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Gelişmekte Olan Ülkelerde Dijital Lojistik Pazar Performansının Hibrit ÇKKV Yöntemleriyle İncelenmesi

Yıl 2023, Cilt: 8 Sayı: 2, 559 - 576, 30.12.2023

Hazal Ezgi Özbek Emre Kadir Özekenci

Öz

Bu çalışmanın amacı, gelişmekte olan ülkelerin dijital lojistik pazar performansını bütünleşik Çok Kriterli Karar Verme (ÇKKV) yöntemlerini kullanarak değerlendirmektir. Bu çalışmada kullanılan kriterler literatür taraması sonucu belirlenmiştir. Kriter ağırlıklarının hesaplanmasında LOPCOW yöntemi kullanılırken, alternatifler MAUT, TOPSIS, MARCOS ve CoCoSo gibi farklı ÇKKV yöntemlerine göre sıralanmıştı. Ayrıca, bu çalışmada Borda sayımı yöntemi kullanılarak alternatiflere ilişkin son sıralama elde edilmiştir. LOPCOW yönteminden elde edilen sonuçlar, geleceğe hazırlık (FR) ve yurt içi lojistik fırsatlarının (DLO) sırasıyla en önemli ve en az önemli kriterler olduğunu göstermiştir. MAUT, TOPSIS, MARCOS ve CoCoSo yöntemlerinden elde edilen sıralama sonuçları, Birleşik Arap Emirlikleri'nin (BAE) en yüksek dijital lojistik pazar performansına sahip olduğunu, onu Çin ve Katar'ın takip ettiğini göstermiştir. Bu çalışmanın, gelişmekte olan ülkelerdeki politika yapıcılar ve şirketlere dijital lojistik pazar performansı hakkında fikir sağlayacağı düşünülmektedir. Bu çalışmanın temel sınırlılığı, ülkelerin dijital lojistik pazar performansının AEMLI ve DCI raporlarından elde edilen verilere dayanarak değerlendirilmesidir. Gelecekteki araştırmalarda farklı kriterlerin kullanılması mümkün olabilir.

