Preface xix Pankaj BHAMBRI, Pushan KUMAR DUTTA, Mudassir KHAN and Marta STAROSTKA-PATYK Chapter 1. AI and Automation: Building Resilient and Sustainable Supply Chains in Uncertain Times 1 Sanam SOOMRO, Mingyue FAN, Ranjeeta SADHWANI and Safia SOOMRO 1.1. Introduction 1 1.2. Understanding supply chain resilience 2 1.3. Risk management frameworks 2 1.

4. Impact of the pandemic on supply chain vulnerabilities 3 1.5. Building resilience post-pandemic 5 1.6. The future of supply chain resilience 7 1.7. Conclusion 10 1.

8. References 11 Chapter 2. Generative AI''s Impact on Supply Chain Decision-Making 17 Pankaj BHAMBRI and Himani SHARMA 2.1. Introduction 17 2.2. Literature review 18 2.3.

Comparison table 22 2.4. Challenges 28 2.5. Technologies 29 2.6. Future scope 30 2.7.

References 31 Chapter 3. Circular Supply Chain Economics 35 Vijay Kumar SINHA and Balajee MARAM 3.1. Introduction 35 3.2. Conceptual foundations 36 3.3. Circular supply-chain economic mechanisms 37 3.

4. Demand and revenue models 38 3.5. Operations research models: closed-loop inventory, pricing and remanufacturing 40 3.6. Metrics for businesses and products 41 3.7. Rules and standards set by the government 44 3.

8. Changes in jobs and structures 45 3.9. Case studies and empirical evidence 45 3.10. Barriers and enablers 46 3.11. Evidence from the real-world and case studies 47 3.

12. Things that get in the way and things that help 48 3.13. A plan for companies to follow to put it into action 51 3.14. Research priorities and gaps 51 3.15. Conclusion 52 3.

16. References 53 Chapter 4. IoT Architecture for End-to-End Visibility 59 Marta STAROSTKA-PATYK 4.1. Introduction 59 4.2. Visibility of supply chains 60 4.3.

Internet of Things (IoT) in logistics and supply chains 61 4.4. IoT for end-to-end visibility in supply chains 64 4.5. IoT challenges and barriers to end-to-end visibility in supply chains 66 4.6. The future of IoT in supply chains and their visibility E2E 68 4.7.

Conclusions 69 4.8. References 69 Chapter 5. Building Blocks of a Transparent IoT Ecosystem 73 Bhagwat KAULWAR, Milind GODASE, Chandrani SINGH and Pankaj BHAMBRI 5.1. Introduction 74 5.2. Characteristics of IoT 76 5.

3. IoT architecture 77 5.4. IoT as XaaS 80 5.5. Conclusion 83 5.6. References 84 Chapter 6.

Blockchain Implementation for Supply Chain Transparency Modeling 87 Helena KOSCIELNIAK 6.1. Introduction 87 6.2. Experimental methods and materials 89 6.3. Results and discussion: case studies 90 6.4.

Conclusion 98 6.5. References 99 Chapter 7. Autonomous Systems in Supply Chain Operations 101 Agnieszka PACUD 7.1. Introduction 101 7.2. Objective and scope of the chapter 104 7.

3. Research procedure 104 7.4. Analysis of results and discussion 106 7.5. Conclusions 111 7.6. References 113 Chapter 8.

Leveraging Data and Analytics for Next-Generation Supply Chain Resilience 117 Karina ZACHARSKA 8.1. Introduction 117 8.2. The challenges of today''s supply chains 119 8.3. The role of data as the foundation for optimization 119 8.4.

The importance of data in supply chain management 120 8.5. Technologies supporting data collection and analysis 121 8.6. Analytical methods and optimization models in supply chain management 126 8.7. Conclusion 129 8.8.

References 130 Chapter 9. Data-driven Supply Chain Optimization 133 Rafa³ NIEDBAL, Paula PYP£ACZ and Muhammad Asif KHAN 9.1. Introduction 133 9.2. Literature review 134 9.3. Automated ML in supply chain optimization 140 9.

4. Conclusion 151 9.5. References 152 Chapter 10. Sustainability Transformation Roadmaps 159 Paula BAJDOR 10.1. Introduction 159 10.2.

Sustainability transformation 161 10.3. Sustainability roadmap structures 162 10.4. Building a sustainable transformation roadmap 169 10.5. Conclusion 171 10.6.

References 172 Chapter 11. Reimagining Supply Chains: Nearshoring and Network Redesign in the Age of AI, Automation and Sustainability 175 Jeffy JOHNSON 11.1. Introduction 176 11.2. Experimental methods and materials 176 11.3. Nearshoring as a resilience strategy 176 11.

