Title

Performance measurement for accountability in corporate governance : A data envelopment analysis approach

Publication Date

5-16-2008

Abstract

Purpose The purpose of this paper is to show the applicability of data envelopment analysis (DEA) in arriving at an unbiased account of relative performance in a set of companies, using the pharmaceutical industry as an example. Design/methodology/approach A DEA-based income efficiency measure of business performance for the pharmaceutical industry is computed. The pharmaceutical industry, which includes many multinational corporations with complex governance problems, and the strategies that allowed firm efficiency rankings to change over time, over ten recent years, are analyzed. Findings The analyses indicate that the inclines and declines in DEA efficiency rankings are related to the strategic choices made by the upper management. Research limitations/implications The paper attempted to trace firm behavior post hoc to validate the DEA rankings. All relevant firm behavior may not have been captured; the paper only attempted to capture behavior reported in the respectable business press, which may introduce a bias. Practical implications The approach may be ideal to evaluate strategic managers (CEOs, general managers, and presidents) by board of directors, since it relates multiple performance indices to a meta-measure of performance. Another group of beneficiaries include sector financial analysts. The approach adds a new dimension to sector analysis, to compare specific industries and identify the relative rankings of firms on multiple performance indices. Originality/value The paper demonstrates the usefulness of DEA in performance governance measurement by applying it to the pharmaceuticals industry. © 2008, Emerald Group Publishing Limited

Publication Title

Review of Accounting and Finance

Volume

7

Issue

2

First Page

121

Last Page

130

DOI

10.1108/14757700810874100

Source Full-text URL

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1211902

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