White Lee and Tower WP
White Lee and Tower WP
White Lee and Tower WP
Companies
disclosures in a large sample of listed biotechnology companies, and test the relationship
between voluntary disclosures of intangible firm value with traditional Agency Theory
variables. The relationships were tested statistically using correlation and multipleregression analysis.
Findings: The key drivers of voluntary intellectual capital disclosures were the level of
board independence, firm age, level of leverage and firm size. Multiple regression analysis
demonstrated that board independence, leverage and size had a significant relationship with
the level of voluntary intellectual capital disclosure. Separate regression controlling for
large-sized and small-sized firms demonstrated that voluntary intellectual capital disclosure
was only driven by board independence and the levels of firm leverage in large firms. The
small firms did not demonstrate this relationship.
Research limitations/implications: Implications of this research are that smaller
biotechnology companies managers are not motivated by external debt-holder demands to
make voluntary disclosures about intangible firm-value. In addition large biotechnology
companies, better able to establish independent board oversight, appear more effective at
driving voluntary intellectual capital disclosures; perhaps in response to greater demand by
owners. A limitation of this study is its Australian context and that data is analysed only
from 2005 financial year annual reports.
Originality/value: To our knowledge this is an original paper whose findings have
valuable implications for managing intellectual capital at the firm level. We clearly
demonstrate that disclosures about intangible firm value is being driven by traditional
Agency Theory Variables and more contemporary corporate governance issues, and that
small firms may be ignoring the importance of disclosing more about their intellectual
capital.
Ownership concentration
Another determinant of intellectual capital disclosure that will be analysed here is ownership
concentration. Ownership concentration is a measure of voting power distribution either to the
owners or the managers. Sometimes also measured as the proportion of management ownership,
it represents a motivation for non-financial disclosures to aid alignment of interests between
managers and owners. Low ownership concentration in firms is equated to manager control,
whereas high ownership concentration firms are equated to owner control. Research to date has
contributed conflicting accounts of whether ownership concentration is likely to be a
determinant of intellectual capital disclosure in firm annual reports. For example, a significant
relationship was demonstrated between ownership structure and voluntary segment disclosures
in diversified Australian firms (McKinnon & Dalimunthe, 1993), but Singh and VanderZahns
(unpublished) intellectual capital study confirms Craswell & Taylors (1992) study of voluntary
reserve disclosures, in that there was no significant association with ownership structure.
Board independence
The monitoring ability of the board will depend on its individual members ability to represent
the shareholders by assessing firm activities and controlling the behaviour of firm managers.
The percentage of independent directors on the board and the size of the board have both been
positively associated with measured levels of disclosure in past studies (Craven and Wallace,
2001; Jaggi and Leung, 2006).
Firm leverage
Traditional agency theory also predicts that highly leveraged firms which have significant
obligations under existing debt covenants incur monitoring costs to reach equilibrium between
self-interested managers as agents for external debt-holders (Dhaliwal et al., 1982). The paper of
Watts and Zimmerman (1986) further explains that the more external financing that is employed
by an organization the more management will attempt to use different policies for their own
benefit. While Singh and VanderZahn (unpublished) find there is a significant positive
correlation between oil and gas firm leverage and intellectual capital disclosure they also review
two other papers with contrary results. A positive correlation between firm leverage and
voluntary segment disclosures was found by Bradbury (1992). No relationship was found
between the same two variables measured in New Zealand firms (Chow and Wong-Boren,
1987).
The research detailed above has led us to make the following null hypotheses:
HoSize: There is no significant association between the political visibility of
biotechnology firms and the level of voluntary intellectual capital disclosure
measured in the annual report.
HoOwnership: There is no significant association between the voting power
distribution amongst the top twenty shareholders in biotechnology firms and the level
of voluntary intellectual capital disclosure measured in the annual reports.
HoIndependence: There is no significant association between the level of Board
independence in biotechnology firms and the level of voluntary intellectual capital
disclosure measured in the annual report.
HoAge: There is no significant association between the age of the biotechnology firm
and the level of voluntary intellectual capital disclosure measured in the annual
report.
As such,
information that is disclosed by other means, such as on the company web-site, is not included
in this study.
Measure of Intellectual Capital disclosure (Dependent variable)
The 78-item disclosure index originally developed by Bukh, Nielson et al. (2005) to measure
intellectual capital disclosures in Danish company IPO prospectuses is used in this study. The
percentage of the disclosure index as a total is calculated in accordance with the following
formula which was presented in the above publication.
