Factors in Taiwanese Firms' Decisions to Adopt Electronic Commerce: An Empirical Study

Factors in Taiwanese Firms’

Decisions to Adopt Electronic

Commerce: An Empirical Study

Jiann-Chyuan Wang and Kuen-Hung Tsai

1. INTRODUCTION

A T the recent ministerial conference of the WTO held in November 2001,ministers from the member countries declared that electronic commerce (e-

commerce) ‘facilitates transactional activities and creates challenges andopportunities for member countries at all stages of development’. The membercountries went on to commit the WTO to the non-imposition of tariffs on e-commerce until the next session, a declaration which serves to confirm arecognition of the importance of e-commerce. Although e-commerce may createa digital divide between many of the member countries, it can serve as thegreatest equaliser for developing countries in terms of shortening thedevelopment gap between these countries and their advanced counterparts.

The term ‘electronic commerce’ is usually defined as business activities takingplace through the increasing popularisation of transactions of goods or serviceson the Internet, the improved usage of the Internet and World Wide Web(WWW), and the reduced costs of systems installation and operation (Hanson,2000).1 For example, it is predicted that the value of the US e-commerce market,

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JIANN-CHYUAN WANG is Research Fellow, Division of Taiwan Economy, Chung-HuaInstitution for Economic Research, Taipei, Taiwan, Republic of China. KUEN-HUNG TSAI isAssistant Research Fellow, Chung-Hua Institution for Economic Research, Taipei, Taiwan,Republic of China and Professor, Department of Shipping and Transportation Management,National Taiwan Ocean University, Keelung.1 E-commerce can be defined in a variety of ways. For instance, OECD (1997) defined it as ‘businessactivities enhancing value exchange via electronic telecommunications networks’. According toStrader and Shaw (1997), e-commerce is ‘a modern way of management providing products andservices of quality and speeding up the delivery of service with lower costs to satisfy organizationsand customers’. Zwass (1996) defined e-commerce as ‘maintaining business relations and processingtransactions through the sharing of business information via information networks’. Although thesedefinitions differ in some ways, they each seem to share the view specified in Hanson (2000).

which was US$41billion in 1999, will grow to US$327billion by 2002. TheTaiwanesee-commercemarket,which wasNT$1 billion in 1999,is predictedtoreach NT$16.5 billion by 2002 (MIC, 1999). This trend indicates that e-commerceprovidesconsiderableopportunitiesfor future businessdevelopment.

Given the Internet’sfeaturesof ubiquity, interactivity andspeed(KenneyandCurry, 1999),theadoptionof e-commercewill bring numerousbenefitsto firms.Theywill beableto establishglobalmarketingnetworksto helpreducehandlingcosts whilst facilitating higher levels of efficiency. They can also respondappropriatelyto customerdemands(by understanding their habits),lower theirinventory levels (throughreal-timeproduction),foster communicationbetweendistantunits andcreatesupplychainsandstrategicalliances(Elango,2000;andKambil, 1997). Transactionsinvolving goodsor serviceson the Internet are,however, likely to cause exchangerisks, particularly if data are stolen oramended,or if transactionsaremadeundera falsename.Thesefactorswill allaffect thedevelopmentof e-commerce(Bhimani,1996).Despitethe risks,manyfirms throughouttheworld continueto introducee-commercefor thebenefitsandflexibility it brings to their business,since enterprisesof all sizes canconveniently explorethe e-commercemarket.

Sincee-commercehasbecomea global trend,andits developmenthasbegunto correlateto a country’scompetitiveness,issuesconcerningfirms’ decisionstoadopte-commerce,particularly the factorsinfluencing their decisions,thereforeneedto be investigatedfully. Rosenand Howard (2000) arguedthat thereareseveralfactors involved in the adoptionof e-commerceby a business,namelyefficiency, convenience,public policy, costs and security. Elango (2000)specifiedtwo potentialbenefitsfrom the adoptionof Internetbusiness,the firstof which wascostsaving(for instance,reducingthe costsof both procurementandthebusinesscycle in orderto improveefficiencyandprecision).Thesecondbenefitwascitedasincreasingdifferentiation(for example,respondingquickly tothemarketandconsumerdemand).Accordingto Bingi et al. (2000),eventhoughe-commercemay cut the costsof datacollectionanddocumentation, whilst alsoenhancingefficient transactions,firms should considercarefully the costs ofdevelopinge-commerce,the exchangerisk involved in Internetbusinessandthepotentiallegal problems.

