Evaluating logistics villages in Turkey using hybrid improved fuzzy SWARA (IMF SWARA) and fuzzy MABAC techniques
Abstract
Positioning in the right location for organizing logistics activities is a determinative factor in the aspect of costs, effectivity, productivity, and performance of these operations carried out by logistics firms. The proper logistics village selection is a crucial, complicated, and time-consuming process for decision-makers who have to make the right and optimal decision on this issue. Decision-makers need a methodological frame with a practical algorithm that can be implemented quickly to solve these decision-making problems. Within this scope, the current paper aims to present an evaluation tool, which provides more reasonable and reliable results for decision-makers to solve the logistics village selection problem that is very complicated and has uncertain conditions based on fuzzy approaches. In this study, we propose the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), a modified and extended version of the traditional fuzzy Step-Wise Weight Assessment Ratio Analysis (F-SWARA) to identify the criteria weights. Also, we suggest applying the fuzzy Multi-Attributive Border Approximation area Comparison (F-MABAC) technique to determine the preference ratings of the alternatives. This combination has many valuable contributions. For example, it proposes to use a more reliable and consistent evaluation scale based on fuzzy sets. Hence, decision-makers can perform more reliable and reasonable pairwise comparisons by considering this evaluation scale. Besides, it presents a multi-attribute evaluation system based on the identified criteria weights. From this perspective, the proposed model is implemented to evaluate eight different logistics village alternatives with respect to nine selection criteria. According to the analysis results, while A8 is the most appropriate option, C1 Gross National Product (GNP) is the most significant criterion. A comprehensive sensitivity analysis was performed to test the robustness and validation of the proposed model, and the results of the analysis approve the validity and applicability of the proposed model. As a result, the suggested integrated MCDM framework can be applied as a valuable and practical decision-making tool to develop new strategies and improve the logistics operations by decision-makers.
Keyword : logistics villages, Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), Multi-Attributive Border Approximation Area Comparison (MABAC), multiple criteria decision making (MCDM)
How to Cite
Hashemkhani Zolfani, S., Görçün, Ömer F., & Küçükönder, H. (2021). Evaluating logistics villages in Turkey using hybrid improved fuzzy SWARA (IMF SWARA) and fuzzy MABAC techniques. Technological and Economic Development of Economy, 27(6), 1582-1612. https://doi.org/10.3846/tede.2021.16004
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Akkaya, G., Turanoglu, B., & Oztas, S. (2015). An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert Systems with Applications, 42, 9565–9573. https://doi.org/10.1016/j.eswa.2015.07.061
Aksoy, O., & Ozyürük, B. (2015). The importance of freight villages: An implementation in TCDD. Applied Mathematical Modelling, 39(19), 6043–6049. https://doi.org/10.1016/j.apm.2015.01.034
Altuntaş, V. C., & Tuna, O. (2015). The prioritisation of service dimensions in logistics centres: a fuzzy quality function deployment methodology. International Journal of Logistics Research and Applications, 19, 1–22. https://doi.org/10.1080/13675567.2015.1008438
Arikan, F. (2012). Freight villages and an application [Master Thesis]. Bahçeşehir University, Istanbul.
Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2011). A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Mathematical and Computer Modelling, 53, 98109. https://doi.org/10.1016/j.mcm.2010.07.023
Biswas, T. K., & Das, M. C. (2019). Selection of commercially available electric vehicle using fuzzy AHP-MABAC. Journal of The Institution of Engineers (India): Series C, 100, 531–537. https://doi.org/10.1007/s40032-018-0481-3
Bobar, Z., Božanić, D., Djurić, K., & Pamučar, D. (2020). Ranking and assessment of the efficiency of social media using the fuzzy AHP-Z num-ber model – Fuzzy MABAC. Acta Polytechnica Hungarica, 17(3), 64. https://doi.org/10.12700/APH.17.3.2020.3.3
Boile, M., Theofanis, S., & Gilbert, P. (2010). Feasibility of Freight Villages in the NYMTC Region (pp. 11–15). The State University of New Jersey.
