Asian Social Science; Vol. 11, No.

24; 2015
ISSN 1911-2017 E-ISSN 1911-2025
Published by Canadian Center of Science and Education

Firm Resources, Corporate Governance and the Disclosure of

Intangible Assets
Walter P. Mkumbuzi1
1
The Department of Accountancy, The University of Zimbabwe, Zimbabwe
Correspondence: Walter P. Mkumbuzi, The Department of Accountancy, The University of Zimbabwe, P O Box
MP167, 630 Churchill Avenue, Mt. Pleasant, Harare, Zimbabwe. Tel: 263-71-680-0268. E-mail:
wmkumbuzi@commerce.uz.ac.zw

Received: April 13, 2015 Accepted: June 10, 2015 Online Published: August 18, 2015
doi:10.5539/ass.v11n24p113 URL: http://dx.doi.org/10.5539/ass.v11n24p113

Abstract
The paper investigates the determinants of intangible asset disclosure with reference to the interaction of
heterogeneous asset and governance characteristics of firms. Specifically, it considers R&D intensity as a
measure of asset heterogeneity and multiple proxies for the effectiveness of the firm’s corporate governance
mechanisms and structures of accountability. Intellectual capital attributes are applied as the measure of
disclosure quality and as the signalling mechanism through which management are able to inform markets of
their competitive advantage. By applying the resource based view of the firm and signalling theory, the paper
extends prior research on the determinants of intangibles disclosure through an analytical framework that
examines the interaction of firm resources, corporate governance and intangibles disclosure. The theoretical
framework combines the RBV of the firm in confirming intangibles as a necessary feature of disclosing firms’
asset base and signalling as the means with which management disclose their competitive advantage. The results
of the analysis indicate a positive relationship between R&D intensity, complexity and scope of activity and the
presence of quality signalling responses. Also, the separation of the roles of chair and non-executive director,
complemented by experienced non-executive directors promote quality signalling through the disclosure of
intellectual capital attributes. These findings support the view that corporate governance mechanisms are only
effective when applied in combination. Governance mechanisms bring about transparency and accountability
through disclosure of these intangibles despite the potential competitive losses. The lack of proprietary costs that
might otherwise restrict disclosure might be attributed to competitors’ inability to imitate such intellectual capital
resources and therefore their inability to duplicate such signals. The findings confirm the interaction between
heterogeneous assets and governance mechanisms in the disclosure of intangibles as signalling mechanisms for
management.
Keywords: intangibles, intellectual capital, disclosure, corporate governance, research and development,
competitive advantage, signalling and resource based view
1. Introduction
1.1 Background
The paper explains the disclosure of intangibles in corporate balance sheets in terms of the interaction of the
possession of unique resources and the structure of governance and accountability. Such an approach is
potentially fruitful as the firm’s senior management are simultaneously concerned with the development of
strategies likely to result in competitive advantage and their accountability for the resources deployed to sustain
such advantage. Put another way, if managers invest in resources that create competitive advantage they have an
incentive to signal such investments where competitors might find such signals difficult to replicate, but may
nonetheless not do so where their activities are poorly monitored by capital market participants. Mere possession
of resources therefore may not be a sufficient condition for their disclosure in the annual report. Although
intangible assets and the role of creative workers are becoming increasingly important in the world economy and
at individual firm level associated with the creation of competitive advantage (Lev, 2001), there has been no
systematic investigation of the link between resource attributes, governance and the disclosure of intangible
assets.

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1.2 Intangible Assets – a Key Source of Competitive Advantage

