Internet Reporting Determinants-NZ

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Abstract

The development of the Internet as a global medium for the dissemination of corporatefinancial information creates a new reporting environment. Extensive literature examinesthe determinants of voluntary financial reporting through traditional media such as print-based annual reports. This paper extends this literature by examining the voluntary adop-tion of the Internet as a medium for transmitting financial reports and determinants of

such voluntary practice by New Zealand companies. The results indicate that some deter-minants of traditional financial reporting—firm size, liquidity, industrial sector and spread of shareholding—are determinants of voluntary adoption of Internet financial reporting (IFR).However, other firm characteristics, such as leverage, profitability and internationalizationdo not explain the choice to use the Internet as a medium for corporate financial reporting.

1. Introduction

Internet financial reporting (IFR) is a recent but fast-growing phenomenon.

Many companies worldwide publish their corporate financial informationon the Internet. Financial information provided on the web includes com-prehensive sets of financial statements, including footnotes; partial setsof financial statements; and/or financial highlights that may include sum-mary financial statements or extracts from such statements. Recent studiesdocument the practice of such reporting among companies in a number of countries.1 This practice is expected to grow to the extent that financialreporting in the near future will move entirely from the current primarily

print-based mode to using the Internet as the primary information dis-semination channel (Lymer et al., 1999; Bagshaw, 2000). The growth of

The authors would like to acknowledge the helpful comments of two anonymous reviewers on earlierdrafts of the paper.

© Blackwell Publishing Ltd. 2003, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

Determinants of Internet Financial Reportingby New Zealand Companies

Peter Oyelere

Sultan Qaboos University, PO Box 20, Al Khod PC 123, Oman

email: [email protected]

Fawzi Laswad

Massey University, New Zealand

Richard Fisher

Lincoln University, New Zealand

Journal of International Financial Management and Accounting 14:1 2003



IFR in combination with the Internet’s multimedia capability and capacityfor interactive communication may challenge the nature of financialreporting, its boundaries, and framework.

Currently, financial statements on the Internet are unregulated. Theglobal accessibility of financial reports on the Internet and the absence of a global regulator have possible implications for groups with interests infinancial reporting, such as financial information preparers, users, auditorsand regulators. Bagshaw (2000) argues that the global accessibility of cor-porate financial reports and the absence of a global regulator necessitatesthe cooperation of national and international organisations to ensure thatcorporate financial information is of the highest quality.

The need for control over IFR largely depends on the degree to whichefficient solutions are currently being found in the market for financialinformation of this nature. Companies elect to develop and maintaincorporate websites and choose to provide financial information on suchwebsites. Substantial accounting literature has emerged in the last 30 yearsthat explains and predicts corporate financial disclosure behaviour. Thisliterature focuses primarily on voluntary reporting through the traditionalmedium of print-based annual reports. The recent development of the Internetas a medium for the dissemination of corporate financial information createsa corporate reporting environment that may be different from the traditionalprint-based one.

This paper examines the determinants of IFR practices of New Zealandcompanies. The examination of such determinants extends the theories andmodels that have been developed in voluntary reporting through traditionalmedia to the new corporate reporting environment created by the Internet.Further, the paper extends prior IFR studies (such as Ashbaugh et al.,1999) by developing a wider definition of IFR and more comprehensivemodel of the determinants of such practices. In this study, a company isclassified as practising IFR when it provides on the web a comprehensiveset of financial statements and/or financial highlights extracted from financialstatements (including partial and/or summarized financial statements).2

The results of our analysis indicate that, to varying degrees, size, liquidity,industry sector and spread of shareholding are the primary determinantsof IFR practices among New Zealand companies. However, other firmcharacteristics associated with voluntary reporting, such as leverage,profitability and internationalization are not associated with IFR.

The remainder of this paper is organized as follows. The next sectionprovides a review of the literature on determinants of corporate disclosureand literature that describes the IFR environment. Section 3 develops

© Blackwell Publishing Ltd. 2003.

Internet Financial Reporting in NZ 27



and states the research hypotheses. This is followed by a description of the research design, including sample and data collection. Data analysisand results are then presented and discussed. Summary and conclusions,

including possible limitations and areas for future research are presentedin the final section.

2. Literature Review

IFR may be viewed as a component of company voluntary disclosurepractices (Ashbaugh et al., 1999). This section overviews the considerableliterature that has emerged in the last 30 years, which examines voluntary

corporate financial reporting. The study reported in this paper draws onthis stream of research to extend the theories and models implicit in thisliterature to the new corporate reporting environment created by theInternet. This section also provides a review of the emerging literature thatexamines practices and issues relating to the recent development of theInternet as a medium for dissemination of corporate financial information.The review highlights specific benefits and costs which distinguish IFRfrom other voluntary disclosure practices.

2.1 Corporate Financial Reporting

The examination of the determinants of disclosure in print-based corporateannual reports represents one of the most systematic and sustained researchefforts in the financial reporting literature. Cerf’s (1961) inaugural empiricalstudy of factors influencing the adequacy of US corporate annual reportdisclosure laid the foundation for a succession of studies conducted in

numerous countries.3

Variables hypothesized to influence disclosure levelsin these studies include a variety of firm specific characteristics, such assize, profitability, listing status, and leverage.

The examination of the determinants of voluntary disclosure is motivatedby various research objectives, including the possibility of inadequate disclos-ure and the need for regulating such disclosure. Inadequate disclosure mayaffect users’ economic decisions and efficiency of capital markets. Alter-natively, systematic differences in disclosure found among firms within and

across industries are used as a basis for the argument that efficient solutionsare being found in the market for financial information (Malone et al., 1993;Wallace and Naser, 1995). Early evidence of market efficiency includesBenston’s (1969) finding that voluntary disclosure was common in the USbefore disclosure regulation imposed by the Securities Exchange Act of 1934.


28 P. Oyelere, F. Laswad and R. Fisher



Table 1. Summary of Determinants of Financial Reporting Disclosure Studies

Dependent No. Variable S

of (disclosure Type of Author(s) Country Firms index) Analysis

Davies & Kelly (1979) Australia 50 Aggregate Univariate Size (Ahmed & Nicholls (1994) Bangladesh 63 Mandatory Mulivariate Audit

ForeiQualiacctg

Ahmed (1996) Bangladesh 118 Aggregate Multivariate AuditForei

Patton & Zelenka (1997) Czech Repub. 50 Mandatory Univariate AuditLeverListinNo. oSize (

Multivariate AuditListinNo. oProfit

Lau (1992) Hong Kong 26 Voluntary Multivariate Lever

Tai et al. (1990) Hong Kong 76 Mandatory Univariate Size (

Wallace & Naser (1995) Hong Kong 80 Aggregate Multivariate Size (Diver



Table 1. Continued

Dependent

No. Variable S


Marston & Robson (1997) India 58 Aggregate Univariate Size (

Singhvi (1968) India 45 Aggregate Univariate OwneProfitSize (Type

Cooke (1991) Japan 48 Voluntary Multivariate IndusListinSize (

Cooke (1992) Japan 35 Aggregate Multivariate IndusListinSize (

Cooke (1993) Japan 48 Aggregate Univariate Listin(LvMHossain et al. (1994) Malaysia 67 Voluntary Univariate Audit

