For the purpose of making a similar investigation, this study used data involving 500 cases. Data are available on market-to-book-value (MBV), identity of the largest owner, “concentration of ownership” assessed in terms of the percentage share of the largest owner, size in terms of the total assets of the company, return on capital in percent (ROCE), and industry type. Therefore, there were six variables.
However, because this investigation is limited to the relationship between ownership structure and company performance, there were only four relevant variables: MBV, identity, concentration of ownership, and ROCE. The relevant independent variables for the study are “identity of the largest owner” and the “concentration of ownership” assessed in terms of the percentage share of the largest owners. In contrast, the relevant dependent variables or company performance variables appropriate from the data set are MBV and ROCE. There was no need to use the variable “industry” because it is irrelevant for the focus of our study. Of course, our study can also cover whether the effect of the independent variables differ in each type of industry or whether the specific effect of the independent variables vary depending in manufacturing, services, and primary industries. However, we need not do this. Similarly, we do not have to cover firm size based on assets because firms can be small or large but asset size does not imply performance. Of course, we can also construct empirical investigations that differentiate the effects based on asset size but, again, we do not have to do this.
We focus in this section on variables that may indicate a possible presence or absence between firm ownership structure and firm performance. In Figure 1, we investigate the scattergram pattern if we have the percentage share of the largest owner of a firm and market to