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Abstract
The paper highlights the importance and validity of the research problem: the major consequence for logistics arising from China’s logistics market due to its effective short-term and long-term strategies and developing transportation wholesale. The presented viewpoint helps to clearly understand the international perspective of the vastly enlarging China’s supply chain market due to its strong links with logistics centres. In recent years, much scientific research and studies have been conducted in China and Europe regarding China’s transport evolution era, from the production stage to the physical distribution stage, involving multiple steps until loads are in customers’ hands. The article considers the optimisation problem of a supply chain with multiple periods and diverse means of transportation. The considered problem can be formulated as a dynamic multi-criteria decision-making problem, in which the criteria are minimising the total cost, minimising the carbon footprint, and minimising the average transporting time.References
Agrawal, R., Majumdar, A., Majumdar, K., Raut, R. D., & Narkhede, B. E. (2022). Attaining sustainable development goals (SDGs) through supply chain practices and business strategies: A systematic review with bibliometric and network analyses. Business Strategy and the Environment, 31(7), 3669-3687. https://doi.org/10.1002/bse.3057
Al-Enazi, A., Bicer, Y., Okonkwo, E. C., & Al-Ansari, T. (2022). Evaluating the utilisation of clean fuels in maritime applications: a techno economic supply chain optimization. Fuel, 322, 124195. https://doi.org/10.1016/j.fuel.2022.124195
Amjad, A., Abbass, K., Hussain, Y., Khan, S., & Sadiq, S. (2022). Effects of the green supply chain management practices on reperformance and sustainable development. Environmental Science and Pollution Research, 29, 66622-66639. https://doi.org/10.1007/s11356-022-19954-w
Anitha, K., Reddy, K. P., Krishnamoorthy, N., & Jaiswal, S. (2021). IoT’s in enabling the supply chain visibility and connectivity and optimization of performance. Materials Today Proceedings. https://doi.org/10.1016/j.matpr.2020.12.343
Autry, C., & Griffis, S. (2008). Supply chain capital: the impact of structural and relational linkages on firm execution and innovation. Journal of Business Logistics, 29(1), 157-173. https://doi.org/10.1002/j.2158-1592.2008.tb00073.x
Bansal, P., Gualandris, J., & Kim, N. (2020). Theorizing supply chains with qualitative big data and topic modeling. Journal of Supply Chain Management, 56(2), 7-18. https://doi.org/10.1111/jscm.12224
Bashar, S., Wang, D., & Rafiq, M. (2023). Adoption of green supply chain management in developing countries: role of consumer cooperation, eco-design, and green marketing. Environmental Science and Pollution Research, 30, 92594-92610. https://doi.org/10.1007/s11356-023-28881-3
Becattini, V., Gabrielli, P., Antonini, C., Campos, J., Acquilino, A., Sansavini, G., & Mazzotti, M. (2022). Carbon dioxide capture, transport and storage supply chains: optimal economic and environmental performance of infrastructure rollout. International Journal of Greenhouse Gas Control, 117, 103635. https://doi.org/10.1016/j.ijggc.2022.103635
Beske, P., Land, A., & Seuring, S. (2014). Sustainable supply chain management practices and dynamic capabilities in the food industry: a critical analysis of the literature. International Journal of Production Economics, 152, 131-143. https://doi.org/10.1016/j.ijpe.2013.12.026
Boskabadi, A., Mirmozafari, M., Yazdani, R., & Farahani, A. (2022). Design of a distribution network in a multi-product, multi-period green supply chain system under demand uncertainty. Sustainable Operations and Computers, 3, 226-237. http://dx.doi.org/10.1016/j.susoc.2022.01.005
Chen, M., & Du, W. (2022). Dynamic relationship network and international management of enterprise supply chain by particle swarm optimization algorithm under deep learning. Expert Systems, 41(5), e13081. https://doi.org/10.1111/exsy.13081
Choi, T.-M., Wen, X., Sun, X., & Chung, S.-H. (2019). The mean-variance approach for global supply chain risk analysis with air logistics in with block chain technology era. Transportation Research Part E: Logistics and Transportation Review, 127, 178-191. https://doi.org/10.1016/j.tre.2019.05.007
Cousins, P. D., Handfield, R. B., Lawson, B., & Petersen, K. J. (2006). Creating supply chain relational capital: the impact of formal and informal socialization processes. Journal of Operations Management, 24(6), 851-863. https://doi.org/10.1016/j.jom.2005.08.007
Coyle, J. J., Bardi, E. J., & Novack, R. A. (2000). Transportation. 5th Edition. Cincinnati: South-Western College Publishing.
