Fuzzy-based multi-criteria decision analysis of environmental regulation and green economic efficiency in a post-COVID-19 scenario: the case of China

Pollution characteristics, distribution and risk level of heavy metals in sediments of the Yangtze River estuary

Pollution characteristics, distribution, risk and sources of 7 heavy metals in sediments of Yangtze River Estuary were investigated. Total concentration ranges of As, Cr, Cu, Cd, Pb, Zn and Ni were [0, 16.5], [1.48, 51.3], [2.66, 318], [0, 0.99], [35.6, 992], [8, 91.3] and [1.88, 108] mg/kg, respectively. Based on the potential ecological risk index and Geoaccumulation index, it was determined that Pb is the most polluted heavy metal. According to class I standard of "Marine sediment quality" of China, mean baseline levels multiples were Pb (8.34) > Cu (0.57) > Cr (0.37) > Zn (0.355) > Ni (0.352) > As (0.28) > Cd (0.00). The study also found the heavy metal content of Pb is the most serious, but most of the Pb content comes from the residual state, which has minimal impact on the environment. The East Nanhui Shoal was identified as the most polluted sub-area in terms of Pb pollution, followed by other specific locations. Considering the pollution level and transport costs, the study concluded that dredge soils of the Yangtze River Estuary Deepwater Channel are not suitable for the restoration of East Hengsha Shoal.

Assessing and prioritizing drivers and strategies for transition to a green energy for sustainable development in China

This study addresses the critical global challenge of climate change, primarily caused by the overconsumption of fossil fuels. Recognizing the urgent need for a transition to green energy (GE) sources such as wind, solar, hydro, and biomass, this research focuses on identifying effective strategies for fostering a sustainable and low-carbon energy future in China. The study employs a combination of the Analytical Hierarchy Process (AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL), both well-established multi-criteria decision-making (MCDM) methods, to analyze various drivers, sub-drivers, and strategies crucial for this transition. Through an extensive literature review, we identified several key drivers and strategies aiding the shift towards GE for sustainable development. The AHP method was applied to evaluate and rank the major drivers and sub-drivers, such as policy, financing, and infrastructure and innovation, that are crucial for China's successful transition to GE. Simultaneously, fuzzy DEMATEL was utilized to prioritize vital strategies, including public awareness and education, financial incentives and support mechanisms, and policy and regulatory frameworks. The findings reveal that, in addition to strong policy and financial support, public awareness and education are critical for advancing GE development in China. This study underscores the importance of integrating various drivers and strategies for effective green energy development, aiming to mitigate the environmental impacts of fossil fuel use.

Spatiotemporal differentiation and convergence characteristics of green economic efficiency in China: from the perspective of pollution and carbon emission reduction

Accurate quantification of pollution and carbon emission reduction policies, as well as analysis of green economic efficiency (GEE), are of great significance to accelerating green economic development in China and contributing to pollution prevention and carbon peaking. Using data from 2006 to 2022, this study incorporates pollution and carbon emission reduction policies into the evaluation system, and uses a model with slacks-based measures and a directional distance function (SBM-DDF) to calculate the GEE of 30 provinces. The Dagum Gini coefficient, kernel density estimation, and spatiotemporal convergence analysis are used to analyze the spatiotemporal differentiation and convergence characteristics of GEE. The findings show that the strengths of the pollution and carbon emission reduction policies are increasing but vary greatly among the provinces. China's overall GEE has a time trend with the characteristics of "decline-fluctuation-stable." The Dagum Gini coefficient reveals the relative differences between the major regions. Both the intra-regional and inter-regional differences tend to widen over time and the latter explains most of the sources of the overall differences. Kernel density estimation shows that the absolute differences between the provinces are generally widening, whereas the absolute differences between the provinces in the central and western regions are smaller than those in the eastern region. No obvious σ convergence characteristics exist in the country overall and the three major regions, but β convergence characteristics are present in each region. The factors affecting changes in the GEE of each region are not the same. The study suggests that the China should further improve the implementation of pollution and carbon emission reduction policies, pay attention to the regional differences and convergence issues of GEE, and promote the coordinated development of green economy in different regions. This study innovatively quantifies the policies related to pollution and carbon emission reduction, providing empirical evidence for understanding the performance of pollution and carbon emission reduction policies in various regions. Furthermore, this study incorporates policies as inputs into the GEE evaluation system, reveals the spatiotemporal differentiation of GEE, thereby providing reference for green economic transformation and sustainable development.

