Abstract
Concentrating on geographically hierarchical data structures and using large-scale satisfaction survey data in Nanjing, this study employs Bayesian spatial multilevel model (MLM) to evaluate Nanjing’s perceived sustainable urbanization. In this study, we consider the geographically hierarchical data structures and the city’s individual perceptions of sustainable urbanization to explore the effect of environment and self-rated health on perceived sustainable urbanization, controlling for individual sociodemographic attributes and household. Through clarifying the spatial dependence and heterogeneity, this paper provides a flexible framework for assessing sustainable urbanization and dealing with the geographical hierarchical data. In particular, by drawing on existing studies, our questionnaire is more representative of the overall characteristics of Nanjing’s population than census data, which can be helpful for understanding whether urbanization is sustainable from individual perspective and further for correcting practices. Based on a survey of 10,077 questionnaires, this paper finds the geographically hierarchical data structures have significantly influenced the evaluation of sustainable urbanization, and the Bayesian spatial MLM is an effective tool for evaluating China’s sustainable urbanization. In particular, this paper takes spatial effects into consideration and compares the geographically hierarchical data. Results show that spatial patterns significantly influence the assessment of sustainable urbanization, and perceived pollution, age, education level, and income are the four key factors influencing individual perceived sustainable urbanization.
Highlights
The 20th and 21st centuries have seen rapid urbanization worldwide, and urbanization is seen as one of the most important strategies for development [1]
There is a substantial decrease in deviance information criterion (DIC) values of single-level regression and multilevel model (MLM), from 10,371.29 to 10,293.27, indicating the importance of unobserved district effects
We observed the decrease in DIC values for spatial MLM compared with the MLM
Summary
The 20th and 21st centuries have seen rapid urbanization worldwide, and urbanization is seen as one of the most important strategies for development [1]. After reform and opening-up launched from 1978, China’s urbanization has dramatically increased [2,3,4,5]. From 1978 to 2016, the proportion of China’s urban population increased from 17.9% to over 57.35% [6]. China’s urbanization growth has been at an unprecedented speed [7] and contributed to promoting China’s economic affluence, improving social services [8] and living standards [9]. Sustainable urbanization is a valid solution to promote China’s sustainable urban development [21], and China’s sustainable urbanization has recieved much research focus [22]. In the process of pursuing sustainable urbanization, finding an effective tool for evaluating
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