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Asymmetric Persuasive Effects of Gain- and Loss-related Messages in Electronic Word of Mouth

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  • Heejae Shin
  • Wirawan Dahana

Abstract

This study examines the aggregate effect of electronic word mouth (eWOM) communications containing multiple messages of different type on brand attitude. It focuses on the moderating role of individuals’ regulatory focus and message proportion in influencing the extent to which consumers respond to gain- and loss-related messages. We develop some hypotheses regarding the interplay between the constructs, and test them through two web-based experimental studies on online product reviews. In study 1, we examine the persuasiveness of four different reviews composed of several combinations of gain- and loss-related messages. In study 2, we modify the proportion of positive and negative messages to examine how the impact of eWOM is affected by disproportionate message structure. The results reveal that different combinations of message types lead to different evaluation of the focal brand. Furthermore, subjects with different regulatory focus exhibit different attitudes toward the focal brand when exposed to the same message combination. In addition, the moderating effects of regulatory focus appear to be altered by eWOM message proportion. Theoretical and managerial implications of this study are discussed.

Suggested Citation

  • Heejae Shin & Wirawan Dahana, 2017. "Asymmetric Persuasive Effects of Gain- and Loss-related Messages in Electronic Word of Mouth," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(12), pages 1-82, November.
    • Handle: RePEc:ibn:ijbmjn:v:12:y:2017:i:12:p:82
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    References listed on IDEAS

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    1. Haugtvedt, Curtis P & Wegener, Duane T, 1994. "Message Order Effects in Persuasion: An Attitude Strength Perspective," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 205-218, June.
    2. Brunel, Frã‰Dã‰Ric F. & Nelson, Michelle R., 2003. "Message Order Effects and Gender Differences in Advertising Persuasion," Journal of Advertising Research, Cambridge University Press, vol. 43(3), pages 330-341, September.
    3. Efraim Turban & David King & Jae Kyu Lee & Ting-Peng Liang & Deborrah C. Turban, 2015. "Marketing and Advertising in E-Commerce," Springer Texts in Business and Economics, in: Electronic Commerce, edition 0, chapter 9, pages 403-456, Springer.
    4. Rajagopal, 2015. "Consumer Value Management," Palgrave Macmillan Books, in: The Butterfly Effect in Competitive Markets, chapter 5, pages 119-143, Palgrave Macmillan.
    5. East, Robert & Hammond, Kathy & Lomax, Wendy, 2008. "Measuring the impact of positive and negative word of mouth on brand purchase probability," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 215-224.
    6. Garbarino, Ellen & Strahilevitz, Michal, 2004. "Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation," Journal of Business Research, Elsevier, vol. 57(7), pages 768-775, July.
    7. Halamish, Vered & Liberman, Nira & Higgins, E. Tory & Idson, Lorraine Chen, 2008. "Regulatory focus effects on discounting over uncertainty for losses vs. gains," Journal of Economic Psychology, Elsevier, vol. 29(5), pages 654-666, November.
    8. Pan, Yue & Zhang, Jason Q., 2011. "Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews," Journal of Retailing, Elsevier, vol. 87(4), pages 598-612.
    9. Gupta, Pranjal & Harris, Judy, 2010. "How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective," Journal of Business Research, Elsevier, vol. 63(9-10), pages 1041-1049, September.
    10. Aaker, Jennifer L & Lee, Angela Y, 2001. ""I" Seek Pleasures and "We" Avoid Pains: The Role of Self-Regulatory Goals in Information Processing and Persuasion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(1), pages 33-49, June.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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