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Specification Seeking: How Product Specifications Influence Consumer Preference

Author

Listed:
  • Christopher K. Hsee
  • Yang Yang
  • Yangjie Gu
  • Jie Chen

Abstract

We offer a framework about when and how specifications (e.g., megapixels of a camera and number of air bags in a massage chair) influence consumer preferences and report five studies that test the framework. Studies 1-3 show that even when consumers can directly experience the relevant products and the specifications carry little or no new information, their preference is still influenced by specifications, including specifications that are self-generated and by definition spurious and specifications that the respondents themselves deem uninformative. Studies 4 and 5 show that relative to choice, hedonic preference (liking) is more stable and less influenced by specifications. (c) 2008 by JOURNAL OF CONSUMER RESEARCH, Inc..

Suggested Citation

  • Christopher K. Hsee & Yang Yang & Yangjie Gu & Jie Chen, 2009. "Specification Seeking: How Product Specifications Influence Consumer Preference," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(6), pages 952-966, April.
    • Handle: RePEc:oup:jconrs:v:35:y:2009:i:6:p:952-966
    DOI: 10.1086/593947
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    Citations

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    Cited by:

    1. Basu, Shankha & Savani, Krishna, 2017. "Choosing one at a time? Presenting options simultaneously helps people make more optimal decisions than presenting options sequentially," Organizational Behavior and Human Decision Processes, Elsevier, vol. 139(C), pages 76-91.
    2. Vaidyanathan, Rajiv & Aggarwal, Praveen, 2020. "Does MSRP impact women differently? Exploring gender-based differences in the effectiveness of retailer-provided reference prices," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    3. C. Lembregts & M. Pandelaere, 2012. "Are All Units Created Equal?: The Effect of Default Units on Product Evaluations," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/812, Ghent University, Faculty of Economics and Business Administration.
    4. Rong Zhang & Jiatong Li & Zongsheng Huang & Bin Liu, 2019. "Return Strategies and Online Product Customization in a Dual-Channel Supply Chain," Sustainability, MDPI, vol. 11(12), pages 1-17, June.
    5. 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.
    6. Hsee, Christopher K. & Yang, Yang & Li, Xilin, 2019. "Relevance insensitivity: A new look at some old biases," Organizational Behavior and Human Decision Processes, Elsevier, vol. 153(C), pages 13-26.
    7. Septianto, Felix & Kemper, Joya A. & Chiew, Tung Moi, 2020. "The interactive effects of emotions and numerical information in increasing consumer support to conservation efforts," Journal of Business Research, Elsevier, vol. 110(C), pages 445-455.
    8. Wen Mao & Harmen Oppewal, 2012. "The attraction effect is more pronounced for consumers who rely on intuitive reasoning," Marketing Letters, Springer, vol. 23(1), pages 339-351, March.
    9. Rashmi Adaval, 2013. "The utility of an information processing approach for behavioral price research," AMS Review, Springer;Academy of Marketing Science, vol. 3(3), pages 130-134, September.
    10. M. Pandelaere & B. Briers, 2011. "How to Make a 29% Increase Look Bigger: Numerosity Effects in Option Comparisons," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/712, Ghent University, Faculty of Economics and Business Administration.

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