In summary, these studies reveal that firms generally believe that theirdecisionsto adopte-commercemaybe influencedby variousfactorssuchasthebenefitsandthe costs,online exchangerisksandpublic policy. However,whilstthese studies have examined the factors involved in firms’ adoption of e-commerce,noneof themhaveobservedthesefactorsfrom a theoreticalcontext.In otherwords,thereis a lackof anyempiricalanalysisof theirobservations.Thispaperthereforeaims to investigatethe factors involved in firms’ decisionstoadopt e-commercefrom an empirical perspectiveand to look into certaintheoreticalissues.The papercomprisesof severalseparatesectionsproviding a

1146 JIANN-CHYUAN WANG AND KUEN-HUNG TSAI

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review of the literature, researchmethodology,analysisand discussion.Theconcluding section will attempt to clarify the findings of this research,itslimitations andthe appropriatedirection for future research.

2. LITERATURE REVIEW

This sectionaimsto review the existingtheoriesregardingthe organisationaladoptionof information technology(IT) and relevantempirical findings. Thefundamental reasonfor sucha review is that firms tendto considerthat Internettransactionsfor goods or servicesbasically involve the application of IT ascomparedto traditional transactionmedia.

a. TheoreticalBackground

Two theoreticalschoolshave emergedin the empirical study of factors infirms’ adoptionof IT: (i) Rogers’ innovationdiffusion theory: in his view, theorganisational decisionto innovateis determinedby innovationcharacteristics,including relative advantage,complexity, compatibility, observability andtriability (Rogers,1983). The integratedanalysisconductedby Tornatzky andKlein (1982) showedthat the first two characteristicswere the main factors inbusinessinnovation.(ii) Critical masstheory (Tornatzkyand Fleischer,1990):This arguesthat firms’ decisionsto innovatecomefrom organisational factors(e.g.scaleandreadiness)andenvironmentalfactors(e.g.marketstructure).BothBrancheauandWetherbe(1990)andFitchman(1993)refer to a combinationofthesefactors,arguingthat Rogers’theory fails to explain the importantreasonswhy firms decideto adoptIT. Accordingto Bouchard(1993),critical masstheoryprovidesa much betterexplanationof firms’ decision-making behaviour.Chauand Tam (2000) recently introduced the technology-push/need-pull (TP/NP)concept,asproposedby Zmud(1984),asa meansof interpretingtheadoptionofnew technology.In their view, the main driver in a firm’s decisionto innovatereliesupongainsfrom new technicalapplicationsanduserneeds.

The empirical studieson the adoption of IT during the 1990s invariablyinvolved a discussionon electronicdatainterchange(EDI). In Grover’s (1993)discriminateanalysisof the top 1000US corporations,usingsubscribersto CIOmagazineas the generalpopulation,he identified a numberof major variables:scale,infrastructure(+), competitiveintensity(+), complexity(+) andthesupportof management(+). BanerjeeandGolhar(1994)foundthroughtheir discriminateanalysisthat customers(+), competitive pressure(+) and speed(+) were thevariablesdeterminingwhetheror not US enterprisesdecidedto implementEDI.Premkumaret al. (1994)applieda regressionanalysisto firms listed in the TopComputerExecutives, producingfindings which showedthat relative advantage

TAIWANESE FIRMS’ DECISIONS TO ADOPT E-COMMERCE 1147


(+) andcosts�ÿ� determinedwhetheror not US firms adoptedEDI, whilst otherinnovativefeatureshadno significantimpact.ReekersandSmithson(1994)useda regressionapproachto analysefirms in Germanyand the United Kingdom,finding that operationalbenefits(+) servedasthe most importantfactor.

