Submitted:
09 June 2024
Posted:
11 June 2024
You are already at the latest version
Abstract

Keywords:
1. Introduction
2. Literature Review
2.1. SCOR Model
2.2. Agrifood Supply Chains, Reverse Logistic and Sustainability
2.3. Disruptive Technology Blockchain
3. Materials and Methods
4. Development and Results
5. Conclusions
5.1. Social Implications
5.2. Practical Implications
- Different agri-food chains may not be identical to those addressed in this case. However, they could consider many of the inputs presented in the study.
- The Smart Contract may be limited or not depending on the technical capabilities of different tools.
- Future Work:
- Agri-food chains and the current scenario offer constant changes; future studies could be oriented towards:
- Efficiency of the blockchain network in real-world scenarios.
- Conceptual and technical evaluation of the level of participation and willingness of each actor in the agri-food chain.
- The relationship between the application of blockchain technology in different processes and its connection to sustainable development goals.
References
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| Compliance | Description | Cost of Operation | Time Operation |
|---|---|---|---|
| Border compliance | The Border compliance includes:
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US$862 | 49 Hours |
| Documentary Compliance | The Documentary Compliance includes:
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US$226 | 12 Hours |
| Conceptual | (Yontar, 2023); (S. Gupta et al., 2023); (S. Joshi et al., 2023); (R. Gupta & Shankar, 2023); (P. Joshi et al., 2023); (Chandan et al., 2023); (Mohammed et al., 2023); (S. Patidar et al., 2023); (Rajput et al., 2023); (Kayikci et al., 2022); (Rejeb et al., 2022); (Agnusdei & Coluccia, 2022); (Collart & Canales, 2022); (Khan et al., 2022); (Saha et al., 2022); (S. Dey et al., 2022); (Rejeb et al., 2022); (Yakubu et al., 2022); (Wunsche et al., 2022); (Hassoun et al., 2022); (P. Kumar et al., 2022); (Guruswamy et al., 2022); (Scuderi et al., 2022); (Bansal et al., 2022); (Vostriakova et al., 2022); (Rezaei & Babazadeh, 2022); (Sharma et al., 2020); (Galanakis et al., 2021); (Antonucci et al., 2019); (Pearson et al., 2019); (Tsolakis et al., 2021); (Gopi et al., 2019); (Barbosa, 2021); (Patra et al., 2021); (A. Patidar et al., 2021);(Cruz & De Arruda Ignacio, 2023); (Srhir et al., 2023);(Tanwar et al., 2022); |
| Empirical | (M. Kumar et al., 2023); (R. Gupta & Shankar, 2023); (S. Patidar et al., 2023); (Kayikci et al., 2022); (Wunsche et al., 2022); (Rogerson & Parry, 2020); (Hew et al., 2020); (Kazancoglu et al., 2022); (Maity et al., 2021); (Phua et al., 2021); |
| Modelling | (Yontar, 2023); (Bhatia & Albarrak, 2023); (M. Kumar et al., 2023); (S. Joshi et al., 2023); (S. Patidar et al., 2023); (Rajput et al., 2023); (Khan et al., 2022); (Lee et al., 2021); (Scuderi et al., 2022); (Bansal et al., 2022); (Luo et al., 2022); (Li et al., 2022); (Kamble et al., 2020); (Prashar et al., 2020); (Yadav & Singh, 2020); (Phua et al., 2021); (Runzel et al., 2021); (Yang et al., 2020); (Abdulhussein et al., 2020); (Patra et al., 2021); (AlJemy et al., 2019); (A. Patidar et al., 2021) |
| Technical | (Bhatia & Albarrak, 2023); (Khan et al., 2022); (D. Kumar et al., 2017); (Lee et al., 2021); (Bansal et al., 2022); (Prashar et al., 2020); (Majdalawieh et al., 2021); (Hilt et al., 2018); (Makarov et al., 2019); (Hofman, 2019); |
| Food Safety and Food Security | (Bhatia & Albarrak, 2023); (M. Kumar et al., 2023); (S. Patidar et al., 2023); (Rajput et al., 2023); (Rajput et al., 2023); (Kayikci et al., 2022); (Collart & Canales, 2022); (Khan et al., 2022); (Saha et al., 2022); (Saha et al., 2022); (S. Dey et al., 2022); (Yakubu et al., 2022); (Wunsche et al., 2022); (Lee et al., 2021); (Scuderi et al., 2022); (Bansal et al., 2022); (Rogerson & Parry, 2020); (Tsolakis et al., 2021); (Prashar et al., 2020); (Abdulhussein et al., 2020); (Majdalawieh et al., 2021); (Patra et al., 2021); |
| Quality | (M. Kumar et al., 2023); (Khan et al., 2022); (Saha et al., 2022); (Yakubu et al., 2022); (Wunsche et al., 2022); (Scuderi et al., 2022); (Majdalawieh et al., 2021); (Patra et al., 2021); |
| Sustainable management and efficient use of natural resources | (Bhatia & Albarrak, 2023); (P. Joshi et al., 2023); (Chandan et al., 2023); (Kayikci et al., 2022); (Collart & Canales, 2022); (Khan et al., 2022); (Yakubu et al., 2022); (Wunsche et al., 2022); (Scuderi et al., 2022); (Bansal et al., 2022); (Vostriakova et al., 2022); (Prashar et al., 2020); (Cruz & De Arruda Ignacio, 2023) |
| Prevention, reduction, recycling | (S. Gupta et al., 2023); (Khan et al., 2022); (Wunsche et al., 2022); |
