ajing li university of bradford , richard pike & roszaini...
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This article was downloaded by: [Universitas Dian Nuswantoro], [Ririh Dian Pratiwi SE Msi]On: 29 September 2013, At: 20:53Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK
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Intellectual capital disclosure and corporategovernance structure in UK firmsJing Li a , Richard Pike b & Roszaini Haniffa aa University of Bradfordb School of Management, University of Bradford, Emm Lane, Bradford, UK, BD9 4JL E-mail:Published online: 04 Jan 2011.
To cite this article: Jing Li , Richard Pike & Roszaini Haniffa (2008) Intellectual capital disclosure and corporate governancestructure in UK firms, Accounting and Business Research, 38:2, 137-159, DOI: 10.1080/00014788.2008.9663326
To link to this article: http://dx.doi.org/10.1080/00014788.2008.9663326
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1. IntroductionThe purpose of this paper is to investigate the in-fluence of corporate governance on intellectualcapital disclosure in corporate annual reports, con-trolling for other firm characteristics. Intellectualcapital is increasingly recognised as having muchgreater significance in creating and maintainingcompetitive advantage and shareholder value(Tayles et al., 2007). Definitions of intellectualcapital vary (for example, Stewart, 1997; Mouritsen,1998). One of the most comprehensive definitionsof intellectual capital is offered by CIMA (2001):‘… the possession of knowledge and experience,professional knowledge and skill, good relation-ships, and technological capacities, which whenapplied will give organisations competitive advan-tage.’ Sveiby (1997) suggests that the concept ofintellectual capital can be categorised into human,structural and organisational capital, while Guthrieand Petty (2000) offer an alternative categorisa-tion: internal structure, external structure andhuman capital. The various forms of intellectualcapital disclosure are valuable information for in-vestors as they help reduce uncertainty about fu-ture prospects and facilitate a more precisevaluation of the company (Bukh, 2003). However,financial reports fail to reflect such a wide range ofvalue-creating intangible assets (Lev and Zarowin,1999), giving rise to increasing information asym-metry between firms and users (Barth et al., 2001),
and creating inefficiencies in the resource alloca-tion process within capital markets.
A number of research reports (e.g. FASB, 2001;ASB, 2007) and academic studies (e.g. Lev, 2001;Mouritsen et al., 2001) have called for greater dis-closure of non-financial indicators of investmentin intangible assets. Cañibano et al. (2000) argue thatthe cost associated with a radical change in the ac-counting system to make it more value relevant forintellectual capital intensive firms is unaffordableand that the sensible approach towards the en-hancement of financial reports is to encourage vol-untary disclosure of intellectual capital information.
Keenan and Aggestam (2001) argue that respon-sibility for the prudent investment of intellectualcapital resides with corporate governance, andthat, depending on the firm’s characteristics andorientation, the governance of publicly-ownedfirms may need to develop new structures andprocesses in annual reports for communicating in-formation about the value created for stakeholdersthrough the firm’s intellectual capital. However, asdiscussed in a later section, the empirical evidencefrom prior studies is limited, with small samplesizes prohibiting more rigorous statistical analysisand external validity. For example, we know verylittle about the main determinants of the variationin levels of intellectual capital disclosure in annu-al reports across firms, including the effects ofgood governance mechanisms.
This paper examines the influence of corporategovernance factors on intellectual capital disclo-sure, and the subcategories comprising it, usingvarious disclosure measures. We hypothesise thatsignificant relationships exist between intellectualcapital disclosure in annual reports and board com-position, role duality, ownership concentration,audit committee size and frequency of audit com-
Accounting and Business Research, Vol. 38. No. 2. pp. 137-159. 2008 137
Intellectual capital disclosure and corporategovernance structure in UK firmsJing Li, Richard Pike and Roszaini Haniffa*
Abstract—This paper investigates the relationship between intellectual capital disclosure and corporate governancevariables, controlling for other firm-specific characteristics, for a sample of 100 UK listed firms. Intellectual capi-tal disclosure is measured by a disclosure index score, supported by word count and percentage of word count met-rics to assess the variety, volume and focus of intellectual capital disclosure respectively. The independent variablescomprise various forms of corporate governance structure: board composition, ownership structure, audit commit-tee size and frequency of audit committee meetings, and CEO role duality. Results of the analysis based on the threemeasures of intellectual capital disclosure indicate significant association with all the governance factors except forrole duality. The influence of corporate governance mechanisms on human, structural and relational capital disclo-sure, based on all three metrics, is also explored.
Keywords: intellectual capital disclosure; corporate governance; content analysis; annual report
*The authors are at the University of Bradford. They wishto thank Musa Mangena, the anonymous reviewers and the editor for their helpful comments.
Correspondence should be addressed to: Professor RichardPike, University of Bradford, School of Management, EmmLane, Bradford, UK, BD9 4JL. E-mail: [email protected]
This paper was accepted for publication in March 2008.
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mittee meetings, controlling for listing age, firmsize and profitability. Using content analysis andregressing the three forms of intellectual capitaldisclosure measures on the explanatory variables,we find support for all hypotheses with the excep-tion of role duality.
The remainder of this paper is organised as fol-lows: the next section reviews the empirical litera-ture on intellectual capital disclosure. Thehypothesis development is outlined in Section 3,followed by the research design in Section 4.Section 5 presents findings on intellectual capitaldisclosure practices from multiple regressionanalyses, and examines the working hypotheses.Finally, Section 6 discusses the findings, implica-tions and limitations of the study.
2. Literature on intellectual capital disclosure studiesInformation on intellectual capital is important tostakeholders in their decision-making. Within anagency context, Jensen and Meckling (1976) arguethat greater disclosure reduces the uncertainty facing investors and thus reduces a firm’s cost of capital. Managers should therefore be willing to dis-close intellectual capital information in order to en-hance the firm’s value by providing investors with abetter assessment of the financial position of thefirm and help reduce the volatility of stock returns.Barth et al. (2001) observe that analyst coverage isgreater for firms investing more heavily in researchand development and advertising, while empiricalstudies suggest a positive share price impact arisesfrom specific intellectual capital indicators such as research and development (R&D) expenditure(Amir and Lev, 1996), capitalisation of software de-velopment expenditure (Aboody and Lev, 1998),and customer satisfaction (Ittner and Larker, 1998).
Gibbins et al. (1990) explore the voluntary dis-closure process giving rise to disclosure outputs inresponse to internal and external stimuli. Theyargue that a company’s readiness to disclose is afunction of its general disclosure position (for ex-ample, an uncritical adherence to information dis-closure norms or to use disclosure as opportunityto gain advantage or boost stock price), antecedents(for example, corporate history, corporate strategy,and market factors), structure, and the use of con-sultants and advisors. While corporate governancemechanisms are not specifically identified, theyhave relevance to all these independent variables,particularly to structure, where governance in-volves the establishing of clear policies.
Abeysekera (2006) observes that the develop-ment of a theoretical framework underlying intel-lectual capital disclosure is in its infancy, with fewstudies providing a strong theoretical basis for in-terpreting their findings. However, the literatureoffers a few theoretical perspectives that may help
explain the variation of intellectual capital disclo-sure. These include arguments based on legitima-cy and stakeholders (Abeysekera and Guthrie,2005), signalling (García-Meca and Martínez,2005), media agenda setting (Sujan andAbeysekera, 2007), agency (Patelli and Prencipe,2007), and information asymmetry (Amir and Lev,1996).
In a review of the current state of financial andexternal reporting research, Parker (2007) identi-fied intellectual capital accounting as a major areafor further research. Most intellectual capital dis-closure studies are cross-sectional and countryspecific. Examples include studies in Australia(e.g. Guthrie and Petty, 2000; Sujan andAbeysekera, 2007), Ireland (Brennan, 2001), Italy(e.g. Bozzolan et al., 2003), Malaysia (Goh andLim, 2004), UK (e.g. Williams, 2001), and Canada(Bontis, 2003). Relatively few longitudinal studieshave been reported (e.g. Abeysekera and Guthrie,2005). Some studies focus on specific aspects ofintellectual capital disclosure, such as human cap-ital reporting (e.g. Subbarao and Zeghal, 1997),while others conduct international comparativestudies (e.g. Vergauwen and van Alem, 2005;Cerbioni and Parbonetti, 2007). Some intellectualcapital disclosure studies have looked beyond an-nual reports to examine other communicationchannels such as analyst presentations (García-Meca et al., 2005).
Most intellectual capital disclosure studies em-ploy content analysis as the research method, butsome use questionnaire surveys (e.g. Bontis,1998). Guthrie and Petty’s (2000) analysis of in-tellectual capital reporting practices suggests thatdisclosure has been expressed in discursive ratherthan numerical terms and that little attempt hasbeen made to translate the rhetoric into measuresthat enable performance of various forms of intel-lectual capital to be evaluated.
