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The gig economy has changed the way firms behave in relation to their human resources, which has impacted every individual in society. This book analyzes Industry 5.0 and the human capital revolution with the rise of the gig economy. Operations and supply chain management are no exception to the influence. This book closes an existing gap in available literature with the novel ideas it brings.
Smart and Sustainable Gig Economy in the Industry 5.0 Era: Engineering and Management Aspects analyzes smart and sustainable supply chain management concepts along with green systems, and smart applications all from a gig economy perspective. Smart applications of Industry 4.0 are merged with a triple-bottom-line approach, and their applicability to a gig economy is discussed along with other hot areas such as AI, and Machine Learning alongside the Industry 5.0 revolution. Case studies, real-world examples, models, and applications are included.
This book presents state-of-the-art knowledge on smart and sustainable supply chain management in a gig economy suitable for researchers, professionals, and UG/PG individuals.
List of contents
Part 1: Foundation & Context. 1.Exploring the Gig Economy: Definitions and Exemplars. 2. The Upcoming Era of Industry 5.0: New Age, New Rules and the Transition from Industry 4.0 to 5.0. 3. Society 5.0, Sustainability and Social Aspects of GIG Economy. Part 2: Core Transformations & Labor Dynamics. 4. Global Trends in GIG Economy: Online Labour Market and Future of Work. 5. Revolutionizing Industry 5.0: Human Resource Transformation in the Gig Era. 6. Designing for Uncertainty: How Organizations and Workers Navigate the Gig Economy's Shifting Structures. Part 3: Operational Applications. 7. Supply Chain Management in Gig Era. 8. Logistics and Cargo Services in Gig Economy. Part 4: Technological Enablers. 9. Machine Learning and Data Analytics in GIG Economy: Big Data Applications. 10. AI, Autonomous Systems, Cloud Technology and Robotics in GIG Economy. 11. The Synergistic Role of Large Language Models (LLMs) and the Gig Economy in Industry 5.0: Reimagining Supply Chains and Labor Dynamics. Part 5: Advanced Applications & Decision-Making. 12. GIG Economy: Mathematical Modeling and Optimization Aspects. 13. Multi-Criteria Decision-Making Methods in Gig Economy: A Comparative Application. Part 6: Strategic & Business Implications. 14. Strategic Management Consultancy in the Age of Industry 5.0: Leveraging the Gig Economy for Business Transformation. 15. Innovative Marketing Strategies for Gig Economy Platforms.
About the author
Ehsan Khajeh has acquired extensive international exposure over the years as an assistant professor in Business Processes and Operations Management at Coventry University, UK. His most recent academic qualifications include a Ph.D. in Management and Business from Kingston University London, MBA from Staffordshire University, UK, and a Bachelors in E-commerce from Malaysia (Staffordshire University). He has over four years of experience in Operations Management and is a researcher with an interest in Logistics and Supply Chain Management, Industry 4.0, Queuing Theory, Operations Management, and Behavioral Operations Management. He is an expert in quantitative and qualitative research methods and tools and has seven years of international experience in management and consulting across Malaysia and the UK.
Zahra Mohammadnazari is an assistant lecturer in the School of Strategy and Leadership at Coventry University, UK. She received her M.Sc. and B.Sc. in Industrial Engineering from the University of Tehran in 2022 and a Master of Research (MRes) in Business Management and Social Science from Kingston University London in 2022. She has been in higher education as a researcher for more than seven years; during this time, she has worked with scholars and academics in different countries and with various backgrounds. She has taught highly diverse groups of students, at both undergraduate and postgraduate levels. Her research interests are optimization, supply chain management, performance assessment, data analytics, and uncertainty modeling. Dr. Mohammadnazari has been a reviewer and guest editor of several reputable journals.
