Ownership structure, corporate governance and firm performance

Based on previous studies, ownership structure is not standardized across different country and economic sectors. In other words, each country or economic sector might have different types of sustainable ownership structure that contribute to the competitive and healthiness of a firm. Failure to establish a sustainable ownership structure may produce a result that is contradicted from what is expected by the shareholders. This situation frames a picture that ownership structure is a vital determinant in enhancing firm performance. By highlighting the corporate governance components that normally used in the academic research, this study tends to identify the important components that applied in the reforms of the Malaysian corporate governance. This study is needed as a tool to proof whether the ownership structures and corporate governance practices are truly influenced firm performance. The purpose of the study is to investigate the relationship between firms\x92 ownership structures, corporate governance practices and firm performance. Specifically, this study narrows the ownership structures categories into, institutional, government, family, foreign, managerial and concentrated. Besides, this study focuses on ten corporate governance components which include board structure, CEO duality, board size, independent board of directors, directors\x92 professionalism/qualification, board meeting, board committee, directors\x92 remuneration, transparency and disclose, merger and acquisition. Firm performance will be measured in the aspect of accounting profitability-return on asset and return on equity, and market performance-Tobin-Q, price to earnings and price to book value. The participating firms of this study are non-financial public firms that are actively listed in the main market of Bursa Malaysia during the 5-year period (2010-2014). The sample will be tested and analyzed by using empirical quantitative method, linear regression, multiple regression and panel data regression analysis