Studies have also been conducted to explore in-tellectual capital related issues from the firm’s per-spective. Chaminade and Roberts (2003)investigate the implementation of intellectual cap-ital reporting systems in Norway and Spain.Habersam and Piper (2003) employ case studies toexplore the relevance and awareness of intellectu-al capital in hospitals. Studies that looked at possi-ble determinants of voluntary intellectual capitaldisclosure include García-Meca et al. (2005) andCerbioni and Parbonetti (2007). Based on analystpresentation reports of listed Spanish companies,García-Meca et al. (2005) found significant asso-ciation between intellectual capital disclosure andsize and type of disclosure meeting but not owner-ship diffusion, international listing status, industrytype and profitability. Based on analysis ofEuropean Biotechnology companies over a periodof three years, Cerbioni and Parbonetti (2007)
138 ACCOUNTING AND BUSINESS RESEARCH
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found governance related variables to strongly in-fluence voluntary intellectual capital disclosure.
In the UK, there has been a limited number of in-tellectual capital disclosure studies compared to itsEuropean counterparts. Williams (2001) conduct-ed a cross-sectional study of 31 companies whileBeattie et al. (2002) undertook a study of 11 com-panies in the food sector. The small sample sizesrestrict generalisation and meaningful interpreta-tion of intellectual capital disclosure. Roslenderand Fincham (2004) explore intellectual capitalawareness among UK firms, and the reasons andmotives underlying such interest.
The foregoing discussion suggests that the liter-ature on the determinants of intellectual capitaldisclosure is limited and inconclusive. Our studybuilds on the previous literature of intellectual cap-ital disclosure practice within a UK context andexamines its relationship with corporate gover-nance structures, listing age, profitability and size.
3. Determinants of intellectual capital disclosure and development of hypothesesCorporate governance mechanisms
Corporate governance is a framework of legal,institutional, and cultural factors shaping the pat-terns of influence that stakeholders exert on mana-gerial decision-making (Weimer and Pape, 1999).The justification for considering corporate gover-nance is that the board of directors manages infor-mation disclosure in annual reports and thereforeconstituents of boards may be important. Holland(2006a: 147) found that boards of directors are atthe heart of corporate financial communications,having active roles in the disclosure process relat-ed to: (1) the provision of primary information re-garding the corporate value-creation process, andtheir contribution towards it; (2) the provision ofinformation about themselves in terms of theirskills in managing the business; (3) the manner inwhich they are organised to conduct financialcommunications; (4) their reputation for disclo-sure honesty; and (5) information about how theirown pay and wealth is tied to company fortunes.
Agency theory provides a framework for linkingvoluntary disclosure behaviour to corporate gover-nance, whereby control mechanisms are designedto reduce the agency problem arising from the sep-aration between ownership and management(Welker, 1995). This argument can be extended tointellectual capital disclosure, whereby manage-ment can determine the level of disclosure andthereby reduce investor uncertainty relating to theimpact of intellectual capital on the firm’s value.High intellectual capital disclosure is therefore ex-pected to provide a more intensive monitoringpackage for a firm to reduce opportunistic behav-iour and information asymmetry.
Adoption of internal control devices, such asaudit committees and non-executive directors, andseparation of the roles of chairman and chief exec-utive, may enhance monitoring quality in criticaldecisions about intellectual capital investment andperformance (Keenan and Aggestam, 2001). Thisis likely to reduce the scope for managerial oppor-tunism and reduce benefits from withholding in-formation, and, as a consequence, intellectual capitaldisclosure in annual reports should be improved.
Board composition – proportion of independentnon-executive directors (INED)
The board of directors is an internal controlmechanism intended to take decisions on behalf ofthe shareholders and to ensure that managementbehaviour is consistent with owners’ interests.Based on resource dependence theory, Haniffa andCooke (2005) argue for more non-executive direc-tors on the board as they can provide wider ex-pertise, prestige and contacts, and play a key rolein influencing disclosure. Extending this argu-ment, and that of Gibbins et al. (1990), to intellec-tual capital, we suggest that the wider expertiseand experience of non-executive directors on theboard will encourage management to take a dis-closure position beyond a ritualistic, uncritical ad-herence to prescribed norms, to a more proactiveposition reflecting the value relevance of intellec-tual capital to stakeholders.
Findings from prior voluntary disclosure studiesthat considered board composition as a possibledeterminant of voluntary disclosure are mixed;some find that the proportion of non-executive di-rectors is positively related with the board’s abili-ty to influence voluntary disclosure decisions (e.g.Beasley, 1996; Chen and Jaggi, 2000), others findno relationship (Ho and Wong, 2001; Brammerand Pavelin, 2006), and yet others observe a nega-tive relationship (Eng and Mak, 2003; Haniffa andCooke, 2005). One reason may be that non-execu-tive directors are not necessarily independent.Independent non-executive directors are typicallyindividuals with relevant expertise and profession-al reputations to defend, with no management roleor links with the company.1 Cotter and Silvester
Vol. 38 No. 2. 2008 139
1 The revised Combined Code (2006) recommends that atleast half of the board, excluding the chairman, should com-prise non-executive directors determined by the board to beindependent as defined by criteria in the Code, in order thatnon-executive directors are able to discharge their responsibil-ities in an objective manner, without interference, bias orfavouritism. For example, a director should not have been anemployee of the group within the last five years, had a mate-rial business relationship with the company within the lastthree years, received additional remuneration from the compa-ny apart from a director’s fee, participate in the company’sshare option or a performance-related pay scheme, close fam-ily ties with any of the company’s advisers, directors or senioremployees, hold cross-directorships or significant links withdirectors, or served on the board for more than nine years.
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(2003) argue that independent non-executive di-rectors are in a better position to monitor executivemanagement. In one of the few studies capturingindependent non-executive directors, Patelli andPrencipe (2007) found a positive correlation withthe amount of voluntary information disclosed bycompanies in their annual reports. We also captureindependent non-executive directors (INED) andargue that:H1: There is a positive relationship between the
level of intellectual capital disclosure andthe proportion of independent non-executivedirectors to the total number of directors onthe board, ceteris paribus.
Role duality (RDUAL)Another way to examine independence of the
board is to consider role duality, a board leadershipstructure in which the same person undertakesboth the roles of chief executive and chairman.2There is widespread acknowledgement that a dom-inant personality commanding a firm may be detri-mental to the interests of shareholders, and thisphenomenon has been found to be associated withpoor disclosure (Forker, 1992) and CEO entrench-ment, resulting in ineffective monitoring of mana-gerial opportunistic behaviour (Haniffa andCooke, 2002). Concentration of decision-makingpower resulting from role duality could impair theboard’s oversight and governance roles, includingdisclosure policies. Separation of the two rolesprovides the essential checks and balances onmanagement behaviour (Blackburn, 1994), as rec-ommended in the revised Combined Code (2006).3Employing similar arguments for role duality asfor independent non-executives, we hypothesisethat:H2: There is a negative relationship between the
level of intellectual capital disclosure androle duality, ceteris paribus.
Ownership structure – share concentration(SCON)
The power of stakeholders to influence manage-ment is a function of the resources they controlthat are essential to the corporation (Smith et al.,2005). Ownership structure therefore will influ-ence the level of monitoring and thereby the levelof voluntary disclosure (Eng and Mak, 2003).Agency theory argues that with greater ownershipdiffusion, firms are more likely to experience pres-sure from shareholders for greater disclosure to re-duce agency costs and information asymmetry(Raffournier, 1995). In contrast, firms with close-ly-held ownership are expected to have less infor-mation asymmetry between management anddominant shareholders who typically have accessto the information they need and can provide an
active governance system that is difficult forsmaller, more passive and less-informed investors(Cormier et al., 2005).4 This is particularly rele-vant to intellectual capital disclosure because fundmanagers have access to such information via pri-vate communication channels (Holland, 2006b).Hence, we hypothesise that:H3: There is a negative relationship between the
level of intellectual capital disclosure andconcentrated share ownership, ceterisparibus.
Audit committee size (SAC) and frequency ofmeetings (MAC)
Board monitoring is a function of not only thestructure and composition of the board, but also ofthe board’s subcommittees where much of the im-portant processes and decisions are monitored andtaken (Cotter and Silvester, 2003). The role ofaudit committees has developed over the years tomeet the challenges of changing business, socialand economic environments. The Smith Report(2003) in the UK identifies the role of audit com-mittees as ensuring that the interests of sharehold-ers are properly protected in relation to financialreporting and internal control. It further recom-mends audit committees to review the significantfinancial reporting issues and judgments made inconnection with the preparation of the company’sfinancial statements, interim reports, preliminaryannouncements and related formal statements,such as the operating and financial review and therelease of price-sensitive information. As such,audit committees can be expected to have a signif-icant impact on value-relevant information disclo-sure, of which intellectual capital forms a largeelement in many firms.
Effective audit committees should improve in-ternal control and act as a means of attenuatingagency costs (Ho and Wong, 2001), and as a pow-erful monitoring device for improving value-rele-vant intellectual capital disclosure. The presenceof an audit committee has been found to be associ-ated with more reliable financial reporting
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2 Role duality is not common among listed companies sincethe majority comply with the recommended code of corporategovernance.
3 However, in voluntary disclosure studies, Haniffa andCooke (2002) and Ho and Wong (2001) failed to find any re-lationship between the extent of voluntary disclosure and roleduality.
