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TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ

Year 2018, Volume: 23 Issue: 4, 127 - 140, 31.12.2018
https://doi.org/10.17482/uumfd.448596

Abstract

Her
geçen gün önemi artan küreselleşme süreciyle birlikte dünyada teknoloji,
ticaret ve iletişim alanlarında büyük gelişmeler görülmüştür. Bu gelişmeler,
şirketlerin birbirleriyle daha rahat iletişim kurması ve ticaret yapabilmesini
önemli ölçüde kolaylaştırmıştır. Şirketlerin birbirlerine bu derece
yakınlaşması, ürünlerin(malların) güvenli ve daha az maliyetli bir şekilde
transferi konusunu önemli bir hale getirmiştir. Herhangi bir ürünün ya da ham
maddenin ortaya çıktığı ilk noktadan, tüketiciye ulaştığı son noktaya kadar
olan tüm faaliyetlerle ilgilenen lojistik sektörü de bu bağlamda, dünyanın en
büyük sektörleri arasında kendine yer bulmuştur. Lojistik sektörünün bu denli
büyümesi de ortaya lojistik dostu şehirler kavramını ortaya çıkarmıştır. Bu
çalışmada ilk olarak, lojistik ve lojistik şehir kapsamı hakkında bilgiler
verilmiş, daha sonra literatürde yer alan dikkat çekici çalışmalar
özetlenmiştir. Çalışma kapsamında Türkiye’de yer alan lojistik dostu şehirleri
belirlemek amacıyla çok kriterli karar verme (ÇKKV) yöntemlerinden entropi
entegreli CODAS yöntemi kullanılmıştır. Bu amaç kapsamında şehirlerin, taşıma
ve depolama, işgücü, otoyollarına erişim, yol altyapısı, trenle
ulaşılabilirliği, su yoluyla ulaşılabilirliği, hava yoluyla ulaşılabilirliği
gibi özellikleri kriter olarak belirlenmiştir ve gerekli veriler toplanmıştır.
Daha sonra şehirler değerlendirilmiştir. Lojistik dostu şehirler belirlenerek,
yöneticilere yardımcı olabilecek bir kaynak hazırlanmıştır.

