IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v199y2025ics0148296325003868.html

User presence in online product reviews: The dual effects on purchase intention

Author

Listed:
  • Kou, Yan
  • Powpaka, Samart
  • Zhou, Lanlan
  • Huang, Jiangyu
  • Lu, Dong

Abstract

Consumers frequently post selfies featuring product usage in online product reviews. This research investigates the dual effects of user presence in product reviews (UPPR) on viewers’ purchase intention and the underlying psychological mechanisms. Through three experiments and an analysis of field data of 3,577 products, our findings revealed that UPPR influences purchase intention in two significant ways, enhancing sense of social presence while decreasing self-congruity. The net effect of UPPR on purchase intention is determined by the diagnosticity of the UPPR information. When UPPR is highly diagnostic, the negative impact of reduced self-congruity dominates, lowering purchase intentions. Conversely, when UPPR is low in diagnosticity, the positive effect of increased sense of social presence prevails, boosting purchase intentions. The findings provide significant theoretical insights into social influence and self-congruity construction in the digital world and offer crucial practical implications for electronic word-of-mouth marketing.

Suggested Citation

  • Kou, Yan & Powpaka, Samart & Zhou, Lanlan & Huang, Jiangyu & Lu, Dong, 2025. "User presence in online product reviews: The dual effects on purchase intention," Journal of Business Research, Elsevier, vol. 199(C).
  • Handle: RePEc:eee:jbrese:v:199:y:2025:i:c:s0148296325003868
    DOI: 10.1016/j.jbusres.2025.115563
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296325003868
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2025.115563?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Jennifer J. Argo & Darren W. Dahl & Rajesh V. Manchanda, 2005. "The Influence of a Mere Social Presence in a Retail Context," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(2), pages 207-212, September.
    2. T. Ravichandran & Chaoqun Deng, 2023. "Effects of Managerial Response to Negative Reviews on Future Review Valence and Complaints," Information Systems Research, INFORMS, vol. 34(1), pages 319-341, March.
    3. Kim, Do Yuon & Lee, Ha Kyung & Chung, Kyunghwa, 2023. "Avatar-mediated experience in the metaverse: The impact of avatar realism on user-avatar relationship," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    4. Sehgal, Nidhi & Jham, Vimi & Malhotra, Gunjan, 2023. "Does green brand anthropomorphism influence repurchase intention? Understanding the impact of brand warmth, psychological ownership, and self-brand congruity," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    5. Zhang, Mingyue & Zhao, Haichuan & Chen, Haipeng (Allan), 2022. "How much is a picture worth? Online review picture background and its impact on purchase intention," Journal of Business Research, Elsevier, vol. 139(C), pages 134-144.
    6. Townsend, Claudia & Neal, David T. & Morgan, Carter, 2019. "The impact of the mere presence of social media share icons on product interest and valuation," Journal of Business Research, Elsevier, vol. 100(C), pages 245-254.
    7. Bigne, Enrique & Chatzipanagiotou, Kalliopi & Ruiz, Carla, 2020. "Pictorial content, sequence of conflicting online reviews and consumer decision-making: The stimulus-organism-response model revisited," Journal of Business Research, Elsevier, vol. 115(C), pages 403-416.
    8. Chaoqun Deng & T. Ravichandran, 2024. "Managerial Response to Online Positive Reviews: Helpful or Harmful?," Information Systems Research, INFORMS, vol. 35(4), pages 1802-1823, December.
    9. Woo, Hongjoo & Shin, Daeun Chloe & Kim, Naeun Lauren & Tong, Zhenghao & Kwon, Soyon, 2024. "Can sharing with others whom consumers Can't see increase their sense of community? An examination of social presence on sharing platforms," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    10. Gensler, Sonja & Völckner, Franziska & Liu-Thompkins, Yuping & Wiertz, Caroline, 2013. "Managing Brands in the Social Media Environment," Journal of Interactive Marketing, Elsevier, vol. 27(4), pages 242-256.
    11. Chen, Lele & Jing, Kunpeng & Mei, Yupeng, 2024. "The effect of consumption goals on review helpfulness: Behavioral and eye-tracking research," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    12. Büyükdağ, Naci & Kitapci, Olgun, 2021. "Antecedents of consumer-brand identification in terms of belonging brands," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    13. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    14. Ahreum Maeng, 2024. "Moral Faces: How Spontaneous Ideological Inferences from Facial Cues Influence Moral Judgments," Societies, MDPI, vol. 14(8), pages 1-13, August.
    15. Ni, Shaowen & Ueichi, Hideo, 2024. "Factors influencing behavioral intentions in livestream shopping: A cross-cultural study," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    16. Vazquez, Erik Ernesto & Patel, Chirag & Alvidrez, Salvador & Siliceo, Lorena, 2023. "Images, reviews, and purchase intention on social commerce: The role of mental imagery vividness, cognitive and affective social presence," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    17. Lv, Xingyang & Liang, Yuqing & Luo, Jia & Liu, Yue, 2022. "Icing on the cake or gilding the lily? The impact of high-modified model images on purchase intention," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    18. Kübler, Raoul V. & Lobschat, Lara & Welke, Lina & van der Meij, Hugo, 2024. "The effect of review images on review helpfulness: A contingency approach," Journal of Retailing, Elsevier, vol. 100(1), pages 5-23.
    19. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    20. Dahl, Darren W & Manchanda, Rajesh V & Argo, Jennifer J, 2001. "Embarrassment in Consumer Purchase: The Roles of Social Presence and Purchase Familiarity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 473-481, December.
    21. 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.
    22. M. Joseph Sirgy, 2018. "Self-congruity theory in consumer behavior: A little history," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 28(2), pages 197-207, April.
    23. Albert M. Muiz Jr. & Hope Jensen Schau, 2005. "Religiosity in the Abandoned Apple Newton Brand Community," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 31(4), pages 737-747, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. HanByeol Stella Choi & Junyeong Lee & Chanhee Kwak & Jinyoung Min, 2025. "The role of review responses in shaping online review content and review space dynamics," Electronic Markets, Springer;IIM University of St. Gallen, vol. 35(1), pages 1-17, December.

