Improved efficiency measures through directional distance formulation of data envelopment analysis

被引：13

作者：

Diabat, Ali ^{[1
]}

Shetty, Udaya ^{[2
]}

Pakkala, T. P. M. ^{[3
]}

机构：

[1] Masdar Inst Sci & Technol, Dept Engn Syst & Management, Abu Dhabi, U Arab Emirates

[2] Govt Karnataka, Directorate Econ & Stat, Udupi 574104, India

[3] Mangalore Univ, Dept PG Studies & Res Stat, Mangalagangothri 574199, Karnataka, India

来源：

ANNALS OF OPERATIONS RESEARCH | 2015年 / 229卷 / 01期

关键词：

Data envelopment analysis; Efficiency; Non-radial efficiency; Directional distance function; SLACKS-BASED MEASURE; TRANSLATION-INVARIANCE; UNDESIRABLE OUTPUTS; DEA;

D O I：

10.1007/s10479-013-1470-9

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

This paper develops a model for an improved efficiency measure through directional distance formulation of data envelopment analysis. It deals with cases where positive and negative values co-exist as production factors. The developed model has properties such as scalar quantity for measuring efficiency and it identifies all sources of inefficiency. The measure is weakly monotonic; units and translation do not vary with respect to inputs and outputs. The proposed model, under some restrictions, reduces to basic Data Envelopment Analysis (DEA) models such as Charnes-Cooper-Rhodes (CCR), Banker-Charnes-Cooper (BCC), and a slack based model (SBM). In addition to the above, the proposed model includes the closest targets for a given inefficient unit to achieve efficiency with less effort. The proposed model is validated using a case study done on Information Technology firms operating in India.

引用

页码：325 / 346

页数：22

共 24 条

[1] Bankruptcy forecasting:: An empirical comparison of AdaBoost and neural networks [J].