A multi-methodology on building a corporate governance index from the perspectives of academics and practitioners for firms in Greece

• Pages: 295-329
• Published date: 04 April 2016
• Date: 04 April 2016
• DOI: https://doi.org/10.1108/CG-08-2015-0107
• Author: Michail Nerantzidis
• Subject Matter: Strategy,Corporate governance

A multi-methodology on building a

corporate governance index from the

perspectives of academics and

practitioners for firms in Greece

Michail Nerantzidis

Michail Nerantzidis is Dr

in Corporate Governance

based at the Department

of Public Administration,

Panteion University of

Political and Social

Sciences, Athens,

Greece.

Abstract

Purpose –The purpose of this paper is to look inside the “black box” in corporate governance (CG)

measurement, and shed some light on how to construct a transparent, reliable and valid index,

considering equally both the academics and practitioners’ perspectives.

Design/methodology/approach –A synthesized literature review is presented and a CG index is

developed combining the strengths of three different methodologies: the Delphi method, the classical

test theory (CTT) and the analytic hierarchy process (AHP). This approach helps authors to break the

process into separate steps and to select the appropriate techniques to support their decision

regarding the norms, the criteria, the variables and the weights that someone should use to construct a

CG index.

Findings –The authors’ analysis indicates that a well-designed CG index requires a combination of

research methods to identify the best options to solve several methodological issues in index

construction. For the application of this multi-methodology in Greece, the authors used two equal and

independent samples to explore the different perspectives regarding the importance of the index

criteria and sub-criteria. This process provides evidence that the opinion of academics and

practitioners in Greece tend to converge. Moreover, it is found that this multi-methodology produces the

highest variation in CG scores and ranking orders, as opposed to a traditional approach, in measuring

CG disclosure, an important issue with econometric implications.

Research limitations/implications –The limitations of this study are associated with the methods

used.

Practical implications –This paper provides practical implications for investors and commercial

vendors. For the former, it highlights the need to be more cautious and/or suspicious when they use CG

ratings, meaning that they should comprehend the base of the ratings models, and for the latter, it

demonstrates the importance of enhancing the transparency in CG indices construction.

Originality/value –The value of the paper lies in improved understanding of the methodological issues

in constructing CG indices. This is quite interesting because this approach could serve as a roadmap

for other researchers.

Keywords Experts, Analytic hierarchy process, Delphi method, Classical test theory,

Corporate governance index

Paper type Research paper

1. Introduction

In recent years, the concept of good corporate governance (CG) is considered as the

hallmark of a well-run company (Wilkes, 2004). Indeed, institutional investors, shareholders

and stakeholders in general are pushing firms to adopt best practices of CG (Koehn and

Ueng, 2005;Wei-An, 2008)[1], an approach that has been promoted mainly because of the

rapid increase in theoretical (Jensen and Meckling, 1976;Shleifer and Vishny, 1997;Denis

Received 11 August 2015

Revised 27 November 2015

Accepted 15 December 2015

The author would like to thank

the Heraclitus II: Investing in

knowledge society through the

European Social Fund, as this

paper draws on data collected

from the authors PhD thesis.

The author is also very grateful

to Dr John Filos for his

comments and supervision, as

well as to all academics and

practitioners who participated

in his research. Furthermore,

the author would like to thank

Dr Ioannis Tsalavoutas for his

recommendations and the

participants in the 10th

European Academic

Conference on “Internal Audit

and Corporate Governance

and in the International

Conference – International

Business ICIB, for their

comments. Last but not least,

the author would like to thank

the anonymous reviewers and

the editor from the Corporate

Governance: The International

Journal of Business in Society

for their invaluable

suggestions for improvement.

DOI 10.1108/CG-08-2015-0107 VOL. 16 NO. 2 2016, pp. 295-329, © Emerald Group Publishing Limited, ISSN 1472-0701 CORPORATE GOVERNANCE PAGE 295

and McConnell, 2003) and empirical research in CG (Gompers et al., 2003;Larcker et al.,

2005;Bebchuk et al., 2009).

In response to these expanding results, stakeholders in general have started to demand

governance ratings (Sherman, 2004;Wei-An, 2008, p. 12) to avoid undesirable outcomes

(Daines et al., 2010), a new trend that has introduced the issue of measuring the CG quality

(Aguilera and Desender, 2012) both by academics (La Porta et al., 1998;Tsipouri and

Xanthakis, 2004;Cheung et al., 2007) and commercial agencies (GMI Ratings, 2013;Risk

Metrics/Institutional Shareholder Services, 2014;Credit Lyonnais Securities Asia, 2010;

Standard and Poor’s, 2007).

In particular, there is an extensive empirical literature examining the relationship between

CG and a company’s performance either as dependent or independent variables,

respectively (Bauer et al., 2004;Black et al., 2006;Bhagat and Bolton, 2007;Bebchuk et al.,

2009;Cheung et al., 2010;Cheung et al., 2011), indicating that there is no clear evidence

regarding the governance ratings and their performance. To address these mixed results,

an increasing number of studies criticized the way of constructing CG indices and

highlighted the practical problems that needed to be understood and solved (Bhagat et al.,

2008;Bozec and Bozec, 2011;Aguilera and Desender, 2012).

Undoubtedly, the majority of the studies which construct CG indices (for example, Drobetz

et al., 2004;Black et al., 2006;Renders et al., 2010;Lazarides and Drimpetas, 2011)donot

take the criteria of validity and reliability into consideration, an approach that casts doubt

on previous efforts regarding measuring CG.

