Seaport logistics of perishable agricultural products: Assessing the effectiveness of a blockchain-based track and trace solution
DOI:
https://doi.org/10.66635/xanf6x73Keywords:
Blockchain technology, Sustainable entrepreneurship, Agri-logistics supply chain, small and medium enterprises (SMEs), Sustainable supply chain innovationAbstract
The increasing global demand for high-quality agricultural products, coupled with significant food wastage in supply chains, highlights the need for efficient and sustainable logistics systems. This study proposes a blockchain-based track and trace solution integrated with Internet of Things (IoT) and Global Positioning System (GPS) technologies to improve transparency, traceability, and quality management in seaport logistics for agricultural exports. The research adopts a conceptual and empirical approach by developing a blockchain architecture and evaluating its effectiveness through an analytical model and a numerical illustration involving the export of spinach from India to Singapore. The results demonstrate that the proposed blockchain-enabled system significantly reduces the risk of product deterioration by ensuring real-time monitoring of critical parameters such as temperature, time, and location. Beyond operational improvements, the study highlights the role of blockchain technology in promoting sustainable entrepreneurship by enabling innovative business models for Agri-logistics startups and enhancing the competitiveness of small and medium enterprises (SMEs) in international markets. The system contributes to sustainable supply chain practices by minimising food waste, improving resource efficiency, and ensuring transparency across stakeholders. The findings align with key Sustainable Development Goals (SDGs), including SDG 2, SDG 9, SDG 12, and SDG 8. The study offers practical implications for policymakers and industry stakeholders to support blockchain adoption in agricultural supply chains, particularly in the Asian context.
References
1.Arduino, G., Carrillo Murillo, D., & Parola, F. (2015). Refrigerated container versus bulk: evidence from the banana cold chain. Maritime Policy & Management, 42(3), 228-245.
2.Aung, M. M., & Chang, Y. S. (2014). Temperature management for the quality assurance of a perishable food supply chain. Food control, 40, 198-207.
3.Vairetti, C., González-Ramírez, R. G., Maldonado, S., Álvarez, C., & Voβ, S. (2019). Facilitating conditions for successful adoption of inter-organizational information systems in seaports. Transportation Research Part A: Policy and Practice, 130, 333-350.
4.Cheaitou, A., & Cariou, P. (2012). Liner shipping service optimisation with reefer containers capacity: An application to northern Europe–South America trade. Maritime Policy & Management, 39(6), 589-602.
5.Dulebenets, M. A., & Ozguven, E. E. (2017). Vessel scheduling in liner shipping: Modeling transport of perishable assets. International Journal of Production Economics, 184, 141-156.
6.Irannezhad, E. (2020). The architectural design requirements of a blockchain-based port community system. Logistics, 4(4), 30.
7.Filina-Dawidowicz, L., & Gajewska, T. (2018). Examination of importance and range of comprehensive service for refrigerated containers in seaports. International Journal of Applied Management Science, 10(1), 26-43.
8.Johnston, H. R., & Vitale, M. R. (1988). Creating competitive advantage with interorganizational information systems. MIS quarterly, 12(2), 153-165.
9.Haass, R., Dittmer, P., Veigt, M., & Lütjen, M. (2015). Reducing food losses and carbon emission by using autonomous control–A simulation study of the intelligent container. International Journal of Production Economics, 164, 400-408.
10.Jedermann, R., Nicometo, M., Uysal, I., & Lang, W. (2014). Reducing food losses by intelligent food logistics. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 372(2017), 20130302.
11.Jović, M., Tijan, E., Aksentijević, S., & Žgaljić, D. (2020). Disruptive innovations in electronic transportation management systems.
12.Ko, D., Kwak, Y., Choi, D., & Song, S. (2015). Design of cold chain application framework (CCAF) based on IOT and cloud. In 2015 8th International Conference on u-and e-Service, Science and Technology (UNESST) (pp. 11-13). IEEE.
13.Lakkakula, P., Bullock, D. W., & Wilson, W. W. (2022). Asymmetric information and blockchains in soybean commodity markets. Applied Economic Perspectives and Policy, 44(1), 273-298.
14.Makukha, K., & Gray, R. (2004). Logistics partnerships between shippers and logistics service providers: the relevance of strategy. International Journal of Logistics Research and Applications, 7(4), 361-377.
15.Platenius, H. (1939). Deterioration of fresh vegetables. Journal of Agricultural Research, 59, 41.
16.Rahmadika, S., Kweka, B. J., Latt, C. N. Z., & Rhee, K. H. (2018, November). A preliminary approach of blockchain technology in supply chain system. In 2018 IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 156-160). IEEE.
17.Salin, V., & Nayga Jr, R. M. (2003). A cold chain network for food exports to developing countries. International Journal of Physical Distribution & Logistics Management, 33(10), 918-933.
18.Tsiulin, S., Reinau, K. H., Hilmola, O. P., Goryaev, N., & Karam, A. (2020). Blockchain-based applications in shipping and port management: a literature review towards defining key conceptual frameworks. Review of International Business and Strategy, 30(2), 201-224.
19.Wang, S., & Meng, Q. (2012). Liner ship route schedule design with sea contingency time and port time uncertainty. Transportation Research Part B: Methodological, 46(5), 615-633.
20.Wang, Y., Han, J. H., & Beynon-Davies, P. (2019). Understanding blockchain technology for future supply chains: a systematic literature review and research agenda. Supply Chain Management: An International Journal, 24(1), 62-84.
21.Wang, S., & Qu, X. (2019). Blockchain applications in shipping, transportation, logistics, and supply chain. In Smart transportation systems 2019 (pp. 225-231). Singapore: Springer Singapore.
22.Wong, C. Y., & Karia, N. (2010). Explaining the competitive advantage of logistics service providers: A resource-based view approach. International Journal of production economics, 128(1), 51-67.
23.Humayun, M., Jhanjhi, N. Z., Hamid, B., & Ahmed, G. (2020). Emerging smart logistics and transportation using IoT and blockchain. IEEE Internet of Things Magazine, 3(2), 58-62.
24.Shahbazi, Z., & Byun, Y. C. (2020). A procedure for tracing supply chains for perishable food based on blockchain, machine learning and fuzzy logic. Electronics, 10(1), 41.
25.Yang, C., Lan, S., Zhao, Z., Zhang, M., Wu, W., & Huang, G. Q. (2022). Edge-cloud blockchain and IoE-enabled quality management platform for perishable supply chain logistics. IEEE Internet of Things Journal, 10(4), 3264-3275.
26.Rambhia, V., Mehta, R., Shah, R., Mehta, V., & Patel, D. (2021, December). Agrichain: A blockchain-based food supply chain management system. In International Conference on Blockchain (pp. 3-15). Cham: Springer International Publishing.
27.Hasan, H., AlHadhrami, E., AlDhaheri, A., Salah, K., & Jayaraman, R. (2019). Smart contract-based approach for efficient shipment management. Computers & industrial engineering, 136, 149-159.
28.IFCO Systems. (2020). Countries with the least and most food waste. IFCO Systems. Retrieved March 17, 2026, from https://www.ifco.com/countries-with-the-least-and-most-food-waste/