Anahtar Kelimeler

Lojistik pazar performans Dijitalleşme Gelişen pazarlar ÇKKV

Kaynakça

  • Aboul-Dahab, K., & Ibrahim, M. A. (2020). Investigating the efficiency of the logistics performance index (LPI) weighting system using the technique for order of preference by similarity to ideal solution (TOPSIS) method. International Journal of Science and Research, 9, 269-277. http://dx.doi.org/10.2139/ssrn.3815764
  • Adıgüzel Mercangöz, B., Yıldırım, B. F., & Kuzu Yıldırım, S. (2020). Time period based COPRAS-G method: application on the Logistics Performance Index. LogForum, 16(2), 239-250. http://doi.org/10.17270/J.LOG.2020.432
  • Agility. (2023). Agility Emerging Markets Logistics Index (AEMLI). Available at: https://www.agility.com/en/emerging-markets-logistics-index/ (07.08.2023)
  • Akyüz, G., & Aka, S. (2017). An Additive Approach With Multi-Criteria Decision Making Methods On Evaluation Of Supplier Performance. Journal Of Management & Economics Research, 15(2), 28-46. https://doi.org/10.11611/yead.277893
  • Bensassi, S., Márquez-Ramos, L., Martínez-Zarzoso, I., & Suárez-Burguet, C. (2015). Relationship between logistics infrastructure and trade: Evidence from Spanish regional exports. Transportation research part A: policy and practice, 72, 47-61. https://doi.org/10.1016/j.tra.2014.11.007
  • Borgogna, A., Sheikh, H., & Raad, M. (2022). Modernizing logistics through digitization. Available at: https://www.strategyand.pwc.com/m1/en/strategic-foresight/sector-strategies/transport-logistics management/modernizing-logistics.html (04.12.2023)
  • Bugarčić, F. Ž., Skvarciany, V., & Stanišić, N. (2020). Logistics performance index in international trade: Case of Central and Eastern European and Western Balkans countries. Business: Theory and Practice, 21(2), 452-459. http://dx.doi.org/10.3846/btp.2020.12802
  • Çakir, S., & Perçin, S. (2013). Çok kriterli karar verme teknikleriyle lojistik firmalarinda performans ölçümü/Performance measurement of logistics firms with multi-criteria decision making methods. Ege Akademik Bakis, 13(4), 449-459.
  • Calabrase, J. (2022). China’s digital inroads into the Middle East. Available at: https://www.eastasiaforum.org/2022/10/19/chinas-digital-inroads-into-the-middle-east/ (05.12.2023)
  • Chejarla, K. C., Vaidya, O. S., & Kumar, S. (2022). MCDM applications in logistics performance evaluation: A literature review. Journal of Multi‐Criteria Decision Analysis, 29(3-4), 274-297. https://doi.org/10.1002/mcda.1774
  • Chow, G., Heaver, T. D., & Henriksson, L. E. (1994). Logistics performance: definition and measurement. International journal of physical distribution & logistics management, 24(1), 17-28.
  • Dare, T. O., Aubyn, L. N. A., & Boumgard, T. (2019). Analyzing, evaluating and improving the logistics performance index (LPI) of a country's economy: Case study: Nigeria, Ghana and Morocco. Master of Science. Malmö: World Maritime University
  • Ecer, F., & Pamucar, D. (2022). A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690
  • García, L., Martí, L., Martín, J. C., & Puertas, R. (2015). A DEA-Logistic Performance Index. In European Transport Conference 2015Association for European Transport (AET). https://aetransport. org/past-etcpapers/conference-papers-2015.
  • Han, H., & Trimi, S. (2018). A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms. Expert systems with applications, 103, 133-145. https://doi.org/10.1016/j.eswa.2018.03.003
  • IMD. (2022). World Digital Competitiveness Index (DCI). Available at: https://www.imd.org/centers/wcc/world-competitiveness-center/rankings/world-digital-competitiveness-ranking/ (19.07.2023)
  • Isik, O., Aydin, Y., & Kosaroglu, S. M. (2020). The assessment of the logistics performance index of CEE countries with the new combination of SV and MABAC methods. LogForum, 16(4), 549-559. http://doi.org/10.17270/J.LOG.2020.504
  • Kara, K., & Yalçın, G. C. (2022). Digital Logistics Market Performance of Developing Countries. International Journal of Academic Accumulation, 5(5). http://dx.doi.org/10.53001/uluabd.2022.38
  • Kara, K., Bentyn, Z., & Yalçın, G. C. (2022). Determining the logistics market performance of developing countries by entropy and MABAC methods. LogForum, 18(4). https://doi.org/10.17270/j.log.2022.752
  • Keeney, R. L., & Raiffa, H. (1993). Decisions with multiple objectives: preferences and value trade-offs. Cambridge university press.
  • KnowESG. (2023). GUUD Singapore Rolls Out New Digital Logistics Platform ClickargoSG. Available at: https://www.knowesg.com/tech/guud-singapore-rolls-out-new-digital-logistics-platform-clickargosg-20012023 (10.10.2023).
