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Türkiye’nin Demiryolu Yük Taşımacılığı Talebinin Zaman Serisi Analizi ile Tahmini

Yıl 2021, Sayı: 58, 137 - 154, 30.04.2021
https://doi.org/10.18070/erciyesiibd.753557

Öz

Taşıma modları içinde yatırım maliyeti yüksek olmasına rağmen kütlesel taşımada navlun
maliyeti oldukça düşük olan mod demiryolu taşımacılığıdır. Demiryolunda taşınacak yük miktarının
tahmin edilmesi etkin planlama yapılmasını sağlar. Bu çalışma Türkiye’de demiryolu yük
taşımacılığına oluşacak talep modeli 1978-2018 arasındaki yıllık zaman serisi verilerini kullanarak
analiz edilmiştir. Johansen eşbütünleşme analizi ve varyans hata düzeltme modeli ile tahminin
belirleyicilerinin kısa ve uzun dönem esneklikleri tahmin edilmiştir. Elde edilen sonuçlara göre
demiryolu yük talebinin en önemli belirleyicisi navlun oranı olmuştur. Demiryolu yük talebinin
navlun oranına göre uzun dönem ve kısa dönem esneklikleri - 0,181 ve -0,184 ile çok yakındır.
Demiryolu yükü talebinin uzun dönemli dış ticaret hacmi esnekliği anlamlı ve pozitiftir, yani ticaret
hacmi arttıkça demiryoluna oluşacak yük talebi artacaktır. Fakat demiryolu yükü talebinin uzun
dönemli Gayrisafi Katma Değer ve Yakıt Fiyatı esneklikleri anlamlı ve negatiftir. Yani bu
değişkenlerdeki artık demiryolu yük talebini azaltacaktır. Hata düzeltme modeline göre demiryolu
yük talebindeki herhangi bir son dönem sapmasının 55%’i bir yıl içinde düzeltilmekte ve uzun dönem
denge ilişkisi eski haline gelebilmektedir.

