Measuring performance interrelatedness in social networks of knowledge workers

摘要

Complexity is usually referred to as the degree of interrelatedness of components within a system. This paper explores the interrelatedness of components within complex social networks by using social network concepts adapted from ‘structural holes’ theory. Analogous to Shannon's Entropy, the study operationalises ‘interrelatedness’ in terms of the extent to which network ties transmit information that is unique and non-redundant based on structural positions of components within a complex social network. We term this index the ‘Information Redundancy Index’ (IRI), developed by combining structural holes measures of ‘efficiency’ and ‘constraint’ to determine the extent of redundant information exchange between components. The study then demonstrates how ‘Information Redundancy’, as a proxy for complexity, can be used to associate with project worker performance in terms of interrelatedness. It is hypothesized that higher levels of ‘Information Redundancy’ within an individual's social network have a detrimental effect on individual performance. Empirical results, from a pilot study of 17 real estate agents show a significant negative correlation between ‘efficiency’ and performance providing partial support for the hypothesis. These results are promising by paving the way for future studies to use social network metrics to capture system-level interactions that emerge in complex social systems. This has significant implications for future development of a practical managerial toolkit for project professionals in an increasingly complex world.