LeverListin



Table 1. Continued

Dependent

No. Variable S


OwneSize (

Multivariate ListinOwneSize (

Chow & Wong-Boren Mexico 52 Voluntary Multivariate Size (

(1987)Fekrat et al. (1996) Multinational 168 Aggregate Univariate Count

IndusCourtis (1979) New Zealand 126 Aggregate Univariate Capit

IndusLeverOwneProfitRepor(PC, P

Size (DIR, Hossain et al. (1995) New Zealand 55 Voluntary Multivariate Lever

ListinSize (



Table 1. Continued



McNally et al. (1982) New Zealand 103 Voluntary Univariate IndusSize (

Inchausti (1997) Spain 138 Aggregate Multivariate AuditListinSize (

Wallace et al. (1994) Spain 50 Mandatory Multivariate LiquiListinSize (

Cooke (1989a) Sweden 90 Aggregate Multivariate IndusListinSize (

Cooke (1989b) Sweden 90 Voluntary Multivariate ListinSize (

Raffournier (1995) Switzerland 161 Voluntary Univariate Asset

AuditIndusInternProfitSize (



Table 1. Continued



AuditInternProfitSize (

Firth (1979) UK 180 Voluntary Univariate Listin

Size (Buzby (1975) USA 88 Aggregate Univariate Size (Malone et al. (1993) USA 125 Aggregate Multivariate Lever

ListinOwne

Singhvi & Desai (1971) USA 155 Aggregate Univariate Audit

ListinOwneProfitSize (



Table 1. Continued

Dependent

No. Variable Sof (disclosure Type of

Author(s) Country Firms index) Analysis

Multivariate ListinProfit

Owusu-Ansah (1998) Zimbabwe 49 Mandatory Multivariate AgeOwne(1-PUProfitSize (

* ANI = Absolute net income; BVD = Book value of debt; BVLTD = Book value of long term debt; CE =DISS = Public issues of long term debt; DP = Dividend pay-out ratio; DR = Dividend rate; EE = Percent eEMP = Number of employees; FACT = Composite variable comprising eight variables; INTG = ProportioML = Multi-listed; PC = Preparation cost; PG = Pages; PUB = Proportion of shares owned by the public;

equity; S = Sales; SH = Number of shareholders; SHF = Shareholders’ funds; SUB = Number of subsidiaTA = Total assets; TOP10 = Proportion of shares owned by top 10 shareholders; U = Unlisted; USH = Pro



there are a number of notable exceptions, e.g., Lau (1992); Malone et al.(1993); Ahmed and Nicholls (1994); and Ahmed (1996).

The association between corporate profitability and disclosure has been

examined by a number of studies. It is argued that disclosure is used bythe managers of profitable firms to signal the firm’s profitability to investors,and to help support management’s continuation and compensation (Singhviand Desai, 1971; Malone et al., 1993). However, Wallace et al. (1994) andLang and Lundholm (1993, pp. 248, 251) caution that disclosure may berelated to variability of a firm’s performance, where performance servesas a proxy for information asymmetries between investors and managers.In general, the empirical findings are conflicting. Studies have found a

positive relationship (Singhvi, 1968; Singhvi and Desai, 1971; Courtis,1979; Owusu-Ansah, 1998), no relationship (McNally et al., 1982; Lau,1992), and a negative relationship (Wallace and Naser, 1995).

Industry has been posited to be associated with disclosure. Wallace andNaser (1995) argue that differential levels of disclosure of similar items infinancial reports published by firms in different industries may arise fromthe adoption of industry-related disclosures. Differences in disclosurelevels between industries could also be attributed to the high level of

voluntary disclosure by a dominant firm within an industry, which leadsto a bandwagon effect (Cooke, 1989a). Empirical studies examining theassociation between industry and disclosure have yielded mixed results.Industry was found to be a determinant of disclosure levels by Courtis(1979), McNally et al. (1982), Cooke (1989a, 1991, 1992), and Fekratet al. (1996); whilst no relationship was found in Tai et al. (1990), Wallaceet al. (1994), and Patton and Zelenka (1997).

Agency theory has largely been used to explain the relationship between

firm leverage and corporate disclosure. It is argued that as leverage increases,there are wealth transfers from fixed claimants to residual claimants. Asdebenture holders are able to “price-protect” themselves, managers andshareholders have an incentive to voluntarily increase the level of monitor-ing, such as by increasing the disclosure of additional information aboutthe firm activities (Myers, 1977; Schipper, 1981). Empirical evidenceregarding the association between leverage and voluntary disclosure isinconclusive. Courtis (1979), Lau (1992), Malone et al. (1993), Hossain

et al. (1994, 1995), Patton and Zelenka (1997) find a positive relationshipbetween leverage and corporate disclosure. Chow and Wong-Boren (1987),Ahmed and Nicholls (1994), Wallace et al. (1994), Raffournier (1995),Wallace and Naser (1995), Ahmed (1996), and Inchausti (1997) find noassociation between the two variables.





Stock exchange listing status (e.g., listed versus unlisted, or listedversus multiple listings) is associated with disclosure (Singhvi and Desai,1971; Firth, 1979; Cooke, 1989a,b, 1991, 1992, 1993; Malone et al., 1993;Hossain et al., 1994, 1995; Wallace et al., 1994; Inchausti, 1997; Pattonand Zelenka, 1997). Cooke (1989a) argues that agency costs increase asshareholders become more remote from management. As unlisted com-panies tend to have a smaller number of shareholders, agency costs areexpected to be lower than those for listed companies. Conversely, due tothe greater separation between owners and managers, listed companies arelikely to incur higher agency costs, such as “monitoring costs”. These costscan be reduced through the voluntary disclosure of additional corporateinformation (Schipper, 1981). Hossain et al. (1995) suggest that bothstock exchange listing status and voluntary corporate disclosure are com-plementary forms of monitoring. Consequently, one would expect to finda positive relationship between the two variables.

A recent meta-analysis by Ahmed and Courtis (1999) attempted to in-tegrate prior voluntary disclosure studies and identify some of the under-lying factors contributing to the variations in the results of these studies.Using 29 voluntary disclosure studies, they found a significant associationbetween disclosure levels and firm size, listing status, and leverage.Further, they argued that prior results were moderated by differences indisclosure index construction, differences in definition of the explanatoryvariables, and differences in research setting.

2.2 Internet Financial Reporting Literature

The literature in relation to financial reporting on the Internet is growing.A number of studies discuss the benefits of IFR, speculate on its future, andidentify issues and concerns in relation to the use of such medium. Somestudies report on surveys of IFR practices in single countries while othersundertake cross-country comparisons. A few studies examine the corporatecharacteristics associated with the choice of Internet corporate financialreporting.

2.2.1 Benefits, issues, future, and professional pronouncements relating

to Internet financial reporting. A number of studies discuss the benefitsof providing financial information on the Internet (e.g., McCafferty, 1995;Louwers et al., 1996; Green and Spaul, 1997; Trites and Sheehy, 1997;Trites, 1999). Cost savings from the reduction of production and distribu-tion associated with print-based annual reports and incidental requests





from non-shareholder financial statement users is one of the main benefitsfrom providing financial reports on the Internet. Internet reportingimproves users’ access to information by providing information that meet

their specific needs, allowing non-sequential access to information throughthe use of hyperlinks, interactive and search facilities, and allowing theopportunity for providing more information than available in annual reports.This improved accessibility of information results in more equitableinformation dissemination among stakeholders.

