Asia Pacific Journal of Accounting and Finance Volume 3 (1), December 2014 THE USE OF ECONOMIC VALUE ADDED (EVA) AND ACCOUNTING EARNINGS AS PRIMARY CONSIDERATION FOR MERGER AND ACQUISITIONS Elfina A. Sambuaga Universitas Indonesia Email: [email protected]Abstract The purpose of this study is to examine the effect of EVA and earnings of the company that became the target of mergers and acquisitions. This study uses logistic regression method of listed companies in Indonesian Stock Exchange that became mergers and acquisitions‟ target during 2008 to 2012. Results of this study indicate that the higher EVA, will increase the probability of the company being targeted. In contrast, higher earnings will decrease the probability of the company being targeted. Further analysis reveals that investor‟s evaluation of EVA is conditional upon company‟s earnings. Results show that high EVA and low earnings or low EVA and high earnings increase the probability of a company becoming a target. However, low EVA and earnings has no effect on the probability of being targeted for mergers or acquisitions. Keywords: economic value added (EVA), earnings, merger and acquisition’s target.
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Asia Pacific Journal of Accounting and Finance
Volume 3 (1), December 2014
THE USE OF ECONOMIC VALUE ADDED (EVA) AND ACCOUNTING
PBV describe how big market appreciation to the book value of a stock. Many investors used
PBV to obtain the information level of investment risk caused by the liquidation of the
company. Proxy PBV used by Palepu (1986), and Espahbodi and Espahbodi (2003). PBV is
obtained by dividing the book value of the stock price. PBV calculation is done in the
following way:
(3.9)
4. RESULTS AND DISCUSSION
4.1 Descriptive Statistics Analysis
Based on Table 2, it is known that EVA variable in the target company has a
minimum and maximum value 17.41 and -4.70, respectively. While the non-target companies
Sambuaga, The Use of Economic Value Added (EVA) and Accounting .... 69
have maximum and minimum of 2.29 and -41.51 EVA. Negative values indicate that the
target company mergers and acquisitions, there are companies that have a negative EVA.
EVA is negative or < 0 shows that the company is not able to create an added value for the
company, despite its financial statements reported earnings. While a positive value means the
company has revenues (accounting income that exceeds the cost of capital).
The maximum and minimum values show that there is a sample of the target company
mergers and acquisitions that have a higher value than the EVA sample of non target
companies. However, on average, the value of the second EVA sample companies have a
significant difference (α = 5 %). It is proved that the number of sample firms that become
targets of mergers and acquisitions, has a different value to the company EVA nontargets.
Unlike the case with AvgEBEI variables obtained from the average profit of the
company before the accounts outstanding for 3 years before becoming the target of mergers
and acquisitions, the company's total assets one period before being targeted. Based on Table
2, all companies have an average net profit (AvgEBEI) positive. This is shown by the average
variable Ebei the target company of 0.00 and a non target of 0.05. A positive value indicates
that the average sample firm is able to generate a net profit, but the company has a non
targeted net profit greater than the target company mergers and acquisitions. On average,
there are significant differences (α = 5 %) on the net income component of the target
company with corporate mergers and acquisitions of non targets.
Based on the maximum value of the sample targeted companies and non target, the
target company AvgEBEI variable is greater than the non-targeted companies, amounting to
0.73 and 0.39. This indicates that there is a sample of the target company had a net profit
higher than the non targeted companies. Instead, based on the minimum value, the sample
contained the target company suffered losses greater than the non-targeted companies. This is
indicated by the minimum value of -0.75 for the target company mergers and acquisitions,
and -0.39 for non targets.
Table 2 also shows the distribution of the sample companies on the condition of EVA
valuation and net income simultaneously. Based on the total sample of 179 companies, there
are 64 companies that have below median EVA but net income (EBEI) above the median. Of
the 64 companies, 38 of which are the target company mergers and acquisitions, and 26 non
targets. This indicates that firms with a low EVA looks attractive for investors/potential
acquirers who have the motivation to replace the old management, due to poor performance
despite higher reported net income. On the other hand, there are also investors/potential
acquirers may think of the profits generated in the event of merger capital of the merger and
acquisition activity. Thus, investors/potential acquirers of this kind would be more interested
in companies that have a high profit, despite the low value EVAnya.