From their observationsof seven individual cases,Iacovou et al. (1995)determinedthat therewereseveralinfluential factors:(i) perceivedbenefits(+)(such as the reduction of inventory levels and improvementsto businesspartnerships);(ii) organisationalreadiness(+) (in terms of the readinessandadequacyof resources);and (iii) external pressure(+) (namely competitionwithin the sameindustryandthe requirementsof their major businesspartners).The logistic regressionanalysisundertakenby Premkumaret al. (1997)showedthatcompetitivepressure(+), thescopeof thecompany(+), customersupport(+)andsupportfrom themanagement(+) all hadanimpacton theadoptionof EDI ina firm; however, the impact on EDI innovation and creativity was not verysignificant.

Throughthe notion of TP/NP,ChauandTam (2000) investigatedthe factorsinvolved in the adoptionof information systemsin firms in Hong Kong. Thefindings of their regressionanalysis revealed that the costs of technologyimplementation�ÿ� (with an insignificant impacton benefits),satisfactionwiththe existing system �ÿ� (needs) and availability of human resources(+)(organisationalfactor) had a significant impact on the decisionto adopt suchsystems.However, factors concerningthe unpredictablemarket and demand,namelylevel of competition,stability of productdemandandcustomerloyalty,wereall insignificant.

In summary,the abovefactors relate mainly to: (i) IT (relative advantages,costs, benefits, speed and satisfaction with the existing system); (ii)organisational factors (infrastructure, readiness, availability of technicalpersonneland businessscale); and (iii) the external environment(consumerdemand,competition within the industry and the unpredictablemarket). Inadditionto thesefactors,a numberof other issuesshouldalsobe noted.

First of all, someof the factorsarevery similar, andthusthereis substantialcorrelationbetweenthesefactors.For example,a firm with more IT personneltends to have larger businessscale, thus the benefit generatedby IT is therealisationof relative advantages,and satisfactionwith the existing systemhasmuch to do with benefitssincethe greaterthe benefits,the higher the level ofsatisfaction.This may well be the reasonfor the insignificant impactsof thebenefitsspecifiedin ChauandTam (2000).2 AnotherexamplewasprovidedbyGrover(1993)in which hereferredto infrastructureasbeinghighly correlatedtohumanresourcesin IT.

2 The authorsdid not list the correlationbetweenvariablesnor discussthis issue.



Secondly,scholarshavepreviouslyapplieddiscriminate,traditionalor logisticregressionanalysis,which mayno longerbeappropriate.Thereasonis that thesestatisticalanalysesassumethe scaleof dependentvariablesas interval scales;however,scalesusedfor measurementin relevantstudies(e.g. the Likert scale)are,theoretically,ordinal scales.Previousstudies(suchasChauandTam,2000)tended to construct dependentvariables with factor scores,causing biasedestimation(Lostovickaand Thamodaran,1991). In addition, thesestudieshaveoften applied convenientor non-randomsampling methodswith researcherstendingto generalisethe results.

There have clearly beenmany variablesin previousstudies,but there wasinvariablyaconsiderablecorrelationbetweenthefactors,andit is consideredthatthe researchmethodsusedin thesestudieswere somewhatbiased.Hencethispaperwill try to simplify thefactorsandavoidtheinappropriateuseof statisticalanalysis.

3. RESEARCHMETHODOLOGY

a. ConceptualFramework

The adoption of e-commerceby firms essentially representsa form ofinvestment.According to investmentdecision theories, the main factors forconsiderationin investmentaretheperceivedbenefits,i.e., thebalanceof profitsand costs,and the perceivedrisks, i.e., the nature of firms and the externalenvironment.Thusthediscussionof firms’ adoptionof e-commercein this paperwill focus on three aspects, the benefits/costs,the organisation and theenvironment(seeFigure 1). This structureindicatesthat when a firm decidesto adopte-commerce,thedecisionwill bebasedupona cost/benefitanalysis,thefirm’s condition and the environment.Factorsinvolved in this processincludeperceivedbenefits,perceivedcosts,readiness,productvariety, exchangesafety,competitivepressureandconsumerdemand.

b. Factor Simplification

As Figure1 shows,the modelusedin this paperexcludessomeof the factorsmentioned earlier in the literature review, including innovative features,satisfactionwith the existing system,humanresourcesin IT, the unpredictablemarket,public policy and laws, whilst someof the variables,suchas productvariety, representadditions to the previous research.There are a number ofreasonsfor excludingcertainfactorsfrom the structure.For example,the reasonfor not consideringthe innovativefeaturesof e-commerceis that theadoptionofIT applicationsrepresentsinvestmentbehaviourby a firm, thus,issuesconsidered



are benefits and costs rather than innovation. Studieshave also shown thatinnovationhasvery little to do with thedecisionto adoptEDI, indeed,it is evenshownas insignificant. In addition, satisfactionwith the existing systemis notincludedin the modelsincethis is alsoclosely relatedto benefits.

