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ED-ELEC: A Robust Multi-Criteria Decision-Making Framework for Evaluating Sustainable Urban Delivery Systems | ||
| Industrial Management Journal | ||
| دوره 18، شماره 2، 2026، صفحه 34-73 اصل مقاله (1.3 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2026.405611.1008271 | ||
| نویسندگان | ||
| Morteza Daripour1؛ Ezzatollah Asgharizadeh* 2؛ Mohammadreza Taghizadeh-Yazdi2 | ||
| 1. PhD Candidate, Faculty of Industrial Management & Technology, College of Management, University of Tehran, Tehran, Iran. | ||
| 2Prof., Faculty of Industrial Management & Technology, College of Management, University of Tehran, Tehran, Iran. | ||
| چکیده | ||
| Objective: The rapid expansion of online food delivery platforms has intensified the need for sustainable and efficient logistics solutions. Evaluating delivery alternatives across economic, environmental, technical, and social dimensions requires robust multi-criteria decision-making (MCDM) tools capable of managing incomplete, uncertain, and conflicting expert judgments. This study develops and validates ED-ELEC, an enhanced MCDM framework that extends D-numbers theory and integrates it with the ELECTRE III outranking method to enable reliable and transparent decision-making under imperfect information. Methodology: A new integration function for D-numbers is introduced to convert incomplete expert evaluations into crisp values while retaining the effects of incompleteness and conflict. A two-stage validation was performed: first, an illustrative example compared the proposed integration function with existing ones and benchmarked the complete ED-ELEC framework against another hybrid method; second, the framework was applied to evaluate sustainable delivery systems involving gasoline motorcycles, electric motorcycles, and drones. Results: The proposed integration function achieved balanced sensitivity to uncertainty and better interpretability. ED-ELEC produced robust, transparent, and stable rankings, identifying electric motorcycles as the most sustainable option, followed by drones and gasoline motorcycles. Conclusion: The ED-ELEC framework effectively combines uncertainty modeling and outranking analysis, providing an adaptive decision-support tool for sustainability evaluation. It enables decision-makers to address incomplete data while improving ranking clarity and robustness in sustainable urban logistics planning. | ||
| کلیدواژهها | ||
| Multi-Criteria Decision-Making (MCDM)؛ D-numbers theory؛ ELECTRE III؛ sustainable logistics؛ online food delivery؛ incomplete information | ||
| مراجع | ||
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Aljohani, K., & Thompson, R. G. (2018). A Stakeholder-Based Evaluation of the Most Suitable and Sustainable Delivery Fleet for Freight Consolidation Policies in the Inner-City Area. Sustainability, 11(1), 124. https://doi.org/10.3390/su11010124
Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
Božanić, D., Pamučar, D., & Komazec, N. (2023). Applying D numbers in risk assessment process: General approach. Journal of Decision Analytics and Intelligent Computing, 3(1), 286–295. https://doi.org/10.31181/jdaic10025122023b
Cherry, C. R., Weinert, J. X., & Xinmiao, Y. (2009). Comparative environmental impacts of electric bikes in China. Transportation Research Part D: Transport and Environment, 14(5), 281–290. https://doi.org/10.1016/j.trd.2008.11.003
Corti, F., D’Alpaos, C., & Greco, L. (2024). Multicriteria evaluation of sustainability in last-mile logistics: a review. Valori e Valutazioni, 36(36), 125–147. https://doi.org/10.48264/VVSIEV-20243608
Das, S., Dutta, R., De, S., & De, S. (2024). Review of multi-criteria decision-making for sustainable decentralized hybrid energy systems. Renewable and Sustainable Energy Reviews, 202, 114676. https://doi.org/10.1016/j.rser.2024.114676
Dekker, R., Bloemhof, J., & Mallidis, I. (2012). Operations Research for green logistics – An overview of aspects, issues, contributions and challenges. European Journal of Operational Research, 219(3), 671–679. https://doi.org/10.1016/j.ejor.2011.11.010
Dempster, A. P. (1967). Upper and Lower Probabilities Induced by a Multivalued Mapping. The Annals of Mathematical Statistics, 38(2), 325–339. https://doi.org/10.1214/aoms/1177698950
Deng, X., & Jiang, W. (2019). A total uncertainty measure for D numbers based on belief intervals. International Journal of Intelligent Systems, 34(12), 3302–3316. https://doi.org/10.1002/int.22195
Deng, X., Hu, Y., Deng, Y., & Mahadevan, S. (2014). Environmental impact assessment based on D numbers. Expert Systems with Applications, 41(2), 635–643. https://doi.org/10.1016/j.eswa.2013.07.088
Deng, X., Hu, Y., Deng, Y., & Mahadevan, S. (2014). Supplier selection using AHP methodology extended by D numbers. Expert Systems with Applications, 41(1), 156–167. https://doi.org/10.1016/j.eswa.2013.07.018
Deng, X., Lu, X., Chan, F. T. S., Sadiq, R., Mahadevan, S., & Deng, Y. (2015). D-CFPR: D numbers extended consistent fuzzy preference relations. Knowledge-Based Systems, 73, 61–68. https://doi.org/10.1016/j.knosys.2014.09.007
Deng, Y. (2012). D numbers: theory and applications. Journal of Information and Computational Science, 9, 2421–2428.
