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TRANSPORTATION SECTOR IN EU-28 AND NETWORK ANALYSIS OF INTERNATIONAL TRADE LOGISTICS

Yıl 2017, Cilt: 5 Sayı: 5, 205 - 230, 01.07.2017

Öz

The European Union EU , as the largest trading block on the world scale, is also a scene of significant trade movements in this geography. When intra-EU exports reaching 3.063 billion euros in 2015 are examined in terms of groups of goods, it can be seen that machines, transportation vehicles, manufacturing industry products, chemicals, etc. have high shares. This situation proves the importance of logistics for the Union. In this context, in the White Paper 2011, a number of objectives related to the logistical future of the EU have been identified. In White Paper 1992 in which the importance of logistic within the Union was first drawn attention to, a number of objectives were identified, such as changing the balance between types of transportation and increasing quality globally. In the 2011 report, which emphasized the importance of a common transport policy, there are also some striking targets for the year 2050 such as completing the high-speed railway network, connecting airports, railroads and sea routes. In this context, in this study, the changing situation over time of road, sea, railway and air transport networks which provides intra-EU trade logistics of the union, and the current situation will be evaluated by network analysis approach

Kaynakça

  • Aladağ, A.E. (2016), “İstanbul Toplu Taşıma Ağı Analizi”. Conference Paper. DOI: 10.13140/RG.2.1.3256.5529.
  • Arora, A. Ve Pandey, M.K. (2011), “Transportation Network Model and Network Analysis od Road Networks”. 12th Esri India User Conference.
  • Barrat, A., Barthelemy, M. ve Vespignani, A. (2004), “Traffic-Driven model of the world wide web graph”. Algorithms and Models for the Web-Graph. Third International Workshop, Springer.
  • Caldarelli, G. “Lectures in complex networks”, http://www.guidocaldarelli.com/images/lectures/Properties.pdf . (23.08.2017)
  • Cheng, Y.Y., Lee, R.K.W., Lim, E.P. ve Zhu, F. (2015), “Measuring Centralities for Transportation Networks Beyond Structures”. Applications of Social Media and Social Network Analysis. Lecture Notes in Social Networks.
  • Cheung, D.P. ve Gunes, M.H. (t.y.), “A Complex Network Analysis of the United States Air Transportation”.
  • Csardi, G. Package ‘igraph’, https://cran.rproject.org/web/packages/igraph/igraph.pdf . (21.08.2017).
  • Çevik, O. ve Gülcan, B. (2011), “Lojistik Faaliyetlerin Çevresel Sürdürülebilirliği ve Marco Polo Programı”. KMÜ Sosyal ve Ekonomik Araştırmalar Dergisi. C:13. S:20. 35-44.
  • Çırpıcı, Y.A. ve Soyyiğit, S. (2017), “Sosyal ve Ekonomik Ağlar”. Kompleksite ve İktisat. İstanbul: Efil Yayınevi.
  • Decarlo, L.T. (1997), “On the Meaning and the Use of Kurtosis”, Psychological Methods, 2 (3). 292-307.
  • Estrada, E. (2015), “Introduction to Complex Networks: Structure and Dynamics”. Evolutionary Equations with Applications in Natural Sciences- Lecture Notes in Mathematics 2126. Switzerland: Springer International Publishing.
  • European Commission. (2009), A Sustainable Future for Transport: Towards an Integrated, Technology-Led and User-Friendly System. Belgium: European Commission.
  • European Commission. (2014), Transport – Connecting Europe’s Citizens and Businesses. Luxembourg: European Commission.