Kaynakça

  • Antonowicz M., Litewski M., Stopyra R. (2019). Role Of The New Sılk Road In Supply Chaın Development İn Poland, ISMC 2019 15th International Strategic Management Conference. https://doi.org/10.15405/epsbs.2019.10.02.14
  • Baykasoğlu A., Subulan K. (2016), A Multi-Objective Sustainable Load Planning Model For İntermodal Transportation Networks With A Real-Life Application, Transportation Research Part E: Logistics and Transportation Review, 95, 207–247.
  • Choi B., Park S-İ, Lee K-D (2019). A System Dynamics Model Of The Modal Shift From Road To Rail: Containerization And Imposition Of Taxes, Hindawi Journal of Advanced Transportation, 2019, 1-9.
  • Crainic, G., Florian, M. ve Leal J.-E. (1990). A Model For The Strategic Planning Of National Freight Transportation by Rail. Transportation Science, 24(1), 2-5.
  • Çekerol, G. S., Nalçakan, M. (2011). Lojistik Sektörü İçerisinde Türkiye Demiryolu Yurtiçi Yük Taşıma Talebinin Ridge Regresyonla Analizi. Marmara Üniversitesi İ.İ.B.F. Dergisi, 31(2), 321-344.
  • De Jong G., Gunn H., Walker W. (2004). National and International Freight Transport Models: An Overview and Ideas for Future Development, Transport Reviews, 24(1),
  • Dickey, D.A., Fuller, W.A. (1979). Distribution Of The Estimators For Autoregressive Time Series With A Unit Root. J. Am. Stat. Assoc. 74 (366a), 427–431.
  • Elbert R., Seikowsky L. (2017), The İnfluences Of Behavioral Biases, Barriers And Facilitators On The Willingness Of Forwarders’ Decision Makers To Modal Shift From Unimodal Road Freight Transport To İntermodal Road–Rail Freight Transport, Journal of Business Economics, 87(8), 1083–1123.
  • Esposito G., Cicatiello L., Ercolano S. (2020). Reforming Railways İn The EU: An Empirical Assessment Of Liberalisation Policies İn The European Rail Freight Market, Transportation Research Part A, 132, 606–613.
  • FitzRoy, F., Smith, I. (1995). The Demand For Rail Transport İn European Countries. Transp. Policy 2 (3), 153–158.
  • Gnap J., Varjan P., Durana P., Kostrzewskı M. (2019), Research on Relatıonshıp Between Freıght Transport And Transport Infrastructure In Selected European Countrıes, Transport Problems, 14(3),63-74
  • Johansen, S., (1988). Statistical Analysis of Cointegration Vectors. J. Econ. Dyn. Control 12 (2–3), 231–254
  • Jourquin B., Beuthe M (2019), Cost, Transit Time And Speed Elasticity Calculations For The European Continental Freight Transport, Transport Policy, 83, 1–12.
  • Kanafanı A. K. (1983), Transportation Demand Analysis, New York: McGraw-Hill
  • KumarA., Anbanandam R. (2020). Evaluating The İnterrelationships Among İnhibitors to İntermodal Railroad Freight Transport in Emerging Economies: A Multistakeholder Perspective, Transportation Research Part A, 132, 559–581.
  • Lu M., Chen Y., Morphet R., Lu Y., Li E. (2019). The Spatial Competition Between Containerised Rail And Sea Transport in Eurasia, 5:122 | https://doi.org/10.1057/s41599-019-0334-6
  • Lu Y., Lang M., Sun Y., Li S. (2020). A Fuzzy Intercontinental Road-Rail Multimodal Routing Model With Time And Train Capacity Uncertainty And Fuzzy Programming Approaches, Digital Object Identifier 10.1109/ACCESS.2020.2971027.
  • Marcos, C.B., Martos, L.P. (2012). Estimating The Demand For Freight Transport: The Private Versus Public Trade-Off in Andalusian Food İndustry. Available at: Encuentros. Alde.Es/Anteriores/Vieea/Autores/B/36.Doc.
  • Milenkovic, M., and Bojovic, N. (2016). Railway Demand Forecasting, Handbook of research on emerging innovations in rail transportation engineering, IGI Global, Hershey, PA, 100-129.
  • Muhammad Z. K., Khan F. N. (2020). Estimating The Demand For Rail Freight Transport in Pakistan: A Time Series Analysis, Journal of Rail Transport Planning & Management, 14, 100176 .
  • Phillips, P.C.B., Perron, P. (1988). Testing For A Unit Root İn Time Series Regression. Biomètrika, Cilt: 75, Sayı:2, ss.336-346.
  • Ramanathan, R., 2001. The Long-Run Behaviour of Transport Performance in India: A Cointegration Approach. Transp. Res. A Policy Pract. 35 (4), 309–320. https://doi.org/10.1016/S0965-8564(99)00060-9.
  • Rao, P.S. (1978). Forecasting The Demand For Railway Freight Services. J. Transp. Econ. Policy 7–26. Retrieved from. http://www.jstor.org/stable/10.2307/20052487.
  • Rossi T., Pozzi R., Pirovano G., Cigolini R. and Pero M. (2020). A New Logistics Model For İncreasing Economic Sustainability of Perishable Food Supply Chains Through İntermodal Transportation, Internatıonal Journal of Logıstıcs Research And Applıcatıons, https://doi.org/10.1080/13675567.2020.1758047
  • Tsamboulas D., Vrenken H., Lekka A.M. (2007),Assessment of a Transport Policy Potential For İntermodal Mode Shift on A European Scale, Transp. Res. Part a Policy Pract., 41,715–733.
  • Wijeweera, A., To, H., Charles, M. (2014). An Empirical Analysis of Australian Freight Rail Demand. Econ. Anal. Policy 44 (1), 21–29. https://doi.org/10.1016/j.eap.2014.01.001
  • Woodburn A. (2019), Rail Network Resilience and Operational Responsiveness During Unplanned Disruption: A Rail Freight Case Study, Journal of Transport Geography, 77, 59–69.
  • Woodburn, A. (2017). An Analysis of Rail Freight Operational Efficiency And Mode Share in The British Port-Hinterland Container Market. Transportation Research Part D, 51, 190–202
  • Zou G., Chau K. W. (2019), Long- and Short-Run Effects of Fuel Prices on Freight Transportation Volumes in Shanghai, Sustainability, 11, 5017.
  • British Petrolium (BP),https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html. Erişim 20/04//2020. STB Sanayi ve Teknoloji Bakanlığı, On Birinci Kalkınma Planı (2019-2023), 2018.
  • TCDD Türkiye Cumhuriyeti Devler Demiryolları, İstatistik Yıllığı, http://www.tcddtasimacilik.gov.tr/sayfa/istatistikler/. Erişim 01/05/2020.
  • The World Bank, https://data.worldbank.org/indicator/NY.GDP.FCST.CD?locations=TR. Erişim 20/04//2020.
  • TUIK Türkiye İstatistik Kurumu, Genel istatistikler http://www.tuik.gov.tr/UstMenu.do?metod=temelist. Erişim 25/04//2020.
  • UTIKAD Uluslararası Taşımacılık ve Lojistik Hizmet Üretenleri Derneği, https://www.utikad.org.tr/Images/BasinBulten/090120192019basintoplantisiv4566696.pdf, Erişim 07/06/2020.
  • UTIKAD, Bir Bakışta: Bakü-Tiflis-Kars demiryolu projesi. https://www.utikad.org.tr/Detay/Sektor-Haberleri/10325/bir-bakista:-baku-tiflis-kars-demiryolu-projesi. Erişim 13/06/2020.