References

  • Adamski, A. (2011) Hierarchical integrated intelligent logistics system platform, Procedia Social and Behavioral Sciences, 27, 1004-1016. doi:10.1016/j.sbspro.2011.08.109
  • Ayyıldız, E. ve Murat, M.(2017) Türkiye’de Yer Alan Şehirlerin Eğitim Performanslarının Çok Kriterli Karar Verme Yöntemleri Kullanılarak Belirlenmesi, Kent Akademisi, 10(2), 255-267.
  • Bukova, B., Brumercikova, E. ve Kondek, P. (2016) The multi-criteria decision in the allocation of logistic centers in the Eu, Transport Means - Proceedings of the International Conference 2016-October, 784-788.
  • Chen, Y. ve Qu, L. (2006) Evaluating the selection of logistics centre location using fuzzy MCDM model based on entropy weight in Intelligent Control and Automation, 2006, WCICA 2006, The Sixth World Congress on 2, 7128-7132. Doi: 10.1109/WCICA.2006.1714468
  • Çalişkan, A., Kalkan, M. ve Ozturkoglu, Y. (2017) City logistics: Problems and recovery proposals, International Journal of Logistics Systems and Management, 26(2), 145-162. Doi: 10.1504/IJLSM.2017.081497
  • Ding, J. F. (2013) Applying an integrated fuzzy MCDM method to select hub location for global shipping carrier-based logistics service providers, WSEAS transactions on information science and applications, 10(2), 47-57.
  • Ding, J. F. ve Chou, C. (2013) An evaluation model of quantitative and qualitative fuzzy multi-criteria decision making approach for location selection of transshipment ports, Mathematical Problems in Engineering, 1-12. Doi: 10.1155/2013/783105
  • Erkan, B. (2014) Türkiye’de Lojistik Sektörü ve Rekabet Gücü, ASSAM Uluslararası Hakemli Dergi, 1(1), 44-65.
  • Gan, W.-H. ve Zhang, H. (2013) City logistics hierarchy of Jiangxi Province based on grey clustering model, International Asia Conference on Industrial Engineering and Management Innovation: Core Areas of Industrial Engineering, IEMI 2012 – Proceeding, 979-989. Doi: 10.1007/978-3-642-38445-5_102
  • Gergin R. E. ve Baki, B. (2015). Türkiye’deki Bölgelerin Lojistik Performanslarının Bütünleştirilmiş AHS ve TOPSIS Yöntemiyle Değerlendirilmesi, Business and Economics Research Journal, 6(4), 115-135.
  • Ghorabaee, M.K., Amiri, M., Zavadskas, E.K., Hooshmand, R., ve Antucheviyien, J. (2017) Fuzzy extension of the CODAS method for multi-criteria market segment evaluation, Journal of Business Economics and Management, 18(1), 1-19. Doi:10.3846/16111699.2016.1278559
  • Güneş, H. ve Esmer, S. (2016) Liman Merkezli Lojistik: Ege Bölgesi için Bir Değerlendirme, Journal of ETA Maritime Science, 4(4), 303-316. Doi: 10.5505/jems.2016.92400
  • Hwang, C.-L. ve Yoon, K. (2012) Multiple attribute decision making: methods and applications a state-of-the-art survey, Springer Science and Business Media, 186. Doi: 10.1007/978-3-642-48318-9_3
  • Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., ve Antucheviciene, J. (2016). A New Combinative Distance-Based Assessment (CODAS) Method For Multi-Crıteria Decision-Making. Economic Computation and Economic Cybernetics Studies and Research, 50(3), 25-44.
  • Kiba-Janiak, M. (2012) Application of AHP method in the field of city logistics, Congress Proceedings - CLC 2012: Carpathian Logistics Congress, 67-173.
  • Korkmaz, M. ve Tanyaş M. (2014) Viking Karma Taşımacılık Projesi ve Samsun İli Üzerindeki Etkileri, Gümüşhane Üniversitesi Sosyal Bilimler Elektronik Dergisi, 5(11), 135-155.
  • Li-li, Q. ve Yan, C. (2007) An interactive integrated MCDM based on FANN and application in the selection of logistic center location, In Management Science and Engineering, ICMSE 2007. International Conference on 162-167. Doi: 10.1109/ICMSE.2007.4421841
  • Liu, A., Shi, J. ve Ma, N. (2016) Research on the Site Selection of a Pivotal Logistics Center Based on Fuzzy Multiple Criteria Decision Making, ICCREM 2016: BIM Application and Offsite Construction - Proceedings of the 2016 International Conference on Construction and Real Estate Management, 455-462. Doi: 10.1061/9780784480274.054
  • Mathew, M., ve Sahu, S. (2018) Comparison of new multi-criteria decision making methods for material handling equipment selection, Management Science Letters, 8(3), 139-150. Doi: 10.5267/j.msl.2018.1.004
  • Ömürberk, N. ve Aksoy, E. (2016) Bir Petrol Şirketinin Çok Kriterli Karar Verme Teknikleri ile Performans Değerlendirmesi, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilim. Fakültesi Dergisi, 21(3), 723-756.
  • Peker, I., Baki, B., Tanyas, M. ve Murat Ar, I. (2016) Logistics center site selection by ANP/BOCR analysis: A case study of Turkey, Journal of Intelligent and Fuzzy Systems, 30(4), 2381-2396. Doi: 10.3233/IFS-152007
  • Ren, Y., Xing, T., ve Zhao, G. (2010) Fuzzy decision analysis on logistics distribution centre location plan, Liaoning Gongcheng Jishu Daxue Xuebao (Ziran Kexue Ban)/Journal of Liaoning Technical University (Natural Science Edition), 29(3), 517-520.
  • Shannon, C. E. (1948) A mathematical theory of communication, bell, System Technical Journal 27, 379-423 ve 623–656, Math. Rev. MR10, 133e. Doi: 10.1002/j.1538-7305.1948.tb01338.x
  • Smirlis, Y. G., Zeimpekis, V. ve Kaimakamis, G. (2012) Data envelopment analysis models to support the selection of vehicle routing software for city logistics operations, Operational Research, 12(3), 399-420. Doi: 10.1007/s12351-010-0100-4
  • Suvacı, B. (2016). Sosyal Bilimler Veri Tabanında Yayımlanan Lojistik ve Tedarik Zinciri Makalelerinin Bibliyometrik Profili, Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(3), 263-281.
  • Tsai, J.-Y., Ding, J.-F., Liang, G.-S. ve Ye, K.-D. (2018) Use of a hybrid mcdm method to evaluate key solutions influencing service quality at a port logistics center in Taiwan, Brodogradnja, 69(1), 89-105. Doi: 10.21278/brod69106
  • Turskis, Z. ve Zavadskas, E. K. (2010) A new fuzzy additive ratio assessment method (ARAS‐F). Case study: The analysis of fuzzy multiple criteria in order to select the logistic centers location, Transport, 25(4), 423-432. Doi: 10.3846/transport.2010.52
  • URL1:http://www.musiad.org.tr/F/Root/Ara%C5%9Ft%C4%B1rma%20ve%20Yay%C4%B1nlar/Ara%C5%9Ft%C4%B1rma%20Raporlar%C4%B1/Ara%C5%9Ft%C4%B1rma%20Raporlar%C4%B1/lojistik_sektor_raporu_2015.pdf 19 Şubat 2018’de erişildi.
  • URL2: http://www.dhmi.gov.tr/havaalanlari.aspx 19 Şubat 2018’de erişildi.
  • URL3: http://www.udhb.gov.tr/i-1-istatistikler.html 19 Şubat 2018’de erişildi.
  • URL4: http://www.tuik.gov.tr/PreTablo.do?alt_id=1059 19 Şubat 2018’de erişildi.
  • URL5:http://www.transmedya.com/dosya-haber/turkiyenin-lojistik-analizi-sasirabilirsiniz-h9482.html 19 Şubat 2018’de erişildi.
  • Wang, T.C., ve Lee, H.D, (2009) Developing a fuzzy TOPSIS approach based on subjective weights and objective weights, Expert Syst. Appl., 36(5), 8980–8985. Doi: 10.1016/j.eswa.2008.11.035
  • Zhang, Y. ve Yang Z. (2018) A comprehensive analysis on logistics center location determination, CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation - Proceedings of the 17th COTA International Conference of Transportation Professionals 2018-January, 2463-2471.Doi: 10.1061/9780784480915.259

