Understanding knowledge workers’ job performance: a perspective of online and offline communication networks

ABSTRACT

Optimal communication networks allow the knowledge workers to get high job performance. As knowledge workers are increasingly relying on the online interaction, it is important to understand how online and offline communication networks respectively enhance job performance. An empirical study is performed using data collected from 103 knowledge workers in a high-tech company. The results show that job performance of knowledge workers is positively influenced by online communication network properties and negatively influenced by offline communication network properties. The positions of knowledge workers within the offline whole communication network negatively moderate the above effects, such that the relationships between job performance and communication network properties are weaker when a knowledge worker occupies a central position. Theoretical contributions and practical implications are discussed.

KEYWORDS:

• Communication network
• online communication
• offline communication
• job performance
• information and communication technology
• information system

Acknowledgments

We would like to thank anonymous reviewers for their very useful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Consistent with prior research (Zhang and Venkatesh 2013), we choose to omit telephone communication in our categorization. Telephone communication has some features of both online and offline communications. It has been considered to be akin to offline communication (Wellman 2001), but it is also possible to be online communication because it is technology mediated and is used to resolve temporal and spatial constraints. Overall, there is ambiguity regarding how best to categorize telephone communication, so we have not included it here.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities (Grant No. N140604008) and by the National Natural Science Foundation of China (NSFC) (Grant No. 71571156).