Sains Malaysiana 50(4)(2021): 1113-1120

http://doi.org/10.17576/jsm-2021-5004-21

 

Evaluation of Safety Performance of Level Crossings in Turkey with Data Envelopment Analysis

(Penilaian Prestasi Keselamatan Lintasan Kereta Api di Turki dengan Analisis Penyampulan Data)

 

KÜRŞAT YILDIZ1 & HARUN KINACI2*

 

1Gazi University, Technology Faculty, Civil Engineering Department, Technical Schools

06500, Ankara, Turkey

 

2Erciyes University, Faculty of Economics and Administrative Sciences Department of Business, 38225, Kayseri, Turkey

 

Diserahkan: 2 November 2019/Diterima: 3 September 2020

 

ABSTRACT

Level crossing, also known as railroad and highway crossings, pose a risk to those who use both modes of transport due to collisions that may occur. This risk associated with level crossings is of great importance both in Turkey and in the world. In this study, data envelopment analysis was performed on the accident data occurring on five types of level crossings in Turkey and a measurement of safety performances of level crossings in Turkey was provided. As a result of the analysis, the most efficient three-level crossings were found to be Hilal-Bandırma in Manisa, Samsun-Kalın in Amasya_1, and Samsun-Kalın in Amasya_2. In addition, a linear regression model that serves with the variables which are the components of level crossing and the number of accidents is established. In this model, it is seen that the ratio of independent variables to dependent variables was statistically significant.

 

Keywords: Accident; data envelopment analysis; level crossing; safety performance

 

ABSTRAK

Lintasan kereta api, juga dikenali sebagai landasan kereta api dan lintasan lebuh raya, dapat menimbulkan risiko kepada mereka yang menggunakan kaedah pengangkutan ini atas sebab wujudnya kemungkinan pelanggaran yang akan berlaku. Risiko ini dikaitkan apabila lintasan kereta api adalah amat penting bagi negara Turki dan dunia. Daripada analisis kajian ini, analisis penyampulan data dijalankan pada data kemalangan yang berlaku pada lima jenis lintasan kereta api di Turki dan satu ukuran prestasi keselamatan lintasan kereta api di Turki telah disediakan. Hasil analisis menunjukkan terdapat tiga kaedah yang didapati paling cekap dalam lintasan kereta api iaitu Hilal-Bandırma di Manisa, Samsun-Kalin di Amasya_1 dan Samsun-Kalin di Amasya_2. Sebagai tambahan, model regresi linear telah dihasilkan yang mempunyai beberapa pemboleh ubah komponen lintasan kereta api dan jumlah kemalangan. Model ini memperlihatkan bahawa julat pemboleh ubah tidak bersandar kepada pemboleh ubah bersandar daripada statistik adalah amat ketara.

 

Kata kunci: Analisis penyampulan data; kemalangan; lintasan kereta api; prestasi keselamatan

 

RUJUKAN

Acarlar, I., Kınacı, H. & Najjari, V. 2014. A new measure for detecting influential DMUs in DEA. Journal of Optimization 2014: 1-7.

Alp, İ. 2006. Performance evaluation of goalkeepers of the world cup. Gazi University Journal of Science 19(2): 119-125.

Avkiran, N.K. 2001. Investigating technical and scale efficiency of Australian universities through data envelopment analysis. Socio-Economic Planning Sciences 35(1): 57-80.

Bal, H. & Adnan, G. 2002. Data envelopment analysis: An application to turkish banking industry. Mathematical and Computational Applications 7(1): 65-72.

Bal, H., Örkcü, H.H. & Çelebioğlu, S. 2010. Improving the discrimination power and weights dispersion in the data envelopment analysis. Computers & Operations Research 37(1): 99-107.

Banker, R.D., Charnes, A. & Cooper, W.W. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis author. Management Science 30(9): 1078-1092.

