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A multi-facet item response theory approach to improve customer satisfaction using online product ratings

Author

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  • Ling Peng

    (Lingnan University)

  • Geng Cui

    (Lingnan University)

  • Yuho Chung

    (Lingnan University)

  • Chunyu Li

    (Guangdong University of Foreign Studies)

Abstract

While online platforms often provide a single composite rating and the ratings of different attributes of a product, they largely ignore the attribute characteristics and customer criticality, which limits managerial action. We propose a multi-facet item response theory (MFIRT) approach to simultaneously examine the effects of product attributes, reviewer criticality, consumption situation, product type, and time in assessing latent customer satisfaction. Analyses of hotel ratings from TripAdvisor and beer ratings from BeerAdvocate suggest that product attributes differ with respect to their discriminating and threshold characteristics and that reviewer segments emphasize different attributes when rating various products over time. The MFIRT approach predicts product performance more accurately than alternative methods and provides novel insights to inform marketing strategies. The MFIRT framework can fundamentally advance how we analyze customer satisfaction and other consumer attitudes and improve marketing research and practice.

Suggested Citation

  • Ling Peng & Geng Cui & Yuho Chung & Chunyu Li, 2019. "A multi-facet item response theory approach to improve customer satisfaction using online product ratings," Journal of the Academy of Marketing Science, Springer, vol. 47(5), pages 960-976, September.
    • Handle: RePEc:spr:joamsc:v:47:y:2019:i:5:d:10.1007_s11747-019-00662-w
    DOI: 10.1007/s11747-019-00662-w
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