The Moderating Effect of Visual Cues in eWOM on the Relationship between Perceived Risk and Purchase Intention

위험지각과 소비자의 구매의도의 관계에 대한 온라인 구전정보의 시각적 단서의 조절효과

  • 안선영 (미국 워싱턴 컬리지 경영학과) ;
  • 홍정화 (미국 텍사스 주립대학교 타일러캠퍼스 경영마케팅학과)
  • Received : 2018.10.02
  • Accepted : 2018.11.20
  • Published : 2018.11.28


The current study examined the moderating effect of visual cues in eWOM on the relationship between perceived risk and purchase intention. Specifically, the study tested the different directions of the moderating effect in positive and negative eWOM. Two studies from a 2 (perceived risk: high vs. low) by 2 (visual cue: presence vs. absence) experimental design were used with online subjects. Findings from study 1 (n=123) supported that visual cues in positive eWOM help to reduce the negative effect of perceived risk on purchase intention. However, study 2 (n=122) showed that visual cues in negative eWOM intensify the negative effect of perceived risk on purchase intention. The findings demonstrated that visual cues in eWOM influence consumers' decision under high risk conditions. We discussed findings of this study how visual cues in positive and negative eWOM can be strategically managed for new online sellers.


eWOM;Perceived Risk;Visual cues of eWOM;Purchase Intention;Online Seller

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Fig. 1. Conceptual model

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Fig. 2. Positive eWOM with visual cues

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Fig. 3. Interaction effect in positive eWOM

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Fig. 4. Interaction Effect in Negative eWOM


