Abstract
ABSTRACTThis study is a literature review on corporate governance. Its objective is to consolidate our knowledge in this field, examine its evolution, and propose avenues for future research. In our review of the past and present literature on various governance measures and their effect on firm performance, we find that the empirical results are mixed for many of the governance mechanisms studied. We propose that these mixed results may be due to applying a “one size fits all” set of governance measures, which is not effective for all types of firms due to the complexity of organizations and the differences in ownership structures. We therefore explore more technologically advanced methodologies, including machine learning. We believe that this line of research could not only improve and refine existing governance measures but also allow us to better target which set of mechanisms might be appropriate for a firm based on its particular characteristics. We encourage future researchers in corporate governance to consider this approach in order to shed light on and fill the gaps in this area of research.
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