Abstract
This study attempts to investigate a method for creating an index from mobility data that not only correlates with the number of people who relocate to a place, but also has causal influence on the number of such individuals. By creating an index based on human mobility data, it becomes possible to predict the influence of urban development on future residential movements. In this paper, we propose a method called the travel cost method for multiple places (TCM4MP) by extending the conventional travel cost method (TCM). We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of a neighborhood. However, conventional TCM does not assume that the opportunity cost of travel time varies according to the departure place. In this paper, TCM4MP is proposed to estimate the opportunity cost of travel time with respect to the departure place. We consider such estimation to be possible due to the use of massive mobility data. We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of the neighborhood. Therefore, we consider that the opportunity cost of travel time has a causal influence on future residential mobility. In this paper, the validity of the proposed method is tested using the smart card data of public transportation in Western Japan. Our proposed method is beneficial for urban planners in estimating the effects of urban development and detecting the shrinkage and growth of a population.
Highlights
Urban planners are making efforts to make cities livable for residents; They are making efforts to predict future population change
We propose a method called TCM4MP to infer the opportunity cost of travel time that varies according to the given place as an index for predicting the number of people who relocate to each place
We have investigated a method for creating an index based on mobility data to estimate the effects of urban development on residential movements
Summary
Urban planners are making efforts to make cities livable for residents; They are making efforts to predict future population change. It is difficult to follow urban development quickly to estimate the effects of urban development on future residential mobility. Previous studies have shown that the urban form influences both non-work travel behavior [1,2,3,4] and residential mobility [5,6]. The amenities of residential neighborhoods reduce the need for non-work travel to distant places and increase the number of in-migrants. If shopping centers and parks are located in a neighborhood, residents do not have to go to shopping centers and parks located far away. Such convenience contributes to an increase in residential movements to such a location
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