  1. S. M. Forsythe & B. Shi. (2003). Consumer Patronage and Risk Perceptions in Internet Shopping. Journal of Business Research, 56(11), 867-875.
  2. M. Hubert, M. Blut, C. Brock, C. Backhaus & T. Eberhardt. (2017). Acceptance of Smartphone‐Based Mobile Shopping: Mobile Benefits, Customer Characteristics, Perceived Risks, and the Impact of Application Context. Psychology & Marketing, 34(2), 175-194.
  3. D. S. Sundaram & C. Webster. (1999). The Role of Brand Familiarity on The Impact of Word-Of-Mouth Communication on Brand Evaluations. Advances in Consumer Research, 26, 664-670.
  4. C. M. Cheung & D. R. Thadani. (2012). The Impact of Electronic Word-Of-Mouth Communication: A Literature Analysis and Integrative Model. Decision Support Systems, 54(1), 461-470.
  5. D. H. Park & J. Lee. (2008). eWOM Overload and Its Effect on Consumer Behavioral Intention Depending on Consumer Involvement. Electronic Commerce Research and Applications, 7(4), 386-398.
  6. T. Hennig-Thurau, K. P. Gwinner, G. Walsh & D. D. Gremler. (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.
  7. D. D. Childers & M. J. Houston. (1984). Conditions for a Picture-Superiority Effect on Consumer Memory. Journal of Consumer Research, 11(2), 643-654.
  8. J. Lee, D. H. Park & I. Han. (2008). The Effect of Negative Online Consumer Reviews on Product Attitude: An Information Processing View. Electronic Commerce Research and Applications, 7(3), 341-352.
  9. A. Khare, L. I. Labrecque & A. K. Asare. (2011). The Assimilative and Contrastive Effects of Word-Of-Mouth Volume: An Experimental Examination of Online Consumer Ratings. Journal of Retailing, 87(1), 111-126.
  10. F. A. Buttle. (1998). Word of Mouth: Understanding and Managing Referral Marketing. Journal of Strategic Marketing, 6(3), 241-254.
  11. S. Tanford & S. Penrod. (1984). Social Influence Model: A Formal Integration of Research on Majority and Minority Influence Processes. Psychological Bulletin, 95(2), 189-225.
  12. D. Litter & D. Melanthiou. (2006). Consumer Perceptions of Risk and Uncertainty and the Implications for Behavior Towards Innovative Retail Services: The Case of Internet Banking. Journal of Retailing and Consumer Services, 13(6), 431-443.
  13. J. Park, S. J. Lennon & L. Stoel. (2005). On-Line Product Presentation: Effects on Mood, Perceived Risk, and Purchase Intention. Psychology and Marketing, 22(9), 695-719.
  14. L. R. Vijayasarathy & J. M. Jones. (2000). Print and Internet Catalog Shopping. Internet Research, 10(3), 191-202.
  15. H. H. Chang & S. W. Chen. (2008). The Impact of Online Store Environment Cues on Purchase Intention. Online Information Review, 32(6), 818-841.
  16. B. Dai, S. Forsythe & W. S. Kwon. (2014). The Impact of Online Shopping Experience on Risk Perceptions and Online Purchase Intentions: Does Product Category Matter?. Journal of Electronic Commerce Research, 15(1), 13-24.
  17. A. Davis & D. Khazanchi. (2008). An Empirical Study of Online Word of Mouth as a Predictor for Multi‐Product Category E‐Commerce Sales. Electronic markets, 18(2), 130-141.
  18. C. Cheng & M. K. Lee. (2008). Online Consumer Reviews: Does Negative Electronic Word-of-Mouth Hurt More? Americas Conference on Information Systems Proceedings, 143. Toronto, Canada.
  19. M. I. Melnik & J. Alm. (2002). Does a Seller's Ecommerce Reputation Matter? Evidence from ebay Auctions. The Journal of Industrial Economics, 50(3), 337-349.
  20. R. M. Reyes, W. C. Thompson & G. H. Bower. (1980). Judgmental Biases Resulting from Differing Availabilities of Arguments. Journal of Personality and Social Psychology, 39(1), 2-12.
  21. M. Kim & S. Lennon. (2008). The Effects of Visual and Verbal Information on Attitudes and Purchase Intentions in Internet Shopping. Psychology & Marketing, 25(2), 146-178.
  22. T. M. Lin, K. Y. Lu & J. J. Wu. (2012). The Effects of Visual Information in eWOM Communication. Journal of Research in Interactive Marketing, 6(1), 7-26.
  23. J. Kisielius & B. Sternthal. (1986). Examining the Vividness Controversy: An Availability-Valence Interpretation. Journal of Consumer Research, 12(4), 418-431.
  24. J. Kim, F. R. Kardes & P. M. Herr. (1991). Consumer Expertise and The Vividness Effect: Implication for Judgment and Inference. Advances in Consumer Research, 18, 90-93.
  25. D. Maheswaran & J. Meyers-Levy. (1990). The Influence of Message Framing and Issue Involvement. Journal of Marketing Research, 27(3), 361-367.
  26. P. F. Wu. (2013). In Search of Negativity Bias: An Empirical Study of Perceived Helpfulness of Online Reviews. Psychology & Marketing, 30(11), 971-984.
  27. W. H. Cummings & M. Venkatesan. (1976). Cognitive Dissonance and Consumer Behavior: A Review of The Evidence. Journal of Marketing Research, 13(3), 303-308.
  28. M. P. Conchar, G. M. Zinkhan, C. Peters & S. Olavarrieta. (2004). An Integrated Framework for the Conceptualization of Consumers' Perceived-Risk Processing. Journal of the Academy of Marketing Science, 32(4), 418-436.
  29. Z. Gurhan-Canli & R. Batra. (2004). When Corporate Image Affects Product Evaluations: The Moderating Role of Perceived Risk. Journal of Marketing Research, 41(2), 197-205.
  30. P. A. Pavlou. (2003). Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk With the Technology Acceptance Model. International Journal of Electronic Commerce, 7(3), 101-134.
  31. B. Mittal & M. S. Lee. (1989). A Causal Model of Consumer Involvement. Journal of Economic Psychology, 10(3), 363-389.
  32. J. Cho & J. Lee. (2006). An Integrated Model of Risk and Risk-Reducing Strategies. Journal of Business Research, 59(1), 112-120.
  33. B. A. Sparks, K. K. F. So & G. L. Bradley. (2016). Responding to Negative Online Reviews: The Effects of Hotel Responses on Customer Inferences of Trust and Concern. Tourism Management, 53, 74-85.
  34. S. J. Doh & J. S. Hwang. (2009). How Consumers Evaluate eWOM (Electronic Word-Of-Mouth) Messages. CyberPsychology & Behavior, 12(2), 193-197.