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The purpose of this paper is to explore the dynamics of online health care communities and the impact of two-way online social support on customers’ well-being and patients’ quality of life, at different social exclusion levels.

An online survey in China’s Anti-Hepatitis B Online Community includes 326 respondents. A combined hierarchical regression analysis and structural equation model test the hypotheses.

Both receiving and giving online social support, as reciprocal altruism behaviors, enhance patients’ well-being. Receiving online social support influences psychological well-being most; giving has the largest impact on existential domains. Social exclusion boosts the benefits of giving online social support but attenuates the benefits of receiving it.

This research focusses on the effects of online social support among socially excluded patients. Extensions could rely on objective instead of subjective measures and alternative methodologies to test the underlying processes. Additional insights could derive from a bidirectional perspective.

Medical treatment institutions should leverage customer resources; health care providers should prioritize patients who feel socially excluded as effective online support providers. Health care community administrators can use several means to convince patients to contribute to communities.

Social support in online health care communities is a collaborative service that uses customers as service resources. This study explains the collaborative service and how customers feel about their bidirectional roles. It also extends reciprocal altruism research to a health information technology realm by systematically exploring how giving, vs receiving, online social support affects customers’ well-being.

The authors empirically examined social capital factors affecting patients' social support acquisition with the aim of providing guidance to patients seeking social support online.

The authors used social network analysis to extract data about social capital factors from online health communities and text mining to identify forms of informational support and emotional support grounded in online, text-based communication. Moreover, the authors employed a random coefficient model to understand the dynamic influence of social capital factors on both informational and emotional support.

The results from the empirical analyses show that structural connections have a lasting impact on the acquisition of both types of support; that is, social connections developed in the past will have an effect on the future. For relational capital, strong ties were less important; the quantity of connections mattered more than the quality when acquiring informational support. The use of health-related language increased the amount of informational support acquired. Over time, patients gained increasing social support, which primarily came from the patients' historical threads, likely via searches from peers facilitated by accumulated social capital.

The authors' research adds to the literature on social capital and social support in online health communities by exploring how the three dimensions of social capital affect social support acquisition. The authors' research also contributes to the online health care literature by examining social support from a dynamic perspective. Practically, the authors' findings provide guidance for patients on what decisions to make to acquire more social support.

Despite having inadequate resources, highly impoverished patients tend to seek and share health information over social media groups to improve each other’s well-being. This study aims to focus on access to health-care information for such patients and aims to provide an understanding of how online health-care communities (OHCs), as transformative service mediators, can be platforms for patients with chronic and nonchronic health conditions to share their experiences in a base-of-the-pyramid (BOP) context.

A large-scale survey among 658 respondents was conducted in a very low-income country. Structural equation modeling was used to test the hypotheses.

A model of patients’ experience sharing (PES), motivations and consequences for health-care services are introduced and tested. The result supports the PES model for patients with chronic health conditions, showing that utilitarian, hedonic and social value dimensions directly influence PES and indirectly influence patients’ continuance intention with OHCs and patient efforts. However, a mediating effect of PES was found only between the value dimensions and patients’ efforts. A negative moderation effect of medical mistrust was found in the relationship between utilitarian value and PES for both chronic and nonchronic patient groups.

This study is a pioneering attempt to develop and test a PES model in a BOP market.

The online health community's success depends on doctors' active participation, so it is essential to understand the factors that affect doctors' knowledge contribution behavior in the online health communities. From the perspective of peer effect, this paper discusses the influence of focal doctors' peers on focal doctors' knowledge contribution behavior and the mechanism behind it. This paper aims to solve these problems.

Empirical data of 1,938 doctors were collected from a Chinese online health community, and propensity score matching and ordinary least squares were employed to verify the proposed theoretical model.

The results show that the presence of focal doctors' peers in online health communities has a positive effect on the knowledge contribution behavior of focal doctors, and the economic returns and social returns of focal doctors' peers have a significant mediating effect.

This paper discusses focal doctors' knowledge contribution behavior from the perspective of peer effect. It enhances the understanding of focal doctors' behavior in the online health communities by exploring the mediating role of their peers' economic and social returns. The results of this paper extend the research in the field of peer effect and online health and provide management implications and suggestions for online health platforms and doctors.

Technology has revolutionized the delivery of health-care services, with e-consultations becoming popular mode of service delivery, especially during the pandemic. Extant research has examined the adoption of e-health consultation services, with little attention paid to examine the switching behavior. This study aims to identify factors affecting patients’ intentions to switch from conventional mode i.e. visiting hospitals/clinics to e-health consultations.

To understand this we use the push–pull–mooring (PPM) framework and integrate variables from status quo bias framework to the model. A cross-section research design was used, which rendered 413 valid responses which were obtained from the patients visiting a traditional hospital setup. The data was analyzed using partial least square – structural equation modeling using SmartPLS 3.0.

Findings suggest that push effects (inconvenience and perceived risk), pull effects (opportunity for alternatives and ubiquitous care), mooring effects (trust) and inertia significantly influence patients’ switching intentions from visiting hospitals/clinics to e-health consultations. Further, habit and switching cost positively influence inertia.

This study shall enable online health-care service providers and practitioners to understand patients’ intentions to switch to online health platforms and accordingly develop related marketing strategies, services and policies to encourage them to switch to the new offerings.

The current study enriches the previous research on e-health services by applying and extending PPM framework as the base model and showing its efficiency in predicting individuals switching intentions in the context of emerging economies. This study bridges the gap by focusing on switching behavior in context of health services.

Free knowledge sharing in the online health community has been widely documented. However, whether free knowledge sharing can help physicians accumulate popularity and further the accumulated popularity can help physicians attract patients remain unclear. To unveil these gaps, this study aims to examine how physicians' popularity are affected by their free knowledge sharing, how the relationship between free knowledge sharing and popularity is moderated by professional capital, and how the popularity finally impacts patients' attraction.

