How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation
Posted: 19 Aug 2019
Date Written: August 15, 2019
Firms and organizations increasingly use real-time performance feedback to evaluate employees. In this exploratory study, we examine the effects of network embeddedness — or the nature of relationships among employees — on performance rating scores. We visualize rating networks within organizations: Employees are nodes, and connections between nodes exist if an evaluation between the pair occurs. We find that different aspects of network embeddedness affect performance rating scores differently. In particular, a rater’s positional embeddedness (measured by eigenvector centrality) is positively associated with the rating score he or she gives. A rater’s structural embeddedness (measured by outdegree centrality) is negatively associated with the rating score he or she gives. We also uncover the moderating effects of anonymity and hierarchy on the role of network embeddedness. Our findings have important implications for the design of performance management systems using network analysis.
Keywords: real-time feedback, performance appraisals, mobile application, network embeddedness, eigenvector centrality, network analysis, econometric model
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