Supply Chain Performance Measurement in Textile Enterprises

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A01=Pranav C. Charkha
A01=Prasenjit Chatterjee
A01=Santosh B. Jaju
analytical hierarchy process
Author_Pranav C. Charkha
Author_Prasenjit Chatterjee
Author_Santosh B. Jaju
Category=KJMV5
Category=KJMV8
Category=KNDD
Delphi method
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Manufacturing Industries
multi-criteria decision making
performance measurement framework for textiles
production and distribution analysis
supply chain evaluation criteria
Supply Chain Management
textile industry operations
Textile Manufacturing

Product details

  • ISBN 9781774913864
  • Weight: 520g
  • Dimensions: 152 x 229mm
  • Publication Date: 28 Jun 2024
  • Publisher: Apple Academic Press Inc.
  • Publication City/Country: CA
  • Product Form: Hardback
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This new volume provides detailed insight into supply chain management (SCM) and supply chain performance measurement (SCPM) in the textile industry. The book provides a comprehensive set of performance sub-criteria for the evaluation of SCPM, offering the information needed to understand, implement, and evaluate the supply chain performance of the textile industry and its cyclic processes.

Using the Delphi method (a process used to arrive at a group opinion or decision by surveying a panel of experts), the authors studied several companies of diverse sizes and applied an analytical hierarchy process to establish crucial performance measurement criteria and sub-criteria. Around 80 textile industry personnel were contacted, including general managers, factory managers, managers, assistant managers, executives, and supervisors involved in various functions related to textile supply chains to discuss procurement, production, and distribution alternatives. The authors employed the multi-criteria decision-making technique, i.e. analytical hierarchy process, for executing pair-wise comparison and establishing priority weights of criteria, sub-criteria, and for estimating the contribution of supply chain cyclic processes to overall supply chain performance.

Pranav C. Charkha, PhD, is Head and Dean of Academics at Pimpri Chichwwad Education Trust’s Nutan Maharashtra Institute of Engineering and Technology, Maharashtra, India. He is also associated with the Indian Society of Technical Education, Institutions of Engineers, and Indian Institution of Industrial Engineering. He has published research papers in international journals and presented papers at international conferences. He is a coordinator for the Center of Excellence (Maharashtra Region) of Visionary Learning Community of India for creating Visionary Leaders for Manufacturing (an initiative of CII and the Japanese International Cooperation Agency).

Santosh B. Jaju, PhD, is Professor in the Department of Mechanical Engineering of G. H. Raisoni College of Engineering, Maharashtra, India. With over 22 years of teaching experience, he has published over 100 research papers in national and international journals and conferences as well as one book and several book chapters. He is a certified lead auditor of ISO 9001: 2008 Quality Management System by IRCA UK. He has filed six patents and completed research projects of the All India Council for Technical Education.

Prasenjit Chatterjee, PhD, is Professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKV Institute of Engineering, West Bengal, India. He has published over 120 research papers in international journals and peer-reviewed conferences and has authored and edited more than 25 books on intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modeling. Dr. Chatterjee is the Editor-in- Chief of the Journal of Decision Analytics and Intelligent Computing and an editor for several book series. He is one of the developers of two multiple-criteria decision-making methods, called Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).

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