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How inconsistent multidimensional reviews on physicians influence patient decisions on online healthcare platforms: A response surface analysis

  • Huazhong Agricultural University
  • Beijing Institute of Technology
  • Digital and Intelligent Service Innovation Management Research Institute of Guangdong-Hong Kong-Macao Greater Bay Area
  • Hong Kong Baptist University

Research output: Contribution to journalArticlepeer-review

Abstract

While review inconsistency has been widely examined in the literature, multidimensional review inconsistency constitutes a unique but underexplored phenomenon, especially in patients' evaluations of physicians. Drawing upon the stereotype content model, our study examines the congruence effects (i.e., the effects of the types of congruence, the degree of incongruence, and the types of incongruence) between physicians’ competence and warmth on patient decisions. We designed two studies: Study 1 collected a panel dataset from a leading Chinese online aesthetic medicine platform, and Study 2 involved a controlled randomized experiment. Results from polynomial regression and response surface analysis suggest that as a physician's competence and warmth ratings increase simultaneously, the likelihood of patients choosing that physician increases at an increasing rate. The degree of competence-warmth incongruence negatively impacts patients’ choices of physicians. Incongruence with low competence but high warmth has a stronger negative impact on patients’ choices of physicians compared to incongruence with low warmth but high competence. We further find that trust in physicians mediates the congruence effects of physicians’ competence and warmth on patient decisions. Implications for both research and practice are further discussed.

Original languageEnglish
Article number103108
JournalInternational Journal of Information Management
Volume91
DOIs
Publication statusPublished - Dec 2026

Keywords

  • Inconsistent reviews
  • Medical service
  • Patient reviews
  • Polynomial regression and response surface analysis
  • Stereotype content model
  • Trust

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