On the other hand, EVA high but lower net income also in demand by investors.
Based on the sample of 50 companies that have high EVA but lower net income, there are 28
companies‟ targeted mergers and acquisitions, and 22 are from non-targets. In this condition,
the investor/acquirer candidates who are motivated to take over undervalued companies, has
a tendency to consider income as a measure of performance. Thus, when the company
reported net income was low, investors soon make it as a sign that the company has
management that is less efficient and should be replaced. Especially when investors/potential
acquirers are able to assess the performance of the company based on the value of EVA, the
70 Asia Pacific Journal of Accounting and Finance Vol. 3 (1), December 2014, 59-87
EVA with high, but lower net income would provide indirect signal to the
investors/prospective acquirers that the company has the ability to create added value for the
company. However, the added value created by the company may result in reported net
income will be lower.
Furthermore, the company that owns EVA and net income (EBEI) below the median.
This condition can only be owned 18 companies, 6 of which are the target company mergers
and acquisitions, and the other 12 are non target companies. The number of targeted
companies in these conditions over a little of everything. This indicates that the selection of
the target company is basically done by taking into account the performance of the company.
When there are no components or performance measure indicates that the company has added
value or capital good ability, then companies are less likely to be targeted mergers and
acquisitions.
Unlike the case with PBV and SIZE variables, both of these variables have no
significant difference (α = 10 %) between the target company mergers and acquisitions, the
company's non targets. Although based on Table 2, the company has a non-target average
PBV higher than the target company. The maximum value of the sample also indicates that
there are companies that have a non-target PBV greater than the target company. As for the
minimum value, the target company has a PBV lower than the non targeted companies.
4.2 Analysis of Different Test Average Variable
Based on the different test results in Table 3, AvgEBEI and AvgEVA variables have
p-value less than 0.05, it can be concluded that the null hypothesis is rejected or accepted
alternative hypotheses. That is, there are significant differences between the average
Economic Value Added (EVA) and the average net income (EBEI) the target company
mergers and acquisitions with companies that do not become targets of mergers and
acquisitions (matched pairs).
PBV and SIZE variables have p values greater than 0.05 then the average enterprise
value (PBV) and firm size (SIZE) has no significant difference between the target company
mergers and acquisitions with companies that do not become targets of mergers and
acquisition (matched pairs). So it can be said that the company's value (PBV) targeted
companies and non targets are the same. Similarly, the size of the company is seen by total
assets, where there is no difference between the size of the target company mergers and
acquisitions with companies that do not become targets of mergers and acquisitions.
4.3 Pearson Correlation Analysis
Table 3 shows that the net profit of the independent variable (AvgEBEI) has a
correlation coefficient of -0.171 (significant at level α = 5 %) of the dependent variable
(TargetMA). Thus it can be said there is a negative correlation between the probability of the
company's net profit to be targets of mergers and acquisitions. This indicates that the
company has a negative net income is likely to be the target of mergers and acquisitions than
other companies.
This correlation shows that the net profit is still seen as an informative source of
information for its users, so it can be used in the decision-making process. Although investors
may realize that the net income figure can be generated from the use of accounting methods
Sambuaga, The Use of Economic Value Added (EVA) and Accounting .... 71
as well as the presence of management decisions. However, the company reported net income
still has a function as a measure of performance during the reporting period, in which the
function of this performance were also applied to represent the company's accounting system.
On the other hand, EVA has positive coeficient correlation but not significant at α =
10 %. This indicates that companies with positive EVA are likely to be targets of mergers and
acquisitions, but it has not been established that the EVA is used investors/potential acquirers
as the basis for target selection consideration. When compared with net income,
investors/potential acquirers prefer evaluations using accounting numbers than the concept of
value added such as EVA. Moreover for investors/potential acquirers in Indonesia, EVA
evaluation may not have been associated with their investment decisions.