Score = ( di/M) x 100%
10
Independence
The independence of the board of directors of the biotechnology companies was measured by
the number of independent directors on the board in the 2005 financial year as a percentage of
total number of directors of the company. This data was available from the second item in the
Australian companys corporate governance statement, and is a mandatory annual report
disclosure required by the Australian Stock Exchange (ASX) listing rules (Structure the board to
add value).
Age
The age of the companies were measured in months from the date of incorporation to the end of
the 2005 financial year which for most of the companies was 30 June 2005. Only six of ninetysix companies in the final sample had a year end date other than 30th June 2005.
Ownership concentration
The ownership concentration in each company was measured as the percentage of total shares
on issue that were held by the twenty largest shareholders. This was measured shortly after the
end of the 2005 financial year.
Leverage
11
Where:
%Top20Sh = percentage of shares owned by the 20 largest shareholders of the company at 2005
year end;
LnLeverage = natural log of total liabilities over total assets of the company at 2005 year end;
LnAge = natural log of the age of the company in months from the date of incorporation to the
last day of the companys 2005 financial year;
Ln%Indep = natural log of the percentage of Board directors that were independent in the 2005
year; and
LnMarkCap = natural log of the market capitalization of the company at 2005 year end.
j = the coefficient on the intercept term;
j = the coefficients 1 through 5 on the independent and control variables; and
j = the error term.
Results
12
The intellectual capital disclosure index is the sum of the firms disclosure in six areas, namely
employees, customers, information technology, processes, research development and strategic
statement. The mean levels of disclosure for the six measures of voluntary intellectual capital
disclosure was 2.96%, 1.44%, 0.15%, 1.67%, 3.99% and 4.78%, respectively. Intellectual
capital disclosures relating to employees, research and development and strategic statement are
the highest and customer and information technology items scored lowest. It is interesting to
compare our results with those of the Danish pharmaceutical and research IPO prospectuses
(Bukh et al., 2005) where the mean disclosure index of intellectual capital was 27.6% for n=7.
In this study, another industry group equivalent that was studied also had a high index compared
to the current: IT and technology companies in Bukh et al. (2005) were 33% for n=17. The
nature of prospective information in the IPOs releases might explain the difference. Of the 96
Australian companies in the sample, 87 recorded no information technology IC, 31 recorded no
customer IC, 30 recorded no processes IC, 26 recorded no employee IC, but only 10 recorded
no research and development IC and 8 recorded no strategic statement IC.
The mean LnMarkCap of the companies was 10.24 or an absolute value of AUD $158 million
with the largest company in the sample having a market capitalization at 30 June 2005 of AUD
$6,342 million and the smallest AUS$1.8 million. The mean LnAge of the companies was 4.64
or an absolute value of 145 months or 12 years, the oldest company was 47 years and the
youngest was 1 year at the 2005 financial year end. The mean Ln%Indep of the companies was
3.38 or an absolute value of 46% with a maximum level of board independence measured at
80% and minimum 0%. It should be noted that the average level of board independence was low
considering an ASX Corporate Governance Requirement for a majority of independent
directors.
take in Table II
13
14
The results of backward linear regression analysis between ICDIndex and the independent
variables in the above model indicate that coefficient for LnLeverage (p=0.059) is moderately
significant when compared with ICDIndex. This finding is consistent with expectations,
supporting the hypothesis that highly leveraged firms disclose more voluntary intellectual
capital information because it may reduce monitoring costs and agency costs of debt to balance
the opposing needs of managers and debt-holders (Dhaliwal et al., 1982). Supporting the board
independence hypothesis, the regression results show that there is a very significant relationship
between Ln%Indep and ICDIndex (p=0.030). The significance of this result indicates that the
structure of the board in these biotechnology companies is a factor in determining the level of
intellectual capital disclosures. As outlined in the hypothesis section earlier the structure of the
board is of vital significance to assessing firm activities and controlling managers behaviour.
So it appears that the level of board independence in biotechnology companies is an important
determining factor in the firms levels of voluntary intellectual capital disclosure (Craven and
Wallace, 2001; Jaggi and Leung, 2006).
take in Table IV
The most significant result of the regression is that the relationship of size (LnMarkCap) and
ICDIndex was demonstrated to a high level (p<0.000). To further investigate the effect of size,
the dataset was separated into large and small firms. Firms whose LnMarkCap is equal to or
above the mean are considered large, while firms that fall below the mean are small firms. A
backwards regression was conducted to identify the relationship between the independent and
dependent variable. The General Linear Model used is:
ICDIIndexj = j + 1%Top20Shj + 2LnLeveragej + 3LnAgej + 4Ln%Indepj + j
The results shown in Table V indicate that the model proposed is only relevant for large
biotechnology firms. Board independence (Ln%Indep) and leverage (LnLeverage) were both
statistically significant only for the companies with LnMarkCap greater than or equal to the
mean, indicating that an increase in board independence and leverage is associated with an
increase in the disclosure of intellectual capital items in the annual report for large firms only.
take in Table V
15
16
17
18
19
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22
23
Variable Description
Dependent
ICDIndex
Independent
%Top20Sh
LnLeverage
The natural log of total assets/total liabilities of the company at 2005 year
end.
