Title: Temporal mining of workplace network connections

Authors: Paul A. Beckman; Monica M. Sharif

Addresses: College of Business, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA, 94132, USA ' College of Business and Economics, California State University – Los Angeles, 5151 State University Dr, Los Angeles, CA 90032, USA

Abstract: This research proposes a novel temporal mathematical method of calculating the added value of an influential individual in a network, called a 'team player', who adds indirect value to their organisation because they drastically improve the future workplace task performance of those with whom they work. Our process uses temporal mining of employee connectivity data where connections are made between co-workers as they work together on an organisational task. The process we describe is based on mathematically-proven algorithms and can be applied to any organisation where employees' project work and performance is tracked. Our application views employees as network points and their joint work on a series of organisational tasks as the links that connect those employees. We use one of the largest online and open data sources containing many years of employee joint task work to apply our proposed algorithm and produce quantitative results.

Keywords: social network analysis; SNA; temporal data mining; employee performance.

DOI: 10.1504/IJBPM.2025.145872

International Journal of Business Performance Management, 2025 Vol.26 No.3, pp.271 - 288

Accepted: 29 May 2023
Published online: 30 Apr 2025 *

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