摘要
Enhancing the efficiency of public services is essential to residents in mountainous areas. It is also important to promote sustainable development of these regions. Analysing residents' satisfaction with public services in mountainous areas can help in evaluating outcomes of fiscal investment and identifying potential coping approaches for improving public service efficiencies. The residents' satisfaction with public services and the factors that influence such satisfaction were examined in this study. A study of 12 towns located in the southwestern Sichuan Province was performed using an entropy-weighted analytic hierarchy process(EWAHP), the technique for order preference by similarity to ideal solution(TOPSIS) and Tobit regression methods. The results indicate that: 1) the spatial distribution of satisfaction with public services is non-uniform, and the spatial distribution structure varies for different types of public services. 2) Residents' satisfaction with public services is influenced by both objective and subjective factors. Population density, economic distance, social and cultural divisions and elevation are the major objective factors, whereas bounded rationality, the hierarchy of needs and service expectations are the main subjective factors. The most effective strategies for enhancing residents' satisfaction with public services are likely to be clustering the population, choosing supply centres with different public services, regulating the cultural division in ethnic minority towns, selecting supply priorities in accordance with residents' needs, implementing targeted intervention policies and establishing ‘bottom-up' and ‘top-down' integrated decision-making mechanisms.
Abstract: Enhancing the efficiency of public services is essential to residents in mountainous areas. It is also important to promote sus- tainable development of these regions. Analysing residents' satisfaction with public services in mountainous areas can help in evaluating outcomes of fiscal investment and identifying potential coping approaches for improving public service efficiencies. The residents' satisfaction with public services and the factors that influence such satisfaction were examined in this study. A study of 12 towns located in the southwestern Sichuan Province was performed using an entropy-weighted analytic hierarchy process (EWAHP), the technique for order preference by similarity to ideal solution (TOPSIS) and Tobit regression methods. The results indicate that: 1) the spatial distribu- tion of satisfaction with public services is non-uniform, and the spatial distribution structure varies for different types of public services. 2) Residents' satisfaction with public services is influenced by both objective and subjective factors. Population density, economic dis- tance, social and cultural divisions and elevation are the major objective factors, whereas bounded rationality, the hierarchy of needs and service expectations are the main subjective factors. The most effective strategies for enhancing residents' satisfaction with public ser- vices are likely to be clustering the population, choosing supply centres with different public services, regulating the cultural division in ethnic minority towns, selecting supply priorities in accordance with residents' needs, implementing targeted intervention policies and establishing 'bottom-up' and 'top-down' integrated decision-making mechanisms. Keywords: mountainous areas; public services; residents' satisfaction; entropy-weighted analytic hierarchy process (EWAHP); technique for order preference by similarity to ideal solution (TOPSIS); Tobit regression; southwestern Sichuan Province
基金
Under the auspices of the National Natural Science Foundation of China(No.41601141,41471469)
Humanities and Social Sciences Youth Foundation of Ministry of Education of the People’s Republic of China(No.14YJCZH130)
Soft Science Research Projects of Science and Technology Office of Sichuan Province(No.2015ZR0115)
Research Foundation of Chengdu University of Information Technology(No.KYTZ201628,J201617)