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The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

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.

Family planning is a vital component of reproductive health that enables individuals to make informed decisions about their fertility and plan for the timing and spacing of their pregnancies. However, marginalized communities, often face significant barriers to accessing family planning information and services, resulting in higher rates of unintended pregnancies and poor reproductive health outcomes. This chapter summarizes the current state of knowledge about knowledge related to family planning among marginalized communities, including the factors that shape knowledge, the implications for reproductive health outcomes, and the strategies for improving knowledge and access to family planning information and services. The review highlights the need for continued research, advocacy, and policy development to ensure equitable access to family planning information and services for all individuals, regardless of their demographic characteristics.

This study aims to explore the interplay between community dynamics and knowledge production using the quantum computing research field as a case study. Quantum computing holds the promise of dramatically increasing computation speed and solving problems that are currently unsolvable in a short space of time. In this highly dynamic area of innovation, computer companies, research laboratories and governments are racing to develop the field.

After constructing temporal co-authorship networks, the authors identify seven different events affecting communities of researchers, which they label: forming, growing, splitting, shrinking, continuing, merging, dissolving. The authors then extract keywords from the titles and abstracts of their contributions to characterize the dynamics of knowledge production and examine the relationship between community events and knowledge production over time.

The findings show that forming and splitting are associated with retaining in memory what is currently known, merging and growing with the creation of new knowledge and splitting, shrinking and dissolving with the curation of knowledge.

Although the link between communities and knowledge has long been established, much less is known about the relationship between the dynamics of communities and their link with collective cognitive processes. To the best of the authors’ knowledge, the present contribution is one of the first to shed light on this dynamic aspect of community knowledge production.

The number of online communities has increased rapidly with the development of the Internet. Although these communities provide users with knowledge-sharing channels, the enthusiasm of the users for participation remains low. Ecosystem theory, social cognitive theory, and some other theories emphasize the importance of environmental factors and hypothesize that the behavior of users is affected by personal factors and environmental factors. In this study, the authors investigated the impact of platform environmental factors on knowledge-sharing behavior and improved the platform environment construction of online communities.

First, the authors analyzed the influencing factors of online community knowledge-sharing from the perspective of the platform environment, constructed a research model, and proposed relevant hypotheses. Then, the authors designed a questionnaire and conducted a survey, and finally tested the hypotheses by using the method of structural equation model.

The results showed that community trust, community management, community incentive, community atmosphere, and community information protection had a significant positive impact on community knowledge-sharing behavior. Community trust played a significant intermediary role in the relationship between community management, community incentive, community information protection, and knowledge-sharing behavior; community information protection only affected knowledge-sharing behavior through community trust. Additionally, community atmosphere did not directly affect knowledge-sharing behavior through the intermediary of community trust.

This study showed that theoretical supplements and practical guidance are significant for conducting research and managing knowledge-sharing in the online community. They help community managers pay more attention to the construction of an online community platform environment.

In this study, the authors analyzed the influencing factors of online community knowledge-sharing from the perspective of the platform environment and introduced community trust as an intermediary variable. The research perspective and model of this study are novel to some extent.

In the extant research on online knowledge communities (OKCs), little attention has been paid to the influence of membership fluidity on the coevolution of the social and knowledge systems. This article aims to fill this gap.

Based on the attraction-selection-attrition (ASA) framework, this paper constructs a simulation model to study the coevolution of these two systems under different levels of membership fluidity.

By analyzing the evolution of these systems with the vector autoregression (VAR) method, we find that social and knowledge systems become more orderly as the coevolution progresses. Furthermore, in communities with low membership fluidity, the microlevel of the social system (i.e. users) drives the coevolution, whereas in communities with high membership fluidity, the microlevel of the knowledge system (i.e. users' views) drives the coevolution.

This paper extends the application of the ASA framework and enriches the literature on membership fluidity of online communities and the literature on driving factors for coevolution of the social and knowledge systems in OKCs. On a practical level, our work suggests that community administrators should adopt different strategies for different membership fluidity to efficiently promote the coevolution of the social and knowledge systems in OKCs.

Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

This study employed self-determination theory (SDT) and the “Motivational affordance–Psychological outcomes–Behavioral outcomes” framework to investigate the relationship between gamification features and knowledge-sharing behavior in online communities.

A theoretical model was tested with 281 Chinese users from an online social question and answer (Q&A) community. Partial least square structural equation modeling was applied to analyze the data.

The empirical results revealed that competence mediated the effects of immersion and achievement-related gamification features on knowledge sharing. Moreover, relatedness mediated the effects of immersion, achievement and social-related gamification features on knowledge sharing.

This study was conducted on a Chinese Q&A platform, and the results may not be generalizable to other cultures or service providers with different goals.

The study's findings indicate that gamification could serve as an effective toolkit for incentivizing and promoting knowledge sharing in online communities. The findings thus provide strategic insights for administrators of online communities seeking to leverage gamification designs to encourage user participation in knowledge-sharing activities.

Research on the role of gamification in promoting knowledge sharing has been limited in scope and has focused on tourism comment communities. Little evidence exists on the effect of gamification within social Q&A communities. Further, the finding of gamification's positive role in motivating knowledge sharing indicates the need for the knowledge-sharing field to focus on contextual factors.

This paper aims to examine the open innovation engagement process in terms of how online community members create and share knowledge for open innovation and the consequences of engagement.

A mixed methods approach based on netnography (Study 1), qualitative interviews (Study 2) and surveys (Study 3) was adopted in three studies.

The results of Study 1 show that hotel brand community members actively create and share their knowledge by evaluating hotel policies, providing service suggestions and creating new service ideas. The results of Study 2 identified enjoyment and empowerment as major antecedents of the engagement and brand loyalty and a sense of brand community as major consequences. In Study 3, the relationships among them were quantitatively examined.

This research provides empirical knowledge on online engagement and identifies the innovation value of online platforms. The research also provides knowledge on the engagement process for open innovation by online community members in terms of its antecedents and consequences. As a main limitation of the study, this research only focuses on a single online brand community.

While most existing tourism research analyzes the role of user-generated content in customer decision-making, this research provides a fresh insight into the innovation value of customer knowledge.

Knowledge sharing in online health communities (OHCs) disrupts consumers' health information-seeking behavior patterns such as seeking health information and consulting. Based on social exchange theory, this study explores how the two dimensions of experts' free knowledge sharing (general and specific) affect customer transactional and nontransactional engagement behavior and how the quality of experts' free knowledge sharing moderates the above relationships.

We adopted negative binomial regression models using homepage data of 2,982 experts crawled from Haodf.com using Python.

The results show that experts' free general knowledge sharing and free specific knowledge sharing positively facilitate both transactional and nontransactional engagement of consumers. The results also demonstrate that experts' efforts in knowledge-sharing quality weaken the positive effect of their knowledge-sharing quantity on customer engagement.

This study provides new insights into the importance of experts' free knowledge sharing in OHCs. This study also revealed a “trade-off” between experts' knowledge-sharing quality and quantity. These findings could help OHCs managers optimize knowledge-sharing recommendation mechanisms to encourage experts to share more health knowledge voluntarily and improve the efficiency of healthcare information dissemination to promote customer engagement.