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Extant research on workplace ostracism has investigated a victimization perspective to understand ostracism at the cost of examining the perpetrator-centric view of ostracism. This study aims to draw on the self-categorization theory and the social exchange theory to investigate the harmful effects of workplace romance in cultivating workplace ostracism from the perspective of perpetrator to combat concerns for victim blaming. This study further proposes that workplace ostracism triggered by workplace romance provokes interpersonal conflict. Besides, this study investigates the moderating role of prosocial behavior in the underlying linkages.

This study uses a multisource, time-lagged research design to collect data from employees working in the service sector organizations in Pakistan. This study analyzes 367 responses using SmartPLS (v 4.0).

The findings of this study reveal that workplace romance elicits workplace ostracism, which, in turn, fosters interpersonal conflict among coworkers. In addition, this study finds that ingroup prosocial behavior strengthens the associations between workplace romance and workplace ostracism, and workplace romance and interpersonal conflict, mediated by workplace ostracism such that the associations are more potent at higher levels of ingroup prosocial behavior and vice versa.

To the best of the authors’ knowledge, this is the first study that examines workplace romance as the perpetrator-centric antecedent of workplace ostracism, and ingroup prosocial behavior in exaggerating the outgroup ostracism and interpersonal conflict.

The aim of this study is to investigate how social media users' experience of seeking emergency information affects their engagement intention toward emergency information with a reciprocity framework integrated with information adoption model.

Drawing on reciprocity theory, indebtedness theory, and information adoption model, an integrative research model is developed. This study employs a questionnaire survey to collect data of 325 social media users in China. Structural equation modeling analyses are conducted to test the proposed theoretical model.

Social media users' experience of seeking emergency information has a strong effect on their perceived information usefulness and indebtedness, while perceived information usefulness further influences community norm, indebtedness, and engagement intention. The authors also found that perceived information usefulness mediates the relationships between experience of seeking emergency information and community norm/indebtedness.

This study offers a new perspective to explain social media users' engagement intention in the diffusion of emergency information. This study contributes to the literature by extending the theoretical framework of reciprocity and applying it to the context of emergency information diffusion. The findings of this study could benefit the practitioners who wish to leverage social media tools for emergency response purposes.

In online user innovation communities (UICs), firms adopt external innovations beyond their internal resources and capabilities. However, little is known about the influences of organizational adoption or detailed adoption patterns on subsequent user innovation. This study aims to examine the influence of organizational adoption, including its level and timing, on users' subsequent innovation behavior and performance.

This research model was validated using a secondary dataset of 17,661 user–innovation pairs from an online UIC. The effect of organizational adoption on users' subsequent innovation likelihood was measured by conducting a panel logistic regression. Furthermore, the effects of organizational adoption on subsequent innovation’ quality and homogeneity and those of the adoption level and timing on subsequent innovation likelihood were tested using Heckman's two-step approach.

The authors found that organizational adoption negatively affects the likelihood of subsequent innovation and its homogeneity but positively affects its quality. Moreover, more timely and lower-level adoption can increase the likelihood of users' subsequent innovation.

This study comprehensively explores organizational adoption's effects on users' subsequent innovation behavior and performance, contributing to the literature on UICs and user innovation adoption. It also provides valuable practical implications for firms on how to optimize their adoption decisions to maintain the quantity, quality, and diversity of user innovations.

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 current study aims to investigate the factors that impact the feedback received on answers to questions in social Q&A communities and whether the expertise-required question influences the role of these factors on the feedback.

To understand the antecedents and consequences that influence the feedback received on answers to online community questions, the elaboration likelihood model (ELM) is applied in this study. The authors use web data crawling methods and a combination of quantitative analyses. The data for this study came from Zhihu; in total, 353,775 responses were obtained to 1,531 questions, ranging from 49 to 23,681 responses per question. Each answer received 0 to 113,892 likes and 0 to 6,250 comments.

The answers' cognitive and emotional components and the answerer's influence positively affect user feedback behavior. In addition, the expertise-required question moderates the effects of the answer's cognitive component and emotional component on the user feedback, moderating the effects of the answerer's influence on the user approval feedback.

This study builds upon a limited yet growing body of literature on a theme of great relevance to scholars, practitioners and social media users concerning the effects of the connotation of answers (i.e. their cognitive and emotional components) and the answerer's influence on user feedback (i.e. approval and collaborative feedback) in social Q&A communities. The authors further consider the moderating role of the domain expertise required by the question (expertise-required question). The ELM model is applied to explore the relationships between questions, answers and feedback. The findings of this study add a new perspective to the research on user feedback and have implications for the management of social Q&A communities.

The motivation to participate in crowdsourcing (CS) platforms is an emerging challenge. Although researchers and practitioners have focused on crowd motivation in the past, the results obtained through such practices have not been satisfactory. Researchers have left unexplored research areas related to CS pillars, such as the evolution of the crowd’s primary motivations, seekers applying effective policies and incentives, platform design challenges and addressing task complexity using the synchronicity of the crowd. Researchers are now more inclined to address these issues by focusing on sustaining the crowd’s motivation; however, sustaining the crowd’s motivation has many challenges.

