Electronic Commerce Research

, Volume 19, Issue 1, pp 159–187 | Cite as

Negative online reviews of popular products: understanding the effects of review proportion and quality on consumers’ attitude and intention to buy

  • Muhammad Rifki ShihabEmail author
  • Audry Pragita Putri


This study investigated the effects of negative online reviews on consumers’ attitude and purchase intention, more specifically in relation to popular products. The investigation took into account the proportion of negative online reviews (low and high) and their quality (low and high), as well as comparing their impact in relation to popular and unpopular products. As a control variable, a website was purposely developed to suit eight different experimental treatments and their manipulations. This study involved 382 participants, who were exposed to the specially created website and asked to perform a specific task. Their responses were captured via questionnaires. The results showed that consumers’ positive attitude to popular products decreased as the proportion of negative online reviews increased. The quality of reviews was found to have a less significant influence on consumer responses. Furthermore, this research revealed that unpopular products were more affected by negative online reviews than popular ones.


Negative online review Popular product Attitude Purchase intention 


Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


  1. 1.
    Lee, J., Park, D. H., & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7(3), 341–352. Scholar
  2. 2.
    Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. Journal of Marketing, 73(5), 90–102. Scholar
  3. 3.
    Park, D. H., & Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications, 7(4), 399–410. Scholar
  4. 4.
    Schlosser, A. E. (2011). Can including pros and cons increase the helpfulness and persuasiveness of online reviews? The interactive effects of ratings and arguments. Journal of Consumer Psychology, 21(3), 226–239. Scholar
  5. 5.
    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. Scholar
  6. 6.
    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. Scholar
  7. 7.
    Chan, Y. Y. Y., & Ngai, E. W. T. (2011). Conceptualising electronic word of mouth activity: An input-process-output perspective. Marketing Intelligence & Planning, 29(5), 488–516. Scholar
  8. 8.
    Cheung, C. M. K., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461–470. Scholar
  9. 9.
    Dholakia, R. R., & Sternthal, B. (1977). Highly credible sources: Persuasive facilitators or persuasive liabilities? Journal of Consumer Research, 3(4), 223. Scholar
  10. 10.
    Herr, P. M., Kardes, F. R., & Kim, J. (1991). Effects of word-of-mouth and on product—An attribute persuasion: Perspective. Journal of Consumer Research, 17(March), 454–462.Google Scholar
  11. 11.
    Sternthal, B., Phillips, L. W., & Dholakia, R. (1978). The persuasive effect of source credibility: A situational analysis. Public Opinion Quarterly, 42(3), 285–314. Scholar
  12. 12.
    Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. Management Science, 54(3), 477–491. Scholar
  13. 13.
    Skowronski, J. J., & Carlston, D. E. (1987). Social judgment and social memory: The role of cue diagnosticity in negativity, positivity, and extremity biases. Journal of Personality and Social Psychology, 52(4), 689–699. Scholar
  14. 14.
    Bailey, A. A. (2004). The use of the Internet in negative consumer-to-consumer articulations. Journal of Marketing Communications, 10(3), 169–182. Scholar
  15. 15.
    Xia, L., & Bechwati, N. N. (2008). Word of Mouse: The role of cognitive personalization in online consumer reviews. Journal of Interactive Advertising, 9(1), 3–13. Scholar
  16. 16.
    See-To, E. W. K., & Ho, K. K. W. (2014). Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust—A theoretical analysis. Computers in Human Behavior, 31(1), 182–189. Scholar
  17. 17.
    Hsieh, Y. C., Chiu, H. C., & Chiang, M. Y. (2005). Maintaining a committed online customer: A study across search-experience-credence products. Journal of Retailing, 81(1), 75–82. Scholar
  18. 18.
    Jiménez, F. R., & Mendoza, N. A. (2013). Too popular to ignore: The influence of online reviews on purchase intentions of search and experience products. Journal of Interactive Marketing, 27(3), 226–235. Scholar
  19. 19.
    Lu, L. C., Chang, W. P., & Chang, H. H. (2014). Consumer attitudes toward blogger’s sponsored recommendations and purchase intention: The effect of sponsorship type, product type, and brand awareness. Computers in Human Behavior, 34, 258–266. Scholar
  20. 20.
    Mudambi, S. M., & Schuff, D. (2010). What makes a helpful review? A study of customer reviews on MIS Quarterly, 34(1), 185–200. Retrieved from
  21. 21.
    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. Scholar
  22. 22.
    Cui, J., Pan, Y., & Wang, L. (2012). Impact of online review on sales: An empirical investigation of experience products with different popularities. In Proceedings2012 international conference on management of e-Commerce and e-Government, ICMeCG 2012 (pp. 48–53).
  23. 23.
    Bolton, G. E., Katok, E., & Ockenfels, A. (2004). How effective are electronic reputation mechanisms? An experimental investigation. Management Science, 50(11), 1587–1602. Scholar
  24. 24.
    Pavlou, P. A., & Gefen, D. (2004). Building effective online marketplaces with institution-based trust. Information Systems Research. Scholar
  25. 25.
