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.

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