Preference, Production and Performance in Data Envelopment Analysis

Abstract

In this paper, we re-examine Data Envelopment Analysis models from perspectives of preference order, production set and performance measure. we investigate the relationship between Data Envelopment Analysis (DEA) and Multiple Criteria Decision Making Theory.There are three key building blocks in a DEA model: preference order, production possibility set and performance measure. It is shown in this work that many known DEA models and new ones, can be derived via this approach.

DEA models with undesirable inputs and outputs

“…In the standard DEA models like CCR and BCC, the classic Pareto preference is assumed, as in this work. However, we emphasize there are many real applications where different preferences are indeed useful, see Liu et al (2006) and Zhang et al (2009) for some examples. Let X = (x 1 , .…”

“…Our main idea is to examine them within the general framework proposed in Liu et al (2006), where some essential building blocks of a DEA model were identified and illustrated. The principal objective of this paper is to discuss the free disposability assumptions and to describe a number of different performance measures or metric functions with attractive properties in the presence of undesirable inputs and outputs and negative data.…”

“…We also discuss some relationship among the existing approaches. We undertake these investigations by utilizing some of the ideas used in Liu et al (2006).…”

“…In Sect. 3 we summarize some metrics used in DEA models following the ideas used in Liu et al (2006). In Sect.…”

Efficiency evaluation of basic research in China

“…Similar models were studied in (Zhu 1996) to study economical development for cities in China. For more explanations of these models, see (Liu, Wu and Sharp, 2004). In the above DEA models, it is impossible to rank the efficient DMUs as their efficiency scores are the unit.…”