Study of reverse supply chain based on products’ life cycle

2015 ◽  
pp. 773-777
Author(s):  
L Zhu ◽  
P Qiao
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
Reverse Supply Chain

Environmental Criteria in a MCDM Context

2010 ◽  
pp. 74-92
Author(s):  
Ahmed Bufardi ◽  
Dimitris Kiritsis
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Life Cycle ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Reverse Supply Chain ◽  
Vacuum Cleaner ◽  
Environmental Criteria ◽  
Selection Of

This chapter addresses the main issues that are worth considering when using environmental criteria in a multiple criteria decision making (MCDM) context and provides some guidance for a proper and efficient use of environmental criteria in a MCDM context. Among the main issues considered in this chapter, we can mention the definition and representation of criteria, their weighting, and their selection. The relation of criterion to other notions such as attribute, objective, goal, and indicator is also explained. Regarding the environmental criteria, we emphasize their main characteristics and indicate how these characteristics can support the users in selecting appropriate MCDM methods. An illustrative example about the selection of the best scenario for the treatment of a vacuum cleaner at the end of its life cycle is given. It shows the type of reverse supply chain problems in which environmental criteria can be used to evaluate and compare alternatives.

Forecasting product returns for recycling in Indian electronics industry

2014 ◽  
Vol 11 (1) ◽  
pp. 102-114 ◽  
Author(s):  
Saurabh Agrawal ◽  
Rajesh K. Singh ◽  
Qasim Murtaza
Keyword(s):  
Supply Chain ◽  
Life Cycle ◽  
Product Life Cycle ◽  
Real Life ◽  
Supply Chain Design ◽  
Reverse Supply Chain ◽  
Product Returns ◽  
Supply Chain System ◽  
Product Life ◽  
Content Type

Purpose – The purpose of this paper is to develop a model for forecasting product returns to the company for recycling in terms of quantity and time. Design/methodology/approach – Graphical Evaluation and Review Technique (GERT) has been applied for developing the forecasting model for product returns. A case of Indian mobile manufacturing company is discussed for the validation of this model. Survey conducted by the company and findings from previous research were used for data collection on probabilities and product life cycle. Findings – Product returns for their recycling are stochastic, random and uncertain. Therefore, to address the uncertainty, randomness and stochastic nature of product returns, GERT is very useful tool for forecasting product returns. Practical implications – GERT provides the visual picture of the reverse supply chain system and helps in determining the expected time of product returns in a much easier way but it requires probabilities of different flows and product life cycle. Both factors vary over a period, so require data update time to time before implementation. Originality/value – This model is developed by considering all possible flows of sold products from customer to their reuse, store or recycle or landfill. First time this type of real life flows have been considered and GERT has been applied for forecasting product returns. This model can be utilized by managers for better forecasting that will help them for effective reverse supply chain design.

Identification of the Barriers of Reverse Supply Chain

2020 ◽  
Author(s):  
Sunil Sunil ◽  
Dharmanshu Kumar ◽  
Udit Mehta ◽  
Rakesh Kumar
Keyword(s):  
Supply Chain ◽  
Reverse Supply Chain

scholarly journals Life Cycle Blue and Grey Water in the Supply Chain of China’s Apparel Manufacturing

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1212
Author(s):  
Ao Liu ◽  
Aixi Han ◽  
Li Chai
Keyword(s):  
Water Pollution ◽  
Supply Chain ◽  
Life Cycle ◽  
Water Consumption ◽  
Agricultural Sector ◽  
Oxygen Demand ◽  
High Water ◽  
Grey Water ◽  
Apparel Manufacturing ◽  
Economic Output

Apparel manufacturing involves high water consumption and heavy water pollution in its supply chain, e.g., planting cotton, producing chemical fibers, and dyeing. This study employs a multi-regional input–output (MRIO) model to (1) assess the life cycle of blue and grey water (chemical oxygen demand (COD) specific) of China’s apparel manufacturing; (2) reveal the hidden linkage among sectors and regions in the whole supply chain; and (3) identify the key regions and upstream sectors with the most water consumption and heaviest water pollution. We found that the agricultural sector (i.e., planting fiber crops) is responsible for primary water consumption and water pollution. In addition, different provinces assume different production roles. Guangdong is a major output province in apparel manufacturing. However, its economic output is contributed to by other regions, such as blue water from Xinjiang and Jiangsu and grey water from Hebei and Shandong. Our research reveals the significance of taking an inter-regional perspective on water resource issues throughout the supply chain in apparel manufacturing. The sustainable development of China’s apparel manufacturing relies on improving water-use efficiency and reasonable industrial layout. The results are of significance and informative for policymakers to build a water-sustainable apparel industry.

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