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Analyzing consumer satisfaction using Interpretive Structural Modeling driven by online reviews: An integrated approach

Author

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  • Liu, Xiao
  • Li, Ming-Yang
  • Yuan, Duo-Ning

Abstract

Consumer satisfaction analysis is crucial in commercial activities. Considering the causal relationships among product/service attributes can significantly enhance the accuracy of consumer satisfaction analysis. This study aims to analyze consumer satisfaction by employing an integrated ISM approach driven by online reviews. The research process consists of three stages: (1) Product/service attributes of consumer concern are extracted from online reviews using BERTopic. (2) A corpus of attribute pairs is constructed, and a Bert-RCNN algorithm is proposed to classify the causal relationships between these pairs. (3) ISM is performed on consumer satisfaction based on product/service attributes and their causal relationships to reveal the hierarchical structure of consumer satisfaction. Finally, a case study of consumer satisfaction analysis is conducted on a five-star hotel to demonstrate the effectiveness of the integrated ISM approach. The research results indicate that this study provides a meaningful contribution to the field of consumer satisfaction.

Suggested Citation

  • Liu, Xiao & Li, Ming-Yang & Yuan, Duo-Ning, 2026. "Analyzing consumer satisfaction using Interpretive Structural Modeling driven by online reviews: An integrated approach," Journal of Business Research, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:jbrese:v:205:y:2026:i:c:s0148296325007313
    DOI: 10.1016/j.jbusres.2025.115908
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