4 Prior disclosure studies provide mixed evidence.Cormier et al. (2005) and Brammer and Pavelin (2006) findsignificant negative associations between ownership concen-tration and engagement in environmental reporting practices.Patelli and Prencipe (2007) find a positive relationship be-tween share ownership diffusion and voluntary disclosure.However, Eng and Mak (2003) fail to find any significant as-sociation between blockholder ownership and voluntary dis-closure.
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(McMullen, 1996), enhanced quality and in-creased disclosure (Ho and Wong, 2001).However, Mangena and Pike (2005) find no rela-tionship between audit committee size and the ex-tent of voluntary disclosure in interim reports.Inactive audit committees are unlikely to monitormanagement effectively and adequate meetingtime should be devoted to the consideration ofmajor issues (Olson, 1999). Price Waterhouse(1993) recommended that audit committees shouldhold a minimum of three or four meetings a yearand special meetings when necessary.
Given the increasing importance of intellectualcapital, we expect larger audit committees, meet-ing more frequently, to have greater influence inoverseeing intellectual capital disclosure practice.Therefore, our next two hypotheses are as follows:H4: There is a positive relationship between the
level of intellectual capital disclosure andaudit committee size, ceteris paribus.
H5: There is a positive relationship between thelevel of intellectual capital disclosure andfrequency of audit committee meetings, ceteris paribus.
Control variablesThe length of time a company has been listed on
a capital market (AGE) may be relevant in ex-plaining the variation of disclosures. Younger list-ed companies without an established shareholderbase are expected to be more reliant on externalfund raising than more mature companies (Barnesand Walker, 2006) and have greater need to reducescepticism and boost investor confidence (Haniffaand Cooke, 2002). Hence, we expect a negative re-lationship between firms’ listing age and level ofintellectual capital disclosure. Profitability (ROA)may be the result of continuous investment in in-tellectual capital and firms may engage in higherdisclosure of such information to signal the signif-icance of their decision in investing in it for long-term growth in the value of the firm. We thereforeexpect a positive relationship between profitabilityand level of intellectual capital disclosure. Largefirms are more visible and more likely to meet in-vestors’ demand for information and we expect apositive relationship between size of company(SA) and level of intellectual capital disclosure.
4. Research method4.1. Sampling design
This study examines intellectual capital disclo-sure in corporate annual reports of UK fully listed companies on the London Stock Exchange(LSE) for financial year-ends between March 2004 and February 2005. Firms in seven industrysectors containing high intellectual capital compa-nies (Pharmaceuticals & Biotechnology, IT,
Telecommunications, Business Services, Media &Publishing, Banking & Insurance, and FoodProduction & Beverage) were selected.5 This pro-vided us with a population size of 319 companies,from which a sample size of 100 was selected(31%). As the number of companies in each indus-try group is not the same, proportionate stratifiedsampling was applied (Moser and Kalton, 1996).
4.2. Development of the research instrumentContent analysis was used to collect the neces-
sary data. An essential element of content analysisis the selection and development of categories intowhich content units can be classified. Various au-thors (e.g. Sveiby, 1997; Meritum, 2002) suggestthat intellectual capital can be grouped into threesubcategories: (1) Human capital, for example,staff education, training, experience, knowledgeand skills, (2) Structural capital, covering internalstructures such as R&D, patents, managementprocesses, and (3) Relational capital, covering ex-ternal relationships such as customer relations,brands and reputation. These forms of intellectualcapital can be leveraged to create competitive ad-vantage and value for stakeholders. However,Beattie and Thomson (2007) observe that there isno consensus or precise definition of the con-stituents of such categories, giving rise to difficul-ties for annual report preparers and researchersseeking to quantify intellectual capital disclosure.Habersam and Piper (2003) argue for a compre-hensive representation of intellectual capital, in-cluding metric and non-metric forms, in order tobetter discern its different dimensions and degreesof transparency. They further suggest a fourth in-tellectual capital category, namely ‘ConnectivityCapital’ linking the other three forms.
The categories and items in our research instru-ment were drawn from previous literature on intel-lectual capital definition and classification. Themajority of previous intellectual capital disclosurestudies have adopted or adapted Sveiby’s (1997)intellectual capital framework, which typicallycontains 22–25 items (Beattie and Thomson,2007). The problem with too few coding cate-gories is that it potentially increases the likelihoodof random agreement in coding decisions and sub-sequently results in an overestimation of reliabili-ty (Milne and Adler, 1999). Similarly, highernumbers of items in the instrument increase thecomplexity (Beattie and Thomson, 2007) and maypotentially increase coding errors (i.e. reliability)(Milne and Adler, 1999). However, in order toachieve greater variation and better understandingof intellectual capital disclosure, we devised a
Vol. 38 No. 2. 2008 141
5 Given the bias towards high intellectual capital industrysectors, the sample cannot claim to represent the intellectualcapital disclosure practice of all LSE listed UK firms.
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more detailed checklist covering items relating tothe three themes: human capital (HIC), structuralcapital (SIC) and relational capital (RIC), captur-ing information in the forms of text, numerical andgraphical/pictorial. While Guthrie and Petty(2000) highlight the difficulty in seeking to quan-tify the qualitative aspects of intellectual capital,evidence from Habersam and Piper (2003) ques-tions this view. All items in the designed researchinstrument were considered equally applicable andtherefore equally capable of disclosure across allsample firms in all three formats.
The initial draft of the research instrument with150 items was pilot tested by one researcher, usinga sample of annual reports (not included in thefinal sample). Based on feedback from the pilottest and discussion with two other researchers, theinstrument was further modified to ensure that itcaptured the necessary and desired information forwhich it was designed. The research instrumentwas reduced to 61 intellectual capital items inthree forms. The operational definitions and cod-ing rules (see Appendix) were defined by one re-searcher and checked and agreed by the other tworesearchers.
Measurement of dependent variablesBeattie and Thomson (2007) argue that many of
the content analysis research methods adopted inprior studies for intellectual capital disclosuremeasurement lack transparency, specificity, uni-formity and rigour, and that these deficiencies maygive rise to misleading evidence. In this study,scoring of the research instrument was performedmanually covering the whole annual report.6
The dependent variable, intellectual capital dis-closure, is measured using three different metrics:disclosure index (ICDI) to indicate the variety;word count (ICWC) to represent the volume; andword count as a percentage of annual report totalword count (ICWC%) to indicate focus in the an-nual report. Our approach in scoring the items inthe research instrument for the purpose of the dis-closure index is essentially dichotomous in that anitem scores one if disclosed and zero, if it is not.7The intellectual capital disclosure index ICDIj foreach company is calculated based on the disclo-sure index score formula used in Haniffa andCooke (2005) as follows:
where nj = number of items for jth firm, nj = 183(i.e. 61 items in three formats), Xij = 1 if ith itemdisclosed, 0 if ith item not disclosed, so that 0 ≤ICDIj ≤ 1.
The use of a dichotomous procedure in scoringthe instrument for the disclosure index can be crit-
icised because it treats disclosure of one item (re-gardless of its form or content) as being equal, anddoes not indicate how much emphasis is given to aparticular content category. To capture the volumeof intellectual capital content and to partly over-come the problem of using an index score, thisstudy introduces another form of measure, namelyintellectual capital word count (ICWC). Words arethe smallest unit of measurement for analysis andcan be expected to provide the maximum robust-ness to the study in assessing the quantity of dis-closure (Zeghal and Ahmed, 1990). Using thesame research instrument, and taking ‘phrases’, orwhat Beattie and Thomson (2007) term ‘pieces ofinformation’ as the basis of coding, the number ofwords relating to each intellectual capital item inthe checklist was counted and added together to ar-rive at ICWC for each company. Graphical andpictorial messages were excluded from the wordcount measure.8
Coding under ‘phrases’ and word count avoidsthe problem of coding sentences in terms of deci-sions over dominant themes, and the ‘phrases’ re-main meaningful in their own right, while enablingthe measuring of the amount of information pro-vided. Coding annual reports into ‘phrases’ is athree-stage process involving: (1) selection of sen-tences containing intellectual capital information;(2) splitting such sentences into ‘phrases’ and se-lecting only those relating to intellectual capital;and (3) coding ‘phrases’ under each relevantitem(s) in the research instrument. Where a
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6 Three coders independently coded the same four annualreports and Krippendorff’s (1980) alpha was used to test forreliability as it can account for chance agreement among mul-tiple coders. The independent scores were all above the mini-mum 80% threshold for content analysis to be consideredreliable (Riffe et al., 2005) and this was achieved after a sec-ond round of independently coding another four annual re-ports. Only one researcher completed the coding for theremaining 92 annual reports. To aid consistency of scoring, theresearch instrument was completed by one researcher, and toincrease reliability of measurement, rescoring was done on arandom selection of 10 firms three months after initial analy-sis, which confirmed over 90% consistent identification ofcontent in the annual reports.
7 Many prior intellectual capital disclosure studies haveadopted the dichotomous (0:1) coding scheme in measuringintellectual capital disclosure, which is mainly for examiningthe presence/absence of intellectual capital items (e.g. Guthrieand Petty, 2000; Brennan, 2001). Some intellectual capital dis-closure studies used weighted coding schemes, which give uneven scores for quantitative and qualitative information(e.g. Bozzolan, et al., 2003; Sujan and Abeysekera, 2007).Consistent with Cooke (1989), items were not weighted be-cause of potential scoring bias and scaling problems.
