An agent-based model to study compliance with safety regulations at an airline ground service organization

作者:Alexei Sharpanskykh, Rob Haest

摘要

According to aviation statistics, most of the safety occurrences happen not in the air, but on the ground. Management of airlines and airports often consider failures to comply with safety-related regulations as 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. To understand the role of motivation for compliance in ground service organizations, in this paper a formal agent-based model is proposed based on theories from social science with a wide empirical support. The model incorporates cognitive, social, and organizational aspects. 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 related to compliance of the platform employees in this study. Based on the model, global sensitivity analysis was performed. The results of this analysis together with the simulation results were used to generate recommendations to improve compliance.

论文关键词:Compliance, Agent-based model, Motivation, Cognitive models, Social contagion

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论文官网地址:https://doi.org/10.1007/s10489-016-0795-x