Document Type : original-application paper

Authors

Department of Civil Engineering, Shomal University, Amol, Iran.

10.22105/dmor.2022.324651.1556

Abstract

Purpose: This study seeks to assess the significant effects of blockchain, as a new decentralized technology, in waste reduction and performance improvement of Freight Transportation Management Systems (FTMS).
Methodolog: The network analysis technique is used as one of the most valid multi-criteria decision-making models. We developed this model in four levels with four main criteria of performance wastes (including cost, time, trust and security and safety), and fourteen sub-criteria, considering the blockchain technologies in four areas of digital infrastructure, visibility, transparency, and smart contracts.
Findings: Findings indicate that each of these technologies, individually and collectively, has reduced the waste of road freight management systems. The digital infrastructure technology reduced time and cost waste by 46.44% and 53.56%, respectively. Visibility has reduced 23.99%, 22.30%, and 53.71% of the wastes of cost, time, and safety, respectively. The transparency technology has influenced time and trust and security by 22.63% and 77.37%, respectively, and smart contracts affected the two above waste categories by 88.81% and 11.19%, respectively. The most effective wastes were identified as transportation costs, control costs, transparency in providing information, control of product conditions, and driver monitoring.
Originality/Value: This study identified the most crucial road freight transport wastes and made it possible to determine priorities in various areas of blockchain technologies for future investment to improve the FTMS performance, and the findings of this study might be a starting point for future studies in this context.

