A Multi-Facet Item Response Theory Approach to Improve Customer Satisfaction Using Online Product Ratings

Ling PENG*, Geng CUI, Yu Ho CHUNG, Chunyu LI

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

20 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)960-976
Number of pages17
JournalJournal of the Academy of Marketing Science
Issue number5
Early online date20 May 2019
Publication statusPublished - Sept 2019

Bibliographical note

This research was enabled by a General Research Fund from the Research Grants Council Hong Kong (Grant No. 13500314).


  • Online product ratings
  • Customer satisfaction
  • Product Attributes
  • Multi-facet item response theory approach
  • E-business
  • Product attributes
  • E-commerce


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