Bottero, M., Dalla Chiara, B., & Deflorio, F. (2013). Wireless sensor networks for traffic monitoring in a logistic centre. Transportation Research Part C: Emerging Technologies, 26, 99–124. https://doi.org/10.1016/j.trc.2012.06.008
Božanić, D., Tešić, D., & Kočić, J. (2019). Multi-criteria FUCOM – Fuzzy MABAC model for the selection of location for construction of sin-gle-span bailey bridge. Decision Making: Applications in Management and Engineering, 2(1), 132–146. https://doi.org/10.31181/dmame1901132b
Büyüközkan, G., Mukul, E., & Kongar, E. (2020). Health tourism strategy selection via SWOT analysis and integrated hesitant fuzzy linguistic AHP-MABAC approach. Socio-Economic Planning Sciences, 74, 100929. https://doi.org/10.1016/j.seps.2020.100929
Can, A. M. (2012). Selection the location of freight village in Samsun with Multi-Criteria Decision Making [Master Thesis]. Erciyes University, Kayseri.
Chen, K. H., Liao, C. N., & Wu, L. C. (2014). A selection model to logistic centers based on TOPSIS and MCGP methods: The case of airline industry. Journal of Applied Mathematics, 2014, 470128. https://doi.org/10.1155/2014/470128
Chen, Y., & Qu, L. (2006). Evaluating the selection of logistics centre location using fuzzy MCDM model based on entropy weight. In 6th World Congress on Intelligent Control and Automation (pp. 7128–7132), Dalian, China. IEEE. https://doi.org/10.1109/WCICA.2006.1714468
Cristea, M., & Cristea, C. (2016). A multi-criteria decision-making approach used for the selection of a logistics center location. Annals of the Uni-versity of Oradea, 24(15). https://doi.org/10.15660/AUOFMTE.2016-1.3202
Dablanc, L. (2007). Goods transport in large European cities: Difficult to organize, difficult to modernize. Transportation Research Part A: Policy and Practice, 41, 280–285. https://doi.org/10.1016/j.tra.2006.05.005
Demiroğlu, Ş., & Elener, A. (2014). Küresel lojistik köyleri ve Türkiye’de kurulması planlanan lojistik köy bölgelerinin ÇKKV yöntemleriyle belir-lenmesi. Dumlupınar University Journal of Social Sciences, 42, 189–202.
Ecer, F. (2020). Çok kriterli karar verme geçmişten günümüze kapsamlı bir yaklaşım. Seçkin Yayıncılık.
Ecer, F. A. (2021). A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies. Renew-able and Sustainable Energy Reviews, 143, 110916. https://doi.org/10.1016/j.rser.2021.110916
Elgu, M., & Elitaş, C. (2011). Yerel ulusal ve uluslararası taşıma ve ticaret açısından lojistik köy merkezlerinin seçiminde bir model önerisi. Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, Celal Bayar Üniversitesi Manisa, 9.
Erkayman, B., Gündoğar, E., Akkaya, G., & İpek, M. (2011). A fuzzy topsis approach for logistics center location selection. Journal of Business Case Studies, 7(3), 49–55. https://doi.org/10.19030/jbcs.v7i3.4263
Fagaraşan, M., & Cristea, C. (2015). Logistic center location: selection using multi-criteria decision making. In Proceedings of the Annual Sessions of Scientific Papers “IMT Oradea” (pp. 193–198).
Fouladgar, M. M., Yazdani, C. A., & Zavadskas, E. (2012). Risk evaluation of tunneling projects. Archives of Civil and Mechanical Engineering, 12, 1–12. https://doi.org/10.1016/j.acme.2012.03.008
Gong, J.‐W., Li, Q., Yin, L., & Liu, H.‐C. (2019). Undergraduate teaching audit and evaluation using an extended MABAC method under q‐rung orthopair fuzzy environment. International Journal of Intelligent Systems, 35(12), 1912–1933. https://doi.org/10.1002/int.22278
Goseiri, K., & Lessan, J. (2008). Location selection for logistic centers using a two-step Fuzzy-AHP and ELECTRE Method. In 9th Asia Pacific Industrial Engineering & Management Systems Conference, Bali, Indonesia.
