Suchergebnisse

The lack of adequate indicators in the research of digital economy may lead to the shortage of data support on decision making for governments. To solve this problem, first we establish a digital economy indicator evaluation system by dividing the digital economy into four types: "basic type", "technology type", "integration type" and "service type" and select 5 indicators for each type. On this basis, the weight of each indicator is calculated to find the deficiencies in the development of some digital economic fields by the improved entropy method. By drawing on the empowerment idea of Analytic Hierarchy Process, the improved entropy method firstly compares the difference coefficient of indicators in pairs and maps the comparison results to the scales 1–9. Then, the judgment matrix is constructed based on the information entropy, which can solve as much as possible the problem that the difference among the weight of each indicator is too large in traditional entropy method. The results indicate that: the development of digital economy in Guangdong Province was relatively balanced from 2015 to 2018 and will be better in the future while the development of rural e-commerce in Guangdong Province is relatively backward, and there is an obvious digital gap between urban and rural areas. Next we extract two new variables respectively to replace the 20 indicators we select through principal component analysis and factor analysis methods in multivariate statistical analysis, which can retain the original information to the greatest extent and provide convenience for further research in the future. Finally, we and provide constructive comments of digital economy in Guangdong Province from 2015 to 2018.

ABSTRACTWith the rapid development of urbanization, urban environmental problems become a big challenge for urban socio‐economic development planning. In this paper, a new Dynamic Assessment method, which integrates technique for order preference by similarity to ideal solution, Entropy weight for time series data analysis, Grey relational analysis and Clustering, is proposed for urban eco‐environmental quality assessment of the Yangtze River Delta and Pearl River Delta in China. A sensitivity analysis is also conducted to identify the influence of weight or value changes of factors. The urban eco‐environmental quality ranking by the proposed method is consistent with the Chinese city competitiveness rankings in 2009 by the Chinese Academy of Social Sciences. It is much easier and more efficient to obtain the urban eco‐environmental quality ranking by the proposed method than by field studies and surveys. Copyright © 2011 John Wiley & Sons, Ltd.

The research analyzes the progress of Member States in the implementation of Europe 2020 strategy targets and goals in 2016–2018. Multiple criteria decision-making approaches applied for this task. The set of headline indicators was divided into two logically explained groups. Interval entropy is proposed as an effective tool to make prioritization of headline indicators in separate groups. The sensitivity of the interval entropy is its advantage over classical entropy. Indicator weights were calculated by applying the WEBIRA (weight-balancing indicator ranks accordance) method. The WEBIRA method allows the best harmonization of ranking results according to different criteria groups—this is its advantage over other multiple-criteria methods. Final assessing and ranking of the 28 European Union countries (EU-28) was implemented through the α-cut approach. A k-means clustering procedure was applied to the EU-28 countries by summarizing the ranking results in 2016–2018. Investigation revealed the countries–leaders and countries–outsiders of the Europe 2020 strategy implementation process. It turned out that Sweden, Finland, Denmark, and Austria during the three-year period were the countries that exhibited the greatest progress according to two headline indicator groups' interrelation. Cluster analysis results are mainly consistent with the EU-28 countries' categorizations set by other authors.

The q-rung orthopair fuzzy set ((ROPFS)-R-q), proposed by Yager, is a more effective and proficient tool to represent uncertain or vague information in real-life situations. Divergence and entropy are two important measures, which have been extensively studied in different information environments, including fuzzy, intuitionistic fuzzy, interval-valued fuzzy, and Pythagorean fuzzy. In the present communication, we study the divergence and entropy measures under the q-rung orthopair fuzzy environment. First, the work defines two new order-alpha divergence measures for (q)ROPFSs to quantify the information of discrimination between two (q)ROPFSs. We also examine several mathematical properties associated with order-alpha (ROPF)-R-q divergence measures in detail. Second, the paper introduces two new parametric entropy functions called "order-alpha (ROPF)-R-q entropy measures" to measure the degree of fuzziness associated with a (ROPFS)-R-q. We show that the proposed order-alpha divergence and entropy measures include several existing divergence and entropy measures as their particular cases. Further, the paper develops a new decision-making approach to solve multiple attribute group decision-making problems under the (ROPF)-R-q environment where the information about the attribute weights is completely unknown or partially known. Finally, an example of selecting the best enterprise resource planning system is provided to illustrate the decision-making steps and effectiveness of the proposed approach ; Chilean Government (Conicyt) through the Fondecyt Postdoctoral Program 3170556