  • Kovács, G., & Kot, S. (2016). New logistics and production trends as the effect of global economy changes. Polish Journal of Management Studies, 14(2), 115-126. http://dx.doi.org/10.17512/pjms.2016.14.2.11
  • Lagoudis, I., Madentzoglou, E. M., Theotokas, I. N., & Yip, T. L. (2019). Maritime cluster attractiveness index. Maritime business review, 4(2), 169-189. http://dx.doi.org/10.1108/MABR-11-2018-0044
  • Magli, D. (2023). Maersk, Microsoft sign digitalisation and decarbonisation partnership. Available at: https://www.porttechnology.org/news/maersk-microsoft-sign-digitalisation-and-decarbonisation-partnership/ (10.10.2023)
  • Martí, L., Martín, J. C., & Puertas, R. (2017). A DEA-logistics performance index. Journal of applied economics, 20(1), 169-192. http://dx.doi.org/10.1016/S1514-0326(17)30008-9
  • Mešić, A., Miškić, S., Stević, Ž., & Mastilo, Z. (2022). Hybrid MCDM solutions for evaluation of the logistics performance index of the Western Balkan countries. ECONOMICS-Innovative and Economics Research Journal, 10(1). http://dx.doi.org/10.2478/eoik-2022-0004
  • Miškić, S., Stević, Ž., Tadić, S., Alkhayyat, A., & Krstić, M. (2023). Assessment of the LPI of the EU countries using MCDM model with an emphasis on the importance of criteria. World Review of Intermodal Transportation Research, 11(3), 258-279. http://dx.doi.org/10.1504/WRITR.2023.10056767
  • Navickas, V., Sujeta, L., & Vojtovich, S. (2011). Logistics systems as a factor of country’s competitiveness. Ekonomika ir vadyba, (16), 231-237.
  • Özekenci E. K. (2023). Assessing The Logistics Market Performance of Developing Countries By SWARA-CRITIC Based CoCoSo Method. LogForum 19 (3),375-394. http://doi.org/10.17270/J.LOG.2023.857.
  • Rasool, F., Greco, M., Morales-Alonso, G., & Carrasco-Gallego, R. (2023). What is next? The effect of reverse logistics adoption on digitalization and inter-organizational collaboration. International Journal of Physical Distribution & Logistics Management. Vol. 53 No. 5/6 pp. 563-588. https://doi.org/10.1108/IJPDLM-06-2022-0173
  • Rezaei, J., van Roekel, W. S., & Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158-169. http://dx.doi.org/10.1016/j.tranpol.2018.05.007
  • Roszkowska, E. (2011). Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/University of Economics in Katowice, 6(1), 200-230.
  • Srisawat, P., Kronprasert, N., & Arunotayanun, K. (2017). Development of decision support system for evaluating spatial efficiency of regional transport logistics. Transportation research procedia, 25, 4832-4851. http://dx.doi.org/10.1016/j.trpro.2017.05.493
  • Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & industrial engineering, 140, 106231. http://dx.doi.org/10.1016/j.cie.2019.106231
  • Strategic Market Research. (2022). Digital logistics market by solution. Available at: https://www.strategicmarketresearch.com/market-report/digital-logistics-market (09.10.2023)
  • Surucu, E., & Sakar, G. D. (2018). Supply chain performance: Measuring the impact of supply chain orientation and brand equity. Journal of Management Marketing and Logistics, 5(1), 1-17. http://doi.org/10.17261/Pressacademia.2018.803
  • Uluskan, M., Akpolat, G., & Şimşek, D. (2022). Evaluation of The Performance of Private Universities witH AHP, COPRAS, SAW, TOPSIS and BORDA Count Methods. Journal of Industrial Engineering, 33(1), 22-61. https://doi.org/10.46465/endustrimuhendisligi.972512
  • Ulutaş, A., & Karaköy, Ç. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model. Economics and Business Review, 5(4), 49-69. http://dx.doi.org/10.18559/ebr.2019.4.3
  • Vukadin, M., & Jovičić, M. (2022) Method of Evaluation of Application of Public-Private Partnerships. Economics-Časopis Za Inovacijska I Ekonomska Istraživanja, 2(1).
  • Wang, M., Lin, S. J., & Lo, Y. C. (2010, December). The comparison between MAUT and PROMETHEE. In 2010 IEEE international conference on industrial engineering and engineering management (pp. 753-757). IEEE. https://doi.org/10.1109/IEEM.2010.5675608
  • Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458
  • Yildirim, B. F., & Adiguzel Mercangoz, B. (2020). Evaluating the logistics performance of OECD countries by using fuzzy AHP and ARAS-G. Eurasian Economic Review, 10(1), 27-45. http://dx.doi.org/10.1007/s40822-019-00131-3
  • Yu, M. M., & Rakshit, I. (2023). An alternative assessment approach to global logistics performance evaluation: Common weight H‐DEA approach. International Transactions in Operational Research. https://doi.org/10.1111/itor.13360