Determining the Logistics Friendly Cities in Turkey Using an Integrated Entropy-CODAS

Year 2018, Volume: 23 Issue: 4, 127 - 140, 31.12.2018
https://doi.org/10.17482/uumfd.448596

Abstract

With the rise of globalization, major developments in
technology, commerce and communication have been seen all over the world. These
developments have made the communication and trade of companies with each other
significantly easier. This closeness of companies to each other has increased
the importance of the issue of products (goods) transfer safely and less
costly. In this context, the logistics sector, which deals with all activities
from the first point of creation any raw materials or products to the last
point in which the products reached to consumers, has found place for itself
among the world’s largest sectors. Such a growth of the logistics industry has
also revealed the concept of logistics-friendly cities. In this study, firstly,
information related to logistics and logistics city is given, then remarkable
studies in the literature are summarized. In order to determine the
logistics-friendly cities in Turkey, the integrated CODAS entropy method which
is the multi-criteria decision making (MCDA) method is used. For this purpose,
the criteria such as capacities transportation and storage, labor forces,
access to motorways, railways, airways and waterways, road infrastructure were
determined and required data were collected. After that the cities were
evaluated. A resource has been created to help managers by identifying logistics-friendly
cities.

References

  • Adamski, A. (2011) Hierarchical integrated intelligent logistics system platform, Procedia Social and Behavioral Sciences, 27, 1004-1016. doi:10.1016/j.sbspro.2011.08.109
  • Ayyıldız, E. ve Murat, M.(2017) Türkiye’de Yer Alan Şehirlerin Eğitim Performanslarının Çok Kriterli Karar Verme Yöntemleri Kullanılarak Belirlenmesi, Kent Akademisi, 10(2), 255-267.
  • Bukova, B., Brumercikova, E. ve Kondek, P. (2016) The multi-criteria decision in the allocation of logistic centers in the Eu, Transport Means - Proceedings of the International Conference 2016-October, 784-788.
  • Chen, Y. ve Qu, L. (2006) Evaluating the selection of logistics centre location using fuzzy MCDM model based on entropy weight in Intelligent Control and Automation, 2006, WCICA 2006, The Sixth World Congress on 2, 7128-7132. Doi: 10.1109/WCICA.2006.1714468
  • Çalişkan, A., Kalkan, M. ve Ozturkoglu, Y. (2017) City logistics: Problems and recovery proposals, International Journal of Logistics Systems and Management, 26(2), 145-162. Doi: 10.1504/IJLSM.2017.081497
  • Ding, J. F. (2013) Applying an integrated fuzzy MCDM method to select hub location for global shipping carrier-based logistics service providers, WSEAS transactions on information science and applications, 10(2), 47-57.
  • Ding, J. F. ve Chou, C. (2013) An evaluation model of quantitative and qualitative fuzzy multi-criteria decision making approach for location selection of transshipment ports, Mathematical Problems in Engineering, 1-12. Doi: 10.1155/2013/783105
  • Erkan, B. (2014) Türkiye’de Lojistik Sektörü ve Rekabet Gücü, ASSAM Uluslararası Hakemli Dergi, 1(1), 44-65.
  • Gan, W.-H. ve Zhang, H. (2013) City logistics hierarchy of Jiangxi Province based on grey clustering model, International Asia Conference on Industrial Engineering and Management Innovation: Core Areas of Industrial Engineering, IEMI 2012 – Proceeding, 979-989. Doi: 10.1007/978-3-642-38445-5_102
  • Gergin R. E. ve Baki, B. (2015). Türkiye’deki Bölgelerin Lojistik Performanslarının Bütünleştirilmiş AHS ve TOPSIS Yöntemiyle Değerlendirilmesi, Business and Economics Research Journal, 6(4), 115-135.
  • Ghorabaee, M.K., Amiri, M., Zavadskas, E.K., Hooshmand, R., ve Antucheviyien, J. (2017) Fuzzy extension of the CODAS method for multi-criteria market segment evaluation, Journal of Business Economics and Management, 18(1), 1-19. Doi:10.3846/16111699.2016.1278559
  • Güneş, H. ve Esmer, S. (2016) Liman Merkezli Lojistik: Ege Bölgesi için Bir Değerlendirme, Journal of ETA Maritime Science, 4(4), 303-316. Doi: 10.5505/jems.2016.92400
  • Hwang, C.-L. ve Yoon, K. (2012) Multiple attribute decision making: methods and applications a state-of-the-art survey, Springer Science and Business Media, 186. Doi: 10.1007/978-3-642-48318-9_3
  • Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., ve Antucheviciene, J. (2016). A New Combinative Distance-Based Assessment (CODAS) Method For Multi-Crıteria Decision-Making. Economic Computation and Economic Cybernetics Studies and Research, 50(3), 25-44.
  • Kiba-Janiak, M. (2012) Application of AHP method in the field of city logistics, Congress Proceedings - CLC 2012: Carpathian Logistics Congress, 67-173.
  • Korkmaz, M. ve Tanyaş M. (2014) Viking Karma Taşımacılık Projesi ve Samsun İli Üzerindeki Etkileri, Gümüşhane Üniversitesi Sosyal Bilimler Elektronik Dergisi, 5(11), 135-155.
  • Li-li, Q. ve Yan, C. (2007) An interactive integrated MCDM based on FANN and application in the selection of logistic center location, In Management Science and Engineering, ICMSE 2007. International Conference on 162-167. Doi: 10.1109/ICMSE.2007.4421841
  • Liu, A., Shi, J. ve Ma, N. (2016) Research on the Site Selection of a Pivotal Logistics Center Based on Fuzzy Multiple Criteria Decision Making, ICCREM 2016: BIM Application and Offsite Construction - Proceedings of the 2016 International Conference on Construction and Real Estate Management, 455-462. Doi: 10.1061/9780784480274.054
  • Mathew, M., ve Sahu, S. (2018) Comparison of new multi-criteria decision making methods for material handling equipment selection, Management Science Letters, 8(3), 139-150. Doi: 10.5267/j.msl.2018.1.004
  • Ömürberk, N. ve Aksoy, E. (2016) Bir Petrol Şirketinin Çok Kriterli Karar Verme Teknikleri ile Performans Değerlendirmesi, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilim. Fakültesi Dergisi, 21(3), 723-756.
  • Peker, I., Baki, B., Tanyas, M. ve Murat Ar, I. (2016) Logistics center site selection by ANP/BOCR analysis: A case study of Turkey, Journal of Intelligent and Fuzzy Systems, 30(4), 2381-2396. Doi: 10.3233/IFS-152007
  • Ren, Y., Xing, T., ve Zhao, G. (2010) Fuzzy decision analysis on logistics distribution centre location plan, Liaoning Gongcheng Jishu Daxue Xuebao (Ziran Kexue Ban)/Journal of Liaoning Technical University (Natural Science Edition), 29(3), 517-520.
  • Shannon, C. E. (1948) A mathematical theory of communication, bell, System Technical Journal 27, 379-423 ve 623–656, Math. Rev. MR10, 133e. Doi: 10.1002/j.1538-7305.1948.tb01338.x
  • Smirlis, Y. G., Zeimpekis, V. ve Kaimakamis, G. (2012) Data envelopment analysis models to support the selection of vehicle routing software for city logistics operations, Operational Research, 12(3), 399-420. Doi: 10.1007/s12351-010-0100-4
  • Suvacı, B. (2016). Sosyal Bilimler Veri Tabanında Yayımlanan Lojistik ve Tedarik Zinciri Makalelerinin Bibliyometrik Profili, Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(3), 263-281.
  • Tsai, J.-Y., Ding, J.-F., Liang, G.-S. ve Ye, K.-D. (2018) Use of a hybrid mcdm method to evaluate key solutions influencing service quality at a port logistics center in Taiwan, Brodogradnja, 69(1), 89-105. Doi: 10.21278/brod69106
  • Turskis, Z. ve Zavadskas, E. K. (2010) A new fuzzy additive ratio assessment method (ARAS‐F). Case study: The analysis of fuzzy multiple criteria in order to select the logistic centers location, Transport, 25(4), 423-432. Doi: 10.3846/transport.2010.52
  • URL1:http://www.musiad.org.tr/F/Root/Ara%C5%9Ft%C4%B1rma%20ve%20Yay%C4%B1nlar/Ara%C5%9Ft%C4%B1rma%20Raporlar%C4%B1/Ara%C5%9Ft%C4%B1rma%20Raporlar%C4%B1/lojistik_sektor_raporu_2015.pdf 19 Şubat 2018’de erişildi.
  • URL2: http://www.dhmi.gov.tr/havaalanlari.aspx 19 Şubat 2018’de erişildi.
  • URL3: http://www.udhb.gov.tr/i-1-istatistikler.html 19 Şubat 2018’de erişildi.
  • URL4: http://www.tuik.gov.tr/PreTablo.do?alt_id=1059 19 Şubat 2018’de erişildi.
  • URL5:http://www.transmedya.com/dosya-haber/turkiyenin-lojistik-analizi-sasirabilirsiniz-h9482.html 19 Şubat 2018’de erişildi.
  • Wang, T.C., ve Lee, H.D, (2009) Developing a fuzzy TOPSIS approach based on subjective weights and objective weights, Expert Syst. Appl., 36(5), 8980–8985. Doi: 10.1016/j.eswa.2008.11.035
  • Zhang, Y. ve Yang Z. (2018) A comprehensive analysis on logistics center location determination, CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation - Proceedings of the 17th COTA International Conference of Transportation Professionals 2018-January, 2463-2471.Doi: 10.1061/9780784480915.259
There are 34 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Research Articles
Authors