Similarly, the PBV and SIZE that have a negative correlation coefficient but is not
significant at α = 10 %. Companies that have enterprise value ( PBV ) is the lower will allow
the company to become the target of mergers and acquisitions, but cannot be certain that the
investors/potential acquirers would take into consideration the value of the target company as
one factor that contributed to affect investment decisions. Similarly, firm size (SIZE), where
a company that has the size of a small company that enables enterprises to be targets of
mergers and acquisitions, but it turns out the size of the company does not have a relationship
with the decision of investors/potential acquirers to determine the target.
Table 4 indicates there is no correlation between the independent variable on the
dependent variable. Early indications based on the results of the Pearson correlation shows
that the variable DUM1, DUM2, DUM3, PBV, and SIZE are not correlated to the probability
of becoming a target company mergers and acquisitions. DUM1, DUM2, DUM3 which is a
combination of EVA and net income may not have a correlation as investors/potential
acquirers in determining the targets of mergers and acquisitions do not see a combination of
EVA and net income as a consideration in the decision. It could be that investors/potential
acquirers only look at one factor alone, without considering other factors.
4.4 Logistic Regression Analysis
1) Effect of EVA and Profit Against Target Mergers and Acquisitions Probability
Tests on the effect of EVA (hypothesis 1a) and income (hypothesis 2a) against the
possibility of becoming a target company mergers and acquisitions carried out by using the
model 1.
Goodness of Fit Test for Model 1 shows that by including independent variables, the
model becomes better. Similar results were also shown by the percentage of correct
predictions (predicted percentage correct). The model with no independent variables are able
to provide correct predictions of 60% , better than the model with only constants are
predicted correctly by 50 %. Overall coefficient test (omnibus test) showed level of
significance under which means simultaneous independent variables in the model is better at
predicting the dependent variable compared with only one independent variable only. Cox
and Snell's R2 and Nagelkerke's R
2 indicates the number 0.069 and 0.092, while the Hosmer
and Lemeshow Test of significance is 0.493 (greater than the level of = 5 %). It can be
concluded that the model is quite good and interpretation of the coefficient in the model can
be resumed.
72 Asia Pacific Journal of Accounting and Finance Vol. 3 (1), December 2014, 59-87
Test results on the first model showed that the independent variables EVA (AvgEVA)
and net income (AvgEBEI) significantly affect the dependent variable at level α = 5 % and 10
%. Significant test results show that both EVA and net income also affect the company
became the target of mergers and acquisitions. This is consistent with previous studies stating
that the decision of target‟s company was influenced by the target company performance
which assessed on the profitability of the company (Alcalde and Espita 2003). The results of
this study showed that the measurement of performance based on EVA and net income also
influence the decisions of investors/potential acquirers in determining the target company.
The following are the results of the regression models to test hypotheses 1 H1a and
H2a:
EVA concept is proven to be taken into consideration investors/potential acquirers as
a measure of corporate performance targets, in decision making mergers and acquisitions.
This is consistent with the results of Lehn and Makhija (1996), Bao and Bao (1998), Kleiman
(1999), Garvey and Milbourn (2000), Kurniadi (2003) and Wardhani (2004) who study the
correlation between the performances of the company compared to EVA with other
performance measurements. On the other hand, net income has a significant effect on the
possibility of becoming a target company mergers and acquisitions compared to EVA. This
indicates that conceptually, EVA may be better than accounting figures such as net income.
But in practice, investors/potential acquirers still use net income figures as a consideration in
determining the targets of mergers and acquisitions. These results are consistent with the
findings of Biddle et al. (1997) who still found that net income as a measure of better
performance.
a) Effect of Economic Value Added (EVA) Against Target Mergers and Acquisitions
Probability
Testing the hypothesis 1a was conducted to test the effect of EVA on the probability
of becoming a target company mergers and acquisitions. Based on logistic regression results
in Table 6 shows that the variable has a positive coefficient and AvgEVA significant at α = 1
%. In contrast to the hypothesis, the test results showed that EVA has a positive influence on
the probability of becoming a target company mergers and acquisitions. This means that
companies with high EVA has a greater probability of becoming a target for mergers and
acquisitions
The influence of EVA to the possibility of becoming a target company's mergers and
acquisitions support the statement of Stewart (2013) which can be one of the EVA material
consideration, because EVA is part of the company's earnings quality. According to
Trautwein (1990), according to the theory of efficiency, mergers and acquisitions is
something that has been planned to achieve synergy, so the concept of EVA can be used to
assess the advantages of the above which synergies can be generated by the target company.
