Technology Adoption in Air Traffic Management: A Combination of Agent-Based Modeling with Behavioral Economics

Roungas, Bill; Raghothama, Jayanth; Baena, Miguel; Ros, Oliva Garcia-Cantu; Alcolea, Ruben; Herranz, Ricardo · 2021 · Crossref

DOI: 10.1109/wsc52266.2021.9715519

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Summary

This paper addresses the historically slow pace of technological change in European Air Traffic Management (ATM), a system responsible for over a billion passengers annually. Despite growing traffic demands and the potential of emerging technologies like digitization and automation, ATM modernization is hindered by strict safety requirements, coordination complexities, and market monopolies. The authors propose a novel Agent-Based Model (ABM) to simulate the ATM technology deployment cycle, aiming to recommend policy measures that overcome adoption barriers. The study is motivated by the need to understand innovation as a complex phenomenon influenced not only by technical factors but also by political, legal, and social aspects. The methodology combines agent-based modeling with behavioral economics to capture the heterogeneity and non-rational behaviors of stakeholders. The model represents the long-term evolution of the system (up to 2050) and includes agents such as Air Navigation Service Providers (ANSPs), airports, airlines, technology providers, labor unions, and policy makers. Unlike traditional aggregated models, this ABM explicitly models individual agent interactions and decision-making processes. It incorporates behavioral economics theories, including bounded rationality, information asymmetry, nudge theory, time dimension effects (e.g., hyperbolic discounting), and social dimensions like herd behavior and fairness. Exogenous variables such as GDP, population growth, fuel prices, and policy measures are defined to influence the simulation, while agents make strategic decisions regarding technology adoption, pricing, and labor conditions. The paper details the specific definitions and objectives of each agent group. For instance, ANSPs aim to balance safety, environment, capacity, and cost efficiency, while airlines seek to maximize profits through network planning and technology adoption. Labor unions are modeled to potentially obstruct deployments to protect labor conditions. The decision-making process accounts for organizational heterogeneity, such as the difference between legacy and low-cost airlines or public and private ANSPs. The model’s outputs are aligned with the Single European Sky’s Key Performance Areas (KPA), including safety, environment, capacity, and cost-efficiency, as well as new KPAs for technology adoption effectiveness and social welfare. The focus is on obtaining qualitative insights into how specific policy measures affect both aggregated system performance and individual agent behaviors, rather than predicting exact adoption numbers. The significance of this work lies in its comprehensive approach, which is one of the first to combine the organizational stakeholder perspective, policy testing, and behavioral economics in ATM technology diffusion. By modeling the coupling between short-term system performance and long-term investment decisions, the ABM provides a tool for testing policy interventions, such as subsidies or flexible charging regulations. The authors conclude that this model serves as an intermediate step toward validating policies that encourage technology adoption, with future work involving validation through behavioral experiments and participatory simulations with industry stakeholders. This approach offers a more realistic representation of innovation processes than traditional models, accounting for the complex social and economic dynamics inherent in the ATM sector.

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