629-4647.
  9. Chen, P. Y., Wu, S. Y., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales, ICIS 2004 Proceedings, 58, 711-724.
  10. Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix, Management Science, 54 (3), 477-91.
  11. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews, Journal of Marketing Research, 43(3), 345-354.
  12. Chintagunta, P. K., Gopinath, S., & 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), 944-957.
  13. Clemons, E. K., Gao, G. G., & Hitt, L. M. (2006). When online reviews meet hyperdifferentiation: A study of the craft beer industry, Journal of Management Information Systems, 23 (2), 149-171
  14. Dellarocas, C., Zhang, X. M., & 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.
  15. Desai, K. K., & Basuroy, S. (2005). Interactive influence of genre familiarity, star power, and critics' reviews in the cultural goods industry: The case of motion pictures, Psychology & Marketing, 22 (3), 203-223.
  16. Duan, W., Gu, B., & Whinston, A. B. (2008a). Do online reviews matter?-An empirical investigation of panel data, Decision Support Systems, 45(4), 1007-1016.
  17. Duan, W., Gu, B., & Whinston, A. B. (2008b). The dynamics of online word-of-mouth and product sales-An empirical investigation of the movie industry, Journal of Retailing, 84 (2), 233-242.
  18. Elberse, A., & Eliashberg, J. (2003). Demand and supply dynamics for sequentially released products in international markets: The case of motion pictures, Marketing Science, 2 (3), 329-354.
  19. Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping, Journal of Business Research, 56 (11), 867-875
  20. Garvin, D. A. (1984). What does "product quality" really mean?, Sloan Management Review, 3, 25-43.
  21. Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication, Marketing Science, 23 (4), 545-560.
  22. Gos ling, S., Hall, C. M., & Andersson, A. C. (2018). The manager's dilemma: a conceptualization of online review manipulation strategies, Current Issues in Tourism, 21 (5), 484-503.
  23. Grewal, D., Gotlieb, J., & Marmorstein, H. (1994). The moderating effects of message framing and source credibility on the price-perceived risk relationship, Journal of Consumer Research, 21 (1), 145-153.
  24. Harmon, R. R., & Coney, K. A. (1982). The persuasive effects of source credibility in buy and lease situations, Journal of Marketing Research, 19 (2), 255-260.
  25. Harrison-Walker, L. J. (2001). The measurement of word-of-mouth communication and an investigation of service quality and customer commitment as potential antecedents, Journal of Service Research, 4 (1), 60-75.
  26. Hurley, R. F., & Estelami, H. (1998). Alternative indexes for monitoring customer perceptions of service quality: A comparative evaluation in a retail context, Journal of the Academy of Marketing Science, 26 (3), 209-221.
  27. Hofstede, G., & Bond, M. H. (1984). Hofstede's culture dimensions: An independent validation using Rokeach's value survey, Journal of Cross-cultural Psychology, 15 (4), 417-433.
  28. Hong, Y., & Pavlou, P. A. (2010). Fit does matter! An empirical study on product fit uncertainty in online marketplaces, ICIS 2010 Proceedings, 218, 1-20.
  29. Hong, Y., & Pavlou, P. A. (2014). Product fit uncertainty in online markets: Nature, effects, and antecedents. Information Systems Research, 25 (2), 328-344.
  30. Hu, N., Bose, I., Koh, N. S., & Liu, L. (2012). Manipulation of online reviews: An analysis of ratings, readability, and sentiments, Decision Support Systems, 52 (3), 674-684.
  31. Huang, P., Lurie, N. H., & Mitra, S. (2009). Searching for experience on the web: An empirical examination of consumer behavior for search and experience goods, Journal of Marketing, 73 (2), 55-69.
  32. Iyengar, R., Van den Bulte, C., & Lee, J. Y. (2015). Social contagion in new product trial and repeat, Marketing Science, 34 (3), 408-429.
  33. Kwark, Y., Chen, J., & Raghunathan, S. (2014). Online product reviews: Implications for retailers and competing manufacturers, Information Systems Research, 25 (1), 93-110.
  34. Lee, M., & Youn, S. (2009). Electronic word of mouth (eWOM) How eWOM platforms influence consumer product judgement, International Journal of Advertising, 28 (3), 473-499.
  35. Levin, A. M., Levin, I. P., & Heath, C. E. (1997). Movie stars and authors as brand names: Measuring brand equity in experiential products, in NA - Advances in Consumer Research 24 eds., 175-181.
  36. Litman, B. R. (1983). Predicting success of theatrical movies: An empirical study, The Journal of Popular Culture, 16 (4), 159-175.
