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This product works well (for me): The impact of first-person singular pronouns on online review helpfulness

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  • Wang, Fang
  • Karimi, Sahar

Abstract

Can linguistic choices of reviewers, such as using first-person singular pronouns (FPSP), affect readers' perception of information helpfulness? When sharing their purchase and consumption experiences, online reviewers tend to excessively use FPSP to refer to themselves. However, the effect of this language choice on readers' perception of information value is unknown. Drawing on communication and psycholinguistic literatures, this research theoretically develops and empirically analyzes the effects of the use of FPSP on perceived review helpfulness. The empirical results, based on a sample of 41,656 reviews from Amazon.com, suggest that the use of these pronouns has a negative impact on the perceived helpfulness of online reviews. In addition, such effects are moderated by review attributes such as length, valence and affective content, being more prominent for shorter reviews, reviews with lower valence and higher level of affect.

Suggested Citation

  • Wang, Fang & Karimi, Sahar, 2019. "This product works well (for me): The impact of first-person singular pronouns on online review helpfulness," Journal of Business Research, Elsevier, vol. 104(C), pages 283-294.
    • Handle: RePEc:eee:jbrese:v:104:y:2019:i:c:p:283-294
    DOI: 10.1016/j.jbusres.2019.07.028
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    as
    1. Ruiz-Mafe, Carla & Chatzipanagiotou, Kalliopi & Curras-Perez, Rafael, 2018. "The role of emotions and conflicting online reviews on consumers' purchase intentions," Journal of Business Research, Elsevier, vol. 89(C), pages 336-344.
    2. Karimi, Sahar & Holland, Christopher P. & Papamichail, K. Nadia, 2018. "The impact of consumer archetypes on online purchase decision-making processes and outcomes: A behavioural process perspective," Journal of Business Research, Elsevier, vol. 91(C), pages 71-82.
    3. Park, Cheol & Lee, Thae Min, 2009. "Information direction, website reputation and eWOM effect: A moderating role of product type," Journal of Business Research, Elsevier, vol. 62(1), pages 61-67, January.
    4. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    5. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    6. Perracchio, Laura A & Meyers-Levy, Joan, 1997. "Evaluating Persuasion-Enhancing Techniques from a Resource-Matching Perspective," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(2), pages 178-191, September.
    7. Aner Sela & S. Christian Wheeler & Gülen Sarial-Abi, 2012. "We Are Not the Same as You and I: Causal Effects of Minor Language Variations on Consumers' Attitudes toward Brands," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(3), pages 644-661.
    8. Huffman, Cynthia & Houston, Michael J, 1993. "Goal-Oriented Experiences and the Development of Knowledge," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(2), pages 190-207, September.
    9. Wang, Fang & Menon, Kalyani & Ranaweera, Chatura, 2018. "Dynamic trends in online product ratings: A diagnostic utility explanation," Journal of Business Research, Elsevier, vol. 87(C), pages 80-89.
    10. Burnkrant, Robert E & Unnava, H Rao, 1995. "Effects of Self-Referencing on Persuasion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(1), pages 17-26, June.
    11. repec:cup:judgdm:v:8:y:2013:i:3:p:372-380 is not listed on IDEAS
    12. Cheng, Yi-Hsiu & Ho, Hui-Yi, 2015. "Social influence's impact on reader perceptions of online reviews," Journal of Business Research, Elsevier, vol. 68(4), pages 883-887.
    13. Purnawirawan, Nathalia & Eisend, Martin & De Pelsmacker, Patrick & Dens, Nathalie, 2015. "A Meta-analytic Investigation of the Role of Valence in Online Reviews," Journal of Interactive Marketing, Elsevier, vol. 31(C), pages 17-27.
    14. Singh, Jyoti Prakash & Irani, Seda & Rana, Nripendra P. & Dwivedi, Yogesh K. & Saumya, Sunil & Kumar Roy, Pradeep, 2017. "Predicting the “helpfulness” of online consumer reviews," Journal of Business Research, Elsevier, vol. 70(C), pages 346-355.
    15. Mick, David Glen, 1992. "Levels of Subjective Comprehension in Advertising Processing and Their Relations to Ad Perceptions, Attitudes, and Memory," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(4), pages 411-424, March.
    16. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    17. Biswas, Dipayan, 2004. "Economics of information in the Web economy: Towards a new theory?," Journal of Business Research, Elsevier, vol. 57(7), pages 724-733, July.
    18. 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.
    19. 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.
    20. Schlosser, Ann E, 2003. "Experiencing Products in the Virtual World: The Role of Goal and Imagery in Influencing Attitudes versus Purchase Intentions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 184-198, September.
    Full references (including those not matched with items on IDEAS)

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    8. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    9. Baidyanath Biswas & Pooja Sengupta & Boudhayan Ganguly, 2022. "Your reviews or mine? Exploring the determinants of “perceived helpfulness” of online reviews: a cross-cultural study," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1083-1102, September.
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