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Seekers who visit professional virtual communities (PVCs) are usually motivated by knowledge-seeking, which is a complex cognitive process. How do seekers search for knowledge, and how is their search linked to prior knowledge or PVC situation factors? From the cognitive process and interactional psychology perspectives, this study investigated the three-way interactions between seekers’ expertise, task complexity, and perceptions of PVC features (i.e. knowledge quality and system quality) on knowledge-seeking strategies and resultant outcomes.

A field experiment was conducted with 119 seekers in a PVC using a 2 × 2 factorial design of seekers’ expertise (i.e. expert versus novice) and task complexity (i.e. low versus high).

The study reveals three significant insights: (1) For a high-complexity task, experts adopt an ask-directed searching strategy compared to novices, whereas novices adopt a browsing strategy; (2) For a high-complexity task, experts who perceive a high system quality are more likely than novices to adopt an ask-directed searching strategy; and (3) Task completion time and task quality are associated with the adoption of ask-directed searching strategies, whereas knowledge seekers’ satisfaction is more associated with the adoption of browsing strategy.

We draw on the perspectives of cognitive process and interactional psychology to explore potential two- and three-way interactions of seekers’ expertise, task complexity, and PVC features on the adoption of knowledge-seeking strategies in a PVC context. Our findings provide deep insights into seekers’ behavior in a PVC, given the popularity of the search for knowledge in PVCs.

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.

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.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

The paper aims to explore “content” factors influencing consumptive and contributive use of enterprise social networking within UK higher education during the COVID-19 pandemic.

The methodology uses genre analysis and grounded theory to analyse empirical data from posts obtained through Microsoft Yammer and a focus group.

The findings reveal the motivators-outcomes-strategies and the barriers-outcomes-strategies of users. Motivators (M) include feature value, Information value, organizational requirement and adequate organizational and technical support. Barriers (B) include six factors, including resisting engagement on the online platform, emotional anxiety, loss of knowledge, the lack of organizational pressure, lack of content quality and lack of time. An Outcomes (O) framework reveals benefits and dis-benefits and strategies (S) relating to improving user engagement.

The research method and resultant model may serve as guidelines to higher educational establishments interested in motivating their staff and scholars around the use of enterprise social network (ESN) systems, especially during face-to-face restrictions.

This research study was conducted during the COVID-19 pandemic which provides a unique setting to examine consumptive and contributive user behaviour of ESN’s. Furthermore, the study develops a greater understanding of “content” factors leading to the benefits or dis-benefits of ESN use, drawing on user motivators, barriers and strategies during the COVID-19 pandemic in UK education.

Knowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.

Drawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.

TMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.

Developers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.

This study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.

The purpose of this study is to develop a model for investigating the sharing of harmful messages by employees using social media using the conspiracy theory from a socio-legal perspective. This study also examines the moderating role of different demographic parameters such as age, gender and education toward sharing harmful messages using social media.

Using the conspiracy theory and social impact theory as the foundation of this study, the authors developed theoretical model and validated it using the structural equation modeling technique with 342 participants from various organizations across Europe and Asia. The study also used different statistical measures to understand the demographic impacts toward sharing harmful messages.

It was found that epistemic, existential and social motives significantly and positively influence employees’ inappropriate message-sharing and seeking behavior, which in turn influences them to share harmful messages on social media. The study also indicates that there are some moderating impacts of employee demography toward sharing harmful messages using social media platforms.

This study investigates the antecedents of sharing harmful messages using social media by employees. The present study could be useful for the organizations leaders as well as policymakers and legal fraternity. The study uses a limited number of feedback to validate the model. Also, this is a cross-sectional study which is another limitation of this study.

This study has proposed and validated a theoretical model by using the conspiracy theory as well as the social impact theory which is unique. Moreover, this study adds value to the existing literature on the harmful impacts of social media and its societal impacts. Besides, the validated model of this study has a high explanatory power which is another uniqueness of this study.

Emergence is a key concept in service-dominant (SD) logic; however, the literature is neonatal on the underlying mechanisms that lead to emergence within service ecosystems. This study aims to address the call by Vargo et al. (2022) for understanding the role of actor engagement in emergence of novel outcomes, by identifying a process of how various actor roles in entrepreneurial ecosystem (EE) emerge as resource through the actor engagement.

Following a longitudinal design, this study conduct interviews from 20 respondents over eight months in three phases (group interviews, post-training, post-funding). This study analyzes the respondents’ engagement in an entrepreneurial service context. This study uses qualitative inductive approach and thematic analysis.

Results show that actor roles emerge as role expectations from essential provider and beneficiary position in a service ecosystem through actor role readiness, manifested as engagement properties in the actor engagement process. This study identifies five actor roles and their corresponding role readiness dimensions that emerge. Based on these propositions through which the authors position generic actor roles emergence within the actor engagement process in a service ecosystem.

This paper advances the understanding of micro-level process in emergence literature in SD logic by providing a conceptual understanding of emergence of actor roles as a resource through actor engagement. By grounding the study in EE, this study provides empirical evidence to the underlying mechanisms at the micro level of resource emergence process in a service ecosystem.

Why and when people working in organisations hide their knowledge has received considerable academic attention. However, little attention has been paid to knowledge hiding in academia itself, even though universities are known as places where knowledge is shared. This study aims to consider the dilemma faced by academics when undertaking research work: should they share or hide what they are doing?

Using empirical evidence drawn from 20 academics in a number of UK Business Schools, the authors carried out in-depth interviews to investigate the effects of strategic knowledge hiding (SKH) on research knowledge work. The authors argue that SKH can drive competitive individuals to establish research superiority.

The findings revealed that most respondents have, for strategic reasons, hidden their tacit and/or explicit knowledge from others during ongoing research processes, but have, at the same time, purposefully sought for knowledge from targeted colleagues.

The findings extend the previous literature by revealing not only the distinctive individual antecedents of SKH but also its positive outcomes. The findings illustrate a pioneering contribution of a systematic model of SKH among university business school academics.