The paper deals with models and methods for evaluation of efficiency of production units. The standard modeling approach for evaluation of efficiency is data envelopment analysis (DEA) based on the definition of efficiency as the ratio of outputs produced by the unit and inputs spent in the production process. Standard data envelopment analysis models divide the units into inefficient and effic...

this paper addresses a multi-criteria decision based methodology to develop a road network cost function for route finding analysis in a geographic information system (gis). over the years, several studies relating to route planning process in gis and intelligent transportation systems (its) have been conducted, most of which rely on the use of one-dimensional variables like distance or time as...

Stepwise benchmark target selection in data envelopment analysis (DEA) is a realistic and effective method by which inefficient decision-making units (DMUs) can choose benchmarks in a stepwise manner. We propose, for the construction of a benchmarking network (i.e., a network structure consisting of an alternative sequence of benchmark targets), an approach that integrates the cross-efficiency ...

The correlated models are introduced in this article regarding revenue efficiency and profit efficiency in dynamic network production systems. The proposed models are not only applicable in measuring efficiency of divisional, periodical and overall efficiencies, but recognizing the exact sources of inefficiency with respect to revenue and profit efficiencies. Two numerical examples, consisting ...

in very recent papers asmild et al. (2003) and halved et al. (2004) based upon potential improvement efficiency index (bogetoft and hougaard,1999) have suggested an alternative nonparametric frontier approach namely multi-directional inefficiency analysis (mea) to estimate the performance efficiency. mea has many advantages over data envelopment analysis (dea) as the standard nonparametric fron...

The authors model the performance of DMUs (decision-making units) using the directional distance function within a two-stage framework. In the first stage of production, DMUs use inputs to produce an intermediate output. In stage 2, the intermediate output is used to produce final outputs. In contrast to DEA (data envelopment analysis) models, the two-stage directional model accounts for a netw...

In this paper, Data Envelopment Analysis (DEA) and super efficient DEA (SE-DEA) are employed to measure the efficiency of Chinese commercial banks. Incorporating Tobit regression analysis, the determinants of banking efficiency are investigated based on Panel data. Overall, the DEA results show relatively low average efficiency levels and state-owned banks are more inefficient than that of join...

Data Envelopment Analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs) with multiple inputs and outputs. The traditional DEA treats decision making units under evaluation as black boxes and calculates their efficiencies with first inputs and last outputs. This carries the notion of missing some intermediate measures in the process of changing the inputs to...

The classic data envelopment analysis (DEA) models have overlooked the intermediate products, internal interactions and the absence of data certainty; and deal with analyzing the network within the “Black Box” mode. This results in the loss of important information and at times a considerable modification occurs in efficiency results. In this paper, a Three-stage network model is considered wit...

The hub location problem is employed for many real applications, including delivery, airline and telecommunication systems and so on. This work investigates on hierarchical hub network in which a three-level network is developed. The central hubs are considered at the first level, at the second level, hubs are assumed which are allocated to central hubs and the remaining nodes are at the third ...