Investigation of Digital Logistics Market Performance in Developing Countries with Hybrid MCDM Methods

Yıl 2023, Cilt: 8 Sayı: 2, 559 - 576, 30.12.2023

Hazal Ezgi Özbek Emre Kadir Özekenci

Öz

The aim of this paper is to evaluate the digital logistics market performance of developing countries using integrated MCDM methods. For this investigation, the criteria were determined based on the previous research. While the LOPCOW method was used to determine the weights of the criteria, the alternatives were ranked based on various MCDM methods, namely MAUT, TOPSIS, MARCOS, and CoCoSo. Additionally, in this study, the final ranking was obtained by the Borda count method. Results from the LOPCOW method showed that future readiness (FR) and domestic logistics opportunities (DLO) were the most and least important criteria, respectively. According to results obtained by the MAUT, TOPSIS, MARCOS and CoCoSo methods showed that, the United Arab Emirates (UAE) has the highest digital logistics market performance, followed by China and Qatar. It is thought that this study will provide insight into digital logistics market performance for policy makers and companies in developing countries. The main limitations of this study that the digital logistics market performance of countries was evaluated based on the data from the AEMLI and DCI reports. In future investigations, it might be possible to use different criteria.

Anahtar Kelimeler

logistics market performance digitalization emerging markets MCDM

Kaynakça

  • Aboul-Dahab, K., & Ibrahim, M. A. (2020). Investigating the efficiency of the logistics performance index (LPI) weighting system using the technique for order of preference by similarity to ideal solution (TOPSIS) method. International Journal of Science and Research, 9, 269-277. http://dx.doi.org/10.2139/ssrn.3815764
  • Adıgüzel Mercangöz, B., Yıldırım, B. F., & Kuzu Yıldırım, S. (2020). Time period based COPRAS-G method: application on the Logistics Performance Index. LogForum, 16(2), 239-250. http://doi.org/10.17270/J.LOG.2020.432
  • Agility. (2023). Agility Emerging Markets Logistics Index (AEMLI). Available at: https://www.agility.com/en/emerging-markets-logistics-index/ (07.08.2023)
  • Akyüz, G., & Aka, S. (2017). An Additive Approach With Multi-Criteria Decision Making Methods On Evaluation Of Supplier Performance. Journal Of Management & Economics Research, 15(2), 28-46. https://doi.org/10.11611/yead.277893
  • Bensassi, S., Márquez-Ramos, L., Martínez-Zarzoso, I., & Suárez-Burguet, C. (2015). Relationship between logistics infrastructure and trade: Evidence from Spanish regional exports. Transportation research part A: policy and practice, 72, 47-61. https://doi.org/10.1016/j.tra.2014.11.007
  • Borgogna, A., Sheikh, H., & Raad, M. (2022). Modernizing logistics through digitization. Available at: https://www.strategyand.pwc.com/m1/en/strategic-foresight/sector-strategies/transport-logistics management/modernizing-logistics.html (04.12.2023)
  • Bugarčić, F. Ž., Skvarciany, V., & Stanišić, N. (2020). Logistics performance index in international trade: Case of Central and Eastern European and Western Balkans countries. Business: Theory and Practice, 21(2), 452-459. http://dx.doi.org/10.3846/btp.2020.12802
  • Çakir, S., & Perçin, S. (2013). Çok kriterli karar verme teknikleriyle lojistik firmalarinda performans ölçümü/Performance measurement of logistics firms with multi-criteria decision making methods. Ege Akademik Bakis, 13(4), 449-459.
  • Calabrase, J. (2022). China’s digital inroads into the Middle East. Available at: https://www.eastasiaforum.org/2022/10/19/chinas-digital-inroads-into-the-middle-east/ (05.12.2023)
