An interactive city choice model and its application for measuring the intercity interaction

TL;DR

This paper introduces a parameter-free interactive city choice (ICC) model based on individual choice behavior to measure intercity interactions, applied to Chinese cities, showing improved consistency over traditional models.

Contribution

The paper proposes a novel ICC model that eliminates the need for parameter setting and better captures intercity interactions from a behavioral perspective.

Findings

ICC model applied to 339 Chinese cities

Model results align more closely with real-world data

Analyzed impact of transportation network changes from 2005 to 2018

Abstract

Measuring the interaction between cities is an important research topic in many disciplines, such as sociology, geography, economics and transportation science. The traditional and most widely used spatial interaction model is the gravity model, but it requires the parameters to be artificially set. In this paper, we propose a parameter-free interactive city choice (ICC) model that measures intercity interaction from the perspective of individual choice behavior. The ICC model assumes that the probability of an individual choosing to interact with a city is proportional to the number of opportunities in the destination city and inversely proportional to the number of intervening opportunities between the origin city and the destination city, calculated using the travel time in the transportation network. The intercity interaction intensity can be obtained by calculating the product of this probability and the origin city's population. We apply the ICC model to measure the interaction intensity among 339 cities in China and analyze the impact of changes in the Chinese land transportation network from 2005 to 2018 on the intercity and city interaction intensity. Compared with the previously widely used spatial interaction models, the measurement results of the ICC model are more consistent with the actual situation.