The advantages of IFR give rise to a number of issues, which includeblurring the line between audited and unaudited information, equity andefficiency of access, introduction of errors, security and integrity of the

information, and other professional issues.Internet reporting blurs the distinction between current financial informa-tion used by management and the historical (and audited) informationmade available to the public (Green and Spaul, 1997; Hodge, 2001). Thisreporting may supersede the historically audited information currentlymade available to shareholders and the company’s broader constituenciesby providing financial information used by management (Laine, 1997).This may place greater demands on auditors to provide opinion on this

data (Trites and Sheehy, 1997).Debreceny and Gray (1999) identify a number of audit and auditorimplications regarding the dissemination of audited financial statementson the Internet. These implications include the association of the auditreport with unaudited information and the responsibilities of auditors tomonitor clients’ websites. Debreceny and Gray argue that if the auditingprofession does not address such issues, the courts and government regu-latory bodies will develop standards to address them.

Access to information on the Internet is currently limited to those withcostly equipment and services, and computer skills. To ensure equity andefficiency, there is a need to make sure that the information provided onthe Internet has been disclosed previously or simultaneously by usingother forms of communication (McCafferty, 1995).

Companies that choose to extract or re-key data from annual reports andmake it accessible through the Internet may introduce errors, which affectthe integrity of the information. Placing a disclaimer concerning the com-

pleteness of the information would alert the users of the information(Hussey and Sowinska, 1999).The security and integrity of corporate information on the Internet may

be compromised intentionally or unintentionally. It is the responsibility of companies to ensure the security and integrity of financial information they





place on the Internet. To overcome such concern, Hussey and Sowinska(1999) suggest that regulators should address the issue of a compulsory filingsystem for financial reporting on a secure and government-controlled server.

There are a number of other professional and technical issues. Providingfinancial information on the Internet may not enhance the understandingof corporate financial information. Generally Accepted Accounting Practice(GAAP) is developed in a traditional reporting environment and may notbe suitable for electronic financial information environment. Users maynot regard Internet reporting as an acceptable substitute for print-basedannual reports. Companies use their websites for many purposes andtherefore financial information may become difficult to locate.

The use of the Internet for the dissemination of corporate informationis a recent phenomenon and some studies speculate on its future. Louwerset al. (1996) note that the future of online financial reporting may involveextending disclosure beyond the reproduction of a print-based annualreport, improving timeliness, expanding scope, and permitting a highdegree of interactive retrieval of information. Timeliness is improved byproviding financial data to the public as soon as possible by disclosingannual report data on the Internet before it is available in hard copy. Thefuture of IFR may include the use of multimedia, such as sound, anima-tion and video to potentially increase the understanding of information.Lymer (1999) suggests that the cost savings and the wide availability of datamade possible by using the Internet are likely to encourage more demand forits use to fulfil statutory, as well as extra-statutory, reporting requirements.

In December 1999, the first professional pronouncement relating to IFRwas released by the Auditing and Assurance Standards Board (AuASB) of the Australian Accounting Research Foundation (AARF) in the form of anAuditing Guidance Statement (AGS 1050) “Audit Issues Relating to theElectronic Presentation of Financial Reports”. AGS 1050 clarifies thatproviding assurance about the effectiveness of the controls and securityover information on the entity’s web site is beyond the scope of the auditof a financial report. The Guidance draws the auditor’s attention to thepractices surrounding the electronic presentation of information on a website as certain characteristics in the presentation of electronic documentsmay increase the risk of inappropriate association of unaudited informa-tion with the audit report. The AGS identifies specific matters that may beaddressed by the auditor with management, to raise awareness of the risksarising and to assess any impact on the audit report to be presented on theentity’s web site. Similar guidance in Bulletin 2001/1: The Electronic

Publication of Auditors’ Reports has recently been issued by the UK





Auditing Practice Board. However, there are no specific audit require-ments/guidance in New Zealand with respect to IFR.

2.2.2 Internet reporting practices. A number of professional studies inthe US, Canada, UK, Ireland and Finland examine corporate financialreporting on the Internet (see, for example, Petravick and Gillett, 1996;Flynn and Galthorpe, 1997; Koreto, 1997; Lymer, 1997; Lymer andTallberg, 1997; Wildstrom, 1997; Brennan and Hourigan, 1998; Marstonand Leow, 1998). These studies report that increasing numbers of com-panies are using the Internet for communicating financial information.However, these studies report little improvement in the provision of such

information where online corporate reports consist mainly of displayinghard copies of annual reports in an electronic format.IFR practices in many countries have been surveyed by a number of

academic studies (UK [Craven and Marston, 1999], Austria and Germany[Pirchegger and Wagenhofer, 1999], International Comparison [Lymeret al., 1999], US and Canada [Trites, 1999], US, UK and Germany [Delleret al., 1999], Sweden [Hedlin, 1999], Spain [Gowthorpe and Amat, 1999],New Zealand [Fisher et al., 2000]). These studies indicate the growing use

of the Internet for corporate dissemination including providing annual re-ports on the Internet and that the extent and sophistication of IFR practicesvaries across countries.

Williams and Ho (1999) compare corporate social disclosure on com-panies’ websites and annual reports in Australia, Singapore, Malaysia andHong Kong. They find that Australian and Singaporean companies providemore corporate social disclosures on websites than in annual reports whilecompanies in Malaysia and Hong Kong are reporting similar information

in the two media.

2.2.3 Characteristics associated with Internet financial reporting. Anumber of studies have examined whether firm characteristics are associatedwith IFR. Craven and Marston (1999) examine the extent of financialinformation disclosure on the Internet by the largest companies in the UKin 1998 and whether such practice is associated with firm size and industrytype. They find that the extent of financial disclosure on the Internet is

positively associated with firm size but not associated with industry type.Ashbaugh et al. (1999) examine the IFR practices of US companies.They find that firms operating websites are larger than firms withoutwebsites. Using univariate analysis, they find profitability, indicators of excellence in reporting practices, and to some extent the percentage of equity





shares held by individual investors are associated with IFR. However, amultivariate logit regression indicates that only firm size is associatedwith IFR. Ashbaugh et al. suggest that future research should develop amore complete model of the determinants of IFR.

Pirchegger and Wagenhofer (1999) examine IFR practices by Austrianand German companies. They find that for Austrian companies IFR isassociated with firm size, measured by sales, and dispersion of its equityownership. However, such results did not extend to German companies.

There has not been an in-depth study of the determinants of IFR. Asdiscussed earlier, many theories or models in the accounting literaturesuch as agency/contracting, signalling and costs/benefits attempt to explaindisclosure choice by identifying the motivations for voluntary reportingpractices. The voluntary and growing use of the Internet as a medium forthe dissemination of financial information provides an opportunity for anin-depth examination of the incentives that motivate such unregulateddissemination of corporate information. An understanding of voluntaryreporting behaviour would be gained by assessing whether the deter-minants associated with traditional dissemination of financial informationthrough print-based annual reports would explain IFR practices.

Several previous studies examining Internet reporting practices, such asAshbaugh et al. (1999) and Pirchegger and Wagenhofer (1999), have reliedon search engines alone in identifying study samples or populations. Thissample selection method may under-identify entities providing Internetfinancial information and may introduce sample selection bias. This studyuses a more comprehensive approach in identifying entities engaging in IFR.

