An improved evaluation framework for industrial green development: Considering the underlying conditions

Wei, Li; Yang, Xi; Liu, Shi Qiang; Li, Meijuan; Chen, Lei; Wu, Xueping; Zhu, Song‐Ping; Masoud, Mahmoud

doi:10.1016/j.ecolind.2019.106044

Cited by 31 publications

(22 citation statements)

References 68 publications

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“…The community of human and natural life is at the core of green development [ 1 , 2 ]. The green development of industrial enterprises, a major concern of industrial ecology and environmental economics researchers, regards industrial enterprises as the main body, e.g., the effect of the market mechanism on the green development of industrial enterprises [ 3 ], the effect of industrial agglomeration on green development efficiency [ 4 ], the influencing mechanism of technology R&D on green development in China’s industrial sector [ 5 ] and the evaluation framework of industrial green development [ 6 , 7 ]. The production activities of industrial enterprises belong to the production subsystem of the green development system, which are not only affected by the policy subsystem, but also provide necessary products and services for the living subsystem.…”

Section: Introductionmentioning

confidence: 99%

Mechanism for Green Development Behavior and Performance of Industrial Enterprises (GDBP-IE) Using Partial Least Squares Structural Equation Modeling (PLS-SEM)

Long

2020

IJERPH

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Although the theory of green development behavior and performance of industrial enterprises (GDBP-IE) reveals that the green development behavior (GDB) of industrial enterprises is affected by internal and external factors and produces performance, it lacks a clear mechanism. This paper aims to verify the theory of GDBP-IE and reveals the mechanism of GDBP-IE in the Chinese context. The partial least squares structural equation modeling (PLS-SEM) method was used to analyze valid samples of Chinese industrial enterprises (N = 615). The empirical conclusions are as follows. (1) Corporate tangible resources, corporate intangible resources (CIR), market environment, public supervision and policy and institutional environment (PIE) have a significant positive effect on GDB (i.e., green supply chain management practice and clean production behavior). (2) Compared with other factors, the positive effect of CIR on GDB is the strongest. (3) The level of positive effect of PIE on GDB is not as significant as other factors. (4) GDB has a significant positive effect on green development performance (i.e., corporate social performance, corporate financial performance and corporate environmental performance). This paper provides effective evidence for researchers to use other methods to further verify the theory of GDBP-IE in the Chinese context. This paper also provides an opportunity for cluster analysis of GDBP-IE in different countries or regions. In addition, this paper not only gives a targeted reference for the government to formulate guidelines concerning the green development of industrial enterprises but also encourages industrial enterprise managers to formulate green development strategies, which is a way to help industrial enterprise managers and workers to participate in and comply with GDB.

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Section: Introductionmentioning

confidence: 99%

Mechanism for Green Development Behavior and Performance of Industrial Enterprises (GDBP-IE) Using Partial Least Squares Structural Equation Modeling (PLS-SEM)

Long

2020

IJERPH

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“…Regarding green assessment methods, scholars have adopted various methods. Some typical evaluation methods such as entropy weight method, TOPSIS (technique for order preference by similarity to ideal solution) [31], LCA (life cycle assessment), principal component analysis, material flows analysis [32] and input-output analysis [20] have been widely used in environmental economic studies to build evaluation models [33][34][35][36][37]. This study adopted the overall entropy method, which is more comprehensive than the traditional entropy weight method, that was used to introduce longitudinal comparisons of time and category [38].…”

Section: Introductionmentioning

confidence: 99%

Green Assessment of Imports and Exports of Wooden Forest Products Based on Forest Processing Industry: A Case Study of China

