Residents’ satisfaction with public services in mountainous areas: An empirical study of southwestern Sichuan Province, China

Abstract

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.

Spatio-Temporal Impact of Rural Livelihood Capital on Labor Migration in Panxi, Southwestern Mountainous Region of China

“…This study used the entropy value method (EVM) to calculate the weights of each indicator. EVM is a weight measure method from thermodynamics, where, using EVM to analyze the weight of each indicator is mainly considered the concept and properties of entropy, but also contains the relative importance degree of each indicator (Song et al, 2017). Using the EVM to calculate the weight can eliminate the interference of human factors, so that the evaluation results are more scientific and reasonable.…”

Efficiency Evaluation of China’s Public Sports Services: A Three-Stage DEA Model

“…The regional GDP allows local governments to allocate production resources, provide public sports goods and services, and improve the efficiency of public sports services. Furthermore, each region's population is based on the natural environment and economic activities, and any rapid change in population size greatly impacts the region's social resources and environmental development, which directly affects the efficiency of government public sports services [35]. Other scholars have argued that the population density of a region is negatively correlated with the cost of government management and supervision.…”

Spatio-temporal Difference and Influencing Factors of Environmental Adaptability Measurement of Human-sea Economic System in Liaoning Coastal Area

“…TOPSIS method is a comprehensive evaluation method which can be used to compare and select according to multiple schemes and indexes. The Entropy weight-TOPSIS is an improvement for the traditional TOPSIS method, traditional TOPSIS weight mainly uses the analytic hierarchy process and the Delphy method with certain subjectivity, Entropy weight-TOPSIS can effectively compensate the defects of subjectivity and arbitrariness, and reflect the indicator information (Du et al, 2014;Liu et al, 2016b;Song et al, 2017). Based on the entropy weight-TOPSIS, the basic steps of environmental adaptability evaluation method of human-sea economic system in Liaoning coastal area are as follows:…”

“…The environmental adaptability index of human-sea economic system in Liaoning coastal area is censored data, which as the dependent variable of regression equation is limited to the range from 0 to 1, if the direct use of ordinary least squares, the estimated parameters will prone to bias, while the panel Tobit model is just dealing with cases where the dependent variable of the regression model is limited. Therefore, the panel Tobit model is used to analyze the factors that may affect the environmental adaptability of human-sea economic system (Guo and Wang, 2015;Kong, 2016;Song et al, 2017). Explanatory variables select marine industry location entropy (X 1 )to characterize marine economic development level, foreign trade dependence degree (X 2 ) characterization of marine industry opening up level, science and education investment accounted as percent- age to fiscal expenditure (X 3 ) characterization of science and technology factors, port cargo throughput (X 4 ) to characterize the level of port construction, industrial structure advanced coefficient (X 5 ) characterization of marine industrial structure, ratio of industrial solid waste utilized (X 6 ) characterization of environmental management.…”