Previous literature has examined the separate effects of resource attribute on intangible asset disclosure
(Archambault & Archambault, 2003; Citron, Holden, Selim, & Oehlcke, 2005), the role of such disclosures as
signals (Bozzolan, Favotto, & Ricceri, 2003; Garcia-Meca, Parra, Martinez, & Larran, 2005) and the role of
governance factors such as board composition on disclosure (Haniffa & Cooke, 2002; Lufti, 1989, Malone, Fries,
& Jones, 1993). Taken together the results of these and other studies suggest that investment in intangible
resource and their disclosure through transparent governance structures are potential mechanisms to secure
competitive advantage and its corollary of superior returns to shareholders. However, previous studies have not
theorised such a relationship nor presented fully integrated tests of the relationships between them.
Understanding of these relationships is important, since, for an increasing number of industries, and more
especially in the service and innovative industries intangibles have become a key source of competitive
advantage (Marr, Gupta, Pike, & Roos, 2003). In order to contribute to this literature therefore, and to enhance
our understanding of the determinants of intangible disclosures, a theoretical framework is suggested linking
disclosure with the impacts of the firm’s asset base, specifically R&D intensity, and the effectiveness of the
firm’s corporate governance mechanisms and structures of accountability. The theoretical relationships are
discussed in section 1.3 below and results from prior empirical surveys assessed. The paper then examines the
determinants of disclosures concerning intangible assets and the joint and separate impact of the firm’s asset
base and governance structure. These propositions are tested using a cross-sectional analysis of a large sample of
disclosures made by UK firms and the results are reported in section 3 below. Section 4 discusses the findings
and draws the conclusions.
1.3 Firm Resources, Corporate Governance and Disclosure: An Analytical Framework
For the purposes of the analysis below, it is assumed that managers are motivated to achieve competitive
advantage, either for the benefit of themselves, or of shareholders and their chosen disclosure strategy is
governed by this attitude. Therefore, disclosures of intangibles are a function of the firm’s competitive strategy
and the requirement to signal the presence of assets likely to create competitive advantage to capital markets.
Sustained competitive advantage (SCA) is defined as delivering sustainable above-normal returns (Peteraf, 1993)
and is likely to be achieved as a result of the possession of unique assets. According to the theory of competitive
heterogeneity such assets might be tangible, but possessed by one firm and not another as a result of
monopolistic market conditions. In contrast, according to the resource-based view of the firm and in particular,
the knowledge-based view of the firm (Grant, 1996); sources of SCA are located in assets that cannot be
purchased in a market. The resource-based view (RBV) explains the competitive advantage of organisations in
terms of bundles of resources (Amit & Schoemaker, 1993; Rumelt, 1984), which are valuable, rare, inimitable
and non-substitutable (VRIN) (Barney, 1991). Super-normal profits consistent with the organisational aspects of
SCA (Barney, 1991) arise from firm specific assets, managerial economies of scope, and organisational
mechanisms of co-ordination (Penrose, 1959; Teece, 1980; Coff, 1997).i As the firm invests in assets such as
specialised production facilities, trade secrets and engineering experience (Teece, Pisano & Sheun, 1997) over
time (Dierickx & Cool, 1989), tacit knowledge is embedded in technically complex routines. According to the
knowledge-based view, SCA arises from such routines (Spender, 1989; Nonaka, 1991). Such assets typically
have intangible characteristics and accordingly the RBV approach is adopted here as a tool for analysing
intangible disclosures, typically linked to firm value creation.
Intangible, as opposed to merely heterogeneous resources may therefore be more likely to be disclosed to the
capital market as signalling devices. The monopolistic possession of tangible resources, for example a telephone
cable network, is likely to be well known by competitors, investors and regulators and is therefore less likely to
be the subject of further elaboration in the annual report. Conversely, the creation of RBV intangibles, for
example investment in organisational and technical processes, is likely to be less well understood by capital
market monitors, creating a potential moral hazard and information asymmetry problem, the logical solution to
which is enhanced accounting disclosure. Moral hazard and information asymmetry problems associated with
intangible assets may be exacerbated by the mendacious but unverified assertions of inferior firms to have made
equivalent investments to their competitors, thereby staking a claim to inequitable shares in superior profits.
More fundamentally, where such investments have occurred, in the absence of disclosure there is no alternative
mechanism for the capital market to adjust returns to reflect the abnormal profits associated with SCA. There is
thus a quality signalling rationale (Akerlof, 1970; Spence, 1973; Healy & Palepu, 1993) for disclosure of
investments in intangibles. Toms (2002) uses this approach, with reference to environmental disclosures, to link
quality signalling using accounting disclosure to the RBV. Other empirical studies have investigated the
signalling properties of intangible disclosure and found that high tech industries investing heavily in intangibles

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aim to promote competitive advantage through disclosure of R&D and technological development processes
(Bozzolan et al., 2003), or to promote the confidence of investors and customers through such disclosures
(Garcia-Meca et al., 2005). A possible extension to these empirical studies can be developed by following Toms
(2002) who argues that governance characteristics will mediate the level of disclosure, so that full disclosure will
occur where monitoring mechanisms are more effective. Theoretical approaches to corporate governance, for
example in new institutional economics argue that an effective board will reduce managerial opportunism and
diffuse agency conflicts (Leftwich, Watts, & Zimmerman, 1981; Fama & Jensen, 1983).

Strength of Governance Structure

Less effective More effective
Quadrant 1 Quadrant 2
Replicable Low disclosure Low disclosure
Organisational Resource Base Non-replicable Quadrant 3 Quadrant 4
Moderate disclosure High disclosure
Figure 1. Resources, governance characteristics and disclosure: an analytical framework

Figure 1 combines the RBV, signalling and governance elements of these theories to explain the extent of
intangible disclosures. On the vertical axis, the resource base of the firm is represented by a continuum, which at
one extreme consists of explicit and easily replicable resources and at the other consists of highly tacit and very
difficult to replicate intellectual and similar intangible assets. On the horizontal axis, the signalling incentive is
represented by a continuum, which at either extreme consists of strong governance mechanisms likely to lead to
full disclosure and at the other weak mechanisms likely to lead to opacity. The framework forms the basis for
developing testable hypotheses to explain the disclosure of intangible assets. In quadrant one, where the asset
base is replicable, for example because it consists of tangible assets that can be purchased in the market, and
governance mechanisms are of limited effectiveness, the lowest disclosure outcome is predicted. In quadrant 2,
where the asset base is replicable and governance mechanisms are more effective, disclosure is the same as in
quadrant 1, since notwithstanding more effective governance, the asset base does not dictate truthful or more
extensive disclosure because the firm has no intangible assets related to SCA. In quadrant 3, where the asset base
is non-replicable, and therefore consisting of non-market purchasable intangibles, but the governance
mechanisms are less effective, disclosure will reach intermediate levels. In quadrant 4, where the asset base is
non-replicable and the governance mechanisms are more effective, disclosure will be at its highest, because
although possessing similar asset bases as quadrant 3 firms, governance mechanisms are likely to overcome
managerial reticence about disclosure, induced for example by concerns about the competitive costs of the
disclosures. The purpose of the paper is to test the implied separate and joint relationships in Figure 1. Before
doing so, it is important to consider suitable measures so that the resource base, governance attributes and
disclosure attributes can be quantified. Prior studies have focused on disclosure and the vertical or horizontal
continua in Figure 1. It is therefore important to examine these studies before deriving suitable proxies for
testing. Disclosure measures are common to all studies and are discussed separately in section 2.1 below.
Relatively little explicit use has been made of RBV in accounting research in general and with reference to
intangible disclosures in particular. At the same time, there is a wide range of attributes that might be used to
quantify the resource bases of firms measured on the vertical continuum. Taking an overview of the literature
these can be generalised into three categories, size related, scope related and complexity related.
1.4 Hypotheses and Research Design
Abeysekera & Guthrie (2005) found that companies with the largest market capitalisation tend to lead the way
insofar as the voluntary reporting of IC is concerned; Bozzolan et al. (2003), Garcia-Meca et al. (2005),
Garcia-Meca and Martinez (2005) and Guthrie, Petty and Ricceri (2006) confirmed size as a measure of firms’
resource base that may lead to the signalling of intangibles. Size appears to be an important explanatory variable
whether measured by total assets, sales (Firth, 1979), or market value (Hossain, Tan, & Adams, 1994; Lang &
Lundholm, 1993). At the one end of the continuum, Ahmed & Nicholls (1994) argue that larger firms are more
likely to have the resources and expertise necessary for the coalition, production and publication of more
informative annual reports; similarly, Firth (1979) relates larger firms with the ability to meet the collecting and
dissemination costs related to such activities. At the other end of the continuum, smaller firms may restrict full

