The objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.
Author(s): Niamat Ullah Ibne Hossain
Series: Greening of Industry Networks Studies, 11
Publisher: Springer
Year: 2023
Language: English
Pages: 263
City: Cham
Contents
Chapter 1: Data Analytics Applications in Supply Chain Resilience and Sustainability Management: The State of the Art and a Wa...
1.1 Introduction
1.2 Publication Trends
1.3 Most Impactful Studies
1.4 Underlying Themes in Data Analytics in Supply Chain in Resilience and Sustainability
1.5 Trending Topics and Future Research
1.6 Conclusion
References
Chapter 2: Enhancing the Viability of Green Supply Chain Management Initiatives Leveraging Data Fusion Technique
2.1 Introduction
2.2 Review of Literature
2.2.1 Barriers and Factors for GSCM Initiative Implementation
2.2.2 Computational Approach for Assessment Methodology
2.3 Evaluation Approach
2.3.1 Analytical Hierarchical Process (AHP)
2.3.2 Dempster-Shafer Theory
2.3.2.1 Frame of Discernment and Basic Probability Assignment
2.3.2.2 DS Rule of Combination
2.3.3 Yager´s Recursive Rule
2.4 Methodology
2.5 GSCM Initiatives´ Model Formulation
2.5.1 Structuring the Hierarchy for Viability Index Assessment
2.5.2 Factor´s Weights and Assessment Grades with Utility
2.6 Analytical Illustration Through a Case Study
2.6.1 Data Collection
2.6.2 Combining the Assessments Using DST
2.6.2.1 Interpreting the Evaluation of Viability Index for GSCM Initiatives Using DST
Assessing the Evaluation Grades for Internal Factors Using DST
Overall Assessment for GSCM Initiative Factors Using DST
2.6.2.2 Interpretive Evaluation of Viability Index for GSCM Initiative Using Yager´s Rule
Assessment of the Internal Factors Using Yager´s Rule
Overall Assessment for GSCM Initiative Factors Using Yager´s Rule
2.6.2.3 Utility Perspective Overall Assessment of Viability Index for GSCM Initiatives
Utility-Based Calculation of the Viability Index
2.6.2.4 Overall Result Interpretation and Comparative Study Between DST and Yager´s Rule
2.7 Sensitivity Analysis
2.8 Discussion
2.8.1 Significant Implications for Managerial Decision-Making
2.9 Conclusion
Appendix: Assessing the Evaluation Grades for External Factors Using DST
References
Chapter 3: Supply Chain Sustainability and Supply Chain Resilience: A Performance Measurement Framework with Empirical Validat...
3.1 Introduction
3.1.1 Supply Chain Sustainability Performance Measurement
3.1.2 Supply Chain Resilience Performance Measurement
3.1.3 Supply Chain Sustainability and Resilience Performance Measurement
3.1.4 Research Gaps
3.2 Developing a New, Integrated Framework for Sustainability and Resilience Performance Measurement
3.2.1 Full Framework
3.2.2 Core Framework
3.2.3 Final Remarks
3.3 Framework Testing: Case Studies
3.3.1 Methodology
3.3.1.1 Sample Selection
3.3.1.2 Data Collection and Analysis
3.4 Results
3.4.1 Supply Chain A
3.4.1.1 General Information
3.4.1.2 Approach to Sustainability and Resilience
3.4.1.3 Framework Validation
3.4.2 Supply Chain B
3.4.2.1 General Information
3.4.2.2 Approach to Sustainability and Resilience
3.4.2.3 Framework Validation
3.4.3 Supply Chain C
3.4.3.1 General Information
3.4.3.2 Approach to Sustainability and Resilience
3.4.3.3 Framework Validation
3.5 Discussion
3.6 Conclusions and Further Research
Appendix: Core Framework
References
Chapter 4: An Assessment of Decision-Making in Resilient and Sustainable Projects Between Literature and Practice
4.1 Introduction
4.2 Literature Review
4.3 Methodology
4.3.1 Theory of Intuitionistic Fuzzy Set (IFS)
4.3.2 DEMATEL Method
4.3.3 Intuitionistic Fuzzy DEMATEL (IF-DEMATEL)
4.4 Results and Analysis
4.4.1 Cause Group
4.4.2 Effect Group
4.4.3 Prominence Vector
4.4.4 Correlations Between the Challenges
4.5 Conclusion
Appendix A
References
Chapter 5: Barriers for Sustainable Supply Chain Management and Their Overcoming Strategies in Context of the Indian Automobil...