| Monitoring and Supervising | (Bhatia & Albarrak, 2023); (R. Gupta & Shankar, 2023); (Rajput et al., 2023); (Khan et al., 2022); (Yakubu et al., 2022); (Lee et al., 2021); (Scuderi et al., 2022); (Bansal et al., 2022); (Luo et al., 2022); (Kazancoglu et al., 2022); (Abdulhussein et al., 2020); (Patra et al., 2021); (AlJemy et al., 2019); |
| Food Provenance | (Bhatia & Albarrak, 2023); (Rajput et al., 2023); (Kayikci et al., 2022); (Collart & Canales, 2022); (Khan et al., 2022); (Yakubu et al., 2022); (Wunsche et al., 2022); (Lee et al., 2021); (Gopi et al., 2019); (Hew et al., 2020); (Kazancoglu et al., 2022); (Runzel et al., 2021); (Yang et al., 2020); (Majdalawieh et al., 2021); (Patra et al., 2021); |
| resilient infrastructure | (Yontar, 2023); (Bhatia & Albarrak, 2023); (S. Joshi et al., 2023); (Mohammed et al., 2023); (S. Patidar et al., 2023); (Rejeb et al., 2022); (Khan et al., 2022); (S. Dey et al., 2022); (Rejeb et al., 2022); (Yakubu et al., 2022); (Wunsche et al., 2022); (Kamble et al., 2020); (Sharma et al., 2020); (Antonucci et al., 2019); (Pearson et al., 2019); (Tsolakis et al., 2021); (Yadav & Singh, 2020); (Maity et al., 2021); (Hilt et al., 2018); (AlJemy et al., 2019); (Hofman, 2019); (A. Patidar et al., 2021); |
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| Timestamp | 24 seconds ago. (May-22-2024 07:53:31 PM +UTC) |
| From | 0c089f0bbdf0f2405bb26438bb0af3e8f735e42f4f |
| To | Contract 0x5c54711eae649da59a07690888294fe7217be884 |
| Value | 0 BNB |
| Transaction Fee | 0.00305299 BNB ($0,75) |
| Gas price | 0.0000000001 BNB (10 Gwwi) |
| SDGs | Indicator | The convergence between Blockchain and SCOR Model ensures: | This application offers: | |||
|---|---|---|---|---|---|---|
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2.1.2 | Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES) | Security and safety of foods based on the verification and monitoring of each step in the Agri-food Chain. | Ensuring a high level of traceability for all operations and knowledge of product delocalizations. It is important when there is a possible agri-food contamination, so that in such an event, the flow of the Agri-food supply chain can be halted, and reverse logistics applied. | ||
| 2.3.1 | Volume of production per labour unit by classes of farming/pastoral/forestry enterprise size | Accurate localization of products at their origin and of each participant in the Agri-food Chain (Stakeholders). | Traceability of participants in the agri-food supply chain and their contributions to each process | |||
| 2.3.2 | Average income of small-scale food producers, by sex and indigenous status | Transparency in each sales operation within the Agri-food Chain, aiming for the correct distribution of profits or gains. | ||||
| 2.C.1 | Indicator of food price anomalies | Identification of market fluctuations and evaluation of those changes. | To understand the variability of costs for each step in the supply chain | |||
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9.3.1 | Proportion of small-scale industries in total industry value added | Adding new value to the Agri-food Chain and offering new consumption opportunities. | Added value by decentralizing and transforming the Agri-food Supply Chain, considering all stakeholders in each process. | ||
| 9.4.1 | CO2 emission per unit of value added | Identifying each process with a high footprint in the Agri-food Chain and sharing that risk. | With each step identified, it is possible to measure the CO2 emissions for each activity within the Agri-food Supply Chain, considering logistics activities through to the value and costs of each stage of the product. | |||
| 9.B.1 | Proportion of medium and high-tech industry value added in total value added | Taking advantage of the benefits of integrating Blockchain and the SCOR Model (traceability, decentralization of information, auditability, trust). | Easy access to traceability for each stakeholder. In this case, every actor can measure the impact of their activities and replicate that logic for their stakeholders. | |||
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12.2.1 | Material footprint, material footprint per capita, and material footprint per GDP | Measuring the foodprint at each step of the Agri-food Supply Chain | Traceability for each process and step, enabling the measurement of footprints and other impacts. | ||
| 12.2.2 | Domestic material consumption, domestic material consumption per capita, and domestic material consumption per GDP | Improving resource consumption based on decentralized information | Flexibility in decision-making based on historical information for each process and product. These data can be used to improve material consumption | |||
| 12.3.1 | (a) Food loss index and (b) food waste index | "Identifying and measuring these indices based on historical information. | A database with a higher level of precision because this information cannot be modified. | |||
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