Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management

2013 ◽  
Vol 56 ◽  
pp. 164-172 ◽  
Author(s):  
Chia-Wei Hsu ◽  
Tsai-Chi Kuo ◽  
Sheng-Hung Chen ◽  
Allen H. Hu
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supplier Selection ◽  
Green Supply Chain Management ◽  
Management Model ◽  
Green Supply Chain ◽  
Chain Management ◽  
Carbon Management

Green Supply Chain Management Model for Sustainable Manufacturing Practices

2017 ◽  
pp. 153-189 ◽  
Author(s):  
Surajit Bag ◽  
Neeraj Anand ◽  
Krishan Kumar Pandey
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Manufacturing Sector ◽  
Sustainable Manufacturing ◽  
Green Supply Chain Management ◽  
Management Model ◽  
Green Supply Chain ◽  
Interpretive Structural Modeling ◽  
Chain Management ◽  
The Relationship

The purpose of this chapter is to identify the dimensions of green supply chain and their impact on manufacturing practices. In this study, the authors used two extended strategies. First thorough review of literature was done considering articles from reputed journals. Second the factors identified from literature review was further refined through experts by forming a problem solving group consisting of seven experts from the manufacturing sector. These factors were used to develop the green supply chain management model using Interpretive structural modeling. Further MICMAC analysis was used to identify the driving and dependence power of the factors. The results of the analysis are very encouraging. Finally, the authors have presented the relationship management strategy for sustainable manufacturing practices.

Construction and Optimization of Green Supply Chain Management Mode of Agricultural Enterprises in the Digital Economy

2022 ◽  
Vol 15 (2) ◽  
pp. 1-18
Author(s):  
Jiang Hu ◽  
Xuetao Li
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Management Practice ◽  
Digital Economy ◽  
Coordination Mechanism ◽  
Green Supply Chain Management ◽  
Management Model ◽  
Green Supply Chain ◽  
Chain Management ◽  
Agricultural Enterprises

Digital economy is a rapidly developing economic form under the background of the information age. This article introduces the construction and optimization of the green supply chain management model of agricultural enterprises under the digital economy, and intends to provide some ideas and directions for the development of green supply chain management of agricultural enterprises based on digital economy. This paper proposes the construction and optimization research methods of the green supply chain management model of agricultural enterprises under the digital economy, including the overview of green supply chain management, the construction of the optimization management model of the green supply chain of agricultural enterprises, and the digital economy under the construction of a green supply chain management practice index system for agricultural enterprises. Experimental results show that average Cronbachα value of each scale factor of the optimized management model in this paper is 0.876, and optimized decision-making coordination mechanism has high internal consistency.

Study on Green Supply Chain Management Model of Chinese Home Appliances Enterprises

2014 ◽  
Vol 945-949 ◽  
pp. 3163-3166
Author(s):  
Wei Liu ◽  
Jing Xin Chen
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Environmental Protection ◽  
Developed Countries ◽  
Green Supply Chain Management ◽  
Management Model ◽  
Green Supply Chain ◽  
Chain Management ◽  
Organic Unity ◽  
Home Appliances

With the global environment worsening, environmental regulations and green barriers of developed countries are more and more powerful, consumers are increasingly concerned about environmental protection products. Chinese home appliances manufacturers are suffered great environmental pressure. Green supply chain management is a new management model. It is able to improve balance of the organic unity between economic efficiency and environmental protection, resource utilization and ecological. The environment is put into the entire supply chain to consider. In this paper, we analyzed the necessity and urgency of implementing green supply chain management, and built green supply chain management mode of Chinese home appliances manufacturers.

Novel q-rung orthopair fuzzy interaction aggregation operators and their application to low-carbon green supply chain management

2021 ◽  
pp. 1-18
Author(s):  
Muhammad Riaz ◽  
Harish Garg ◽  
Hafiz Muhammad Athar Farid ◽  
Muhammad Aslam
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supplier Selection ◽  
Weighted Averaging ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Environmental Concerns ◽  
Low Carbon ◽  
Chain Management ◽  
Carbon Supply

The low-carbon supply chain management is big a challenge for the researchers due to the rapid increase in global warming and environmental concerns. With the advancement of the environmental concerns and social economy, it is an unavoidable choice for a business to achieve sustainable growth for low-carbon supply chain management. Since the root of the chain depends upon the supplier selection and choosing an excellent low-carbon supply. Green supplier selection is one of the most crucial activities in low-carbon supply chain management, it is critical to develop rigorous requirements and a system for selection in low-carbon green supply chain management (LCGSCM). A q-rung orthopair fuzzy number (q-ROFN) is pair of membership degree (MD) and non-membership degrees (NMD) which is reliable to address uncertainties in the various real-life problems. This article sets out a decision analysis approach for interactions between MDs and NMDs with the help of q-ROFNs. For this objective, we develop new aggregation operators (AOs) named as, q-rung orthopair fuzzy interaction weighted averaging (q-ROFIWA) operator, q-rung orthopair fuzzy interaction ordered weighted averaging (q-ROFIOWA) operator, q-rung orthopair fuzzy interaction hybrid averaging (q-ROFIHA) operator, q-rung orthopair fuzzy interaction weighted geometric (q-ROFIWG) operator, q-rung orthopair fuzzy interaction ordered weighted geometric (q-ROFIOWG) operator and q-rung orthopair fuzzy interaction hybrid geometric (q-ROFIHG) operator. These AOs define an advanced approach for information fusion and modeling uncertainties in multi-criteria decision-making (MCDM). At the end, a robust MCDM approach based on newly developed AOs is developed. Some significant properties of these AOS are analyzed and the efficiency of the developed approach is assessed with a practical application towards sustainable low-carbon green supply chain management.

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