Exploring the sustainable development path of green financial system in the context of carbon neutrality and carbon peaking based on quality function deployment and G1-entropy methods: Evidence from China

In the 75th session of the United Nations General Assembly, the Chinese government first proposed the goal of carbon neutrality and carbon peaking. Since then, China’s economy and society have undergone a comprehensive green and sustainable development upgrade and transformation. The development of green finance can provide financial support for achieving dual carbon goals and mitigate the impact of climate change. More importantly, it can contribute to the national economy’s and society’s sustainable development. We innovatively draw on the quality function deployment theory in marketing to logically formulate the research idea of this paper. On this basis, we also apply the G1-entropy method from fuzzy mathematical theory for quantitative research. We innovatively address the actual national conditions in China and fully integrate green elements in constructing the index system from green finance and sustainability perspectives. Finally, we calculate index weights through G1-entropy quantification to assess the development quality of China’s green financial system and qualitatively propose countermeasures for the quality of China’s green financial development with respect to key index factors. Specifically, we sort out this paper in the following three aspects: (1) we innovatively combined the quality function deployment theory and built the quantitative analysis process architecture in this paper, which enhanced the readability of this paper (2) we realized the use of quantitative research for qualitative analysis and proposed the G1-entropy value method, which made up for the defects of the subjective and objective methods in the traditional assessment methods (3) we realized the organic combination of quantitative and qualitative analysis and proposed relevant countermeasure suggestions based on the quantitative index calculation results, which provided relevant countermeasure suggestions for promoting the sustainable and high-quality development of green finance in China. Our study will provide a set of perfect assessment methods for the quality improvement path and sustainable development strategy formulation after the construction of China’s future green financial system. It can also provide a reference assessment idea for the high-quality and sustainable development of China’s green finance, which will further help China’s economic transition to green and low-carbon and the achievement of the double carbon goal.

Analyzing inclusive green growth in China: a perspective of relative efficiency

Inclusive Green Growth (IGG) has important reference value for China's ecological civilization construction and transformation of economic development. Therefore, this study assesses China's IGG level from the perspective of relative efficiency. The IGG efficiency (IGGE) was measured at the provincial level in China from 2000 to 2020 by using Super-Epsilon-Based Measure (EBM) model that considers undesirable outputs. The spatiotemporal pattern of IGGE was analyzed by kernel density estimation and spatial autocorrelation. The results indicate a fluctuating trend from 2000 to 2020 for the IGGE of China, and significant differences between regional and interprovincial IGGE were observed. On average, the eastern region presented the highest efficiency, while the level in the central regions was lowest. There is a positive spatial autocorrelation in the IGGE distribution, and the agglomeration of spatial distribution fluctuated during the study period. The IGGE has spatial spillover effects at the provincial level according to the spatial Durbin model. Among the influencing factors, the spatial spillover effects of industrial structure, government administrative capability, and industrialization level are significant. The regression results also confirm the Environmental Kuznets Curve effect between IGG and economic growth in China. Finally, some implicit policies can be established based on the empirical analysis.

Data-driven evaluation framework for the effectiveness of rural vitalization in China: an empirical case study of Hubei Province

Rural vitalization (RV) has attracted more and more attention in China, especially since the Rural Vitalization Strategy (RVS) was proposed to restrict rural decline in 2017. The evaluation of RV is an effective means to objectively identify the characteristics and problems of rural development, so exploring scientific and rational evaluation methods is important for sustainable rural development. Therefore, this study builds a data-driven evaluation framework from a "bottom-up" perspective, and selects Hubei Province as the object to evaluate the effectiveness of RV. The evaluation index system is formed based on the concept and connotation of RV, which contains six dimensions, namely thriving businesses (TB), pleasant living environments (PLE), social etiquette and civility (SEC), effective governance (EG), living in prosperity (LP), and organization system (OS). The empirical results indicate that there is a low level of variation of the total scores but an obvious disparity in the dimensional scores in 13 prefecture-level and 83 county-level regions. At county-level, the regional development stage has an impact on the effectiveness of RV, and regions with a higher economy or endowed with better resources perform better. The results of spatial analysis further reveal that there is regional agglomeration as well as differences in various dimensions, and regions with characteristic industries or policy support perform better. Compared with the traditional evaluation method, differentiated evaluation objectives and diversified data are considered in the evaluation process of this study. The results and discussion shown in this study could provide empirical evidence for policymakers to effectively promote RV in the future.