8 Beattie and Thomson (2007) identify the problems withword count (such as print size, colour, font variations and dis-closures in graphs/pictures format), and propose a measure ad-dressing the differentiation in length and number of sentencesused in expressing similar meanings encountered by codingsentences.
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‘phrase’ relates to more than one item in the check-list and cannot be split, it is then coded under allthe related items and the word count is evenly dis-tributed across all the items coded. An example isshown as follows,
‘The trust and confidence of all our stakeholders,together with our reputation, are among our mostvaluable assets.’ (AstraZeneca plc 2004 Annualreport).The sentence was split into three ‘phrases’: (1)
The trust and confidence of all our stakeholders,(2) together with our reputation, (3) are among ourmost valuable asset. Phrase 1 was coded under ‘re-lationship with stakeholders’, phrase 2 was codedunder ‘company reputation’ and phrase 3 wasequally distributed between the two items.
Krippendorff (1980) further notes that words area preferred measure when it is intended to measurethe amount of total space devoted to a topic and toascertain the importance of that topic. Althoughword count is not assumed to be representative ofthe quality of disclosure, it is assumed to be in-dicative of the overall responsiveness by corporatemanagement.9 The greater the number of words re-lated to intellectual capital being disclosed in rela-tion to the total number of words in the annualreports, the greater the emphasis given by man-agement on intellectual capital information.Hence, we introduced a third measure, ICWC%,which is the proportion of intellectual capital wordcount to the total word count of the whole annualreport. This measure captures the intellectual cap-ital focus in the annual report. For example, a firmwith a short annual report may have a low ICDIand ICWC but a high ICWC%, conveying to thereader the importance placed by management onintellectual capital information.
Measurement of independent variablesThe independent variables are categorised into
two groups: corporate governance and controlvariables. Data are drawn from corporate annualreports and Thomson Research. Table 1 summaris-es the operationalisation of both independent anddependent variables.
4.3. Data analysisMultiple regression is used to test the relation-
ship between intellectual capital disclosure (basedon each of the three measures) and the various cor-porate governance and control variables. To iden-tify potential multicollinearity problems, thecorrelations between independent variables werereviewed and the variance inflation factors (VIF)computed. In addition, tests were conducted fornormality, based on skewness and kurtosis andKolmogorov-Smirnov Lilliefors (for goodness offit), for all dependent and continuous independent
variables and when normality was a problem, thedata was transformed.10 An analysis of residuals,plots of the studentised residuals against predictedvalues as well as the Q-Q plot were conducted totest for homoscedasticity, linearity and normalityassumptions. The regression equation is as follows:
ICD = β0 + β1 INEDi + β2 RDUALi+ β3 SqSCONi + β4 SACi+ β5 MACi + β6 LnAGEi+ β7 ROAi + β8 LnSAi + εi
Where,ICD = Intellectual capital disclosure index
(ICDI), log of intellectual capitalword count (LnICWC), or intellectu-al capital word count percentage(ICWC%);
INED = Proportion of independent non-exec-utive directors on board (proxy forboard composition, %);
RDUAL = 1 if the roles of chairman and CEOare held by the same person; 0 if oth-erwise;
SqSCON = Square root of cumulative sharehold-ing by significant shareholders (i.e.shareholders holding more than 3% oftotal shares outstanding to total sharesoutstanding, %);
SAC = Audit committee size (total numberof directors on the audit committee)(proxy for internal auditing function);
MAC = Frequency of audit committee meet-ings (total number of audit committeemeetings held within the year to its fi-nancial year end) (proxy for internalauditing function);
AGE = Log of length of listing on LSE (list-ing age);
ROA = Return on assets (proxy for firm per-formance: profitability);
LnSA = Log of sales (proxy for firm size);β = parameters;εi = error term; andi = the ith observation.
Vol. 38 No. 2. 2008 143
9 This assumption is based on the belief that managementhas editorial control of content when a large number of de-mands for inclusion of information are likely to exist. Annualreports are time-consuming and costly to produce, and man-agement must rationalise the competing demands for space.As a result space must be allocated on the basis of some per-ception of the importance of information to report users.
10 The standard tests for skewness and kurtosis revealed thatshare concentration, listing age and firm size were not nor-mally distributed. Appropriate transformations were conduct-ed to ensure data normality. Listing age and firm size weretransformed using logarithmic transformation, whereas squareroot transformation was more effective for share concentra-tion.
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Table 2 presents the correlation and partial cor-relation matrices (controlling for log of sales, aproxy for size).11
It can be seen from both panel A and B of Table 2that all variables showed significance for at leastone intellectual capital disclosure measure. Table 2,Panel A reveals that, with the exception of log offirm size, independent variable associations are allbelow 0.30. The VIFs for each independent vari-able (shown in Table 6) are all less than 2, sug-gesting that multicollinearity is not a problem.12
Panel B of Table 2 reveals no multicollinearityamong explanatory variables after controlling forsize. It can also be seen from Panel B of Table 2that board composition (INED) shows significantassociation with all measures of intellectual capitaldisclosure. Size of audit committee (SAC), fre-
quency of audit committee meetings (MAC), andshare concentration (SqSCON), show highly sig-nificant (1% and 5% levels) association with ICDIand log of ICWC, but not with ICWC%. Return onassets (ROA) and log of listing age (LnAGE) showsignificant correlation with ICDI and ICWC% re-spectively, at the 5% level.
144 ACCOUNTING AND BUSINESS RESEARCH
Table 1Measurement of dependent and independent variables
Variable Proxy Measurement
Dependent variables
1 ICDI Variety of intellectual Number of items in the research instrument capital disclosure disclosed in the annual report divided by 183
2 ICWC Volume of intellectual Total number of words disclosed in relation to capital disclosure intellectual capital information in the annual report
3 ICWC% Focus of intellectual Intellectual capital disclosure word count divided capital disclosure by total word count of the annual report
Independent variables
Corporate governance factors
1 Board Independent non-executive Number of independent non-executive directors composition directors (INED) on board (specified in the annual reports) divided
by total number of directors on board
2 Ownership Share concentration (SCON) Cumulative shareholdings by individuals or structure organisations classified as substantial shareholders
(currently a 3% stake required by the Companies Act 1985), with exception of significant directors’shareholding, to the total number of outstanding common shares
3 Internal auditing Size of audit committee Number of directors on board in audit committeemechanism (SAC)
4 Internal auditing Frequency of audit Number of audit committee meetings held within mechanism committee meetings (MAC) the financial year of the annual report
5 Role duality Combined role of chairman Dummy variable with a value of 1 if the roles of and CEO (RDUAL) chairman and CEO are held by the same person
Control variables
6 Length of listing Listing age (AGE) Number of days listed scaled by 365 days a yearon LSE
7 Performance: Return on assets (ROA) Return/total assets for the financial year of the profitability annual report
8 Firm size Sales (SA) Sales revenue of financial year
11 Due to the significant effect of size on disclosure, the par-tial correlation (controlling for size) was considered to bemore appropriate for identifying the marginal effects of otherfactors that were significantly correlated to level of intellectu-al capital disclosure.
12 Previous authors suggest multicollinearity becomes a se-rious problem where correlations exceed 0.8 or VIFs exceed10 (Haniffa and Cooke, 2005). Further, the condition indexes,using eigenvalues of the independent variables correlation ma-trix, were also acceptable with all being below 20.
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Vol. 38 No. 2. 2008 145
Tabl
e 2
Cor
rela
tion
and
part
ial c
orre
latio
n (c
ontr
ollin
g fo
rsiz
e ef
fect
– sa
les a
s a p
roxy
) mat
rice
s
Pane
l AC
orre
latio
n be
twee
n de
pend
ent a
nd in
depe
nden
t var
iabl
es
ICD
ILn
ICW
CIC
WC
%IN
EDSA
CM
ACSq
SCO
NLn
AGE
ROA
LnSA
ICD
I1.
000
LnIC
WC
0.85
6***
1.00
0
ICW
C%
0.50
0***
0.56
5***
1.00
0
INED
0.34
0***
0.41
1***
0.24
**1.
000
SAC
0.51
1***
0.58
5***
0.17
5*0.
234*
*1.
000
MA
C0.
498*
**0.
528*
**0.
151
0.18
5*0.
283*
**1.
000
SqSC
ON
–0.4
42**
*–0
.443
***
–0.2
2**
–0.1
73*
–0.1
67*
–0.1
79*
1.00
0
LnA
GE
0.11
90.
163
–0.1
640.
121
0.26
5***
0.13
7–0
.118
1.00
0
RO
A0.
205*
*0.
146
0.10
1–0
.023
0.08
90.
071
–0.1
340.
216*
*1.
000
LnSA
0.70
4***
0.69
3***
0.10
40.
206*
*0.
485*
**0.
510*
**–0
.399
***
0.28
7***
0.08
21.
000
Pane
l B P
artia
l cor
rela
tion
betw
een
depe
nden
t and
inde
pend
ent v
aria
bles
con
trol
ling
for
size
effe
ct
ICD
I1.
