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Mitigating risk in ecommerce transactions: perceptions of information credibility and the role of user-generated ratings in product quality and purchase intention

Abstract

Although extremely popular, electronic commerce environments often lack information that has traditionally served to ensure trust among exchange partners. Digital technologies, however, have created new forms of “electronic word-of-mouth,” which offer new potential for gathering credible information that guides consumer behaviors. We conducted a nationally representative survey and a focused experiment to assess how individuals perceive the credibility of online commercial information, particularly as compared to information available through more traditional channels, and to evaluate the specific aspects of ratings information that affect people’s attitudes toward ecommerce. Survey results show that consumers rely heavily on web-based information as compared to other channels, and that ratings information is critical in the evaluation of the credibility of online commercial information. Experimental results indicate that ratings are positively associated with perceptions of product quality and purchase intention, but that people attend to average product ratings, but not to the number of ratings or to the combination of the average and the number of ratings together. Thus suggests that in spite of valuing the web and ratings as sources of commercial information, people use ratings information suboptimally by potentially privileging small numbers of ratings that could be idiosyncratic. In addition, product quality is shown to mediate the relationship between user ratings and purchase intention. The practical and theoretical implications of these findings are considered for ecommerce scholars, consumers, and vendors.

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References

  1. 1.

    Aldás-Manzano, J., Currás-Pérez, R., & Sanz-Blas, S. (2011). Online information quality as determinant of perceived risk reduction in e-commerce:An application to apparel virtual stores. International Journal of Internet Marketing and Advertising, 6(4), 352. doi:10.1504/IJIMA.2011.043656.

  2. 2.

    Arndt, J. (1968). Selective processes in word of mouth. Journal of Advertising Research, 8(3), 19–22.

  3. 3.

    Bae, S., & Lee, T. (2010). Gender differences in consumers’ perception of online consumer reviews. Electronic Commerce Research, 11(2), 201–214. doi:10.1007/s10660-010-9072-y.

  4. 4.

    Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. doi:10.1037/0022-3514.51.6.1173.

  5. 5.

    Bauer, R. (1960). Consumer behavior as risk taking. Dynamic marketing for a changing world (p. 398). Chicago, IL: American Marketing Association.

  6. 6.

    Belanger, F., Hiller, J. S., & Smith, W. J. (2002). Trustworthiness in electronic commerce: The role of privacy, security, and site attributes. The Journal of Strategic Information Systems, 11(3–4), 245–270. doi:10.1016/S0963-8687(02)00018-5.

  7. 7.

    Bennett, P., & Mandell, R. (1969). Prepurchase information seeking behavior of new car purchasers: The learning hypothesis. Journal of Marketing Research, 6(4), 430–433.

  8. 8.

    Bettman, J. (1973). Perceived risk and its components: A model and empirical test. Journal of Marketing Research, 10(2), 184–190.

  9. 9.

    Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992–1026.

  10. 10.

    Census Bureau. (2010). Statistical abstract of the United States. Washington, DC.

  11. 11.

    Chaiken, S. (1987). The heuristic model of persuasion. In M. P. Zanna, J. M. Olson, & C. P. Herman (Eds.), Social influence: The Ontario symposium (Vol. 5, pp. 3–39). Hillsdale, NJ: Erlbaum.

  12. 12.

    Chaiken, S., Liberman, A., & Eagly, A. H. (1989). Heuristic and systematic information processing within and beyond the persuasion context. In J. S. Uleman & J. A. Bargh (Eds.), Unintended thought (pp. 212–252). New York: Guilford Press.

  13. 13.

    Chaiken, S., Wood, W., & Eagly, A. H. (1996). Principles of persuasion. In E. T. Higgins & A. Kruglanski (Eds.), Social psychology: Handbook of basic mechanisms and processes. New York: Guilford Press.

  14. 14.

