Airport selection from multiple airports using social awareness approach: A case study in Kinki Region, Japan
Tadahiko Murata, Naoki Kasatani
Abstract
Tadahiko Murata, Naoki Kasatani
Abstract
In this paper, we assess a train fare strategy by developing an agent-based simulation tool for air travelers' airport selection in Kinki Region, Japan. Kinki Region includes four prefectures that are Osaka, Hyogo, Nara and Kyoto. That region has three airports for domestic travelers: Osaka Airport, Kansai Airport and Kobe Airport. Since Osaka Airport and Kobe Airport locate near to the urban area of Kinki Region, it is important for Kansai Airport to take some actions to collect more air travelers. In order to share air travelers in this region, cooperation among these three airports is highly important. We assess a train fare strategy in order to attract more travelers by reducing the access fee to the airport using an agent-based simulation tool. In developing simulation tool, we employ a social awareness approach. That is, we develop parameters in our tool based on real statistics. Simulation results show an appropriate train fare for Kansai Airport.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In this paper, we assess a train fare strategy by developing an agent-based simulation tool for air travelers' airport selection in Kinki Region, Japan. Kinki Region includes four prefectures that are Osaka, Hyogo, Nara and Kyoto. That region has three airports for domestic travelers: Osaka Airport, Kansai Airport and Kobe Airport. Since Osaka Airport and Kobe Airport locate near to the urban area of Kinki Region, it is important for Kansai Airport to take some actions to collect more air travelers. In order to share air travelers in this region, cooperation among these three airports is highly important. We assess a train fare strategy in order to attract more travelers by reducing the access fee to the airport using an agent-based simulation tool. In developing simulation tool, we employ a social awareness approach. That is, we develop parameters in our tool based on real statistics. Simulation results show an appropriate train fare for Kansai Airport.
Key concepts: International airport, Transport engineering, Order (exchange), Selection (genetic algorithm), Computer science, Engineering, Business, Finance