Data envelopment analysis and its key variants utilized in the transport sector

Abstract

Having reviewed the international literature on data envelopment analysis (DEA), a non-parametric linear programming method used for efficiency evaluation, the aim of the author with the present article was to fill a gap by collecting and summarizing the essence of the main variants of DEA applied in the transport sector. Thus the DEA CCR, BCC and the Simar-Wilson method are presented. DEA CCR enables the efficiency evaluation under constant, DEA BCC under variable returns to scale. The Simar-Wilson method, also referred to as the truncated bootstrap method, is currently seen as the most reliable technique for hypothesis testing and confidence interval estimation under DEA. Some extensions, like the super-efficient DEA, the principal component analysis and the MNDEA are also highlighted. The variants included in the article were selected on the basis of their application in the transport sector, of which examples are also provided.

Upgrading Multilevel Full Cost Allocation: Case Transport

“…Cost is namely one of the factors determining efficiency. Here more comprehensive and nonparametric methods like data envelopment analysis (DEA) can be utilised [12].…”

“…Let us introduce r 12 = C 1 / C 2 in our example. Substituting by r 12 the missing cost elements can be determined from (4) and (5):( 1 2 )( 1 3 )Using (12) and (13) for C 1 and C 2 respectively, the final cost calculation of profit objects, e.g. the one of profit object A in formula (10), can be executed exactly.…”

Supplier Evaluation with Environmental Aspects and Common DEA Weights

“…The selection of weights in most of the cases happens in advance as part of a group decision; however very often reflect subjective judgement. One of the most important limitations of this method that weights for various supplier performance attributes used in the weighted, additive scoring model are arbitrary set (Markovits-Somogyi, 2011;Markovits-Somogyi et al, 2011;Narasimhan et al, 2001). Thus the final ranking of the supplier is heavily dependent on the assignment of these weights, which are often difficult to specify in an objective manner.…”

Strategic policy instruments in managing freight transport demand

“…Such actions often do not need very expensive development instruments, rather policy-like regulatory measures which offer relatively cheap, easily applicable solutions, first of all via reorganization of the legal background and road pricing. However, wider application of these instruments requires deeper impact analysis in advance like DEA [1]. This article demonstrates that in given regulatory framework such administrative and financial regulatory instruments can lead to significant modifications in the road freight transport.…”