Evaluation and obstacle degree analysis of low-carbon development level in Fujian province–based on entropy weight TOPSIS method

Abstract

With the introduction of “dual carbon” goals of “peaking its carbon emissions before 2030 and achieving carbon neutrality by 2060" and the gradual promotion of the carbon trading market, it is the main trend to achieve low-carbon and clean development in the future. It is of great practical significance to effectively measure the low-carbon development level and conduct obstacle degree analysis. Based on this, this article aims to investigate the low-carbon development level index of Fujian province from 2006 to 2019 by using the entropy weight TOPSIS model. Then, the key influencing factors are explored by using the obstacle degree model. The results show that the low-carbon development level index of Fujian province shows a fluctuating upward trend, rising from 0.164 in 2006 to 0.803 in 2019. The environmental system has always been an important factor affecting the low-carbon development in Fujian province, with an average annual obstacle degree of 46.52%, but the impact of the other three subsystems is also gradually increasing. Green innovation, energy conservation, air pollution, economic development, and environmental governance are the top five indexes with the highest annual obstacles. Based on the previous results, this article puts forward corresponding policy recommendations, which provide theoretical support for the low-carbon development of Fujian province.

Determinants of Low-Carbon Logistics Capability Based on Dynamic fsQCA: Evidence from China’s Provincial Panel Data

“…As a generally used MCDM method, the technique for order preference by similarity to an ideal solution (TOPSIS) is a methodology used to sort finite evaluation objects according to their proximity to the ideal solution, which has been widely used to evaluate concerns [42,46]. In order to highlight the varying degrees of importance of various indicators in the evaluation index, this paper employs the entropy method to calculate the weights for multiple indicators and then combines the TOPSIS model to evaluate and rank the low-carbon logistics capacity [47,48]. Further, in order to identify the multifactor combination influencing the effect of regional low-carbon logistics capacity, this paper will use the dynamic fsQCA model to conduct a comparative analysis of low-carbon logistics capacity and put forward corresponding countermeasure suggestions to accelerate the process of regional low-carbon logistics capacity construction with high quality.…”

“…Considering the previous literature review and referencing Che et al [6], Zhou et al [7], and Xiang et al [47], this paper selects the outcome variable and antecedent conditions accordingly. The outcome variable is the low-carbon logistics capability (LCL).…”

Regional Difference and Obstacle Factors of China’s High-Quality Development from the Perspective of Coupling Coordination

“…This paper mainly evaluates the subsystem of openness from outer circulation and inner circulation [44]. (6) The subsystem of sharing. Sharing development is aimed at solving the unequal distribution and insufficient sharing of social resources in China.…”

“…At present, the issue of carbon emissions cannot be ignored [4,5]. In 2020, China introduced the "dual carbon" goals of "peaking its carbon emissions before 2030 and achieving carbon neutrality by 2060" [6]. The "dual carbon" goal brings pressure and challenges to China's high-quality development and also provides a new impetus.…”

An Evaluation System of the Modernization Level of Irrigation Districts with an Analysis of Obstacle Factors: A Case Study for North China

“…There are various mathematical techniques that can be classified as MCDM methods and used for irrigation district evaluation, such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [20], Bayesian Network (BN) models [21], Data Envelopment Analysis (DEA) [22], the Variable Fuzzy Set (VFS) [23], the Weighted Average Method [24], the Project Pursuit Model [25], VIse Kriterijumski Optimizacioni Racun (VIKOR) [26], and the Best-Worst Method (BWM) [27]. Among these methods, TOPSIS is a decisionmaking technique for multiple-objective decision analysis that was proposed by Hwang and Yoon [28,29] and has been successfully applied in many fields, including, but not limited to, electrical network management [30], assessments [31,32], human resource management [33], supplier selection [34], and carbon regulation [35,36]. Here, an emphasis is placed on the quantifiable difference between the evaluation object's state at a specific time and the ideal state, which can be effectively handled by TOPSIS [37,38].…”