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Which type of online review is more persuasive? The influence of consumer reviews and critic ratings on moviegoers

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Abstract

Due to the external cultural characteristics and the experiential nature of movies, movie reviews by professional critics and ordinary consumers can significantly influence the behavioural intentions of moviegoers. This study employed a \(2\times 2\times 2\) between-subject factorial design to investigate the influence of consumer expectation and online reviews on movie selection and evaluation by moviegoers. Our results indicate that, without considering the interaction effect, potential moviegoers attach greater importance to consumer reviews than they do critical reviews, and that consumer reviews influence their movie selection as well as their post-viewing evaluation. The influence of negative consumer reviews on movie selection is stronger than that of positive consumer reviews. In contrast, positive consumer reviews are more influential in the evaluation of movies than are negative reviews. Consumer expectations were found to moderate the influence of consumer review valence on movie selections and subsequent evaluations. In addition, moviegoers with lower expectations toward a movie were more inclined to be influenced by consumer WOM and expert opinions. Managerial implications for online marketing managers and limitations are also discussed.

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References

  1. West, P. M., & Broniarczyk, S. M. (1998). Integrating multiple opinions: The role of aspiration level on consumer response to critic consensus. Journal of Consumer Research, 25(1), 38–51.

    Article  Google Scholar 

  2. Bae, S., & Lee, T. (2011). Gender differences in consumers’ perception of online consumer reviews. Electronic Commerce Research, 11(2), 201–214.

    Article  Google Scholar 

  3. Robinson, R., Goh, T., & Zhang, R. (2012). Textual factors in online product reviews: a foundation for a more influential approach to opinion mining. Electronic Commerce Research, 12(3), 301–330.

    Article  Google Scholar 

  4. Mizerski, R. W. (1982). An attribution explanation of the disproportionate influence of unfavorable information. Journal of Consumer Research, 9(3), 301–310.

    Article  Google Scholar 

  5. Sotiriadis, M., & Zyl, C. (2013). Electronic word-of-mouth and online reviews in tourism services: the use of twitter by tourists. Electronic Commerce Research, 13(1), 103–124.

    Article  Google Scholar 

  6. Burgess, L., Parish, B., & Alcock, C. (2011). To what extent are regional tourism organisations (RTOs) in Australia leveraging the benefits of web technology for destination marketing and eCommerce? Electronic Commerce Research, 11(3), 341–355.

    Article  Google Scholar 

  7. Chaffee, S. H. (1982). Mass media and interpersonal channels: Competitive, convergent, or complementary? In G. Gumber & R. Cathar (Eds.), Inter/media: Interpersonal communication in a media world. New York: Oxford University Press.

    Google Scholar 

  8. Bone, P. (1995). Word-of-mouth effects on short-term and long-term product judgments. Journal of Business Research, 32(3), 213–223.

    Article  Google Scholar 

  9. 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 Services Marketing, 4(1), 60–75.

    Google Scholar 

  10. Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of Marketing, 70(3), 74–89.

    Article  Google Scholar 

  11. 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.

    Article  Google Scholar 

  12. Holbrook, M. (1999). Popular appeal versus expert judgment of motion picture. Journal of Consumer Research, 26(2), 144–155.

    Article  Google Scholar 

  13. Clement, M., Proppe, D., & Rott, A. (2007). Do critics make bestsellers? Opinion leaders and the success of books. Journal of Media Economics, 20(2), 77–105.

    Article  Google Scholar 

  14. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing, 18(1), 38–52.

    Article  Google Scholar 

  15. Moon, S., Bergey, P., & Iacobucci, D. (2010). Dynamic effects among movie ratings, movie revenues, and viewer satisfaction. Journal of Marketing, 74(1), 108–121.

    Article  Google Scholar 

  16. Duan, W., Bin, G., & Andrew, B. W. (2008). Do online reviews matter? An empirical investigation of panel data. Decision Support Systems, 45(4), 1007–1016.

    Article  Google Scholar 

  17. Chintagunta, P. K., Gopinath, S., & Venkataraman, S. (2010). The effects of online user reviews on movie box office performance: Accounting for sequential. Marketing Science, 29(5), 944–957.

    Article  Google Scholar 

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

    Article  Google Scholar 

  19. d’Astous, A., & Touil, N. (1999). Consumer evaluations of movies on the basis of critics’ judgments. Psychology & Marketing, 16(8), 677–694.

    Article  Google Scholar 

  20. Park, D., & Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research & Applications, 7(4), 399–410.

    Article  Google Scholar 

  21. Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: classic and contemporary approaches. Dubuque, Iowa: W.C. Brown Co., Publishers.

    Google Scholar 

  22. Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341–352.

