Understanding the effect of professional and social signals on physician performance on online health platforms

Purpose Drawing on signaling theory, this study investigates the interaction between professional signals (professional capital) and social signals (peer and patient recognition) in shaping physician performance on online health platforms (OHPs). Design/methodology/approach The research model is tested using panel data from a leading OHP. We employed the correlated random-effects model to test the research hypotheses. Findings Results confirm that professional capital, peer recognition and patient recognition each positively associate with physician performance. Both peer recognition and patient recognition, as online-generated social signals, substitute for professional capital, a signal generated and certified offline but displayed online. Crucially, the three-way interaction effect confirms that social signals jointly substitute for professional signal. Originality/value This study contributes to the online health platform and digital platform signaling literature by theorizing and empirically testing how institutionally generated professional signals interact with peer- and patient-generated social signals. Its primary contribution is the identification and testing of a joint substitution mechanism: peer and patient recognition together reduce the marginal value of professional capital. The study also highlights an alternative platform-supported career path, especially for junior physicians, and offers implications for platform governance, physician reputation management and equitable online health ecosystem design.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2026-10-31
DOI
https://doi.org/10.1108/imds-07-2025-1053
Primary Topic
Expert finding and Q&A systems
Type
article
Field-Weighted Citation Impact
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article

Understanding the effect of professional and social signals on physician performance on online health platforms

Guorui Fan, Zhaohua Deng, Di Wang
Industrial Management & Data Systems
Expert finding and Q&A systems
article

Understanding the effect of professional and social signals on physician performance on online health platforms

Guorui Fan, Zhaohua Deng, Di Wang
article en

Abstract

Purpose Drawing on signaling theory, this study investigates the interaction between professional signals (professional capital) and social signals (peer and patient recognition) in shaping physician performance on online health platforms (OHPs). Design/methodology/approach The research model is tested using panel data from a leading OHP. We employed the correlated random-effects model to test the research hypotheses. Findings Results confirm that professional capital, peer recognition and patient recognition each positively associate with physician performance. Both peer recognition and patient recognition, as online-generated social signals, substitute for professional capital, a signal generated and certified offline but displayed online. Crucially, the three-way interaction effect confirms that social signals jointly substitute for professional signal. Originality/value This study contributes to the online health platform and digital platform signaling literature by theorizing and empirically testing how institutionally generated professional signals interact with peer- and patient-generated social signals. Its primary contribution is the identification and testing of a joint substitution mechanism: peer and patient recognition together reduce the marginal value of professional capital. The study also highlights an alternative platform-supported career path, especially for junior physicians, and offers implications for platform governance, physician reputation management and equitable online health ecosystem design.

Industrial Management & Data Systems
Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 6%
Expert finding and Q&A systems
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Understanding the effect of professional and social signals on physician performance on online health platforms — Guorui Fan, Zhaohua Deng, et al. · Industrial Management & Data Systems (2026) | TGRS Research Map | TGRS