3. Hypotheses Development and Statement

IFR is unregulated, and as such, firm disclosure is likely to reflect thetrade-off between the relevant perceived costs and benefits of supplement-ing traditional financial reporting with IFR. Costs could include preparationand dissemination costs, litigation costs, or loss of competitive position;while benefits may include factors such as reductions in agency costs, andavoidance of political or legal costs. The literature reviewed in the preced-ing section provides the basis for the research hypotheses relating to IFR.

As discussed in the previous section, agency costs tend to increase withfirm size (Hossain et al., 1995). As voluntary disclosure can reduce mon-itoring costs, a significant agency cost, one would expect to find greaterdisclosure among large firms relative to small firms. Further, as the costof information production and dissemination on the Internet is likely to





be largely unrelated to firm size (Pirchegger and Wagenhofer, 1999), thebenefits of disclosure over the Internet are likely to be increasing withsize. As a consequence, the first hypothesis (stated in alternative form) is:

H 1: There is a positive association between company size and the

voluntary use of IFR.

Lang and Lundholm (1993, pp. 248–249) suggest that there is a com-mon perception that management is more forthcoming with information“… when the firm is performing well than when it is performing poorly”.One explanation, based on signalling theory, is that in such situations man-agement is keen to raise shareholder confidence and support managementcompensation contracts (Singhvi and Desai, 1971; Malone et al., 1993).Poorer performing firms may avoid using voluntary disclosure techniques,such as IFR, preferring instead to “… restrict access to accounting informa-tion to more determined users” (Craven and Marston, 1999, p. 323). However,Lang and Lundholm (1993, p. 249) suggest that sometimes, “certain typesof negative information (particularly earnings information) may be dis-closed voluntarily to reduce the likelihood of legal liability”, e.g., due tounexpectedly large losses. We hypothesize, in alternative form, that:

H 2: There is an association between company profitability and the


The concern that regulators, investors, and other users have regardingcompanies’ going concern status, may motivate highly liquid companiesto make their high levels of liquidity known through voluntary disclosureson the Internet (Wallace and Naser, 1995; Owusu-Ansah, 1998). The use

of Internet for providing financial information may be an expression of management’s confidence in a company’s solvency and future prospects.This leads to the following hypothesis:

H 3: There is a positive association between company liquidity and the


The degree of internationalization of a firm is likely to be associated

with voluntary disclosure because as a company expands its foreignoperations, its need to raise capital internationally increases (Cooke, 1991,1992). Such a company will have an incentive to lower capital costs throughthe voluntary release of information (Choi, 1973; Owusu-Ansah, 1998).IFR provides potential international investors with immediate access to© Blackwell Publishing Ltd. 2003.




both financial and non-financial information concerning the company’saffairs at relatively little cost to both the investors and the reporting entity(Ashbaugh et al., 1999; Craven and Marston, 1999; Williams and Ho,1999). This discussion leads to the following hypothesis:

H 4: There is a positive association between internationalization and the


Agency theory explains and predicts that managers of companieswhose ownership is diffuse have an incentive to disclose more informationto assist shareholders in monitoring their behaviour (Raffournier, 1995).IFR allows companies to provide users with more comprehensive, in

depth, and timely information than that included in traditional financialstatements, and in a manner which may reduce the users’ information costs(Ashbaugh et al., 1999). This is expressed in the following hypothesis:

H 5: There is a positive association between diffuseness of ownership

and the voluntary use of IFR.

Political cost theory suggests that industry membership may affect the

political vulnerability of firms (Inchausti, 1997; Craven and Marston,1999). Firms in industries that are more politically vulnerable may usevoluntary disclosure to minimize political costs, such as regulation, break-up of the entity/industry, etc. Signaling theory also suggests industry dif-ferences in disclosure. If a company within an industry fails to follow thedisclosure practices, including Internet disclosures, of others in the sameindustry, then it may be interpreted that the company is hiding bad news(Craven and Marston, 1999). Evidence supporting an association between

industry and the extent of financial information provided on corporatewebsites was recently provided by Ettredge et al. (2001). Their resultsreinforced comments obtained by the researchers from a sample InvestorRelations directors that they monitored competitor’s websites to bench-mark their own site content and to avoid their company being perceivedas “backwards” relative to industry peers. This discussion leads to thefollowing hypothesis:

H 6: There is an association between industry type and the voluntary useof IFR.

Agency theory explains and predicts that the potential for wealth trans-fers from fixed claimants to residual claimants increases with leverage





(Jensen and Meckling, 1976; Myers, 1977; Watts, 1977). To mitigate theeffects of price-protection by fixed claimants, highly leveraged firmshave an incentive to voluntarily increase the level of corporate disclosure

to such stakeholders through traditional financial statements, and othermedia, such as IFR. This is expressed in the following hypothesis:

H 7: There is a positive association between leverage and the voluntary

use of IFR.

As all sample firms were listed on the New Zealand Stock Exchange,listing status was not examined as a potential determinant of the voluntary

use of IFR in this paper.

4. Research Design

This section describes the research design of the study including sampledescription and data collection.

4.1 Sample

All 229 companies listed on the New Zealand Stock Exchange (NZSE) asat the end of 1998 were included in this study. Three approaches were usedto determine the Internet presence or otherwise of the companies. First,two websites—The Global Register <http://www.globalregister.co.nz>and Knowledge Basket <http://www.knowledge-basket.co.nz/datex/free/ webs.htm>5—were consulted to establish presence and obtain the webaddresses of relevant companies. Second, searches, using the <www.

metacrawler.com> search engine were carried out on the companies notavailable from the above two websites. Finally, the remaining companieswere contacted by telephone to find out whether or not they have estab-lished corporate websites and if so obtain web addresses. The use of mul-tiple sources was considered necessary given the speed of developmentsregarding website establishment among companies. This approach is animprovement on the typical method of identifying websites through searchengines only.

Table 2 presents the distribution of website- and non-website-usingNew Zealand companies by industry and foreign listing. Primary, service,and investment sectors are the largest industries on the New Zealand Stock Exchange.6 About one third of companies listed on the New ZealandStock Exchange are also listed on foreign stock exchanges.





One hundred and twenty-three companies (53.7%) have websites withthe highest proportions of such companies with websites being in eitherthe Primary industry (32.5%) or the Services industry (27.6%). On intra-industrial basis, the Energy sector has the highest proportion of cor-porate website with 79% of energy companies having websites. Thiscompares to about 71 and 70% respectively for the Goods and Primarysectors.

About one-third (32.3%) of the companies are foreign-listed. Of these,about 60% (44) have websites, as compared to 51% (79) of companies notlisted overseas, suggesting foreign listing as a potential factor affectingcompanies’ decision to create websites.

