Data Mining in Research on Determinants of CEO Motivation: A Structural Equation Model Analysis Based on Chinese Public Companies

Data mining is an important way to discover the hidden patterns of data from a large quantity of data by precise mathematical means, which can be used for decision making in corporate governance. This research investigated determinants of CEO motivation, focusing on CEO compensation and CEO ownership. Based on a sample of 631 Chinese public companies, a structure equation model has been used in analysis, results of which reported that CEO compensation is more strongly related to firm size in firms with dispersed ownership than in firms with concentrated ownership, while corporate financial performance has more influence on CEO compensation in firms with concentrated ownership than in firms with dispersed ownership. In addition, it is found that a CEO will be paid more if there is a compensation committee in his company and corporate status can affect CEO compensation. The foundings also show that firms with concentrated ownership perform better than firms with dispersed ownership and CEOs are motivated with more managerial ownership in latter than in former.