Baysal, E.M., Uygur, M. & Toklu, B. 2004. A study of the relative efficiency of TCDD Ports, using data envelopment analysis. Journal of the Faculty of Engineering and Architcture of Gazi University 19(4): 437-442.

Boame, A.K. 2004. The technical efficiency of Canadian urban transit systems. Transportation Research Part E-Logistics and Transportation Review 40(5): 401-416.

Charnes, A., Cooper, W.W. & Rhodes, E. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2(6): 429-444.

Cui, Q. & Ye, L. 2015. Evaluating energy efficiency for airlines: An application of VFB-DEA. Journal of Air Transport Management 44(45): 34-41.

Djordjević, B., Evelin, K. & Tomislav, J.M. 2018. Non-radial DEA model: A new approach to evaluation of safety at railway level crossings. Safety Science 103: 234-246.

European Railway Agency. 2014. Annual Report 2014. Luxembourg: Publications Office of the European Union.

Fare, R., Grosskopf, S. & Lee, W. 1995. Productivity in Taiwanese manufacturing industries. Applied Economics 27(3): 259-265.

Fare, R., Grosskopf, S. & Tyteca, D. 1996. An activity analysis model of the environmental performance of firms application to fossil-fuel-fired electric utilities. Ecological Economics 18: 161-175.

Ghazel, M. 2009. Using stochastic petri nets for level-crossing collision risk assessment. IEEE Transactions on Intelligent Transportation Systems 10(4): 668-677.

Karlaftis, M.G. 2004. A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. European Journal of Operational Research 152: 354-364.

Karlaftis, M.G. & Tsamboulas, D. 2012. Efficiency measurement in public transport: Are findings specification sensitive? Transportation Research Part A Policy and Practice 46(2): 392-402.

Khoudour, L., Ghazel, M., Boukour, F., Heddebaut, M. & El Miloudi, K. 2009. Towards safer level crossings: Existing recommendations, new applicable technologies and a proposed simulation model. European Transport Research Review 1(1): 35-45.

Liang, C., Ghazel, M. & Cazier, O. 2018. Using Bayesian networks for the purpose of risk analysis at railway level crossings. IFAC-PapersOnLine 51(9): 142-149.

Liu, J.S., Louis, Y.Y., Lu, W.M.L. & Bruce, J.Y. 2013. Data envelopment analysis 1978-2010: A citation-based literature survey. Omega (United Kingdom) 41(1): 3-15.

Lovell, K.C.A. & Pastor, J.T. 1999. Radial DEA models without inputs or without outputs. European Journal of Operational Research 118: 46-51.

Malekmohammadi, N., Jaafar, A.B. & Monsi, M. 2010. Setting targets with interval data envelopment analysis models via wang method. Sains Malaysiana 39(3): 485-489.

Olesen, O.B. & Petersen, N.C. 1995. Incorporating quality into data envelopment analysis: A stochastic dominance approach. International Journal of Production Economics 39: 117-135.

Ray, S.C. 1991. Resource use efficinecy in sublic schools: A study of connecticut data. Management Science 17(12): 1620-1628.

Sampaio, B.R., Neto, O.L. & Sampaio, Y. 2008. Efficiency analysis of public transport system: Lesson for institutional planning. Transportation Research Part A 42: 445-454.

Sözen, A., Alp, İ. & Özdemir, A. 2010. Assessment of operational and environmental performance of the thermal power plants in Turkey by using data envelopment analysis. Energy Policy 38(10): 6194-6203.

Thanassoulis, E. & Dyson, R.G. 1992. Estimating preferred target input-output levels using data envelopment analysis. European Journal of Operational Research 56(1): 80-97.

von Hirschhausen, C. & Cullmann, A. 2010. A nonparametric efficiency analysis of German public transport companies. Transportation Research Part E 46: 436-445.

 

*Pengarang untuk surat-menyurat; email: hkinaci@erciyes.edu.tr

 

 

sebelumnya