Open Access
Issue
RAIRO-Oper. Res.
Volume 56, Number 3, May-June 2022
Page(s) 1995 - 2014
DOI https://doi.org/10.1051/ro/2022070
Published online 30 June 2022
  • I. Ali and I. Gölgeci, Managing climate risks through social capital in agrifood supply chains. Supply Chain Manage. Int. J. 25 (2020) 1–16. [Google Scholar]
  • APHIS, USDA, Animal disease traceability: summary of program reviews and proposed directions from state-federal working group. https://www.aphis.usda.gov/publications/animal_health/adt-summary-program-review.pdf (2018). [Google Scholar]
  • APHIS, USDA, Sheep and goat identification. Available at https://www.aphis.usda.gov/aphis/ourfocus/animalhealth/animal-disease-information/sheep-and-goat-health/scrapie-tags (2020). [Google Scholar]
  • J.F. Arvis, Germany tops 2016 logistics performance index. Web page The World Bank, http://www.worldbank.org (2016). [Google Scholar]
  • N. Bumbudsanpharoke and S. Ko, Nano-food packaging: an overview of market, migration research, and safety regulations. J. Food Sci. 80 (2015) R910–R923. [CrossRef] [Google Scholar]
  • M.P. Caro, M.S. Ali and M.E.A. Vecchio, Blockchain-based traceability in Agri-Food supply chain management: a practical implementation. In: 2018 IoT Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany) (2018) 1–44. [Google Scholar]
  • Y.H. Chen, X.W. Wen, B. Wang and P.Y. Nie, Agricultural pollution and regulation: how to subsidize agriculture? J. Cleaner Prod. 164 (2017) 258–264. [CrossRef] [Google Scholar]
  • H. Chen, Z. Tian and F. Xu, What are cost changes for produce implementing traceability systems in China? Evidence from enterprise A. Appl. Econ. 51 (2019) 687–697. [CrossRef] [Google Scholar]
  • C. CN, Two places have detected the new coronavirus in the outer packaging of imported seafood. https://baijiahao.baidu.com/s?id=1672329966417563915&wfr=spider&for=pc (2020). [Google Scholar]
  • A.J. Collart and E. Canales, How might broad adoption of blockchain-based traceability impact the U.S. fresh produce supply chain? Appl. Econ. Perspect. Policy 44 (2022) 219–236. [CrossRef] [Google Scholar]
  • C.B.B. Comunicación, De Alan Turing al “ciberpunk”: la historia de “blockchain”. https://www.bbva.com/es/historia-origen-blockchain-bitcoin/ (2017). [Google Scholar]
  • H.N. Dai, Z. Zheng and Y. Zhang, Blockchain for Internet of things: a survey. IEEE Int. Things J. 6 (2019) 8076–8094. [CrossRef] [Google Scholar]
  • N. Deepa, Q.V. Pham, D.C. Nguyen, S. Bhattacharya, B. Prabadevi, T.R. Gadekallu, P.K.R. Maddikunta, F. Fang and P.N. Pathirana, A survey on blockchain for big data: approaches, opportunities, and future directions. Future Gener. Comput. Syst. 131 (2022) 209–226. [CrossRef] [Google Scholar]
  • W. Du, S.L. Pan, D.E. Leidner and W. Ying, Affordances, experimentation and actualization of FinTech: a blockchain implementation study. J. Strategic Inf. Syst. 28 (2019) 50–65. [CrossRef] [Google Scholar]
  • N. Fu, X. Zhang and Z. Jia, Game analysis on government subsidy for agricultural enterprise’ IoT investment. IOP Conf. Ser. Mater. Sci. Eng. 688 (2019) 55040. [Google Scholar]
  • J.F. Galvez, J.C. Mejuto and J. Simal-Gandara, Future challenges on the use of blockchain for food traceability analysis. TrAC Trends Anal. Chem. 107 (2018) 222–232. [CrossRef] [Google Scholar]
  • B. Hou, L. Wu and X. Chen, Market simulation of traceable food in China based on conjoint-value analysis: a traceable case of pork. Int. Food Agribusiness Manage. Rev. 23 (2020) 735–746. [CrossRef] [Google Scholar]