The model includes organisational readinessinsteadof the availability ofhumanresourcesin IT, which indicatetheorganisation’slevelof readinessfor thenewapplications.Themoreresourcestherearein a firm, thebetterits applicationof e-commercewill be.The unpredictablemarketis the main sourceof externalpressure,including competition in the trade (Mansfield et al., 1977; andRobertsonandGatignon,1986)andthedemandsof thoseprocessingtransactions(Iacovou et al., 1995). Hence this paper investigatesonly the demandfor e-commerce,along with variablessuch as competition and consumerdemand,whenfirms areundercompetitivepressure.

This paperalso excludesseveralsubjectivefactors such as laws regardingtransactionson the Internetand the government’sincentiveschemes.Althoughthesefactorsmay well affect the decisionto introducee-commerce(RosenandHoward,2000;andBingi et al., 2000),suchimpactsdo not haveanysignificantimpacton theoutcomefor firms, sincetheylie at theheartof theexpansionof e-commercewithin the industry.The senseof insecuritycausedby inadequateorinsufficient lawsmayvary betweenbusinessowners,andthis canberevealedbymeasuringtheir perceptionof exchangesafety.

Onething which doesneedto beexplainedfurtheris thatsomefirms decidetoadopte-commercebecauseof greaterproductvariety.Variousproductswhichare

FIGURE 1ConceptualFramework



introducedto themarketthroughtheInternetnot only reducemarketbarriersbutalso producepotential economiesof scope(Nayyar and Kazanjian,1993; andBoeker and Huo, 1998). Firms with high product variety tend to differentiatethemselvesfrom their competitorsandusuallyactasinnovativeleaders.In otherwords,it is easyfor thesefirms to adopttechnicalinnovation(Miles andSnow,1978;andPorter,1980),hence,productvariety is includedwithin the model inthis paper.

4. HYPOTHESES

a. PerceivedBenefits

Since firms innovate in order to improve their businessperformance,differential profitability becomesone of the main factors in their decision-makingprocess(Mansfield,1968;Mansfieldetal., 1977;Davies,1979;andDosi,1988).Firmstendto improvetheir profits throughinnovationwith suchstandardobviouslybeing relative to the previoususer(of the old product).For instance,businessprofits increasewhen new equipmentis adopted,as comparedto theprofits generatedthroughtheuseof theold equipment.It is likely that firms willinnovate when they sensethat differential profitability is higher than theirexpectations. As the empirical studiesof O’Callaghanet al. (1992)andGroverandGoslar(1993)haveshown,the greaterthe benefitsperceivedby firms fromthe adoptionof IT, the more likely they will be to adoptsuchinnovation.

A numberof advantagesof e-commercearedescribedin theliterature,suchasquick andreal-timetransactions,thepromotionof efficiency in procurementandthe reduction of data collection or documentationcosts (Bingi, Mir andKhamalah, 2000; and Elango, 2000). E-commercemay even help firms tomanagetheir businessperformance(Kambil, 1997;andCappelandMyerscough,1997).However,there is a greaterlikelihood of firms adoptinge-commerceiftheythink thatsuchadoptionwill leadto higherprofits; conversely,therewill belesslikelihood of suchadoptionif it is perceivedthat e-commercewill makenodifference to a firm’s profits, as comparedto the continueduse of existingtransactionmedia(fax, telephone,postandexpressdelivery). Thuswe arrive atour first hypothesis:

H1: Firms with greaterperceivedbenefits from the implementationof e-commercearemore likely to pursueits adoption.