    Chang, T.-Z., & Wildt, A. (1994). Price, product information, and purchase intention: An empirical study. Journal of the Academy of Marketing Science, 22(1), 16–27. doi:10.1177/0092070394221002.

  15. 15.

    Chen, P., Dhanasobhon, S., & Smith, M. (2007). All reviews are not created equal: The disaggregate impact of reviews and reviewers at amazon. Com. Paper presented at the Carnegie Mellon Research Showcase.

  16. 16.

    Chen, P., Wu, S., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales. In Proceedings of the international conference on information systems (ICIS-04), pp. 711–724.

  17. 17.

    Cheng, X., & Zhou, M. (2010). Empirical study on credibility of electronic word of mouth. Proceedings of the 2010 international conference on management and service science (MASS), pp. 1–4.

  18. 18.

    Cheung, C. M. K., Lee, M. K. O., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18, 229–247. doi:10.1108/10662240810883290.

  19. 19.

    Cheung, C. M. K., & Thadani, D. R., (2010). The state of electronic word-of-mouth research: A literature analysis. PACIS 2010 Proceedings. Paper 151.

  20. 20.

    Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research (JMR), 43(3), 345–354. doi:10.1509/jmkr.43.3.345.

  21. 21.

    Cosley, D., Lam, S. K., Albert, I., Konstan, J. A., & Riedl, J. (2003). Is seeing believing? How recommender system interfaces affect users’ opinions. Presented at the SIGCHI conference on Human Factors in Computing Systems.

  22. 22.

    Cox, D., & Rich, S. (1964). Perceived risk and consumer decision-making: The case of telephone shopping. Journal of Marketing Research, 1(4)32–39.

  23. 23.

    Danielson, D. R. (2005). Web credibility. In C. Ghaoui (Ed.), Encyclopedia of human-computer interaction (pp. 713–721). Hersey, PA: Idea Group.

  24. 24.

    De Maeyer, P. D. (2012). Impact of online consumer reviews on sales and price strategies: A review and directions for future research. Journal of Product & Brand Management, 21(2), 132–139. doi:10.1108/10610421211215599.

  25. 25.

    Dellarocas, C., & Wood, C. A. (2008). The sound of silence in online feedback: Estimating trading risks in the presence of reporting bias. Management Science, 54(3), 460–473.

  26. 26.

    Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. The Journal of Abnormal and Social Psychology, 51(3), 629–636. doi:10.1037/h0046408.

  27. 27.

    Dhar, V., & Chang, E. A. (2009). Does chatter matter? The impact of user-generated content on music sales. Journal of Interactive Marketing, 23(4), 300–307. doi:10.1016/j.intmar.2009.07.004.

  28. 28.

    Dodds, W. B., & Monroe, K. B. (1985). The effect of brand and price information on subjective product evaluations. Advances in Consumer Research, 12, 85–90.

  29. 29.

    Doh, S.-J., & Hwang, J.-S. (2009). How Consumers Evaluate eWOM (Electronic Word-of-Mouth) Messages. CyberPsychology & Behavior, 12, 193–197. doi:10.1089/cpb.2008.0109.

  30. 30.

    Duan, W., Gu, B., & Whinston, A. (2008). Do online reviews matter?—An empirical investigation of panel data. Decision Support Systems, 45(4), 1007–1016.

  31. 31.

    Duan, W., Gu, B., & Whinston, A. B. (2009). Informational cascades and software adoption on the Internet: An empirical investigation. MIS, 33(1), 23–48.

  32. 32.

    Easley, D., & Kleinberg, J. (2010). Chapter 19: Cascading behavior in networks. Networks, crowds, and markets: Reasoning about a highly connected world (pp. 563–609). Cambridge: Cambridge University Press.

  33. 33.

    Egermann, H., Grewe, O., Kopiez, R., & Altenmüller, E. (2009). Social feedback influences musically induced emotions. Annals of the New York Academy of Sciences, 1169(1), 346–350. doi:10.1111/j.1749-6632.2009.04789.x.

