IDEAS home Printed from https://ideas.repec.org/a/oup/jconrs/v33y2007i4p479-489.html
   My bibliography  Save this article

Not as Happy as I Thought I'd Be? Affective Misforecasting and Product Evaluations

Author

Listed:
  • Vanessa M. Patrick
  • Deborah J. MacInnis
  • C. Whan Park

Abstract

We introduce the concept of affective misforecasting (AMF) and study its impact on product evaluations. Study 1 examines whether and when AMF affects evaluations, finding that AMF has an impact on evaluations when the affective experience is worse (but not when better) than forecasted. Study 2 tests a process model designed to understand how and why AMF influences evaluations. The extent of elaboration is shown to underlie the observed effects. The studies demonstrate the robustness of the findings by controlling for alternative factors, specifically experienced affect, expectancy disconfirmation, and actual performance, which might have an impact on these judgments. (c) 2007 by JOURNAL OF CONSUMER RESEARCH, Inc..

Suggested Citation

  • Vanessa M. Patrick & Deborah J. MacInnis & C. Whan Park, 2007. "Not as Happy as I Thought I'd Be? Affective Misforecasting and Product Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(4), pages 479-489, December.
  • Handle: RePEc:oup:jconrs:v:33:y:2007:i:4:p:479-489
    DOI: 10.1086/510221
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/510221
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1086/510221?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 search for a different version of it.

    Citations

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


    Cited by:

    1. Ritu Agarwal & Michelle Dugas & Guodong (Gordon) Gao & P. K. Kannan, 2020. "Emerging technologies and analytics for a new era of value-centered marketing in healthcare," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 9-23, January.
    2. Maria Pollai & Erik Hoelzl & Flavia Possas, 2010. "Consumption-related emotions over time: Fit between prediction and experience," Marketing Letters, Springer, vol. 21(4), pages 397-411, December.
    3. Yu Zhang & Bingjia Shao, 2019. "The Effectiveness of Customer Participation and Affective Misforecasting in Online Post-Recovery Satisfaction," Sustainability, MDPI, vol. 11(24), pages 1-22, December.
    4. Ashwani Monga & Haipeng (Allan) Chen & Michael Tsiros & Mona Srivastava, 2012. "How buyers forecast: Buyer–seller relationship as a boundary condition of the impact bias," Marketing Letters, Springer, vol. 23(1), pages 31-45, March.
    5. Yushi Wang & Licheng Sun & Shilong Li, 2022. "Production Decisions of Automakers Considering the Impact of Anticipated Regret under the Dual-Credit Policy," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    6. Guan, Zhimin & Yu, Tianyang & Dong, Jingyang & Zhang, Jun, 2024. "Impact of consumers’ anticipated regret on brand owners’ blockchain adoption in the presence of a secondhand market," International Journal of Production Economics, Elsevier, vol. 271(C).
    7. Jürgen Neumann & Dominik Gutt & Dennis Kundisch, 2018. "The Traveling Reviewer Problem – Exploring the Relationship between Offline Locations and Online Rating Behavior," Working Papers Dissertations 44, Paderborn University, Faculty of Business Administration and Economics.
    8. Baojun Jiang & Chakravarthi Narasimhan & Özge Turut, 2017. "Anticipated Regret and Product Innovation," Management Science, INFORMS, vol. 63(12), pages 4208-4323, December.
    9. Moldes, Olaya & Banerjee, Robin & Easterbrook, Matthew J. & Harris, Peter R. & Dittmar, Helga, 2019. "Identity changes and well-being gains of spending money on material and experiential consumer products," Journal of Economic Psychology, Elsevier, vol. 72(C), pages 229-244.
    10. Niladri Syam & Partha Krishnamurthy & James D. Hess, 2008. "What I Thought I Wanted? Miswanting and Regret for a Standard Good in a Mass-Customized World," Marketing Science, INFORMS, vol. 27(3), pages 379-397, 05-06.
    11. Ha, Sejin & Huang, Ran & Park, Jee-Sun, 2019. "Persuasive brand messages in social media: A mental imagery processing perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 41-49.

    More about this item

    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:oup:jconrs:v:33:y:2007:i:4:p:479-489. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://academic.oup.com/jcr .

    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.