Measuring congestion in data envelopment analysis without solving any models

Measuring congestion in data envelopment analysis with common weights

measuring congestion in data envelopment analysis with common weights

Congestion Status Identification Using Slack Based Models in Data Envelopment Analysis

Congestion is a wasteful stage of the production process where outputs are reduced due to excessive amount of inputs. There are several approaches in data envelopment analysis (DEA) literatures to treat congestion. The concept of strong and weak congestion first developed by Tone and Sahoo [Tone, K., Sahoo, B.K., 2004. Degree of scale economies and congestion: A unified DEA approach. European J...

Generalized Fuzzy Inverse Data envelopment Analysis Models

Traditional DEA models do not deal with imprecise data and assume that the data for all inputs and outputs are known exactly. Inverse DEA models can be used to estimate inputs for a DMU when some or all outputs and efficiency level of this DMU are increased or preserved. this paper studies the inverse DEA for fuzzy data. This paper proposes generalized inverse DEA in fuzzy data envelopment anal...

Efficiency of Centralized Structures in Data Envelopment Analysis Ratio Models

This paper investigates the centralized resource allocation with centralized structures by using the data envelopment analysis-ratio (DEA-R) models. To this end, it proposes a method to determine the resource allocation of centralized structures such that the ratio of inputs to outputs are minimized.