Efficiency evaluation of urban transport using the DEA method
Research background: An efficient and effectively functioning transport of a city is of great importance both for people who reside within it, as well as companies doing business there. It is an integral part of modern economy and society in the dimension of production and consumption. However, apart from having a positive impact, transport also carries many social costs including congestion, traffic accidents and a negative influence on the natural environment. Consequently, urban transport is an increasingly important area of city management.
Purpose of the article: The aim of this study is to assess the technological effectiveness of transport in selected Polish cities. The author created a ranking of cities and identified ways of improve efficiency.
Methods: The test procedure used the non-parametric method of Data Envelopment Analysis (DEA). The data for analysis was drawn from the Local Data Bank of the Central Statistical Office defining expenses in the transport section as well as data on the condition and use of transport infrastructure. Calculations were made using Frontier Analyst Application software dedicated to the DEA method. Performance results were determined using the BCC model. The analysis was con-ducted for 18 cities with district status from 150 to 500 thousands inhabitants.
Findings & Value added: The main result is the author’s ranking of transport effectiveness in Polish cities. The analysis showed that urban transport is characterized by a rather low technological effectiveness. Full technological efficiency has been shown by five cities: Białystok, Sosonowiec, Bielsko-Biała, Olsztyn and Rzeszów. An average of the urban transport efficiency reached 51.1%. The lowest effectiveness was only 2.77%. This means that a substantial number of cities do not use optimal inputs. The DEA method enriches the methodology used by scientists to study transport effectiveness.
Banker, R. D., Charnes, A., Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9). doi: 10.1287/mnsc.30.9.1078.
Balcerzak, A. P., Kliestik, T., Streimikiene, D., & Smrčka L. (2017). Non-parametric approach to measuring the efficiency of banking sectors in European Union Countries. Acta Polytechnica Hungarica, 14(7). doi: 10.12700/APH. 14.7.2017.7.4.
Balcerzak, A. P., & Pietrzak, M. B. (2017). Digital economy in Visegrad Coutnries. Multiple-criteria decision analysis at regional level in the years 2012 and 2015. Journal of Competitiveness, 9(2). doi: 10.7441/joc.2017.02.01.
Bartoszewicz, A. & Lelusz, H. (2016). Conception and directions of using the DEA method to measure the efficiency of local governments - selected aspects. Finanse, Rynki Finansowe, Ubezpieczenia, 2(80). doi: 10.18276/frfu. 2016.2.80/2-23.
Brzezicki, Ł. (2016). Efficiency of the education proces in higher vocational schools in 2012. Acta Universitatis Lodziensis Folia Oeconomica 4(323). doi: 10.18778/0208-6018.323.04.
Charnes, A., Cooper, W. W., & Rhodes E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6). doi: 10.1016/0377-2217(78)90138-8.
Cheba, K., & Szopik-Depczyńska, K. (2017). Multidimensional comparative analysis of the competitive capacity of the European Union countries and geographical regions. Oeconomia Copernicana, 8(4). doi: 10.24136/oc.v8i4.30.
Chodakowska, E. (2015). The future of evaluation of lower secondary school’s management. Business, Management and Education, 13(1). doi: 10.3846/bme .2015.256.
Coelli, T. J., & Prasada Rao, D. S. (2005). Total factor productivity growth in agriculture: a malmquist index analysis of 93 countries, 1980-2000. Agricultural Economics, 32(1). doi: 10.1111/j.0169-5150.2004.00018.x.
Ćwiąkała-Małys, A., & Nowak, W. (2009). Methods of classifying DEA models. Badania Operacyjnie i Decyzje, 3.
Díaz, G., & Charles V. (2016). Regulatory design and technical efficiency: public transport in France. Journal of Regulatory Economics, 50(3). doi: 10.1007/s11149-016-9308-4.
European Commission (2010). Toledo Urban Development Declaration. Retrieved from: http://ec.europa.eu/regional_policy/archive/newsroom/pdf/201006_toledo _declaration_en.pdf (20.02.2017).
European Commission (2013). Together towards competitive and resource-efficient urban mobility. Retrieved from: https://ec.europa.eu/transport/sites/ transport/files/themes/urban/doc/ump/com(2013)913_en.pdf (15.02.2017).
Guillermo, D., & Vincent, Ch. (2016). Regulatory design and technical efficiency: public transport in France. Journal of Regulatory Economics, 50(3). doi: 10.7835/ccwp-2015-11-0020.
Guzik, B. (2009). Basic analytical capabilities of the CCR-DEA model. Operations Research and Decision, 19(1).
Hajduk, S. (2016). Assessment of urban transport - a comparative analysis of selected cities by taxonomic methods. Economics and Management, 8(4). doi: 10.1515/emj-2016-0034.
Hajduk, S. (2015). The spatial management vs. innovativeness of medium-size cities of poland. Procedia - Social and Behavioral Sciences, 213. doi: 10.1016/j.sbspro.2015.11.499.