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disclosure due to competitive costs attributable to larger companies within their industries (Hossain & Taylor,
2007). Prior empirical research finds a positive association between the scope and complexity of the
organisation’s activities and disclosure. Scope of activity is measured in terms of SIC codes, which is strongly
associated with disclosure (Archambault & Archambault, 2003; Citron et al., 2005), which earlier studies explain
in terms of resource set (Zarzeski, 1996) or increased diversification (Verrecchia, 1983). Operating in several
diverse areas or sectors requires the management of a greater amount of information as such firms may increase
disclosure in response to the high complexity of operations (Raffournier, 1995; Depoers, 2000). Multiple listing
may be indicative of the scope and complexity of organisations activities. Multiple listing may lead to diffusion
in ownership concentration as foreign investors acquire equity, agency costs may accumulate as the likelihood of
conflicts of interests between shareholders and management increase. Furthermore, due to distance, language
and cultural barriers, foreign shareholders are likely to experience higher levels of information asymmetry
consistent with the suggestions of Cooke (1998). In this way, multiple listing increases the information disclosed
and thus promotes corporate transparency and accountability. Firms with intangible resources have more
incentive to disclose IC in order to reduce agency costs (Fama & Jensen, 1983) related to monitoring. Several
empirical studies (Singhvi & Desai, 1971; Firth, 1979; Cooke, 1992; Hossain et al., 1994; Giner, 1997) have
found that firms listed on several stock exchanges provide enhanced disclosures.
Meanwhile Nixon’s (1997) conclusions suggest management views disclosure of R&D expenditure as vital to
capital market valuation, suggesting the potential to link the RBV with the signalling approach. Voluntary
disclosure of intellectual capital (VDIC) could signal the quality of R&D activities with higher expected returns
particularly where the costs of the signal are negatively correlated with the quality (Seaton & Walker, 1997). In a
study on voluntary disclosure in R&D industries, Jones (2007) finds that firms disclose a variety of information
about all stages of R&D activity. Generally, disclosures of early and late stage R&D activity reduce information
asymmetry as to how R&D will translate into sales. Such signals enable the market to identify firm resources
that sustain competitive advantage. A significant limitation on any likely relationship between signalling
incentives and disclosure is the notion of competitive cost. Competition may restrict full disclosure of
intellectual capital (IC) as disclosure may lead to a potential unfavourable change in future earnings (Dye, 1985;
Guo, Lev, & Zhou, 2004). For this reason, the framework in Figure 1 allows for a trade-off between the
competitive organisation of the industry, which varies on the vertical axis with the degree of replicability, and
the incentives for signalling that too must be reflected in empirical tests. As with the vertical axis of Figure 1, the
implied relationships on the horizontal axis have a number of possible measures. The ones that have attracted the
most attention in the prior empirical literature are measures of board structure, incentive and involvement, (for
example, Haniffa & Cooke, 2002; Lufti, 1989; Malone et al., 1993) and these are the ones that are also given
prominence in this study.
Using Malaysian data, Haniffa and Cooke (2002) found a significant and negative relationship between the
presence of a non-executive chair and voluntary disclosure; other board related governance variables including
proportion of independent directors and role duality, were insignificant. They concluded that their findings
contradict agency theory, indicating the possibility that non-executives must have incentives to keep information
private. Forker (1992) argues for example that a dominant personality in a dual role poses a threat to monitoring
quality and is detrimental to the quality of disclosure. Eng and Mak (2003) found that a higher proportion of
independent non-executive directors to be associated with reduced voluntary disclosure. Haniffa and Cooke
(2005) also suggest that non-executives lack the experience and knowledge to promote voluntary disclosure on
corporate social responsibility issues. In a study on unlisted companies in the UK, Lufti (1989) reported an
insignificant result on the influence of independent directors on voluntary disclosure. Similarly, in the US
Malone et al. (1993), reported an insignificant result between mandatory and voluntary disclosure and proportion
of outside directors. Reasons for negative effects of non-executive directors more generally may include stifling
strategic actions (Goodstein, Gautam, & Boeker, 1994), excessive monitoring (Baysinger & Butler, 1985), lack
of business knowledge (Patton & Baker, 1987) and lack of real independence (Demb & Neubauer, 1992). On the
other hand, in line with the predictions of agency theory, Adams and Hossain (1998) and Chen and Jaggi (2000)
found empirical evidence of a positive relation between proportion of independent directors and disclosure in
Hong Kong. The disclosure attributes differed in these studies, which have used different country contexts and
differing levels of mandatory disclosure. In view of the mixed findings in these studies, the relationships would
certainly be worth retesting using British data.
For reasons of enhanced executive director power or poor monitoring of their activities, high executive
remuneration may be associated with low VDIC. Lufti (1989) identified share option schemes as encouraging
voluntary disclosure in UK unlisted companies. However, due to the opportunistic behaviour of directors, agency