Ertuğrul Ayyıldız

Selin Yalçın

Publication Date December 31, 2018
Submission Date July 27, 2018
Acceptance Date December 6, 2018
Published in Issue Year 2018 Volume: 23 Issue: 4

Cite

APA Ayyıldız, E., & Yalçın, S. (2018). TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, 23(4), 127-140. https://doi.org/10.17482/uumfd.448596
AMA Ayyıldız E, Yalçın S. TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ. UUJFE. December 2018;23(4):127-140. doi:10.17482/uumfd.448596
Chicago Ayyıldız, Ertuğrul, and Selin Yalçın. “TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 23, no. 4 (December 2018): 127-40. https://doi.org/10.17482/uumfd.448596.
EndNote Ayyıldız E, Yalçın S (December 1, 2018) TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 23 4 127–140.
IEEE E. Ayyıldız and S. Yalçın, “TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ”, UUJFE, vol. 23, no. 4, pp. 127–140, 2018, doi: 10.17482/uumfd.448596.
ISNAD Ayyıldız, Ertuğrul - Yalçın, Selin. “TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 23/4 (December 2018), 127-140. https://doi.org/10.17482/uumfd.448596.
JAMA Ayyıldız E, Yalçın S. TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ. UUJFE. 2018;23:127–140.
MLA Ayyıldız, Ertuğrul and Selin Yalçın. “TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, vol. 23, no. 4, 2018, pp. 127-40, doi:10.17482/uumfd.448596.
Vancouver Ayyıldız E, Yalçın S. TÜRKİYE’DE YER ALAN LOJİSTİK DOSTU ŞEHİRLERİN BÜTÜNLEŞİK ENTROPİ-CODAS KULLANILARAK BELİRLENMESİ. UUJFE. 2018;23(4):127-40.

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