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.

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This paper discusses how the neighbours affect the decision of consumer behaviour over diffusion of innovation. An agent-based model of diffusion is proposed on an online social network which have both "scale-free" and "regular" properties. The findings of the studies of consumer activity in order to show the following points: 1) the informative effect can cause a takeoff , but it is not sufficient to reach the completion of diffusion, 2) the combination of the informative and normative effects can easily bring a takeoff , which is a point in time within the adoption curve that the existence of a sufficient amount of adopters of an innovation or a product. After the takeoff , the diffusion is accelerated and reaches the completion in the end, 3) the informative effect makes information propagate fast, and so does the normative effect over a network that has characteristics of scale-free and high cluster, 4) in a selective advertisement, the most effective approach is non-selective advertisement for all consumers. This paper shows that it is inadequate to think that opinion leaders only adopt a product and transmit the information of usability impressions to other consumers in order to trigger diffusion on online human-relationship networks. Rather, diffusion is promoted entirely by active communication among non-opinion leaders which have received such information from opinion leaders.