Stewart (2013) also added that conceptually, the acquisition decision is not much
different than any other investment decisions. When the company decided to make an
acquisition, the company not only 'buy' revenue of the target company, but also the quality of
earnings is the risk, return, growth prospects, as well as the value of his EVA. Companies that
have EVA positive value means the returns produced by the company exceeds the cost of
capital rate or rate of return expected by investors. On the contrary, if EVA is negative, it
mean that no increase firm value or firm value is reduced due to the resulting rate of return is
Sambuaga, The Use of Economic Value Added (EVA) and Accounting .... 73
lower than investors demanded (Stewart 1991). But Young and O'Byrne (1996) add that
when EVA is negative, not always interpreted negatively as well. Because the company could
have a long -term investment or a large project, but the return of investment is not realized in
the short term.
The result of this study also supports the concept of EVA as a performance measure.
Lehn and Makhija (1996) study the correlation between EVA and better returns compared
with other performance measures such as ROA, ROE, ROS, and MVA. When compared with
a profit, Kleiman (1999), and Garvey and Milbourn (2000) also still supports the EVA as a
performance measurement that correlates better with the return of the company. In its
findings found that EVA is correlated with the share price more than profit. Thus, if a
company with a high EVA has a higher probability of being targeted for mergers and
acquisitions, then perhaps investors/potential acquirers will be considering the benefits
obtained after mergers and acquisitions. Investor/potential acquirer have confidence that by
acquiring companies with high EVA, the company may acquire in the future rate of return
exceeds the cost of capital or the expected rate of return on its shareholders.
b) Influence Of Profit against Target Mergers and Acquisitions Probability.
Hypothesis 2a testing was conducted to test the effect of net income (EBEI) against
the probability of becoming a target company mergers and acquisitions. Based on logistic
regression results in Table 6 shows that the AvgEBEI variable has a negative coefficient and
is significant at α = 1 %. The results of these tests show that the income effecting the
probability of the company being targeted. Coefficient sign corresponding with prediction
means companies with higher profit have a lower probability of becoming a target for
mergers and acquisitions than other companies. The regression results support the research
hypothesis 2a, so the hypothesis2a can not be rejected.
The influence of gain or profit on the probability ofcompanies to become targets of
mergers and acquisitions as evidenced in this study supports the results of research Alcalde
and Espita (2003) and Shleifer and Vishny (1997). Alcalde and Espita (2003) found that
firms with low profitability will have a greater probability to be acquired. Similarly,
companies that‟s have poor performance (Shleifer and Vishny 1997). These results are also in
accordance with the motivation of mergers and acquisitions according to Damodaran (2001),
which took over a company that is managed by poor management and replace it.
In line with agency theory, managers also have a tendency to perform earnings
management. Healy (1985) stated that the presence of asymmetric information between
investors and management create an opportunity for management to perform earnings
management. The existence of earnings management also makes the acquisition target
company has always benefited from the acquisition event when compared with the acquirer's
shareholders (Roll 1986, Bradley et al. 1988, Franks and Harris 1989). Based on this
consideration, any one reason investors/potential acquirers are more likely to choose a
company that has a lower net profit is to avoid earnings management by the company with
net income looks good.
c) Effect of PBV and SIZE against Target Merger and Acquisition Probability.
The test results showed that all the control variables do not significantly affect the
likelihood of stock options investment management. PBV variable as a proxy for the value of
74 Asia Pacific Journal of Accounting and Finance Vol. 3 (1), December 2014, 59-87
the company was negative and not significant at level = 10 % affect the likelihood the
company being targeted. This result is in contrast to results of previous studies conducted on
a sample of companies in Indonesia (Nisa 2007). This may be due to improper proxy used to
measure the value of the company. In another study (Hasbrouck 1985, Bartley and Boardman
1990, Walter 1994) use Tobin's Q as the value of the company. They stated that the q ratio or
Tobin's Q can be explained and demonstrated the ability of the model to better distinguish
between the target company and the non targets.
