An Agent-based Model to Study Compliance with Safety Regulations at an Airline Ground Service Organization

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.