图书简介
This book provides decision and theory development models for sustainable procurement supply chain operations. It will assist organizations in making their supply chain more efficient, by covering all three major analytics: descriptive, predictive, and perspectives in the context of sustainable procurement supply chain operations.
1. Conceptual Framework in Sustainable Procurement: Sustainable Development Goals (SDGs) Focused Content Analysis Approach. 2. The Internet of Things-Enabled SMART Procurement: The Next Horizon. 3. Framework for Measuring the Procurement Performance in the Dairy Supply Chain. 4. Modeling the Sustainable Procurement Initiatives Using Fuzzy-Based MCDM Framework. 5. Green Procurement Research: A Review and Modeling Supplier Selection Problem Using GREY Method 6. New Model for Sustainable Supplier Selection Using Fuzzy DEMATEL. 7. Supplier Selection for Protective Relays of Power Transmission Network with the Fuzzy Approach. 8. Multiple Objective Decision-Making Methods in Supplier Selection. 9. Assessing the Drivers to Gain Sustainable Competitive Advantage: An Interpretive Structural Modeling Approach. 10. Analyzing the Drivers of Sustainable Procurement Using the DEMATEL Approach. 11. Barriers on Sustainable Supply Chain Management Implementation for Turkish SME Suppliers: A Fuzzy Analytic Hierarchy Process Approach. 12. Integrating Sustainability into Humanitarian Procurement: A Prioritization of Barriers and Enablers. 13. Text Mining Applied to Literature on Sustainable Supply Chain (1996-2018): An Analysis Based on Scopus. 14. Multi-criteria Decision-Making Techniques to Address Sustainable Procurement in Supply Chain Operations. 15. The Investigation of Sustainable Procurement System Satisfying Turkey’s Energy Demand by Means of Multi-period Interval Parameter Integer Liner Programming (MP-IPILP). 16. A Mixed-Integer Sustainable Public Transportation Model of Procurement Purposes Surrounding a Construction Site 17. A Sustainable Inventory Optimization Problem under Process Flexibility 18. Sustainability of Advance Machine Learning Algorithms in Manufacturing.
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