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위험지각과 소비자의 구매의도의 관계에 대한 온라인 구전정보의 시각적 단서의 조절효과

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

  • 안선영 (미국 워싱턴 컬리지 경영학과) ;
  • 홍정화 (미국 텍사스 주립대학교 타일러캠퍼스 경영마케팅학과)
  • 투고 : 2018.10.02
  • 심사 : 2018.11.20
  • 발행 : 2018.11.28

초록

본 연구는 온라인 판매자에 대한 위험지각이 소비자의 구매의도에 미치는 관계에 구전정보의 시각적 단서가 어떠한 조절효과를 미치는가를 검증하기 위한 목적으로 시행되었다. 본 연구는 긍정 혹은 부정적으로 나뉜 구전정보에 따라 시각단서의 조절효과 방향이 다를 것이라는 가설하에 2(위험지각: 고 vs. 저) X 2(시각적 단서: 유 vs. 무)의 두 실험연구가 진행되었다. 첫 번째 연구결과(n=123), 긍정적 구전정보에서의 시각적 단서는 위험지각이 소비자 구매의도에 미치는 부정적 영향을 줄여주는 것으로 밝혀졌다. 하지만 두 번째 연구결과(n=122), 부정적 구전정보에서의 시각적 단서는 위험지각이 소비자 구매의도에 미치는 영향을 더욱 강화해주는 것으로 검증되었다. 본 연구결과는 온라인 구전정보의 시각적 단서가 소비자 의사결정에 설득력을 높여줌을 시사하였다. 또한, 본 연구결과를 바탕으로 온라인 판매자에 대한 소비자의 위험지각이 높은 경우, 긍정적 부정적 구전정보의 시각단서를 어떻게 전략적으로 활용할 수 있을지에 대한 실무적 함의를 논의하였다.

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.

키워드

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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

참고문헌

  1. S. M. Forsythe & B. Shi. (2003). Consumer Patronage and Risk Perceptions in Internet Shopping. Journal of Business Research, 56(11), 867-875. https://doi.org/10.1016/S0148-2963(01)00273-9
  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. https://doi.org/10.1002/mar.20982
  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. https://doi.org/10.1016/j.dss.2012.06.008
  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. https://doi.org/10.1016/j.elerap.2007.11.004
  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. https://doi.org/10.1002/dir.10073
  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. https://doi.org/10.1086/209001
  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. https://doi.org/10.1016/j.elerap.2007.05.004
  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. https://doi.org/10.1016/j.jretai.2011.01.005
  10. F. A. Buttle. (1998). Word of Mouth: Understanding and Managing Referral Marketing. Journal of Strategic Marketing, 6(3), 241-254. https://doi.org/10.1080/096525498346658
  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. https://doi.org/10.1037/0033-2909.95.2.189
  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. https://doi.org/10.1016/j.jretconser.2006.02.006
  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. https://doi.org/10.1002/mar.20080
  14. L. R. Vijayasarathy & J. M. Jones. (2000). Print and Internet Catalog Shopping. Internet Research, 10(3), 191-202. https://doi.org/10.1108/10662240010331948
  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. https://doi.org/10.1108/14684520810923953
  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. https://doi.org/10.1080/10196780802044776
  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. https://doi.org/10.1111/1467-6451.00180
  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. https://doi.org/10.1037/0022-3514.39.1.2
  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. https://doi.org/10.1002/mar.20204
  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. https://doi.org/10.1108/17505931211241341
  23. J. Kisielius & B. Sternthal. (1986). Examining the Vividness Controversy: An Availability-Valence Interpretation. Journal of Consumer Research, 12(4), 418-431. https://doi.org/10.1086/208527
  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. https://doi.org/10.1177/002224379002700310
  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. https://doi.org/10.1002/mar.20660
  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. https://doi.org/10.1177/002224377601300313
  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. https://doi.org/10.1177/0092070304267551
  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. https://doi.org/10.1509/jmkr.41.2.197.28667
  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. https://doi.org/10.1080/10864415.2003.11044275
  31. B. Mittal & M. S. Lee. (1989). A Causal Model of Consumer Involvement. Journal of Economic Psychology, 10(3), 363-389. https://doi.org/10.1016/0167-4870(89)90030-5
  32. J. Cho & J. Lee. (2006). An Integrated Model of Risk and Risk-Reducing Strategies. Journal of Business Research, 59(1), 112-120. https://doi.org/10.1016/j.jbusres.2005.03.006
  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. https://doi.org/10.1016/j.tourman.2015.09.011
  34. S. J. Doh & J. S. Hwang. (2009). How Consumers Evaluate eWOM (Electronic Word-Of-Mouth) Messages. CyberPsychology & Behavior, 12(2), 193-197. https://doi.org/10.1089/cpb.2008.0109