Purpose The purpose of this paper is to examine how the usage of enterprise social media (ESM) affects eventual employee turnover. Design/methodology/approach This study developed a theoretical model based on the proposition that different ESM usage behaviors (utilitarian use, hedonic use and social use) have different effects on employee turnover, and job type and job level can moderate the effect of ESM usage on turnover. The model was examined empirically using 1,791 employee samples from a large high-tech manufacturing enterprise deploying ESM. Findings The results indicate that the utilitarian and social use of ESM has negative effects on turnover, but the hedonic use of ESM has positive effects on turnover. Furthermore, for employees working in different job types and job levels, there are significant differences concerning the effect of ESM usage on their turnover. Practical implications ESM managers should encourage employees to use ESM for utilitarian needs and social support but restrict excessive use of ESM for leisure. In addition, different ESM use policies depending upon job types and job levels could be adopted to retain valuable employees. Originality/value Few studies have focused on how usage of ESM affects eventual employee turnover. Given the lack of theoretical research and empirical evidence, the authors developed a theoretical model and conducted an empirical study to fill the research gap.

Online depression communities give people additional opportunities to share their experiences and exchange social support to care for themselves in fighting against depression. We aimed to explore what drives patients to share in online depression communities. We used three dimensions of social capital (structural, relational, and cognitive) to explain their sharing behaviors. We further proposed that five factors (social interaction ties, a sense of shared identity, trust, expertise, and a sense of shared values) will have significant, positive effects on sharing behaviors and that there are differences among patients who have spent different lengths of time participating in online depression communities. We then chose a popular online depression community in China as our data source and obtained a dataset consisting of 31,440 posts from 197 members. Then, we employed panel data regression analyses to test all six hypotheses. The results revealed that all five factors had significant, positive effects (p < 0.01) on patients’ sharing behaviors, and the effects were significantly different across groups. Our empirical results help designers and managers of online depression communities take specific measures to facilitate community members’ access to social capital resources. Meanwhile, our results have implications for existing health management and e-health literature.

Online depression communities offer people with depressed symptoms new opportunities to obtain health information and provide social support for each other to fight against the depression. We sought to investigate whether usage of online community help improve depression outcomes and determine which types of usage behaviors have positive or negative effects on depression. We proposed that two dimensions of the sense of belonging (sense of identity and trust) and three dimensions of the sense of support (informational, emotional, and socializing) have significant effects on depression, and further considered gender difference and its effect on depression. We obtained a dataset consisting of 465,337 posts from 244 members from a popular online depression community to test all 10 proposed hypotheses. The results reveal that (i) the sense of shared identity, trust, informational support, and emotional support have positive effects on depression, while socializing support have negative effects on depression, and (ii) the sense of shared identity and trust have more positive effects on depression for female users than male users while socializing support has a more negative effect on depression for female users than for male users. The findings have important practical implications for designers and managers of online depression communities.

This study focuses on employee involvement in enterprise social media (ESM) and the impact of ESM on job performance. Few studies found empirical support for this perspective due to limited sample size either the difficulty of accessing the data on user behavior in ESM and their job performance. We addressed this research gap through a data-sharing agreement with a large, high-tech manufacturing enterprise with internal social media and conducted a cooperative study on the impact of employee behaviors involved in ESM on their job performance. We divided online activities on ESM into information-sharing behaviors, information-seeking behaviors and general usage behaviors and then employed hierarchical regression analysis to investigate how the various usage behaviors of employees on ESM affect their job performance significantly. We find that information-seeking behaviors on ESM have positive effects on job performance, but information-sharing behaviors on ESM have negative effects on job performance. Overall, the usage of social media within enterprise social media use could help improve employee job performance. Moreover, to test whether the timing of ESM usage (during working hours or off-work hours) may affect employee job performance, we add a variety of moderator variables into the model. The results show that information-sharing behaviors, information-seeking behaviors and general usage behaviors during working hours negatively moderate the relationship between ESM usage and job performance. The findings have valuable managerial implications for the use of ESM.INDEX TERMS Enterprise social media, information sharing, information seeking, job performance.