Affiliation:
1. School of Engineering, The University of Tokyo, Japan
2. GRID INC., Japan
3. Institute for AI and Beyond of the University of Tokyo, Japan
Abstract
There has been a growing interest in transdisciplinary approaches to improve the added value of cities, such as smart cities. To add value to a city, not only the hard infrastructure but also the soft systems are important. Systematic distribution of incentives such as the holding of events and the issuing of coupons is significant as a means of creating liveliness in cities. This paper proposes a system that supports effective incentive selection using a human flow simulator. A part of the city, including a station and commercial facilities, is reproduced on the simulator by modeling the customer behavior based on actual data. We simulate the behavioral paths of individual customers with different incentives. The list of the incentives is proposed and the result of the simulation suggests insights for the selection of the appropriate incentive to improve sales and the liveliness of the city as a whole.