Forecasting of Turkey’s Demand for Railway Freight Transportation with Time Series Analysis

Yıl 2021, Sayı: 58, 137 - 154, 30.04.2021
https://doi.org/10.18070/erciyesiibd.753557

Öz

Among the transportation modes,it is the type of railway transportation that has a very low
freight cost in mass transportation, although the investment cost is high. Estimating the amount of
load to be carried on the rail provides effective planning for managers. This study was analyzed using
annual time series data between 1978-2018 will consist of rail freight demand in Turkey. The short
and long term flexibility of the estimation was estimated with the Johansen cointegration analysis and
error correction model. According to the results obtained, the most important determinant of the rail
freight demand was the freight rate. According to the freight rate of the rail freight demand, the longterm and short-term elasticities are almost the same as - 0.181 and -0.184. The long-term trade
volume flexibility of the demand for rail freight is meaningful and positive, meaning that the demand
for the rail will increase as the trade volume increases. However, the long-term Gross Value Added
and Fuel Price elasticities of the demand for the railway load are significant and negative. In other
words, these variables will now reduce the demand for rail freight. According to the error correction
model, 55% of any last-term deviation in the rail freight demand is corrected within a year and the
long-term balance relationship can be restored..

Kaynakça

  • Antonowicz M., Litewski M., Stopyra R. (2019). Role Of The New Sılk Road In Supply Chaın Development İn Poland, ISMC 2019 15th International Strategic Management Conference. https://doi.org/10.15405/epsbs.2019.10.02.14
  • Baykasoğlu A., Subulan K. (2016), A Multi-Objective Sustainable Load Planning Model For İntermodal Transportation Networks With A Real-Life Application, Transportation Research Part E: Logistics and Transportation Review, 95, 207–247.
  • Choi B., Park S-İ, Lee K-D (2019). A System Dynamics Model Of The Modal Shift From Road To Rail: Containerization And Imposition Of Taxes, Hindawi Journal of Advanced Transportation, 2019, 1-9.
  • Crainic, G., Florian, M. ve Leal J.-E. (1990). A Model For The Strategic Planning Of National Freight Transportation by Rail. Transportation Science, 24(1), 2-5.
  • Çekerol, G. S., Nalçakan, M. (2011). Lojistik Sektörü İçerisinde Türkiye Demiryolu Yurtiçi Yük Taşıma Talebinin Ridge Regresyonla Analizi. Marmara Üniversitesi İ.İ.B.F. Dergisi, 31(2), 321-344.
  • De Jong G., Gunn H., Walker W. (2004). National and International Freight Transport Models: An Overview and Ideas for Future Development, Transport Reviews, 24(1),
  • Dickey, D.A., Fuller, W.A. (1979). Distribution Of The Estimators For Autoregressive Time Series With A Unit Root. J. Am. Stat. Assoc. 74 (366a), 427–431.
  • Elbert R., Seikowsky L. (2017), The İnfluences Of Behavioral Biases, Barriers And Facilitators On The Willingness Of Forwarders’ Decision Makers To Modal Shift From Unimodal Road Freight Transport To İntermodal Road–Rail Freight Transport, Journal of Business Economics, 87(8), 1083–1123.
  • Esposito G., Cicatiello L., Ercolano S. (2020). Reforming Railways İn The EU: An Empirical Assessment Of Liberalisation Policies İn The European Rail Freight Market, Transportation Research Part A, 132, 606–613.
  • FitzRoy, F., Smith, I. (1995). The Demand For Rail Transport İn European Countries. Transp. Policy 2 (3), 153–158.
  • Gnap J., Varjan P., Durana P., Kostrzewskı M. (2019), Research on Relatıonshıp Between Freıght Transport And Transport Infrastructure In Selected European Countrıes, Transport Problems, 14(3),63-74
  • Johansen, S., (1988). Statistical Analysis of Cointegration Vectors. J. Econ. Dyn. Control 12 (2–3), 231–254
  • Jourquin B., Beuthe M (2019), Cost, Transit Time And Speed Elasticity Calculations For The European Continental Freight Transport, Transport Policy, 83, 1–12.
  • Kanafanı A. K. (1983), Transportation Demand Analysis, New York: McGraw-Hill
  • KumarA., Anbanandam R. (2020). Evaluating The İnterrelationships Among İnhibitors to İntermodal Railroad Freight Transport in Emerging Economies: A Multistakeholder Perspective, Transportation Research Part A, 132, 559–581.