  • Chejarla, K. C., Vaidya, O. S., & Kumar, S. (2022). MCDM applications in logistics performance evaluation: A literature review. Journal of Multi‐Criteria Decision Analysis, 29(3-4), 274-297. https://doi.org/10.1002/mcda.1774
  • Chow, G., Heaver, T. D., & Henriksson, L. E. (1994). Logistics performance: definition and measurement. International journal of physical distribution & logistics management, 24(1), 17-28.
  • Dare, T. O., Aubyn, L. N. A., & Boumgard, T. (2019). Analyzing, evaluating and improving the logistics performance index (LPI) of a country's economy: Case study: Nigeria, Ghana and Morocco. Master of Science. Malmö: World Maritime University
  • Ecer, F., & Pamucar, D. (2022). A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690
  • García, L., Martí, L., Martín, J. C., & Puertas, R. (2015). A DEA-Logistic Performance Index. In European Transport Conference 2015Association for European Transport (AET). https://aetransport. org/past-etcpapers/conference-papers-2015.
  • Han, H., & Trimi, S. (2018). A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms. Expert systems with applications, 103, 133-145. https://doi.org/10.1016/j.eswa.2018.03.003
  • IMD. (2022). World Digital Competitiveness Index (DCI). Available at: https://www.imd.org/centers/wcc/world-competitiveness-center/rankings/world-digital-competitiveness-ranking/ (19.07.2023)
  • Isik, O., Aydin, Y., & Kosaroglu, S. M. (2020). The assessment of the logistics performance index of CEE countries with the new combination of SV and MABAC methods. LogForum, 16(4), 549-559. http://doi.org/10.17270/J.LOG.2020.504
  • Kara, K., & Yalçın, G. C. (2022). Digital Logistics Market Performance of Developing Countries. International Journal of Academic Accumulation, 5(5). http://dx.doi.org/10.53001/uluabd.2022.38
  • Kara, K., Bentyn, Z., & Yalçın, G. C. (2022). Determining the logistics market performance of developing countries by entropy and MABAC methods. LogForum, 18(4). https://doi.org/10.17270/j.log.2022.752
  • Keeney, R. L., & Raiffa, H. (1993). Decisions with multiple objectives: preferences and value trade-offs. Cambridge university press.
  • KnowESG. (2023). GUUD Singapore Rolls Out New Digital Logistics Platform ClickargoSG. Available at: https://www.knowesg.com/tech/guud-singapore-rolls-out-new-digital-logistics-platform-clickargosg-20012023 (10.10.2023).
  • Kovács, G., & Kot, S. (2016). New logistics and production trends as the effect of global economy changes. Polish Journal of Management Studies, 14(2), 115-126. http://dx.doi.org/10.17512/pjms.2016.14.2.11
  • Lagoudis, I., Madentzoglou, E. M., Theotokas, I. N., & Yip, T. L. (2019). Maritime cluster attractiveness index. Maritime business review, 4(2), 169-189. http://dx.doi.org/10.1108/MABR-11-2018-0044
  • Magli, D. (2023). Maersk, Microsoft sign digitalisation and decarbonisation partnership. Available at: https://www.porttechnology.org/news/maersk-microsoft-sign-digitalisation-and-decarbonisation-partnership/ (10.10.2023)
  • Martí, L., Martín, J. C., & Puertas, R. (2017). A DEA-logistics performance index. Journal of applied economics, 20(1), 169-192. http://dx.doi.org/10.1016/S1514-0326(17)30008-9
  • Mešić, A., Miškić, S., Stević, Ž., & Mastilo, Z. (2022). Hybrid MCDM solutions for evaluation of the logistics performance index of the Western Balkan countries. ECONOMICS-Innovative and Economics Research Journal, 10(1). http://dx.doi.org/10.2478/eoik-2022-0004
  • Miškić, S., Stević, Ž., Tadić, S., Alkhayyat, A., & Krstić, M. (2023). Assessment of the LPI of the EU countries using MCDM model with an emphasis on the importance of criteria. World Review of Intermodal Transportation Research, 11(3), 258-279. http://dx.doi.org/10.1504/WRITR.2023.10056767