Craig, R. C., & Easton, P. L. (2011). Sustainable supply chain management: evolution and future directions. International Journal of Physical Distribution & Logistics Management, 41(1), 46-62. https://doi.org/10.1108/09600031111101420
Craighead, Ch. W., Blackhurst, J., Rungtusanatham, M. J., & Handfield, R. B. (2007). The severity of supply chain disruptions: design characteristics and mitigations capabilities. Decision Sciences, 38(1), 131-156. https://doi.org/10.1111/j.1540-5915.2007.00151.x
Ding, Q., & Zhao, H. (2021). Study on e-commerce logistics cost control methods in the context of COVID-19 prevention and control. Soft Computing, 25, 11955-11963. https://doi.org/10.1007/s00500-021-05624-5
Fahimnia, B., Jabbarzadeh, A., & Sarkis, J. (2018). Greening versus resilience: A supply chain design perspective. Transportation Research Part E: Logistics and Transportation, 119, 129-148. https://doi.org/10.1016/j.tre.2018.09.005
Feng, Y., Lai, K. H., & Zhu, Q. (2022). Green supply chain innovation: emergence, adoption, and challenges. International Journal of Production Economics, 248, 108497. https://doi.org/10.1016/j.ijpe.2022.108497
Feser, E. J., & Bergman, E. M. (2000). National Industrial Cluster Analysis. Regional Studies, 34, 1-19. https://doi.org/10.1080/00343400050005844
Gao, J., Xiao, Z., Wei, H., & Zhou, G. (2020). Dual-channel green supply chain management with eco-label policy: a perspective of two types of green products. Computers & Industrial Engineering, 146, 106613. https://doi.org/10.1016/j.cie.2020.106613
Gezdur, A., & Bhattacharjya, J. (2017). Digitization in the Oil and Gas Indus try: Challenges and Opportunities in Information and Communication Technology. Proceedings of 18th IFIP WG 5.5 Working Conference on Virtual Enterprises, Vicenza, Italy, 97-103. https://doi.org/10.1007/978-3-319-65151-4_9
Ghadimi, P., Azadnia, A. H., Heavey, C., Dolgui, A., & Can, B. (2016). A review on the buyer–supplier dyad relationships in sustainable procurement context: past, present and future. International Journal of Production Research, 54(5), 1443-1462. https://doi.org/10.1080/00207543.2015.1079341
Ghorbanpour, A., & Azimi, Z. N. (2022). Application of green supply chain management in the oil industries: modeling and performance analysis. Materials Today Proceedings, 49(3), 542-553. https://doi.org/10.1016/j.matpr.2021.03.672
Govindan, K., Fattahi, M., & Keyvanshokooh, E. (2017). Supply chain network design under uncertainty: A comprehensive review and future research directions. European Journal of Operational Research, 263, 108-141. https://doi.org/10.1016/j.ejor.2017.04.009
Gupta, P., Mehlawat, M. K., Aggarwal, U., & Khan, A. Z. (2022). An optimization model for a sustainable and socially beneficial four-stage supply chain. Information Sciences, 594, 371-399. https://doi.org/10.1016/j.ins.2022.02.032
Hallikas, J., & Lintukangas, K. (2016). Purchasing and supply: An investigation of risk management performance. International Journal of Production Economics, 171, 487-494. https://doi.org/10.1016/j.ijpe.2015.09.013
Hasani, A., Mokhtari, H., & Fattahi, M. (2021). A multi-objective optimization approach for green and resilient supply chain network design: a real-life case study. Journal of Cleaner Production, 278, 123199. https://doi.org/10.1016/j.jclepro.2020.123199
Ivanov, D. (2018). Revealing interfaces of supply chain resilience and sustainability: a simulation study. International Journal of Production Research, 56(10), 3507-3523. https://doi.org/10.1080/00207543.2017.1343507
Kausar, A. M., Hasan, S. M., & Qureshi, S. M. (2023). Exploring the critical success factors of a resilient supply chain. Engineering Management in Production and Services, 15(1), 41-56. https://doi.org/10.2478/emj-2023-0004
