Handbook on Artificial Intelligence and the Circular Economy

Edited by Ashutosh Samadhiya, Assistant Professor of Operations and Supply Chain Management, Jindal Global Business School, OP Jindal Global University, Sonipat, India, Anil Kumar, Professor of Operations, Supply Chain, and Business Analytics, Samuel O. Idowu, Professor of Accounting and Sustainability, Guildhall School of Business and Law, London Metropolitan University, UK and Pankaj Dutta, Professor of Decision Sciences and Operations Research, Shailesh J. Mehta School of Management, Indian Institute of Technology (IIT) Bombay, Mumbai, India

• ContentsPART I FOUNDATIONS AND STRATEGIC PERSPECTIVES OF AI IN THECIRCULAR ECONOMY1 Introduction to the handbook on AI and the circular economy 2Ashutosh Samadhiya, Anil Kumar, Samuel O. Idowu and Pankaj Dutta2 Artificial intelligence as a catalyst for the circular economy: trends andfuture direction 12Jayalaxmi Samal, Ashyashree Praharaj, Ashok Kumar Patra andBiswajit Prasad Chhatoi3 Supporting the circular economy using digital technologies in operationsmanagement processes 28Das Suman Suman Kumar and Nicola Saccani4 AI and traditional wisdom: Bridging modernity and tradition in strategicdecision-making 39Pragati Kachhi, Kritika Tekwani and Akanksha Singh5 The role of AI in driving circular economy governance in mergers andacquisitions of Indian chemical industries 62Biswadeep Dutta6 The impact of AI on privacy law: investigation on data protection in themodern era 80Abhilasha Khare, Aditya Kedari and Pranjali BawanePART II AI IN SUSTAINABLE PRODUCT DESIGN, MANUFACTURING,AND INDUSTRIAL EFFICIENCY7 AI and sustainable product design 95Ananya Mishra and Pradeep Kautish8 Artificial intelligence as an enabler of remanufacturing in circulareconomy system: a systematic literature review 110Farheen Naz, Ashutosh Samadhiya, Anil Kumar, Samuel O. Idowu andPankaj Dutta9 Predicting manufacturing defects using machine learning algorithms 123Gopi R., Aditya Sharma , Savita Sangam and Saurabh Pratap10 A data analytics approach for the selection of suppliers for achieving bettersustainability of the manufacturing industries 140Swarup Paul Paul11 Agents-based model for MODFJSP with efficient energy consumption 156Manojkumar Pal, Murari Lal Mittal, Sagar Ghuge and Surya Prakash12 Challenges and implementation of AI for resource efficiency and wastereduction in MSMEs in India 166Lalit KumarPART III AI IN CIRCULAR SUPPLY CHAINS, GREEN LOGISTICS, ANDECO-MARKETING13 Ethical logistics and green supply chain management 183Hajar Fatorachian14 Integrating emerging technologies in circular supply chains: a review ofkey trends and a way ahead 204Ashutosh Mishra, Akshay Dvivedi and Pradeep Kumar15 Implementing sustainable practices in Amazon’s supply chain managementsystem 222Chinmay Mali and Sujay Naik16 Multi-objective 4-dimensional green transportation problem for multi-items through IoT driven vehicle velocity 242Md Samim Aktar and Deepak Sharma17 Decoding eco-purchases: the interplay of green packaging, environmentalawareness and brand image 261Rajesh Moharana, Himanshi Garg and Sonalika SarangiPART IV AI FOR SUSTAINABLE HEALTHCARE, ENERGY, AND DIGITALINNOVATION18 Sustainable digital health: integrating AI and circular economy principles 282Kavita Rawat Garg, Krishan Kumar Pandey and Gaurav Kabra19 AI-enabled healthcare waste sorting using a multi-layer perceptronalgorithm and its validation with Kolmogorov-Arnold networks 301Ananya Kapoor, Vaibhav Sharma and Rajeev Agrawal20 Optimizing renewable energy system maintenance: an integrated approachof GA with ML techniques 323Nisha T. N. and Vijayakumar Bharathi S.21 Leveraging technology for digital green financing and renewable energy:public opinion and emerging trends in India 345Varsha R. and Nayana N.22 Leveraging AI for sustainable agile practices: strategies for green softwaredevelopment 367Pooja R. Nair and Krishnan Ramanathan

‘This Handbook provides a timely and comprehensive exploration of how artificial intelligence can enable circularity across industries. It bridges sustainability science and digital innovation, offering both conceptual depth and practical insight for researchers, practitioners, and policy-makers pursuing regenerative, data-driven transitions.’