000
LnIC
WC
0.71
9***
1.
000
ICW
C%
0.60
3***
0.
688*
**
1.00
0IN
ED0.
281*
**
0.38
0***
0.
225*
* 1.
000
SAC
0.27
3***
0.
394*
**
0.14
30.
157
1.00
0M
AC
0.22
8**
0.28
1***
0.
114
0.09
50.
047
1.00
0Sq
SCO
N–0
.248
**
–0.2
53**
–0
.196
* –0
.101
0.03
30.
031
1.00
0Ln
AG
E–0
.122
–0.0
52–0
.204
**0.
066
0.15
–0.0
12–0
.004
1.00
0R
OA
0.20
8**
0.12
30.
093
–0.0
410.
056
0.03
4–0
.111
0.20
1**
1.00
0
***
= si
gnifi
cant
at .
01 le
vel,
** =
sig
nific
ant a
t .05
leve
l, *
= si
gnifi
cant
at .
10 le
vel
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5. Results5.1. Descriptive analysis of intellectual capitaldisclosure
Table 3 presents the results of the descriptiveanalysis of intellectual capital disclosure by eachof the 61 items in the checklist under three cate-gories in various formats. The most frequently dis-closed human capital items in text form arenumber of employees, employee motivation,work-related competence, and other employee fea-tures. Other commonly disclosed human capitalitems include employee relationship, entrepreneur-ial spirit, development and training, work-relatedknowledge, employee age, equality, relation,skills, and commitment. Human capital items leastdisclosed are vocational qualifications, employeeproductivity and flexibility. In all three formats,the most disclosed structural capital items are busi-ness process, technology, R&D, management phi-losophy, overall infrastructure and distributionnetwork. The strategic importance of customer andsupply chain relationships in intellectual capitaldisclosure is evidenced by the most discloseditems being customers, relationship with suppliersand stakeholders, market presence, customer rela-tionships and market leadership, with over 90% ofsampled firms having disclosures of such items.
5.2. Descriptive statisticsDescriptive statistics of each measure of intel-
lectual capital disclosure, at both overall and sub-category levels, and the independent variables forthe sample companies are shown in Table 4.
The mean index (ICDI) is 0.36 with slight varia-tion in the variety of human, structural and rela-tional capital disclosure, and the mean aggregateword count (ICWC) is 10,488 words, accountingfor 26.3% of the overall annual report word count(ICWC%). ICDI ranges from 0.16 to 0.56; ICWCranges from 1,234 to 51,430 words and ICWC%ranges from 8.9% to 42.6%.13
The rankings of means for human, structural andrelational capital disclosure change according tothe disclosure measure employed. Structural capi-tal ranks highest (37%) for the disclosure indexscore, relational capital ranks highest in terms ofword count, while structural capital and relationalcapital are joint highest for focus, each forming9% of the total annual report word count. In allcases, human capital is in third place, although notfar behind the other two. The relational-structural-human ranking for word count (38%, 34% and28% of total intellectual capital respectively) isconsistent with findings from prior intellectualcapital disclosure studies (e.g. Guthrie and Petty,
2000; Bozzolan et al., 2003; Goh and Lim, 2004;Vandemaele et al., 2005), demonstrating systemat-ic differences in the level of reporting on intellec-tual capital elements. If firms focus on thedisclosure of those intellectual capital elementsthat are most value and stakeholder relevant(Vergauwen et al., 2007), relational capital wouldseem to be most important in this regard.
The means of corporate governance variables forsample firms indicate that less than half of theboard in our sample consists of independent non-executive directors (INED). The mean for the cu-mulative significant shareholdings (excludingsignificant directors’ shareholding) is 30%. Themajority (86%) have three or more directors in theaudit committee, suggesting compliance with rec-ommended best practice. In addition, the medianfor the audit committee meeting frequency is fourtimes per year, with 83% of sample companiesmeeting three or more times during the financialyear, in line with the Price Waterhouse (1993) rec-ommendation.
The results for intellectual capital disclosure bythe three formats (text, number, graph/picture) areshown in Table 5. It can be seen that human, struc-tural and relational capitals are disclosed in allthree forms in the sample annual reports. Only forstructural capital in text form do we observe allpossible items disclosed. On average, 43 (70%) ofthe 61 intellectual capital items in the research in-strument have text disclosures. This falls to 29%disclosure in numerical form, and 8% in graph/picture form, although one firm had one-third ofits intellectual capital disclosure in graph/pictureform.
Our results confirm that intellectual capital dis-closures are still mainly in text form, in line withprevious studies (e.g. Guthrie and Petty, 2000;Brennan, 2001). The extensive use of numericalinformation in intellectual capital disclosure iden-tified in the study is encouraging, supporting thefinding of Sujan and Abeysekera (2007).
5.3. Regression resultsTable 6 summarises the multiple regression re-
sults for all three intellectual capital disclosuremeasures.
The first panel reports the multiple regression re-sults for the ICDI model, producing an adjusted R2
of 62%. With the exception of role duality(RDUAL), all corporate governance factors exam-ined are significant: size of audit committee (SAC)at the 1% level, and board composition (INED),frequency of audit committee meetings (MAC)and square root of share concentration (SqSCON)at the 5% level. Firm size (LnSA) is significant atthe 1% level. Results also show positive relation-ship between ROA and ICDI, while log of listingage (LnAGE) is negatively associated, both signif-
146 ACCOUNTING AND BUSINESS RESEARCH
13 Given that previous studies have adopted different re-search instruments, it is not possible to make meaningful com-parison.
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Vol. 38 No. 2. 2008 147
Tabl
e 3
Num
ber
of c
ompa
nies
disc
losin
g ite
ms i
n th
e ch
eckl
ist u
nder
thre
e fo
rmat
s14
Av.
Av.
Av.
Hum
an c
apita
lT
NG
PW
CRe
latio
nal c
apita
lT
NG
PW
CSt
ruct
ural
cap
ital
TN
GP
WC
Num
ber o
f em
ploy
ees
100
999
101
Cus
tom
ers
9982
4896
5In
telle
ctua
l pro
perty
5838
521
5Em
ploy
ee a
ge67
950
19M
arke
t pre
senc
e92
7126
382
Proc
ess
100
7821
605
Empl
oyee
div
ersi
ty44
133
18C
usto
mer
rela
tions
hips
9047
1529
5M
anag
emen
t phi
loso
phy
100
2114
422
Empl
oyee
equ
ality
921
079
Cus
tom
er a
cqui
sitio
n78
426
116
Cor
pora
te c
ultu
re58
12
32Em
ploy
ee re
latio
nshi
p99
456
307
Cus
tom
er re
tent
ion
6525
445
Org
anis
atio
n fle
xibi
lity
400
017
Empl
oyee
edu
catio
n51
00
15C
usto
mer
trai
ning
& e
duca
tion
171
19
Org
anis
atio
n st
ruct
ure
8943
945
5Sk
ills/
know
-how
9214
511
4C
usto
mer
invo
lvem
ent
182
17
Org
anis
atio
n le
arni
ng33
00
26Em
ploy
ee w
ork-
rela
ted
100
530
417
Com
pany
imag
e/re
puta
tion
656
1246
Res
earc
h &
dev
elop
men
t94
6311
382
com
pete
nces
Empl
oyee
wor
k-re
late
d91
240
142
Com
pany
aw
ards
392
1347
Inno
vatio
n71
1515
108
know
ledg
eEm
ploy
ee a
ttitu
des/
beha
viou
r72
1515
63Pu
blic
rela
tion
6963
1116
5Te
chno
logy
98
4621
220
Empl
oyee
com
mitm
ents
8859
011
4D
iffus
ion
& n
etw
orki
ng47
123
47Fi
nanc
ial d
ealin
gs10
080
538
6Em
ploy
ee m
otiv
atio
n10
010
012
605
Bra
nds
6919
1815
3C
usto
mer
sup
port
func
tion
5321
368
Empl
oyee
pro
duct
ivity
175
03
Dis
tribu
tion
chan
nels
50
205
76K
now
ledg
e-ba
sed
6914
065
infr
astru
ctur
eEm
ploy
ee tr
aini
ng
789
145
Rel
atio
nshi
p w
ith s
uppl
iers
9681
211
6Q
ualit
y m
anag
emen
t &82
137
87im
prov
emen
tVo
catio
nal q
ualif
icat
ions
102
03
Bus
ines
s co
llabo
ratio
n78
4914
212
Acc
redi
tatio
n (c
ertif
icat
e)
517
457
Empl
oyee
dev
elop
men
t95
244
404
Bus
ines
s ag
reem
ents
5934
519
8O
vera
ll in
fras
truct
ure/
capa
bilit
y97
6213
272
Empl
oyee
flex
ibili
ty24
90
8Fa
vour
ite c
ontra
ct64
4517
237
Net
wor
king
634
023
Entre
pren
euria
l spi
rit96
81
125
Res
earc
h co
llabo
ratio
n22
60
26D
istri
butio
n ne
twor
k65
3612
111
Empl
oyee
cap
abili
ties
742
131
Mar
ketin
g50
219
73Em
ploy
ee te
amw
ork
513
922
Rel
atio
nshi
p w
ith s
take
hold
ers
9442
2362
3Em
ploy
ee in
volv
emen
t46
193
34M
arke
t lea
ders
hip
9135
815
4w
ith c
omm
unity
Oth
er e
mpl
oyee
feat
ures
10
02
8527
614
T, N
, and
GP
repr
esen
ts th
e nu
mbe
r of f
irms p
rovi
ding
dis
clos
ure
in te
xt, n
umbe
rs a
nd g
raph
s/pi
ctur
es re
spec
tivel
y; a
nd A
v. W
C re
pres
ents
the
aver
age
num
ber o
f wor
ds d
iscl
osed
by
the
sam
ple
firm
s.