Hamamcıoğglu, C., & Oguztimur, S. (2017). The comparison of basic transportation infrastructure and freight villages’ locations between Germany and Turkey. Journal of Traffic and Transportation Engineering, 5, 77–92. https://doi.org/10.17265/2328-2142/2017.02.003
Jokić, Ž., Božanić, D., & Pamučar, D. (2021). Selection of fire position of mortar units using LBWA and Fuzzy MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 4(1), 115–135. https://doi.org/10.31181/oresta20401156j
Kayikci, Y. (2010). A conceptual model for intermodal freight logistics centre location decisions. Procedia – Social and Behavioral Sciences, 2(3), 6297–6311. https://doi.org/10.1016/j.sbspro.2010.04.039
Kersuliene, V., Zavadskas, E., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11, 243–258. https://doi.org/10.3846/jbem.2010.12
Kumar, A., & Anbanandam, R. (2019). Development of social sustainability index for freight transportation system. Journal of Cleaner Produc-tion, 210, 77–92. https://doi.org/10.1016/j.jclepro.2018.10.353
Li, Y., Liu, X., & Chen, Y. (2011). Selection of logistics center location using axiomatic fuzzy set and TOPSIS methodology in logistics manage-ment. Expert Systems with Applications, 38, 7901–7908. https://doi.org/10.1016/j.eswa.2010.12.161
Liang, W., Zhao, G., Wu, H., & Dai, B. (2019). Risk assessment of rockburst via an extended MABAC method under fuzzy environment. Tunnel-ling and Underground Space Technology, 83, 533–544. https://doi.org/10.1016/j.tust.2018.09.037
Lipscomb, T., Long, S., & Grasman, S. (2011). Sustainability criteria for inland freight hub location evaluation. In Transportation Research Board Annual Meeting (Paper 11-1847).
Mardani, A., Zavadskas, E., Khalifah, Z., Zakuan, N., Jusoh, A., Nor, K., & Khoshnoudi, M. (2017). A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015. Renewable and Sustainable Energy Reviews, 71, 216–256. https://doi.org/10.1016/j.rser.2016.12.053
Mavi, R. K., Goh, M., & Zarbakhshnia, N. (2017). Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry. The International Journal of Advanced Manufacturing Technology, 91, 2401–2418. https://doi.org/10.1007/s00170-016-9880-x
Mihajlović, J., Rajković, P., Petrović, G., & Ćirić, D. (2019). The selection of the logistics distribution center location based on MCDM methodol-ogy in southern and eastern region in Serbia. Operational Research in Engineering Sciences: Theory and Applications, 2(2), 72–85. https://doi.org/10.31181/oresta190247m
Mokhtarian, P. A. (2004). Conceptual analysis of the transportation impacts of B2C E-commerce. Transportation, 31, 257–284. https://doi.org/10.1023/B:PORT.0000025428.64128.d3
Nedeljković, M., Puška, A., Doljanica, S., Virijević Jovanović, S., Brzaković, P., Stević, Ž., & Marinkovic, D. (2021). Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model. PLoS ONE, 16(2), e0246857. https://doi.org/10.1371/journal.pone.0246857
Nguyen, L., & Notteboom, T. (2017). Public-private partnership model selection for dry port development: An application to Vietnam. World Re-view of Intermodal Transportation Research, 6, 229–239. https://doi.org/10.1504/WRITR.2017.086208
Organisation for Economic Co-operation and Development. (2020). Report, connecting businesses and consumers during COVID-19: Trade in parcels. https://www.oecd.org/coronavirus
Önden, İ., Acar., A. Z., & Eldemir, F. (2018). Evaluation of the logistics center locations using a multi-criteria spatial approach. Transport, 33(2), 322–334. https://doi.org/10.3846/16484142.2016.1186113
Özceylan, E., Erbaş, M., Tolon, M., Kabak, M., & Durğut, T. (2016). Evaluation of freight villages: A GIS-based multi-criteria decision analysis. Computers in Industry, 76, 38–52. https://doi.org/10.1016/j.compind.2015.12.003
Ozdemir, S., Keskin, B., Eren, T., & Oüzcan, E. (2020). Tuürkiye’deki Lojistik Merkezleri Yatırım Önceliklerinin Değerlendirilmesinde (Çok Okçütlü Bir Karar Modeli Önerisi). Demiryolu Muühendisligi, 12, 83–94. https://doi.org/10.47072/demiryolu.722626
Pamucar, D., & Božanić, D. (2019). Selection of a location for the development of multimodal logistics center: Application of single-valued neu-trosophic MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 2, 55–71. https://doi.org/10.31181/oresta1902039p
Pamucar, D., & Cirovic, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approxi-mation area Comparison (MABAC). Expert Systems with Applications, 42, 3016–3028. https://doi.org/10.1016/j.eswa.2014.11.057
