Agent-Based Self-Service Technology Adoption Model for Air-Travelers: Exploring Best Operational Practices

Abstract

The continuous development of the service economy and an aging society with fewer children is expected to lead to a shortage of workers in the near future. In addition, the growth of the service economy would require service providers to meet various service requirements. In this regard, self-service technology (SST) is a promising alternative to securing labor in both developed and emerging countries. SST is expected to coordinate the controllable productive properties in order to optimize resources and minimize consumer stress. As services are characterized by simultaneity and inseparability, a smoother operation in cooperation with the consumer is required to provide a certain level of service. This study focuses on passenger handling in an airport departure lobby with the objective of optimizing multiple service resources comprising interpersonal service staff and self-service kiosks. Our aim is to elucidate the passenger decision-making mechanism of choosing either interpersonal service or self-service as the check-in option, and to apply it to analyze several scenarios to determine the best practice. The experimental space is studied and an agent-based model is proposed to analyze the operational efficiency via a simulation. We expand on a previous SST adoption model, which is enhanced by introducing the concept of individual traits. We focus on the decision-making of individuals who are neutral toward the service option, by tracking the actual activity of passengers and mapping their behavior into the model. A new method of validation that follows a different approach is proposed to ensure that this model approximates real-world situations. A scenario analysis is then carried out with the aim of exploring the best operational practice to minimize the stress experienced by the air travelers and to meet the business needs of the airline managers at the airport. We collected actual data from the Departure Control System of an airline to map the real-world data to the proposed model. Passenger behavior was extracted by front-line service experts and clarified through consecutive on-site observations.

Self-Service Technology in the Hospitality and Tourism Settings: A Critical Review of the Literature

“…Through the successful adoption of SSTs, firms and customers enjoy many direct and indirect postadoption benefits (Gummerus et al, 2019). On the one hand, direct benefits refer to improvements in internal efficiency, including reduced labor and transaction costs (Curran et al, 2003; Ueda & Kurahashi 2018). On the other hand, SSTs have indirect benefits of improving the relationship between the company and its customers and competitors and enhancing the competitive advantage of the company (Curran et al, 2003).…”

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“…Hipotesis 9 didasari oleh penelitian sebelumnya yang menjelaskan bahwa Social Influence, tingkat keberpengaruhan orang penting yang berkaitan dengan petugas dapat mempengaruhi penggunaan m-Services (Ueda & Kurahashi, 2018). Dalam penelitian (Ayodeji & Rjoub, 2021) bahwa Social Influence dapat memberikan signifikansi yang positif terhadap minat penggunaan e-learning application.…”

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