IDEAS home Printed from https://ideas.repec.org/a/spr/elcore/v25y2025i4d10.1007_s10660-023-09769-3.html
   My bibliography  Save this article

Factors affecting customer intention to return in online shopping: the roles of expectation disconfirmation and post-purchase dissonance

Author

Listed:
  • Yun Wang

    (Carleton University)

  • Bo Yu

    (Dalhousie University)

  • Jing Chen

    (Dalhousie University)

Abstract

This study integrates expectation disconfirmation theory and cognitive dissonance theory into a model to explain why individual customers choose to return purchased products. The study uses survey results to test the impact of negative expectation disconfirmation and post-purchase dissonance on consumers’ return intention and confirm that they work as dual mechanisms to independently predict customers’ product returns; importantly, the research emphasizes the multidimensionality of post-purchase dissonance (i.e., cognitive and emotional dissonance) and their joint impact on customers’ intention to return. Moreover, the current study explores the impact of a large group of factors, including online reviews, product-related factors, and shopper-related factors on product returns through the dual mechanisms. Regarding online review factors, the results highlight the critical roles of aggregated indicators (i.e., review consistency) and individual review content (i.e., emotions expressed in reviews) in affecting customers’ return intention, through the mediation of cognitive dissonance and emotional dissonance. Significant effects are also identified between product-related factors (e.g., price) and negative expectation disconfirmation, and between shopper-related factors (e.g., income) and post-purchase dissonance. theoretical and managerial implications of the findings are discussed.

