Book Title: Emerging Trends in Commerce and Management
Editor: Dr. Nilesh Anute
ISBN: 978-81-979197-7-0
Chapter: 24
DOI: https://doi.org/10.59646/emc24/255
Authors:
Mr. Deepak Tulsiram Patil, Assistant Professor, Amity University, Dubai.
Dr. Kiran S. Kale, Associate Professor (MBA), Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri, Pune, Maharashtra, India.
Learning Objectives
In this chapter, we delve into the dynamic landscape of operations and supply chain management, highlighting the latest trends that are transforming these crucial areas. One primary focus is the digital transformation, which integrates advanced technologies such as artificial intelligence, machine learning, the Internet of Things (IoT), and blockchain to enhance supply chain efficiency and resilience. These technologies enable better visibility, optimize operations, and support data-driven decision-making. Additionally, the chapter explores the growing emphasis on sustainability and green supply chains, where businesses adopt eco-friendly practices to minimize environmental impact and enhance brand reputation. The role of globalization is also examined, revealing how global supply chains have become more complex and necessitating sophisticated strategies to manage varying regulatory environments and geopolitical risks. Technological advancements, including automation and advanced analytics, are revolutionizing supply chain operations, improving productivity and reducing costs. Risk management and resilience are critical topics, highlighting the need for companies to proactively identify and mitigate potential disruptions through strategies like diversifying suppliers and maintaining buffer stocks. Finally, the chapter looks ahead to future innovations such as 5G, augmented reality (AR), and virtual reality (VR), which are expected to further enhance supply chain capabilities and responsiveness.
References
- Ghasemi, F. Goodarzian, A. Abraham, A new humanitarian relief logistic network for multi-objective optimization under stochastic programming, Appl. Intell. 52 (12) (2022) 13729–13762.
- Ghasemi, H. Hemmaty, A. Pourghader Chobar, M.R. Heidari, M. Keramati, A multi-objective and multi-level model for location-routing problem in the supply chain based on the customer’s time window, J. Appl. Res. Ind. Eng. (2022).
- Ghasemi, H.A. Khalili, A.P. Chobar, S. Safavi, F.M. Hejri, A new multi-echelon mathematical modeling for pre-and post-disaster blood supply chain: robust optimization approach, Discret. Dyn. Nat. Soc. 2022 (2022) 1–10.
- Li, Y. Gong, Z. Wang, S. Liu, Big data and big disaster: a mechanism of supply chain risk management in global logistics industry, Int. J. Oper. Prod. Manag. 43 (2) (2023) 274–307.
- Shokouhifar, M. Ranjbarimesan, Multivariate time-series blood donation/ demand forecasting for resilient supply chain management during COVID-19 pandemic, Clean. Logist. Supply Chain 5 (2022), 100078.