Low-Carbon Supply Chain Management: A Fuzzy-DEMATEL Analysis of Some Practical Issues of Indian Manufacturing Industries

2020 ◽  
pp. 33-42
Author(s):  
Vivek Gupta ◽  
Arvind Jayant
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Manufacturing Industries ◽  
Low Carbon ◽  
Fuzzy Dematel ◽  
Chain Management ◽  
Carbon Supply

Measuring Low Carbon Supply Chain

2019 ◽  
pp. 1105-1116
Author(s):  
Muhammad Shabir Shaharudin ◽  
Yudi Fernando
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Greenhouse Gas Emission ◽  
Review Literature ◽  
Extended Model ◽  
Low Carbon ◽  
Chain Management ◽  
Carbon Supply ◽  
Or Practice ◽  
Reduce Carbon Emission

The threat of climate change is due to increasing carbon emissions of manufacturing production and transportation. Currently, government is encouraging manufacturing to reduce carbon emission and conduct low carbon supply chain management (LCSCM). In order to solve the greenhouse gas emission dilemma, LCSCM is essential for manufacturing firms' stakeholders. Supply chain partners are expected to know the proper measurement of emissions to solve this problem. This chapter's aim is to review literature on how to measure LCSCM. In the past, the concept of green supply chain management (GSCM) was practiced to promote and reduce environmental risks. However, GSCM is a driver or practice to achieve environmental outcomes. The extended model of GSCM currently practices LCSCM through carbon footprint (CF) concept. In other words, LCSCM is an outcome that both interests researchers and persuades practitioners.

Measuring Low Carbon Supply Chain

2018 ◽  
pp. 5446-5455
Author(s):  
Muhammad Shabir Shaharudin ◽  
Yudi Fernando
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Greenhouse Gas Emission ◽  
Review Literature ◽  
Extended Model ◽  
Low Carbon ◽  
Chain Management ◽  
Carbon Supply ◽  
Or Practice ◽  
Reduce Carbon Emission

The threat of climate change is due to increasing carbon emissions of manufacturing production and transportation. Currently, Government is encouraging manufacturing to reduce carbon emission and conducting Low Carbon Supply Chain Management (LCSCM). In order to solve greenhouse gas emission dilemma, LCSCM is essential for manufacturing firm's stakeholders. Supply chain partners are expected to know the proper measurement of emissions to solve this problem. This study aim is to review literature on how to measure LCSCM. In the past, the concept of Green Supply Chain Management (GSCM) is practiced to promote and reduce environmental risks. However, GSCM is a driver or practice to achieve environmental outcome. The extended model of GSCM has currently practices in LCSCM through Carbon Footprint (CF) concept. In other word, LCSCM is an outcome that both researcher interests and practitioner persuades.

scholarly journals A Fuzzy-Grey Multicriteria Decision Making Approach for Green Supplier Selection in Low-Carbon Supply Chain

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Qinghua Pang ◽  
Tiantian Yang ◽  
Mingzhen Li ◽  
Yi Shen
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Supplier Selection ◽  
Multicriteria Decision Making ◽  
Low Carbon ◽  
Chain Management ◽  
Multicriteria Decision ◽  
Green Supplier Selection ◽  
Carbon Supply

Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach.

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.

Low carbon supply chain: a state-of-the-art literature review

2018 ◽  
Vol 29 (2) ◽  
pp. 398-428 ◽  
Author(s):  
Chiranjit Das ◽  
Sanjay Jharkharia
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
English Language ◽  
Relevant Literature ◽  
Low Carbon ◽  
Chain Management ◽  
Content Type ◽  
Location Selection ◽  
Carbon Supply

Purpose The purpose of this paper is to review the relevant literature on low carbon supply chain management (LCSCM) and classify it on contextual base. It also aims at identifying key decision-making issues in LCSCM. This paper also highlights some of the future challenges and scope of research in this domain. Design/methodology/approach A content analysis is carried out by systematically collecting the literature from major academic sources over a period of 18 years (2000-2017), identifying structural dimensions and classifying it on contextual base. Findings There is an increasing trend of research on LCSCM, but this research is still in a nascent stage. All supply chain functions such as supplier selection, inventory planning, network design and logistic decisions have been redefined by integrating emissions-related issues. Research limitations/implications Limitation of this study is inherent in its unit of analysis. Only peer-reviewed journal articles published in English language have been considered in this study. Practical implications Findings of prior studies on low carbon inventory control, transportation planning, facility allocation, location selection and supply chain coordination have been highlighted in this study. This will help supply chain practitioners in decision making. Originality/value Though there are an increasing number of studies about carbon emission-related issues in supply chain management, the present literature lacks to provide a review of the overarching publications. This paper addresses this gap by providing a comprehensive review of literature on emissions-related issues in supply chain management.

scholarly journals Low-Carbon Supply Chain Management Considering Free Emission Allowance and Abatement Cost Sharing

2018 ◽  
Vol 10 (7) ◽  
pp. 2110 ◽  
Author(s):  
Peng Wu ◽  
Yixi Yin ◽  
Shiying Li ◽  
Yulong Huang
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Cost Sharing ◽  
Abatement Cost ◽  
Low Carbon ◽  
Chain Management ◽  
Emission Allowance ◽  
Carbon Supply
Sign in / Sign up

Export Citation Format

Share Document