Spatial and social inequalities of job accessibility in Kunshan city, China: Application of the Amap API and mobile phone signaling data

Abstract

The equity distribution of job accessibility for different traffic modes or different groups of people is a socio-spatial inequalities issue, which analyses and identifies job accessibility gaps. However, few studies have focused on the inequality of accessibility in medium-sized cities of developing countries. This paper aims to determine the spatial gaps of urban public transportation services in Kunshan by analyzing the difference in job accessibility between public transportation and private cars, and social inequalities between different housing price communities. First, resident population and employments data were obtained by mobile phone signaling data, and the travel time of different traffic modes during the morning peak hour were used by the Amap Application Programming Interface (API). This method helps researchers obtain more accurate travel costs because it provides real-time information about traffic conditions. Then we use relative accessibility to identify areas with large accessibility gaps, using the Gini index to evaluate the equity of different housing price communities' job accessibility. The study finds that as the travel time threshold changes, the job accessibility gaps between public transportation and private cars gradually narrow. At the same time, the results of the Gini index show that high house prices communities have a fairer distribution of job accessibility. This research provides a scientific basis for optimizing the socio-spatial distribution of public transportation services in China context.