Supply Chain Risk Management via Enhanced Observability
DOI:
https://doi.org/10.53469/jgebf.2024.06(11).07Keywords:
Management, real time, analytics, Resilience, Risk Assessment, Information Sharing, Transparency, Machine Learning, Predictive, Analytics, Internet of Things, SCRM, logistics, Big Data, tourism, Operational Risk, Blockchain, Technology, Decision Support SystemsAbstract
Supply Chain Risk Management is crucial for maintaining the resilience and reliability of supply chains in today's complex and rapidly changing business environment. This paper explores the role of improved observability in enhancing SCRM efforts. Improved observability, which involves the visibility and understanding of real - time supply chain activities, has emerged as a key driver for effective risk management. By leveraging advanced technologies such as the Internet of Things, big data analytics, and blockchain, supply chain practitioners can gain granular insights into operations, thereby significantly improving their capability to identify, assess, and prioritize risks.
References
Addo - Tenkorang, R., & Helo, P. (2016, November 1). Big data applications in operations/supply - chain management: A literature review. Elsevier BV, 101, 528 - 543. https: //doi. org/10.1016/j. cie.2016.09.023
Blackhurst, J., Craighead, C W., Elkins, D., & Handfield, R. (2005, October 1). An empirically derived agenda of critical research issues for managing supply - chain disruptions. Taylor & Francis, 43 (19), 4067 - 4081. https: //doi. org/10.1080/00207540500151549
Ding, R. (2014, September 1). The Research and Management Strategies of Supply Chain Risks. Trans Tech Publications, 644 - 650, 5523 - 5527. https: //doi. org/10.4028/www.scientific. net/amm.644 - 650.5523
Fu, J., Chakpitak, N., Goldsmith, P., Sureephong, P., & Kunarucks, T. (2012, October 1). Creating a Knowledge Supply Chain for e - Tourism Curriculum Design. IGI Global, 8 (4), 71 - 94. https: //doi. org/10.4018/jkm.2012100104
Hassan, M M D. (2006, January 12). Engineering supply chains as systems. Wiley - Blackwell, 9 (1), 73 - 89. https: //doi. org/10.1002/sys.20042
Heskett, J L. (1971, March 1). Controlling customer logistics service., 1 (3), 141 - 145. https: //doi. org/10.1108/eb038839
Johnson, M E., & Davis, T. (1998, June 1). Improuing supply chain performance by using order fulfillment metrics. Wiley, 17 (3), 3 - 16. https: //doi. org/10.1002/npr.4040170304
Kengpol, A., & Tuammee, S. (2015, May 21). The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: an empirical study. Taylor & Francis, 54 (4), 1020 - 1038. https: //doi. org/10.1080/00207543.2015.1041570
Mabert, V A., & Venkataramanan, M A. (1998, July 1). Special Research Focus on Supply Chain Linkages: Challenges for Design and Management in the 21st Century. Wiley - Blackwell, 29 (3), 537 - 552. https: //doi. org/10.1111/j.1540 - 5915.1998. tb01353. x
Muñoz, A., & Clements, M. (2008, April 1). Disruptions in Information Flow: A Revenue Costing Supply Chain Dilemma. Multidisciplinary Digital Publishing Institute, 3 (1), 30 - 40. https: //doi. org/10.3390/jtaer3010005
Sriadhi, S. (2017, March 1). Model of The Material Inventory Management Using Multimedia based Information System. IOP Publishing, 180, 012239 - 012239. https: //doi. org/10.1088/1757 - 899x/180/1/012239
Wang, X., & Ma, J. (2009, May 1). Application and Research of Analytic Hierarchy Process in Project Investment Appraisal and Decision - Making. https: //doi. org/10.1109/ebiss.2009.5137936
Zhang, D., Pee, L G., & Cui, L. (2021, January 8). Artificial intelligence in E - commerce fulfillment: A case study of resource orchestration at Alibaba's Smart Warehouse. https: //www.sciencedirect. com/science/article/pii/S0268401220315036
Zhou, W., Wang, H., Shi, V., & Chen, X. (2022, July 4). A Decision Model for Free - Floating Car - Sharing Providers for Sustainable and Resilient Supply Chains. Multidisciplinary Digital Publishing Institute, 14 (13), 8159 - 8159. https: //doi. org/10.3390/su14138159
Zokaeï, K. (2010, January 1). Value chain analysis of the UK food sector. Elsevier BV, 187 - 211. https: //doi. org/10.1533/9781845697778.3.187
Zsidisin, G A., Ellram, L M., Carter, J R., & Cavinato, J L. (2004, June 1). An analysis of supply risk assessment techniques. Emerald Publishing Limited, 34 (5), 397 - 413. https: //doi. org/10.1108/09600030410545445
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