Keywords

Main Subjects

[1] Taleshi, M. (2006). Examining and evaluating pricing methods in road transportation of goods and providing suitable solutions for it. (In Persian). https://ganj.irandoc.ac.ir/#/articles/7195d16f08cd8e3bc3ff659aa96df477
[2]  Hu, T. L., Sheu, J. B., & Huang, K. H. (2002). A reverse logistics cost minimization model for the treatment of hazardous wastes. Transportation research part E: logistics and transportation review, 38(6), 457–473.
[3]  List, G. F., Wood, B., Turnquist, M. A., Nozick, L. K., Jones, D. A., & Lawton, C. R. (2006). Logistics planning under uncertainty for disposition of radioactive wastes. Computers & operations research, 33(3), 701–723.
[4]  Tijan, E., Aksentijević, S., Ivanić, K., & Jardas, M. (2019). Blockchain technology implementation in logistics. Sustainability, 11(4), 1185. https://doi.org/10.3390/su11041185
[5]  Dasaklis, T. K., Casino, F., & Patsakis, C. (2020). Atraceability and auditing framework for electronic equipment reverse logistics based on blockchain: the case of mobile phones [presentation]. International conference on information, intelligence, systems and applications (IISA) (pp. 1–7). https://doi.org/10.1109/IISA50023.2020.9284394
[6]  Kouhizadeh, M., & Sarkis, J. (2018). Blockchain practices, potentials, and perspectives in greening supply chains. Sustainability, 10(10), 3652. https://doi.org/10.3390/su10103652
[7]  Wamba, S. F., & Queiroz, M. M. (2020). Blockchain in the operations and supply chain management: Benefits, challenges and future research opportunities. International journal of information management, 52, 102064. https://doi.org/10.1016/j.ijinfomgt.2019.102064
[8]  Chang, S. E., Chen, Y. C., & Lu, M. F. (2019). Supply chain re-engineering using blockchain technology: a case of smart contract based tracking process. Technological forecasting and social change, 144, 1–11.
[9]  Rodriguez Espindola, O., Chowdhury, S., Beltagui, A., & Albores, P. (2020). The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, artificial intelligence and 3D printing. International journal of production research, 58(15), 4610–4630.
[10] Wright, A., & De Filippi, P. (2015). Decentralized blockchain technology and the rise of lex cryptographia. https://ssrn.com/abstract=2580664
[11] Aghajani Mir, S. F., Rajabi Kafshgar, F. Z., & Arab, A. (2022). Identifying and prioritizing challenges of implementing blockchain technology in the supply chain: a Bayesian BWM group-based approach. Journal of decisions and operations research, 6(4), 464–483. (In Persian). https://doi.org/10.22105/dmor.2021.277066.1336
[12] Cai, Y., Choi, T. M., & Zhang, J. (2021). Platform supported supply chain operations in the blockchain era: supply contracting and moral hazards. Decision sciences, 52(4), 866–892.
[13] Bai, C. A., Cordeiro, J., & Sarkis, J. (2020). Blockchain technology: business, strategy, the environment, and sustainability. Business strategy and the environment, 29(1), 321–322.
[14]   Baumers, M., & Holweg, M. (2019). On the economics of additive manufacturing: experimental findings. Journal of operations management, 65(8), 794–809.
[15]  Myerson, P. (2012). Lean supply chain and logistics management. McGraw-Hill Education.
[16] Rahimi, A., & Hosseinzadeh Saljooghi, F. (2018). Multi-objective programming model for determining the efficiency and returns to scale in supply chain management of two-stage: a case study of resin companies in Iran. Journal of decisions and operations research, 2(3), 213–227. (In Persian) . DOI:10.22105/dmor.2018.57124
[17] Wijewickrama, M., Chileshe, N., Rameezdeen, R., & Ochoa, J. J. (2021). Information sharing in reverse logistics supply chain of demolition waste: a systematic literature review. Journal of cleaner production, 280, 124359. https://doi.org/10.1016/j.jclepro.2020.124359
[18] Rahiminezhad Galankashi, M., & Helmi, S. A. (2016). Assessment of hybrid Lean-Agile (Leagile) supply chain strategies. Journal of manufacturing technology management, 27(4), 470–482.
[19] Christopher, M. (2016). Logistics and supply chain management. FT Publishing International. https://books.google.com
[20] Ozalp, I., Suvaci, B., & Tonus, H. Z. (2010). A new approach in logistics management: Just IN Time-Logistics (JIT-L). International journal of business and management studies, 2(1), 37–45.
[21] Irani, Z., & Sharif, A. M. (2016). Sustainable food security futures: perspectives on food waste and information across the food supply chain. Journal of enterprise information management, 29(2), 171–178.
[22]  Raak, N., Symmank, C., Zahn, S., Aschemann-Witzel, J., & Rohm, H. (2017). Processing-and product-related causes for food waste and implications for the food supply chain. Waste management, 61, 461–472.
[23]  Carter, C. R., Rogers, D. S., & Choi, T. Y. (2015). Toward the theory of the supply chain. Journal of supply chain management, 51(2), 89–97.
[24]  Frohlich, M. T., & Westbrook, R. (2001). Arcs of integration: an international study of supply chain strategies. Journal of operations management, 19(2), 185–200.
[25]  Nakasumi, M. (2017). Information sharing for supply chain management based on block chain technology [presentation]. 2017 IEEE 19th conference on business informatics (CBI) (Vol. 1, pp. 140–149). https://doi.org/10.1109/CBI.2017.56
[26]  Casey, M. J., & Wong, P. (2017). Global supply chains are about to get better, thanks to blockchain. Harvard business review, 13, 1–6.
[27]  Mansfield-Devine, S. (2017). Beyond Bitcoin: using blockchain technology to provide assurance in the commercial world. Computer fraud & security, 2017(5), 14–18.
[28]  Roeck, D., Sternberg, H., & Hofmann, E. (2020). Distributed ledger technology in supply chains: a transaction cost perspective. International journal of production research, 58(7), 2124–2141.
[29] Michelman, P. (2017). Seeing beyond the blockchain hype. MIT sloan management review, 58(4), 17. https://search.proquest.com/openview
[30] Collomb, A., & Sok, K. (2016). Blockchain/distributed ledger technology (DLT): what impact on the financial sector? Digiworld economic journal, (103). https://www.academia.edu/download/50652048/DWEJ_103_COLLOMB_SOK.pdf
[31] Tian, F. (2016). An agri-food supply chain traceability system for china based on rfid & blockchain technology [presentation]. 2016 13th international conference on service systems and service management (ICSSSM) (pp. 64–82). https://core.ac.uk/download/pdf/154897065.pdf#page=66