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148 ACCOUNTING AND BUSINESS RESEARCHTa
ble
4D
escr
iptiv
e st
atist
ics f
orde
pend
ent a
nd in
depe
nden
t var
iabl
es (u
ntra
nsfo
rmed
)
z-te
st
z-te
st
K–S
M
ean
Med
ian
Min
Max
SDSk
ewne
ssK
urto
sis
Lilli
efor
s15
Dep
ende
nt v
aria
bles
ICD
I0.
360.
360.
160.
560.
080.
90–0
.99
0.08
ICW
C10
488
8551
1234
5143
089
01.2
9.46
12.8
70.
19*
ICW
C%
0.26
30.
259
0.08
90.
426
0.07
20.
79–1
.06
0.05
HIC
DI
0.35
50.
348
0.21
20.
561
0.07
31.
50–0
.31
0.07
SIC
DI
0.37
10.
370
0.13
00.
574
0.09
20.
07–0
.89
0.07
RIC
DI
0.36
50.
349
0.11
10.
667
0.12
20.
79–1
.14
0.08
HIC
WC
2945
2558
545
8507
1598
.23.
430.
980.
12*
SIC
WC
3551
2526
466
2364
834
67.6
13.3
228
.83
0.19
*R
ICW
C39
9226
8922
329
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4634
.611
.99
23.2
70.
24*
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WC
%0.
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0.08
00.
033
0.17
40.
026
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0.61
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0.08
40.
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0.28
10.
039
7.27
11.3
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12*
RIC
WC
%0.
090
0.08
30.
020
0.26
60.
047
3.42
2.03
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Inde
pend
ent v
aria
bles
Cor
pora
te g
over
nanc
e fa
ctor
sB
oard
com
posi
tion
(%) (
INED
)0.
470.
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180.
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13–0
.11
–0.9
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09O
wne
rshi
p co
ncen
tratio
n (%
) (SC
ON
)29
.63
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19–1
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udit
com
mitt
ee s
ize
(num
ber)
(SA
C)
3.46
31
71.
06–
––
Aud
it co
mm
ittee
mee
ting
(num
ber)
(MA
C)
3.70
41
91.
41–
––
Rol
e du
ality
(RD
UA
L)0.
090
01
0.29
––
–
Firm
-spe
cific
fact
orLi
stin
g ag
e (A
GE)
(yea
rs)
17.1
510
.69
0.45
71.8
716
.71
5.99
2.58
0.19
*Pr
ofita
bilit
y (R
OA
) (%
)4.
383.
66–9
.53
18.6
75.
790.
030.
540.
09Fi
rm s
ize
(SA
) £m
4036
.738
3.1
0.00
1739
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287
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Vol. 38 No. 2. 2008 149
Table 5Descriptive statistics for intellectual capital disclosure by category under three formats
Intellectual capital Max categories Format Min Max possible Mean % SD
Human capital Text 9 20 22 15.87 72 2.44Numbers 3 12 22 6 27 2.11Graphs/pictures 0 8 22 1.54 7 1.33All 14 37 66 23.41 35 4.82
Structural capital Text 5 18 18 13.21 73 2.49Numbers 1 12 18 5.42 30 2.30Graphs/pictures 0 6 18 1.42 8 1.49All 7 31 54 20.05 37 4.99
Relational capital Text 3 20 21 13.52 64 3.33Numbers 1 15 21 7.05 34 3.35Graphs/pictures 0 10 21 2.41 11 2.43All 7 42 63 22.98 36 7.67
Intellectual capital Text 19 57 61 42.6 70 7.07Numbers 7 38 61 17.44 29 6.95Graphs/pictures 0 20 61 4.91 8 5.00All 29 103 183 66.44 36 15.52
icant at the 5% level.The second panel reveals that the log of ICWC
(LnICWC) regression model, with an adjusted R2
of 67%, yields even stronger associations than theICDI model. Results show highly significant (1%level) relationships between LnICWC and four ofthe five corporate governance factors examined,i.e. INED, SAC, MAC and SqSCON. However,unlike the ICDI model, ROA and LnAGE are notsignificant. LnSA is still significant at the 1%level.
The explanatory power of the ICWC% model isweaker (adjusted R2 of 11.2%), as shown in thethird panel. INED and LnAGE show significantassociations at the 5% level, with SqSCON show-ing a weak relationship (10% level). All other cor-porate governance factors are insignificant, but inthe direction predicted. Neither LnSA nor ROA isrelated to ICWC%.
Table 7 presents a summary of multiple regres-sion results for each of the three intellectual capi-tal subcategories based on the word count metric:LnHICWC (log of human capital word count);LnSICWC (log of structural capital word count);and LnRICWC (log of relational capital wordcount).18
We observe that the two audit committee vari-ables (SAC and MAC) are significantly associatedwith all three intellectual capital subcategories,confirming our hypothesis of the role these com-mittees play in influencing the level of intellectual
capital disclosure in its various forms. In addition,relational capital disclosures are significantly as-sociated with INED and SqSCON; structural capi-tal disclosures are significantly associated withINED, while human capital disclosures are associ-ated with RDUAL, all in the direction hypothe-sised.
5.4. Examination of hypothesesTable 8 summarises the associations between the
independent variables and intellectual capital dis-closure measures, namely, variety (ICDI), volume(ICWC) and focus (ICWC%).
Board composition was expected to be one ofthe major corporate governance determinants forintellectual capital disclosure. The significant pos-itive results of all three measures of intellectualcapital disclosure, especially for variety (5% level)and volume (1% level), support our hypothesis(H1) that the greater the presence of independentnon-executive directors on the board, the greaterthe intellectual capital disclosure. Detailed analy-sis at item level (not included) reveals that firmswith more independent non-executive directorsdisclose significantly more human capital items(e.g. employee relations and work-related compe-tence, but not diversity or equality), structural cap-ital items (e.g. management philosophy, corporateculture, innovation, knowledge-based infrastruc-ture, and quality management and improvement),and relational capital items (e.g. market presence,relationships with suppliers, business agreements,and marketing issues). They offer support to argu-ments based on both agency and resource depend-ence theories.
18 The ICDI models for each of the three intellectual capitalsubcategories reveals broadly similar associations and are nottherefore presented.
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150 ACCOUNTING AND BUSINESS RESEARCHTa
ble
6M
ultip
le r
egre
ssio
n re
sults
for
ICD
I, Ln
ICW
C a
nd IC
WC
%
ICD
ILn
ICW
CIC
WC
%
Uns
tand
ardi
sed
Stan
dard
ised
U
nsta
ndar
dise
d St
anda
rdis
ed
Uns
tand
ardi
sed
Stan
dard
ised
co
effic
ient
sco
effic
ient
sco
effic
ient
sco
effic
ient
sco
effic
ient
sco
effic
ient
s
Std.
Std.
Std.
VIF
Ber
ror
Beta
tSi
g.B
erro
rBe
tat
Sig.
Ber
ror
Beta
tSi
g.
(Con
stan
t)0.
181
0.03
45.
402
0.00
07.
155
0.27
526
.053
0.00
00.
234
0.04
55.
254
0.00
0
SAC
1.38
10.
016
0.00
60.
205
2.80
50.
006
0.20
00.
047
0.29
14.
275
0.00
00.
011
0.00
80.
162
1.46
00.
148
MA
C1.
374
0.00
90.
004
0.15
62.
142
0.03
50.
101
0.03
50.
195
2.88
30.
005
0.00
50.
006
0.09
80.
882
0.38
0
INED
1.10
40.
106
0.04
30.
160
2.45
60.
016
1.22
50.
354
0.21
13.
465
0.00
10.
115
0.05
70.
200
2.01
00.
047
SqSC
ON
1.24
2–0
.007
0.00
3–0
.162
–2.3
430.
021
–0.0
630.
024
–0.1
70–2
.633
0.01
0–0
.007
0.00
4–0
.180
–1.7
020.
092
RD
UA
L1.
084
–0.0
130.
019
–0.0
45–0
.702
0.48
4–0
.229
0.15
2–0
.090
–1.5
010.
137
–0.0
100.
025
–0.0
40–0
.407
0.68
5
LnA
GE
1.18
3–0
.012
0.00
5–0
.155
–2.2
950.
024
–0.0
640.
041
–0.0
98–1
.552
0.12
4–0
.017
0.00
7–0
.268
–2.6
020.
011
RO
A1.
084
0.00
20.