Business Model Innovation Paths of Manufacturing Oriented towards Green Development in Digital Economy

China's manufacturing industry has been confronted with the issue of extensive development with high input, high consumption, and high emissions for a long time, and its green development is the key to reaching carbon neutrality in China. Under the digital economy, business model innovation is the fundamental means of the green development of manufacturing enterprises. Four representative listed companies in China's manufacturing were selected as typical cases for the case study. Through open, axial, and selective coding that is based on proceduralized grounded theory, this study profoundly explores business model innovation paths of the manufacturing industry oriented towards green development in the digital economy following the research logic of "green development orientation-business model innovation process-business model innovation result". Moreover, this study further compares the differences among paths and discusses each path's effectiveness and applicable conditions. Results show that: (1) Four green business model innovation paths are revealed based on the four green development orientations: efficiency-oriented path, value-oriented path, user-oriented path, and ecology-oriented path. (2) Different enterprises pursue distinct business model innovation paths. The scientific premise for enterprises to opt for the optimal innovation path is the matching of upgrading demands, existing conditions, and path characteristics. Ultimately, the following policy implications are offered: First, promote the green innovation of business models in the manufacturing industry. Second, consider enterprises' heterogeneity and implement differentiated support policies. This study can serve as theoretical support and decision-making reference for business model innovation and green development in manufacturing enterprises.

Does the construction of innovative cities promote urban green innovation?

As a typical example of an innovative governance environment, innovative city has become the focus of political and academic circles. Discussing the green innovation effect of this policy is beneficial in providing decision support for enhancing urban green innovation capability and solving the dilemma of urban resources. Based on data from 241 cities in China from 2005 to 2017, this paper takes innovative city construction as a "quasi-natural experiment" and uses the difference-in-differences method to empirically study the impact of China's innovative city construction on urban green innovation. The results show that innovative urban construction: has a positive effect on improving urban green innovation, and that this effect will gradually increase with time; promotes urban green innovation by expanding the scope of technology application, improving the efficiency of resource allocation and promoting the adjustment of industrial structure; and presents heterogeneity in cities' location, size and hierarchy. Finally, this paper proposes that the government should promote innovative policies in an orderly manner on the basis of following the principle of adapting measures to local conditions, as well as incorporating green innovation performance into the evaluation system for innovative city construction.

To what extent do waste management strategies need adaptation to post-COVID-19?

The world has been grappling with the crisis of the COVID-19 pandemic for more than a year. Various sectors have been affected by COVID-19 and its consequences. The waste management system is one of the sectors affected by such unpredictable pandemics. The experience of COVID-19 proved that adaptability to such pandemics and the post-pandemic era had become a necessity in waste management systems and this requires an accurate understanding of the challenges that have been arising. The accurate information and data from most countries severely affected by the pandemic are not still available to identify the key challenges during and post-COVID-19. The documented evidence from literature has been collected, and the attempt has been made to summarize the rising challenges and the lessons learned. This review covers all raised challenges concerning the various aspects of the waste management system from generation to final disposal (i.e., generation, storage, collection, transportation, processing, and burial of waste). The necessities and opportunities are recognized for increasing flexibility and adaptability in waste management systems. The four basic pillars are enumerated to adapt the waste management system to the COVID-19 pandemic and post-COVID-19 conditions. Striving to support and implement a circular economy is one of its basic strategies.

A Novel Multi-Criteria Assessment Approach for Post-COVID-19 Production Strategies in Vietnam Manufacturing Industry: OPA–Fuzzy EDAS Model

The global manufacturing supply chain has been disrupted by the negative impacts of the pandemic. In Southeast Asia, Vietnam’s manufacturing industry is one of the most strongly integrated with global and regional supply chains. The production strategies in the “new normal” are the key solution to the survival and sustainable development of manufacturers. This study aims to develop a two-stage framework to investigate the impacts of COVID-19 and the post-COVID-19 production strategies for Vietnam’s manufacturing industry. As a theoretical contribution, this study proposes a novel and robust integration approach, which combines the Ordinal Priority Approach (OPA) and Fuzzy Evaluation Based on Distance from Average Solution (Fuzzy EDAS), for the first time. The negative impacts of the pandemic were identified and weighted by the OPA method. Then, production strategies were comprehensively evaluated using the Fuzzy EDAS method. Findings indicate that digitization and on-site renewable energy are the most essential recovery strategies for manufacturing in Vietnam. These findings are validated by comparisons with the results of recent multiple criteria decision-making (MCDM) methods. Furthermore, weight sensitivity analysis reveals different suitability of strategies for short-term and long-term negative impacts. As a managerial implication, the multi-scenario ranking results help managers to make resource-allocation decisions for the implementation of post-COVID-19 production strategies.

Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.