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costs may be incurred unless controlled by adequate governance mechanisms (Evans, Evans, & Loh, 2002).
Where the objectives of shareholders and directors are aligned as illustrated by Conyon, Peck and Sadler (2000),
directors’ compensation may serve as a mechanism to bring about better governance (Ooghe & De Langhe, 2002)
and therefore more accountability and transparency through improved disclosure. Few studies have examined the
relationship between intangibles’ disclosure and role duality in the chief executive officer and chair. On the one
hand, role duality indicates the absence of separation of decision control and decision management (Fama &
Jensen, 1983), on the other, segregation of duties would indicate enhanced control and governance. Finkelstein
and D’Aveni (1994) and Gul and Leung (2004) argue that a concentration of decision-making power may
mitigate the independence of the board and reduce its effectiveness in its monitoring role. This result is similar to
that reported by Forker (1992) in his study of dominant personality and quality of disclosure. Although Gul and
Leung (2004) suggest role duality is associated with lower levels of disclosure, this relationship is found to be
weaker in the presence of experienced non-executive directors. Similarly, in a study on European Biotechnology
companies, Cerbioni and Parbonetti (2007) identified that chief executive officer duality suppresses the
disclosure of forward-looking IC information; however, board structure was found to enhance disclosure. Given
these prior studies, it appears that good governance structures may mitigate the agency costs that may be
attributed to role duality. According to agency theory, combined functions can significantly impair the board’s
most important functions of monitoring, disciplining and compensating senior managers (Barako, Hancock, &
Izan, 2006); as such, role duality may remove the necessary checks and balances over management behaviour
(Blackburn, 1994). The mitigating effect of non-executive directors on this role duality is indicative of the effect
of good governance on disclosure levels. Thus, although there has been considerable empirical work examining
the relationship between governance and disclosure, it has not been integrated theoretically or tested empirically in
conjunction with aspects of the firm’s resource base. Tests examining resource attributes have also yielded separate
but interesting results. The next section will set out a methodology and model for examining the combined impact
of the factors discussed in the review above.
2. Methodology
2.1 Data and Method

Internal External Human Capital HC (7)

Structural Capital SC (8) Relational Capital RC (8)
1.Patents 9.Brands 17.Know-how
2.Copyrights 10.Customers 18.Training
3.Trademarks 11.Customer loyalty 19.Level of education
4.Management philosophy 12.Distribution channels 20.Vocational qualifications
5.Corporate culture 13.Business collaborations 21. Staff development
6.Management processes 14.Licensing agreements 22.Entrepreneurial spirit
7.Information systems 15.Favourable contracts 23.Innovativeness
8.Financial relations 16.Franchising agreements
Figure 2. Intangible attributes
Source: Adapted from Guthrie and Petty (2000)

Sample firms were selected from the FTSE All Share Index for the year 2003/2004 in the Financial Times.
Banks, financial, insurance, life assurance, mining, oil and gas, real estate, speciality and other finance and
investment and property industries were excluded and every second and third company was selected from the
remaining population and their annual reports obtained. This yielded a sample of 460 usable annual reports. A
content analysis of the annual reports of sample firms was conducted by adapting the methodologies of Guthrie,
Petty, Ferrier and Well (1999), Bozzolan et al. (2003) and Milne and Adler (1999). Following the approach
applied by Beattie, McInnes and Fearnley (2004, 32), this research splits sentences into text units which are
related to intangible attributes. Other visual forms of communication that have been found to provide an
immediate and effective means of corporate disclosure (Beattie & Jones 2001; Beattie & Thompson 2006;
Davison & Skerratt, 2007) are included. In summary, a voluntary disclosure of an intangible attribute was
defined as any text unit, illustration, diagram or graphical presentation that explained the attribute in any part of