Khan, M. T., Idrees, M. D., Rauf, M., Sami, A., Ansari, A., & Jamil, A. (2022). Green supply chain management practices’ impact on operational performance with the mediation of technological innovation. Sustainability, 14(6), 3362. https://doi.org/10.3390/su14063362
Korpela, J., Hallikas, T., & Dahlberg, T. (2017). Digital supply chain transformation toward blockchain integration. Proceedings of the 50th Hawaii International Conference on System Sciences, 4182-4191. https://doi.org/10.24251/HICSS.2017.506
Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29, 65-83. https://doi.org/10.1016/S0019-8501(99)00113-3
Lee, H., & Yang, H. M. (2003). Strategies for a global logistics and economic hub: Incheon International Airport. Journal of Air Transport Management, 9(2), 113-121. https://doi.org/10.1016/S0969-6997(02)00065-0
Li, S., Peng, G., & Xing, F. (2019). Barriers of embedding big data solutions in smart factories: insights from sap consultants. Industrial Management & Data Systems, 119(5), 1147-1164. https://doi.org/10.1108/imds-11-2018-0532
Liu, E. B., Peng, Y., Peng, S. B., Yu, B., & Chen, Q. K. (2022). Research on low carbon emission optimization operation technology of natural gas pipeline under multi-energy structure. Petroleum Science, 19(6), 3046-3058. https://doi.org/10.1016/j.petsci.2022.09.025
Lizbetin, J., Hlatka, M., & Bartuska, L. (2018). Issues Concerning Declared Energy Consumption and Greenhouse Gas Emissions of FAME Biofuels. Sustainability, 10(9), 3025. https://doi.org/10.3390/su10093025
Long, R., Ouyang, H., & Guo, H. (2020). Super-slack-based measuring data envelopment analysis on the spatial-temporal patterns of logistics ecological efficiency using global Malmquist Index model. Environmental Technology & Innovation, 18, 100770. https://doi.org/10.1016/j.eti.2020.100770
Majeed, M. U., Aslam, S., Murtaza, S. A., Attila, S., & Molnár, E. (2022). Green marketing approaches and their impact on green purchase intentions: mediating role of green brand image and consumer beliefs towards the environment. Sustainability, 14(18), 11703. https://doi.org/10.3390/su141811703
Mansour, M. A., Beithou, N., Alsqour, M., Tarawneh, S. A., Al Rababa’a, K., Al Saqoor, S., & Chodakowska, E. (2023). Hierarchical risk communication management framework for construction projects. Engineering Management in Production and Services, 15(4), 104-115. https://doi.org/10.2478/emj-2023-0031
Mehri Charvadeh, M., Pourmousa, S., Tajdini, A., Tamjidi, A., & Safdari, V. (2022). Presenting a management model for a multi-objective sustainable supply chain in the cellulosic industry and its implementation by the NSGA-II meta-heuristic algorithm. Discrete Dynamics in Nature and Society. https://doi.org/10.1155/2022/8794472
Nabeeh, M., Abdel-Basset, A., & Aboelfetouh, A. (2019). Neutrosophic Multi-Criteria Decision Making Approach for IoT-Based Enterprises. IEEE, 7, 59559-59574. https://doi.org/10.1109/ACCESS.2019.2908919
Nath, M. P., Priyadarshini, S. B. B., & Mishra, D. (2022). Supply chain management (SCM): Employing various big data and metaheuristic strategies. In S. Dehuri & Y.W. Chen (Eds.), Advances in Machine Learning for Big Data Analysis (pp. 145-165). Singapore: Springer. https://doi.org/10.1007/978-981-16-8930-7_6
Pavlov, A., Ivanov, D., Pavlov, D., & Slinko, A. (2019). Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics. Annals of Operation Research, 1-30. https://doi.org/10.1007/s10479-019-03182-6
Rasi, E. R. (2022). Optimization Bi objective for designing sustainable supply chain network economic based competition by cost management approach. Advances in Mathematical Finance and Applications, 7(2), 293-312. https://doi.org/10.22034/AMFA.2020.1881758.132
Rong, D., Zhao, Y., Han, C., Yang, M., & Liu, F. (2022). Research on dual channel supply chain decision making of new retailing enterprises considering service behavior in the era of big data. Journal of Global Information Management, 30(9), 1-16. https://doi.org/10.4018/jgim.291529
