Multi-Criteria Analysis Techniques to Assess the Efficiency of Using Blockchain in Logistics
Abstract
Introduction. In complex areas of supply chain management and logistics, there is a need to use innovative solutions to improve economic efficiency, which is particularly important in the context of evolving digital technologies. The solution to the supply chain management problem is based on the use of multicriteria analysis methods to assess the efficiency of implementing modern information technologies in purchase procedures, such as blockchain technology, on the flexibility of the supply chain.
Aim and tasks. The study aims to examine the effects of blockchain to the adaptability of supply chains, its transparency, and the trust levels among its participants.
Results. The developed multi-criteria analysis tool provides the ability to specify weighting coefficients individually for each of the evaluated criteria, making it possible to consider a particular company's priorities within the framework of the optimised process. A survey of experts who knew the subject area under study was conducted to obtain the data necessary for analysis. This can provide expert opinions to assess the feasibility of certain alternatives when making decisions. The assessment conducted by experts revealed three main effects of blockchain and smart contracts on business: increasing the reliability of stored information, increasing the integrity of stored information, and integrating various information flows into a single information system.
Conclusions. The developed multi-criteria analysis tool allows for the specification of weighting factors, or “preferences”, for each of the examined criteria. This feature allows for considering a company’s priorities within the context of the process being improved. Blockchain and smart contracts offer key benefits in streamlining logistics procedures, primarily by bolstering the trust and dependability of the data storage system by creating local copies of data for each participant in the chain and improving data quality by integrating data from various sources into a single blockchain platform. In addition, it increases data security and minimises the risk of falsification because of the impossibility of making unauthorised changes to the database (at the current stage of system development) and the high degree of information integrity ensured by its distributed storage.
Keywords:
multi-criteria analysis, supply chain, blockchain, logistics, management, purchase procedures.References
Azimov, D., & Petrova, M. (2022). Determination of the efficiency of implementing blockchain technology into the logistics systems. Business Management, 4, 52-67
Bai, С., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International Journal of Production Economics, 229, 1-15. https://doi.org/10.1016/j.ijpe.2020.107776
Cheung, W., Chiang, A.H., Sambamurthy, V., Setia, P. (2018). Lean vs. Agile supply chain: The effect of IT architectures on supply chain capabilities and performance. Editorial Introduction, 63–88. https://doi.org/10.17705/1pais.10103
Colin, M., Galindo, R., & Hernández, O. (2015). Information and Communication Technology as a Key Strategy for Efficient Supply Chain Management in Manufacturing SMEs. Procedia Computer Science, 55, 833–842.
Daneshvar, M., Razavi Hajiagha, S. H., Tupėnaitė, L., & Khoshkheslat, F. (2020). Effective factors of implementing efficient supply chain strategy on supply chain performance. Technological and Economic Development of Economy, 26(4), 947-969. https://doi.org/10.3846/tede.2020.12827
Gregory, R., Failing, L., Harstone, M., Long, G., McDaniels, T., & Ohlson, D. (2012). Structured decision making: a practical guide to environmental management choices. John Wiley & Sons.
Gu, M., Yang, L., & Huo, B. (2021). The impact of information technology usage on supply chain resilience and performance: An ambidexterous view. International Journal of Production Economics, 232(107956), 107956. https://doi.org/10.1016/j.ijpe.2020.107956
Hofmann, E., Strewe, U. M., & Bosia, N. (2017). Supply Chain Finance and Blockchain Technology: The case of reverse securitisation. Springer.