LnAge
The natural log of the age of the company from the date of incorporation to
the last day of the companys 2005 financial year.
Ln%Indep
Control
LnMarkCap
As a proxy for size: the natural log of the Market Capitalization of the
company on the last day of the companys 2005 financial year.
24
Statistics
ICDIndex
N
Mean
Std. Error of Mean
Median
Std. Deviation
Skewness
Kurtosis
Valid
ICDIemp
ICDIcust
ICDIit
ICDIproc
ICDIrd
ICDIstrat
Ln%Indep
LnAge
%Top20Sh
LnMarkCap
LnLeverage
96
96
96
96
96
96
96
96
96
96
96
96
14.96
2.96
1.44
.15
1.67
3.99
4.78
3.38
4.64
56.27
10.24
-2.13
.78
.27
.16
.05
.17
.25
.31
.14
.09
1.80
.15
.12
14.10
2.60
1.30
.00
1.300
3.80
3.80
3.91
4.56
59.25
9.95
-2.09
7.64
2.65
1.55
.49
1.71
2.44
3.02
1.39
.86
17.64
1.46
1.19
.68
.75
1.63
3.54
1.34
.184
.84
-1.89
-.28
-.36
1.08
-.23
.46
.55
2.82
1.80
-.747
1.27
2.03
-.31
-.32
1.86
.14
37.2
12.8
6.4
2.6
7.7
9.0
15.4
4.38
3.79
80
8.17
6.26
Minimum
1.3
.0
.0
.0
.0
.0
.0
.00
2.54
12
7.49
-5.39
Maximum
38.5
12.8
6.4
2.6
7.7
9.0
15.4
4.38
6.33
92
15.66
.86
Range
12.76
# There were too few biotechnology firms measuring IT disclosures to make ICDIit a valid measure.
25
Correlation
Sig. (2-tailed)
Ln%Indep
Ln%Indep
.405(**)
.207(*)
.020
.014
.557
.000
.043
.035
.058
.178
-.106
.733
.576
.083
.304
-.192
.227(*)
.350(**)
.062
.026
.000
.026
-.046
.803
.655
.136
Correlation
Correlation
Correlation
Correlation
Sig. (2-tailed)
LnLeverage
LnLeverage
-.061
Sig. (2-tailed)
LnMarkCap
LnMarkCap
.249(*)
Sig. (2-tailed)
%Top20Sh
%Top20Sh
.238(*)
Sig. (2-tailed)
LnAge
LnAge
.187
Correlation
26
4Ln%Indepj + 5LnMarkCapj + j
t-statistic
Constant
-4.933
-0.944
0.348
Ln%Indep
1.115
2.207
0.030
LnLeverage
1.119
1.912
0.059
LnMarkCap
1.821
3,717
0.000
Variables
27
+ j
t-value
t-value
Constant
13.252
3.581
0.001
12.725
15.548
0.000
Ln%Indep
3.130
3.264
0.002
LnLeverage
3.092
3.179
0.003
Variables
Model Summary:
96
96
0.305
0.000
Adj R
0.268
0.000
F-statistic
8.137
Significance
0.001
R2
2
28
E17
E18
E19
n=96,
division or function
100%
E20
E1
E21
Career opportunities
E2
E22
58
E3
E23
Pensions
44
E4
E24
Insurance policies
34
E5
E25
E6
E26
E7
E27
E8
E9
24
E10
C1
Number of customers
E11
C2
E12
C3
55
E13
C4
E14
C5
10
C6
C7
C8
Education/training of customers
and activities
E15
E16
Page 29
C9
C10
13
C11
C12
C13
C14
Repurchases
P8
44
65
activities
RD2
R&D expenses
79
RD3
RD4
IT1
Description of investments in IT
RD5
IT2
RD6
54
IT3
RD7
32
IT4
Description of IT facilities
RD8
29
IT5
IT expenses
RD9
30
Processes (8 items)
P1
12
SS1
31
P2
SS2
14
P3
SS3
49
P4
12
SS4
43
P5
38
SS5
30
P6
SS6
14
P7
SS7
36
SS8
programs
Page 30
SS9
44
SS10
43
SS11
SS12
SS13
SS14
objective
SS15
31
Page 31