Pamucar, D. S., Tarle, S. P., & Parezanovic, T. (2018). New hybrid multi-criteria decision-making DEMATEL-MAIRCA model: sustainable selec-tion of a location for the development of multimodal logistics centre. Economic Research-Ekonomska Istraživanja, 31(1), 1641–1665. https://doi.org/10.1080/1331677X.2018.1506706
Peker, I., Bakib, B., Tanyas, & Ar, I. M. (2016). Logistics center site selection by ANP/BOCR analysis: A case study of Turkey. Journal of Intel-ligent & Fuzzy Systems, 30, 2383–2396. https://doi.org/10.3233/IFS-152007
Percin, S. (2018). Evaluating airline service quality using a combined fuzzy decision-making approach. Journal of Air Transport Management, 68, 48–60. https://doi.org/10.1016/j.jairtraman.2017.07.004
Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., & Pamucar, D. (2021). Application of interval fuzzy logic in selecting a sustainable supplier on the example of agricultural production. Symmetry, 13, 774. https://doi.org/10.3390/sym13050774
ReportLinker (n.d.). Logistics market – Global industry analysis, size, share, growth, trends, and forecast 2018–2026. https://www.reportlinker.com
Sengul, D., & Cagil, G. (2020). Bulanık SWARA ve bulanık Analitik Hiyerarşi Prosesi yöntemi ile iş degerlemesi. DUJE, 11(3), 965–976. https://doi.org/10.24012/dumf.715363
Stankovic, M., Stevic, Z., Das, D., Subotic, M., & Pamucar, D. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathemat-ics, 8, 1–17. https://doi.org/10.3390/math8030457
Sun, Y., Zhou, X., Jeyaraj, A., Shang, R.-A., & Hu, F. (2019). The impact of enterprise social media platforms on knowledge sharing: An af-fordance lens perspective. Journal of Enterprise Information Management, 32(2), 233–250. https://doi.org/10.1108/JEIM-10-2018-0232
Tanyaş, M., & Bamyacı, M. (2008). Organize Lojistik Bölgesi Yer Seçimi Problemi için Bir Çok Ölçütlü Karar Verme Modeli: AHP-SAW. In Mersin Sempozyumu, 19–22 Kasım 2009, Mersin.
Tsamboulas, D., & Kapros, S. (2003). Freight village evaluation under uncertainty with public and private financing. Transport Policy, 10, 141–156. https://doi.org/10.1016/S0967-070X(03)00002-7
Tomić, V., Marinković, D., & Marković, D. (2014). The selection of logistic centers location using multi-criteria comparison: Case Study of the Balkan Peninsula. Acta Polytechnica Hungarica, 11, 10.
Ulutaş, A., Karakuş, C. B., & Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and CoCoSo methods. Journal of Intel-ligent & Fuzzy Systems, 38(4), 4693–4709. https://doi.org/10.3233/JIFS-191400
Unnikrishnan, A., & Figliozzi, M. A. (2020). A Study of the impact of COVID-19 on home delivery purchases and expenditures (Working Paper). Civil and Environmental Engineering Faculty Publications.
Uyanık, C. (2016). An integrated DEMATEL-Intuitionistic Fuzzy TOPSIS methodology for logistics centers location selection [Master Thesis]. Marmara University.
Uysal, F., & Gülmez, M. (2014). Fuzzy graph theory and matrix approach application for the selection of logistics centre location in the Mediterra-nean region of Turkey. Verimlilik Dergisi, 1, 89–104.
Uysal, H. T., & Yavuz, K. (2014). Selection of logistics centre location via ELECTRE method: a case study in Turkey. International Journal of Business and Social Science, 5(9), 276–289.
Turskis, Z., Zavadskas, E., Antucheviciene, J., & Kosareva, N. (2015). A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. International Journal of Computers Communications & Control, 10(6), 113–123. https://doi.org/10.15837/ijccc.2015.6.2078
Vlachopoulou, M., Silleos, G., & Manthou, V. (2001). Geographic information systems in warehouse site selection decisions. International Jour-nal of Production Economics, 71(1–3), 205–212. https://doi.org/10.1016/S0925-5273(00)00119-5
Vrtagić, S., Softić, E., Subotić, M., Stević, Ž., Dordevic, M., & Ponjavic, M. (2021). Ranking road sections based on MCDM model: New im-proved fuzzy SWARA (IMF SWARA). Axioms, 10(2), 92. https://doi.org/10.3390/axioms10020092
Wang, S., & Liu, P. (2007). The evaluation study on location selection of logistics center based on fuzzy AHP and TOPSIS. In International Con-ference on Wireless Communications, Networking and Mobile Computing (pp. 3779–3782). IEEE. https://doi.org/10.1109/WICOM.2007.935
Yıldırım, Y., & Önder, E. (2014a). Evaluating potential freight villages in Istanbul using multi criteria decision making techniques. Journal of Lo-gistic Management, 3(1), 1–10.