How to design regional characteristics to improve green economic efficiency: a fuzzy-set qualitative comparative analysis approach

Developing green economy has become the focus of governments, scholars, and entrepreneurs all over the world; however, the realization path of green economic efficiency for the regions under the interaction of multiple factors has still been uncertain. This study takes 30 provincial-level regions in China as the empirical object and applies a new method of fuzzy-set qualitative comparative analysis to explore the configuration of conditions for achieving green economic efficiency, which effectively improves the link between theory and practice. This study reveals that the improvement of green economy efficiency is the result of the joint action of multiple factors, and one factor in isolation is not enough for explaining it. Besides, there exist three equivalent paths to achieve high green economic efficiency; therefore, regions can design the most appropriate promotion strategy according to the determined paths. The result shows that high marketization is the core condition for achieving high green economy efficiency. Among the three paths, the combination of environmental regulation, urbanization, marketization, and technological innovation has the highest unique coverage, which alone explains how most regions have achieved high green economic efficiency. Third, four paths for achieving low green economy efficiency have been identified in this study, which provides lessons for regional governments to avoid the decline in green economy efficiency. And specially, the combination of high urbanization, high environment regulation, and high technological innovation can lead to low green economy efficiency because of low marketization. The conclusion improves the theory of green development and provides a practical reference for the regional government to develop green economy.

Assessment of green economic efficiency in China using analytical hierarchical process (AHP)

Global health, as well as worldwide development regimes, was seriously threatened by the COVID-19 pandemic and Delta variant outbreaks. In addition to pledging to adapt to and mitigate climate change, experts, economists, and policymakers expressed their determination to do so. Green growth and sustainable development have become the focus of policymakers and governments. The progress toward green economic efficiency (GEE), which will benefit the economy, society, and environment, continues. In terms of green growth and development, implementing environmental regulations and policies has been one of the most challenging aspects of the process. China, the world's second-largest economy, has begun its journey to GEE. Nonetheless, the green economy faces many challenges. The objective of the study is to use AHP analysis to analyze environmental regulation and GEE in China. Accordingly, the study identified three alternative approaches to achieve GEE by analyzing four criteria and ten sub-criteria in the context of environmental regulations in China. The analytical hierarchy process (AHP) has been used to rank criteria, sub-criteria, and alternative approaches. According to the model, China's best path to GEE is through resource efficiency and green purchasing strategies. This article offers an insightful assessment of sustainable development in the Chinese economy.

Efficiency Evaluation of Regional Environmental Management Systems in Russia Using Data Envelopment Analysis

The concept of eco-efficiency has recently become an issue of great importance due to the growing trend of environmental degradation, and many approaches based on Data Envelopment Analysis (DEA) are used in the literature to evaluate the environmental performance of economic systems. However, research to date has paid little attention to the possibility of extending the DEA approach to the problem of measuring the economic feasibility of eco-efficiency improvement. The main aim of this study is to evaluate the efficiency of investments focused on improving the eco-efficiency of the regional economy in Russia using the DEA approach. The various types of costs for environmental protection measures are considered as inputs and the annual decrease in specific environmental impacts of the regional economy are considered as outputs of DEA models. This is different from previous research, which generally focused on environmental efficiency only, omitting the integration of economic aspects in eco-efficiency measures. This study compares three different modifications of basic DEA models in the context of technical complexity and practical feasibility. The results show that the efficiency of regional environmental management in many Russian regions has a great potential for improvement. From a practical point of view, the Slack-Based Measure (SBM) model provides the most accurate results for policy applications. Unlike other ratings, the DEA-SBM model may stimulate an optimization of environmental protection spending and the introduction of technological and organizational eco-innovations.

Performance of Fuzzy Multi-Criteria Decision Analysis of Emergency System in COVID-19 Pandemic. An Extensive Narrative Review

The actual coronavirus disease 2019 (COVID-19) pandemic has led to the limit of emergency systems worldwide, leading to the collapse of health systems, police, first responders, as well as other areas. Various ways of dealing with this world crisis have been proposed from many aspects, with fuzzy multi-criteria decision analysis being a method that can be applied to a wide range of emergency systems and professional groups, aiming to confront several associated issues and challenges. The purpose of this critical review was to discuss the basic principles, present current applications during the first pandemic wave, and propose future implications of this methodology. For this purpose, both primary sources, such as scientific articles, and secondary ones, such as bibliographic indexes, web pages, and databases, were used. The main search engines were PubMed, SciELO, and Google Scholar. The method was a systematic literature review of the available literature regarding the performance of the fuzzy multi-criteria decision analysis of emergency systems in the COVID-19 pandemic. The results of this study highlight the importance of the fuzzy multi-criteria decision analysis method as a beneficial tool for healthcare workers and first responders’ emergency professionals to face this pandemic as well as to manage the created uncertainty and its related risks.