Pundir, Ashok Kumar, Ganapathy, L., Maheshwari, Pratik, and Kumar, M Neeraj
2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2020 11th IEEE Annual. :0201-0207 Nov, 2020
Pundir, Ashok Kumar, Ganapathy, L., Maheshwari, Pratik, and Thakur, Shashikant
2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2020 11th IEEE Annual. :0223-0229 Nov, 2020
Kumar, Ramesh, Ganapathy, L., Gokhale, Ravindra, and Tiwari, Manoj Kumar
International Journal of Production Research. Jun2020, Vol. 58 Issue 11, p3527-3553. 27p. 5 Diagrams, 12 Charts, 1 Graph.
Subjects
Distribution planning, Production planning, Supply chains, Literature reviews, and Web databases
Abstract
Production and distribution are the two primary internal elements of the supply chain. This paper presents a systematic literature review (SLR) of quantitative approaches for the integration of production and distribution planning (IPDP) in the supply chain. We provide a classification framework with eight dimensions and give a brief overview of the quantitative approaches such as modelling approaches and solution approaches for the IPDP problem in the supply chain. The SLR has been carried out using two basic search databases Scopus and Web of Science. In all, we identify relevant articles in the period from 2000 to 2019. We also highlight certain research opportunities, suggestions, and research gaps for possible future research by assessing the current knowledge on the quantitative approaches for IPDP problems in the supply chain. [ABSTRACT FROM AUTHOR]
Technological Forecasting and Social Change, 2021, 165, C.
Subjects
Large group decision making, Big Data, Circular economy, Automobile industry, PROMETHEE, and Sustainability
Abstract
The present study uses a large group decision-making technique to identify and rank the best big data-driven circular economy (BDDCE) practices in the auto-component industry. The data pertaining to the BDDCE practices were collected from the decision-makers in three groups, namely, purchasing, manufacturing, and logistics & marketing function from the auto-component manufacturing industry. First, the consensus on the BDDCE practices within the group was ascertained followed by determining the decision weights using the percentage distributions and subjective weights. This was followed by the by computing the dominance degrees on pairwise comparisons of the BDDCE practices and ranking them using the PROMETHEE II method. The findings indicated that the BDDCE practices that were more inclined towards the enhancement of internal supply chain integration were most preferred and highly ranked by the decisionmakers in the auto-component industry as compared to the practices that were focused on improving the supplier and customer interfaces such as green purchasing, sale of excess inventory, and developing recycling systems for end-of-life products and materials . The high ranked BDDCE practices included minimization of the raw material consumption, plan for reuse, recycle, recovery of material, parts, and reduction of the process waste at the design stage.