  34. 34.

    Etzion, H., & Awad, N. (2007). Examining the relationship between number of online reviews and sales. Paper presented at the 2007 Conference on Information Systems and Technology (CIST). Seattle, WA.

  35. 35.

    Eysenbach, G. (2008). Credibility of health information and digital media: New perspective and implications for youth. In M. J. Metzger & A. J. Flanagin (Eds.), Digital media, youth, and credibility (pp. 123–154). Cambridge, MA: MIT Press.

  36. 36.

    Flanagin, A. (2007). Commercial markets as communication markets: Uncertainty reduction through mediated information exchange in online auctions. New Media & Society, 9, 401–423.

  37. 37.

    Flanagin, A., & Metzger, M. (2000). Perceptions of internet information credibility. Journalism and Mass Communication Quarterly, 77(3), 515–540.

  38. 38.

    Floh, A., Koller, M., & Zauner, A. (2009). The impact of perceived valence, perceived information credibility and valence intensity of online reviews on purchase intentions. Presented at the 9th International Conference on Electronic Business, Macau.

  39. 39.

    Fogg, B. J. (2003). Computers as persuasive social actors. In B. Fogg’s (Ed.), Persuasive technology: Using computers to change what we think and do (pp. 31–60). San Francisco, CA: Morgan Kaufmann.

  40. 40.

    Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291–313.

  41. 41.

    Gregg, D. G., & Walczak, S. (2010). The relationship between website quality, trust and price premiums at online auctions. Electronic Commerce Research, 10(1), 1–25.

  42. 42.

    Ha, H. (2002). The effects of consumer risk perception on pre purchase information in online auctions: Brand, word of mouth, and customized information. Journal of Computer Mediated Communication, 8(1).

  43. 43.

    Hawes, J., & Lumpkin, J. (1986). Perceived risk and the selection of a retail patronage mode. Journal of the Academy of Marketing Science, 14(4), 37–42.

  44. 44.

    Herr, P., Kardes, F., & Kim, J. (1991). Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective. Journal of Consumer Research, 17(4), 454–462.

  45. 45.

    Horrigan, J. (2008a). The internet and consumer choice. Pew Internet & American Life Project report Retrieved June 8, 2010, from http://www.pewinternet.org/Reports/2008/The-Internet-and-Consumer-Choice.aspx

  46. 46.

    Horrigan, J. (2008b). Online shopping. Pew Internet and American Life Project report Retrieved June 8, 2010, from http://www.pewinternet.org/Reports/2008/Online-Shopping.aspx

  47. 47.

    Hu, N., Liu, L., & Zhang, J. (2008). Do online reviews affect product sales? The role of reviewer characteristics and temporal effects. Information Technology and Management, 9(3), 201–214.

  48. 48.

    Hu, N., Pavlou, P., & Zhang, J. (2006). Can online reviews reveal a product’s true quality?: Empirical findings and analytical modeling of online word-of-mouth communication. Paper presented at the Conference on Electronic Commerce, Ann Arbor, Michigan.

  49. 49.

    Huberman, B. A., & Asur, S. (2010). Predicting the future with social media. Whitepaper, Palo Alto, CA: HP Labs.

  50. 50.

    Jalilvand, M. R., & Samiei, N. (2012). The effect of electronic word of mouth on brand image and purchase intention. Marketing Intelligence & Planning, 30(4), 460–476.

  51. 51.

    Jansen, J. (2010). Online product research. Pew Internet & American Life Project. Retrieved from http://www.pewinternet.org/Reports/2010/Online-Product-Research.aspx.

  52. 52.

    Kato, Y., Kurohashi, S., & Inui, K. (2008). Information credibility on the web. Internet Research, 18(2), 204–205.

  53. 53.

    Klein, T. J., Lambertz, C., Spagnolo, G., & Stahl, K. O. (2006). Last Minute Feedback. SSRN eLibrary. Retrieved from http://ssrn.com/paper=921876

  54. 54.