  • Fagiolo, G., Reyes, J. ve Schiavo, S. (2010), The Evolution of the World Trade Web: A Weighted Network Analysis. Journal of Evolutionary Economics. 20. 479-514.
  • Fuge, M. Tee K. & Agogino, A. Network Analysis of Collaborative Design Networks: A Case Study of OpenIDEO”
  • https://ideal.umd.edu/papers/fuge_tee_openideo_jcise_final_2013.pdf . (23.08.2017).
  • Haznagy, A., Fi, I, London, A. Ve Nemeth, T. (2015), “Complex Network Analysis of Public Transportation Networks: A Comprehensive Study”. Models and Technologies for Intelligent Transportation Systems. 3-5 June 2015. Budapest – Hungary.
  • Hein, O., Schwind, M. ve König, W. (2006), “Scale-Free Networks – The Impact of Fat Tailed Degree Distribution on Diffusion and Communication Processes”. Wirtschaftsinformatik. 48 (4). 267-275.
  • Howell, A. (2012), Network Statistics and Modeling the Global Trade Economy: Exponential Random Graph Models and Latent Space Models: Is Geography Dead?. University of California Unpublished Thesis.
  • Kleinberg, J.M. (1999), “Authoritative Sources in a Hyperlinked Enironment”. https://www.cs.cornell.edu/home/kleinber/auth.pdf . (16.03.2017).
  • Kolaczyk, E. D. (2009), Statistical analysis of network data methods and models. Springer.
  • Kurt, C. (2010), Türkiye’de Ulaştırma Sektörü İçerisinde Lojistiğin Yeri ve Önemi. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü İktisat Politikası Anabilim Dalı Yayınlanmamış Yüksek Lisans Tezi. İstanbul.
  • Laszlo – Barabasi, A. ve Reka, A. “Emergence of scaling in random networks”. http://snap.stanford.edu/class/cs224w-readings/barabasi99scaling.pdf . (15.04.2017).
  • Leon, C. ve Berndsen, R.J. (2014), “Rethinking Financial Stability: Challenges Arising from Financial Networks’ Modular Scale-free Architecture”. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2398185 . (21.08.2017).
  • Lovric, M. (2010), Skewness. International Encyclopedia of Statistical Science. New York: Springer.
  • Mitchell, M. (2009), Complexity A Guided Tour. Oxford University Press.
  • Newman, M.E.J. (2010), Networks An Introduction.
  • Newman, M.E.J. “Mixing Patterns in Network”. http://arxiv.org/pdf/condmat/0209450v2.pdf . (21.08.2017).
  • OECD. (2009), Applications of Complexity science for public policy- new tools for finding unanticipated consequences and unrealized opportunities.
  • Opsahl, T. ve Panzarasa, P. (2009), “Clustering in Weighted Networks”. Social Networks. 31. 155-163.
  • Reichardt, J. (2009), “Introduction to Complex Networks”. Structure in Complex Networks Lecture Notes in Physics. Berlin: Springer-Verlag Heidelberg.
  • Rincon, C.E.L., Machado, C. ve Paipilla, N.M.S. (2015), “Identifying Central Bank Liquidity Super-Spreader in Interbank Funds Network”. EBC Discussion Paper. Vol. 2015-010.
  • Tutar, E., Tutar, F. Ve Yetişen, H. (2009), “Türkiye’de Lojistik Sektörünün Gelişmişlik Düzeyinin Seçilmiş AB Ülkeleri (Romanya ve Macaristan) ile Karşılaştırmalı Bir Analizi”. KMU İİBF Dergisi. Yıl:11. Sayı:7. 190-216.
  • https://ec.europa.eu/jrc/en/research-topic/transport-sector-economicanalysis . (22.07.2017).
  • http://igraph.org/r/doc/fit_power_law.html . (21.08.2017).
  • https://ec.europa.eu/transport/themes/infrastructure/about-ten-t_en . (21.08.2017).
  • https://ec.europa.eu/transport/themes/infrastructure_en . (21.08.2017).
  • https://ec.europa.eu/info/law/better-regulation/initiatives/ares-2017- 3272163_en . (21.08.2017).

