Keywords
PUBLIC UTILITIES
INPUT-OUTPUT ANALYSIS
LINEAR PROGRAMMING
PUBLIC TRANSPORT
GESTIÓN DE RECURSOS
SERVICIOS DE UTILIDAD PÚBLICA
ANÁLISIS INSUMO-PRODUCTO
PROGRAMACIÓN LINEAL
TRANSPORTE PÚBLICO
How to Cite
Abstract
This article represents an application of frontier models for the evaluation of the relative technical efficiency in the regulated public transport sector in Costa Rica. Using data from a survey made by Autoridad Reguladora de Servicios Públicos (ARESEP) in 2009 a data envelopment analysis (DEA) model was computed to obtain the relative efficiency for the public service provided in interregional public transit routes around the country. As output variables, the number of passenger for kilometer of travel and monthly average of passenger per bus were used. As input variables, we used the spending of many key aspects to provide the service. Based on the model, the 29 interregional routes were classified and ranked by their respective efficiency. In addition, for those classified as inefficient, some enhancement factors were provided.References
Andersen, P., & Petersen, N. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261-1264.
Barnum, D., Hart, J., y McNeil, S. (2007). Comparing the Efficiency of Public Transportation Subunits Using Data Envelope Analysis. Journal of Public Transportation, 10(2), 1-16. https://doi.org/10.5038/2375-0901.10.2.1
Barnum, D. T., Tandon, S., & McNeil, S. (2008). Comparing the Performance of Bus Routes after Adjusting for the Environment Using Data Envelopment Analysis. Journal of Transportation Engineering, 134(2), 77-85. https://doi.org/10.1061/(ASCE)0733-947X(2008)134:2(77)
Bogetoft, P., y Otto, L. (2015). Benchmark and Frontier Analysis Using DEA and SFA. Viena, Austria: CRAN-Project. Recuperado de https://cran.r-project.org/web/packages/Benchmarking/Benchmarking.pdf
Bonifaz F., J. L., & Santin, D. (2000). Eficiencia relativa de las empresas distribuidoras de energía eléctrica en el Perú: una aplicación del análisis envolvente de datos (DEA). Apuntes: Revista de Ciencias Sociales, (47), 111-138. https://doi.org/10.21678/apuntes.47.499
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
Coelli, T., Estache, A., Perelman, S., & Trujillo, L. (2003). Una introducción a las medidas de eficiencia para reguladores de servicios públicos y de transporte. Colombia: Banco Mundial en coedición con Alfaomega Colombiana S.A.
Coelli, T., Passada, D., O'Donnell, C., & Battese, G. (2005). An Introduction to Efficiency and Productivity Analysis (2° ed.). Boston: Kluwer Academic.
Daouia, A., & Laurent, T. (2015). Partial Frontier Analysis. Viena, Austria: CRAN-Project. Recuperado de https://cran.r-project.org/web/packages/frontiles/frontiles.pdf
Daraio, C., & Simar, L. (2007). Advanced Robust and Nonparametric Methods in Efficiency Analysis. Nueva York, Estados Unidos: Springer Science+Business Media, LLC.
De Borger, B., Kerstens, K., & Costa, Á. (2002). Public transit performance: What does one learn from frontier studies? Transport Reviews, 22(1), 1-38. https://doi.org/10.1080/01441640010020313
Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253. https://doi.org/10.2307/2343100
Garcia, I. M. (2009). Technical and Scale Efficiency in Spanish Urban Transport: Estimating with Data Envelopment Analysis. Advances in Operations Research, 2009, 1-15. https://doi.org/10.1155/2009/721279
Hidalgo, J., & Navarro, D. (2016). Análisis de la Eficiencia Técnica del Sector de Transporte Público: Costa Rica 2009. (Tesis para optar por el grado de Licenciatura), San José, Costa Rica, Universidad de Costa Rica.
Hong, Y. P., & Pan, C.-T. (1992). Rank-Revealing QR Factorizations and the Singular Value Decomposition. Mathematics of Computation, 58(197), 213-232. https://doi.org/10.2307/2153029
Karlaftis, M., Gleason, J., y Barnum, D. (2013). Bibliography of Urban Transit Data Envelopment Analysis (DEA) Publications. Recuperado de https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1350583
Komsta, L. (2015). Tests for Outliers. Viena, Austria: CRAN-Project. Recuperado de https://cran.r-project.org/web/packages/outliers/outliers.pdf
LCR Logística. (2002). Consultoría para la elaboración de una encuesta sobre los operadores del transporte reminerado de personas, modalidad autobús, en todo el país. Informe Final de la licitación restringida No. I-2001 de ARESEP [documento no publicado], San José, Costa Rica.
Lovell, C. A. K., & Rouse, A. P. B. (2003). Equivalent standard DEA models to provide super-efficiency scores. Journal of the Operational Research Society, 54(1), 101-108. https://doi.org/10.1057/palgrave.jors.2601483
Novaes, A. G. N., Silveira, S. F., & Medeiros, H. C. (2010). Efficiency and productivity analysis of the interstate bus transportation industry in Brazil. Pesquisa Operacional, 30(2), 465-485. https://doi.org/10.1590/S0101-74382010000200012
Penny, K. (1996). Appropriate Critical Values When Testing for a Single Multivariate Outlier by Using the Mahalanobis Distance. Journal of the Royal Statistical Society. Series C (Applied Statistics), 45(1), 73–81. https://doi.org/10.2307/2986224
Sampaio, B. R., Neto, O. L., & Sampaio, Y. (2008). Efficiency analysis of public transport systems: Lessons for institutional planning. Transportation Research Part A: Policy and Practice, 42(3), 445-454. https://doi.org/10.1016/j.tra.2008.01.006
Sheth, C., Triantis, K., & Teodorović, D. (2007). Performance evaluation of bus routes: A provider and passenger perspective. Transportation Research Part E: Logistics and Transportation Review, 43(4), 453-478. https://doi.org/10.1016/j.tre.2005.09.010
Wilson, P. W. (2008). FEAR: A software package for frontier efficiency analysis with R. Socio-Economic Planning Sciences, 42(4), 247-254. https://doi.org/10.1016/j.seps.2007.02.001