The 123 companies with websites use them to provide a broad rangeof information. Table 3 presents classes of information provided at thesecorporate websites. Four major classes of information were identified:products and/or services information (about 99% of websites); corporate



Table 2. Distribution of Website- and Non-Website-Using Companies by Industry and Foreign Listing

Panel A: By industrial sector*

Total No Website Website

% (of industryCount % Count % Count total)

Primary (G01) 58 25.3 18 17.0 40 32.5 (70)Energy (G02) 14 6.1 3 2.8 11 8.9 (79)Goods (G03) 28 12.2 8 7.5 20 16.3 (71)Property (G04) 20 8.7 12 11.3 8 6.5 (40)

Services (G05) 58 25.3 24 22.6 34 27.6 (59)Investment (G06) 51 22.3 41 38.7 10 8.1 (20)Total 229 100.0 106 100.0 123 100.0 (n/a)

Panel B: By foreign listing status

% (of listed Count % Count % Count total)

Listed in New Zealand only 155 67.7 76 71.7 79 64.2 (51)

Listed in New Zealand andforeign exchanges 74 32.3 30 28.3 44 35.8 (60)Total 229 100.0 106 100.0 123 100.0

* Based on New Zealand Stock Exchange market sector groupings.



history, background and profiles (94%); news and announcements (68%);and financial information7 (73%). In addition to these major categories,companies also provide other types of information such as referencematerials including articles and links to other useful/related websites

(33%); e-commerce facilities, including online booking, shopping and/ortracking (24%); social-oriented, environmental and/or community-relatedinformation (22%); and employment and job opportunities (12%).

About three-quarters (73.2%) of companies with websites in this studyprovide financial information on their websites. For the purpose of thisresearch, the 229 NZSE-listed companies were classified into three types:(1) companies without a website (n = 106); (2) companies with a website,and not engaging in IFR (n = 33); and (3) companies with a website and

engaging in IFR (n = 90). In this study, the 139 companies in categories(1) and (2) were grouped together as non-Internet financial reporting com-panies (N-IFRC), while the 90 companies that engage in IFR were classedas Internet financial reporting companies (IFRC).

Table 4 presents the main features, frequency, format and types of financial information provided by IFRC. Companies were classified intothree categories on the basis of whether they provided comprehensiveannual financial statements only (38%), financial highlights only (18%),

or both financial statements and highlights (44%). Although not reportedin Table 4, 94% of comprehensive financial statements incorporated anaudit report, whilst financial highlights were generally not accompaniedby an audit report unless they included a set of summarized financial state-ments. Some companies provide archives for previous years’ financial



Table 3. Type of Information Published at Listed Companies’ Websites(n = 123)

Main types of information published Companies %

Product or service information 122 99.2Company history or background 116 94.3News and announcements 83 67.5Financial information 90 73.2

Other types of information published Reference information (articles/links to other useful sites) 40 32.5E-Commerce (uses some form of e-commerce, e.g., onlinebooking, shopping, tracking, etc) 29 23.6

Social (environmental and/or community information) 27 22.0Employment (information on employment opportunities) 15 12.2



information. Two main formats—Hypertext Mark-up Language (HTML)and Portable Document File (PDF)—are predominantly used for theprovision of financial information. Thirty-seven of the 90 companies pro-vide financial information in PDF format only compared to the 31 whichuse the HTML format only. Eighteen companies employ both formats,while the remaining four companies use other formats such as MS Wordsand MS Excel spreadsheets.

Panel B of Table 4 presents the extent to which companies utilisecertain electronic features to enhance the display, readability, and under-standability of the financial information they provide on their websites.About 81% of such companies use graphic, video and/or audio features toenhance the provision of financial information on their sites. Fifty-sevenof the companies use hyperlinks to ensure easier navigation and cross-referencing of their financial information, while 22 of them provide userswith the option to view their financial information with or without frames.However, very few New Zealand companies took advantage of the online



Table 4. IFR Practices of New Zealand Companies

Panel A: Type of financial information, number of years, and electronic format (n = 90)

Total No. of Years Format

Type of No. of 4 or Information Companies % 1 2 3 More PDF HTML Both Others

– Comprehensivefinancial statementsonly 34 37.8 17 13 3 1 17 9 6 2

– Financial highlightsonly 16 17.8 6 7 2 1 2 14 – –

– Both comprehensivefinancial statementsand financial highlights 40 44.4 13 8 10 9 18 8 12 2

Total 90 100 36 28 15 11 37 31 18 4

Panel B: Electronic features used in providing financial information (n = 90)

Electronic Features No. of Companies %

– Graphics, video or audio 73 81.1– Hyperlinks 57 63.3

– Appropriate screen layout for data view 45 50.0– Options available for viewing data in frame/no-frame 22 24.4



nature of the web to provide real-time and other market-related informationsuch as share prices/stock tickers, analyst factbooks, back orders, labourcontracts, monthly/weekly sales, stock plans and performance reports.

Five companies provide links to other websites which have real-time shareprices/stock tickers for many companies. This indicates that New Zealandpractice is lagging behind US practices in providing a wider informationset, as reported by Ashbaugh et al. (1999).

4.2 Data Collection

Data for relevant variables in this study were collected from corporate

websites for companies with Internet financial reports,8

and the Datexdatabase9 for the remaining companies. Where these two sources failed toyield the required data, hard copies of the company’s annual reports andaccounts were consulted. Finally, various publications of the New ZealandStock Exchange and several editions of The New Zealand Business Who’s

Who (1996–98) directory were consulted to obtain additional descriptivedetails such as industry group sectors, foreign listings, and location of con-trol. The primary data variables collected and their respective definitions

are presented in Table 5.

5. Data Analysis and Results

Univariate and multivariate analytical approaches were employed in thestudy to identify the determinants of IFR. First, exploratory data analysiswas carried out to determine the tendencies of the collected data. The 229companies were divided into two categories: companies providing financial

reports on the Internet (IFRC) and companies not providing financialreports on the Internet (N-IFRC). The latter group included both com-panies with websites but no financial information and companies withoutwebsites. Descriptive statistics pertaining to the independent variables forIFRC and N-IFRC are presented in Table 6.

Comparison between IFRC and N-IFRC reveal that companies thatengage in IFR are generally larger and more profitable than non-IFR ones.Their average market value of $10,819 million is far greater than that of

N-IFRC (only $169 million). A similar disparity is observed for the othermeasure of size (Total assets) used in this study. IFRC are associated withhigher levels of profitability across both unadjusted (not reported here)and size-adjusted variables. On average, IFRC also appear to be moreliquid than N-IFRC. A greater proportion (76%) of N-IFRC’s shares are





held by their top 40% shareholders, indicating narrower spread of owner-ship among IFRC. Also, a greater proportion (52%) of IFRC are inter-nationalized as against only 37% of N-IFRC.

Univariate independent sample t-tests and Chi-square tests on therelevant independent variables for the two categories of companies, IFRCand N-IFRC, are presented in Table 7. The results of the tests indicatesupport for H

1, in that differences in size are statistically significant across

the two measures of size, market capitalization and total assets. Differ-ences in both average market capitalisation and total assets are significantat the 1% level.

Profitability and leverage appear not to be associated with IFR when thetwo groups are compared as no statistically significant differences werefound. On this basis, it appears that H

2and H

7are not supported in this

study. With respect to ownership spread, IFRC’s shareholding base is



Table 5. Research Variables

Variables Definition*

SizeMarket capitalization Market value of companies as measured by their totalcapitalisation as at the end of 1998

Total assets Average total assets

ProfitabilityReturn on equity Profit after tax × 100

Shareholder equityReturn on total asset Profit after tax × 100

Total assets

LiquidityCash assets by total assets Cash and similar items

Total assets

Internationalization Foreign listed and/or controlled

Share spread The proportion of shares owned by the top 40% of shareholders

Industrial sector Main industrial group sector: G01 = Primary;G02 = Energy; G03 = Goods; G04 = Property;G05 = Services; and G06 = Investment

LeverageDebt to equity ratio Total debt

Shareholder equity

* Averages are for the three years 1996 to 1998 for all variables other than internationalization andindustrial sector.