    Article  Google Scholar 

  23. Faber, R. J., & O’Guinn, T. C. (1984). Effect of media advertising and other sources on movie selection. Journalism Quarterly, 61(2), 317–377.

    Article  Google Scholar 

  24. Blackshaw, P. (2006). Reconcilable differences. Marketing Management, 15(5), 38–40.

    Google Scholar 

  25. Hsieh, J. K., Hsieh, Y. C., & Tang, Y. C. (2012). Exploring the disseminating behaviors of eWOM marketing: persuasion in online video. Electronic Commerce Research, 12(2), 201–224.

    Article  Google Scholar 

  26. Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78(2), 311–329.

    Article  Google Scholar 

  27. Zeithaml, V. A. (1981). How consumer evaluation processes differ between goods and services. In J. H. Donnelly & W. R. George (Eds.), Marketing of services (pp. 186–190). Chicago: American Marketing Association.

    Google Scholar 

  28. Gerdes, J., Stringam, B., & Brookshire, R. (2008). An integrative approach to assess qualitative and quantitative consumer feedback. Electronic Commerce Research, 8(4), 217–234.

    Article  Google Scholar 

  29. Park, D., & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electronic Commerce Research and Applications, 7(4), 386–398.

    Article  Google Scholar 

  30. Buttle, F. A. (1998). Word of mouth: understanding and managing referral marketing. Journal of Strategic Marketing, 6(3), 241–254.

    Article  Google Scholar 

  31. Singh, J., & Pandya, S. (1991). Exploring the effects of consumers’ dissatisfaction level on complaint behaviours. European Journal of Marketing, 25(9), 7–21.

    Article  Google Scholar 

  32. Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketing Science, 23(4), 545–560.

    Article  Google Scholar 

  33. Chiou, J. S., & Cheng, C. (2003). Should a company have message boards on its websites. Journal of Interactive Marketing, 17(3), 50–61.

    Article  Google Scholar 

  34. Arndt, J. (1967). Word of mouth advertising: A review of the literature. New York: Advertising Research Federation.

    Google Scholar 

  35. Fiske, H. (1980). A long/high view from a stationary geo satellite on project cost control. Engineering Costs & Production Economics, 5(2), 81–87.

    Article  Google Scholar 

  36. Skowronski, J. J., & Carlston, D. E. (1989). Negativity and extremity biases in impression formation: A review of explanations. Psychological Bulletin, 105(1), 131–142.

    Article  Google Scholar 

  37. Park, C., & Lee, T. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67.

    Article  Google Scholar 

  38. Sen, S., & Lerman, D. (2007). Why are you telling me this? An examination into negative consumer reviews on the Web. Journal of Interactive Marketing, 21(4), 76–94.

    Article  Google Scholar 

  39. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, New Jersey: Prentice-Hall Press.

    Google Scholar 

  40. Mowen, J. C., & Minor, M. (1998). Consumer behavior. New Jersey: Prentice-Hall.

    Google Scholar 

  41. Macinnis, H. (1997). Consumer behavior. New York: Houghton Mifflin Company.

    Google Scholar 

  42. Burzynski, M. H., & Bayer, D. J. (1977). The effect of positive and negative prior information on motion picture appreciations. Journal of Social Psychology, 101(2), 215–218.

    Article  Google Scholar 

  43. Banerjee, A. V. (1992). A simple model of herd behavior. Quarterly Journal of Economics, 107(3), 797–817.

    Article  Google Scholar 

  44. Lascu, D., & Zinkhan, G. (1999). Consumer conformity: review and applications for marketing theory and practice. Journal of Marketing Theory & Practice, 7(3), 1–12.

    Google Scholar 

  45. Bickart, B., & Schindler, R. M. (2001). Internet forums as influential sources of consumer information. Journal of Interactive Marketing, 15(3), 31–40.

    Article  Google Scholar 

  46. Hennig-Thurau, T., & Walsh, G. (2003). Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the internet. International Journal of Electronic Commerce, 8(2), 51–74.

    Google Scholar 

  47. Cameron, S. (1995). On the role of critics in the culture industry. Journal of Cultural Economics, 19(4), 321–331.

    Article  Google Scholar 

  48. Gershoff, A. D., Ashesh, M., & Anirban, M. (2003). Consumer acceptance of online agent advice: Extremity and positivity effects. Journal of Consumer Psychology, 13(1–2), 161–171.

    Article  Google Scholar 

  49. Mitchell, A. A., & Dacin, P. A. (1996). The assessment of alternative measures of consumer expertise. Journal of Consumer Research, 23(3), 219–239.

    Article  Google Scholar 

  50. Gilly, M. C., Graham, J. L., Wolfinbarger, M., & Yale, L. J. (1998). A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science, 26(2), 83–100.