Firm size (SIZE) is positive and not significant at level = 10 % affect the likelihood
the company being targeted. These results are consistent with previous studies conducted by
Nisa (2007) using samples in Indonesia. Nisa (2007) found that firm size does not affect the
possibility of the company becoming the target of mergers and acquisitions. This might be
because there are big companies in Indonesia who will be the target of mergers and
acquisitions. Thus, both large companies and small companies were equally likely to be
targeted.
2). Effect of EVA and Profit In Simultaneous
The second model is used to test the EVA and net income in the company. There are 3
conditions to see the trend of companies being targeted, namely (1) a company with a low
value of EVA and high income, (2) companies with high EVA and low income, (3)
corporation with EVA and low income.
Goodness of Fit Test for Model 2 shows the -2LL value at Step 1 (after put the
dependent variable) is smaller than Step 0 (only constants), thus it can be said that by
including independent variables, the model becomes better. Similar results were also shown
by the percentage of correct predictions (predicted percentage correct). The model with no
independent variables were able to deliver the correct prediction of 60.2 %, better than the
model with only constants are predicted correctly by 50 %. Significance Hosmer and
Lemeshow test was 0.493 (greater than the level of = 5 %), meanwhile Cox and Snell's R2
and Nagelkerke's R2 indicates the number 0.069 and 0.092.
Although the overall coefficient test (omnibus test) indicates significance at the above
level which means simultaneous independent variables taken together can not account for
the probability of becoming a target company mergers and acquisitions, but these problems
can be solved through the opinion expressed by Gujarati (2009, p.563) which states that in
the binary logistic regression equation, the more attention and priority is the expected
coefficient sign and significance of the coefficients. Goodness of Fit ranks second only to the
significance and expected sign of the coefficient. By the statement, the value of the Omnibus
Test insignificant can be ignored. Thus can be concluded that the model is quite good and the
interpretation of the coefficients in the model can be resumed.
Test results of model 2 in Table 8 showed that DUM1 namely EVA and below the
median net income above the median, significantly affect the dependent variable at level α =
10 %. Likewise DUM2, namely EVA above the median and below the median net income,
significantly affect the dependent variable at level α = 5 %. These results are consistent with
the hypothesis of Alcalde and Espita (2003), and Shleifer and Vishny (1997) that the lower
performance of the company, then the company is likely to become targets of mergers and
Sambuaga, The Use of Economic Value Added (EVA) and Accounting .... 75
acquisitions. The combination between net income and EVA in consideration of target
selection shows that the net profit is still the important information in decision-making
(Subramanyam 1996), but the other net income can not be used independently to evaluate the
performance of the company (Utomo 1999). This is due to the asymmetry of information that
can be used by the target company's management to perform earnings management in order
to influence the market price in order to negotiate the acquisition (Trueman and Titman 1988;
Dye 1988). EVA can be used so that the performance information that is able to identify the
business units that can earn revenue exceeds the cost of capital, and can create the possibility
of a more productive compared to other measuring devices (O'Byrne 1996).
The following are the results of the regression models to test hypotheses H3a 1 , H4A
and H5A :
Unlike DUM3 variables, namely EVA and net income both under the median, does
not significantly affect the dependent variable at level α = 10 %. The results indicate that
investors/potential acquirers do not choose a company that will be targeted without
considering its performance, because the decision will affect the incentives or bonuses to be
earned (Healy 1985; Holthausen et al. 1995; Gaver and Austin 1995). Thus, companies with
lower both EVA and net income does not affect the probability of becoming a target
company mergers and acquisitions.