The authors collect a panel dataset from Hepatitis B within an online health community platform with 10,888 observations from April 2020 to August 2020. The authors develop a model that integrates free knowledge sharing, popularity, professional capital, and patients' attraction. The hierarchical regression model is used to for examining the impact of free knowledge sharing on physicians' popularity and further investigating the impact of popularity on patients' attraction.

The authors find that the quantity of articles acted as the heuristic cue and the quality of articles acted as the systematic cue have positive effect on physicians' popularity, and this effect is strengthened by physicians' professional capital. Furthermore, physicians' popularity positively influences their patients' attraction.

This study reveals the aggregation of physicians' popularity and patients' attraction within online health communities and provides practical implications for managers in online health communities.

The impact of image is widely investigated in various research fields. However, its effect in online health communities is rarely studied. In this research, the authors develop a theoretical model to assess the impact of physicians' image on patients' choices in online health communities.

The authors developed a web crawler based on R language program to collect more than 40,000 physicians' images and other related information from their homepages in Haodf.com–a leading online health community in China. The features of physicians' images are computed by Face++ Application Programming Interface (API) through the following variables: beauty, smile and skin status.

The empirical results derive the following findings: (1) physician's beauty or physical attractiveness has no significant effect on patients’ choice; (2) Smile has a positive effect on patients’ choices; (3) Physician's skin status also positively affects patients' choices; (4) Physician's professional capital strengthens the effect of beauty, smile and skin status on patients' choices; (5) Beauty and skin status are the substitutes for each other, and smile and skin status are the substitutes for each other too.

Also, this study provides implications for both physicians and online health community platform managers.

This study provides new evidence in understanding the impact of physician's online image and contributes to the literature on signaling theory, impression management theory and patients' choices.

Doctor–medical institution collaboration (DMIC) services are an emerging service mode in focal online health communities (OHCs). This new service mode is anticipated to affect user satisfaction and doctors' engagement behaviors. However, whether and how DMIC occurs is still ambiguous because the topic is rarely examined. To bridge this gap, this study explores doctors' participation in DMIC services and its effects on their online performance, as well as its effect on patients' evaluation of them on OHC platforms.

The authors propose hypotheses based on structural holes theory. A unique dataset obtained from one of the most popular OHCs in China is used to test the hypotheses, and difference-in-differences estimation is adopted to test the causality of the relationship.

The results demonstrate that providing DMIC services improves doctors' online consultation performance and patients' evaluations of them but has no significant effect on doctors' knowledge-sharing performance on OHC platforms. Doctors' knowledge-sharing performance and consultation performance mediate the relationship between participation in DMIC services and patients' evaluation of doctors. Regarding doctors' participation in DMIC services, its impact on doctors' consultation performance and patients' evaluation of them is weaker for doctors with higher professional titles than for doctors with lower professional titles.

The findings clarify the value creation mechanisms of online collaboration between doctors and medical institutions and thereafter facilitate doctors' participation in DMIC services and enhance the sustainable development of OHCs.

Effectively engaging patients is critical for the sustainable development of online health communities (OHCs). Although physicians’ general knowledge-sharing, which is free to the public, represents essential resources of OHCs that have been shown to promote patient engagement, little is known about whether such knowledge-sharing can backfire when superfluous knowledge-sharing is perceived as overwhelming and anxiety-provoking. Thus, this study aims to gain a comprehensive understanding of the role of general knowledge-sharing in OHCs by exploring the spillover effects of the depth and breadth of general knowledge-sharing on patient engagement.

The research model is established based on a knowledge-based view and the literature on knowledge-sharing in OHCs. Then the authors test the research model and associated hypotheses with objective data from a leading OHC.

Although counterintuitive, the findings revealed an inverted U-shape relationship between general knowledge-sharing (depth and breadth of knowledge-sharing) and patient engagement that is positively associated with physicians’ number of patients. Specifically, the positive effects of depth and breadth of general knowledge-sharing increase and then decrease as the quantity of general knowledge-sharing grows. In addition, physicians’ offline and online professional status negatively moderated these curvilinear relationships.

This study further enriches the literature on knowledge-sharing and the operations of OHCs from a novel perspective while also offering significant specific implications for OHCs practitioners.

Online medical teams (OMTs) are gaining popularity as a new form of online health service to provide patients with prompt and guaranteed treatment. While the effective development of an OMT depends on physicians’ active participation, there is insufficient research on how a doctor gains from the OMT, especially from the multilevel and cross-level perspectives. In attempting to narrow this knowledge gap, the authors hypothesize multilevel and cross-level professional capital determinants of physicians’ performance in online health-care communities (OHCs) through the lens of social exchange theory.

This study develops a cross-level model to explain the effects of individual and team professional capital on physicians’ performance. To test the research model and hypotheses, the authors leverage data of 10,398 physicians engaged in 2,611 popular OMTs in China in conjunction with the hierarchical linear model approach.

The results indicated that physicians’ status capital (SC) and decisional capital (DC) are positively related to their performance. The SC and DC of an OMT not only increase physicians’ performance but also indirectly strengthen the positive effect of physicians’ SC on their performance. In contrast, OMTs’ SC and DC lessen the importance of physicians’ DC in promoting their performance.

By studying the mechanism between professional capital and physicians’ performance, this study provides several contributions to theory and practice. Specifically, this study contributes to the extant professional capital research by uncovering the influencing pathways of professional capital on physicians’ performance from a cross-level perspective. These findings suggest physicians pay close attention to the strength and mechanism of OMTs’ professional capital in improving their online performance.