Hollingsworth, B. (2008). The measurement of efficiency and productivity of health delivery. Health Economics, 17(10). doi: 10.1002/hec.1391.
Jiang, Q. J., Baran, J., & Wysokiński, M. (2016). Comparison of agriculture efficiency of Chinese provinces. Roczniki Naukowe Stowarzyszenia Ekonomistów Rolnictwa i Agrobiznesu, 18(2).
Jill, J. (2006). Data envelopment analysis and its application to the measurement of efficiency in higher education. Economics of Education Review, 25(3). doi: 10.1016/j.econedurev.2005.02.005.
Karlafis, M. G. (2004). A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. European Journal of Operational Research, 152(2). doi: 10.1016/s0377-2217(03)00029-8.
Kluczek, A. (2017). Assessing measures of energy efficiency improvement opportunities in the industry. LogForum, 13(1). doi: 10.17270/J.LOG.2017.1.3.
Kozłowska, J. (2014). Application of DEA method in measuring technical efficiency of polish service sector companies. Scientific Papers of Silesian University of Technology. Organization and Management Series, 73(1919).
Liu, J. S., Lu, L. Y. Y., & Lin, B. J. Y. (2013). Data envelopment analysis 1978-2010: a citation-based literature survey. Omega, 41(1). doi: 10.1016/j.omega.2010.12.006 .
Ministry of Infrastructure and Development (2015). National urban policy 2023. Retrieved from: http://www.mr.gov.pl/media/11579/Krajowa_Polityka _Miejska_2023.pdf (13.02.2017).
Ministry of Transport, Construction and Maritime (2013). Transport Development Strategy until 2020 (with outlook until 2030). Retrieved from: https://mib.gov.pl/media/3511/Strategia_Rozwoju_Transportu_do_2020_roku.pdf (18.02.2017).
Motevali Haghighi, S., Torabi S. A., & Ghasemi, R. (2016). An integrated approach for performance evaluation in sustainable supply chain network (with a case study). Journal of Cleaner Production, 137. doi:10.1016/j.jclepro. 2016.07.119.
Nazarko. J., Komud, M., Kuźmicz, K., Szubzda, E., & Urban, J. (2008). The DEA method in public sector institutions efficiency analysis on the basis of higher education institutions. Operations Research and Decision, 18(4).
Noworól, A. (2011). City management - theoretical foundations. In B. Kożuch & C. Kochalski (Eds.). Strategic city management in theory and practice of the Poznan City Hall. Kraków: Instytut Spraw Publicznych Uniwersytetu Jagiellońskiego.
Pact of Amsterdam (2016). Urban Agenda for the EU. Retrieved from http://ec.europa.eu/regional_policy/sources/policy/themes/urban-development/ agenda/pact-of-amsterdam.pdf (10.02.2017).
Pietrzak, M. B., Balcerzak, A. P., Gajdos, A., & Arendt, Ł (2017). Entrepreneurial environment at regional level: the case of Polish path towards sustainable socio-economic development. Entrepreneurship and Sustainability Issues, 5(2). doi: 10.9770/jesi.2017.5.2(2).
Ramzi, S., Afonso, A. & Ayadi, A. (2016). Assessment of efficiency in basic and secondary education in Tunisia: a regional analysis. International Journal of Educational Development, 51. doi: 10.2139/ssrn.2228576.
Retzlaff-Robertsa, D., Changb, C. F., & Rubinb, R. M. (2004). Technical efficiency in the use of health care resources: a comparison of OECD countries. Health Policy, 69. doi: 10.1016/j.healthpol.2003.12.002.
Sarkar, S. (2016). Application of PCA and DEA to recognize the true of a firm: a case with primary schools. Benchmarking: An International Journal, 23(3). doi: 10.1108/bij-11-2014-0100.
Sarrico, C. S. (2007). Data envelopment analysis: A comprehensive text with models, application, references and DEA-solver software. Journal of the Operational Research Society 52(12). doi: 10.1057/palgrave.jors.2601257.
White Paper (2011). Roadmap to a single European transport area - towards a competitive and resource efficient transport system European Commission. Retrieved from http://ec.europa.eu/transport/sites/transport/files/themes/strategies/ doc/2011_white_paper _en.pdf (10.02.2017).
Wiegmans, B. & Dekker, S. (2016). Benchmarking deep-sea port performance in the Hamburg-Le Havre range. Benchmarking: An International Journal, 23(1). doi: 10.1108/BIJ-04-2013-0050.
Wiśnicki, B., Chybowski, L., & Czarnecki, M. (2017). Analysis of the efficiency of port container terminals with the use of the data envelopment analysis method of relative productivity evaluation. Management Systems in Production Engineering, 1(25). doi: 10.1515/mspe-2017-0001.
This work is licensed under a Creative Commons Attribution 4.0 International License.