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the annual report. All such disclosures are excluded from mandatory disclosure in the Companies Act 1989, EC
Directives (Fourth and Seventh), Statement of Standard Accounting Practice, FRS (7, 10 and 11) and the
disclosure rules issued by the LSE. It is also necessary to identify a priori intangible attributes. The most
common framework originates from Sveiby (1997, 12) and was developed by Guthrie (2001, 35). Guthrie and
Petty (2000), Brennan (2001), April, Bosma and Delgon (2003), Bozzolan et al., (2003) and Guthrie et al., (2004)
all applied this framework. For the purposes of comparability with these studies, twenty-three intangible
attributes were identified as representative and are illustrated in Figure 2. Milne and Adler (1999) suggest that as
the number of content categories increases, the potential for coding errors increases. Conversely, as the number
of categories decreases, the likelihood of random agreement in coding decisions increases. Bearing in mind the
importance of comparison and replicability, the research defines the 23 intangible attributes as illustrated in
Figure 2 as representative of an equilibrium point that ensures limited coding errors and limited random
agreement. Agreement levels are assisted by a structured analysis of intangible components following the
framework developed by Sveiby (1997) and adapted by Guthrie and Petty (2000). As Figure 2 illustrates,
intangibles are accordingly analysed into internal structures (organisational capital), external structures
(customer/relational capital) and employee competence (human capital).
2.2 Research Design
To ascertain that the scoring was consistent and accurate according to the chosen scoring procedure a
verification test was carried out by three researchers from the field in a similar process as that conducted by
Guthrie and Petty (2000). Twenty annual reports were randomly selected, scored, compared and correlated.
These annual reports were verified and agreed by three independent persons. Explanatory notes on each IC
attribute and examples of specific IC disclosures in practice were discussed before the start of the analysis
consistent with Bozzolan et al. (2003). The ANOVA test for variance illustrated significantly similar objectivity
after 20 annual reports had been coded. The results of the 20 companies pre-tested provided significant evidence
of consistency in the coding process. This consistency is important to ensure that each IC attribute in any annual
report, is selected if it meets the criteria. The 23 attributes were used to compile a disclosure score (DISC) which
is used as a variable in the empirical model below.
2.3 Model Tested
The model tested examines the relationship between SCA, governance attributes and disclosure as suggested by
Figure 1. The empirical form of the model and a summary of defined variables are set out below. R&D, SIZE
and IND measure the position of the firm on the vertical axis of Figure 1 and the remaining variables the position
on the horizontal axis, according to research intensity, scale and scope/complexity respectively. R&D is defined
as the ratio of research and development expenditure to sales revenues, as obtained from Datastream. SIZE is
defined as net sales or revenues representing gross sales and other operating revenue less discounts, returns and
allowances and is taken from DataStream. IND is a grouping variable ordered by SIC code to reflect broadly
increasing complexity, beginning with basic (BASIC), which is used as the reference group, engineering (ENG),
electrical (ELEC), pharmaceutical (PHAR), retailers (RET), computer (COMP) and services (SERV). The
classification of the sample into these groups is detailed in Figure 3.

SIC Code Industry # of Obs

202 Basic Forestry and paper 2
1589 Food producers and processors 18
1596 Beverages 6
1600 Tobacco 2
4521 Construction and bldg materials. 34
62
2410 Chem Chemicals 12
2463 Personal care and h'hold prods 5
5212 Household goods and textiles 14
31
2840 Eng Steel and other 2
2710 Engineering and machinery 24
3430 Automobiles and parts 10
3530 Aerospace and Defence 7
43
3002 Elec Info Tech Hardware 17

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3210 Electronic and electrical equip't 16

4013 Electricity 3
4100 Utilities (Ex-electricity 8
5147 Diversified industries 6
50
2441 Phar Pharmaceuticals and biotech 14
14
5211 Ret General retailers 35
5211 Food and drug retailers 6
41
7222 Comp Software and computer services 31
7412 Support services 59
7420 Telecommunication services 12
7440 Media and entertainment 39
141
6340 Serv Transport 22
8511 Health 14
9210 Leisure and hotels 25
61
Figure 3. Sample classification by industry and SIC code

Multiple listing (MLTL) represents companies listed on more than one stock exchange and is obtained from the
annual report. NONEXEC is the ratio of non-executive directors to total directors and is obtained from the
annual report, as is EXECREM, the ratio of executive remuneration to market value. DUALITY combines the
dual roles of chief executive officer and company chair; this variable is measured by a dichotomous variable and
is obtained from the annual report, as is CNED that represents a non-executive chair.
DISC = β0 + β1 R&D + β2 SIZE + β3 IND + β4 MLTL + β5 NONEXEC +
β6 EXECREM + β7 DUALITY + β8 CNED + ɛ (1)
where: β0 : intercept;
β1 – β8 : coefficient of slope parameters;
ε : error term.
2.4 Research Design
Descriptive statistics for variables included in equations (1) are set out in Table 1. Panel A of Table 1 presents
descriptive statistics and correlation matrix for continuous variables; correlations above the diagonal illustrate
the cross-correlations between non-continuous governance variables. Panel B of Table 1 presents descriptive
statistics on the determinants of disclosure by industry and Panel C of Table 1 by governance dummy variable.
The statistics in Table 1 Panel A indicate significant cross-correlations in the governance variables, suggesting
that these might be substitutes for modelling purposes, and similarly between industry and R&D intensity.
3. Results
3.1 Descriptive Statistics

Table 1 Panel A. Descriptive statistics and correlation matrix for continuous variables
Standard
Variable Mean A B C D E F G H
deviation
A DISC 0.561 0.118 1 0.211*** -0.011 -0.118
B SIZE 5.811 2.013 0.278*** 1 0.449*** 0.005 -0.101
C R&D 0.044 0.240 0.085* -0.234*** 1 0.188*** 0.026 -0.019
D NONEXEC 0.490 0.177 0.052 0.013 0.044 1 0.089 -0.194*** 0.366***
E EXCREM 1864.480 2321.618 0.236*** 0.502*** -0.065 0.145*** 1 0.186*** -0.155** 0.018
F MLTL 0.200 0.401 0.215*** 0.481*** -0.008 -0.037 0.331*** 1 0.094 -0.158**
G DUALITY 0.112 0.315 1 -0.298***
H CNED 0.522 0.500 1

