Data-driven secure, resilient and sustainable supply chains: gaps, opportunities, and a new generalised data sharing and data monetisation framework

被引:106
作者
Bechtsis, Dimitrios [1 ,2 ]
Tsolakis, Naoum [3 ]
Iakovou, Eleftherios [4 ]
Vlachos, Dimitrios [1 ]
机构
[1] Aristotle Univ Thessaloniki, Dept Mech Engn, Thessaloniki, Greece
[2] Int Hellen Univ, Dept Ind Engn & Management, Thessaloniki, Greece
[3] Univ Cambridge, Sch Technol, Dept Engn, Cambridge, England
[4] Texas A&M Univ, Dept Engn Technol & Ind Distribut, J Mike Walker Dept Mech Engn 66, Mosbacher Inst Trade Econ & Publ Policy, College Stn, TX USA
关键词
supply chain resilience; sustainability; security; data sharing and monetisation; artificial intelligence; blockchain; BIG DATA ANALYTICS; TRANSACTION-COST; PREDICTIVE ANALYTICS; MANAGEMENT; FUTURE; DISRUPTION; SELECTION; IMPACT; PERFORMANCE; SIMULATION;
D O I
10.1080/00207543.2021.1957506
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The increasing exposure of global supply chains to severe disruptions such as the ones related to the COVID-19 pandemic, clearly demonstrated the need for novel data-driven risk management paradigms that monetise data from internal and external stakeholders to support supply chain security, resilience, and sustainability. We first motivate the challenges that supply chains are facing under the new realities. We then provide a critical taxonomy of the relevant literature and identify gaps which include: (i) the impact of security on supply chain operations; (ii) cost effective resiliency strategies and practices; and (iii) the social and labour dimensions of sustainability. We then propose a new generalised framework that encompasses all the identified challenges, gaps in literature and in practice, and opportunities in supply chain management research. The proposed framework is validated through a real-world case study of the organic food supply chain. This validation further highlights the need for data-driven digital technologies that enable data collection and management, secure storage and effective data processing towards data monetisation for supply chain security, cost-competitive resilience, and sustainability across end-to-end operations.
引用
收藏
页码:4397 / 4417
页数:21
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