Tian

Vũ

et al. 2021

Forests

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The research on international trade competitiveness is progressing continuously. Environmental factors have been gradually considered in the competitiveness of international trade. However, the green assessment system of international trade competitiveness is not perfect. Building a model based on the trade economy is complex. This study combines environmental pollution data based on the forest processing industry with trade flows. Environmental trade competitiveness, pollution treatment, and trade scale were selected as the three criterion levels to construct an assessment system. The weight and score of each index were calculated by the overall entropy method. The overall entropy method is more comprehensive than the traditional entropy weight method due to introduce longitudinal comparisons of time and category. This method is a dynamic evaluation model with analysis of three-dimensional sequential data tables. The use of this method enables the assessment model to analyze more comprehensively the green level of a country’s trade in wooden forest products in terms of time and product category. The green level of chemical wood pulp and sawn timber trade in China is at a high level. The pollution treatment and trade scale of chemical wood pulp and sawn timber attained a medium level of matching. The trades in particle board, hardboard, newsprint, carton board, and wrapping paper are at medium levels of green. The trades in medium density fiberboard and plywood have poor levels of green and need to improve their green production capacity. It is suggested that China should increase investment in scientific research, as well as establish policies to restrict and treat pollution in the industry of wooden forest products, while increasing the export volumes of products with high added value. China should attach importance to the pollution resulting from the manufacture of wooden forest products. The state should support policies for these producers reducing production emissions.

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“…At the same time, the original growth model in China, characterized by quantity, scale, and speed, has failed to meet the requirements of the new norm of economic development [7]. Green development is an important opportunity for the development of new industries such as energy conservation and environmental protection [8]. Therefore, the key to solving this problem is to promote green manufacturing based on the deep integration of manufacturing industry and information technology.…”

Section: Introductionmentioning

confidence: 99%

“…Many scholars have studied the aspects related to industry, university, and research institutions [ 8 , 13 ]. However, there are fewer studies on the green technology innovation process of enterprises under multi-agent cooperation [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ].…”

Section: Introductionmentioning

confidence: 99%

Improving the Effectiveness of Multi-Agent Cooperation for Green Manufacturing in China: A Theoretical Framework to Measure the Performance of Green Technology Innovation

Yin

Zhang

2020

IJERPH

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A green manufacturing system is an important tool to realize green transformation of the manufacturing industry. The systematicness of green technology innovation as the key foundation of green manufacturing supports the entire huge green manufacturing system. In order to improve the effectiveness of multi-agent cooperation, it is necessary to analyze a series of green technology innovation achievements of manufacturing enterprises under multi-agent cooperation. First of all, inter-indicator correlation analysis and exploratory factor analysis were used to construct the evaluation index system of the green technology innovation performance of manufacturing enterprises under multi-agent cooperation. Then, a secondary combined evaluation model was constructed based on the evaluation conclusions. Finally, a theoretical framework was constructed to measure the performance of the green technology innovation of manufacturing enterprises under multi-agent cooperation. The results of this study are as follows: The evaluation index system of the green technology innovation performance of manufacturing enterprises under multi-agent cooperation is composed of the technology output, economic output, and social effect of green technology innovation. The key factors that influence the green technology innovation performance of manufacturing enterprises under multi-agent cooperation are the proportion of green technology transformation in traditional technology, the number of papers published jointly by multi-agent cooperation, the user acceptance of green technology products, and the degree of improvement of public environmental preference and consciousness. A fusion of technology of subjective and objective methods is an effective evaluation technique and can be applied to evaluate the performance of green technology innovation. The secondary combined evaluation combines the evaluation conclusions obtained by each single evaluation method in a certain form.

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An improved evaluation framework for industrial green development: Considering the underlying conditions

Cited by 31 publications

References 68 publications

Mechanism for Green Development Behavior and Performance of Industrial Enterprises (GDBP-IE) Using Partial Least Squares Structural Equation Modeling (PLS-SEM)

Mechanism for Green Development Behavior and Performance of Industrial Enterprises (GDBP-IE) Using Partial Least Squares Structural Equation Modeling (PLS-SEM)

Green Assessment of Imports and Exports of Wooden Forest Products Based on Forest Processing Industry: A Case Study of China

Improving the Effectiveness of Multi-Agent Cooperation for Green Manufacturing in China: A Theoretical Framework to Measure the Performance of Green Technology Innovation

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