Abstract

The gravity model is a widely recognized tool for estimating the movement of people and goods. In this study, we introduce two gravitational variables, population size and regional GDP per capita (RGDPPC), to explain the characteristics of population movement between and within cities in South Korea. A log-linearized gravity model is employed to run regression analyses at three spatial levels: the national level (encompassing the entirety of South Korea), the metropolitan level (focusing on the Seoul and Busan Metropolitan Transportation Areas) and the city level (specifically in Seoul and Busan). The study incorporates data on various modes of transportation from 246 of the 250 municipalities in South Korea. Predictive performance of the model is better when utilizing national-level data. However, as spatial area decreases and population density increases, the models explanatory power decreases significantly when relying solely on data related to either population size or RGDPPC. The findings suggest that incorporation of both population size and RGDPPC into the gravity model best captures the dynamics of traffic flow within economically integrated regions. This relationship is analogous to gravitational fields generated by two distinct types of mass. Including both population size and RGDPPC, the gravity model can be leveraged effectively to estimate traffic patterns, particularly within regions characterized by high economic integration.

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