5.1 Introduction
5.2 Literature Review
5.2.1 Sustainability and Supply Chain Management
5.2.2 Indian Automobile Industry and Sustainable Supply Chain Management
5.3 Research Methodology
5.3.1 Application of Fuzzy TOPSIS
5.4 Results and Discussion
5.5 Implications of the Study
5.5.1 Theoretical Implications
5.5.2 Managerial Implications
5.6 Conclusions
Appendixes
Appendix A: Data from Ten Experts for Fuzzy TOPSIS
Appendix B
Appendix C
Appendix D
Appendix E
Appendix F
References
Chapter 6: Prioritizing Sustainability Criteria of Green Supply Chains Using the Best-Worst Method
6.1 Introduction
6.2 Literature Review
6.3 Green Supply Chain Sustainability Assessment Model
6.4 Best-Worst Method
6.5 Application and Results
6.6 Discussion
6.7 Conclusion
References
Chapter 7: Economic Performance Analysis of a Resilient and Sustainable Supply Chain: Adoption of Electric Vehicles as a Susta...
7.1 Introduction
7.2 Literature Review
7.3 Methodology
7.3.1 Vehicle Selection and Data Collection
7.3.2 Economic Analysis
7.3.2.1 Operating Cost
7.3.2.2 Maintenance Cost
7.3.2.3 Salvage Value
7.3.2.4 Life Cycle Cost
7.3.3 Environmental Impact Analysis
7.4 Results and Discussion
7.4.1 Sensitivity Analysis
7.5 Conclusion
References
Chapter 8: Integrating Circular Economy and Reverse Logistics for Achieving Sustainable Dairy Operations
8.1 Introduction
8.2 Methods
8.3 Literature
8.3.1 Dairy Farming in Bangladesh
8.4 Dairy Wastes
8.5 Circular Economy
8.6 Reverse Logistics in the Dairy Industry
8.7 Integrating Reverse Logistics and Circular Economy
8.8 A System Dynamic-Based Dairy Model
8.9 Simulation Results
8.10 Concluding Remarks
References
Chapter 9: The Impact of Big Data Analytics Capabilities on the Sustainability of Maritime Firms
9.1 Introduction
9.2 Big Data Analytics Capability (BDAC) and Sustainability Performance
9.2.1 Dimensions of Big Data Analytics Capabilities
9.2.2 BDA Infrastructure Flexibility
9.2.3 BDA Management Capabilities
9.2.4 BDA Personal Expertise
9.3 The MCDM Framework
9.4 DAC Implementation in Norwegian Maritime Firms
9.4.1 The Most Implemented Criteria and Its Preference Over All Criteria
9.4.2 The Least Implemented Criteria and Preference of All Criteria Over It
9.4.3 The Optimal Weights of Criteria
9.4.4 Aggregate Impact Scores
9.5 Discussions and Implications
9.5.1 Implications for Practice
9.5.2 Implications for Research
9.6 Conclusions
References
Chapter 10: Smart Transportation Logistics: Achieving Supply Chain Efficiency with Green Initiatives
10.1 Introduction
10.2 Transportation Practice and Carbon Emission
10.3 Transportation Logistics and Sustainability
10.4 Sustainability and Transportation
10.5 Green Supply Chain, Logistics, and Sustainability
10.6 Methodology
10.7 Future Smart Transportation Model and Mechanism
10.8 Tentative Prediction About the Future Transportation
10.9 Conclusion
References
Index
