Description

Book Synopsis

Sustainable Procurement is an emerging concept in supply chain and operations management. Manufacturing industries have made improvements in moving from cost-based to quality-based, and customer-focused supply chain management strategies. This is becoming an integrated component in the supply chain system, with players becoming aware of the regulations and needs of the customer. It is imperative for production firms to look at the procurement activity as one of the strategic enablers for sustaining the business in the competitive global environment. This book will provide industries with an understanding of the concepts related to sustainable procurement policies and its implementation.

  • Provides decision and theory development models in sustainable procurement supply chains
  • Includes contributions in all three major analytics: descriptive, predictive, and perspectives in the context of sustainable procurement supply chain
  • Discusses new business models wi

    Table of Contents

    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.

Sustainable Procurement in Supply Chain

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    £137.75

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    Order before 4pm tomorrow for delivery by Mon 29 Jun 2026.

    A Hardback by Sachin K. Mangla, Sunil Luthra, Suresh Kumar Jakhar

    15 in stock


      View other formats and editions of Sustainable Procurement in Supply Chain by Sachin K. Mangla

      Publisher: Taylor & Francis Ltd
      Publication Date: 1/14/2019 12:06:00 AM
      ISBN13: 9781138608153, 978-1138608153
      ISBN10: 1138608157
      Also in:
      Engineering: general

      Description

      Book Synopsis

      Sustainable Procurement is an emerging concept in supply chain and operations management. Manufacturing industries have made improvements in moving from cost-based to quality-based, and customer-focused supply chain management strategies. This is becoming an integrated component in the supply chain system, with players becoming aware of the regulations and needs of the customer. It is imperative for production firms to look at the procurement activity as one of the strategic enablers for sustaining the business in the competitive global environment. This book will provide industries with an understanding of the concepts related to sustainable procurement policies and its implementation.

      • Provides decision and theory development models in sustainable procurement supply chains
      • Includes contributions in all three major analytics: descriptive, predictive, and perspectives in the context of sustainable procurement supply chain
      • Discusses new business models wi

        Table of Contents

        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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