Yıldırım, Y., & Önder, E. (2014b). VIKOR method for ranking logistic villages in Turkey. Journal of Management and Economic Research, 23, 293–314. https://doi.org/10.11611/JMER236
Żak, J., & Weglinski, S. (2014). The selection of the logistics center location based on MCDM/A methodology. Transportation Research Proce-dia, 3, 555–564. https://doi.org/10.1016/j.trpro.2014.10.034
Zalluhoğlu, A. E., Aracıoğlu, B., & Bozkurt, S. (2014). Lojistik Köy Kurulumunun Lojistik Hizmet Sağlayıcılar Açısından Değerlendirilmesi: İzmir Örneği. Ege Strategic Research Journal, 2, 81–103. https://doi.org/10.18354/esam.39733
Zarbakhshnia, N., Soleimani, H., & Ghaderi, H. (2018). Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed Fuzzy COPRAS in the presence of risk criteria. Applied Soft Computing, 65, 307–319. https://doi.org/10.1016/j.asoc.2018.01.023
Zhang, H., Wei, G., & Chen, X. (2021). CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection. Journal of Intelligent & Fuzzy Systems, 41(1), 1009–1019. https://doi.org/10.3233/JIFS-202954
Aksoy, O., & Ozyürük, B. (2015). The importance of freight villages: An implementation in TCDD. Applied Mathematical Modelling, 39(19), 6043–6049. https://doi.org/10.1016/j.apm.2015.01.034
Altuntaş, V. C., & Tuna, O. (2015). The prioritisation of service dimensions in logistics centres: a fuzzy quality function deployment methodology. International Journal of Logistics Research and Applications, 19, 1–22. https://doi.org/10.1080/13675567.2015.1008438
Arikan, F. (2012). Freight villages and an application [Master Thesis]. Bahçeşehir University, Istanbul.
Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2011). A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Mathematical and Computer Modelling, 53, 98109. https://doi.org/10.1016/j.mcm.2010.07.023
Biswas, T. K., & Das, M. C. (2019). Selection of commercially available electric vehicle using fuzzy AHP-MABAC. Journal of The Institution of Engineers (India): Series C, 100, 531–537. https://doi.org/10.1007/s40032-018-0481-3
Bobar, Z., Božanić, D., Djurić, K., & Pamučar, D. (2020). Ranking and assessment of the efficiency of social media using the fuzzy AHP-Z num-ber model – Fuzzy MABAC. Acta Polytechnica Hungarica, 17(3), 64. https://doi.org/10.12700/APH.17.3.2020.3.3
Boile, M., Theofanis, S., & Gilbert, P. (2010). Feasibility of Freight Villages in the NYMTC Region (pp. 11–15). The State University of New Jersey.
Bottero, M., Dalla Chiara, B., & Deflorio, F. (2013). Wireless sensor networks for traffic monitoring in a logistic centre. Transportation Research Part C: Emerging Technologies, 26, 99–124. https://doi.org/10.1016/j.trc.2012.06.008
Božanić, D., Tešić, D., & Kočić, J. (2019). Multi-criteria FUCOM – Fuzzy MABAC model for the selection of location for construction of sin-gle-span bailey bridge. Decision Making: Applications in Management and Engineering, 2(1), 132–146. https://doi.org/10.31181/dmame1901132b
Büyüközkan, G., Mukul, E., & Kongar, E. (2020). Health tourism strategy selection via SWOT analysis and integrated hesitant fuzzy linguistic AHP-MABAC approach. Socio-Economic Planning Sciences, 74, 100929. https://doi.org/10.1016/j.seps.2020.100929
Can, A. M. (2012). Selection the location of freight village in Samsun with Multi-Criteria Decision Making [Master Thesis]. Erciyes University, Kayseri.
Chen, K. H., Liao, C. N., & Wu, L. C. (2014). A selection model to logistic centers based on TOPSIS and MCGP methods: The case of airline industry. Journal of Applied Mathematics, 2014, 470128. https://doi.org/10.1155/2014/470128
Chen, Y., & Qu, L. (2006). Evaluating the selection of logistics centre location using fuzzy MCDM model based on entropy weight. In 6th World Congress on Intelligent Control and Automation (pp. 7128–7132), Dalian, China. IEEE. https://doi.org/10.1109/WCICA.2006.1714468
Cristea, M., & Cristea, C. (2016). A multi-criteria decision-making approach used for the selection of a logistics center location. Annals of the Uni-versity of Oradea, 24(15). https://doi.org/10.15660/AUOFMTE.2016-1.3202
Dablanc, L. (2007). Goods transport in large European cities: Difficult to organize, difficult to modernize. Transportation Research Part A: Policy and Practice, 41, 280–285. https://doi.org/10.1016/j.tra.2006.05.005
Demiroğlu, Ş., & Elener, A. (2014). Küresel lojistik köyleri ve Türkiye’de kurulması planlanan lojistik köy bölgelerinin ÇKKV yöntemleriyle belir-lenmesi. Dumlupınar University Journal of Social Sciences, 42, 189–202.
