IDEAS home Printed from https://ideas.repec.org/p/rco/dpaper/343.html
   My bibliography  Save this paper

The Impact of Uncertainty on Customer Satisfaction

Author

Listed:
  • Back, Camila

    (LMU Munich)

  • Spann, Martin

    (LMU Munich)

Abstract

Customer satisfaction is an important metric to predict customer behavior and as a result firms' profitability. Expectations of a product's performance serve as a reference point against which customers evaluate their satisfaction with the products' actual performance. However, what is the effect of uncertainty in expectations? This paper develops a novel theoretical model of satisfaction, in which expectations reflect distributions of individual beliefs about performance outcomes. Based on this model, uncertainty shifts subjective reference points upward. That is, uncertainty increases the performance level at which customers switch from being dissatisfied to being satisfied. Furthermore, uncertainty has an attenuating effect on both positive and negative deviations of actual performance from subjective reference points. Put differently, a bad performance feels less bad and a good performance feels less good when it is expected, compared with unexpected. The authors find support for the model's predictions in an experimental study on product delivery as well as a field study based on online reviews. In addition, the authors develop a model-based tool that predicts the effect of uncertainty on customer satisfaction across different customizable scenarios. The paper's results carry implications for firms' communication, customer valuation and recovery strategies.

Suggested Citation

  • Back, Camila & Spann, Martin, 2022. "The Impact of Uncertainty on Customer Satisfaction," Rationality and Competition Discussion Paper Series 343, CRC TRR 190 Rationality and Competition.
    • Handle: RePEc:rco:dpaper:343
    as

    Download full text from publisher

    File URL: https://rationality-and-competition.de/wp-content/uploads/2022/10/343.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruth N. Bolton & Katherine N. Lemon & Matthew D. Bramlett, 2006. "The Effect of Service Experiences over Time on a Supplier's Retention of Business Customers," Management Science, INFORMS, vol. 52(12), pages 1811-1823, December.
    2. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    3. Stephen X. He & Samuel D. Bond, 2015. "Why Is the Crowd Divided? Attribution for Dispersion in Online Word of Mouth," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 41(6), pages 1509-1527.
    4. Roland T. Rust & J. Jeffrey Inman & Jianmin Jia & Anthony Zahorik, 1999. "What You Know About Customer-Perceived Quality: The Role of Customer Expectation Distributions," Marketing Science, INFORMS, vol. 18(1), pages 77-92.
    5. West, Patricia M & Broniarczyk, Susan M, 1998. "Integrating Multiple Opinions: The Role of Aspiration Level on Consumer Response to Critic Consensus," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(1), pages 38-51, 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. S. Sriram & Pradeep K. Chintagunta & Puneet Manchanda, 2015. "Service Quality Variability and Termination Behavior," Management Science, INFORMS, vol. 61(11), pages 2739-2759, November.
    2. Liu, Mengmeng & Morrin, Maureen & Chae, Boyoun Grace, 2022. "Stop arguing! How childhood exposure to interparental conflict affects consumer response toward product review dispersion," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1093-1107.
    3. 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.
    4. Bella Rozenkrants & S Christian Wheeler & Baba Shiv & Gita JoharEditor & Derek RuckerAssociate Editor, 2017. "Self-Expression Cues in Product Rating Distributions: When People Prefer Polarizing Products," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(4), pages 759-777.
    5. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    6. Wang, Feng & Liu, Xuefeng & Fang, Eric (Er), 2015. "User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects," Journal of Retailing, Elsevier, vol. 91(3), pages 372-389.
    7. 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.
    8. 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.
    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. Gregory DeCroix & Xiaoyang Long & Jordan Tong, 2021. "How Service Quality Variability Hurts Revenue When Customers Learn: Implications for Dynamic Personalized Pricing," Operations Research, INFORMS, vol. 69(3), pages 683-708, May.
    11. 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.
    12. Xie, Guangming & Lü, Kevin & Gupta, Suraksha & Jiang, Yushi & Shi, Li, 2021. "How Dispersive Opinions Affect Consumer Decisions: Endowment Effect Guides Attributional Inferences," Journal of Retailing, Elsevier, vol. 97(4), pages 621-638.
    13. Xitong Li, 2018. "Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold," Information Systems Research, INFORMS, vol. 29(3), pages 739-754, September.
    14. Seung Hwan (Shawn) Lee, 2019. "An Exploration of Initial Purchase Price Dispersion and Service-Subscription Duration," Sustainability, MDPI, vol. 11(9), pages 1-14, April.
    15. Yang, Wenjuan & Zhang, Jiantong & Yan, Hong, 2022. "Promotions of online reviews from a channel perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    16. Dong, Xiaodan & Zhang, Zelin & Zhang, YiJing & Ao, Xiang & Tang, Tanya (Ya), 2024. "Post diversity: A new lens of social media WOM," Journal of Business Research, Elsevier, vol. 170(C).
    17. Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2016. "Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth," Information Systems Research, INFORMS, vol. 27(1), pages 131-144, March.
    18. Liu, Fu & Wei, Haiying & Wang, Xingyuan & Zhu, Zhenzhong & Chen, Haipeng Allan, 2023. "The influence of online review dispersion on consumers’ purchase intention: The moderating role of dialectical thinking," Journal of Business Research, Elsevier, vol. 165(C).
    19. Langan, Ryan & Besharat, Ali & Varki, Sajeev, 2017. "The effect of review valence and variance on product evaluations: An examination of intrinsic and extrinsic cues," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 414-429.
    20. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.

    More about this item

    Keywords

    customer satisfaction; uncertainty; probabilistic beliefs; prospect theory;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:rco:dpaper:343. 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: Viviana Lalli (email available below). General contact details of provider: https://rationality-and-competition.de .

    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.