The control variables in these tests namely SIZE and PBV also does not significantly
affect the dependent variable on the level of = 10 %. Firm size (SIZE) that does not
significantly affect the probability of a target company in accordance with the results of Nisa
(2007), where large companies are categorized based on total assets, as well as small, does
not affect the probability of the company being targeted mergers and acquisitions. a) Effect of low EVA but high Net Income againts Target Mergers and Acquisitions
Probability
To study the influence of EVA and net income together against the possibility of
becoming a target company mergers and acquisitions, both are transformed into a dummy
variable (DUM1), with a value of 1 if the EVA is under the median and net income above the
median and 0 if other. Based on test results, Table 8 shows that the variable DUM1 has a
positive and significant coefficient at α = 10 %. The results of this test indicate that DUM1
not affect the probability of becoming a target company mergers and acquisitions. It can be
concluded that companies with low EVA, but high net profit, has a probability of becoming a
target of mergers and acquisitions.
Based on the results of this test, it can be seen that investors/potential acquirers who
have the motivation to acquire companies that have low performance, not considering the low
net income as consideration for the targeting, but companies are likely to see the value of
EVA as performance evaluation. Investor/potential acquirer may be aware that companies
with high profit not necessarily have a good performance (Utomo 1999), because the profit
rate could be influenced by the choice of accounting methods used and business decision
management (Bernstein and Siegel 1979). Moreover, if managers attempt to profit
management companies to raise prices in order to negotiate the acquisition market (Trueman
and Titman 1988). So with the concerned management to show high profits to efforts that
76 Asia Pacific Journal of Accounting and Finance Vol. 3 (1), December 2014, 59-87
performance looks good, but on the other hand it shows that the value of the company as well
as the value does not indicate an increase in net profits.
b) Effect of high EVA but low Net Income against Target Mergers and Acquisitions
Probability.
The next test for the hypothesis 4a is intended to study the effect of EVA and net
income simultaneously on the dependent variable, ie the probability of becoming a target
company mergers and acquisitions. EVA and net income is transformed into a dummy
(DUM2), with a value of 1 if the EVA is in the net income above the median and below the
median, and 0 if other. The test results indicate that the variable DUM1 has a positive and
significant coefficient at α = 5 %. The regression results indicate that DUM2 influence on the
probability of merger and acquisition targets. This means that companies with high EVA Ebei
low but can increase the probability of becoming a target company mergers and acquisitions.
These results support the hypothesis 4a, so that the hypothesis 4a is not rejected (accepted).
Based on these results, it can be seen that the investors/potential acquirers who have
the motivation to acquire companies with low performance are more likely to judge a
company based on the value of it net earnings. This is consistent with Biddle et al. (1995),
Liu et al. (2002), and Francis et al. (2003), income has an important role as the primary
source of information used by investors than the current dividends and cash. Net income was
assessed by investors/potential acquirers as an important part to reflect the company's
performance (Dechow 1994).
On the other hand, the results of this study also showed that companies with low
profits do not necessarily have a bad performance. Thus, for investors/potential acquirers, it
will tend to benefit. Due to the company's net income on the other hand has a high value of
EVA. Companies may have a particular investment or investment that results have not been
fully provide returns to the company, so the company's net profit seen lower, but it has a high
value added.
c) Effect of low EVA and Net Income against Target Mergers and Acquisitions
Probability.
Testing the hypothesis 5a is intended to study the effect of EVA and net income
together against the probability of becoming a target company mergers and acquisitions. Low
EVA and net income was transformed as dummy variable (DUM3). Based on the regression
results of Table 8 shows that the variable has a negative coefficient DUM3 and not
significant at α = 10 %. The regression results indicate that DUM3 no effect on the
probability of merger and acquisition targets. This means that companies with low EVA and
EBEI can not increase the probability of becoming a target company mergers and
acquisitions. These results do not support the hypothesis 5a, so that the hypothesis5a is
rejected.
Based on these results, it shows that the possibility of the company chosen as the
target depends on the motivation of investors/potential acquirers. Companies with this
condition will not be selected if the investor or prospective acquirer to realize that the
company is not going to bring beneficial synergies. As the Haspeslagh and Jemison (1991)
that the decisionmaking process for mergers and acquisitions as a stage analysis process
begins with determining goals, do a search and filtering systematically, then evaluate the
strategy and finances. So that investors and potential acquirers actually consider the condition
Sambuaga, The Use of Economic Value Added (EVA) and Accounting .... 77
of the target company in order to generate profitable synergies. This is done
investors/potential acquirers so that the merger and acquisition decisions are taken for profit,
as suggested by Heller (2000) that the success of mergers and acquisitions depends on a
company's ability to identify targets with a good strategy. Thus, investors/potential acquirers
do not just pick a target even possible to have a low acquisition price.
