Navigating the dynamic effects of multiple signals: evidence from online physician consultations

Purpose Existing research has provided limited insights into the dynamic mechanisms through which multiple signals are interpreted within online health communities (OHCs). This study attempts to initiate a more integrative understanding of the dynamic interaction effects between patient-generated signals (i.e. herding and word-of-mouth signals) and physician-generated signals (i.e. central effort and peripheral effort signals) on online physician consultations. Design/methodology/approach This study adopts a dynamic panel modelling approach, applying longitudinal data collected from 844 physicians from June to December 2020. Specifically, the two-step system, generalised method of moments (GMM) with instrumental variables and propensity score matching (PSM) were employed to estimate the proposed research model. Findings This research provides empirical evidence that the herding signal and the word-of-mouth (WOM) signal have a positive effect on physician consultations within OHCs. Our findings also demonstrate that the peripheral effort signal complements the effect of the WOM signal on physician consultations, whereas it substitutes for the influence of the herding signal on physician consultations. In addition, this study finds that the central effort signal substitutes the effect of the WOM signal on physician consultation as it intensifies. Originality/value This study contextualises and frames a multidimensional signal framework of the herding signal, the WOM signal, the central effort signal and the peripheral effort signal in OHCs, which augments the predominant applications of signalling theory in e-commerce contexts. Furthermore, this research broadens the theoretical comprehension of signalling theory by revealing the substitutive and complementary effects among these signals, particularly in a mixed signalling environment.

Authors

Institutions

Publication Details

Journal
Internet Research
Published
2026-01-15
DOI
https://doi.org/10.1108/intr-08-2024-1209
Primary Topic
Healthcare Systems and Technology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Navigating the dynamic effects of multiple signals: evidence from online physician consultations

Yajie Hu, Kuanchin Chen, Shasha Zhou
Internet Research
Healthcare Systems and Technology
article

Navigating the dynamic effects of multiple signals: evidence from online physician consultations

Yajie Hu, Kuanchin Chen, Shasha Zhou
article en

Abstract

Purpose Existing research has provided limited insights into the dynamic mechanisms through which multiple signals are interpreted within online health communities (OHCs). This study attempts to initiate a more integrative understanding of the dynamic interaction effects between patient-generated signals (i.e. herding and word-of-mouth signals) and physician-generated signals (i.e. central effort and peripheral effort signals) on online physician consultations. Design/methodology/approach This study adopts a dynamic panel modelling approach, applying longitudinal data collected from 844 physicians from June to December 2020. Specifically, the two-step system, generalised method of moments (GMM) with instrumental variables and propensity score matching (PSM) were employed to estimate the proposed research model. Findings This research provides empirical evidence that the herding signal and the word-of-mouth (WOM) signal have a positive effect on physician consultations within OHCs. Our findings also demonstrate that the peripheral effort signal complements the effect of the WOM signal on physician consultations, whereas it substitutes for the influence of the herding signal on physician consultations. In addition, this study finds that the central effort signal substitutes the effect of the WOM signal on physician consultation as it intensifies. Originality/value This study contextualises and frames a multidimensional signal framework of the herding signal, the WOM signal, the central effort signal and the peripheral effort signal in OHCs, which augments the predominant applications of signalling theory in e-commerce contexts. Furthermore, this research broadens the theoretical comprehension of signalling theory by revealing the substitutive and complementary effects among these signals, particularly in a mixed signalling environment.

Internet Research
City University of Hong Kong (HK), Nanjing University of Information Science and Technology (CN), Systems Analytics (United States) (US), Nanjing University (CN), Zhejiang University of Finance and Economics (CN)
Openalex Percentile: Top 87%
Healthcare Systems and Technology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.