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Data sharing in food supply chains and the feasibility of cross-chain data platforms for added value

供应链 业务 产业组织 采购 价值链 营销 环境经济学 经济
作者
Jochem Jonkman,Ismail Badraoui,Thierry Verduijn
出处
期刊:Transportation research procedia 卷期号:67: 21-30 被引量:10
标识
DOI:10.1016/j.trpro.2022.12.031
摘要

Data analysis and data sharing is becoming increasingly important for creating value in the food supply chain. Readily available data is often already shared between supply chain parties, but to achieve additional benefits these parties will have to invest in additional data capturing. Especially product identity-claims, such as sustainable, equitable, or traceable from farm to fork, require transparency of all parties participating in a supply chain and necessitate investments that unlock the required data. This poses problems in supply chains where power is distributed. Typically, supply chains benefitting from the opportunities of data sharing have a higher degree of vertical integration, in which the power of a purchasing party forces suppliers to invest in data capture and exchange. Such investments are not always a possibility: food supply chains can have a dynamic set of participants, meaning that part of the supplier-purchaser relations is discontinuous or even ad-hoc, making investments in chain-specific data infrastructure unattractive for the chain parties involved. Cross-chain data platforms could contribute to solve such problems, although such initiatives have also generally been pushed by dominant supply chain parties. This limits the scope of application of such platforms. In this research, we discuss the feasibility of cross-chain platforms based on case studies with seafood, fresh fruit, fruit juice and processed potato supply chains in the Netherlands. Five dimensions appear to determine the fit with a cross-chain data platform: (i) shared interest in supply chain performance and data sharing, (ii) parallel chains and dynamic chain composition, (iii) alignment in incentives for data collection, (iv) degree of digitisation, and (v) revenue model for data sharing and collaboration.
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