How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation

Fox School of Business Research Paper

Forthcoming in Information Systems Research

40 Pages Posted: 19 Aug 2019 Last revised: 22 Jan 2022

See all articles by Mariia Petryk

Mariia Petryk

University of Florida - Information Systems and Operations Management

Michael Rivera

Temple University - Fox School of Business and Management

Siddharth Bhattacharya

George Mason University, School of Business

Liangfei Qiu

University of Florida - Warrington College of Business Administration

Subodha Kumar

Temple University - Fox School of Business

Date Written: January 20, 2022

Abstract

Firms and organizations are increasingly using real-time performance feedback mechanisms to evaluate employees, where any employee (rather than just the supervisor) can rate other employees. Hence, a need arises to better understand how network positions of employees in such a system impact their performance. Analyzing nearly 4,000 feedback instances from employees at five major organizations that utilize such a real-time performance feedback application called DevelapMe, we explore the effects of network embeddedness – or the nature of relationships among employees – on performance rating scores according to two dimensions of embeddedness: (i) positional – the position of an individual in the emerging network of performance ratings, and (ii) structural – the extent to which a person is entrenched in a network of relationships. We visualize rating networks within organizations: Employees are nodes, and connections between nodes exist if an evaluation between the pair occurs. We find that specific 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 others. However, 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, as well as the sentiment of the textual comments provided with feedback. 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

Suggested Citation

Petryk, Mariia and Rivera, Michael and Bhattacharya, Siddharth and Qiu, Liangfei and Kumar, Subodha, How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation (January 20, 2022). Fox School of Business Research Paper, Forthcoming in Information Systems Research, Available at SSRN: https://ssrn.com/abstract=3438032

Mariia Petryk (Contact Author)

University of Florida - Information Systems and Operations Management ( email )

Warrington College of Business
ISOM Department STZ
Gainesville, FL 32611-7169
United States

Michael Rivera

Temple University - Fox School of Business and Management ( email )

Philadelphia, PA 19122
United States

Siddharth Bhattacharya

George Mason University, School of Business ( email )

Enterprise Hall, School of Business
Fairfax, VA VA 22030
United States
2679681502 (Phone)
22030 (Fax)

HOME PAGE: http://https://business.gmu.edu/facultyandresearch/faculty/profile/115/443/

Liangfei Qiu

University of Florida - Warrington College of Business Administration ( email )

Gainesville, FL 32611
United States

HOME PAGE: http://sites.google.com/site/qiuliangfei/

Subodha Kumar

Temple University - Fox School of Business ( email )

Philadelphia, PA 19122-____
United States

HOME PAGE: http://sites.temple.edu/subodha/

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