001
0.14
92.
309
0.02
30.
009
0.00
80.
071
1.17
10.
245
0.00
20.
001
0.11
91.
212
0.22
9
LnSA
1.91
60.
015
0.00
30.
451
5.24
50.
000
0.10
50.
024
0.34
74.
340
0.00
0–0
.002
0.00
4–0
.077
–0.5
900.
556
R2
0.64
90.
696
0.18
4
Adj
. R2
0.61
80.
669
0.11
2
Std.
err
or0.
051
0.41
80.
068
F va
lue
21.0
3326
.005
2.56
8
Sig.
F0.
000
0.00
00.
014
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Role duality was not found to influence intellec-tual capital disclosure and our hypothesis (H2) wasrejected. Share ownership concentration showedsignificant negative associations with all threemeasures of intellectual capital disclosure as hy-pothesised, especially by variety (5% level) andvolume (1% level). The finding supports our hy-pothesis (H3) that companies with more concen-trated share ownership are less responsive toinvestors’ information costs, since the dominantshareholders typically have regular access to the
information they require and hence there is lesspressure for intellectual capital disclosure in annu-al reports. Analysis at intellectual capital subcate-gory level reveals that the impact of blockshareholders is mainly on the volume of relationalcapital disclosure (e.g. customers, market presenceand leadership, customer relationship and acquisi-tion, company awards, public relation, distributionchannel, relationship with suppliers and stakehold-ers, business collaboration and marketing).
Audit committee size was found to be positively
Vol. 38 No. 2. 2008 151
Table 7Multiple regression results for human, structural and relational capital disclosure based on word count
LnHICWC LnSICWC LnRICWC
VIF t Sig. t Sig. t Sig.
(Constant) 28.717 0.000 16.177 0.000 14.041 0.000
SAC 1.381 5.121 0.000 2.924 0.004 3.437 0.001
MAC 1.374 2.497 0.014 2.482 0.015 2.326 0.022
INED 1.104 1.538 0.128 3.239 0.002 2.785 0.007
SqSCON 1.242 –1.299 0.197 –1.647 0.103 –3.272 0.002
RDUAL 1.084 –2.030 0.045 –0.787 0.433 –1.067 0.289
LnAGE 1.183 –2.111 0.038 –0.116 0.908 –2.045 0.044
ROA 1.084 0.502 0.617 0.939 0.350 1.532 0.129
LnSA 1.916 5.040 0.000 2.449 0.016 3.728 0.000
R2 0.685 0.536 0.633
Adj. R2 0.657 0.495 0.601
Std. error 0.339 0.554 0.631
F value 24.733 13.153 19.625
Sig. F 0.000 0.000 0.000
Table 8Summary of multiple regression results
Hypothesis support
Predicted Actual ICDI LnICWC ICWC % Hypotheses sign sign (variety) (volume) (focus)
Board composition (H1) + + Moderate Strong ModerateRole duality (H2) – – None None NoneShare concentration (H3) – – Moderate Strong WeakAudit committee size (H4) + + Strong Strong NoneFrequency of auditcommittee meetings (H5) + + Moderate Strong NoneListing age – – Moderate None ModerateROA + + Moderate None NoneSales + + Strong Strong None
Strong = significant at .01 level, Moderate = significant at .05 level, Weak = significant at .10 level
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associated with ICDI and LnICWC, supportingour hypothesis (H4) that companies with largeraudit committees tend to provide greater intellec-tual capital disclosure in their annual reports. Thisis in line with the recommendations of the SmithReport (2003) that audit committees have respon-sibility to oversee documents such as the operatingand financial review. This document typically hasa strong intellectual capital disclosure emphasis.Results support hypothesis (H5) that a positive re-lationship exists between level of intellectual cap-ital disclosure and frequency of audit committeemeetings. This suggests that audit committee activity is an important factor in monitoring man-agement behaviour with regard to reducing infor-mation asymmetry through intellectual capitaldisclosure.
6. Summary and conclusionsResults based on multiple regression models forthe three intellectual capital disclosure measuresindicate that, with the exception of role duality, allcorporate governance variables together with firmsize, profitability and listing age are associatedwith one or more of the intellectual capital disclo-sure measures. This is consistent with Keenan andAggestam’s (2001) argument, previously untested,that corporate governance impacts on efficient intellectual capital management, including itscommunication to stakeholders. The significantpositive association for board composition pro-vides evidence for independent directors’ functionas a monitoring mechanism, which enhances theeffectiveness of the board and reduces both agencycosts and information asymmetries between prin-cipals and agents. Moreover, their breadth of ex-pertise and knowledge heighten the board’sawareness of the importance of intellectual capitaldisclosure, especially structural and relational cap-ital. We also find confirmation of our share con-centration, audit committee size and frequency ofaudit committee meetings hypotheses, under-
pinned by agency theory arguments. Where shareownership is highly concentrated, smaller share-holders’ interests in relation to intellectual capitalneed to be protected via corporate governancemechanisms, such as greater independence of theboard and larger, more active audit committees forbetter intellectual capital communication.
We argue that, as well as the variety and volumeof disclosure, it is meaningful to measure eachfirm’s disclosure focus (ICWC%) to examine theproportion of annual reports devoted to intellectu-al capital. On average, 26% of annual report dis-closures were devoted to intellectual capital; thisfocus is not size dependent and is greater wherefirms have a higher proportion of independentnon-executive directors and shareholdings aremore widely spread.
Our findings indicate that, in the absence ofmandatory disclosure, effective corporate gover-nance mechanisms impact positively on the vari-ety, volume (word count) and format (text,numbers, graphs/pictures) of intellectual capitaldisclosure. Future research could usefully explorethe relationships identified in the study in greaterdepth through organisational case studies.
There are several limitations in this study. First,the disclosure scoring sheet is self-developed,which causes difficulty for comparison with priorstudies. Second, the study focuses only on corpo-rate annual reports and future studies may consid-er other media. Third, there will be other factorsthat affect companies’ intellectual capital disclo-sure practices that have not been examined in thisstudy.19 Finally, the study has not attempted to in-clude corporate culture. For example, companiesthat choose to have good disclosure policies mayalso choose to operate good corporate governancepractices.
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AppendixDefinition and nature of information
Human capital
1 Number of employees Employee count of a firm, employee breakdown by, e.g. market (business operation or geographical segments), department and job function, and information about its changes and reasons for such changes.
2 Employee age Biological age of employees in the firm. Includes qualitative description ofage-related advantages/strengths of a company’s employees, and indicatorssuch as average age of a company’s employees and age distribution.
3 Employee diversity Diversity is defined as the division of classes among a certain population. The item refers to the mix of, e.g. ethnicity, gender, colour, and sexual orientation. Relevant disclosures include employee diversity policy, the mix and breakdown of employee by race, religion, and culture.
4 Employee equality Equal treatment of people irrespective of social and cultural differences.Related disclosures include employee equality policy and initiatives taken for enforcement, senior management by gender, and percentage of disabledemployees.
5 Employee relationship The recognition of importance of employees, employee appreciation, dependence on key employees, employee satisfaction, loyalty, Health & Safety and working environment. It also includes initiatives to build andimprove employee relationship, e.g. trade union activities, promotion in shareownership and employee contractual relationships.
6 Employee education Education of directors as well as other employees. Employees’ professionalrecognition is classified under employee work-related competences.
7 Skills/know-how Disclosures can be description of knowledge, know-how, expertise or skills of directors and other employees. Matrices could also be shown indicatingnumber of employees with such skills, etc.
8 Employee work-related The knowledge and skills that can be useful to accomplish jobs. It refers to, competences e.g. current positions held outside the company by directors, professional
recognition/qualification, awards won (external), and employee publications.
9 Employee work-related What is acquired during the job in terms of tacit, explicit and implicit knowledge knowledge. It mainly relates to knowledge that employees have related
to their current job description, including employees’ previous working experiences.
10 Employee attitudes/ It reflects how employees are working. Relevant disclosures could be, e.g. behaviour employee friendliness, welcoming, hard working, optimism, enthusiasm, and
identification of individuals with company’s goals.
11 Employee commitments It refers to employees being bound emotionally/intellectually to the organisation. It covers, e.g. description of employee commitments, employeecommitment matrix/index, and indicators such as attendance of meetings.
12 Employee motivation Policies, initiatives and evidence of motivation of directors and other employees. It includes reward (internal) and incentives systems, e.g. employee explicit recognition, performance/psychometric/occupational assessment, and indicators of such as employee turnover,20 stability, absence,and seniority.
13 Employee productivity21 It is typically measured as output per employee or output per labour-hour, anoutput which could be measured in physical terms or in price terms. It showsthe value added and efficiency of employees. Indicators include, e.g. employeevalue added, revenue or customers per employee.
20 Information about directors’ retirement is not included as employee turnover.21 Directors’ achievements based on incentive schemes are classified as employee motivation information rather than em-ployee productivity. It is considered more appropriate to reflect on the motivational effectiveness of incentive schemes.
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AppendixDefinition and nature of information (continued)
14 Employee training It includes, e.g. training policies, training programmes, training time, attendance, investment in training, number of employees trained per period,and training results/effectiveness/efficiency.
