CHAPTER 6: DATA ANALYSIS AND DISCUSSION
6.7. Empirical results – testing of control variables
To minimise the impact of other variables that may explain observed relationships with corporate performance, four control variables (size, age, growth and financial leverage) are included within the regression models. The connections between firm size and dependent variables is not significant under four research models and neither is firm age, thus it is impossible to make any conclusion regarding both of control variables.
The interactions between firm growth and dependent variables are significant at 10 percent level under the INVEFF, ROE and TOBINQ model and 5 percent level under
ASSTURN model (see Table 6.7). The effects of firm growth on asset turnover, return on equity or Tobin q are significantly positive, indicating higher rate of sales growth creates a firm’s better wealth. These results show a similar trend with the previous studies such as Ming-Chin et al. (2005), Hong Pew et al. (2007), Nazari (2010), Clarke et al. (2011).
Whereas for investment efficiency, the result is not somewhat surprising when it is both negative and statistically significant at p value < 0.10 (β = -0.091, t value = 1.921). This negative association alike the studies of Q. Li and Wang (2010), F. Chen et al. (2011), Juan Pedro Sánchez and Gomariz (2012), indicating firm growth may lead to managers’
incautiousness in their investment decisions that in turns wound in investment efficiency.
The interactions between financial leverage and dependent variables are significant at 10 percent level under INVEFF, ROE model and 5 percent level under Tobin q model (see Table 6.7). The effects of financial leverage on ROE and Tobin q are significantly positive, indicating that leverage under financial strategy planning helps to increase the rate of return by generating a greater return on borrowed money than the cost of using that money. Moreover, the correlation between financial leverage and investment efficiency is significantly negative (β = -0.112, t value = 1.837). This implies that firms with a high proportion of debt are supervised by debt covenants that mitigate investment inefficiency (Juan Pedro Sánchez & Gomariz, 2012).
Table 6.7. Summary of the testing results of control variables
Control variables
Asset turnover model
Investment
efficiency model ROE model Tobin q model
β Result β Result β Result β Result
Firm size
(SIZE) -0.011 No
accepted 0.004 No
accepted -0.028 No
accepted 0.006 No accepted Firm age
(AGE) -0.015 No
accepted -0.037 No
accepted -0.004 No
accepted -0.027 No accepted Firm growth
(GRW)
0.234
** Accepted -0.091
* Accepted 0.045
* Accepted 0.139
* Accepted Financial
leverage (LEV) 0.076 No accepted
-0.112
* Accepted 0.057
* Accepted 0.079
** Accepted
Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)
Source: Calculated by the author in SmartPLS 3.1
SUMMARY OF CHAPTER 6
The results of this study have successfully answered all research questions. This study has confirmed that there are reciprocal correlations between intellectual capital components. More generally, the outcomes of this study support for the idea that the modified VAIC model can estimate IC components, especially estimating structural capital via organizational capital and innovation capital, associated with firms’ performance and affect firms’ market value and profitability and productivity successfully. Not only support the combination of different types of resources, this finding but also provides evidence to be in favour of resource-based theory which suggests resources, e.g. physical capital, intellectual capital, are very vital inputs to develop advanced managerial systems e.g. SMA to cater the increasing requirements of sophisticated managerial information, which in turn add more values to a firm.
Furthermore, this study confirms relationships between firms’ financial performance indicators and their strategic management accounting practices. In the opened research, under the mediating role of SMA practices, SMA practices fully or partially mediates the positive influence of IC components over corporate performance. With regard to the usage of SMA system within Vietnamese public traded companies, it appears firms still generally favour the use of strategic management accounting to manage IC. It suggests that more contemporary systems are typically used in this observed samples and it therefore appears that such firms are making operational and strategic decisions using strategic management accounting systems.
To re-confirm the role of SMA practices in managing intangibles, the research outcomes highlight only strategic accounting approaches are used to manage human capital. Remarkably, the findings validate the usefulness of all groups of strategic management accounting practices as techniques to manage structural capital. Except for strategic accounting approaches, three remaining groups of SMA practices (strategic cost management, competitor accounting, customer accounting) are most appropriately situated as techniques of relational capital management.
The next chapter is going to discussed some of the implications for integrations of strategic management accounting practices into intellectual capital management.