    Lange, C., Rousseau, F., & Issanchou, S. (1998). Expectation, liking, and purchase behavior under economical constraint. Food Quality and Preference, 10(1), 31–39.

  55. 55.

    Lee, J., & Lee, J.-N. (2009). Understanding the product information inference process in electronic word-of-mouth: An objectivity-subjectivity dichotomy perspective. Information & Management, 46(5), 302–311.

  56. 56.

    Lee, J., Park, D.-H., & Han, I. (2011). The different effects of online consumer reviews on consumers’ purchase intentions depending on trust in online shopping malls: An advertising perspective. Internet Research, 21(2), 187–206. doi:10.1108/10662241111123766.

  57. 57.

    Lee, S. (2009). How do online reviews affect purchasing intention? African Journal of Business Management, 3(10), 576–581.

  58. 58.

    Lee, Z., Im, I., & Lee, S. (2000). The effect of negative buyer feedback on auction prices in internet auction markets. Paper presented at the 21st International Conference on Information systems, Brisbane, Australia.

  59. 59.

    Lim, N. (2003). Consumers’ perceived risk: Sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216–228.

  60. 60.

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

  61. 61.

    Locander, W., & Hermann, P. (1979). The effect of self-confidence and anxiety on information seeking in consumer risk reduction. Journal of Marketing Research, 16(2), 268–274.

  62. 62.

    Lopez-Nicolas, C., & Monlina-Castillo, F. J. (2008). Customer knowledge management and e-commerce: The role of customer perceived risk. International Journal of Information Management, 28(2), 102–113.

  63. 63.

    Mackiewicz, J. (2007). Reviewer bias and credibility in online reviews. Paper presented at the Association for Business Communication Annual Convention.

  64. 64.

    Mascha, M. F., Miller, C. L., & Janvrin, D. J. (2011). The effect of encryption on Internet purchase intent in multiple vendor and product risk settings. Electronic Commerce Research, 11(4), 401–19.

  65. 65.

    Metzger, M. J. (2007). Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research. Journal of the American Society for Information Science and Technology, 58(13), 2078–2091. doi:10.1002/asi.20672.

  66. 66.

    Metzger, M., Flanagin, A., & Medders, R. (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60(3), 413–439.

  67. 67.

    Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & McCann, R. (2003). Credibility in the 21st century: Integrating perspectives on source, message, and media credibility in the contemporary media environment. In P. Kalbfeisch (Ed.), Communication Yearbook 27 (pp. 293–335). Mahwah, NJ: Lawrence Erlbaum.

  68. 68.

    Miyazaki, A., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer Affairs, 35, 27–44.

  69. 69.

    Moskowitz, H. R. (1995). The dollar value of product quality: The effect of pricing versus overall liking on consumer stated purchase intent for pizza. Journal of Sensory Studies, 4, 239–247.

  70. 70.

    Mueller, S., & Szolnoki, G. (2010). The relative influence of packaging, labeling, branding and sensory attributes on liking and purchase intent: Consumers differ in their responsiveness. Food Quality and Preference, 21(7), 774–83.

  71. 71.

    Napolitano, F., Braghieri, A., Piasentier, E., Favotto, S., Naspetti, S., & Zanoli, R. (2010). Effect of information about organic production on beef liking and consumer willingness to pay. Food Quality and Preference, 21(2), 207–12.

  72. 72.

    Papaioannou, T. G., & Stamoulis, G. D. (2010). A mechanism that provides incentives for truthful feedback in peer-to-peer systems. Electronic Commerce Research, 10(3–4), 331–362. doi:10.1007/s10660-010-9059-8.

  73. 73.

    Parasuraman, A., Zeithaml, V., & Berry, L. (1996). The behavioral consequences of service quality. Journal of Marketing, 60, 31–46.

  74. 74.

    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.

  75. 75.

    Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: Classic and contemporary approaches. Dubuque, IA: Brown.