  • Navickas, V., Sujeta, L., & Vojtovich, S. (2011). Logistics systems as a factor of country’s competitiveness. Ekonomika ir vadyba, (16), 231-237.
  • Özekenci E. K. (2023). Assessing The Logistics Market Performance of Developing Countries By SWARA-CRITIC Based CoCoSo Method. LogForum 19 (3),375-394. http://doi.org/10.17270/J.LOG.2023.857.
  • Rasool, F., Greco, M., Morales-Alonso, G., & Carrasco-Gallego, R. (2023). What is next? The effect of reverse logistics adoption on digitalization and inter-organizational collaboration. International Journal of Physical Distribution & Logistics Management. Vol. 53 No. 5/6 pp. 563-588. https://doi.org/10.1108/IJPDLM-06-2022-0173
  • Rezaei, J., van Roekel, W. S., & Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158-169. http://dx.doi.org/10.1016/j.tranpol.2018.05.007
  • Roszkowska, E. (2011). Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/University of Economics in Katowice, 6(1), 200-230.
  • Srisawat, P., Kronprasert, N., & Arunotayanun, K. (2017). Development of decision support system for evaluating spatial efficiency of regional transport logistics. Transportation research procedia, 25, 4832-4851. http://dx.doi.org/10.1016/j.trpro.2017.05.493
  • Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & industrial engineering, 140, 106231. http://dx.doi.org/10.1016/j.cie.2019.106231
  • Strategic Market Research. (2022). Digital logistics market by solution. Available at: https://www.strategicmarketresearch.com/market-report/digital-logistics-market (09.10.2023)
  • Surucu, E., & Sakar, G. D. (2018). Supply chain performance: Measuring the impact of supply chain orientation and brand equity. Journal of Management Marketing and Logistics, 5(1), 1-17. http://doi.org/10.17261/Pressacademia.2018.803
  • Uluskan, M., Akpolat, G., & Şimşek, D. (2022). Evaluation of The Performance of Private Universities witH AHP, COPRAS, SAW, TOPSIS and BORDA Count Methods. Journal of Industrial Engineering, 33(1), 22-61. https://doi.org/10.46465/endustrimuhendisligi.972512
  • Ulutaş, A., & Karaköy, Ç. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model. Economics and Business Review, 5(4), 49-69. http://dx.doi.org/10.18559/ebr.2019.4.3
  • Vukadin, M., & Jovičić, M. (2022) Method of Evaluation of Application of Public-Private Partnerships. Economics-Časopis Za Inovacijska I Ekonomska Istraživanja, 2(1).
  • Wang, M., Lin, S. J., & Lo, Y. C. (2010, December). The comparison between MAUT and PROMETHEE. In 2010 IEEE international conference on industrial engineering and engineering management (pp. 753-757). IEEE. https://doi.org/10.1109/IEEM.2010.5675608
  • Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458
  • Yildirim, B. F., & Adiguzel Mercangoz, B. (2020). Evaluating the logistics performance of OECD countries by using fuzzy AHP and ARAS-G. Eurasian Economic Review, 10(1), 27-45. http://dx.doi.org/10.1007/s40822-019-00131-3
  • Yu, M. M., & Rakshit, I. (2023). An alternative assessment approach to global logistics performance evaluation: Common weight H‐DEA approach. International Transactions in Operational Research. https://doi.org/10.1111/itor.13360
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Lojistik
Bölüm Araştırma Makalesi
Yazarlar

Hazal Ezgi Özbek 0000-0003-3259-6817

Emre Kadir Özekenci 0000-0001-6669-0006

Erken Görünüm Tarihi 23 Aralık 2023
Yayımlanma Tarihi 30 Aralık 2023
Gönderilme Tarihi 11 Ekim 2023
Kabul Tarihi 23 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 8 Sayı: 2

Kaynak Göster

APA Özbek, H. E., & Özekenci, E. K. (2023). Investigation of Digital Logistics Market Performance in Developing Countries with Hybrid MCDM Methods. JOEEP: Journal of Emerging Economies and Policy, 8(2), 559-576.
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