An Agent Based Simulation System for Analyzing Stress Regulation Policies at the Workplace

Sergio Muñoz López & Carlos A. Iglesias. (2021). An Agent Based Simulation System for Analyzing Stress Regulation Policies at the Workplace. Journal of Computational Science.

Abstract:
Workplace stress has a significant impact on productivity, since keeping workers’ stress on an adequate level results a key factor for companies to increase their performance. While a high stress level may conduct to anxiety or absenteeism, a low level may also have undesirable consequences, such as lack of motivation. To identify and understand all the elements which interfere on workers’ stress results a key factor in order to improve workers’ performance. However, the complexity of human behavior increases the difficulty of recognizing the influence of these stressors and finding a way to regulate workers’ stress. This paper proposes the use of agent-based simulation techniques for addressing the challenge of analyzing workers’ behavior and stress regulation policies. The main contributions of the paper are: (i) the definition of a stress model that takes into account work and ambient conditions to calculate the stress and the productivity of workers; (ii) the implementation of this model in an agent-based simulation system, enabling the analysis of workplace stress and productivity for different stress regulation policies; (iii) the analysis of four different stress regulation policies; and (iv) the validation of the model with a sensitivity analysis and with its application to a living lab.
JCR 2019 Q1 2.644, SJR 2020 Q1 0.7, Scopus 2019 Q1 5.9