Board of directors’ effectiveness and firm performance of Sri Lankan listed companies – A partial least squares structural equation modeling approach - Tharsika, K. (University of Kelaniya, Sri Lanka, 2023)
The ongoing discourse on the connection between the effective board of directors and firm performance will remain to be an important area of research study for a very long time. In addition, despite the vast amount of research conducted on the relationship between individual characteristics of the board members and firm performance, there are few studies that concentrate on the characteristics of the entire board as a single variable. This paper investigates the empirical study of the relationship between the effectiveness of the board of directors and the firm performance of listed companies in Sri Lanka. The study employed a panel data approach over a five-year period from 2018 to 2022 with a sample of 100 companies listed on the Colombo Stock Exchange. It has two latent variables: Effectiveness of the board of directors as an independent variable with four indicators (board size, board independence, board meeting, and board gender diversity), and firm performance of the firm as a dependent variable with two indicators (return on assets and return on equity). Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyze the data. Empirical results demonstrate that an effective board is positively associated with firm performance. The findings are crucial for stakeholders, policymakers, and regulatory bodies to increase the efficacy of their board of directors and boost Sri Lankan companies' performance. This study contributes to the existing literature by investigating for the first time, using the PLS-SEM, the relationship between the effectiveness of a board of directors and the firm performance of Sri Lankan companies. Future studies can use the moderating variable between these variables.
Keywords: Effective board of directors; Firm performance; Partial least squares; Structural equation modelling