Privacy protection and data coordination mechanism of supply chain based on blockchain

Tang, Fei; Lin, Jing-wen; Xing, Lili; Yang, Xianggui; He, Hongping; Ma, Shenglin; Huang, Dong

doi:10.1117/12.2685950

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Mitigation strategies for ensuring data security include the use of advanced technologies such as AI, machine learning, and proactive blockchain to address challenges related to data collection, analysis, and processing (Shahzad et al, 2020). Additionally, the implementation of privacy protection and data coordination mechanisms based on blockchain can help address privacy and security issues when exchanging large amounts of data within supply chains (Tang et al, 2023).…”

Section: Challenges In Adopting Big Data In Supply Chain Managementmentioning

confidence: 99%

Reviewing the use of big data in supply chain optimization in the USA

Israel Osejie Okoduwa,

Bankole Ibrahim Ashiwaju,

Jeremiah Olawumi Arowoogun

et al. 2024

World J. Adv. Res. Rev.

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This paper provides a succinct overview of the review conducted on the utilization of Big Data in supply chain optimization within the United States. The advent of Big Data analytics has revolutionized traditional supply chain management, offering unprecedented opportunities for enhancing efficiency, reducing costs, and improving overall operational performance. This comprehensive review examines the current state of Big Data applications in supply chain optimization, focusing specifically on the context of the United States. The review begins by outlining the fundamental role of Big Data in transforming supply chain processes. It delves into various aspects, including data collection, processing, and analysis, emphasizing their impact on decision-making and strategic planning. Notably, the study highlights real-world examples of successful Big Data implementations within the U.S. supply chain landscape, showcasing how companies have leveraged data-driven insights to streamline operations and gain a competitive edge. Furthermore, the paper explores the challenges associated with the adoption of Big Data in supply chain management. It addresses concerns related to data security, privacy, and the need for advanced technological infrastructure. Additionally, the review considers the organizational and cultural shifts required for successful integration, emphasizing the importance of a holistic approach to implementation. The paper concludes by pointing towards future trends and potential developments in the use of Big Data for supply chain optimization in the U.S. It underscores the evolving nature of technology and its continued impact on reshaping supply chain strategies. The insights derived from this review contribute to a deeper understanding of the current landscape, offering valuable implications for practitioners, researchers, and policymakers engaged in optimizing supply chain processes through the harnessing of Big Data analytics.

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Section: Challenges In Adopting Big Data In Supply Chain Managementmentioning

confidence: 99%

Reviewing the use of big data in supply chain optimization in the USA

Israel Osejie Okoduwa,

Bankole Ibrahim Ashiwaju,

Jeremiah Olawumi Arowoogun

et al. 2024

World J. Adv. Res. Rev.

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Big Data Analytics for Supply Chain Optimization

Vaghani

2024

Advances in Logistics, Operations, and Management Science

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Despite the extensive discussion on the benefits of BDA in supply chains, there remains a lack of systematic understanding of how BDA can be effectively linked to Supply Chain Optimization (SCO). This document explores the cumulative published literature from 2014 and 2024, so as to ascertain the impact of big data analytics on supply chain optimization. 64 articles were selected from diverse academic journals, and from these articles, information was gathered, analyzed, and organized. The results shows that Big data is often used for making predictions in SCO; big data analytics has a lot of difficulties dealing with large amounts of data related to managing the supply chain, which include too much data, problems with data quality, keeping data safe and private, difficulty in analyzing data, ability to grow as needed, and complicated supply chains. The study recommends that big data projects should begin with specific goals instead of just hoping people will use them. Starting with small test projects can help show the benefits of big data analytics.

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Privacy protection and data coordination mechanism of supply chain based on blockchain

Cited by 2 publications

References 14 publications

Reviewing the use of big data in supply chain optimization in the USA

Reviewing the use of big data in supply chain optimization in the USA

Big Data Analytics for Supply Chain Optimization

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