    Article  Google Scholar 

  51. Weinberger, M. G., & Dillon, W. R. (1980). The effects of unfavorable product rating information. Advances in Consumer Research, 7(1), 528–532.

    Google Scholar 

  52. Assael, H. (1984). Consumer behavior and marketing action. Boston: Kent Publishing Company.

    Google Scholar 

  53. Wang, A. (2005). Integrating and comparing other’s opinions: The effects of third-party endorsements on online purchasing. Journal of Website Promotion, 1(1), 105–129.

    Article  Google Scholar 

  54. Ohanian, R. (1991). The impact of celebrity spokespersons’ perceived image on consumers’ intention to purchase. Journal of Advertising Research, 31(1), 46–54.

    Google Scholar 

  55. Kirmani, A., & Rao, A. R. (2000). No pain, no gain: A critical review of the literature on signaling unobservable product quality. Journal of Marketing, 64(2), 66–79.

    Article  Google Scholar 

  56. Hogarth, R. M., & Einhorn, H. J. (1992). Order effects in belief updating: The belief-adjustment model. Cognitive Psychology, 24(1), 1–55.

    Article  Google Scholar 

  57. Lavine, H., Borgida, E., & Sullivan, J. L. (2000). On the relationship between attitude involvement and attitude accessibility: Toward a cognitive-motivational model of political information processing. Political Psychology, 21(1), 81–106.

    Article  Google Scholar 

  58. Parasuraman, A. A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.

    Google Scholar 

  59. Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. New York: Springer-Verlag.

    Book  Google Scholar 

  60. Keng, C., Liao, T., & Yang, Y. (2012). The effects of sequential combinations of virtual experience, direct experience, and indirect experience: the moderating roles of need for touch and product involvement. Electronic Commerce Research, 12(2), 177–199.

    Article  Google Scholar 

  61. Park, C. W., & Young, S. M. (1986). Consumer response to television commercials: The impact of involvement and background music on brand attitudeformation. Journal of Marketing Research, 23(1), 11–24.

    Article  Google Scholar 

  62. Park, D., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125–148.

    Article  Google Scholar 

  63. Eckert, J. A., & Goldsby, T. J. (1997). Using the elaboration likelihood model to guide customer service-based segmentation. International Journal of Physical Distribution & Logistics Management, 27(9), 600–615.

    Article  Google Scholar 

  64. Anderson, N. H. (1981). Foundations of information integration theory. San Diego, CA: Academic Press.

    Google Scholar 

  65. Simonin, B. L., & Ruth, J. A. (1998). Is a company known by the company it keeps? Assessing the spillover effects of brand alliances on consumer brand attitudes. Journal of Marketing Research, 35(1), 30–42.

    Article  Google Scholar 

  66. Linton, J. M., & Petrovich, J. A. (1988). The application of the consumer information acquisition approach to movie selection: An exploratory study. Current Research in Film: Audiences, Economics, and Law, 4, 24–45.

    Google Scholar 

  67. Kaakinen, J. K., Hyona, J., & Keenan, J. M. (2003). How prior knowledge, WMC, and relevance of information affect eye fixations in expository text. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(3), 447–457.

    Google Scholar 

  68. Blackwell, R. D., Miniard, P. W., & Engel, J. F. (2001). Consumer Behavior. Fort Worth, TX: Harcourt College Publisher.

    Google Scholar 

  69. Holbrook, M. B., & Batra, R. (1987). Assessing the role of emotions as mediators of consumer responses to advertising. Journal of Consumer Research, 14(3), 404–420.

    Article  Google Scholar 

  70. Wortzel, L. (1979). Multivariate Analysis. Upper Saddle River, New Jersey: Prentice Hall.

    Google Scholar 

  71. Tormala, Z. (2011). Experts are more persuasive when they’re less certain. Harvard Business Review, 89(3), 32–33.

    Google Scholar 

  72. Kim, M. G., Chenya, W., & Mattila, A. S. (2010). The relationship between consumer complaining behavior and service recovery. International Journal of Contemporary Hospitality Management, 22(7), 975–991.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Business Administration, National Chin-Yi University of Technology, No. 57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung, 41170, Taiwan, ROC

    Wen-Chin Tsao

  2. No. 9, Aly. 123, Ln. 398, Sec. 4, Dongqi Rd., Dongshi Dist., Taichung, 423, Taiwan, ROC

    Wen-Chin Tsao

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Correspondence to Wen-Chin Tsao.

Appendix 1: A sample of experimental movie reviews (valence: positive/rating: five star)

Appendix 1: A sample of experimental movie reviews (valence: positive/rating: five star)

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Tsao, WC. Which type of online review is more persuasive? The influence of consumer reviews and critic ratings on moviegoers. Electron Commer Res 14, 559–583 (2014). https://doi.org/10.1007/s10660-014-9160-5

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