Ecer, F. (2020). Çok kriterli karar verme geçmişten günümüze kapsamlı bir yaklaşım. Seçkin Yayıncılık.
Ecer, F. A. (2021). A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies. Renew-able and Sustainable Energy Reviews, 143, 110916. https://doi.org/10.1016/j.rser.2021.110916
Elgu, M., & Elitaş, C. (2011). Yerel ulusal ve uluslararası taşıma ve ticaret açısından lojistik köy merkezlerinin seçiminde bir model önerisi. Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, Celal Bayar Üniversitesi Manisa, 9.
Erkayman, B., Gündoğar, E., Akkaya, G., & İpek, M. (2011). A fuzzy topsis approach for logistics center location selection. Journal of Business Case Studies, 7(3), 49–55. https://doi.org/10.19030/jbcs.v7i3.4263
Fagaraşan, M., & Cristea, C. (2015). Logistic center location: selection using multi-criteria decision making. In Proceedings of the Annual Sessions of Scientific Papers “IMT Oradea” (pp. 193–198).
Fouladgar, M. M., Yazdani, C. A., & Zavadskas, E. (2012). Risk evaluation of tunneling projects. Archives of Civil and Mechanical Engineering, 12, 1–12. https://doi.org/10.1016/j.acme.2012.03.008
Gong, J.‐W., Li, Q., Yin, L., & Liu, H.‐C. (2019). Undergraduate teaching audit and evaluation using an extended MABAC method under q‐rung orthopair fuzzy environment. International Journal of Intelligent Systems, 35(12), 1912–1933. https://doi.org/10.1002/int.22278
Goseiri, K., & Lessan, J. (2008). Location selection for logistic centers using a two-step Fuzzy-AHP and ELECTRE Method. In 9th Asia Pacific Industrial Engineering & Management Systems Conference, Bali, Indonesia.
Hamamcıoğglu, C., & Oguztimur, S. (2017). The comparison of basic transportation infrastructure and freight villages’ locations between Germany and Turkey. Journal of Traffic and Transportation Engineering, 5, 77–92. https://doi.org/10.17265/2328-2142/2017.02.003
Jokić, Ž., Božanić, D., & Pamučar, D. (2021). Selection of fire position of mortar units using LBWA and Fuzzy MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 4(1), 115–135. https://doi.org/10.31181/oresta20401156j
Kayikci, Y. (2010). A conceptual model for intermodal freight logistics centre location decisions. Procedia – Social and Behavioral Sciences, 2(3), 6297–6311. https://doi.org/10.1016/j.sbspro.2010.04.039
Kersuliene, V., Zavadskas, E., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11, 243–258. https://doi.org/10.3846/jbem.2010.12
Kumar, A., & Anbanandam, R. (2019). Development of social sustainability index for freight transportation system. Journal of Cleaner Produc-tion, 210, 77–92. https://doi.org/10.1016/j.jclepro.2018.10.353
Li, Y., Liu, X., & Chen, Y. (2011). Selection of logistics center location using axiomatic fuzzy set and TOPSIS methodology in logistics manage-ment. Expert Systems with Applications, 38, 7901–7908. https://doi.org/10.1016/j.eswa.2010.12.161
Liang, W., Zhao, G., Wu, H., & Dai, B. (2019). Risk assessment of rockburst via an extended MABAC method under fuzzy environment. Tunnel-ling and Underground Space Technology, 83, 533–544. https://doi.org/10.1016/j.tust.2018.09.037
Lipscomb, T., Long, S., & Grasman, S. (2011). Sustainability criteria for inland freight hub location evaluation. In Transportation Research Board Annual Meeting (Paper 11-1847).