  • Lu M., Chen Y., Morphet R., Lu Y., Li E. (2019). The Spatial Competition Between Containerised Rail And Sea Transport in Eurasia, 5:122 | https://doi.org/10.1057/s41599-019-0334-6
  • Lu Y., Lang M., Sun Y., Li S. (2020). A Fuzzy Intercontinental Road-Rail Multimodal Routing Model With Time And Train Capacity Uncertainty And Fuzzy Programming Approaches, Digital Object Identifier 10.1109/ACCESS.2020.2971027.
  • Marcos, C.B., Martos, L.P. (2012). Estimating The Demand For Freight Transport: The Private Versus Public Trade-Off in Andalusian Food İndustry. Available at: Encuentros. Alde.Es/Anteriores/Vieea/Autores/B/36.Doc.
  • Milenkovic, M., and Bojovic, N. (2016). Railway Demand Forecasting, Handbook of research on emerging innovations in rail transportation engineering, IGI Global, Hershey, PA, 100-129.
  • Muhammad Z. K., Khan F. N. (2020). Estimating The Demand For Rail Freight Transport in Pakistan: A Time Series Analysis, Journal of Rail Transport Planning & Management, 14, 100176 .
  • Phillips, P.C.B., Perron, P. (1988). Testing For A Unit Root İn Time Series Regression. Biomètrika, Cilt: 75, Sayı:2, ss.336-346.
  • Ramanathan, R., 2001. The Long-Run Behaviour of Transport Performance in India: A Cointegration Approach. Transp. Res. A Policy Pract. 35 (4), 309–320. https://doi.org/10.1016/S0965-8564(99)00060-9.
  • Rao, P.S. (1978). Forecasting The Demand For Railway Freight Services. J. Transp. Econ. Policy 7–26. Retrieved from. http://www.jstor.org/stable/10.2307/20052487.
  • Rossi T., Pozzi R., Pirovano G., Cigolini R. and Pero M. (2020). A New Logistics Model For İncreasing Economic Sustainability of Perishable Food Supply Chains Through İntermodal Transportation, Internatıonal Journal of Logıstıcs Research And Applıcatıons, https://doi.org/10.1080/13675567.2020.1758047
  • Tsamboulas D., Vrenken H., Lekka A.M. (2007),Assessment of a Transport Policy Potential For İntermodal Mode Shift on A European Scale, Transp. Res. Part a Policy Pract., 41,715–733.
  • Wijeweera, A., To, H., Charles, M. (2014). An Empirical Analysis of Australian Freight Rail Demand. Econ. Anal. Policy 44 (1), 21–29. https://doi.org/10.1016/j.eap.2014.01.001
  • Woodburn A. (2019), Rail Network Resilience and Operational Responsiveness During Unplanned Disruption: A Rail Freight Case Study, Journal of Transport Geography, 77, 59–69.
  • Woodburn, A. (2017). An Analysis of Rail Freight Operational Efficiency And Mode Share in The British Port-Hinterland Container Market. Transportation Research Part D, 51, 190–202
  • Zou G., Chau K. W. (2019), Long- and Short-Run Effects of Fuel Prices on Freight Transportation Volumes in Shanghai, Sustainability, 11, 5017.
  • British Petrolium (BP),https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html. Erişim 20/04//2020. STB Sanayi ve Teknoloji Bakanlığı, On Birinci Kalkınma Planı (2019-2023), 2018.
  • TCDD Türkiye Cumhuriyeti Devler Demiryolları, İstatistik Yıllığı, http://www.tcddtasimacilik.gov.tr/sayfa/istatistikler/. Erişim 01/05/2020.
  • The World Bank, https://data.worldbank.org/indicator/NY.GDP.FCST.CD?locations=TR. Erişim 20/04//2020.
  • TUIK Türkiye İstatistik Kurumu, Genel istatistikler http://www.tuik.gov.tr/UstMenu.do?metod=temelist. Erişim 25/04//2020.
  • UTIKAD Uluslararası Taşımacılık ve Lojistik Hizmet Üretenleri Derneği, https://www.utikad.org.tr/Images/BasinBulten/090120192019basintoplantisiv4566696.pdf, Erişim 07/06/2020.
  • UTIKAD, Bir Bakışta: Bakü-Tiflis-Kars demiryolu projesi. https://www.utikad.org.tr/Detay/Sektor-Haberleri/10325/bir-bakista:-baku-tiflis-kars-demiryolu-projesi. Erişim 13/06/2020.
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Özlem Karadağ Albayrak 0000-0003-0832-0490

Yayımlanma Tarihi 30 Nisan 2021
Kabul Tarihi 16 Şubat 2021
Yayımlandığı Sayı Yıl 2021 Sayı: 58

Kaynak Göster

APA Karadağ Albayrak, Ö. (2021). Türkiye’nin Demiryolu Yük Taşımacılığı Talebinin Zaman Serisi Analizi ile Tahmini. Erciyes Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi(58), 137-154. https://doi.org/10.18070/erciyesiibd.753557

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