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2015. Measuring and managing (un)sustainable workload under digitization: A frontier-based job demands-resources model

Invited abstract in session MA-48: DEA and its application, stream Data Envelopment Analysis and its Application.

Monday, 8:30-10:00
Room: 60 (building: 324)

Authors (first author is the speaker)

1. Ahmed-Youssef Oukassou
Economics & Quantitative Methods, IESEG SCHOOL OF MANAGEMENT
2. Marijn Verschelde
Department of Economics and Quantitative Methods, IÉSEG School of Management

Abstract

In this paper, we bridge the psychological Job Demands & Resources (JD-R) literature with the operations literature on activity analysis. The JD-R model provides a comprehensive framework, categorizing risk factors associated with different occupations. On one hand, resources positively affect performance, while on the other hand, demands relate to work conditions. Understanding the health impairment process (strain due to excessive demands) and the motivational process (resource-driven well-being enhancement) is essential in defining a sustainable level of workload. We apply a multidimensional nonparametric activity analysis on the JD-R model, to assess the relation between resources, demands, and mental well-being of employees. Using event-level data of railway control room operators, we construct a multidimensional JDR indicator for digital production, which we empirically validate by using proxies for operational risk and employee well-being.

Keywords

Status: accepted


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