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The descriptive statistics indicate that larger companies are more likely to list on multiple exchanges; in addition,
these firms generally compensate their executives with higher rates of pay. It is therefore not surprising that an
association exists between disclosure and executive remuneration and disclosure and multiple listing due to the
correlation attributed to the size variable.
In contrast, R&D is found to be more concentrated in relatively smaller firms, given that this ratio decreases with
increasing size as represented by turnover. The significant cross-correlations in the governance variables indicate
that executive officers receive significantly more compensation in the presence of experienced non-executive
directors. Whether non-executives are motivated by the need to match or better market rates or whether this is an
indication of ineffective governance measures remains to be investigated. Nevertheless, the statistics indicate
that multiple listed companies are more likely to provide better remuneration to their directors; however, given
that multiple listed firms are generally large companies, it may be that this association is attributed to size. The
Spearman co-efficients which are used for the grouping variables in Table 1 Panel A, reflect the significant
association between multiple listing and size in the positive association of this listing status with intangibles
disclosure and with executive remuneration. The relationship between R&D intensity and multiple listing is not
reflected in the Pearson co-efficients, which are used for continuous variables, particularly as the relationship
with size is negative. It appears therefore that R&D is more closely associated with multiple listing than it is with
size. There is therefore an expectation that smaller multiple listed companies are associated with R&D intensity.
Experienced non-executive directors support the segregation of decision-making and decision-management,
preferring to spread decision making-power; as such, the dual role of chair and chief executive officer is not
often found where these governance mechanisms exist. Furthermore, as this role duality suppresses executive
remuneration, and as experienced non-executive directors appear to be aligned to directors interests in as far as
compensation is concerned, it may be expected that experienced non-executive directors may not favour the
appointments of a combined chair and chief executive. Of additional interest is the favourable interaction
between experienced non-executive directors and the appointment of a chair who is a non-executive director that
may be attributed to the alignment of non-executive agendas. However, it is more likely that non-executive
chairs favour boards that have a significant number of experienced non-executive directors. Nevertheless, such
non-executive chairs are not common amongst multiple listed companies nor are they found in firms in which a
dual role exists between the chair and the chief executive.

Table 1 Panel B. Descriptive statistics by industry

Industry Group R&D SIZE EXECREM NONEXEC DUALITY CNED MLTL
Mean
BASIC 0.003 6.481 0.490 2292.469 0.065 0.629 0.210
CHEM 0.015 5.936 0.544 2154.764 0.080 0.600 0.280
ENG 0.017 6.529 0.436 1526.328 0.186 0.558 0.256
ELEC 0.096 5.777 0.496 1620.832 0.100 0.380 0.300
PHAR 0.708 5.126 0.518 1629.219 0.000 0.615 0.538
RET 0.006 6.043 0.497 1694.411 0.170 0.426 0.106
COMP 0.025 5.231 0.493 1993.988 0.106 0.504 0.142
SERV 0.007 5.915 0.483 1618.296 0.121 0.569 0.172
Standard Dev
BASIC 0.007 1.749 0.147 1787.529 0.248 0.487 0.410
CHEM 0.020 1.930 0.196 3101.887 0.277 0.500 0.458
ENG 0.017 1.979 0.210 1335.894 0.394 0.502 0.441
ELEC 0.178 2.447 0.230 2725.804 0.303 0.490 0.463
PHAR 1.187 3.032 0.263 1791.161 0.000 0.506 0.519
RET 0.018 1.934 0.145 1343.355 0.380 0.500 0.312
COMP 0.064 1.855 0.149 2895.665 0.309 0.502 0.350
SERV 0.018 1.729 0.182 1733.180 0.329 0.500 0.381

Panel B of Table 1 indicates the variation in descriptive statistics by industry. The results provide further support
that R&D intensity may be a substitute for industry group given that BASIC industries are the least R&D
intensive and PHAR industries highly R&D intensive. The results support the premise that R&D intensive firms
disclose more intangibles; although these firms are generally smaller they are nevertheless multiple listed.
Governance mechanisms ensure that an acceptable number of experienced non-executive directors are appointed

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in these firms and that executives are adequately compensated. Although such firms as those found in PHAR
industries support the existence of a non-executive chair, none of these companies is chaired by their chief
executive. In contrast, firms in BASIC industries are very large and are less likely to list on an additional
exchange.

Table 1 Panel C. Descriptive statistics by governance dummy variable

Variable DUALITY CNED
Mean
DISC 0.558 0.547
SIZE 5.986 5.578
NONEXEC 0.366 0.549
EXCREM 1848.740 1721.993
Standard deviation
DISC 0.130 0.118
SIZE 2.700 1.806
NONEXEC 0.230 0.122
EXCREM 4268.706 1625.473
Notes: *** p-value <0.01; ** p-value <0.05; * p-value <0.10; Pearson’s coefficients reported for pairs of
continuous variables and Spearman for pairings involving dichotomous variables.

Moreover, these firms generally have less well-paid executives; this may be consistent with the existence of the
highest concentration of experienced non-executives and highest number of non-executive chairs for any
industry. These relationships are generally reflected in industries of similar R&D intensity. BASIC industries are
associated with RET and SERV industries whereas the characteristics of PHAR industries are found in ELEC
and COMP industries. In Panel C of Table 1, the results illustrate that duality in the chair and chief executive
promotes intangibles disclosure, accountability and transparency marginally more than the duality in the
non-executive chair. Firms that appoint a dual chair and chief executive officer are larger than those appointing a
non-executive chair; these firms employ less experienced non-executive directors as a result it appears that
executives in these firms receive slightly less compensation. These relationships are borne in mind for the
purpose of specifying and reporting the results of the inferential models below.
3.2 Regression Analysis
This section reports the results of the relation between disclosure, heterogeneous firm resources and governance
characteristics. Table 2 presents the results of the inferential models; Models 1 to 7 present the results using
non-parametric quantile regression (QREG), since ordinary least squares (OLS) model residuals demonstrated
non-normal characteristics. Models 8 and 9 report results for selected OLS specifications using
heteroscedasticity adjusted standard errors, as these demonstrate normal characteristics and are therefore
presented in Table 2 for reference and comparison.