Suggested Citation

  • Yun Wang & Bo Yu & Jing Chen, 2025. "Factors affecting customer intention to return in online shopping: the roles of expectation disconfirmation and post-purchase dissonance," Electronic Commerce Research, Springer, vol. 25(4), pages 2729-2763, August.
  • Handle: RePEc:spr:elcore:v:25:y:2025:i:4:d:10.1007_s10660-023-09769-3
    DOI: 10.1007/s10660-023-09769-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10660-023-09769-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10660-023-09769-3?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. 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. Young Kwark & Jianqing Chen & Srinivasan Raghunathan, 2014. "Online Product Reviews: Implications for Retailers and Competing Manufacturers," Information Systems Research, INFORMS, vol. 25(1), pages 93-110, March.
    3. 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.
    4. Vicki McKinney & Kanghyun Yoon & Fatemeh “Mariam” Zahedi, 2002. "The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach," Information Systems Research, INFORMS, vol. 13(3), pages 296-315, September.
    5. Sun, Miao & Chen, Jing & Tian, Ye & Yan, Yufei, 2021. "The impact of online reviews in the presence of customer returns," International Journal of Production Economics, Elsevier, vol. 232(C).
    6. Minnema, Alec & Bijmolt, Tammo H.A. & Gensler, Sonja & Wiesel, Thorsten, 2016. "To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns," Journal of Retailing, Elsevier, vol. 92(3), pages 253-267.
    7. Yili (Kevin) Hong & Paul A. Pavlou, 2014. "Product Fit Uncertainty in Online Markets: Nature, Effects, and Antecedents," Information Systems Research, INFORMS, vol. 25(2), pages 328-344, June.
    8. Nachiketa Sahoo & Chrysanthos Dellarocas & Shuba Srinivasan, 2018. "The Impact of Online Product Reviews on Product Returns," Information Systems Research, INFORMS, vol. 29(3), pages 723-738, September.
    9. Tsiros, Michael & Mittal, Vikas, 2000. "Regret: A Model of Its Antecedents and Consequences in Consumer Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 26(4), pages 401-417, March.
    10. Kostyra, Daniel S. & Reiner, Jochen & Natter, Martin & Klapper, Daniel, 2016. "Decomposing the effects of online customer reviews on brand, price, and product attributes," International Journal of Research in Marketing, Elsevier, vol. 33(1), pages 11-26.
    11. Filieri, Raffaele & Lin, Zhibin & Pino, Giovanni & Alguezaui, Salma & Inversini, Alessandro, 2021. "The role of visual cues in eWOM on consumers’ behavioral intention and decisions," Journal of Business Research, Elsevier, vol. 135(C), pages 663-675.
    12. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    13. R. Filieri & Z. Lin & G. Pino & S. Alguezaui & A. Inversini, 2021. "The role of visual cues in eWOM on consumers’ behavioral intention and decisions," Post-Print hal-04779114, HAL.
    14. 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.
    15. Prabuddha De & Yu (Jeffrey) Hu & Mohammad S. Rahman, 2013. "Product-Oriented Web Technologies and Product Returns: An Exploratory Study," Information Systems Research, INFORMS, vol. 24(4), pages 998-1010, December.
    16. Rosen, Dennis L. & Olshavsky, Richard W., 1987. "The dual role of informational social influence: Implications for marketing management," Journal of Business Research, Elsevier, vol. 15(2), pages 123-144, April.
    17. Kristine de Valck & Roberts V. Kozinets & Andrea C. Wojnicki & Sarah J.S. Wilner, 2010. "Networked Narratives: Understanding Word-of-Mouth Marketing in Online Communities," Post-Print hal-00458424, HAL.
    18. Bian, Qin & Forsythe, Sandra, 2012. "Purchase intention for luxury brands: A cross cultural comparison," Journal of Business Research, Elsevier, vol. 65(10), pages 1443-1451.
    19. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    20. Kim, Junyong & Gupta, Pranjal, 2012. "Emotional expressions in online user reviews: How they influence consumers' product evaluations," Journal of Business Research, Elsevier, vol. 65(7), pages 985-992.
    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. Sun, Miao & Chen, Jing & Tian, Ye & Yan, Yufei, 2021. "The impact of online reviews in the presence of customer returns," International Journal of Production Economics, Elsevier, vol. 232(C).
    2. Pei-Yu Chen & Yili Hong & Ying Liu, 2018. "The Value of Multidimensional Rating Systems: Evidence from a Natural Experiment and Randomized Experiments," Management Science, INFORMS, vol. 64(10), pages 4629-4647, October.
    3. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    4. Nachiketa Sahoo & Chrysanthos Dellarocas & Shuba Srinivasan, 2018. "The Impact of Online Product Reviews on Product Returns," Information Systems Research, INFORMS, vol. 29(3), pages 723-738, September.
    5. Yufei Zhang & Clay M. Voorhees & G. Tomas M. Hult, 2024. "Dynamic interplays between online reviews and marketing promotions," Journal of the Academy of Marketing Science, Springer, vol. 52(6), pages 1820-1841, November.
    6. Schulz, Petra & Shehu, Edlira & Clement, Michel, 2019. "When consumers can return digital products: Influence of firm- and consumer-induced communication on the returns and profitability of news articles," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 454-470.
    7. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    8. 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.
    9. Dominik Gutt, 2018. "In the Eye of the Beholder? Empirically Decomposing Different Economic Implications of the Online Rating Variance," Working Papers Dissertations 40, Paderborn University, Faculty of Business Administration and Economics.
    10. Jingchuan Pu & Young Kwark & Sang Pil Han & Qiang Ye & Bin Gu, 2024. "Uncertainty Reduction vs. Reciprocity: Understanding the Effect of a Platform-Initiated Reviewer Incentive Program on Regular Ratings," Information Systems Research, INFORMS, vol. 35(3), pages 1363-1381, September.
    11. Wanshu Niu & Liqiang Huang & Xixi Li & Jie Zhang & Mingliang Chen, 2023. "Beyond the review information: an investigation of individual- and group-based presentation forms of review information," Information Technology and Management, Springer, vol. 24(2), pages 159-176, June.
    12. Björn Stöcker & Daniel Baier & Benedikt M. Brand, 2021. "New insights in online fashion retail returns from a customers’ perspective and their dynamics," Journal of Business Economics, Springer, vol. 91(8), pages 1149-1187, October.
    13. Young Kwark & Gene Moo Lee & Paul A. Pavlou & Liangfei Qiu, 2021. "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data," Information Systems Research, INFORMS, vol. 32(3), pages 895-913, September.
    14. Kim, Taeyong & Hwang, Seungsoo & Kim, Minkyung, 2022. "Text analysis of online customer reviews for products in the FCB quadrants: Procedure, outcomes, and implications," Journal of Business Research, Elsevier, vol. 150(C), pages 676-689.
    15. Christoph Schneider & Markus Weinmann & Peter N.C. Mohr & Jan vom Brocke, 2021. "When the Stars Shine Too Bright: The Influence of Multidimensional Ratings on Online Consumer Ratings," Management Science, INFORMS, vol. 67(6), pages 3871-3898, June.
    16. Yabing Jiang & Hong Guo, 2015. "Design of Consumer Review Systems and Product Pricing," Information Systems Research, INFORMS, vol. 26(4), pages 714-730, December.
    17. 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.
    18. Duong, Quang Huy & Zhou, Li & Van Nguyen, Truong & Meng, Meng, 2025. "Understanding and predicting online product return behavior: An interpretable machine learning approach," International Journal of Production Economics, Elsevier, vol. 280(C).
    19. Ni Huang & Tianshu Sun & Peiyu Chen & Joseph M. Golden, 2019. "Word-of-Mouth System Implementation and Customer Conversion: A Randomized Field Experiment," Information Systems Research, INFORMS, vol. 30(3), pages 805-818, September.
    20. Hang Yin & Shuang Zheng & William Yeoh & Jie Ren, 2021. "How online review richness impacts sales: An attribute substitution perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(7), pages 901-917, July.

    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:spr:elcore:v:25:y:2025:i:4:d:10.1007_s10660-023-09769-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.