Fernández, E., Figueira, J. R., Navarro, J., Solares, E., & Díaz, R. (2025). Integrating second-order effects in ELECTRE methods with an interval-based approach. Omega, 137, 103353. https://doi.org/10.1016/j.omega.2025.103353
Figueira, J. R., Greco, S., Roy, B., & Słowiński, R. (2013). An Overview of ELECTRE Methods and their Recent Extensions. Journal of Multi-Criteria Decision Analysis, 20(1–2), 61–85. https://doi.org/10.1002/mcda.1482
Figueira, J., Greco, S., & Ehrogott, M. (2005). Multiple Criteria Decision Analysis: State of the Art Surveys (Vol. 78). Springer New York. https://doi.org/10.1007/b100605
French, S. (2023). Reflections on 50 years of MCDM: Issues and future research needs. EURO Journal on Decision Processes, 11, 100030. https://doi.org/10.1016/j.ejdp.2023.100030
Garg, V., Niranjan, S., Prybutok, V., Pohlen, T., & Gligor, D. (2023). Drones in last-mile delivery: A systematic review on Efficiency, Accessibility, and Sustainability. Transportation Research Part D: Transport and Environment, 123(April), 103831. https://doi.org/10.1016/j.trd.2023.103831
Goodchild, A., & Toy, J. (2018). Delivery by drone: An evaluation of unmanned aerial vehicle technology in reducing CO 2 emissions in the delivery service industry. Transportation Research Part D: Transport and Environment, 61, 58–67. https://doi.org/10.1016/j.trd.2017.02.017
Govindan, K., Soleimani, H., & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 240(3), 603–626. https://doi.org/10.1016/j.ejor.2014.07.012
Hashemi, S. S., Hajiagha, S. H. R., Zavadskas, E. K., & Mahdiraji, H. A. (2016). Multicriteria group decision making with ELECTRE III method based on interval-valued intuitionistic fuzzy information. Applied Mathematical Modelling, 40(2), 1554–1564. https://doi.org/10.1016/j.apm.2015.08.011
Hollingsworth, J., Copeland, B., & Johnson, J. X. (2019). Are e-scooters polluters? The environmental impacts of shared dockless electric scooters. Environmental Research Letters, 14(8), 084031. https://doi.org/10.1088/1748-9326/ab2da8
Hou, H., & Zhao, C. (2021). A Novel Integration Method for D Numbers Based on Horizontal Comparison. Axioms, 10(4), 312. https://doi.org/10.3390/axioms10040312
Hou, H., & Zhao, C. (2022). A Novel D–SCRI–EDAS Method and Its Application to the Evaluation of an Online Live Course Platform. Systems, 10(5), 157. https://doi.org/10.3390/systems10050157
Kraus, L., & Proff, H. (2021). Sustainable Urban Transportation Criteria and Measurement—A Systematic Literature Review. Sustainability, 13(13), 7113. https://doi.org/10.3390/su13137113
Li, H. F., & Wang, J.J. (2007). An Improved Ranking Method for ELECTRE III. In Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing, 6659–6662. IEEE. https://doi.org/10.1109/WICOM.2007.1634
Liang, W., Rodríguez, R. M., Wang, Y.-M., Goh, M., & Ye, F. (2023). The extended ELECTRE III group decision making method based on regret theory under probabilistic interval-valued hesitant fuzzy environments. Expert Systems with Applications, 231, 120618. https://doi.org/10.1016/j.eswa.2023.120618
Liu, P., Zhu, B., & Wang, P. (2021). A weighting model based on best–worst method and its application for environmental performance evaluation. Applied Soft Computing, 103, 107168. https://doi.org/10.1016/j.asoc.2021.107168
Liu, S., & Lin, Y. (2011). Grey systems: Theory and applications (Vol. 68). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-16158-2
Lohmann, P. M., Gsottbauer, E., Farrington, J., Human, S., & Reisch, L. A. (2024). Choice architecture promotes sustainable choices in online food-delivery apps. PNAS Nexus, 3(10). https://doi.org/10.1093/pnasnexus/pgae422
Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126–4148. https://doi.org/10.1016/j.eswa.2015.01.003
Matsuyuki, M., Chotib, Nurhasana, R., Antokida, Y., Fitrinitia, I. S., Made Shellasih, N., & Rizky Ningtyas, F. (2024). Assessment of the sustainability of online food delivery from the perspective of CO2 emissions and transport intensity: A case study in Jakarta. Transportation Research Interdisciplinary Perspectives, 27, 101200. https://doi.org/10.1016/j.trip.2024.101200
Montazer, G. A., Saremi, H. Q., & Ramezani, M. (2009). Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection. Expert Systems with Applications, 36(8), 10837–10847. https://doi.org/10.1016/j.eswa.2009.01.019
Nur, F., Alrahahleh, A., Burch, R., Babski-Reeves, K., & Marufuzzaman, M. (2020). Last mile delivery drone selection and evaluation using the interval-valued inferential fuzzy TOPSIS. Journal of Computational Design and Engineering, 7(4), 397–411. https://doi.org/10.1093/jcde/qwaa033