b. PerceivedCosts

Innovationmaygive riseto bothperceivedbenefitsandperceivedcosts(whichincludesboth initial andotherongoingcosts).For example,expenditureon the



implementation of new processeswill include equipment procurement,equipmenttesting and personneltraining. Generally, the higher the costs ofinnovation, then the slower the pace of innovation expansionis likely to be(Mansfield, 1968; and Davies, 1979). The costs of e-commerce includeinvestment in the process of its adoption (networks, PCs, data storage,demonstration, servers, software/hardware and other peripheral devices),organisational modification, training, managementand maintenance.Clearly,firms arelikely to be lesswilling to adopte-commerceif thecostsof investmentaretoo high. Hencewe haveour secondhypothesis:

H2: Firmswhichperceivehighercostsin theadoptionof e-commercearelesslikely to adopte-commerce.

c. Readiness

Organisationalreadinessreflects a firm’s technologicalcapabilities,or thelevel of use of innovative knowledgeand skills (Dosi, 1991); organisationswithout suchcapacitywill be lessableto adoptinnovationandthusdemonstratelower readiness.Firms with insufficient readinessmay incur higher initial costswhenimplementinginnovation.As Karlsson(1988and1991)pointsout, a lackof knowledgemayreducethespeedof distributionof IT applications.Henceboththeintroductionandimplementationof innovativesystemsaremucheasierwhengreaterknowledge,skills andresourcesareavailable(DewarandDutton,1986).In termsof e-commercespecifically, firms may needto acquirethe knowledgeandskills relatingto theInternetin orderto reducecostsandimproveefficiency.This discussionleadsto the third hypothesis:

H3: Firmsat a higherstateof readinessaremorelikely to adopte-commerce.

d. ProductVariety

Product variety illustrates the opportunitiestaken by firms to explore firm-specific assets in various markets (Markides, 1992; and Montgomery andWernerfelt,1988).The explorationof marketsfeaturinga variety of productsorserviceswill greatlyreducethecostof propertyusagewhilst generatingeconomiesof scope(NayyarandKazanjian,1993).In otherwords,whenenteringthe marketvia the Internet,a wider varietyof productsmaycontributeto economiesof scopewhilst alsoreducingmarketentry barriers.Firms with higherproductvariety candifferentiatethemselvesfrom their competitors,sotheywill find it easierto acceptinnovation (Miles and Snow, 1978; and Porter, 1980). The empirical study byBoekerandHuo(1998)alsosupportsthisview. E-commercerelatedfirms find thateconomicdevelopmentis morereadily facilitated if they canexploretheir marketthroughthe Internet in order to provide potentialcustomerswith more thorough



and wide-rangingproduct introductions.With their wide variety of products,itbecomesmore cost effective to exchangetransactioninformation and furtherexplorethe market.The fourth hypothesisis therefore:

H4: Firms with higherproductvariety aremorelikely to adopte-commerce.

e. ExchangeSafety

Internetsecurityhasbeenregardedasthekey to e-commercediffusion (Campand Sirbu, 1997; Elofson and Robinson,1998; and O’Keefe and McLachern,1998). In the environmentof e-commerce,information, tablesand documentsrelatedto commercialactivities are transmittedvia the Internetand WWW byelectronicform. Severalcriminal behavioursareharmfulto exchangesafety,suchas system intrusion, data stealing and tamper, and imposture. Since theenvironmentof transactionsis lesssecure,thecostswill begreater(Williamson,1987),hencea firm’s perceptionof exchangesafetywill influenceits decisiontoadopte-commerce.Our fifth hypothesisis therefore:

H5: Firms which perceivelower exchangesafety levels are less likely toadopte-commerce.

f. CompetitivePressure

External pressureservesas anotherimportant factor in firms’ decisionstoadoptinnovation,sincea firm hasto beinnovativein orderto competewith otherfirms within the same industry. Kimberly and Evansko (1981) argued thatcompetition between firms within the same industry is one of the majorenvironmental factorsinfluencingtheir decisionsto adoptinnovation.Thenotionthat competitivepressureforces firms to apply IT was assertedby PorterandMillar (1985)andsupportedby CohenandLevinthal (1989),which alsoshowedthat firms innovatein order to keepup with their competitors.