To fill this gap, this study conducted a systematic literature review (SLR) to investigate and map the challenges and factors affecting sustained motivation during CS with the overcoming implications. Studies that satisfied the inclusion criteria were published between 2010 and 2021.

Important sustainable factors are extracted using the grounded theory that has sustained participation and the factors' cohesion leads to the identification of challenges that the pillars of CS face. Crowds being the most vital part of CS contests face the challenge of engagement. The results reported the factors that affect the crowd’s primary and post-intentions, perceived value of incentives and social and communal interaction. Seekers face the challenge of knowledge and understanding; the results identify the reason behind the crowd’s demotivation and the impact of theories and factors on the crowd's psychological needs which helped in sustaining participation. Similarly, the platforms face the challenge of being successful and demanding, the results identify the latest technologies, designs and features that seekers proclaim and need the platforms designer's attention. The identified task challenges are completion and achievement; the authors have identified the impact of trait of task and solving mechanisms that have sustained participation.

The study identifies, explores and summarizes the challenges on CS pillars researchers are facing now to sustain contributions by keeping participants motivated during online campaigns. Similarly, the study highlights the implication to overcome the challenges by identifying and prioritizing the areas concerning sustainability through the adoption of innovative methods or policies that can guarantee sustained participation.

Achieving project success is the goal of every project. Due to various project requirements, some of the key determinants of project success cannot be met. The purpose of this paper is to understand relying factors that can lead to a successful project that includes project management maturity, decision-making, coordination and knowledge management.

A self-administered survey was distributed to 231 project managers in the Malaysian project management community. Analysis using partial least square structural equation modelling was applied in testing the proposed relationship between these latent variables.

Finding shows that all the hypotheses were supported and significant. The most impactful factor is project management maturity, followed by knowledge management.

Implication to the project management industry includes providing autonomy to individuals involved in their expertise and management of efficient cross-functional teams between teams in the project. A systematic knowledge management system through a central repository would contribute to the efficient and flexible distribution of knowledge throughout the project process.

This study is one of the few studies focussing on determinants of project success in Malaysia.

Drawing upon information processing theory (IPT) and natural resource-based view (NRBV), this study analyses the role of social media technologies (SMT) on internal and external environmental collaboration and green innovation (green product, process and managerial innovation).

This study took in-depth empirical research by developing a survey questionnaire to identify the relationship between SMTs, environmental collaboration and green innovation. The respondents of the questionnaire were supply chain professionals working in the manufacturing industry of Pakistan. The survey collected 475 responses, which were tested through PLS-SEM using Smart-PLS.

The study results indicate that SMTs positively influence both internal and external environmental collaboration. Furthermore, internal environmental collaboration (IEC) fosters green products and green managerial innovation. In contrast, external environmental collaboration (EEC) fosters green processes and green managerial innovation. This study has also tested the mediation of IEC and EEC, which shows that both IEC and EEC mediate all the relationships except green process and green product innovation. The results also revealed that innovation capabilities moderate the relationship between environmental collaboration and green innovation.

Though this study has various practical implications, it is not free of limitations. First, the data were collected from Pakistan, and the results may only be compared with other developing countries. Second, few social media platforms have been considered, but they are increasing in numbers and could be used in upcoming studies. Third, green innovation in the context of products, processes and management is considered, but the concept is evolving, and its other indicators can be taken in upcoming studies.

This study addresses the implication of SMTs, environmental collaboration, innovation capabilities and green innovation, which are helpful for managers and policymakers to design policies.

This study provides the seminal operationalization of SMTs in environmental collaboration and green innovation. This study emphasizes innovation capabilities that firms should adopt.

Members' knowledge contribution behavior has positive significance for maintaining the activity of the knowledge community, as well as for improving knowledge interaction efficiency and member viscosity. With the development of the mobile Internet, knowledge communities based on social platforms have become more convenient and popular. This study aims to explore what and how factors influence members' knowledge contribution behavior in social knowledge communities from the perspective of social distance.

Based on the theory of reciprocity and on the theory of self-efficacy, hypotheses and research models are proposed. In the empirical study, WeChat learning group is selected as the research case. The empirical investigation (N = 244) collects research data through questionnaires.

I-intention and we-intention both have positive influence on members' knowledge contribution behavior. Knowledge self-efficacy positively moderates the influence of we-intention and affects knowledge contribution behavior. In addition, I-intention is positively affected by expected knowledge benefit, expected emotional benefit and expected image benefit, while costs have no effect. We-intention is positively influenced by affective commitment, continuance commitment and normative commitment in relationship strength, as well as affiliation to the contributing climate.

This paper aims to discuss I-intention, we-intention, and their roles in members' knowledge contribution behavior. It is a beneficial development for existing research to combine the characteristics of new style communities with systematical analysis of knowledge contribution behavior. Findings may provide enlightenment to the social knowledge community on diversity development and differentiated marketing strategies.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.