    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. 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.
    2. Ana Babić Rosario & Kristine Valck & Francesca Sotgiu, 2020. "Conceptualizing the electronic word-of-mouth process: What we know and need to know about eWOM creation, exposure, and evaluation," Journal of the Academy of Marketing Science, Springer, vol. 48(3), pages 422-448, May.
    3. Roma, Paolo & Aloini, Davide, 2019. "How does brand-related user-generated content differ across social media? Evidence reloaded," Journal of Business Research, Elsevier, vol. 96(C), pages 322-339.
    4. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    5. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    6. Peng-Fei Cheng & Song-Liang Li & Si-Jie Cheng, 2025. "Dynamic Evolutionary Game Analysis of Online Praise Reward Behavior of E-commerce Platform," SAGE Open, , vol. 15(1), pages 21582440251, March.
    7. Zhuolan Bao & Wenwen Li & Pengzhen Yin & Michael Chau, 2021. "Examining the impact of review tag function on product evaluation and information perception of popular products," Information Systems and e-Business Management, Springer, vol. 19(2), pages 517-539, June.
    8. Hallie S. Cho & Manuel E. Sosa & Sameer Hasija, 2022. "Reading Between the Stars: Understanding the Effects of Online Customer Reviews on Product Demand," Manufacturing & Service Operations Management, INFORMS, vol. 24(4), pages 1977-1996, July.
    9. Paulo B. Goes & Mingfeng Lin & Ching-man Au Yeung, 2014. "“Popularity Effect” in User-Generated Content: Evidence from Online Product Reviews," Information Systems Research, INFORMS, vol. 25(2), pages 222-238, June.
    10. Lifang Peng & Qinyu Liao & Xiaorong Wang & Xuanfang He, 2016. "Factors affecting female user information adoption: an empirical investigation on fashion shopping guide websites," Electronic Commerce Research, Springer, vol. 16(2), pages 145-169, June.
    11. Liu, Yang & Chen, Yuan & Fan, Zhi-Ping, 2021. "Do social network crowds help fundraising campaigns? Effects of social influence on crowdfunding performance," Journal of Business Research, Elsevier, vol. 122(C), pages 97-108.
    12. 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.
    13. Rizal Edy Halim & Shinta Rahmani & Gita Gayatri & Asnan Furinto & Yudi Sutarso, 2022. "The Effectiveness of Product Sustainability Claims to Mitigate Negative Electronic Word of Mouth (N-eWOM)," Sustainability, MDPI, vol. 14(5), pages 1-18, February.
    14. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    15. Yabing Jiang & Hong Guo, 2015. "Design of Consumer Review Systems and Product Pricing," Information Systems Research, INFORMS, vol. 26(4), pages 714-730, December.
    16. Dongpu Fu & Yili Hong & Kanliang Wang & Weiguo Fan, 2018. "Effects of membership tier on user content generation behaviors: evidence from online reviews," Electronic Commerce Research, Springer, vol. 18(3), pages 457-483, September.
    17. Babajide Abubakr Muritala & Maria-Victoria Sánchez-Rebull & Ana-Beatriz Hernández-Lara, 2020. "A Bibliometric Analysis of Online Reviews Research in Tourism and Hospitality," Sustainability, MDPI, vol. 12(23), pages 1-18, November.
    18. Zhen Li & Fangzhou Li & Jing Xiao & Zhi Yang, 2020. "Topic Features in Negative Customer Reviews: Evidence Based on Text Data Mining," The Review of Socionetwork Strategies, Springer, vol. 14(1), pages 19-40, April.
    19. Mingfeng Lin & Paulo Goes, 2012. "The Appeal of Third-party Certifications: Information Unraveling in Natural Experiments," Working Papers 12-02, NET Institute.
    20. Michael Scholz & Verena Dorner, 2013. "The Recipe for the Perfect Review?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 141-151, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:eee:jbrese:v:199:y:2025:i:c:s0148296325003868. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.