  76. 76.

    Rao, A. R., & Monroe, K. B. (1989). The effect of price, brand name, and store name on buyers’ perceptions of product quality: An integrative review. Journal of Marketing Research, 26(3), 351–357.

  77. 77.

    Reichheld, F. (2003). The one number you need to grow. Harvard Business Review, 81(12), 46–55.

  78. 78.

    Render, B., & O’Connor, T. S. (1976). The influence of price, store name, and brand name on perception of product quality. Journal of the Academy of Marketing Science, 4(4), 722–730.

  79. 79.

    Resnick, P., & Zeckhauser, R. (2002). Trust among strangers in internet transactions: Empirical analysis of eBay’s reputation system. In M. Bayne (Ed.), Advances in applied microeconomics: A research annual (Vol. 11, pp. 127–157). Amsterdam: Elsevier Science.

  80. 80.

    Richins, M. (1983). Negative word-of-mouth by dissatisfied consumers: A pilot study. The Journal of Marketing, 47(1), 68–78.

  81. 81.

    Rieh, S. Y., & Danielson, D. R. (2007). Credibility: A multidisciplinary framework. In B. Cronin (Ed.), Annual review of information science and technology, Vol. 41. (pp. 307–364). Medford, NJ: Information Today.

  82. 82.

    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), 301–30.

  83. 83.

    Samadi, M., & Yaghoob-Nejadi, A. (2009). A survey of the effect of consumers’ perceived risk on purchase intention in e-shopping. Business Intelligence Journal, 2(2), 261–275.

  84. 84.

    Sheth, J., & Venkatesan, M. (1968). Risk-reduction processes in repetitive consumer behavior. Journal of Marketing Research, 5(3), 307–310.

  85. 85.

    Steffes, E. M., & Burgee, L. E. (2009). Social ties and online word of mouth. Internet Research, 19(1), 42–59. doi:10.1108/10662240910927812.

  86. 86.

    Taylor, J. (1974). The role of risk in consumer behavior. The Journal of Marketing, 38(2), 54–60.

  87. 87.

    Wolf, J. R., & Muhanna, W. A. (2011). Feedback mechanisms, judgment bias, and trust formation in online auctions. Decision Sciences, 42, 43–68. doi:10.1111/j.1540-5915.2010.00301.x.

  88. 88.

    Wu, P. C. S., & Wang, Y.-C. (2011). The influences of electronic word-of-mouth message appeal and message source credibility on brand attitude. Asia Pacific Journal of Marketing and Logistics, 23(4), 448–472. doi:10.1108/13555851111165020.

  89. 89.

    Ye, Q., Law, R., & Gu, B. (2009). The impact of online user reviews on hotel room sales. International Journal of Hospitality Management, 28(1), 180–182. doi:10.1016/j.ijhm.2008.06.011.

  90. 90.

    Zhang, K. Z. K., Lee, M. K. O., & Zhao, S. J. (2010). Understanding the informational social influence of online review platforms. ICIS 2010 Proceedings. Paper 71.

  91. 91.

    Zhu, H., Huberman, B., & Luon, Y. (2011). To switch or not to switch: Understanding social influence in recommender systems. Retrieved from http://arxiv.org/abs/1108.5147

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Acknowledgments

The authors thank the John D. and Catherine T. MacArthur Foundation for their generous support of this work.

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Correspondence to Andrew J. Flanagin.

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Flanagin, A.J., Metzger, M.J., Pure, R. et al. Mitigating risk in ecommerce transactions: perceptions of information credibility and the role of user-generated ratings in product quality and purchase intention. Electron Commer Res 14, 1–23 (2014). https://doi.org/10.1007/s10660-014-9139-2

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Keywords

  • Ecommerce
  • Credibility
  • User-generated content
  • Amazon
  • Product ratings
  • Electronic word of mouth
  • Information credibility
  • Purchase intention
  • Product quality
  • User ratings