4. Conceptual foundations of nearshoring 177 11.5. Drivers of nearshoring adoption 177 11.6. Benefits of nearshoring 178 11.7. Challenges and risks of nearshoring 179 11.

8. Industry case studies 180 11.9. Theoretical and analytical frameworks 181 11.10. Future directions in nearshoring research 181 11.11. Network redesign and digital twins 181 11.

12. Challenges and future directions 184 11.13. Sustainability and ESG compliance in supply chains 187 11.14. Analysis of supply chain performance graphs 189 11.15. Recommendations 192 11.

16. Conclusion 193 11.17. References 193 Chapter 12. Digital Supply Chain Talent Development: Preparing the Workforce for Next-Gen Supply Chains 197 Pankaj BHAMBRI and Sita RANI 12.1. Introduction: the looming talent crisis in a digital era 197 12.2.

Defining the next-generation supply chain professional 200 12.3. A strategic framework for talent development 202 12.4. The critical role of academia and industry partnerships 205 12.5. Case study: building a future-ready talent pipeline in practice 206 12.6.

Conclusion: securing competitive advantage through strategic talent management 207 12.7. References 210 Chapter 13. Change Management for Supply Chain Transformation 213 S. KAVITHAMBIKA, K.M. SANTHOSHA, R. KIRAN and Pankaj BHAMBRI 13.

1. Introduction 213 13.2. Theoretical foundations of change management 214 13.3. Framework for supply chain change management 219 13.4. Importance of leadership and governance structures 221 13.

5. Challenges and barriers 221 13.6. Enablers and best practices 222 13.7. The future 222 13.8. References 223 Chapter 14.

Future Horizons: Emerging Technologies and Models 227 Krishi Pallab SAIKIA, Debjit DHAR, Rik DAS and Saranik MAHAPATRA 14.1. Introduction 228 14.2. A unified framework for intelligent data migration 231 14.3. The role of generative AI in cross-domain data migration 237 14.4.

Real-world applications across domains: bridging petrochemical and medical data ecosystems 241 14.5. Synthetic evaluation and performance metrics 246 14.6. Future directions 250 14.6.1. Explainable AI for semantic transformation 251 14.

7. Conclusion 252 14.8. References 252 Chapter 15. Cybersecurity and Zero Trust Architectures in Supply Chains 255 P. ASHOK, Venkatesh RAMAMURTHY, S. Lakshmi SRIDEVI and K. Murali KRISHNA 15.

1. Introduction 256 15.2. Literature review 256 15.3. Architectures in supply chain landscape 258 15.4. The pillars of Zero Trust in the supply chain context 260 15.

5. Implementing ZTA: an architectural shift 263 15.6. Zero Trust for next-generation supply chain technologies 263 15.7. Technical challenges/limitations 263 15.8. Future enhancements 264 15.

9. Conclusion 264 15.10. References 265 Chapter 16. Additive Manufacturing and the Rise of Digital Inventory 271 Pankaj BHAMBRI and Mudassir KHAN 16.1. Introduction: the burden of physical inventory 271 16.2.

Defining the digital inventory paradigm 272 16.3. Additive manufacturing as the enabling technology 273 16.4. Strategic benefits: resilience, agility and cost redefinition 273 16.5. The sustainability imperative: waste reduction and localized production 274 16.6.

Implementation challenges and considerations 275 16.7. Future horizons: integrating digital inventory with AI and IoT 276 16.8. Conclusion: a roadmap for adoption 278 16.9. References 279 Chapter 17. Ethical and Social Governance of AI-enabled Supply Chains 283 Pankaj BHAMBRI and Marta STAROSTKA-PATYK 17.

1. Introduction: the imperative for ethical AI in global supply chains 283 17.2. Core ethical challenges posed by supply chain AI 287 17.3. Societal implications and stakeholder perspectives 289 17.4. Frameworks for ethical AI governance in supply chains 291 17.

5. Implementing social governance: beyond compliance 293 17.6. Building the governance infrastructure 295 17.7. Metrics, reporting and continuous improvement 297 17.8. Case studies: navigating ethical dilemmas 299 17.

9. Conclusion: toward responsible and trustworthy AI-powered supply chains 301 17.10. References 303 Chapter 18. Revolutionizing Supply Chains with Artificial Intelligence and Machine Learning: A Conceptual Model 307 Sunitaa TANK, Manika GARG and Bharat Kumar TANK 18.1. Introduction 307 18.2.

Literature review 308 18.3. Methodology 310 18.4. Conceptual model 311 18.5. Findings 313 18.6.

Implications 314 18.7. Conclusion 315 18.8. Future research directions 316 18.9. References 317 Chapter 19. Enabling AI in Supply Chain Transformation: An MCDM-Based Analysis of Critical Success Factors 321 Tripti SHARMA.