Table 6. Descriptive Statistics

Variable Statistics N-IFRC* IFRC* All Companies

SizeMarket capitalization Mean $168,584.82 $10,818,606.49 $4,831,907.92($’000) Median $32,860.53 $180,360.46 $69,133.80

Std Deviation $491,529.21 $84,682,364.32 $56,073,471.34Percentile 25 $10,225.02 $50,049.25 $13,446.55Percentile 75 $139,237.42 $783,505.63 $289,087.76

Total assets ($’000) Mean $349,088.43 $3,084,020.49 $1,584,219.04Median $61,679.36 $297,887.33 $101,546.77Std Deviation $1,162,857.25 $7,540,835.81 $5,302,146.81Percentile 25 $16,427.00 $60,080.11 $30,922.00Percentile 75 $198,619.67 $2,690,183.33 $535,511.58

ProfitabilityReturn on equity Mean 0.02 0.18 0.09Median 0.04 0.08 0.06Std Deviation 0.22 1.17 0.81Percentile 25 –0.03 0.01 –0.01Percentile 75 0.12 0.12 0.12

Return on total asset Mean 0.02 0.01 0.01Median 0.02 0.04 0.03Std Deviation 0.19 0.13 0.17Percentile 25 –0.01 0.01 –0.01Percentile 75 0.08 0.06 0.07

Liquidity

Cash assets by total Mean 0.06 0.20 0.13assets Median 0.01 0.03 0.02

Std Deviation 0.15 0.60 0.43Percentile 25 0.01 0.01 0.01Percentile 75 0.09 0.12 0.09

Internationalization Count: Yes 49 47 96No 90 43 133

Share spread Mean 75.96 68.82 72.81Median 82.34 74.55 79.06Std Deviation 20.89 19.63 20.60

Percentile 25 69.71 54.69 60.69Percentile 75 91.43 84.15 88.69

Industry Count: Primary 24 34 58Energy 6 8 14Goods 14 14 28Property 13 7 20Services 37 21 58Investment 45 6 51

LeverageDebt to equity ratio Mean 2.01 2.47 2.22

Median 1.61 1.43 1.57

Std Deviation 1.83 4.48 3.32Percentile 25 1.24 0.91 1.12Percentile 75 2.31 2.02 2.10

* N-IFRC = Non-Internet financial reporting companies (n = 139); IFRC = Internet financial reportingcompanies (n = 90).



more dispersed as lower percentages of shares are retained in the hands of their top 40% of shareholders. The difference between the two groups issignificant at the 5% level and thus supports H

5.

Similarly, there is a statistically significant difference at the 5% level inthe levels of liquidity between the two categories of companies. In general,the results of the univariate test appear to provide support for H

3, with

IFRC reporting greater levels of liquidity than N-IFRC. H

4(internationalization) and H

6(industry) were tested at the univariate

level using chi-square tests. The difference in the internationalization of N-IFRC and IFRC is statistically significant at the 5% level, while differ-ences among industry sectors are significant at the 1% level.



Table 7. Univariate Sample Test of Independent Variables for N-IFRC and IFRC

Panel A: T-test of variables on interval scale

Mean Difference(Standard errors

Variable of mean) t-value Significance#

Size: Market capitalization (log) 0.8565 5.895 0.000***(0.1453)

Total assets (log) 0.7608 5.732 0.000***(0.1327)

Profitability: Return on equity –0.1551 –1.186 0.239(0.1308)

Return on total assets 0.0103 0.427 0.670(0.0240)

Liquidity: Cash assets by total assets –0.1408 –2.093 0.020**(0.0673)

Share spread 7.1435 2.290 0.012**(3.1198)

Leverage: Debt to equity ratio –0.4538 –0.859 0.196(0.5284)

Panel B: Pearson’s Chi-square test of variables on categorical scale

Variable Value df Asymp. Sig. (2-sided)

Internationalization 6.462 1 0.011** Industry 28.885 5 0.000***

# significance is 1-tailed for all variables except for profitability which is 2-tailed.** and *** indicate significance at the 5 and 1% levels, respectively.



In summary, the univariate analysis indicates that, IFRC are larger,relatively more liquid, and have a more widely dispersed shareholdingbase than N-IFRC. These results are consistent with the findings of Craven

and Marston (1999) and Ashbaugh et al. (1999). Also, IFRC appear to havea greater degree of internationalization than their N-IFRC counterparts. Itis unclear at this stage if this is logically associable with the fact that IFRCare larger, with wider dispersal of their shareholding base.

This paper further investigates whether IFR practices of these companiescan be predicted from a combination of these variables. A multivariatelogistic regression analysis is employed, with the dependent variable classi-fied as a binary choice between IFRC and N-IFRC. Logit analysis enables

us to investigate the probability of an event’s occurrence in relation to anumber of measurable independent variables, with the estimation allowingus to compare the relative importance of these variables.

Two models, A and B, incorporating different measures of the independ-ent variables, size and profitability, were specified in order to investigatethe determinants of IFR among the listed companies. The models examinedwere of the following form:

Yi =α

+ β 1 (Size)i + β 2 (Profitability)i

+ β 3(Liquidity)

i+ β

4(Internationalization)

i+ β

5(Ownership Spread)

i

+ β 6–10

(Industry1–5

)i+ β

11(Leverage)

i+ µ

I (1)

Where, for theith firm in Model A,

Y = IFR practice; 0 for N-IFRC and 1 for IFRCα = the constant of the equation

Size = log of market capitalisationProfitability = return on total assetsLiquidity = cash assets by total assetsInternationalization = foreign listing or foreign control (1 = yes, 0 = no)Ownership spread = proportion of shares held by top 40% shareholdersIndustry = Industrial sector—Industry

1is primary sector (G01),

1 if yes and 0 otherwise; Industry2

is energy sector(G02), 1 if yes and 0 otherwise; Industry

3is goods

sector (G03), 1 if yes and 0 otherwise; Industry4 isproperty sector (G04), 1 if yes and 0 otherwise;Industry

5is services sector (G05), 1 if yes and 0

otherwise; Investment sector (G06) is the refer-ence group10





Leverage = total debt to equity ratioµ = error term

The exploratory variables used in Model B are identical to those of Model

A above except for the following:

Size = log of total assetsProfitability = return on equity

To assess possible multicollinearity issues, the correlations among themodels’ continuous independent variables are measured and reported inTable 8. As one would expect, the two measures of size are highly cor-related, as are the alternative measures of profitability. Although not reportedhere, we also found a high level of correlation between the measures of internationalization on the one hand, and ownership spread and size (totalassets) on the other. It appears, from this finding, that highly international-ized companies are generally larger and more widely owned. However, areview of collinearity diagnostics11 did not indicate that multicollinearitywould be a concern in the subsequent analyses.

The results of the estimate of Model A for all 229 companies arereported under A1 in Table 9. Model A1, which accurately classifies morethan 79% of the observations in this study is statistically significant atthe 1% level. The results of its estimation indicate that IFR practices arehighly dependent on size, liquidity, and ownership spread, thereby sup-porting H

1, H

3, and H

5. Size is a statistically significant predictor at the

1% level, while liquidity and ownership spread are significant at the 10%and 5% level, respectively. Profitability, internationalization, industry, andleverage are not significant.