Özaşkın, A., & Görener, A. (2023). An integrated multi-criteria decision-making approach for overcoming barriers to green supply chain management and prioritizing alternative solutions. Supply Chain Analytics, 3, 100027. https://doi.org/10.1016/j.sca.2023.100027
Qi, J., Hu, J., & Peng, Y. (2025). Interval D-preference-based VIKOR for multiple-criteria group design evaluation with imprecise and unreliable information. Advanced Engineering Informatics, 64, 103058. https://doi.org/10.1016/j.aei.2024.103058
Rodrigues, T. A., Patrikar, J., Oliveira, N. L., Matthews, H. S., Scherer, S., & Samaras, C. (2022). Drone flight data reveal energy and greenhouse gas emissions savings for very small package delivery. Patterns, 3(8), 100569. https://doi.org/10.1016/j.patter.2022.100569
Roy, B. (1991). The outranking approach and the foundations of ELECTRE methods. Theory and Decision, 31(1), 49–73. https://doi.org/10.1007/BF00134132
Saaty, R. W. (1987). The analytic hierarchy process-what it is and how it is used. In Mathematical Modelling, 9(3-5), 161-179. https://doi.org/10.1016/0270-0255(87)90473-8
Safaei Ghadikolaei, A., & Gholamrezatabar Divkolaei, Z. (2014). Determinants of framework for assessing the sustainability of food supply chains using fuzzy analytic network process (Case study: Selected meat production companies of Mazandaran). Industrial Management Journal, 6(3), 535-554. https://doi.org/10.22059/imj.2014.50704
Saha, A., Simic, V., Senapati, T., Dabic-Miletic, S., & Ala, A. (2023). A Dual Hesitant Fuzzy Sets-Based Methodology for Advantage Prioritization of Zero-Emission Last-Mile Delivery Solutions for Sustainable City Logistics. IEEE Transactions on Fuzzy Systems, 31(2), 407–420. https://doi.org/10.1109/TFUZZ.2022.3164053
Schmidt, S., & Saraceni, A. (2024). Consumer acceptance of drone-based technology for last mile delivery. Research in Transportation Economics, 103, 101404. https://doi.org/10.1016/j.retrec.2023.101404
Shafer, G. (1976). A Mathematical Theory of Evidence. Princeton University Press. https://doi.org/10.2307/j.ctv10vm1qb
Shekhovtsov, A., Kozlov, V., Nosov, V., & Sałabun, W. (2020). Efficiency of Methods for Determining the Relevance of Criteria in Sustainable Transport Problems: A Comparative Case Study. Sustainability, 12(19), 7915. https://doi.org/10.3390/su12197915
Sotoudeh-Anvari, A. (2024). A state-of-the-art review on D number (2012-2022): A scientometric analysis. Engineering Applications of Artificial Intelligence, 127, 107309. https://doi.org/10.1016/j.engappai.2023.107309
Stolaroff, J. K., Samaras, C., O’Neill, E. R., Lubers, A., Mitchell, A. S., & Ceperley, D. (2018). Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery. Nature Communications, 9(1), 409. https://doi.org/10.1038/s41467-017-02411-5
Wang, C.-N., Nguyen, N.-A.-T., Dang, T.-T., & Hsu, H.-P. (2021). Evaluating Sustainable Last-Mile Delivery (LMD) in B2C E-Commerce Using Two-Stage Fuzzy MCDM Approach: A Case Study from Vietnam. IEEE Access, 9, 146050–146067. https://doi.org/10.1109/ACCESS.2021.3121607
Wang, N., Liu, X., & Wei, D. (2018). A Modified D Numbers’ Integration for Multiple Attributes Decision Making. International Journal of Fuzzy Systems, 20(1), 104–115. https://doi.org/10.1007/s40815-017-0323-0
Weiss, M., Dekker, P., Moro, A., Scholz, H., & Patel, M. K. (2015). On the electrification of road transportation – A review of the environmental, economic, and social performance of electric two-wheelers. Transportation Research Part D: Transport and Environment, 41, 348–366. https://doi.org/10.1016/j.trd.2015.09.007
World Economic Forum, & Accenture. (2024, December). Transforming urban logistics: Sustainable and efficient last-mile delivery in cities [White paper]. World Economic Forum. https://reports.weforum.org/docs/WEF_Transforming_Urban_Logistics_2024.pdf
Yaftiyan, F., Saghafi, F., & Hosseinzadeh, M. (2025). Analyzing Key Variables in Recurrent Carbon Reduction Policies Using a Hybrid Approach: A Focus on Pharmaceutical Distributors in Iran. Industrial Management Journal, 17(2), 1-26. https://doi.org/10.22059/imj.2025.392285.1008233
Yusoff, B., Pratama, D., Kilicman, A., & Abdullah, L. (2023). Circular Intuitionistic Fuzzy ELECTRE III Model for Group Decision Analysis. Informatica, 881–908. https://doi.org/10.15388/23-INFOR536
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X | ||
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