Table 2. Model (1) regression results

Model 1 2 3 4 5 6 7 8 9
Dependent variable DISC DISC DISC DISC DISC DISC DISC DISC DISC
Independent variables
0.564*** 0.452*** 0.319*** 0.320*** 0.304*** 0.566*** 0.310*** 0.346*** 0.352***
CONSTANT
(12.52) (19.14) (9.00) (9.47) (7.04) (11.61) (8.78) (14.50) (12.04)
0.177 0.079** 0.013 0.030*
R&D
(0.78) (2.49) (0.67) (1.71)
0.017 0.017 0.016 0.010 0.012
MLTL
(1.00) (1.03) (0.75) (0.56) (0.09)
0.059* 0.059* 0.035 0.059 0.062* 0.034
NONEXEC
(1.68) (1.72) (0.86) (1.33) (1.85) (1.17)
0.000 0.000 0.000 0.000 0.000 0.000
EXECREM
(1.33) (0.95) (1.25) (0.62) (0.88) (1.07)
0.009 0.022 0.009 0.006 -0.001
DUALITY
(0.48) (0.98) (0.38) (0.32) (-0.03)
-0.022* -0.022* -0.020 -0.023* 0.018*
CNED
(-1.72) (-1.79) (-1.24) (-1.75) (-1.72)

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0.026*** 0.018*** 0.018*** 0.019*** 0.019*** 0.021*** 0.020*** 0.024*** 0.021***

SIZE
(8.15) (4.75) (4.80) (5.20) (4.29) (5.03) (5.26) (10.06) (6.61)
-0.269*** -0.261***
CHEM
(-5.80) (-5.36)
-0.245*** 0.019 0.015 0.033 -0.242*** 0.018 -0.012 -0.005
ENG
(-5.64) (0.63) (0.51) (0.90) (-5.35) (0.59) (-0.52) (-0.23)
-0.131*** 0.145*** 0.133*** 0.155*** -0.122*** 0.138*** 0.109*** 0.110***
ELEC
(-3.10) (4.95) (4.70) (4.41) (2.76) (4.68) (4.35) (4.40)
0.251*** 0.249*** 0.264*** 0.249*** 0.211*** 0.231***
PHARM
(6.20) (6.34) (5.34) (5.62) (7.97) (9.91)
-0.248*** 0.018 0.016 0.026 -0.242*** 0.020 0.004 0.004
RETAIL
(-5.74) (0.60) (0.55) (0.74) (-5.46) (0.66) (0.15) (0.16)
-0.101** 0.160*** 0.159*** 0.166*** -0.100** 0.159*** 0.128*** 0.127***
COMP
(-2.49) (6.15) (6.37) (5.25) (-2.46) (6.06) (6.28) (6.27)
-0.115*** 0.145*** 0.141*** 0.155*** -0.115*** 0.145*** 0.115*** 0.118***
SERV
(-2.70) (5.08) (5.15) (4.46) (2.65) (5.04) (5.17) (5.40)
Shapiro-Wilk p-value 0.607 0.614
F 34.64*** 27.36***
Adj R2 0.224 0.046 0.232 0.232 0.229 0.231 0.233 0.367 0.373
N 439 439 439 439 439 439 439 439 439
Notes:
Numbers in parentheses are t-statistics based on White’s (1980) heteroscedasticity consistent estimation
matrix.Significance levels (one-tailed test except intercept terms and industry dummies):
*** p < .01; ** p < .05; * p < .10

Table 2 reports Shapiro-Wilk test results for residual normality in these models. The interaction between
intangibles disclosure and the heterogeneous asset base is examined in Models 1, 2 and 8; that with governance
mechanisms in Models 3, 4, 5, 6 and 9; and the combined interaction between disclosure, heterogeneous firm
resources and governance characteristics in Model 7. Consistent with Abeysekera & Guthrie (2005) and
Garcia-Meca & Martinez (2005), the results of all inferential models confirm that large firms’ that possess
imitable and unique intangible assets are able to signal SCA. In Model 2, although providing a lower explanatory
factor in the QREG model relative to other inferential models, the results of Model 8, the OLS model do
indicate a positive influence of R&D activities on intangibles disclosure. The interaction between the scope and
complexity of the organisation’s activities and disclosure are examined by both the industry dummies and the
investment in R&D. Models 1 and 2 indicate that R&D intensity may be a substitute for industry complexity and
may as suggested by Nixon (1997), be linked to the RBV with the signalling approach. Firms in such industries
as PHARM, ELEC and COMP may be prejudiced by the current reporting regime that is unable to account for
the complex nature of intangible resources. To increase and sustain value to shareholders, the onus is on
management to signal SCA through intangibles disclosure; such signals enhance transparency and accountability,
reduce information asymmetry and are not likely to accrue proprietary costs. The lack of competitive losses
associated with such disclosures has been attributed to the unique nature of intangibles.
Model 3 to 7 and Model 9 present the interaction between the heterogeneous asset base and the firm’s corporate
governance mechanisms and structures of accountability. Industry dummies control for the existence of
intangibles resources as represented by complexity in operations; governance mechanisms, experienced
non-executive directors and the separation of the dual role of non-executive chair promote intangibles disclosure
as presented by the results of Models 3, 4 and 7. However, the influence of experienced non-executive directors
is limited when the dual role is not in place as illustrated by Model 5. Model 4 indicates little variation in
disclosure whether firms combine the roles of chief executive officer and chair or not; other governance
measures effect on disclosure however is influenced by the presence or absence of complimentary structures.
Models 3, 4 and 7 illustrate this finding; within firms that are multiple listed, non-executive chairs and
experienced non-executive directors are significantly more influential in promoting intangibles disclosure than in
companies with one listing status. The increase in reporting requirements due to multiple listing appears evident
here, however where these multiple listed companies do not appoint a non-executive chair, experienced
non-executive directors become ineffective in ensuring accountability and transparency through disclosure. The
results support the analysis based on the descriptive statistic reported in section 3.1 above as it appears
governance mechanisms are more effective when working in cooperation.