For this reason, this study shed some light on how to construct a transparent, reliable and

valid index, considering equally the academics and practitioners’ perspectives. In

particular, this is the first study – as far as we know – that provides advance knowledge

regarding the design and implementation of CG index. This is quite interesting because it

contributes to the discussion on the forward research agenda of CG index construction.

The remaining of this paper is organized as follows. The next section reviews the literature.

Section 3 describes the theoretical background in CG index development, while the

application of the proposed model is presented in Section 4. Section 5 discusses the

contribution of this methodology, as opposed to another approach in measuring the CG

disclosure. Finally, the conclusions and research perspectives are exposed in Section 6.

2. Literature review

2.1 Literature review on measuring corporate governance

In the aftermath of Enron’s collapse, varieties of academic and commercial indices are

being constructed to measure the CG (Bozec and Bozec, 2011). This widespread CG

evaluation reflects the stakeholders’ desire to improve transparency, accountability,

responsibility and, of course, economic performance (Aguilera and Cuervo-Cazurra, 2009;

Ntim et al., 2012). Therefore, CG rating systems could be used as a powerful indicator of

the extent to which a company is currently adding, or has the potential to add in the future

shareholder value (Mallin, 2001, p. 257). Thus, the premise of CG indices could be

summarized as follows:

[. . .] Companies that focus on CG and transparency will, over time, generate superior returns

and economic performance and lower their cost of capital (Sherman, 2004,p.6).

This means that the basic underlying assumption of CG indices is that they adequately

capture the quality of CG. However, what is the meaning of capturing the quality of CG?

Does it mean that the construction captures the firm’s level governance quality or the

disclosure quality (Bhagat et al., 2008;Aguilera and Desender, 2012)? In literature review,

there is a variety of studies in emerging markets (Klapper and Love, 2004), as well as in

Europe (Drobetz et al., 2004;Tsipouri and Xanthakis, 2004;Florou and Galarniotis, 2007),

the USA (Brown and Caylor, 2006;Bhagat and Bolton, 2007;Bebchuk et al., 2009) and Asia

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(Black et al., 2006;Cheung et al., 2007), which use different CG indices to capture the

“latent variable” of CG quality. This illustrates that these studies benchmark the voluntary

CG disclosure, with the expectation to capture the quality of the firms’ governance.

However, despite the great effort of the empirical studies to measure the CG disclosure,

there is an extensive literature review that criticizes the methodological challenges of this

procedure (Bozec and Bozec, 2011;Aguilera and Desender, 2012). For instance, there is

a theoretical gap among the variables (Florou and Galarniotis, 2007), the criteria

(Nerantzidis, 2015), the weights (Graafland et al., 2004;Bozec and Bozec, 2011) and the

norms that someone should use to construct a reliable and valid index. These theoretical

gaps support the idea of Bhagat et al. (2008, p. 1803), according to which, the CG indices

are highly imperfect instruments.

2.2 Main criteria in index construction

According to literature review, there are two main criteria that researchers should take into

account when constructing indices: reliability and validity (Krippendorff, 2013). However, a

prerequisite for the index construction is a prior investigation of the country’s environment,

which, in the case of CG, is the main characteristic of each country’s CG framework

(Figure 1).

Based on the first criterion, an index is considered as reliable if the results can be

replicated by another researcher (Marston and Shrives, 1991, p. 197). Thus, in case the

scores are extracted from CG statements (CGS) and remain constant over time, then

there is no obstacle to repetition. Moreover, the developments in CG reporting give the

opportunity to researchers to decide more objectively whether a variable is disclosed or

not. This means that the problem of “applicability” (that probably companies will not

provide any information regarding some provisions) is not such an important issue for our

analysis, as it is reflected in EU Directives (2006/46/EC and 2007/63/EC). However, it is

worth mentioning that the theory of measurement indicates that researchers have to pay

attention to statistical items analysis when constructing indices (Tsipouri and Xanthakis,

2004;Florou and Galarniotis, 2007). This means that researchers (in compliance studies

and CG indices) prefer not to rely on statistical methods for their analysis, namely, classical

test theory (CTT) (Allen and Yen, 2002;Crocker and Algina, 2006) and item response

theory (IRT) (Hambleton et al., 1991;Embretson and Reise, 2000) but to calculate ratings

using a simplistic procedure: 1 point if the provision is disclosed and 0 otherwise. In fact,

this practice would be excellent in studies that present compliance scores; however, it is

not “ideal” in constructing indices because it does not take into account the effects and

interrelationships between variables (Cox, 1972;Edelen and Reeve, 2007).

Referring to the second criterion, an index can be considered as valid if it measures what

its user claims it measures (Krippendorff, 2013, p. 329). But does this really happen in CG

index construction? As we can see in empirical studies (Black, 2001;Klein et al., 2005;

Black et al., 2006;Bebchuk et al., 2009;Cheung et al., 2010), there is no consensus on one

particular CG index or on a measuring approach of CG (Marston and Shrives, 1991,

p. 198). However, this is one facet of the validity problem. In particular, as Krippendorff

(2013, p. 334) mentioned, researchers have to consider a plethora of validity dimensions

such as construct validity, content validity and criterion-related validity. Nevertheless,

researchers in compliance studies and CG indices have the tendency to “overlook” the

criterion of validity either as a whole (Klapper and Love, 2004;Tsipouri and Xanthakis,

2004;Cheung et al., 2007;Lazarides and Drimpetas, 2011) or partially (Tsalavoutas et al.,

2010;Nerantzidis, 2015).

2.3 Prior CG indices

Several empirical studies have constructed CG indexes. As it can be seen in Table I, these

are classified in two categories. On the first panel (Panel A), the commercial CG indices

(GMI Ratings, 2013;Institutional Shareholder Services, 2014;Credit Lyonnais Securities

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