  • Q. Hu, Q. Xu and B. Xu, Introducing of online channel and management strategy for green agri-food supply chain based on pick-your-own operations. Int. J. Environ. Res. Public Health 16 (2019) 1990. [CrossRef] [Google Scholar]
  • J. Hu, Y. Liu and D. Ma, Dynamic strategy of food supply chain considering greenness and traceable goodwill under technological innovation. Soft Sci. (2020) 1–10. [Google Scholar]
  • A. Imeri and D. Khadraoui, The security and traceability of shared information in the process of transportation of dangerous goods. Paper presented at the IFIP International Conference on New Technologies (2018). [Google Scholar]
  • S. Jangirala, A.K. Das and A.V. Vasilakos, Designing secure lightweight blockchain-enabled RFID-based authentication protocol for supply chains in 5G mobile edge computing environment. IEEE Trans. Ind. Inf. 16 (2019) 7081–7093. [Google Scholar]
  • L. Jiaxing, W. Jigang and J. Guiyuan, Blockchain-based public auditing for big data in cloud storage. Inf. Process. Manage. 57 (2020) 1–17. [Google Scholar]
  • S.S. Kamble, A. Gunasekaran and S.A. Gawankar, Achieving sustainable performance in a data-driven agriculture supply chain: a review for research and applications. Int. J. Prod. Econ. 219 (2020) 179–194. [CrossRef] [Google Scholar]
  • H.M. Kim and M. Laskowski, Toward an ontology-driven blockchain design for supply-chain provenance. Int. J. Intell. Syst. Accounting Finance Manage. 25 (2018) 18–27. [CrossRef] [Google Scholar]
  • W. Li and S. Zhao, Research on decision-making model of high-quality fresh agricultural products dual-channel supply chain considering the application of traceability system. Oper. Res. Manage. Sci. 28 (2019) 98–109. [Google Scholar]
  • P. Liu, Investment decision and coordination of green agri-food supply chain considering information service based on blockchain and big data. J. Cleaner Prod. 277 (2020) 123646. [CrossRef] [Google Scholar]
  • P. Liu and S. Wang, Logistics outsourcing of fresh enterprises considering fresh-keeping efforts based on evolutionary game analysis. IEEE Access 9 (2021) 25659–25670. [CrossRef] [Google Scholar]
  • P. Liu and S.P. Yi, A study on supply chain investment decision-making and coordination in the Big Data environment. Ann. Oper. Res. 270 (2018) 235–253. [CrossRef] [MathSciNet] [Google Scholar]
  • P. Liu and S.P. Yi, Investment decision-making and coordination of a three-stage supply chain considering data company in the big data era. Ann. Oper. Res. 78 (2018) 1–17. [Google Scholar]
  • R.A. Lopez, X. He and E. De Falcis, What drives China’s new agricultural subsidies? World Dev. 93 (2017) 279–292. [CrossRef] [Google Scholar]
  • C. Martin, Logistics & Supply Chain Management: Financial Times Prentice Hall, Harlow, England (1992). [Google Scholar]
  • A. McAfee, E. Brynjolfsson, T.H. Davenport, D.J. Patil and D. Barton, Big data: the management revolution. Harvard Bus. Rev. 90 (2012) 60–68. [Google Scholar]
  • B.K. Mohanta, S.S. Panda and D. Jena, An overview of smart contract and use cases in blockchain technology. Paper presented at the 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (2018). [Google Scholar]
  • B. Nelson and T. Olovsson, Security and privacy for big data: a systematic literature review. Paper presented at the IEEE International Conference on Big Data (2017). [Google Scholar]