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Individually, other board related governance variables including role duality in the chief executive officer and
chair, multiple listing and executive remuneration are insignificant in influencing the signalling of intangibles as
illustrated by Model 3 to 7 and by Model 9. The results illustrate that experienced non-executive directors
promote transparency and accountability, although this relationship is found to be weak as illustrated by Model 9.
The effectiveness of this role is dependent on the chair being an executive director and further that firms have
supporting governance structures modelled on multiple listed companies. Such structures where roles and
responsibilities are separated allow experienced non-executive directors to compliment the existing governance
mechanisms in enhancing VDIC particularly where the resource base is non-replicable. Thus, the absence of the
separation of decision control and decision management (Fama & Jensen, 1983) leads to a lack of transparency
and accountability. Furthermore, a concentration of decision-making power may mitigate the independence of
the board and reduce its effectiveness in its monitoring role. The results are consistent with the findings of
Cerbioni and Parbonetti (2007) who identified that chief executive officer duality suppresses the disclosure of
forward-looking IC information. Directors’ compensation has been associated with reduced agency costs;
however, the results do not provide evidence for this hypothesis. The theoretical basis for linking executive
remuneration with intangible disclosure levels has not been confirmed in contrast to Lufti (1989), where
executive remuneration is insignificant in explaining the variation in intangibles disclosure. Directors’
compensation is therefore insufficient in influencing management into better governance (Ooghe & De Langhe,
2002).
Although some prior studies have confirmed multiple listing as significant in disclosure studies, the results
indicate that VDIC may be independent of the number of listings a firm may have. As multiple listing may
expand both the diversity and the operating sectors of a firm, it may promote transparency and accountability in
reducing asymmetric information. Furthermore, additional disclosures may be required to account for the
increase in the complexity of operations. Nevertheless, the results of all models indicate that the incremental
reporting requirements and additional governance measures attributed to a foreign listing may not have a direct
impact on the signalling of intangibles. Overall, the QREG models report results that are consistent with those of
the robust OLS models.
4. Discussion
This paper examines the determinants of the disclosure of intangibles, specifically the interaction of
heterogeneous assets and governance mechanisms on disclosure. As a measure of disclosure, each firm was
allocated a disclosure score based on 23 IC attributes. The regression results show that size as a measure of
scope, R&D intensity as a measure of complexity of operating activities, and the separation of the roles of chair
and non-executive director, complimented by the existence of experienced non-executive directors as
governance mechanisms, support the analytical and theoretical framework as illustrated in Figure 1. Industry
dummy variables illustrate the variation in the signalling of intangibles with increasing complexity of operations
and R&D intensity. Overall, the results are consistent with the separate effects of resource attributes on the
disclosure of intangible assets (Archambault & Archambault, 2003; Citron et al., 2005) and with the role of such
disclosures as signals (Bozzolan et al., 2003; Garcia-Meca et al., 2005). The results suggest that the influence of
board composition on disclosure supports the hypothesis that governance mechanisms enhance accountability
and transparency (Haniffa & Cooke, 2002; Lufti, 1989; Malone et al., 1993).
The results indicate that investment in intangible resources and their disclosure through transparent governance
structures are potential mechanisms to secure competitive advantage. These governance structures have been
seen to be more effective when not in conflict as such the mere presence of intangible resources may not be a
sufficient condition for their disclosure in the annual report. Governance mechanisms that encourage the
separation of dual roles and support the appointment of experienced non-executive directors promote
transparency and accountability.
Industry dummies and R&D intensity illustrate that those technological and innovative industries, that posses
valuable, rare, inimitable and non-substitutable assets, are able to sustain their competitive advantage through
intangibles disclosure (Barney, 1991). These intangible assets are found in firms operating in highly complex
and R&D intensive industries that may be prejudiced by the current reporting practice that lacks adequate
procedures to identify, organise and manage investment in intangibles such as R&D development costs. These
firms have been found to be highly technological and innovative and therefore linked to non-manufacturing
and/or service industries. Other characteristics that have been attributed to these firms include being IA intensive,
having economies of scale, having minimal or zero marginal cost as most services are outsourced. The results
indicate that PHARM, ELEC and COMP are industries that fall under this category.

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The current paper is the first to study intangibles disclosure by examining the interaction of firm resources,
corporate governance and intangibles disclosure within a RBV and signalling theoretical framework. Effective
corporate governance mechanisms enhance transparency and accountability for firms undertaking highly
complex operations. This is especially so for firms that possess VRIN intangibles, assets that are not easily
imitated and as such do not accrue proprietary costs on disclosure. There may be a potential benefit in future
research on temporal links between IC value drivers and IC performance; future research may also investigate
how disclosure of SCA influences the market and financial risk attributed to firms.
Acknowledgements
I am indebted to Professor S. Toms, my PhD supervisor and mentor, for useful comments, criticisms and
suggestions on an earlier draft.
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Note
Note 1. Investment in strategic human resource assets (Mueller, 1996; Wright et al., 1994) is a sufficient but not
a necessary condition for realized super-normal profits, since the employment of such assets simultaneously
leads to the creation of internal rent appropriation possibilities.

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