[Background]: Improvement of synergies in medical and nursing services can help governments to optimize the allocation of medical resources ; however, an appropriate evaluation method is critical for a suitable decision process in this regard. [Method]: To assess the medical and nursing service combination (MNSC) at a regional level, this study applied a five-dimension evaluation index composed of 28 basic response areas related to the MNSC development status in China, determining its respective weight through the Delphi and entropy methods. [Result]: This empirical exercise analyzed the MNSC supply system by interviewing nine heads of medical and nursing institutions and eleven healthcare-related government personnel during August of 2020 in Xinxiang City, Henan province, P.R China. Results showed: (1) public satisfaction with the fees charged by Medical and Nursing service Institutions (MNSI) ; (2) Medicare and supply services' policy publicity ; (3) the external financing situation of MNSI ; (4) the medical staff's professional quality ; (5) the medical facilities and supply of MNSI ; and (6) that the recognition level of the development plan of MNSI scored the highest effect on the synergy of MNSC supply among the assessed factors. [Conclusion]: These results showed that an evaluation based on the Delphi and entropy methods can effectively integrate the opinions of experts and related institutions to evaluate synergies on the medical and nursing service supply.

This study is motivated by the Zhuhai municipal government, which needs to select a sustainable ferry operator. Previous research has ignored the evaluation and selection of ferry operators. In addition, since ferry operator evaluation involves conflicting qualitative and quantitative criteria, and there may be uncertainty and ambiguity in the evaluation of criteria by experts, a fuzzy multi-criteria decision-making (MCDM) approach is required to address this challenge. To this end, this paper proposes an integrated MCDM framework model to evaluate and select the best ferry operator. First, a ferry operator evaluation index system with 15 sub-criteria is constructed according to literature and expert opinions; then the fuzzy analytic hierarchy process (FAHP) is used to determine the subjective weight of the criteria, and the entropy weight (EW) method is used to calculate the objective weight of the criteria. We use the linear weighting method to obtain the comprehensive weights of the criteria; finally, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method is adapted to determine the best ranking of the alternatives. This paper takes the Wanshan Islands in Zhuhai as a real case study to verify the proposed FAHP-EW-FTOPSIS method. The results show that the proposed method can be effectively applied to the evaluation and selection of ferry operators. Sensitivity analysis of criteria weights demonstrates the effectiveness and robustness of the proposed framework model. Key findings based on the research provide management insights that can benefit relevant stakeholders. This is the first paper to study the evaluation and selection of ferry operators. Hence, the evaluation index system and integrated framework model proposed in this paper can make important contributions to the evaluation of ferry operators.

AbstractBuilding resilient cities has become a hot topic in urban planning and risk management. Adopting the perspective of the social‐ecological system (SES), this paper incorporated economy–ecology–society–infrastructure into an integrated research framework and established a system for assessing the urban resilience development level. The entropy weight method was combined with a cloud model to systematically calculate and classify the resilience of 31 provinces (cities) in China. The evaluation results show that (1) the overall level of urban resilience in China was relatively low; the regional analysis showed that (2) the urban resilience of the eastern region was higher than the national average and that of the central and western regions, and from the perspective of the four subsystems, (3) the comprehensive development of each subsystem was the key to improving urban resilience. Finally, five improvement strategies were proposed to provide ideas for enhancing urban SES ability.