Huo, B. (2012). The impact of supply chain integration on company performance: an organizational capability perspective. Supply Chain Management: An International Journal, 17(6), 596–610. https://doi.org/10.1108/13598541211269210
Kamble, S.S., Gunasekaran, A., & Gawankar, S.A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications, International Journal of Production Economics, 219, 179-194. https://doi.org/10.1016/j.ijpe.2019.05.022
Kiker, G. A., Bridges, T. S., Varghese, A., Seager, T. P., & Linkov, I. (2005). Application of multicriteria decision analysis in environmental decision making. Integrated Environmental Assessment and Management, 1(2), 95–108. https://doi.org/10.1897/ieam_2004a-015.1
Kim, H., Park, S.-Y., & Joh, W.-I. (2019). A study on technology development performance and technology commercialization performance according to the technology development capability of SMEs focusing on a comparative analysis of technology business groups. Journal of Open Innovation Technology Market and Complexity, 5(3), 65. https://doi.org/10.3390/joitmc5030065
Korhonen, P. J., Silvennoinen, K., Wallenius, J., & Öörni, A. (2012). Can a linear value function explain choices? An experimental study. European Journal of Operational Research, 219(2), 360–367. https://doi.org/10.1016/j.ejor.2011.12.040
Korolchuk, M., Korolchuk, V., Myronets, S., Boltivets, S., Mostova, I., & Koval, V. (2021). Competitive Properties of Trading Companies Managers. Revista Geintec-Gestao Inovacao e Tecnologias, 11(2), 941-954.
Kouhizadeh, M., Saberi, S., & Sarkis, J. (2021). Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. International Journal of Production Economics, 231(107831), 107831. https://doi.org/10.1016/j.ijpe.2020.107831
Manupati, V. K., Schoenherr, T., Ramkumar, M., Wagner, S. M., Pabba, S. K., & Inder Raj Singh, R. (2020). A blockchain-based approach for a multi-echelon sustainable supply chain. International Journal of Production Research, 58(7), 2222–2241. https://doi.org/10.1080/00207543.2019.1683248
Meidute-Kavaliauskiene I, Yıldız B, Çiğdem Ş, & Činčikaitė R. (2021). An Integrated Impact of Blockchain on Supply Chain Applications. Logistics. Vol. 5(2):33. https://doi.org/10.3390/logistics5020033
Miglierina, E., Molho, E., Patrone, F., & Tijs, S. H. (2008). Axiomatic approach to approximate solutions in multiobjective optimization. Decisions in Economics and Finance, 31, 95-115.
Nykyforov, A., Sushchenko, O., Petrova, M., & Pohuda, N. (2021). Multi-Criteria Technologies for Managerial Decisions System Analysis. Access to science, business, innovation in digital economy, ACCESS Press, 2(2), 150-161. https://doi.org/10.46656/access.2021.2.2(3)
Oláh, J., Karmazin, G., Pető, K., & Popp, J. (2018). Information technology developments of logistics service providers in Hungary. International Journal of Logistics Research and Applications, 21(3), 332–344. https://doi.org/10.1080/13675567.2017.1393506
Petrova, M., Popova, P., Popov, V., Shishmanov, K., & Marinova, K. (2022). Digital ecosystem: Nature, types and opportunities for value creation. In Communications in Computer and Information Science (pp. 71–85). Springer International Publishing. https://doi.org/10.1007/978-3-031-14985-6_5
Pournader, M., Shi, Y., Seuring, S., & Koh, S. C. L. (2020). Blockchain applications in supply chains, transport and logistics: a systematic review of the literature. International Journal of Production Research, 58(7), 2063–2081. https://doi.org/10.1080/00207543.2019.1650976
Qulmatova, S., Karimov, B., & Azimov, D. (2022). Data analysis and forecasting in agricultural enterprises. In Proceedings of the 6th International Conference on Future Networks & Distributed Systems, ICFNDS '22, pp. 536-541. https://doi.org/10.1145/3584202.3584282
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261
Soltany, Z., Rostamzadeh, R., Skrickij, V. (2018). A model to evaluate supply chain technology implementation influence on organizational performance. Transport, 33(3), 779-792.
Tippayawong, K.Y., Patchanee, P., Sopadang, A., & Takao, E. (2010). Factors Affecting Efficient Supply Chain Operational Performance of High and Low Technology Companies in Thailand. Management Science and Engineering. 4(3), 24–33.
Wang, Z., Ye, F., & Tan, K. H. (2014). Effects of managerial ties and trust on supply chain information sharing and supplier opportunism. International Journal of Production Research, 52(23), 7046–7061. https://doi.org/10.1080/00207543.2014.932931
If the article is accepted for publication in the journal «Economics. Ecology. Socium» the author must sign an agreementon transfer of copyright. The agreement is sent to the postal (original) or e-mail address (scanned copy) of the journal editions.
