Garbage in garbage out: The precarious link between IoT and blockchain in food supply chains
•Presents a theoretical argument based on a study of Australia-China beef exports.•Critiques data quality and validity assumptions in many IoT and blockchain systems.•Changes oracle identity and data validity practices using ‘common knowledge’ notion.•Limits possible capricious claims on IoT data pe...
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| Vydáno v: | Journal of industrial information integration Ročník 25; s. 100261 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Inc
01.01.2022
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| Témata: | |
| ISSN: | 2452-414X, 2452-414X |
| On-line přístup: | Získat plný text |
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| Shrnutí: | •Presents a theoretical argument based on a study of Australia-China beef exports.•Critiques data quality and validity assumptions in many IoT and blockchain systems.•Changes oracle identity and data validity practices using ‘common knowledge’ notion.•Limits possible capricious claims on IoT data performance in blockchain systems.•Proposes mechanism design for data to become lead indicators of desired future states.
The application of blockchain in food supply chains does not resolve conventional IoT data quality issues. Data on a blockchain may simply be immutable garbage. In response, this paper reports our observations and learnings from an ongoing beef supply chain project that integrates Blockchain and IoT for supply chain event tracking and beef provenance assurance and proposes two solutions for data integrity and trust in the Blockchain and IoT-enabled food supply chain. Rather than aiming for absolute truth, we explain how applying the notion of ‘common knowledge’ fundamentally changes oracle identity and data validity practices. Based on the learnings derived from leading an IoT supply chain project with a focus on beef exports from Australia to China, our findings unshackle IoT and Blockchain from being used merely to collect lag indicators of past states and liberate their potential as lead indicators of desired future states. This contributes: (a) to limit the possibility of capricious claims on IoT data performance, and; (b) to utilise mechanism design as an approach by which supply chain behaviours that increase the probability of desired future states being realised can be encouraged. |
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| ISSN: | 2452-414X 2452-414X |
| DOI: | 10.1016/j.jii.2021.100261 |