Assessing Railway Transportation Performance of European Countries with CRITIC and ROV Techniques

Year 2023, , 93 - 106, 31.01.2023

Karahan Kara , Galip Cihan Yalçın

https://doi.org/10.47072/demiryolu.1175529

Cited By: 2

Abstract

Rail transport is among the modes of transport that provides safe and reliable logistics services for the transport of passengers, goods, and dangerous goods. The decrease in railway transport volumes in recent years reveals the necessity of examining the railway transport performance. In this research, it is aimed to determine the railway transport performance of European countries in 2020. Sixteen railway performance criteria have been determined. Three of these criteria are cost-based and thirteen criteria are benefit-based. The criterion weights have been calculated by the Criteria Importance Through Intercriteria Correlation (CRITIC) technique. The railway transport performance of twenty-three European countries is presented using the Range of Value (ROV) technique. The data set has been obtained from the Eurostat database. According to the research findings, the three criteria with the highest weight are determined as rail accidents victims, rail accidents, accidents involving transport of dangerous goods. The three countries with the highest railway transport performance are Germany, Italy, and Sweden. Suggestions for increasing the railway transportation performance levels of the countries are presented.

Keywords

Railway transport performance, MCDM, CRITIC, ROV.

Avrupa Ülkelerinin Demiryolu Taşımacılığı Performansının CRITIC ve ROV Teknikleriyle Değerlendirilmesi

Abstract

Demiryolu taşımacılığı yolcuların, malların ve tehlikeli maddelerin taşınmasında emniyetli ve güvenilir lojistik hizmet sunan ulaştırma modları arasında yer almaktadır. Son yıllarda demiryolu taşıma hacimlerinde düşüşlerin yaşanması demiryolu taşımacılık performansının incelenmesi gerekliliğini ortaya çıkarmaktadır. Bu araştırmada Avrupa ülkelerinin 2020 yılı demiryolu taşımacılık performansının belirlenmesi amaçlanmıştır. Araştırmada on altı demiryolu performans kriteri belirlenmiştir. Bu kriterlerin üç tanesi maliyet esaslı on üç tanesi fayda esaslı kriterdir. Kriter ağırlıkları kriterler arası korelasyon yoluyla kriterlerin önem tespiti (CRITIC) tekniğiyle tespit edilmiştir. Yirmi üç adet Avrupa ülkesinin demiryolu taşımacılık performansı değer aralığı (ROV) tekniğiyle hesaplanmıştır. Veri seti Eurostat’den elde edilmiştir. Araştırma bulgularına göre performans kriter ağırlığı en yüksek olan üç kriter demiryolu kaza kurbanları, demiryolu kazaları, tehlikeli madde taşımacılığındaki kazalar olarak belirlenmiştir. Demiryolu taşımacılık performansı en yüksek olan üç ülke ise Almanya, İtalya ve İsveç’tir. Ülkelerin demiryolu taşımacılık performans düzeylerinin artırılmasına yönelik öneriler sunulmuştur.

Keywords

Demiryolu taşımacılık performansı, MCDM, CRITIC, RoV.