  • D.C. Nguyen, P.N. Pathirana, M. Ding and A. Seneviratne, Blockchain for 5G and beyond networks: a state of the art survey. J. Network Comput. App. 166 (2020) 102693. [CrossRef] [Google Scholar]
  • D.C. Nguyen, P.N. Pathirana, M. Ding and A. Seneviratne, Integration of blockchain and cloud of things: architecture, applications and challenges. IEEE Commun. Surv. Tutorials 22 (2020) 2521–2549. [CrossRef] [Google Scholar]
  • P. Olsen and M. Borit, The components of a food traceability system. Trends Food Sci. Technol. 77 (2018) 143–149. [CrossRef] [Google Scholar]
  • L. Pawczuk, R. Massey and D. Schatsky, Breaking Blockchain Open: Deloitte’s 2018 Global Blockchain Survey. Accessed 2020. https://www2.deloitte.com/content/dam/Deloitte/cz/Documents/financial-services/cz-2018-deloitte-globalblockchain-survey.pdf:Deloitte (2018). [Google Scholar]
  • H. Peng and T. Pang, Optimal strategies for a three-level contract-farming supply chain with subsidy. Int. J. Prod. Econ. 216 (2019) 1–36. [Google Scholar]
  • J.C. Pérez-Mesa, L. Piedra-Muoz, E. Galdeano-Gómez and C. Giagnocavo, Management strategies and collaborative relationships for sustainability in the agrifood supply chain. Sustainability 13 (2021) 749. [CrossRef] [Google Scholar]
  • K. Rabah, Convergence of AI, IoT, big data and blockchain: a review. Lake Inst. J. 1 (2018) 1–18. [Google Scholar]
  • R. Rajagopal, A.K. Agariya and C. Rajendran, Predicting resilience in retailing using grey theory and moving probability based Markov models. J. Retail. Consumer Serv. 62 (2021) 102599. [CrossRef] [Google Scholar]
  • M.A. Rubio, G.M. Tarazona and L. Contreras, Big Data and Blockchain Basis for Operating a New Archetype of Supply Chain. Springer, Cham (2018). [Google Scholar]
  • M.K. Saggi and S. Jain, A survey towards an integration of big data analytics to big insights for value-creation. Inf. Process. Manage. 54 (2018) 758–790. [CrossRef] [Google Scholar]
  • K. Salah and M.A. Khan, IoT security: review, blockchain solutions, and open challenges. Future Gener. Comput. Syst. 82 (2018) 395–411. [CrossRef] [Google Scholar]
  • P. Sckokai and D. Moro, Modeling the reforms of the common agricultural policy for Arable crops under uncertainty. Soc. Sci. Electron. Publ. 88 (2010) 43–56. [Google Scholar]
  • Sohu, New coronavirus has been detected in the outer packaging of frozen seafood 20201217. https://www.sohu.com/a/413025856_100000405 (2020). [Google Scholar]
  • S. Stranieri, F. Riccardi, M. Meuwissen and C. Soregaroli, Exploring the impact of blockchain on the performance of agri-food supply chains. Food Control 119 (2021) 107495. [CrossRef] [Google Scholar]
  • B. Sundarakani, A. Ajaykumar and A. Gunasekaran, Big data driven supply chain design and applications for blockchain: an action research using case study approach. Omega 102 (2021) 102452. [CrossRef] [Google Scholar]
  • A.C. Tagarakis, L. Benos, D. Kateris, N. Tsotsolas and D. Bochtis, Bridging the gaps in traceability systems for fresh produce supply chains: overview and development of an integrated IoT-based system. Appl. Sci. 11 (2021) 7596. [CrossRef] [Google Scholar]
  • S.L. Taste, The world’s first blockchain farm-rice bags for good food, 2020/05/16. http://www.agrichains.cn/ (2020). [Google Scholar]
  • N. Tengfei, Y.U. Haisuo and D.U. Shaofu, Agriculture supply chain optimization based on supply and demand uncertainty with government subsidy policies. J. Univ. Sci. Technol. Chin. 47 (2017) 267–273. [Google Scholar]