On the other hand, companies with lower both EVA and net income has the
probability to be selected by the investor/prospective acquirer if they are motivated by a
comparison between the cost of acquisition of the new project. This is because of the thought
that acquiring undervalued companies that will be cheaper compared to the cost of new
investment projects (Hasbrouck 1985). Alcalde and Espita (2003) in his research found that
companies that want to be acquired is a company that has low profitability and poor corporate
value.
5. CONCLUSION AND LIMITATIONS
This study aims to empirically examine whether EVA and net income affect the
likelihood of becoming a target company mergers and acquisitions in Indonesia. The larger
the value of EVA companies, then the company will increase the likelihood of becoming a
target for mergers and acquisitions. Conversely, the greater the net income decreases the
possibility of becoming a target company mergers and acquisitions. These results also
showed that net profit more influence on the decisions of investors/potential acquirers in
mergers and acquisitions selecting targets compared to EVA. It can be seen from the
significance of the variable net income and EVA. So from these results it appears that
although EVA conceptually better than net income, but investors remained practically using
net income as part of the decision making.
On the other hand, the combination of EVA and earnings are also taken into account
by investors/potential acquirers. Companies that have a combination of low EVA but higher
net income, and EVA high but lower net income affect the likelihood of becoming a target
company mergers and acquisitions. Conversely, when the EVA and net profit showed values
equally low, does not affect the possibility of the company chosen as a target.
The presence of a combination of EVA and net income as consideration becomes the
target company mergers and acquisitions may be influenced by the motivation of
investors/potential acquirers. First, if the investor/prospective acquirer is more likely to
choose investments in companies that have a good performance based on earnings
information, then the company will be selected as the target of companies with high profit
without considering it low EVA value. On the other hand, investors/potential acquirers who
have the motivation to choose a company with a low performance, will be seen the value of
EVA despite higher net profit.
Second, if investors/potential acquirers have the motivation to acquire a low
performing companies based on net income figures, the company with the lower net income
would have the possibility to be targeted. Along with that, if the investor/acquirer candidates
today are also considering the company's ability to create value through a number of EVA,
the company with the lower net income, but has a high value of EVA will have the possibility
to become a target. EVA here gives a signal to investors/potential acquirers that the company
78 Asia Pacific Journal of Accounting and Finance Vol. 3 (1), December 2014, 59-87
has the ability to create added value. Thus, investors/potential acquirers would tend to judge
that the company may have a low performance if judged from the amount of net income, but
on the other hand, this company has the ability to create added value that may not be
measured by the amount of profit.
In addition, other factors such as the value of the company PBV and firm size (SIZE)
is not shown to have an influence on the probability of becoming a target company mergers
and acquisitions. This proves that the investors/potential acquirers in choosing targets tend to
look at the performance of the company compared to the value and size of the company.
Overall, this study found that the performance of the company is the foundation
consideration of investors/potential acquirers in decision making, especially in mergers and
acquisitions. EVA and net income is a performance measurement tool that can be used to
look at the possibility of becoming a target company mergers and acquisitions. However,
when compared with EVA, net profit is still the most dominant information used by investors
in considering the merger and acquisition targets.
This study has limitations by using the figures obtained from published financial
statements to calculate the value of EVA. The study also does not take into account the
company's stock price targets and non targets as a proxy. As for the sample, this study is only
limited to domestic companies listed, and do not distinguish sample target company merger
or acquisition targets.
The next study may compare the effect of EVA that can be measured using the figures
of financial statements with information that EVA is calculated by using the
Stewardadjustment. Entering the stock price as a proxy to determine the company became the
target of mergers and acquisitions. Distinguishing influence consideration of EVA and net
income to determine the target of mergers and acquisitions on foreign and domestic
companies are listed and non listed, also separating the target company merger and
acquisition targets
Sambuaga, The Use of Economic Value Added (EVA) and Accounting .... 79
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