AbstractIn today's world, creating safe, comfortable, and beautiful slow communities has become an urgent research topic for addressing energy crises, environmental pollution, and traffic congestion. This study explored the relationship between the built environment and residents' leisure-time physical activities in slow communities in Shanghai. This study uses the analytic hierarchy process and entropy weight method to construct a new evaluation model to explore the sustainability mechanism. The results of the study are as follows. First, women participated in walking, jogging, and bicycling activities at a higher rate than men. Second, various leisure-time physical activities have different requirements for the built environment. Third, the built environment of slow communities in Shanghai shows a "pyramid" type of spatial stratification phenomenon. This study contributes to a new evaluation system and optimization model for promoting leisure-time physical activities, providing theoretical and methodological guidance for constructing livable slow communities in developing countries and promoting slow living.

AbstractThe prevailing environmental, social and governance (ESG) framework is currently based on micro‐ESG indicators. Research on national ESG is often limited to theory building and policy analysis. Based on previous scholars, this paper constructs a national ESG index framework consisting of 39 indices and updates the national ESG indices for 121 countries worldwide from 1990 to 2021 using the entropy weight method, aiming to provide a set of instrumental indices that capture the status and evolution of national ESG performance. The research findings are as follows: First, the Gini coefficient shows that the gap between national ESG performance has gradually widened over time. Second, the kernel density distribution suggests that global ESG performance is on the rise. High‐income countries are placing greater emphasis on ESG growth. Third, the results of the Markov transformation matrix suggest that there is a "club convergence" in ESG performance across countries.

With the transition of China's economy from the stage of rapid growth to the stage of high-quality development, the influence of the introduction of FDI on the high-quality development of regional economy has become more and more an issue to be discussed. This paper selects Guangdong Province as the frontier of China's reform and opening up. Combining with the new development concept of innovation, coordination, green, development and sharing, the high-quality development system of Guangdong's economy is constructed and the high-quality development index of Guangdong's economy is measured by entropy weight method. On this basis, empirical analysis of FDI on the quality of Guangdong province's economic development. Research shows that FDI can significantly promote the high-quality economic development of Guangdong, where technological progress and government intervention are important factors to promote the high-quality economic development of Guangdong, while industrial development hinders the high-quality economic development of Guangdong, urbanization has a positive role in promoting the high-quality economic development of Guangdong. However, the results were not significant. The results of quantile regression showed that for different levels of high-quality economic development, the promoting effect of FDI presented differences, specifically, with the improvement of the level of high-quality economic development, the promoting effect of FDI on high-quality economic development presented a gradual downward trend. Guangdong is in the important stage of the high-quality economic development to the objective and the role of FDI on Guangdong economy high-quality development, to distinguish the different economic development level of high-quality parts for the sensitivity of the FDI, specific aim ground is made science and Guangdong economy development stage of FDI into high-quality policy, to ensure high-quality economic growth is of great significance in Guangdong.

[EN] Many techniques exist for the evaluation of nutrient pollution, but most of them require large amounts of data and are difficult to implement in countries where accurate water quality information is not available. New methods tomanage subjectivity, inaccuracy or variability are required in such environments so that watermanagers can invest the scarce economic resources available to restore themost vulnerable areas. We propose a new methodology based on grey clusteringwhich classifies monitoring sites according to their need for nitrogen pollution management when only small amounts of data are available. Grey clustering focuses on the extraction of information with small samples, allowing management decision making with limited data. We applied the entropy-weight method, based on the concept of information entropy, to determine the clustering weight of each criterion used for classification. In order to reference the pollution level to the anthropogenic pressure, we developed two grey indexes: the Grey Nitrogen Management Priority index (GNMP index) to evaluate the relative need for nitrogen pollution management based on a spatiotemporal analysis of total nitrogen concentrations, and the Grey Land Use Pollution index (GLUP index), which evaluates the anthropogenic pressures of nitrogen pollution based on land use. Both indexes were then confronted to validate the classification. We applied the developedmethodology to eight estuaries of the SouthernGulf ofMexico associated to beaches,mangroves and other coastal ecosystems which may be threatened by the presence of nitrogen pollution. The application of the new method has proved to be a powerful tool for decision making when data availability and reliability are limited. This method could also be applied to assess other pollutants. ; This work was supported by Erasmus Mundus -MAYANET Grant Agreement Number 2014-0872/001-001, funded with support of the European Commission, and an Excellence Scholarship awarded by the Mexican Government through the Mexican ...

