Home // International Journal On Advances in Systems and Measurements, volume 13, numbers 3 and 4, 2020 // View article

Agent-Based Simulation of Strain and Motivation in Human Work Performance

Authors:
Stephanie C. Rodermund
Bernhard Neuerburg
Fabian Lorig
Ingo J. Timm

Keywords: Human Work Performance; Agent-based Modeling; Job Demands-Resources Model; Strain; Achievement Motivation

Abstract:
Even though the relevance of the “human factor” on the performance of work processes is well known, the design and optimization of such processes, e.g., in factories, often strongly focuses on machines. Especially intrinsic mental states such as strain and motivation can influence the human workers’ performance and thus the organizational outcome. This paper is based on a previous agent-based model of human work processes and extends this model using Atkinson’s theory of achievement motivation. The combination of the job demands-resources model with a more advanced motivation theory allows for a more sophisticated and realistic modeling of task selection based on its difficulty, individual competencies, and perceived attractiveness. Experiments are presented, to demonstrate the model’s capability to simulate human work performance and the mutual influences between job demands, resources, personal resources, as well as the intrinsic mental states of strain and motivation.

Pages: 240 to 249

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: December 30, 2020

Published in: journal

ISSN: 1942-261x