References

• [1] M. Song, G. Zhang, W. Zeng, J. Liu, and K. Fang, “Railway transportation and environmental efficiency in China”, Transportation Research Part D: Transport and Environment, vol. 48, pp. 488-498, 2016, doi: 10.1016/j.trd.2015.07.003
• [2] O. P. Hilmola, “European railway freight transportation and adaptation to demand decline: Efficiency and partial productivity analysis from period of 1980-2003”, International Journal of Productivity and Performance Management, vol. 56, no. 3, pp. 205-225, 2007, doi: 10.1108/17410400710731428
• [3] Y. K. Al-Douri, P. Tretten, and R. Karim, “Improvement of railway performance: a study of Swedish railway infrastructure”, Journal of Modern Transportation, vol. 24, no. 1, pp. 22-37, 2016, doi: 10.1007/s40534-015-0092-0
• [4] A. Ait Ali, & J. Eliasson, “European railway deregulation: an overview of market organization and capacity allocation”, Transportmetrica A: Transport Science, vol. 18, no. 3, pp. 594-618, 2022, doi: 10.1080/23249935.2021.1885521
• [5] H. Zeybek, “Uluslararası Ticarette Demiryolunun Lojistik Performansa Etkisi”, Demiryolu Mühendisliği, vol. 9, pp. 79-90, 2019.
• [6] K.Yildiz, & M. T. Ahi, “Demiryolu Lojistiğinde Tedarik Zinciri Performans Metrikleri”, Demiryolu Mühendisliği, vol. 11, pp. 14-25, 2020.
• [7] C. Stenström, A. Parida, and D. Galar, “Performance indicators of railway infrastructure” The international Journal of railway technology, vol. 1, no. 3, pp. 1-18, 2012, doi: 10.4203/ijrt.1.3.1
• [8] N. G. Harris, C. S. Mjøsund, and H. Haugland, “Improving railway performance in Norway”, Journal of Rail Transport Planning & Management, vol. 3, no. 4, pp. 172-180, 2013, doi: 10.1016/j.jrtpm.2014.02.002
• [9] M. Kyriakidis, A. Majumdar, and W. Y. Ochieng, “Data based framework to identify the most significant performance shaping factors in railway operations”, Safety science, vol. 78, pp. 60-76, 2015, doi: 10.1016/j.ssci.2015.04.010
• [10] S. Duranton, A. Audier, J. Hazan, M. P. Langhorn, and V. Gauche, “The 2012 European railway performance index”, The Boston Consulting Group, 17, 2017.
• [11] M. Kyriakidis, A. Majumdar, and W. Y. Ochieng, “The human performance railway operational index—a novel approach to assess human performance for railway operations”, Reliability engineering & system safety, vol. 170, pp. 226-243, 2018, doi: 10.1016/j.ress.2017.10.012
• [12] T. Åhrén, and A. Parida “Maintenance performance indicators (MPI) for benchmarking the railway infrastructure: a case study”, Benchmarking: An International Journal, vol. 16, no. 2, pp. 247-258, 2009, doi: 10.1108/14635770910948240
• [13] Z. Yang, F. Schmid, and C. Roberts, “Assessment of railway performance by monitoring land subsidence”, In 6th IET conference on railway condition monitoring (RCM 2014) (pp. 1-6). IET, September 2014.
• [14] R. Ranjan, P. Chatterjee, and S. Chakraborty, “Performance evaluation of Indian Railway zones using DEMATEL and VIKOR methods”, Benchmarking An International Journal, vol. 23, no. 1, pp. 78, 2016, doi: 10.1108/BIJ-09-2014-0088
• [15] N. Bhanot, H. Singh, and R. S. Bhatti, “Benchmarking of Indian rail freight by DEA. In Encyclopedia of Business Analytics and Optimization (pp. 273-291)”, IGI Global, 2014.
• [16] N. Tahir, “Efficiency analysis of Pakistan railway in comparison with China and India”, International Journal of Transport Economics, vol. 40, no. 1, pp. 71-98, 2013.
• [17] T. Jitsuzumi, and A. Nakamura, “Causes of inefficiency in Japanese railways: Application of DEA for managers and policymakers”, Socio-Economic Planning Sciences, vol. 44, no. 3, pp. 161-173, 2010, doi: 10.1016/j.seps.2009.12.002
• [18] M. M. Yu, and E. T. Lin, “Efficiency and effectiveness in railway performance using a multi-activity network DEA model”, Omega, vol. 36, no. 6, pp. 1005-1017, 2008, doi: 10.1016/j.omega.2007.06.003
• [19] S. Stoilova, N. Munier, M. Kendra, & T. Skrúcaný, “Multi-criteria evaluation of railway network performance in countries of the TEN-T orient–east med corridor”, Sustainability, vol. 12, no. 4, pp. 1482, 2020, doi: 10.3390/su12041482
• [20] V. Sangiorgio, A. M. Mangini, and I. Precchiazzi, “A new index to evaluate the safety performance level of railway transportation systems”, Safety science, vol. 131, no. 104921, 2020, doi: 10.1016/j.ssci.2020.104921
• [21] M. G. Sharma, R. M. Debnath, R. Oloruntoba, & S. M. Sharma, “Benchmarking of rail transport service performance through DEA for Indian railways”, International Journal of Logistics Management, vol. 27, no. 3, pp. 629-649, 2006, doi: 10.1108/IJLM-08-2014-0122
• [22] I. Iyigun, “Evaluation of efficiency of rail transportation of black sea countries by using an integrated MCDM approach”, Economy & Business Journal, vol. 13, no. 1, pp. 305-323, 2009.
• [23] A. Fraszczyk, T. Lamb, & M. Marinov, “Are railways really that bad? An evaluation of rail systems performance in Europe with a focus on passenger rail”, Transportation Research Part A: Policy and Practice, vol. 94, pp. 573-591, 2016, doi: 10.1016/j.tra.2016.10.018
• [24] V. Simić, R. Soušek, Soušek, & S. Jovčić, “Picture Fuzzy MCDM Approach for Risk Assessment of Railway Infrastructure. Mathematics, vol. 8, no. 12, pp. 1-29, 2020
• [25] Eurostat, “Database”, Available: https://ec.europa.eu/eurostat/data/database [access date: 22.08.2022].
• [26] D. Diakoulaki, G. Mavrotas, and L. Papayannakis, “Determining objective weights in multiple criteria problems: The critic method”, Computers & Operations Research, vol. 22, no. 7, pp. 763-770, 1995.
• [27] M. Keshavarz Ghorabaee, M. Amiri, E. Kazimieras Zavadskas, and J. Antuchevičienė, “Assessment of third-party logistics providers using a CRITIC–WASPAS approach with interval type-2 fuzzy sets”, Transport, vol. 32, no. 1, pp. 66-78, 2017 doi: 10.3846/16484142.2017.1282381
• [28] Ö. Akçakanat, E. Aksoy, and T. Teker, “CRITIC ve MDL Temelli EDAS yöntemi ile Tr-61 bölgesi bankalarinin performans değerlendirmesi”, Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, vol. 1, no. 32, pp. 1-24, 2018.
• [29] M. Demircioğlu, and İ. T. Coşkun, “CRITIC-MOOSRA yöntemi ve UPS seçimi üzerine bir uygulama”, Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, vol. 27, no. 1, pp. 183-195, 2018.
• [30] D. S. Yakowitz, L. J. Lane, and F. Szidarovszky, “Multi-attribute decision making: dominance with respect to an importance order of the attributes”, Applied Mathematics and Computation, vol. 54, no. 2-3, pp. 167-181, 1993.
• [31] E. Çinaroğlu, “CRITIC Temelli CODAS ve ROV yöntemleri ile ab ülkeleri yaşam kalitesi analizi”, Bingöl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 5, no. 1, pp. 337-364, 2021, doi: 10.33399/biibfad.868418
• [32] A. Mitra, “Grading of raw jute fibres using criteria importance through intercriteria correlation (CRITIC) and range of value (ROV) approach of multi-criteria decision making”, Journal of Natural Fibers, pp. 1-17, 2021, doi: 10.1080/15440478.2021.1951422
• [33] M. E. Mkhalet, S. Aziz, and R. Saidi “The application of Entropy-ROV methods to formulate global performance for selecting the automotive suppliers in Morocco”, Journal of theoretical and applied information technology, vol. 96, no. 16, pp. 5522-5536, 2018.