Purpose
The complicated social relationship in Chinese culture requires human resource management (HRM) practitioners to be aware of the implications of social network. This paper aims to disclose the relevance between social network structure and employees’ performance.
Design/methodology/approach
An empirical research is exploited in this paper. Based on cluster sampling method, the authors collected 336 employees’ socio-demographic characteristic data and social network data by means of face-to-face interviews using the structured questionnaire. In addition, employees’ performance data were obtained from the financial department, to support subsequent correlation analysis, grey relational analysis and OLS regression analysis.
Findings
The informal network, rather than the formal network, was observed to contribute more toward employees’ individual performance. We further found that structure centrality has a distinct advantage in delineating an individual’s power and status in the network, success over degree centrality, thus predicting individual performance.
Practical implications
For the management practice of an organization, the present study’s empirical results demonstrate that informal relations have a more decisive influence on individual performance than formal relations. This research also found that the structure centrality, from the perspective of networks’ structure heterogeneity, is valuable in discovering crucial staff in social networks, especially those in informal network associations.
Originality/value
First, the relations between network structure and individual performance have been summarized. Second, the different influences between formal and informal networks on individual performance have been discussed. Third, a new index – structure centrality to recapitulate network structure for developing social network theory – introduced. Finally, this paper is an attempt to explore the associations between social network structure and employees’ performance from the perspective of the whole network.
Inequality is rising where social network segregation interacts with urban topology