15 Vocational qualifications It refers to education, managed and monitored by trade and professional organisations (Brooking, 1996), received by an employee for a particular vocation that proves the skill, knowledge and understanding he/she has to do a job well.
16 Employee development22 Employee career development. Disclosures include employee developmentpolicies and programmes (e.g. succession planning), recruitment policies (e.g. internal promotion). Indicators include change of employee seniority,and rate of internal promotion.
17 Employee flexibility Strategies used by employers to adapt the work of employees to their production/business cycles; and a method to enable workers to adjust workinglife and working hours to their own preferences. For example,temporary/fixed-term contracts, relaxed hiring and firing regulations, adjustable working hours or schedules (e.g. part-time, flexible workinghours/shifts, working time accounts, leave, and overtime), outsourcing, job rotation, tele/home-workers, outworkers.
18 Entrepreneurial spirit It refers to, e.g. employee engagement (e.g. employee suggestion systems/consultations, rate of employee suggestions acceptance), empowerment (responsibility taking), creativity (e.g. valuing creativity, tolerance of creativepeople), innovativeness, knowledge sharing, and employee proactive/reactiveability.
19 Employee capabilities Other employee abilities apart from the above discussed, e.g. communicationability, interpersonal ability, sensitivity (e.g. thoughtful), reflexibility, andmanagement quality.
20 Employee teamwork Teamwork is the concept of people working together cooperatively. It coversinformation about culture of teamwork (expert teams and networks, teamworkcapacity), programmes that enhance relationships between employees within/across departments.
21 Employee involvement Employee social competence can be reflected by their involvement with with community community. It is defined as providing employees opportunities for contact
with an often concealed but significant part of the firm’s stakeholders.
22 Other employee features It refers to the special display or attraction of, or gives special prominence to,employees of the firm, e.g. photographs of employees, other employee profileinformation (e.g. positions held).
Structural capital
1 Intellectual property It is a term that encompasses patents, copyrights, trademarks, trade secrets, licenses, commercial rights and other related fields. It covers the assets of acompany which is protected by law.
2 Process It normally refers to a company’s management (sales tools, company co-operation forms, corporate specialisation, operational or administrativeprocesses). It includes utilisation of organisation resources, processes/ procedures / routines, and documentations which enables the company or employees to follow. Indicators are, e.g. efficiency, effectiveness, and productivity.
3 Management philosophy ‘The way leaders in the firm think about the firm and its employees’(Brooking, 1996: 62), i.e. the way a firm’s managed.
22 Not formal qualifications as degrees.
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AppendixDefinition and nature of information (continued)
4 Corporate culture The set of key values, beliefs, attitudes and understanding shared by peopleand groups in an organisation, which controls the way members of the organisation interact with each other and with other stakeholders. It covers information about, e.g. description of the firm’s corporate culture and value,stories and myths that build up about people, events and history conveying amessage about what is valued within a firm.
5 Organisation flexibility A company’s ability to face challenges and changes, such as specific processes firms use to alter their resource base.
6 Organisation structure Reporting lines, hierarchies, and the way that work flows through the business, including management structure and business models.
7 Organisation learning A characteristic of an adaptive organisation. It covers what firms learn fromexperience and incorporate the learning as feedback into their planningprocess.
8 Research & It refers to future-oriented, longer-term activities in business practice, which development (R&D) can achieve higher levels of knowledge and improvement in business
practice, allowing the organisation to exploit competitive advantages. It includes, e.g. R&D policies, programmes, planning, progress, budgets, successful rate, rate of peer-reviewed publications.
9 Innovation Defined as the successful implementation of creative ideas within a firm byintroducing something new and useful (radical or incremental changes toproducts, processes or services).
10 Technology A collection of techniques, which is the current state of humanity’s knowledge of how to combine resources to produce desired products, to solve problems, fulfil needs, or satisfy wants. It includes machines, IT (e.g. computer hardware and software), IS (e.g. SAP, PeopleSoft, database), technical methods, and techniques.
11 Financial dealings Defined as the favourable relationships the firm has with investors, banks andother financiers, financial ratings, financial facilities available, and listings.
12 Customer support Functions for customer support, such as customer support centres (e.g. call function centres) and other related activities and programmes.
13 Knowledge-based It includes, e.g. documented materials (e.g. shared database) that a firm shares infrastructure amongst employees, facilities or centres (knowledge centres, laboratories) for
training & learning, and knowledge management and sharing programmes/policies/facilities.
14 Quality management Practices in maintaining and improving quality standards of products and & improvement services. Information considered relevant includes, e.g. policies and
objectives, programmes, control activities (e.g. TQM), description of quality performance, and existence of quality committee.
15 Accreditations A process in which certification of competency, authority, or credibility is (certificate) presented. It has been broadly referred to as quality certificates. ‘Investor in
people’ accreditation represents a firm’s commitment to its employees; henceclassified under employee relationship.
16 Overall infrastructure/ Infrastructure/capabilities of a firm that cannot be classified under the other capability 17 structural capital items. Where acquisitions are stated to add a firm’s
capability of products and services provision, such information is includedunder this item.
17 Networking The systems available in a firm that allows interaction of people via a broadarray of communication media and devices, e.g. voicemail, e-mail, voice orvideo conferencing, the internet, groupware and corporate intranets, personaldigital assistants, and newsletters.
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AppendixDefinition and nature of information (continued)
18 Distribution network Internal networks of distribution, such as distribution centres. It is what acompany owns and forms a very essential part of the business supply chain.
Relational capital
1 Customers General customer information, e.g. type of customers, customer names, reputation of customers, customer base, knowledge of markets/customers, andcustomer purchasing histories.
2 Market presence It covers target markets of a firm, geographically or by market segmentation,percentage of sales represented by each market segment, and market share.
3 Customer relationships It includes policies and programmes for building customer relationships (e.g.customer loyalty schemes, customer satisfaction survey and the initiativestaken for improvement, complaints management), current relationships withcustomers (e.g. customer satisfaction and loyalty, customer recommendation,recognition of dependence on key customers, customer perception (e.g. expressed by direct quotes), and various activities/indicators that enhance customer relationships, such as on-time deliveries, convenience of returninggoods, value for money).
4 Customer acquisition It refers to a company’s new customers/contracts (unless identified asfavourite contracts). It also includes a company’s effort on acquiring new ormore customers, such as investments/costs.
5 Customer retention It focuses on retaining the existing customers. Relevant information includese.g. the number of repeated customers/contracts, renewed contracts, backlogorders, and customer repurchase.
6 CTE Customer training & education (CTE), such as presentation, road shows, exhibitions, etc.
7 Customer involvement It focuses on customer consultation on product or services development,which could also include customer and company connectivity.
8 Company image/ It refers to the evaluation/perception of a firm by its stakeholders in terms of reputation their effect, esteem, and knowledge, and what a company stand for.
9 Company awards It includes awards to a company which is not specifically to other aspects,such as innovation or employees.
10 Public relation It is the managing of outside communication of an organisation to create and maintain a positive image. Public relations involve, e.g. popularising successes and downplaying failures.
11 Diffusion & networking It includes taking part in social events, courses, conferences, lectures, or otherpresentations or seminars.
12 Brands23 Information about, e.g. brand names, brand images, brand awareness, brandloyalty (e.g. word of mouth advocacy), brand-building strategies and activities, and brand-related sales.
13 Distribution channels Defined as appropriate mechanisms of getting products and services into themarket (Brooking, 1996). It refers to various third party distribution channels,e.g. distributors, agents, dealers.
14 Relationship with It includes, e.g. knowledge of suppliers, relationships with them (such as suppliers reliance on key suppliers, bargaining power against suppliers, support of
suppliers, and payment terms).
23 Brands have been classified under relational capital in various studies (e.g. Bozzolan et al., 2003; Brennan, 2001;Guthrie and Petty, 2000). Although authors such as Rodgers (2003) consider brands as a structural capital item, it is con-sidered in this study that brands themselves are not able to create value for firms and it is the attachment of the market andcustomers, and the positive perception consumers have relating to the brand that lead to purchase decisions and add valueto the firm.
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AppendixDefinition and nature of information (continued)
15 Business collaboration Collaborations established with other business partners. It covers issues suchas strategic alliances, joint venture and partnership for the purpose of workingtogether to improve effectiveness and efficiency by combining each other’sadvantages.
16 Business agreements It includes such as licensing and franchising agreements. However, the transactions are not within a consolidated group of companies.
17 Favourite contract A contract obtained because of the unique market position held by the firm(Brooking, 1996). It includes description of the contract and the favourablerelationships.
18 Research collaboration Collaborations with scientific associations or institutions (e.g. schools anduniversities) for research or development purposes for the benefit of the company or the community.
19 Marketing It includes, e.g. marketing initiatives, investments, strategies, capabilities, andeffects (e.g. awareness raised or sales created).
20 Relationship with A firm’s relationship with stakeholders, which cannot be covered by stakeholders relationship with customers, suppliers and shareholders, e.g. community,
government, and competitors.
21 Market leadership A firm’s leadership in various markets or top positions. Market share supplementing market leadership statement is also included.
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