AB-28 ÜLKELERİNDE ULAŞIM SEKTÖRÜ VE ULUSLARARASI TİCARET LOJİSTİĞİNİN AĞ ANALİZİ İLE İNCELENMESİ

Yıl 2017, Cilt: 5 Sayı: 5, 205 - 230, 01.07.2017

Öz

Dünya ölçeğindeki en büyük ticaret bloğu olan Avrupa Birliği AB , bu coğrafyada oldukça önemli ticaret hareketlerine de sahne olmaktadır. 2015 yılı itibariyle 3063 milyar Euro’ya varan birlik içi ihracat mal grupları cinsinden incelendiğinde; makineler, ulaşım araçları, imalat sanayi ürünleri, kimyasallar gibi mal gruplarının yüzdelik ağırlığının yüksek olduğu görülmektedir. Bu durum da birlik içerisinde lojistiğin önemini kanıtlar durumdadır. Bu kapsamda, Beyaz Kitap 2011’de AB’nin lojistik geleceğine ilişkin birtakım hedefler de belirlenmiştir. Birlik içinde lojistiğin önemine dikkatlerin ilk kez çekildiği 1992 yılındaki Beyaz Kitapta o dönemde ulaşım türleri arasındaki dengenin değiştirilmesi, ulaşıma giderek küresel bir nitelik kazandırılması gibi birtakım amaçlar belirlenmiştir. Ortak bir ulaştırma politikasının önemine dikkat çeken 2011 raporunda ise yüksek hızlı demiryolu ağını tamamlamak; havalimanları, demiryolları ve denizyollarını birbirine bağlamak gibi 2050 hedefleri de göze çarpmaktadır. Bu kapsamda, bu çalışmada AB-28’in birlik içi ticaret lojistiğinin sağlandığı karayolu, denizyolu, demiryolu ve havayolu ulaşım ağlarının zamansal değişimi ve mevcut durumu ağ analizi yaklaşımı ile değerlendirilecektir

