Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics

Dear Colleagues,

In the past, when globalization was still in its initial stages of development, market competition was less intense, rendering logistics operations much simpler and more primitive. The completion of activities with the lowest possible logistics costs or delivery time was emphasized as the primary goal (Ho et al., 2010). However, today logistics are faced with significantly more complex challenges that arise as a result of the efforts of the economy and society to fit into the requirements of the trend of modern logistics. On the one hand, there are increasingly strict requirements regarding the quality of logistics services, which arise as a result of accelerated globalization (Bykova et al., 2021), the growth of competition (Barker et al., 2021), and the development of e-commerce (Cao et al., 2021). These have helped to generate an increased volume of global commodity and transport flows. On the other hand, trends such as digitization (de Andres Gonzalez et al., 2021) and the application of Industry 4.0 and 5.0 technologies in logistics (Jafari et al., 2022), improvements to sustainability via the principles of the triple bottom line (economic, environmental and social sustainability) (Khan et al., 2022) and the circular economy (Mishra et al., 2022), the growth in resilience of supply chains in response to global challenges (wars and pandemics, such as COVID-19) (Mena et al., 2022 ), etc. contribute to the growing complexity of goods and transport flows. Solutions for the mentioned problems should be sought in the development and application of new technologies, the networking of technologies, and the design and deployment of new strategies, concepts, initiatives, measures, etc., for solving institutional, legal, organizational, and technological problems. In addition, efforts should be made for theeducation of all interest groups, i.e., participants in logistics chains who may participate in creating sustainable smart logistics solutions. Smart logistics refers to the use of advanced technologies such as AI, Internet of Things (IoT), and big data analytics to optimize and streamline supply chain and transportation processes. The goal of smart logistics is to increase efficiency, reduce costs, improve customer satisfaction, and enhance overall supply chain visibility and control. As a practice, involves real-time monitoring and control of supply chain operations, predictive analysis for optimizing routes and schedules, and automating many manual tasks for improved accuracy and speed.

Since these problems are complex and often include multiple alternatives, criteria and stakeholders, they could be solved only by applying different techniques and methods of operational research (OR). Among potential methods, the multi-criteria decision-making (MCDM) methods stand out. MCDM is one of the most important and fastest-growing sub-fields of OR. Accordingly, the aim of this SI is to define innovative solutions in the field of MCDM and outline their application in achieving sustainable smart logistics solutions. If successful, we will contribute to literature and practice by defining new MCDM methodologies and models for solving real-life problems of contemporary logistics. Although articles should deal primarily with expanding the body of literature, primarily in the area of logistics, submissions are also welcome in the areas of OR, MCDM, Industry 4.0, or any of the following topics:

• Application of existing and development of new MCDM methods for solving various problems in sustainable smart logistics.
• Development of hybrid MCDM models in the conventional environment or the environment of intuitionistic and interval sets, for solving various problems in sustainable smart logistics.
• Development of optimization models for various problems in sustainable smart logistics.
• Application of heuristics and metaheuristics for solving various problems in sustainable smart logistics.
• Applications of MCDM methods for sustainable transportation planning and routing.
• Integration of sustainability criteria into MCDM models for smart logistics.
• Analysis of the trade-off between economic efficiency and environmental sustainability in smart logistics. 
• Development of novel MCDM methods for sustainable smart logistics.
• Evaluating the impact of smart logistics on supply chain sustainability.
• Case studies of the implementation of MCDM methods in smart logistics.
• Comparison of different MCDM methods for sustainable smart logistics.
• The role of big data and machine learning in sustainable smart logistics decision making.
• Optimization of energy consumption in smart logistics using MCDM methods.
• Sustainable smart logistics in urban areas: challenges and opportunities.

Related papers:

1. Barker, J. M., Gibson, A. R., Hofer, A. R., Hofer, C., Moussaoui, I., & Scott, M. A. (2021). A competitive dynamics perspective on the diversification of third-party logistics providers’ service portfolios. Transportation Research Part E: Logistics and Transportation Review, 146, 102219.
2. Bykova, O. N., Repnikova, V. M., Starovoytov, V. G., Artamonova, K. A., Gavel, O. Y., & Sharonin, P. N. (2021). Formation of the logistics services market for small and medium-sized businesses in the context of globalization. Academy of Strategic Management Journal, 20(1), 1–10.
3. Cao, K., Xu, Y., Wu, Q., Wang, J., & Liu, C. (2021). Optimal channel and logistics service selection strategies in the e-commerce context. Electronic Commerce Research and Applications, 48, 101070.
4. de Andres Gonzalez, O., Koivisto, H., Mustonen, J. M., & Keinänen-Toivola, M. M. (2021). Digitalization in just-in-time approach as a sustainable solution for maritime logistics in the baltic sea region. Sustainability, 13(3), 1173.
5. Ho, W., Lee, C. K., & Ho, G. T. S. (2010). Multiple criteria optimization of contemporary logistics distribution network problems. OR insight, 23(1), 27–43.
6. Jafari, N., Azarian, M., & Yu, H. (2022). Moving from Industry 4.0 to Industry 5.0: What Are the Implications for Smart Logistics?. Logistics, 6(2), 26.
7. Khan, S. A. R., Yu, Z., & Farooq, K. (2022). Green capabilities, green purchasing, and triple bottom line performance: Leading toward environmental sustainability. Business Strategy and the Environment.
8. Mena, C., Karatzas, A., & Hansen, C. (2022). International trade resilience and the Covid-19 pandemic. Journal of Business Research, 138, 77–91.
9. Mishra, A., Dutta, P., Jayasankar, S., Jain, P., & Mathiyazhagan, K. (2022). A review of reverse logistics and closed-loop supply chains in the perspective of circular economy. Benchmarking: An International Journal, (ahead-of-print).

Dr. Mladen Krstić
Dr. Željko Stević
Dr. Snežana Tadić
Guest Editors

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