Table 8. Pearson’s Correlation Matrix of Independent Variables

Return Log of Log of Return on Market Total on Total

Capitalization Assets Equity Assets Leverage Liquidity

Log of total assets 0.674***Return on equity 0.274*** 0.031

Return on total assets 0.263** 0.233*** 0.351***Leverage 0.083 0.141* 0.477*** 0.101Liquidity –0.063 –0.172** 0.041 –0.107 0.044Share spread 0.006 –0.044 0.035 –0.031 0.107 –0.086

*, ** and *** indicate significance at the 10, 5 and 1% levels (2-tailed), respectively.



Cook’s Distance test is used to explore potential outlying or misclassifiedcases, which indicates that two outlying cases were exercising dispropor-tionate influence on the residuals resulting from the estimation of Model A1.These cases were removed and the model is re-estimated with a smaller



Table 9. Multivariate Logistic Regression Results

Model

Research Variable# Expected Sign A1 A2 B1 B2

Constant –5.796*** –6.905*** –5.747*** –6.203***(1.690) (1.852) (1.655) (1.735)

Size + 1.510*** 1.751*** 1.394*** 1.536***(0.326) (0.359) (0.284) (0.310)

Profitability +/– –2.562 –3.307 0.433 –0.863(1.986) (2.120) (0.407) (1.393)

Liquidity + 2.782* 3.132* 3.092** 4.303**(1.454) (1.749) (1.368) (1.686)

Internationalization + 0.257 0.427 0.231 0.150(0.498) (0.526) (0.479) (0.494)Ownership Spread – –0.030** –0.037** –0.030** –0.032**

(0.013) (0.014) (0.012) (0.013)Industry +/– ** **

Industry1(Primary) +/– 0.508 0.602 0.905** 0.753*

(0.407) (0.424) (0.393) (0.408)Industry

2(Energy) +/– 0.181 0.138 0.616 0.564

(0.559) (0.574) (0.556) (0.572)Industry

3(Goods) +/– 0.373 0.439 0.373 0.431

(0.475) (0.501) (0.465) (0.482)

Industry4 (Property) +/– –0.186 –0.091 –0.533 –0.649(0.617) (0.638) (0.550) (0.564)

Industry5(Services) +/– 0.458 0.729 0.497 0.571

(0.427) (0.462) (0.419) (0.428)Leverage + –0.058 0.077 –0.047 –0.059

(0.113) (0.161) (0.089) (0.092)–2 Log likelihood 153.839 142.231 162.693 157.749Nagelkerke R2 0.427 0.482 0.438 0.454Chi2 statistics 59.852*** 68.653*** 65.887*** 68.040***Degrees of freedom 11 11 11 11

Number of observations 229 227 229 227Correctly predicted: N-IFRC 85.2% 81.6% 84.6% 82.2%

IFRC 72.1% 71.6% 68.0% 67.6%Overall 79.5% 77.3% 77.1% 75.6%

*, ** and *** indicate significance at the 10, 5 and 1% levels, respectively.# Explanatory variables for the models are: Size = log of market capitalization (A1 and A2), log of total assets (B1 and B2); Profitability = return on total assets (A1 and A2), return on equity (B1 andB2); Liquidity = cash assets by total assets; Internationalization = foreign listing/control; Ownershipspread = Proportion of shares held by top 40% of shareholders; Industry = industrial sector; Leverage= Total debt to equity ratio.



sample of 227 companies. The results of this estimation are presented asA2 in Table 9. Model A2, for which the two outliers were removed, is alsosignificant at the 1% level, with about 77% rate of correctly predictedobservations. Its results are broadly similar to those of Model A1.

Model B1 was estimated using alternative variables for size and profit-ability. The results confirm the findings in the previous models that size,level of liquidity, and ownership spread are positively related to IFR prac-tices. In addition, industry is also found to be a significant predictor of IFRat the 5% level. Of industry’s constituent categories, the primary industrygroup sector is significant at the 5% level. The direction of its regressioncoefficient indicates that relative to the average of all industry groupsectors, companies in the primary group sector are more likely to engagein IFR. Profitability, internationalization, and leverage are not significant.

Similar to the procedure applied to Model A1 above, Cook’s Distance

test revealed that two of the cases in the study exerted disproportionateinfluence on the coefficients that resulted from Model B1’s estimation.Model B2 is a re-estimation of B1 excluding the two outlying cases. Theresults again confirm the influence of size, liquidity, ownership spread,and industry on companies’ IFR practices.

Across the four sub-models (A1, A2, B1, and B2) estimated in thisstudy, size is shown to have a significant and positive impact on IFR practice.Larger firms are more likely to engage in IFR. This finding is consistentwith those reported by Ashbaugh et al. (1999) in the US, Pirchegger andWagenhofer (1999) in Austria, and Craven and Marston (1999) in the UK.It is also in line with the findings of a number of studies on hard copy-based corporate disclosure (McNally et al., 1982; Hossain et al., 1995;Wallace and Nasar, 1995; Owusu-Ansah, 1998). It appears that largercompanies are able to derive scale benefits from voluntarily using theInternet as a medium for financial disclosure and are less likely to becompetitively disadvantaged by such incremental reporting.

Liquidity is positively related to IFR across the four models. It appearsthat companies which are relatively cash-rich are more likely to engage inIFR, taking advantage of the additional medium to communicate manage-ment’s confidence in the company’s solvency and future prospects. Thisresult is consistent with that of Wallace et al. (1994), who found liquidityto be an incentive for voluntary disclosure in traditional print-based financialstatements.

Higher level of shareholding by the top 40% of shareholders wasconsistently negatively related to IFR practices in all four models. Thecombination of the finding relating to size and that of ownership spread





suggests that IFR companies are not only large, but their shareholding ismore widely dispersed. Incremental voluntary disclosure through the webcould be viewed as an additional channel of communication set up by IFR

companies to reach their more widely dispersed owners. This practicereduces such owners’ information costs and assists them in monitoringmanagement behaviour.

The statistically significant coefficients for industrial sector in twoof the models provide additional insight into the factors that determinecompanies’ IFR practices. Cross-industrial differences in disclosure re-quirements have previously been reported to influence both conventionaldisclosure practices (see Owusu-Ansah, 1998) and the more recent practice

of disclosing financial information on corporate websites (Ettredge et al.,2001). In this study, compared to the average across all sectors, companiesin the primary industry group sector are more likely to engage in IFR.This result is similar to that of Ettredge et al. (2001), who found that UScompanies in the primary industry group sector, together with those in theservices industry group sector, were more extensive users of IFR thancompanies in other industry group sectors. Overall, the result in this studyis consistent with a political cost explanation. There is a significant body

of literature which suggests a linkage between the political costs specificto many of the industries forming the primary industry group sector, suchas oil and gas, steel, mining, chemicals, etc., and accounting choice (forexample, Cahan, 1992; Cahan et al., 1997; Han and Wang, 1998).

Internationalization, which was positively and significantly related toIFR practice at the univariate level was found to be insignificantly relatedat the multivariate level. There is a logical co-relation between a company’ssize and the spread of its ownership on the one hand, and its degree of

internationalization, on the other. It appears that the effects of inter-nationalization as an independent variable is now largely accounted for bysize and ownership spread, two factors that are found to be consistentlyand significantly related to IFR in this study.

