IDEAS home Printed from https://ideas.repec.org/a/ibn/ijbmjn/v12y2017i12p82.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/ijbm/article/download/70903/39334
    Download Restriction: no
    File URL: http://www.ccsenet.org/journal/index.php/ijbm/article/view/70903
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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, Frédéric 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Das, Gopal & Mukherjee, Amaradri & Smith, Ronn J., 2018. "The Perfect Fit: The Moderating Role of Selling Cues on Hedonic and Utilitarian Product Types," Journal of Retailing, Elsevier, vol. 94(2), pages 203-216.
    2. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print halshs-01923196, HAL.
    3. Agnieszka Zablocki & Bodo Schlegelmilch & Michael J. Houston, 2019. "How valence, volume and variance of online reviews influence brand attitudes," AMS Review, Springer;Academy of Marketing Science, vol. 9(1), pages 61-77, June.
    4. Bin Guo & Shasha Zhou, 2017. "What makes population perception of review helpfulness: an information processing perspective," Electronic Commerce Research, Springer, vol. 17(4), pages 585-608, December.
    5. Oksana Loginova, 2008. "Exposure Order Effects and Advertising Competition," Working Papers 0806, Department of Economics, University of Missouri.
    6. Davis, Robert & Smith, Sandra D. & Lang, Bodo U., 2017. "A comparison of online and offline gender and goal directed shopping online," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 118-125.
    7. Wang, Fang & Du, Zhao & Wang, Shan, 2023. "Information multidimensionality in online customer reviews," Journal of Business Research, Elsevier, vol. 159(C).
    8. Park, Tae-Youn & Kim, Seongsu & Sung, Li-Kuo, 2017. "Fair pay dispersion: A regulatory focus theory view," Organizational Behavior and Human Decision Processes, Elsevier, vol. 142(C), pages 1-11.
    9. Munzel, Andreas, 2016. "Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 96-108.
    10. Koller, Monika & Floh, Arne & Zauner, Alexander & Rusch, Thomas, 2013. "Persuasibility and the self – Investigating heterogeneity among consumers," Australasian marketing journal, Elsevier, vol. 21(2), pages 94-104.
    11. Takumi Kato, 2022. "Rating valence versus rating distribution: perceived helpfulness of word of mouth in e-commerce," SN Business & Economics, Springer, vol. 2(11), pages 1-24, November.
    12. Ray, Arghya & Bala, Pradip Kumar & Rana, Nripendra P., 2021. "Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach," Journal of Business Research, Elsevier, vol. 128(C), pages 391-404.
    13. King, Robert Allen & Racherla, Pradeep & Bush, Victoria D., 2014. "What We Know and Don't Know About Online Word-of-Mouth: A Review and Synthesis of the Literature," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 167-183.
    14. Loginova, Oksana, 2009. "Exposure order effects and advertising competition," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 528-538, August.
    15. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    16. Xu, Xun, 2020. "Examining an asymmetric effect between online customer reviews emphasis and overall satisfaction determinants," Journal of Business Research, Elsevier, vol. 106(C), pages 196-210.
    17. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Grenoble Ecole de Management (Post-Print) halshs-01923196, HAL.
    18. McKay-Nesbitt, Jane & Bhatnagar, Namita & Smith, Malcolm C., 2013. "Regulatory fit effects of gender and marketing message content," Journal of Business Research, Elsevier, vol. 66(11), pages 2245-2251.
    19. Filieri, Raffaele, 2015. "What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM," Journal of Business Research, Elsevier, vol. 68(6), pages 1261-1270.
    20. Xu, Yunjie (Calvin) & Kim, Hee-Woong, 2008. "Order Effect and Vendor Inspection in Online Comparison Shopping," Journal of Retailing, Elsevier, vol. 84(4), pages 477-486.

    More about this item

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ijbmjn:v:12:y:2017:i:12:p:82. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.