Evaluation of Agricultural Green Development Based on Gini Coefficient and Hesitation Fuzzy Multi-Attribute Decision-Making: The Case of China

Abstract

In order to systematically solve the problem of formulating agricultural green development strategies based on the four dimensions of policy green, industry green, science and technology green, and awareness green, this paper uses the method of combining the Gini coefficient with hesitation fuzzy multi-attribute decision-making to carry out research. The research shows that: (1) The three most critical factors affecting the green development of agriculture are “consumers’ awareness of purchasing green agricultural products”, “investment in the construction of rural ecological civilization” and “the number of farmers’ scientific and technological training”, and the corresponding index weights are 0.12, 0.1 and 0.1, respectively. (2) There are differences in policy, industry, science and technology, and consciousness in the green development of agriculture. The green development of policy shows an obvious upward trend. The industrial green development shows a relatively gentle upward trend. The green development of science and technology showed rapid growth from 2011 to 2017, and the growth slowed down in the following two years and showed a downward trend in 2020. The awareness of green development shows a relatively stable upward trend. (3) The green development of agriculture is jointly driven by the relevant interests of the supply side, the demand side, and the regulator, and the demand side’s requirements for high-quality agricultural products become a stronger driving force for the green development of agriculture. The change in the consciousness and thinking of agricultural product producers on the supply side has become the basis for the green development of agriculture, and the implementation of government policies has become an important guarantee for the green development of agriculture. The innovation of this paper is to build an evaluation index system including government, consumers, farmers’ awareness of multiple subjects, government policies at all levels, industrial production status, and agricultural production technology. At the same time, we build an evaluation model that can comprehensively analyze quantitative and qualitative indicators. In view of the need for a holistic analysis of the agricultural system in the study of agricultural green development, future studies will include air pollution emissions and agricultural transport services in the evaluation model to improve the scientific and universal model.

Research on the Level of Agricultural Green Development, Regional Disparities, and Dynamic Distribution Evolution in China from the Perspective of Sustainable Development

“…They provided suggestions for optimizing paths and upgrading green agricultural production in China [66]. Wan et al (2023) measured the level of agricultural green development in China from four dimensions: policy greenness, industry greenness, technological greenness, and awareness greenness. They combined the Gini coefficient with the hesitant fuzzy multiattribute decision-making method to analyze the state of agricultural green development in China [16].…”

“…Wan et al (2023) measured the level of agricultural green development in China from four dimensions: policy greenness, industry greenness, technological greenness, and awareness greenness. They combined the Gini coefficient with the hesitant fuzzy multiattribute decision-making method to analyze the state of agricultural green development in China [16]. adopted a new perspective based on the symbiosis of agricultural ecosystems to construct an evaluation indicator system for agricultural green development, including green production, green innovation, green ecological protection, and green economy.…”

“…Currently, within the academic community, there are three main approaches to measuring and analyzing the level of agricultural green development: calculating green total factor productivity [8][9][10], estimating agricultural carbon emissions [11][12][13], and calculating the comprehensive indices of agricultural green development [14][15][16]. Existing research outcomes in this field are significant for exploring green development, offering valuable insights for the direction of this study.…”

“…Shaanxi(27), Shanxi (4) Henan(16), Inner Mongolia (5)Yangtze River Basin Comprehensive Economic Region (YRBCE)Hubei(17), Hunan(18), Jiangxi (14), Anhui(12) Great Southwest Comprehensive Economic Region (GSCER) Yunnan (25), Guizhou(24), Sichuan(23), Chongqing (22) Guangxi (20)Great Northwest Comprehensive Economic Region (GNCER) Gansu(28), Qinghai (29), Ningxia(30), Tibet(26), Xinjiang(31) …”

Impact Effects of Cooperative Participation on the Adoption Behavior of Green Production Technologies by Cotton Farmers and the Driving Mechanisms

“…Green development is an inevitable requirement for the construction of ecological civilization [67], and it should not be overlooked that agricultural pollution has become one of the most serious environmental pollution problems in China [35], and green development in agriculture is imminent. In China, farmers are the front-line main body of agricultural production, as well as the direct adopters and beneficiaries of agricultural green production methods [37].…”