An agent-based model to study effects of team processes on compliance with safety regulations at an airline ground service organization

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Abstract

Maintaining high levels of safety under conditions of ever increasing air traffic is a challenging task. Failures to comply with safety-related regulations are often considered to be important contributors to safety occurrences. To address the issue of compliance, approaches based on external regulation of the employees’ behavior were proposed. Unfortunately, an externally imposed control is often not internalized by employees and has a short-term effect on their performance. To achieve a long-term effect, employees need to be internally motivated to adhere to regulations. Theories from social sciences propose that team processes play an important role in the dynamics of individual motivation. In this paper an agent-based model is proposed, by which the impact of social interaction and coordination in teams of platform employees on their individual motivation and compliance with safety regulations at an airline ground service organization are explored. The model was simulated and partially validated by a case study performed at a real airline ground service organization. The model was able to reproduce behavioral patterns of compliance of the platform employees in this study.

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APA

Sharpanskykh, A., & Haest, R. (2015). An agent-based model to study effects of team processes on compliance with safety regulations at an airline ground service organization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9387, pp. 492–500). Springer Verlag. https://doi.org/10.1007/978-3-319-25524-8_31

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