Measuring Managerial Ability Using a Two‐stage SFA‐DEA Approach

• Published date: 01 October 2016
• Author: Giovanni D'Orio,Graziella Bonanno,Stefania Veltri
• Date: 01 October 2016
• DOI: http://doi.org/10.1002/kpm.1528

■Research Article

Measuring Managerial Ability Using a

Two-stage SFA-DEA Approach

Stefania Veltri

1

*, Giovanni D’Orio

2

and Graziella Bonanno

3

1

Department of Business Administration and Law, University of Calabria, Arcavacata di Rende, Italy

2

Department of Economics, Statistics and Finance, University of Calabria, Arcavacata di Rende, Italy

3

Department of Computer, Control, and Management Engineering ‘Antonio Ruberti’- Sapienza University,

Rome

The article focuses on the measurement of a relevant component of the human capital, the managerial ability (MA).

Quantifying MA is central to management literature. Prior research indicates that manager specific features (ability,

talent, reputation, or style) affect economic outcomes but, in management literature, most of the measures used in

archival research also reflect significant aspects of the firm that are outside of management’s control. The article aims

to find a measure, better than existing ones, which allows distinguishing the effect of the manager from the effect of

the firm in creating firm value. The article uses the “two-stage SFA-DEA”approach, in which both Stochastic Frontier

Approach (SFA) and Data Envelopment Analysis (DEA) are used to estimate the efficiency scores firms adopt to

derive a measure of MA. The idea is to obtain a measure of MA as a residue of the inefficiency equation of SFA

and to use it as a new input to insert in the “second/third”DEA stage. Italian banks have been chosen as the sample

to investigate and implement the model. The differences in results with or without this new MA measure provide

evidence of the existence of this contribution. The originality of the article consists in the proposition of a new model

to measure MA, which outperforms the alternative measures, simple to use as it is based on easily obtainable financial

data and available for a broad cross section of firms, so opening the door to a wide array of studies previously difficult

to conduct. Copyright © 2016 John Wiley & Sons, Ltd.

INTRODUCTION

Managing IC efficiently (that is, managing and

transforming various intangible resources to create

or maximize value) is considered the key to sustain

competitive edge for each kind of organization

(Kujansivu, 2009; Kweh et al., 2013; Veltri &

Bronzetti, 2015). The measurement of intellectual

capital (IC) and its contribution to the firm’s value

is one of the central theme of the IC literature, since

from the pioneering article of Bontis (1998)

(Andrikopoulos, 2010; Booker et al., 2008; Dumay,

2014; Serenko & Bontis, 2004; Veltri, 2012). Several

are the measurement method proposed and used in

literature, both quantitative and qualitative (Pulic,

2000; Veltri, 2014). Nonetheless, there is no consen-

sus on IC measurement (Dumay, 2014; Uziene,

2010), and many frameworks have been criticized

as they focus on single dimension on IC, without

taking into consideration the complex process of

IC efficiency management, and to be subjective

(Feroz et al., 2003). Recently, data envelopment

analysis (DEA), a non-parametric approach, has be-

come fashionable in the IC management research

(e.g. Campisi & Costa, 2008; Kweh et al., 2014a;

Lu & Hung, 2011; Lu et al., 2010; Wu et al., 2006;

Yang & Chen, 2010), also because DEA allows mul-

tiple inputs and multiple outputs to be evaluated

concurrently without requiring prior information

about the relationship among multiple performance

measures and interactions among various perfor-

mance measures in an objective way (Alfano and

D’Orio, 2002).

In this study, the authors also employ DEA to

evaluate the IC efficiency management, but this

study is different from others using DEA to measure

IC (Kweh et al., 2013; Leitner et al., 2005; Yalama &

Coskun, 2007) for two main reasons. The first reason

is that the paper do not use just the DEA approach,

but a more complex approach, in which both sto-

chastic frontier approach (SFA) and DEA are used

*Correspondence to: Stefania Veltri, Department of Business Ad-

ministration and Law, University of Calabria, Cubo 3C, Ponte P.

Bucci, 87040 Arcavacata di Rende (CS), Italy.

E-mail: stefania.veltri@unical.it

Knowledge and Process Management

Volume 23 Number 4 pp 247–258 (2016)

Published online in Wiley Online Library

(www.wileyonlinelibrary.com) DOI: 10.1002/kpm.1528

Copyright © 2016 John Wiley & Sons, Ltd.