In the event of pandemic, it is essential for government authority to implement responses to control the pandemic and protect people's health with rapidity and efficicency. In this study, we first develop an evaluation framework consisting of the entropy weight method (EWM) and the technique for order preference by similarity to ideal solution (TOPSIS) to identify the preliminary selection of Fangcang shelter hospitals; next, we consider the timeliness of isolation and treatment of patients with different degrees of severity of the infectious disease, with the referral to and triage in Fangcang shelter hospitals characterized and two optimization models developed. The computational results of Model 1 and Model 2 are compared and analyzed. A case study in Xuzhou, Jiangsu Province, China, is used to demonstrate the real-life applicability of the proposed models. The two-stage localization method gives decision-makers more options in case of emergencies and can effectively designate the location. This article may give recommendations of and new insights into parameter settings in isolation hospital for governments and public health managers.

The Chinese central government has released detailed carbon emissions abatement targets at the provincial level, but provides no specific emissions reduction targets at the city level. Most provincial governments simply allocate carbon emissions reduction tasks to their cities based on the GDP of their cities. Allocation approaches, however, should emphasize the most effective distribution to reach overall targets that reflect actual reduction capacities of cities. This paper proposes an allocation method at the city level by combining a data envelop analysis method, an entropy weight method and a clustering analysis method using the Yangtze River Delta region as a case study. Results of our analysis indicate that cities with higher carbon emissions abatement potentials, financial abilities, a larger number of above-scaled industrial enterprises and higher GDP are better positioned to reduce carbon emissions and should be assigned proportionately higher reduction targets. The merits and policy implications of the proposed approach are discussed in comparison to simply using GDP to allocate emission reduction targets.

This research precisely analyzes the delay causes of one of the most delayed hydropower project in Pakistan. In this study, grey relation analysis has been employed which has strong analytical ability, in the process of grey relational analysis calculation, the same weight cannot fully reflect the optimality of evaluation, so we have used the entropy weight method to improve it, at the same time, we have used full information reflected by the evaluation index. The socioeconomic problems which are delaying this project (Diamar‐Basha dam) which include poor resettlement plan for local people, compensation of land, threat of cultural heritage, and ecological impacts of this project. It gives quantitative analysis by taking into account several issues in infrastructural project activities like historical and geographical disputes between local people and Governments, their socioeconomic impacts on affected population due to lack of finance and land use conflicts. The deeper roots behind the excusable delays of construction of the Diamar‐Basha dam are discovered in its true spirit while the putative reasons are decorated how this project get into such a predicament and further delay in construction of dam will make it a mirage project.

With the rapid development of China&rsquo ; s economy, the demand for water resources continues to sharply increase, which has gradually contributed to serious environmental problems. The Chinese government has proposed establishing a natural resource balance sheet, which is expected to solve this problem by assessing the value of water resources. The main purpose of this study was to assess the value of water resources in Wuhan from 2013 to 2017. Based on a fuzzy mathematical evaluation model, 15 indicators were chosen considering the three main aspects of resources, society, and the environment to construct a water resource evaluation indicator system. In addition, the analytic hierarchy process (AHP) and entropy weight methods were combined to determine the index weight. Based on this, we calculated the value of water resources in Wuhan from 2013 to 2017. The results demonstrated that the values of water resources in Wuhan from 2013 to 2017 were US$2.910 billion, US$5.006 billion, US$9.223 billion, US$14.167 billion, and US$7.189 billion, respectively. Therefore, this paper provides a scientific foundation for the rational establishment of water prices, the assessment of local natural resource assets, and the preparation of natural resource balance sheets.