ESTIMATING TECHNICAL AND SCALE EFFICIENCIES OF EUROPEAN RAIL TRANSPORT USING BOOTSTRAP DATA ENVELOPMENT ANALYSIS
ERWIN T. J. LIN *
Department of Marketing and Logistics, Mingdao University, 369 Wen-Hua Rd., Peetow, Changhua 52345, Taiwan.
*Author to whom correspondence should be addressed.
Abstract
Rail transport has long played an important role in the economic development for a country; therefore enhancing its operating performance is a crucial issue to be sustainable in a competitive context. Many researchers have paid attention to measuring performance of rail transport using data envelopment analysis (DEA) in the past several decades, however, DEA has been criticized for not taking into account statistical error and lacking any hypothesis testing. This study applies Bootstrap DEA (BDEA) method to estimate the technical efficiency and confidence intervals, as well as scale efficiency for some selected European Union member states’ rail companies in the year of 2010.
The empirical results indicate that using DEA method ten (eleven) railways are evaluated as efficient, and the average technical efficiency is 0.724 (0.773) based on the assumptions of constant (variable) returns to scale technology. While using BDEA, none of 26 railways is evaluated as efficient and the counterparts of efficiencies are 0.396 and 0.431, respectively, implying that the DEA method overestimates the efficiencies of railways under study. The results also indicate that the 90% confidence intervals of average efficiency estimated by BDEA are (0.357, 0.524), from which one can obtain the outputs that each railway should expand, so as to be efficient. Furthermore, the result also suggests that null hypothesis of constant returns to scale cannot be rejected. Finally, based on the results some strategies for improving railways’ performance and possible avenues of future research are proposed.
Keywords: Data envelopment analysis, bootstrap DEA, rail transport, performance estimation, confidence interval