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Measuring performance & interrelatedness in social networks of knowledge workers

Published: 25 August 2013 Publication History

Abstract

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.

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cover image ACM Conferences
ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
August 2013
1558 pages
ISBN:9781450322409
DOI:10.1145/2492517
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 25 August 2013

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Author Tags

  1. complex networks
  2. complex systems
  3. complexity
  4. performance
  5. social network analysis
  6. structural holes

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ASONAM '13
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ASONAM '13: Advances in Social Networks Analysis and Mining 2013
August 25 - 28, 2013
Ontario, Niagara, Canada

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