Mardani, A., Zavadskas, E., Khalifah, Z., Zakuan, N., Jusoh, A., Nor, K., & Khoshnoudi, M. (2017). A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015. Renewable and Sustainable Energy Reviews, 71, 216–256. https://doi.org/10.1016/j.rser.2016.12.053
Mavi, R. K., Goh, M., & Zarbakhshnia, N. (2017). Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry. The International Journal of Advanced Manufacturing Technology, 91, 2401–2418. https://doi.org/10.1007/s00170-016-9880-x
Mihajlović, J., Rajković, P., Petrović, G., & Ćirić, D. (2019). The selection of the logistics distribution center location based on MCDM methodol-ogy in southern and eastern region in Serbia. Operational Research in Engineering Sciences: Theory and Applications, 2(2), 72–85. https://doi.org/10.31181/oresta190247m
Mokhtarian, P. A. (2004). Conceptual analysis of the transportation impacts of B2C E-commerce. Transportation, 31, 257–284. https://doi.org/10.1023/B:PORT.0000025428.64128.d3
Nedeljković, M., Puška, A., Doljanica, S., Virijević Jovanović, S., Brzaković, P., Stević, Ž., & Marinkovic, D. (2021). Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model. PLoS ONE, 16(2), e0246857. https://doi.org/10.1371/journal.pone.0246857
Nguyen, L., & Notteboom, T. (2017). Public-private partnership model selection for dry port development: An application to Vietnam. World Re-view of Intermodal Transportation Research, 6, 229–239. https://doi.org/10.1504/WRITR.2017.086208
Organisation for Economic Co-operation and Development. (2020). Report, connecting businesses and consumers during COVID-19: Trade in parcels. https://www.oecd.org/coronavirus
Önden, İ., Acar., A. Z., & Eldemir, F. (2018). Evaluation of the logistics center locations using a multi-criteria spatial approach. Transport, 33(2), 322–334. https://doi.org/10.3846/16484142.2016.1186113
Özceylan, E., Erbaş, M., Tolon, M., Kabak, M., & Durğut, T. (2016). Evaluation of freight villages: A GIS-based multi-criteria decision analysis. Computers in Industry, 76, 38–52. https://doi.org/10.1016/j.compind.2015.12.003
Ozdemir, S., Keskin, B., Eren, T., & Oüzcan, E. (2020). Tuürkiye’deki Lojistik Merkezleri Yatırım Önceliklerinin Değerlendirilmesinde (Çok Okçütlü Bir Karar Modeli Önerisi). Demiryolu Muühendisligi, 12, 83–94. https://doi.org/10.47072/demiryolu.722626
Pamucar, D., & Božanić, D. (2019). Selection of a location for the development of multimodal logistics center: Application of single-valued neu-trosophic MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 2, 55–71. https://doi.org/10.31181/oresta1902039p
Pamucar, D., & Cirovic, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approxi-mation area Comparison (MABAC). Expert Systems with Applications, 42, 3016–3028. https://doi.org/10.1016/j.eswa.2014.11.057
Pamucar, D. S., Tarle, S. P., & Parezanovic, T. (2018). New hybrid multi-criteria decision-making DEMATEL-MAIRCA model: sustainable selec-tion of a location for the development of multimodal logistics centre. Economic Research-Ekonomska Istraživanja, 31(1), 1641–1665. https://doi.org/10.1080/1331677X.2018.1506706
Peker, I., Bakib, B., Tanyas, & Ar, I. M. (2016). Logistics center site selection by ANP/BOCR analysis: A case study of Turkey. Journal of Intel-ligent & Fuzzy Systems, 30, 2383–2396. https://doi.org/10.3233/IFS-152007
Percin, S. (2018). Evaluating airline service quality using a combined fuzzy decision-making approach. Journal of Air Transport Management, 68, 48–60. https://doi.org/10.1016/j.jairtraman.2017.07.004
Puška, A., Nedeljković, M., Hashemkhani Zolfani, S., & Pamucar, D. (2021). Application of interval fuzzy logic in selecting a sustainable supplier on the example of agricultural production. Symmetry, 13, 774. https://doi.org/10.3390/sym13050774
ReportLinker (n.d.). Logistics market – Global industry analysis, size, share, growth, trends, and forecast 2018–2026. https://www.reportlinker.com
Sengul, D., & Cagil, G. (2020). Bulanık SWARA ve bulanık Analitik Hiyerarşi Prosesi yöntemi ile iş degerlemesi. DUJE, 11(3), 965–976. https://doi.org/10.24012/dumf.715363
Stankovic, M., Stevic, Z., Das, D., Subotic, M., & Pamucar, D. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathemat-ics, 8, 1–17. https://doi.org/10.3390/math8030457
Sun, Y., Zhou, X., Jeyaraj, A., Shang, R.-A., & Hu, F. (2019). The impact of enterprise social media platforms on knowledge sharing: An af-fordance lens perspective. Journal of Enterprise Information Management, 32(2), 233–250. https://doi.org/10.1108/JEIM-10-2018-0232
Tanyaş, M., & Bamyacı, M. (2008). Organize Lojistik Bölgesi Yer Seçimi Problemi için Bir Çok Ölçütlü Karar Verme Modeli: AHP-SAW. In Mersin Sempozyumu, 19–22 Kasım 2009, Mersin.