Kaynakça

  • Aladağ, A.E. (2016), “İstanbul Toplu Taşıma Ağı Analizi”. Conference Paper. DOI: 10.13140/RG.2.1.3256.5529.
  • Arora, A. Ve Pandey, M.K. (2011), “Transportation Network Model and Network Analysis od Road Networks”. 12th Esri India User Conference.
  • Barrat, A., Barthelemy, M. ve Vespignani, A. (2004), “Traffic-Driven model of the world wide web graph”. Algorithms and Models for the Web-Graph. Third International Workshop, Springer.
  • Caldarelli, G. “Lectures in complex networks”, http://www.guidocaldarelli.com/images/lectures/Properties.pdf . (23.08.2017)
  • Cheng, Y.Y., Lee, R.K.W., Lim, E.P. ve Zhu, F. (2015), “Measuring Centralities for Transportation Networks Beyond Structures”. Applications of Social Media and Social Network Analysis. Lecture Notes in Social Networks.
  • Cheung, D.P. ve Gunes, M.H. (t.y.), “A Complex Network Analysis of the United States Air Transportation”.
  • Csardi, G. Package ‘igraph’, https://cran.rproject.org/web/packages/igraph/igraph.pdf . (21.08.2017).
  • Çevik, O. ve Gülcan, B. (2011), “Lojistik Faaliyetlerin Çevresel Sürdürülebilirliği ve Marco Polo Programı”. KMÜ Sosyal ve Ekonomik Araştırmalar Dergisi. C:13. S:20. 35-44.
  • Çırpıcı, Y.A. ve Soyyiğit, S. (2017), “Sosyal ve Ekonomik Ağlar”. Kompleksite ve İktisat. İstanbul: Efil Yayınevi.
  • Decarlo, L.T. (1997), “On the Meaning and the Use of Kurtosis”, Psychological Methods, 2 (3). 292-307.
  • Estrada, E. (2015), “Introduction to Complex Networks: Structure and Dynamics”. Evolutionary Equations with Applications in Natural Sciences- Lecture Notes in Mathematics 2126. Switzerland: Springer International Publishing.
  • European Commission. (2009), A Sustainable Future for Transport: Towards an Integrated, Technology-Led and User-Friendly System. Belgium: European Commission.
  • European Commission. (2014), Transport – Connecting Europe’s Citizens and Businesses. Luxembourg: European Commission.
  • Fagiolo, G., Reyes, J. ve Schiavo, S. (2010), The Evolution of the World Trade Web: A Weighted Network Analysis. Journal of Evolutionary Economics. 20. 479-514.
  • Fuge, M. Tee K. & Agogino, A. Network Analysis of Collaborative Design Networks: A Case Study of OpenIDEO”
  • https://ideal.umd.edu/papers/fuge_tee_openideo_jcise_final_2013.pdf . (23.08.2017).
  • Haznagy, A., Fi, I, London, A. Ve Nemeth, T. (2015), “Complex Network Analysis of Public Transportation Networks: A Comprehensive Study”. Models and Technologies for Intelligent Transportation Systems. 3-5 June 2015. Budapest – Hungary.
  • Hein, O., Schwind, M. ve König, W. (2006), “Scale-Free Networks – The Impact of Fat Tailed Degree Distribution on Diffusion and Communication Processes”. Wirtschaftsinformatik. 48 (4). 267-275.
  • Howell, A. (2012), Network Statistics and Modeling the Global Trade Economy: Exponential Random Graph Models and Latent Space Models: Is Geography Dead?. University of California Unpublished Thesis.
  • Kleinberg, J.M. (1999), “Authoritative Sources in a Hyperlinked Enironment”. https://www.cs.cornell.edu/home/kleinber/auth.pdf . (16.03.2017).
  • Kolaczyk, E. D. (2009), Statistical analysis of network data methods and models. Springer.
  • Kurt, C. (2010), Türkiye’de Ulaştırma Sektörü İçerisinde Lojistiğin Yeri ve Önemi. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü İktisat Politikası Anabilim Dalı Yayınlanmamış Yüksek Lisans Tezi. İstanbul.
  • Laszlo – Barabasi, A. ve Reka, A. “Emergence of scaling in random networks”. http://snap.stanford.edu/class/cs224w-readings/barabasi99scaling.pdf . (15.04.2017).
  • Leon, C. ve Berndsen, R.J. (2014), “Rethinking Financial Stability: Challenges Arising from Financial Networks’ Modular Scale-free Architecture”. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2398185 . (21.08.2017).
  • Lovric, M. (2010), Skewness. International Encyclopedia of Statistical Science. New York: Springer.
  • Mitchell, M. (2009), Complexity A Guided Tour. Oxford University Press.
  • Newman, M.E.J. (2010), Networks An Introduction.
  • Newman, M.E.J. “Mixing Patterns in Network”. http://arxiv.org/pdf/condmat/0209450v2.pdf . (21.08.2017).
  • OECD. (2009), Applications of Complexity science for public policy- new tools for finding unanticipated consequences and unrealized opportunities.
  • Opsahl, T. ve Panzarasa, P. (2009), “Clustering in Weighted Networks”. Social Networks. 31. 155-163.
  • Reichardt, J. (2009), “Introduction to Complex Networks”. Structure in Complex Networks Lecture Notes in Physics. Berlin: Springer-Verlag Heidelberg.
  • Rincon, C.E.L., Machado, C. ve Paipilla, N.M.S. (2015), “Identifying Central Bank Liquidity Super-Spreader in Interbank Funds Network”. EBC Discussion Paper. Vol. 2015-010.
  • Tutar, E., Tutar, F. Ve Yetişen, H. (2009), “Türkiye’de Lojistik Sektörünün Gelişmişlik Düzeyinin Seçilmiş AB Ülkeleri (Romanya ve Macaristan) ile Karşılaştırmalı Bir Analizi”. KMU İİBF Dergisi. Yıl:11. Sayı:7. 190-216.
  • https://ec.europa.eu/jrc/en/research-topic/transport-sector-economicanalysis . (22.07.2017).
  • http://igraph.org/r/doc/fit_power_law.html . (21.08.2017).
  • https://ec.europa.eu/transport/themes/infrastructure/about-ten-t_en . (21.08.2017).
  • https://ec.europa.eu/transport/themes/infrastructure_en . (21.08.2017).
  • https://ec.europa.eu/info/law/better-regulation/initiatives/ares-2017- 3272163_en . (21.08.2017).
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Research Article
Yazarlar

Semanur Soyyiğit Bu kişi benim

Şerafettin Keleş

Aslı Cansın Doker Bu kişi benim

Yayımlanma Tarihi 1 Temmuz 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 5 Sayı: 5

Kaynak Göster

APA Soyyiğit, S., Keleş, Ş., & Doker, A. C. (2017). AB-28 ÜLKELERİNDE ULAŞIM SEKTÖRÜ VE ULUSLARARASI TİCARET LOJİSTİĞİNİN AĞ ANALİZİ İLE İNCELENMESİ. The International New Issues in Social Sciences, 5(5), 205-230.

The International New Issues in Social Sciences, is international, Scientific, peer-reviewed Journal.
Tini-SOS journal is to evaluate scientific articles in the field of social sciences, especially based on field studies structured in accordance with scientific criteria, and conducts studies to publish studies that provide appropriate measures.