Quantitative Measurement of the Sustainable Water Resource Development System in China Inspired by Dissipative Structure Theory

In an attempt to ensure sustainable water resource development, this paper constructs a comprehensive scientific index evaluation system focused on the macro socio-economic-ecological environment. Inspired by the theory of dissipative structure, the sustainable development system of water resources is regarded as a complex and huge dissipative system. In order to effectively measure the coordinated development status and orderly evolution trend of the system, this paper uses the information entropy method to construct the measurement model of the water resources system and analyze its internal entropy flow changes. The empirical analysis of the water resources in China from 2007 to 2016 found that coordinated water resource subsystem development could achieve sustainable development, and that over the examined period, the sustainable water resource development system in China became more orderly and coordinated; therefore, the sustainable development aim is gradually being achieved

Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy TOPSIS: A Case Study from 30 Provinces, China

In connection with the sustainable development of scenic spots, this paper, with consideration of resource conditions, economic benefits, auxiliary industry scale and ecological environment, establishes a comprehensive measurement model of the sustainable capacity of scenic spots; optimizes the index system by principal components analysis to extract principal components; assigns the weight of principal components by entropy method; analyzes the sustainable capacity of scenic spots in each province of China comprehensively in combination with TOPSIS method and finally puts forward suggestions aid decision-making. According to the study, this method provides an effective reference for the study of the sustainable development of scenic spots and is very significant for considering the sustainable development of scenic spots and auxiliary industries to establish specific and scientific countermeasures for improvement

Reliability Evolution of Elevators Based on the Rough Set and the Improved TOPSIS Method

Focusing on reliability evaluation of elevator equipment operation, this paper builds a model for reliability evaluation of elevator equipment. First, we analyze the factors influencing the reliability of elevators and extract the initial evaluation indicators from four macro-perspectives: people, management, equipment, and environment, to build the index system for reliability evaluation of elevator equipment. And, we reduce the indicator set to remove the unnecessary indicators by using the rough set and weight the reduced indicators according to expert opinions. Finally, on this basis, we combine the grey number theory with the TOPSIS method to build an improved TOPSIS evaluation model, to evaluate the reliability of elevators and determine the optimal ordering

Measurement and Prediction of Regional Tourism Sustainability: An Analysis of the Yangtze River Economic Zone, China

In view of sustainable development of tourism, this paper firstly constructs a more comprehensive and scientific index system from the economical/societal/resource-related/environmental aspects of tourism and evaluates the sustainable and comprehensive development level of tourism in 11 provinces and cities of the Yangtze River economic zone by using the weighted TOPSIS (The Technique for Order Preference by Similarity to an Ideal Solution ) method; secondly, it analyzes the coupling coordination evolution relationship between tourism and the economy/society/resources/environment in different provinces and cities of the Yangtze river economic zone based on the coupling coordination model from the spatio-temporal dimension; and finally, it predicts the coupling coordination degree of the provinces and cities in the region in the next few years by the grey model (1,1) and puts forward some countermeasures and suggestions. According to the study, this method provides an effective reference to the study on the sustainable development of tourism and is very significant for learning the sustainable development of regional tourism and establishing specific and scientific countermeasures for improvement

How Would Economic Development Influence Carbon Productivity? A Case from Hubei in China

Carbon productivity, defined as the gross domestic product (GDP) per unit of CO2 emissions, has been used by provincial governments in China as in indicator for effort and effect in addressing climate-change problems. The aggregate impact of economic growth on carbon productivity is complex and worthy of extensive investigation to design effective environmental and economic policies. Based on a novel combination of the smooth transition regression model and the Markov regime-switching regression model, this paper analyzes time series data on carbon productivity and economic growth from Hubei Province in China. The results show that the influence of economic growth on carbon productivity is highly nonlinear. In general, economic growth has a positive impact on improving carbon productivity. From a longitudinal perspective, this nonlinear positive impact is further divided into three stages, transiting from a high regime to a low regime and then back to a high regime. The high regime stage, in which economic growth has stronger positive influence on enhancing carbon productivity, is expected to last for considerably longer time than the low regime stage. It is more probable for a low regime stage to transit to a high regime. Once the relation of carbon productivity and economic growth enters the high regime status it becomes relatively stable there. If the government aims to achieve higher carbon productivity, it is helpful to encourage stronger economic development. However, simply enhancing carbon productivity is not enough for curbing carbon emissions, especially for fast growing economies

Impacts of Haze on Housing Prices: An Empirical Analysis Based on Data from Chengdu (China)

Based on cross-section data of 20 districts in Chengdu, this article reviews the relationships between haze and housing prices with the combined application of Spatial Error Model (SEM) and Spatial Lag Model (SLM). The results illustrate that haze significantly have negative impacts on both the selling and rental prices of houses. Controlling other variables, if the air quality index rises by 0.1, the housing selling prices and rental prices will drop by 3.97% and 4.01%, respectively. Interestingly, housing rental prices have a more significant response to the air quality than housing sale prices. Residents are willing to pay a premium for better air quality and the influence of air quality is partially reflected in housing prices, which indicates that better air quality has been becoming a scarce resource with the improvement of people’s living standard. Furthermore, the impacts of haze on housing prices are also expected to lead to a “crowding out effect” in different regions. This would be detrimental for human capital accumulation and will accelerate the regional divergence in the internal economy and population structure, thus forming a region “fence” within cities