    Caminal, R., & Vives, X. (1996). Why market shares matter: An information-based theory. The Rand Journal of Economics, 27(2), 221–239. Scholar
  26. 26.
    Chen, P.-Y., Wu, S., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales. In Twenty-fifth international conference on information systems (pp. 711–723). Retrieved from
  27. 27.
    Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(March), 133–148. Retrieved from
  28. 28.
    Kanouse, D. E., & Hanson Jr., R. L. (1972). Negativity in evaluations. In E. E. Jones, D. E. Kanouse, H. H. Kelley, R. E. Nisbett, S. Valins & B. Weiner (Eds.), Attribution: Perceiving the causes of behavior (pp. 47–62). Hillsdale: Lawrence Erlbaum Associates, Inc.Google Scholar
  29. 29.
    Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–292. Scholar
  30. 30.
    Filieri, R. (2015). What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research, 68(6), 1261–1270. Scholar
  31. 31.
    Park, D.-H., 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. Scholar
  32. 32.
    Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530–545. Scholar
  33. 33.
    Ives, B., Olson, M., & Baroudi, J. (1983). The measurement of user information satisfaction. Communications of the ACM, 26(10), 785–793. Scholar
  34. 34.
    Wang, R. Y. W., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Source Journal of Management Information Systems, 12(4), 5–33. Scholar
  35. 35.
    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(3), 229–247. Scholar
  36. 36.
    Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10(2), 135–146. Scholar
  37. 37.
    Benedicktus, R. L., Brady, M. K., Darke, P. R., & Voorhees, C. M. (2010). Conveying trustworthiness to online consumers: Reactions to consensus, physical store presence, brand familiarity, and generalized suspicion. Journal of Retailing, 86(4), 310–323. Scholar
  38. 38.
    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. Scholar
  39. 39.
    Pan, Y., & Zhang, J. Q. (2011). Born unequal: A study of the helpfulness of user-generated product reviews. Journal of Retailing, 87(4), 598–612. Scholar
  40. 40.
    Maryanchyk, I. (2008). Are ratings informative signals? The analysis of the netflix data. NET Institute working paper no. 08-22, (October), pp. 1–40. Retrieved from
  41. 41.
    DeSarbo, W. S., Kim, J., Choi, S. C., & Spaulding, M. (2002). A gravity-based multidimensional scaling model for deriving spatial structures underlying consumer preference/choice judgments. Journal of Consumer Research, 29(1), 91–100. Scholar
  42. 42.
    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. Scholar
  43. 43.
    MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of Marketing Research, 23(2), 130–143. Scholar
  44. 44.
    Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research (Vol. 480). Reading, MA: Addison Wesley. Scholar
  45. 45.
    De Magistris, T., & Gracia, A. (2008). The decision to buy organic food products in Southern Italy. British Food Journal, 110(9), 929–947. Scholar
  46. 46.
    Spears, N., & Singh, S. N. (2004). Measuring attitude toward the brand and purchase intentions. Journal of Current Issues & Research in Advertising, 26(2), 53–66. Scholar
  47. 47.
    Wu, P. C. S., Yeh, G. Y. Y., & Hsiao, C. R. (2011). The effect of store image and service quality on brand image and purchase intention for private label brands. Australasian Marketing Journal, 19(1), 30–39. Scholar
  48. 48.
    Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.Google Scholar
  49. 49.
    Kim, D. J., Ferrin, D. L., & Raghav Rao, H. (2009). Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Information Systems Research, 20(2), 237–257. Scholar
  50. 50.
    Sia, C. L., Lim, K. H., Leung, K., Lee, M. K. O., Huang, W. W., & Benbasat, I. (2009). Web strategies to promote internet shopping: Is cultural-customization needed? MIS Quarterly, 33(3), 491–512.Google Scholar
  51. 51.
    Freedman, L. (2008). Merchant and customer perspectives on customer reviews and user-generated content.\_WhitePaper\_0204\_4.pdf.
  52. 52.
    Goh, Y. S. (2010). The influence of product-brand fit and product-category fit on product attitude and purchase intention: The role of brand strength and processing fluency. ProQuest dissertations and theses. Retrieved from
  53. 53.
    Lee, M., & Youn, S. (2009). Electronic word of mouth (eWOM). International Journal of Advertising, 28(3), 473–499. Scholar
  54. 54.
    Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill. Scholar
  55. 55.
    Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64. Scholar
  56. 56.
    Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104. Scholar
  57. 57.
    Gefen, D., & Straub, D. W. (2005). A practical guide to factorial validity using PLS-GRAPH:tutorial and annotated example. Communications of the Association for Information Systems, 16(5), 20. Retrieved from file:///F:/Mendeley/2005/Gefen/Gefen-2005-PLS-GRAPHTUTORIALANDANNOTATEDEXAMPLE.pdf.Google Scholar
  58. 58.
    Hair, J. F. J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Long Range Planning. Scholar
  59. 59.
    Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. Scholar
  60. 60.
    Zhu, L., Zhang, W., & Zhu., Y. (2012). Research on the influence of online reviews on internet consumer purchasing decision. In 2012 international conference on management of e-Commerce and e-Government (ICMeCG) (pp. 38–41). IEEE.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Computer ScienceUniversitas IndonesiaDepokIndonesia

Personalised recommendations