UNIDAD DE ADMINISTRACIÓN DE BIENES (BODEGA)

Due to the insignificant relations between the variables of board diversity and financial firm performance, a portfolio analysis may give additional insight. It may be possible that, for example, firms with on average a higher female representation have on average higher financial firm performance. In order to reveal addition insights, both board diversity variables gender and age are split up into three categories; low, medium, high. Afterwards the financial firm performance measures are included, followed by the control variables. For each variable the mean and standard deviation are given, based on the three categories of the given board diversity variable. Besides the split up, the data from BOD and BOM are, similar to previous analysis in this study, separated8.

5.5.1 Gender diversity

For the gender diversity variable, the three categories entails 0-15% female representation in the category low, 16-30% female representation is category medium. Category high entails all the firms above 30% female representation.

- Table 9 about here –

Table 9 clearly shows that only 2 firms (Nedap NV and Koninklijke Ahold NV) have female representation of above 30% in the BOD. This amount of firms is very low, in comparison to the sample size of 95 firms. Most of the firms appear to be in the lowest category of female representation, at least 77 firms. Based on the mean performance measures ROA and LnTQ, the results suggest that firms with a higher percentage of female representation (above 30%) perform better. The mean ROA in category high is 8.64, whilst the mean ROA in category low is quite lower, 5.27. A remarkable result, which is in line with prior research, is the mean firm age. Following the results in table 9, it appears to be that older firms are more diverse in terms of gender. Furthermore, no significant differences exist between the three categories. One announcement I have to make; these results should be interpreted with caution due to the small sample size within the categories.

- Table 10 about here –

Similar to table 9, table 10 show the results from the portfolio analysis based on data of BOM for the gender diversity variable. According to the BOM data, it appears that most of the firms are in the lower category. In contrast to the results from table 9, table 10 reveals that the performance measure ROA has a far lower mean for the high category. This result may suggest that, in comparison to BOD data, female representation in the board of management is less effective than in BOD in order to enhance financial firm performance. One of the theories which may explain this result is Yermack (1996), who argues that the appointment of women to the board may cause delay in decision-making, and additionally financial firm performance, due to the longer time to reach consensus. For firm size, it appears to be that the largest firms have gender diversity in the medium category. In addition, these firms have a lower liquidity and a larger board size in comparison to the other two categories. Again this result may be in line with the theory of Yermack (1996) who also suggest that smaller boards are more effective than large boards, the benefits can be out-weighted by the costs due to poorer communication and decision-making for larger boards. Once again, these results should be interpreted with caution due to the small sample size of only 3 firms in category

medium.

5.5.2 Age diversity

To see if there is addition insight based on splitting up the data in categories, age diversity is also divided into three categories. The low category entails all the firms with an age diversity scale 0-75. In addition, medium category is based on firms with an age diversity scale between 76 and 150. Lastly, category high entails all firms with an age diversity scale of above 150.

- Table 11 about here –

According to the results in table 11, it appears to be that only 12 firms have an age diversity scale of above 150. A remarkable result is the suggestion that less diverse BOD’s in terms of age, have on average higher firm performance (ROA and LnTQ). This result may suggest that, together with the results from table 9, firms have to have BOD’s with a high female representation and board members around the same age. For firm age, the results suggest that age diversity is more likely to exist in firms which are on average younger. This substantiates previous findings of this study in the regression analyses. Furthermore, no significant differences exist between the three categories.

- Table 12 about here –

For the board of management, only one Dutch listed firm (Oranjewoud NV) exceeded the 150 age diversity scale. For this reason that only one firm is in category high, no standard deviations for the variables can be provided. Also for this reason, it is not possible to make reliable suggestions and conclusions based on category three. Therefore I compare category low and medium with each other, and find that in fact there are no significant differences. The only major difference is in means of the prior performance variable ROA. PP_ROA appears to be much higher for the 60 firms in the

low category (3.85) than for the 34 firms in the medium category (0.36). This result may suggest that

firms with less diverse BOM’s in terms of age performed better than more diverse BOM’s in the past. Looking at the current ROA of both categories, no significant difference exists.

5.5.3 Conclusion portfolio analysis

Based on the portfolio analysis some addition insight has been provided. According to the mean performance measures ROA and LnTQ, the results suggest that firms with a higher percentage of female representation in the BOD (above 30%) perform better. This is in line with the arguments for hypothesis 1. Thereby, it appears to be that older firms are more diverse in terms of gender. In contrast the results suggest that age diversity is more likely to exist in firms which are on average younger. These additional insights may suggest that, if firms would like to enhance their financial firm performance, firms have to have BOD’s with a high female representation and board members around the same age. As mentioned previously; these results should be interpreted with caution due to the small sample sizes within the categories.