  • F. Tian, An agri-food supply chain traceability system for China based on RFID & blockchain technology. Paper presented at the 2016 13th international conference on service systems and service management (ICSSSM). IEEE (2016). [Google Scholar]
  • K. Tian, X. Zhuang and B. Yu, The incentive and supervision mechanism of banks on third-party B2B platforms in online supply chain finance using big data. Mobile Inf. Syst. 2021 (2021) 1–16. [Google Scholar]
  • M.S.J. Tripoli, Emerging Opportunities for the Application of Blockchain in the Agri-food Industry: : FAO and ICTSD: Rome and Geneva. Licence: CC BY-NC-SA 3 (2018). [Google Scholar]
  • M. Ul Hassan, M.H. Rehmani and J. Chen, Privacy preservation in blockchain based IoT systems: integration issues, prospects, challenges, and future research directions. Comput. Syst. 97 (2019) 512–529. [Google Scholar]
  • D. Unal, M. Hammoudeh, M.A. Khan, A. Abuarqoub and R. Hamila, Integration of federated machine learning and blockchain for the provision of secure big data analytics for internet of things. Comput. Secur. 109 (2021) 102393. [CrossRef] [Google Scholar]
  • V.G. Venkatesh, K. Kang and B. Wang, System architecture for blockchain based transparency of supply chain social sustainability. Rob. Comput.-Integr. Manuf. 63 (2020) 101896. [CrossRef] [Google Scholar]
  • K. Wang, Design of agricultural product quality and safety big data fusion model based on blockchain technology. Paper presented at the International Conference on Advanced Hybrid Information Processing (2019). [Google Scholar]
  • C. Wang, M. Deng and J. Deng, Factor reallocation and structural transformation implications of grain subsidies in China. J. Asian Econ. 71 (2020) 101248. [CrossRef] [Google Scholar]
  • X.Y. Wu, Z.P. Fan and B.B. Cao, An analysis of strategies for adopting blockchain technology in the fresh product supply chain. Int. J. Prod. Res. (2021) 1–18. DOI: 10.1080/00207543.2021.1894497. [Google Scholar]
  • Y. Yang, Z. Cai and Y. Liu, Blockchain + Big Data: Break Through the Bottleneck and Open a New Era of Intelligence. China Machine Press, Beijing (2019). [Google Scholar]
  • F. Ye, Z. Cai, Y.U. Chen, Y. Li and G. Hou, Subsidize farmers or bioenergy producer? The design of a government subsidy program for a bioenergy supply chain. Nav. Res. Logistics 68 (2021) 1082–1097. [CrossRef] [Google Scholar]
  • F. Zhang, N.V.R. Masna, S. Bhunia, C. Chen and S. Mandal, Authentication and traceability of food products through the supply chain using NQR spectroscopy. Paper presented at the 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) (2017). [Google Scholar]
  • A. Zhang, R.Y. Zhong and M.E.A. Farooque, Blockchain-based life cycle assessment: an implementation framework and system architecture. Resour. Conserv. Recycling 152 (2020) 104512. [CrossRef] [Google Scholar]
  • R. Zhang, W. Ma and J. Liu, Impact of government subsidy on agricultural production and pollution: a game-theoretic approach. J. Cleaner Prod. 285 (2021) 124806. [CrossRef] [Google Scholar]
  • S. Zheng, D. Lambert, S. Wang and Z. Wang, Effects of agricultural subsidy policies on comparative advantage and production protection in China. Chin. Econ. 46 (2013) 20–37. [CrossRef] [Google Scholar]
  • Z. Zheng, S. Xie, H. Dai, X. Chen and H. Wang, An overview of blockchain technology: architecture, consensus, and future trends. Paper presented at the 6th IEEE International Congress on Big Data (2017). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.