Next-Gen Supply Chains

1. Auflage 2026
ISBN: 978-1-83669-074-0
Verlag: John Wiley & Sons

Buch, Englisch, 416 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 757 g

In an era defined by global disruptions, sustainability mandates and rapid technological advancement, Next-Gen Supply Chains provides an essential roadmap for navigating the complex transformation of global supply networks. This comprehensive book moves beyond isolated trends to present an integrated framework where generative AI, blockchain, autonomous systems and the Internet of Things converge to build resilient, efficient and responsible operations.

This book masterfully bridges the critical gap between theoretical concepts and practical implementation, offering readers actionable strategies, detailed case studies from industry leaders such as Amazon and Lenovo, and robust frameworks for risk management, ethical AI governance and circular economy integration. With its unique emphasis on the synergy between technological innovation and the necessary human capital development, the book is an indispensable resource for supply chain executives, operations managers, technology implementers and academics seeking to future-proof their organizations and master the strategic imperatives of the modern supply chain landscape.

Autoren/Hrsg.

Bhambri, Pankaj

Dutta, Pushan Kumar

Khan, Mudassir

Starostka-Patyk, Marta

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Informatik Rechnerarchitektur
• Mathematik | Informatik EDV | Informatik Technische Informatik Hardware: Grundlagen und Allgemeines

Inhaltsverzeichnis

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, Akash RAI, Indrajit GHOSAL and Md. Rahat KHAN

19.1. Introduction 321
19.2. Literature review 323
19.3. Methodology 326
19.4. Findings and discussion 330
19.5. Conclusion and future work 333
19.6. References 334

Chapter 20. Sustainable Intelligence: Aligning Ethical AI in Global Supply Chain Systems 337
Gagandeep SINGH, Jasdeep Singh WALIA and Priya MANDIRATTA

20.1. Introduction 337
20.2. Review of the literature 338
20.3. Research gap 343
20.4. Theoretical framework 344
20.5. Proposed framework concerning sustainable intelligence in AI-enabled supply chains 347
20.6. Implications of the study 350
20.7. Conclusion and scope for future research work 353
20.8. References 354

List of Authors 359
Index 365

Über Autor(innen)

Pankaj Bhambri is an associate professor and a Stanford Top 2% Scientist. He is a postdoctoral researcher, specializing in machine learning and wireless communications. His research focuses on AI, blockchain and sustainable computing.

Pushan Kumar Dutta is an associate professor and Erasmus Mundus scholar, specializing in AI and edge computing. His research focuses on bridging data analytics and sustainable technology for smart cities and healthcare.

Mudassir Khan is an assistant professor and postdoctoral fellow, specializing in big data analytics and AI. His research on deep learning and IoT applications concerns healthcare and computer science.

Marta Starostka-Patyk is a professor specializing in logistics and supply chain management. Her research focuses on sustainable logistics, reverse logistics and information technologies in modern supply chains.