Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 22, 2023
Date Accepted: Feb 17, 2024
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Effect of Negative Online Reviews and Physician Response on Health Consumer’s Choice: An Attribution Perspective
ABSTRACT
Background:
The Covid-19 pandemic highlights the importance of online medical services. Although some researchers have investigated how numerical ratings affect consumer choice, limited studies have focused on the effect of negative textual reviews that physicians most concern.
Objective:
This study aims to investigate how negative review characteristics (proportion and claim type) and physician response influence consumers’ physician evaluation process under the conditions where the physician’s overall rating is high.
Methods:
Utilizing a 2*2*2 between-subject decision-controlled experiment, this study examined participants’ judgement on physicians with different textual reviews. Collected data were analyzed using t test and Partial Least Squares.
Results:
Negative review proportion (β=-0.371, p<0.001) and review claim type (β=-0.343, p<0.001) have significantly greater effect on consumers’ physician selection intention than physician response (β=0.194, p<0.001). Physician attribution mediates the effects of review proportion (β=-0.150, p<0.001), review claim type (β=-0.068, p<0.01) and physician response (β=0.167, p<0.001) on consumer choice. Reviewer attribution also mediates the effects of review proportion (β=-0.071, p<0.001), review claim type (β=-0.025, p<0.05) and physician response (β=0.096, p<0.001) on consumer choice. The moderating effects of physician response on the relationship between review proportion and physician attribution (β=-0.185, p<0.001), review proportion and reviewer attribution (β=-0.110, p<0.001), claim type and physician attribution (β=-0.123, p<0.01), claim type and reviewer attribution (β=-0.074, p<0.05) are all significant.
Conclusions:
Negative review characteristics and physician response significantly influence consumer choice through the causal attribution to physicians and reviewers. Negative reviews have positive effect if consumers locate the causal of negative review mainly to reviewers. Physician response decreases the influence of negative reviews through direct and moderating effects. We proposed some practical implications for physicians to manage their online reputation.
Citation
