Green Supplier Evaluation and Selection: Models, Methods and Applications

1. Auflage 2021
ISBN: 978-981-16-0381-5
Verlag: Springer Nature Singapore

Buch, Englisch, 366 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 752 g

This book offers an introduction to various models and methods for green supplier evaluation and selection (GSES) within different information settings. As such, it provides valuable knowledge, useful GSES methods and practical examples that can be considered by manufacturers in selecting appropriate green suppliers to improve their environmental performance and customer satisfaction. This book is useful for practitioners and researchers working in the fields of supply chain management, operation management, information science, industrial engineering, and management science. It is also useful as a textbook for postgraduate and senior undergraduate students.

Zielgruppe

Research

Autoren/Hrsg.

You, Xiao-Yue

Liu, Hu-Chen

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Betriebliches Energie- und Umweltmanagement
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Einkauf, Logistik, Supply-Chain-Management
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik

Inhaltsverzeichnis

Green Supply Chain Management.- Green Supplier Evaluation and Selection: Literature Review.- GSES based on Intuitionistic Fuzzy VIKOR Method.- GSES based on Picture Fuzzy VIKOR Method.- GSES using Interval 2-tuple Linguistic Distance Operators.- GSES with Interval-valued Intuitionistic Uncertain Linguistic AQM.- GSES with Interval-valued Intuitionistic Uncertain Linguistic GRA-TOPSIS.- GSES with Large Group Uncertain Linguistic MULTIMOORA Method.- GSES using Double Hierarchy Hesitant Linguistic Sets and Decision Field Theory.- GSES using Linguistic Z-numbers and AQM.

Über Autor(innen)

Hu-Chen Liu received his M.Sc. degree in Industrial Engineering from Tongji University, Shanghai, China, in 2010, and his Ph.D. degree in Industrial Engineering and Management from Tokyo Institute of Technology, Tokyo, Japan, in 2013. He is currently a professor at the School of Economics and Management, Tongji University. His main research interests include quality and reliability management, Petri net theory and application, and green supply chain management. He has published more than 100 publications including 3 books and 90+ journal papers. Majority of them are published in leading journals of related areas, such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, IEEE Transactions on Reliability, International Journal of Production Economics, International Journal of Production Research, and Annals of Operations Research.  

Dr. Liu is Associate Academician of the International Academy for Quality and is a senior member of the IEEE Systems, Man, and Cybernetics Society, the IEEE Reliability Society, the INFORMS, the Institute of Industrial & Systems Engineers (IISE), and the China Association for Quality.

Xiao-Yue You received her Ph.D. degree in Business Administration from Tongji University, Shanghai, China, in 2019. She was also a joint Ph.D. student in International Manufacturing, Institute for Manufacturing at the University of Cambridge from 2017 to 2019. She is now an assistant professor at the Sino-German College of Applied Sciences (CDHAW in German), Tongji University. Her current research interests include strategy management, green supply management, and lean management. She has published more than 30 journal papers in leading journals of related areas, such as IEEE Transactions on Cybernetics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, International Journal of Production Research, Computers& Industrial Engineering, and Reliability Engineering and System Safety.