Sakib, S. (2021). Usage of data analytics in improving sourcing of supply chain inputs. Preprints, 2021100103. https://doi.org/10.20944/preprints202110.0103.v1
Sawik, T. (2011). Selection of supply portfolio under disruption risks. Omega, 39(2), 194-208. https://doi.org/10.1016/j.omega.2010.06.007
Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision Support Systems, 54(4), 1513-1520. https://doi.org/10.1016/j.dss.2012.05.053
Shahzad, A., Zhang, K., & Gherbi, A. (2020). Intuitive development to examine collaborative IoT supply chain system underlying privacy and security levels and perspective powering through proactive blockchain. Sensors, 20(13), 3760. https://doi.org/10.3390/s20133760
Sheng, X., Chen, L., Yuan, X., Tang, Y., Yuan, Q., Chen, R., Wang, Q., Ma, Q., Zuo, J., & Liu, H. (2023). Green supply chain management for a more sustainable manufacturing industry in China: a critical review. Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 25(2), 1151-1183. https://doi.org/10.1007/s10668-022-02109-9
Soleimani, H., Chhetri, P., Fathollahi-Fard, A. M., Mirzapour Al-e-Hashem, S. M. J., & Shahparvari, S. (2022). Sustainable closed-loop supply chain with energy efficiency: Lagrangian relaxation, reformulations and heuristics. Annals of Operations Research, 318(1), 531-556. https://doi.org/10.1007/s10479-022-04661-z
Stolze, H. J., Murfield, M. L. U., & Esper, T. L. (2015). The role of social mechanisms in demand and supply integration: an individual network perspective. Journal of Business Logistics, 36(1), 49-68. https://doi.org/10.1111/jbl.12069
Tang, C. S. (2006). Perspectives in supply chain management. International Journal of Production Economics, 103, 451-488. https://doi.org/10.1016/j.ijpe.2005.12.006
Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52, 639-657. https://doi.org/10.1287/mnsc.1060.0515
Tseng, M. L., Chang, C. H., Lin, C. W. R., Wu, K. J., Chen, Q., Xia, L., & Xue, B. (2020). Future trends and guidance for the triple bottom line and sustainability: a data driven bibliometric analysis. Environmental Science and Pollution Research, 27, 33543-33567. https://doi.org/10.1007/s11356-020-09284-0
Velasquez, M., & Hester, P. T. (2013). An Analysis of Multi-Criteria Decision Making Methods. International Journal of Operations Research, 10(2), 56-66. https://www.researchgate.net/publication/275960103_An_analysis_of_multi-criteria_decision_making_methods
Vincent, A. A., Segun, I. B., Loretta, N. N., & Abiola, A. (2021). Entrepreneurship, agricultural value-chain and exports in Nigeria. United International Journal for Research and Technology, 2(08), 1-8. https://uijrt.com/articles/v2/i8/UIJRTV2I80001.pdf
Wang, X., Chen, G., & Xu, S. (2022). Bi-objective green supply chain network design under disruption risk through an extended NSGA-II algorithm. Clean Logistics and Supply Chain, 3, 100025. https://doi.org/10.1016/j.clscn.2021.100025
Wichmann, B. K., & Kaufmann, L. (2016). Social network analysis in supply chain management research. International Journal of Physical Distribution & Logistics Management, 46(8), 740-762. https://doi.org/10.1108/IJPDLM-05-2015-0122
Xu, S., Zhang, X., Feng, L., & Yang, W. (2020). Disruption risks in supply chain management: a literature review based on bibliometric analysis. International Journal of Production Research, 58(11), 3508-3526. https://doi.org/10.1080/00207543.2020.1717011
Yang, S. (2022). Analysis for supply chain management: evidence from Toyota. BCP Business & Management, 34, 1204-1209. https://doi.org/10.54691/bcpbm.v34i.3160
Yu, Z., & Khan, S. A. R. (2022). Green supply chain network optimization under random and fuzzy environment. International Journal of Fuzzy Systems, 24(2), 1170-1181. https://doi.org/10.1007/s40815-020-00979-7
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