Tsamboulas, D., & Kapros, S. (2003). Freight village evaluation under uncertainty with public and private financing. Transport Policy, 10, 141–156. https://doi.org/10.1016/S0967-070X(03)00002-7
Tomić, V., Marinković, D., & Marković, D. (2014). The selection of logistic centers location using multi-criteria comparison: Case Study of the Balkan Peninsula. Acta Polytechnica Hungarica, 11, 10.
Ulutaş, A., Karakuş, C. B., & Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and CoCoSo methods. Journal of Intel-ligent & Fuzzy Systems, 38(4), 4693–4709. https://doi.org/10.3233/JIFS-191400
Unnikrishnan, A., & Figliozzi, M. A. (2020). A Study of the impact of COVID-19 on home delivery purchases and expenditures (Working Paper). Civil and Environmental Engineering Faculty Publications.
Uyanık, C. (2016). An integrated DEMATEL-Intuitionistic Fuzzy TOPSIS methodology for logistics centers location selection [Master Thesis]. Marmara University.
Uysal, F., & Gülmez, M. (2014). Fuzzy graph theory and matrix approach application for the selection of logistics centre location in the Mediterra-nean region of Turkey. Verimlilik Dergisi, 1, 89–104.
Uysal, H. T., & Yavuz, K. (2014). Selection of logistics centre location via ELECTRE method: a case study in Turkey. International Journal of Business and Social Science, 5(9), 276–289.
Turskis, Z., Zavadskas, E., Antucheviciene, J., & Kosareva, N. (2015). A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. International Journal of Computers Communications & Control, 10(6), 113–123. https://doi.org/10.15837/ijccc.2015.6.2078
Vlachopoulou, M., Silleos, G., & Manthou, V. (2001). Geographic information systems in warehouse site selection decisions. International Jour-nal of Production Economics, 71(1–3), 205–212. https://doi.org/10.1016/S0925-5273(00)00119-5
Vrtagić, S., Softić, E., Subotić, M., Stević, Ž., Dordevic, M., & Ponjavic, M. (2021). Ranking road sections based on MCDM model: New im-proved fuzzy SWARA (IMF SWARA). Axioms, 10(2), 92. https://doi.org/10.3390/axioms10020092
Wang, S., & Liu, P. (2007). The evaluation study on location selection of logistics center based on fuzzy AHP and TOPSIS. In International Con-ference on Wireless Communications, Networking and Mobile Computing (pp. 3779–3782). IEEE. https://doi.org/10.1109/WICOM.2007.935
Yıldırım, Y., & Önder, E. (2014a). Evaluating potential freight villages in Istanbul using multi criteria decision making techniques. Journal of Lo-gistic Management, 3(1), 1–10.
Yıldırım, Y., & Önder, E. (2014b). VIKOR method for ranking logistic villages in Turkey. Journal of Management and Economic Research, 23, 293–314. https://doi.org/10.11611/JMER236
Żak, J., & Weglinski, S. (2014). The selection of the logistics center location based on MCDM/A methodology. Transportation Research Proce-dia, 3, 555–564. https://doi.org/10.1016/j.trpro.2014.10.034
Zalluhoğlu, A. E., Aracıoğlu, B., & Bozkurt, S. (2014). Lojistik Köy Kurulumunun Lojistik Hizmet Sağlayıcılar Açısından Değerlendirilmesi: İzmir Örneği. Ege Strategic Research Journal, 2, 81–103. https://doi.org/10.18354/esam.39733
Zarbakhshnia, N., Soleimani, H., & Ghaderi, H. (2018). Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed Fuzzy COPRAS in the presence of risk criteria. Applied Soft Computing, 65, 307–319. https://doi.org/10.1016/j.asoc.2018.01.023
Zhang, H., Wei, G., & Chen, X. (2021). CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection. Journal of Intelligent & Fuzzy Systems, 41(1), 1009–1019. https://doi.org/10.3233/JIFS-202954