  37. Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue, Journal of Marketing, 70 (3), 74-89
  38. Mandrik, C. A., & Bao, Y. (2005). Exploring the concept and measurement of general risk aversion, in NA - Advances in Consumer Research Volume 32, eds., 531-539.
  39. Matzler, K., Grabner-Krauter, S., & Bidmon, S. (2008). Risk aversion and brand loyalty: the mediating role of brand trust and brand affect, Journal of Product and Brand Management, 17 (3), 154-162.
  40. Mayzlin, D., Dover, Y., & Chevalier, J. (2014). Promotional reviews: An empirical investigation of online review manipulation, American Economic Review, 104 (8), 2421-2455.
  41. Misra, S., Coughlan, A. T., & Narasimhan, C. (2005). Salesforce compensation: An analytical and empirical examination of the agency theoretic approach, Quantitative Marketing and Economics, 3 (1), 5-39.
  42. Moe, W. W., & Trusov, M. (2011). The value of social dynamics in online product ratings forums, Journal of Marketing Research, 48 (3), 444-456.
  43. Moore, W. L., & Lehmann, D. R. (1980). Individual differences in search behavior for a nondurable, Journal of Consumer Research, 7 (3), 296-307
  44. Nam, S., Manchanda, P., & Chintagunta, P. K. (2010). The effect of signal quality and contiguous word of mouth on customer acquisition for a video-on-demand service, Marketing Science, 29 (4), 690-700.
  45. Narayanan, S., & Manchanda, P. (2009). Heterogeneous learning and the targeting of marketing communication for newproducts, Marketing Science, 28 (3), 424-441.
  46. Nelson, P. (1970). Information and consumer behavior, Journal of Political Economy, 78 (2), 311-329.
  47. Nelson, P. (1974). Advertising as information, Journal of Political Economy, 82 (4), 729-754.
  48. Pavlou, P. A., & Gefen, D. (2004). Building effective online marketplaces with institutionbased trust. Information Systems Research, 15 (1), 37-59.
  49. Purnawirawan, N., De Pelsmacker, P., & Dens, N. (2012). Balance and sequence in online reviews: How perceived usefulness affects attitudes and intentions, Journal of interactive marketing, 26 (4), 244-255.
  50. Qiu, L., Pang, J., & Lim, K. H. (2012). Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: The moderating role of review valence, Decision Support Systems, 54 (1), 631-643.
  51. Ruef, M., Aldrich, H. E., & Carter, N. M. (2003). The structure of founding teams: Homophily, strong ties, and isolation among US entrepreneurs. American Sociological Review, 68 (2), 195-222
  52. Schubert, P., & Ginsburg, M. (2000). Virtual communities of transaction: The role of personalization in electronic commerce, Electronic Markets, 10 (1), 45-55.
  53. Shimp, T. A., & Bearden, W. O. (1982). Warranty and other extrinsic cue effects on consumers' risk perceptions, Journal of Consumer Research, 9 (1), 38-46.
  54. Sun, M. (2012). How does the variance of product ratings matter?, Management Science, 58 (4), 696-707.
  55. 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), 1-27.
  56. Wan, Y., Nakayama, M., & Sutcliffe, N. (2012). The impact of age and shopping experiences on the classification of search, experience, and credence goods in online shopping, Information Systems and e-Business Management, 10 (1), 135-148.
  57. Weathers, D., Sharma, S., & Wood, S. L. (2007). Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods, Journal of Retailing, 83 (4), 393-401.
  58. Wellman, B., Boase, J., & Chen, W. (2002). The networked nature of community: Online and offline, It & Society, 1 (1), 151-165.
  59. Wright, A. A., & Lynch Jr, J. G. (1995). Communication effects of advertising versus direct experience when both search and experience attributes are present, Journal of Consumer Research, 21 (4), 708-718.
  60. Yang, J., Kim, W., Amblee, N., & Jeong, J. (2012). The heterogeneous effect of WOMon product sales: why the effect of WOMvalence is mixed?, European Journal of Marketing, 46 (11-12), 1523-1538.
  61. Yin, D., Mitra, S., & Zhang, H. (2016). Research note-When do consumers value positive vs. negative reviews? An empirical investigation of confirmation bias in online word of mouth, Information Systems Research, 27 (1), 131-144.
  62. Zeithaml, V. A. (1981). How consumer evaluation processes differ between goods and services, in Donnelly, J.A. and George, W.R. (Eds). Marketing of Services, American Marketing Association, Chicago, IL, 186-190.
  63. Zhang, L., Choi, K., & Lee, J. (2017). The periodic relationship between eWOM volume/ valence and box office revenue, Knowledge Management Research, 18 (2), 65-83.
  64. Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics, Journal of Marketing, 74 (2), 133-148.