Jiangxi University of Finance and Economics

About: Jiangxi University of Finance and Economics is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Fuzzy logic & China. The organization has 2865 authors who have published 3556 publications receiving 41567 citations.

A method to analyze the rank reversal problem in the ELECTRE II method

Abstract: In multi-criteria decision-making (MCDM) methods, the rank reversal is a highly important problem for analyzing the reliability of MCDM methods. The main objective of this paper is to analyze and precisely predict the occurrence of rank reversal in the ELECTRE II method. First, some useful properties of the optimal alternatives are obtained in the descending and ascending distillation processes. Second, two new concepts named combination relation digraph and numerator matrix are proposed to precisely analyze and greatly simplify the rank reversal in the ELECTRE II method. Third, all the reasons for the rank reversal in the ELECTRE II method are revealed more completely. Fourth, the necessary and sufficient conditions are proposed for determining whether or not the rank reversal occurs in the ELECTRE II method. Additionally, the proposed methods in this paper are valid for analyzing the rank reversal in the ELECTRE method with discriminating thresholds. Finally, five examples are used to evaluate the correctness and effectiveness of the methods that are proposed in this paper.

Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study

Abstract: Background The 2019 novel Coronavirus (COVID-19) emerged in Wuhan, China in December 2019 and has been spreading rapidly in China. Decisions about its pandemic threat and the appropriate level of public health response depend heavily on estimates of its basic reproduction number and assessments of interventions conducted in the early stages of the epidemic. Methods We conducted a mathematical modeling study using five independent methods to assess the basic reproduction number (R0) of COVID-19, using data on confirmed cases obtained from the China National Health Commission for the period 10th January – 8th February. We analyzed the data for the period before the closure of Wuhan city (10th January – 23rd January) and the post-closure period (23rd January – 8th February) and for the whole period, to assess both the epidemic risk of the virus and the effectiveness of the closure of Wuhan city on spread of COVID-19. Findings Before the closure of Wuhan city the basic reproduction number of COVID-19 was 4.38 (95% CI: 3.63 – 5.13), dropping to 3.41 (95% CI: 3.16 – 3.65) after the closure of Wuhan city. Over the entire epidemic period COVID-19 had a basic reproduction number of 3.39 (95% CI: 3.09 – 3.70), indicating it has a very high transmissibility. Interpretation COVID-19 is a highly transmissible virus with a very high risk of epidemic outbreak once it emerges in metropolitan areas. The closure of Wuhan city was effective in reducing the severity of the epidemic, but even after closure of the city and the subsequent expansion of that closure to other parts of Hubei the virus remained extremely infectious. Emergency planners in other cities should consider this high infectiousness when considering responses to this virus. Funding National Natural Science Foundation of China, China Medical Board, National Science and Technology Major Project of China

Measuring the Total-Factor Carbon Emission Performance of Industrial Land Use in China Based on the Global Directional Distance Function and Non-Radial Luenberger Productivity Index

Abstract: Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote the sustainable use of industrial land. This paper aims to analyze the dynamic changes in the total-factor carbon emission performance of industrial land use (TCPIL) in China by applying a global directional distance function (DDF) and non-radial Luenberger productivity index. The empirical results show that the eastern region enjoys better TCPIL than the central and western regions, but the regional gaps in TCPIL are narrowing. The growth in NLCPILs (non-radial Luenberger carbon emission performance of industrial land use) in the eastern and central regions is mainly driven by technological progress, whereas efficiency improvements contribute more to the growth of NLCPIL in the western region. The provinces in the eastern region have the most innovative and environmentally-friendly production technologies. The results of the analysis of the influencing factors show implications for improving the NLCPIL, including more investment in industrial research and development (R&D), the implementation of carbon emission reduction policies, reduction in the use of fossil energy, especially coal, in the process of industrial production, actively learning about foreign advanced technology, properly solving the problem of surplus labor in industry and the expansion of industrial development.