To summarize, the results of multivariate analysis generally stronglyand consistently support H

1(size), H

3(liquidity), and H

5(ownership spread).

Support is also found for H 6

(industry), but the results do not support H 2

(profitability), H 4

(internationalization) and H 7

(leverage).

6. Summary and Conclusion

The development of the Internet as a medium for global corporate communi-cation creates a new channel for the dissemination of corporate financial





information. Due to its increasing usage, its multimedia capability and itscapacity for interactive communication, the Internet is challenging thevery nature of financial reporting, its boundaries, its frameworks, and evenits fundamental role in society. The global access of financial reports onthe Internet could produce further impetus for global standards for financialreporting.

A significant proportion of companies have set up websites and someof them use their websites to provide financial information. This paperreports on the website practices of New Zealand-listed companies and thedeterminants of IFR practices among these companies. In particular, itbuilds on the comprehensive literature on voluntary reporting and uses awider definition of IFR and a more comprehensive model of the deter-minants of IFR than previously employed in the IFR literature.

The results of the study indicate that firm size, liquidity, industrialsector and the spread of ownership motivate the provision of IFR. Thelarger a company is, the more likely it is to set up a website and to use itfor IFR. This finding suggests that large companies are deriving benefitsfrom setting up websites and providing financial information on thismedium. Companies with greater levels of liquidity are also more likelyto engage in IFR. Likewise, the industry group sector of a company is apredictor of its likelihood of engaging in IFR, with companies operatingin the primary industry group sector, such as those in the oil and gas, andforestry industries, are more likely to engage in IFR than companies fromother industry group sectors. The higher the proportion of shareholding,by the top 40% of shareholders, the lower the probability that a companywould provide financial information on the Internet.

Although considerable literature suggests that disclosure levels in print-based financial reports are associated with other firm characteristics,no significant relationship was found between IFR and profitability, inter-nationalization, and leverage in this study. This suggests that the IFRenvironment and culture is somewhat different from the traditional print-based financial reporting environment. These differences in reportingenvironments may reflect differences in cost, benefit, demand, and supplystructures in such information environments. The lack of associationbetween the adopting of the Internet for the display of corporate financialinformation and the internationalization of a company is particularly sur-prising, since it is expected that such companies would take advantage of the Internet’s ability for providing global access to the stakeholders of suchcompanies. It is however noteworthy that significant positive relationshipwas found between internationalization and IFR at the univariate level,





and its influence may have been subsumed within those of size and spreadof ownership at the multivariate level.

Future research may consider explanatory variables specific to the IFR

environment, which may provide further insights into IFR practices. Suchfactors may include the age and levels of education of company directors/ managers, attitude of management to IT and new ideas, the age and strat-egic position of each company in its industry, and the stage in the life cycleof the company’s major products. These factors may influence voluntaryuse of the Internet for financial reporting purposes. Also, researchers inthis evolving area may investigate other disclosure-related issues such asthe frequency and timeliness of IFR and the level of users’ interest and needs

in respect of IFR, possibly measured by frequency of visits to corporatewebsites to download or view financial information. These issues areparticularly pertinent as interest in continuous on-line reporting grows.Continuous on-line reporting is the practice by which firms providefinancial or non-financial information simultaneous with, or within a shortperiod of, the occurrence of relevant events. Our study is based on NZpractices; practices in other countries and international comparisons of determinants of IFR are useful in the development of a comprehensive

predictive model for the choice of IFR.

Notes

1. See for example, Craven and Marston, 1999 (UK); Pirchegger and Wagenhofer,1999 (Austria and Germany); Trites, 1999 (US and Canada); Deller et al., 1999 (USA, UKand Germany); Hedlin, 1999 (Sweden); Gowthorpe and Amat, 1999 (Spain); and Fisheret al., 2000 (New Zealand). Lymer et al. (1999) also document an international comparisonof IFR practices.

2. Ashbaugh et al. (1999) defines corporate IFR as the provision on a company’s

website of either “(1) a comprehensive set of financial statements (including footnotes),(2) a link to its annual report elsewhere on the Internet or (3) a link to the U.S. Securityand Exchange Commission’s (SEC) Electronic Data Gathering, Analysis and Retrieval(EDGAR) system” (p. 241). In New Zealand, there is no central archive for electronicfinancial information, similar to the US SEC’s EDGAR system.

3. For example, Bangladesh (Ahmed and Nicholls, 1994; Ahmed, 1996), Hong Kong(Tai et al., 1990; Lau, 1992; Wallace and Naser, 1995), India (Singhvi, 1968; Marston andRobson, 1997), Japan (Cooke, 1991, 1992, 1993), Mexico (Chow and Wong-Boren, 1987),New Zealand (Courtis, 1979; McNally et al., 1982; Hossain et al., 1995) Sweden (Cooke,1989a,b), UK (Firth, 1979), and USA (Singhvi and Desai, 1971; Buzby, 1975; Malone

et al., 1993).4. For example, see Singhvi, 1968; Singhvi and Desai, 1971; Buzby, 1975; Daviesand Kelly, 1979; Courtis, 1979; Firth, 1979; McNally et al., 1982; Chow and Wong-Boren,1987; Cooke, 1989a,b, 1991, 1992; Tai et al., 1990; Hossain et al., 1994; Wallace et al.,1994; Hossain et al., 1995; Raffournier, 1995; Wallace and Naser, 1995; Inchausti, 1997;Marston and Robson, 1997; Patton and Zelenka, 1997; Owusu-Ansah, 1998.





5. These websites identify and provide links to the websites of New Zealand listedcompanies. As at December 1999, the Global Register site provided links to the websitesof 14 of the 102 companies listed thereon, while the Knowledge Basket site is linked to 69(out of 139) company sites.

6. Companies listed on the New Zealand Stock Exchange come from 13 differentindustry sectors. These single sectors are further grouped into 6 group sectors—Primary(Mining, Forestry & Forest Products, Building Materials & Construction, Agriculture &Fishing), Energy (Energy Processing, Distribution & Utilities), Goods (Food & Beverages,Textiles & Apparel, Intermediate & Durables), Property, Services (Transport, Ports, Leisure& Tourism, Consumer, Media & Telecommunications, Finance & Other), and Investment.

7. A company is identified as providing financial information where it provides onthe web a comprehensive set of financial statements and/or financial highlights extractedfrom such financial statements (including partial and/or summarized financial statements).The comprehensive financial statements may contain GAAP reconciliations where NewZealand companies are also listed on foreign exchanges. For example, in compliance with

the SEC’s FORM 20F disclosure requirements, New Zealand companies registered in theUS provide in notes to the financial statements reconciliation of New Zealand-GAAP toUS-GAAP where the amounts are materially different.

8. A random sample of the financial data collected from this source were cross-checked against other sources (Datex database or Annual Report hard copies) to validatetheir accuracy.

9. Datex is a database of New Zealand listed company information, including annualreport extracts and data such as daily share prices and dividends.

10. Deviation contrasts are used for the categories of the industry variable in subsequentlogit analyses. Unlike indicator contrasts, which compare each category to the referencecategory, deviation contrasts compare each category other than the excluded category(investment industry group sector in this study) to the unweighted average of all categories.

11. The Tolerance statistics relating to the independent variables were reviewed. Inaccordance with Menard (1995, pp. 65–67), these statistics were produced as output fromSPSS linear regressions using the same dependent and independent variables as used in thecorresponding logistic regression models.

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