DEA and its use in the regulation of water companies

Abstract

This paper begins with an introduction to the basic principles of data envelopment analysis (DEA). DEA is a linear programming-based method for assessing the productive efficiencies of operating units such as bank branches, sales outlets, schools or individuals. This paper then goes on to describe the use of DEA in the regulatory framework. Regulation, employed to safeguard the public interest, is increasingly playing an major role in Great Britain and other countries in the aftermath of the privatisation of publicly owned companies including utilities which still enjoy a good degree of monopoly power. This paper gives an account of the use of DEA to estimate potential cost savings at water companies in the context of the price review conducted by the regulator of water companies in England and Wales in 1994. It also highlights certain generic issues arising in the use of DEA in the regulatory context. This paper should prove of interest both to those who want to know about DEA as a tool in general and to those interested in efficiency measurement under regulation.

Publication DOI: https://doi.org/10.1016/S0377-2217(99)00436-1
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
Aston University (General)
Additional Information: Copyright © 2000 Elsevier Science B.V. This accepted manuscript version is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License [https://creativecommons.org/licenses/by-nc-nd/4.0/]
Uncontrolled Keywords: Data envelopment analysis,Performance measurement,Regulation,Water industry,Information Systems and Management,Management Science and Operations Research,Statistics, Probability and Uncertainty,Applied Mathematics,Modelling and Simulation,Transportation
Publication ISSN: 1872-6860
Last Modified: 04 Apr 2024 07:10
Date Deposited: 30 Jun 2023 14:59
Full Text Link:
Related URLs: https://www.sci ... 377221799004361 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2000-11-16
Authors: Thanassoulis, Emmanuel (ORCID Profile 0000-0002-3769-5374)

Export / Share Citation


Statistics

Additional statistics for this record