[32] Francisco, K., & Swanson, D. (2018). The supply chain has no clothes: technology adoption of blockchain for supply chain transparency. Logistics, 2(1), 1-13. https://doi.org/10.3390/logistics2010002
[33] 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.
[34]  Wang, J., Wu, P., Wang, X., & Shou, W. (2017). The outlook of blockchain technology for construction engineering management. Frontiers of engineering management, 4(1), 67–75. DOI:10.15302/J-FEM-2017006
[35]  Bocek, T., Rodrigues, B. B., Strasser, T., & Stiller, B. (2017). Blockchains everywhere-a use-case of blockchains in the pharma supply-chain [presentation]. IEE symposium on integrated network and service management (IM) (pp. 772–777). https://doi.org/10.23919/INM.2017.7987376
[36]   Dolgui, A., & Ivanov, D. (2020). Exploring supply chain structural dynamics: new disruptive technologies and disruption risks. International journal of production economics, 229, 107886. https://doi.org/10.1016/j.ijpe.2020.107886
[37]   Omar, I. A., Jayaraman, R., Debe, M. S., Salah, K., Yaqoob, I., & Omar, M. (2021). Automating procurement contracts in the healthcare supply chain using blockchain smart contracts. IEEE access, 9, 37397–37409.
[38]   Aghaei, M. (2021). Identification and ranking technological capabilities in order to enhance resilience of the supply chain. Journal of innovation management and operational strategies, 2(3), 229–243. https://www.magiran.com/paper/2369545 LK
[39]  Tavakkoli-Moghaddam, R., Ghahremani-Nahr, J., Samadi Parviznejad, P., Nozari, H., & Najafi, E. (2022). Application of internet of things in the food supply chain: a literature review. Journal of applied research on industrial engineering, 9(4), 475–492.
[40] Junaid, M., Xue, Y., Syed, M. W., Li, J. Z., & Ziaullah, M. (2019). A neutrosophic ahp and topsis framework for supply chain risk assessment in automotive industry of Pakistan. Sustainability12(1), 154. https://www.mdpi.com/2071-1050/12/1/154
[41] Sadeghi Moghadam, M. R., Alibakhshi, R., & Khalili, E. (2015). An Assessment of Selected Mutual Funds in Iran Stock Market Using a Combined Method of TOPSIS, VIKOR and Similarity-Based Approach. Financial research journal, 17(2), 259–282.
[42] Nozari, H., & Ghahremani-Nahr, J. (2021). Provide a framework for implementing agile big data-based supply chain (case study: FMCG companies). Innovation management and operational strategies, 2(2), 128–136. (In Persian). https://www.journal-imos.ir/article_136140_c2e53be75b723e5873e1eb29805cdf22.pdf?lang=en
[43] Mardani, A., Jusoh, A., Nor, K., Khalifah, Z., Zakwan, N., & Valipour, A. (2015). Multiple criteria decision-making techniques and their applications--a review of the literature from 2000 to 2014. Economic research-ekonomska istraživanja, 28(1), 516–571.
[44]   Pohekar, S. D., & Ramachandran, M. (2004). Application of multi-criteria decision making to sustainable energy planning—A review. Renewable and sustainable energy reviews, 8(4), 365–381.
[45] Vaidya, O. S., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European journal of operational research, 169(1), 1–29.
[46]  Wang, N., Chen, X., Wu, G., Chang, Y. C., & Yao, S. (2018). A short-term based analysis on the critical low carbon technologies for the main energy-intensive industries in China. Journal of cleaner production, 171, 98–106.
[47]   Büyüközkan, G., & Güleryüz, S. (2016). An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. International journal of production economics, 182, 435–448. DOI:https://doi.org/10.1016/j.ijpe.2016.09.015
[48]   Chemweno, P., Pintelon, L., Van Horenbeek, A., & Muchiri, P. (2015). Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach. International journal of production economics, 170, 663–676.
[49]   Hallikainen, P., Kivijärvi, H., & Tuominen, M. (2009). Supporting the module sequencing decision in the ERP implementation process—An application of the ANP method. International journal of production economics, 119(2), 259–270.
[50]   Lam, J. S. L. (2015). Designing a sustainable maritime supply chain: A hybrid QFD--ANP approach. Transportation research part E: logistics and transportation review, 78, 70–81.
[51]   Zhu, L., Wu, Y., Gai, K., & Choo, K. K. R. (2019). Controllable and trustworthy blockchain-based cloud data management. Future generation computer systems, 91, 527–535.
[52]   Kusi-Sarpong, S., Gupta, H., & Sarkis, J. (2019). A supply chain sustainability innovation framework and evaluation methodology. International journal of production research, 57(7), 1990–2008.
[53]   Wong, W. P., Ignatius, J., & Soh, K. L. (2014). What is the leanness level of your organisation in lean transformation implementation? An integrated lean index using ANP approach. Production planning & control, 25(4), 273–287. https://doi.org/10.1080/09537287.2012.674308
[54]   Zaim, S., Sevkli, M., Camgöz-Akdaug, H., Demirel, O. F., Yayla, A. Y., & Delen, D. (2014). Use of ANP weighted crisp and fuzzy QFD for product development. Expert systems with applications, 41(9), 4464–4474.
[55]   Nilashi, M., Ahmadi, H., Ahani, A., Ravangard, R., & Bin Ibrahim, O. (2016). Determining the importance of hospital information system adoption factors using fuzzy analytic network process (ANP). Technological forecasting and social change, 111, 244–264.
[56]   Saaty, T. L., & Hu, G. (1998). Ranking by eigenvector versus other methods in the analytic hierarchy process. Applied mathematics letters, 11(4), 121–125.
[57]   Saaty, T. L. (2004). Decision making—the analytic hierarchy and network processes (AHP/ANP). Journal of systems science and systems engineering, 13, 1–35. https://doi.org/10.1007/s11518-006-0151-5
[58]   Mustajoki, J., & Hämäläinen, R. P. (2000). Web-HIPRE: Global decision support by value tree and AHP analysis. INFOR: information systems and operational research, 38(3), 208–220.
[59]   Mousavi Arab, S. A., Homayounfar, M., & Ajalli, M. (2022). Balanced performance evaluation of B2C online stores with using a hybrid fuzzy ANP and fuzzy WASPAS approach. Journal of decisions and operations research, 6(Special Issue), 1–14. http://dx.doi.org/10.22105/dmor.2021.287084.1403
[60]   Leung, L. C., Hui, Y. V, & Zheng, M. (2003). Analysis of compatibility between interdependent matrices in ANP. Journal of the operational research society, 54(7), 758–768.