In orderto copewith thetrendtowardsincreasinglyfiercecompetitioncausedby thriving IT development, firms may use these applications to createopportunities and superiority (Thong and Yap, 1995). Kenney and Curry(1999) took Amazon as an exampleto demonstratethat the Internet providesfirst-mover advantages,with firms gaining the ability to put pressureon theircompetitorsthrougheconomiesof scale.McBridge (1997)alsonotedthat manyfirms turn to theInternetdueto competitivepressure.Changingcustomerdemandalsobringsexternalpressureto bearon firms sincethey invariablyaim to satisfycustomerdemandsin order to gain further orders.For example,domesticfirmsmay adopte-commerceto improve their supply chain managementin order toobtain OEM ordersfrom major internationalPC manufacturers.Thus our finaltwo hypothesesare:



H6: Firms facing greatercompetitivepressureare more likely to adopt e-commerce.

H7: Firms facing greaterrequirementpressureare more likely to adopt e-commerce.

5. MEASUREMENT

a. DependentVariable

The decisionto adopte-commerceis the dependentvariablein this model; inthe sameway asin previousstudies,the variableis definedasa firm’s decisionwhetheror not to adopte-commerce.The final decisionis representedby thenumbers‘1’ and ‘0’, with ‘1’ indicating that the firm hasdecidedto adopte-commerce(including thosewith adoptionin progress)whilst ‘0’ meansthat, atthe time of submittingthe data,the firm hadnot takenany decisionto adopte-commerce.

b. IndependentVariable

‘Perceived Benefits’ indicate that firms will expect (perceive) significantbenefits(suchasreducingtheir inventory levels,reactingpromptly to consumerdemandandstrengtheningrelationswith their businesspartners).Thefour levels(1–4), respectivelyindicate‘DisagreeEntirely’, ‘Disagree’, ‘Agree’ and ‘AgreeEntirely’ that adoptinge-commercewill leadto significantbenefits.

‘PerceivedCosts’evaluatea firm’s predictedcostsof adoptinge-commerce,including the costs of maintenance,management,recruitment, training andadjustmentsto theseprocedures.Four levelsarealsoappliedto this evaluation:‘DisagreeEntirely’, ‘Disagree’,‘Agree’ and‘AgreeEntirely’ thatvery largecostswill be involved in the adoptionof e-commerce.

‘Readiness’refersto a firm’s possessionof professionalknowledgeandskills.Basically,this is not an easyvariableto measure;whilst multiple indicatorscanbe appliedto the measurement,this alsohasmuchto do with the positioningoftheinformationdepartmentwithin thefirm (Iacovouet al., 1995).Thegreatertherecognitionof the information departmentwithin the firm, the more IT will bevaluedand implemented.Wherethe personin chargeof the unit is a companyexecutive,themanagementteamis morelikely to haveapositiveattitudetowardsIT andwill value greateraccessto resourcesrelatedto professionalknowledgeand skills (Thong and Yap, 1995). Usually, the higher the value of theinformation department,the greaterwill be the firm’s possessionof enhancedknowledgeandskills; it will alsobe easierfor the firm to adoptandimplementinnovation(DewarandDutton,1986).In orderto simplify theanalysis,this paper



refers to the recognitionof the information departmentas a proxy variable.3

Thereare four levels of measurement(1–4), representinga rangebetweenthedepartmentbelonging to a certain functional unit and being an independentprofessional unit.4

‘Product Variety’ representsthe level of variety of a firm’s products orservicesprovided for other firms within the sameindustry. The measurementscalecomprisesfour levels (1–4) indicating that the productsthat they offer toother firms are ‘Much Fewer’, ‘Fewer’, ‘More’ and ‘Much More’ than theircompetitors.

‘ExchangeSafety’ evaluatesfirms’ concernsover e-commercetransactions.Fourlevels(1–4)areusedasthescale,indicatingthata firm regardse-commercetransactions as ‘Very Insecure’, ‘Insecure’, ‘Secure’ or ‘Very Secure’.‘CompetitivePressure’is definedasthe level of competitionwithin the industry.The four levels(1–4)showthata firm perceivescompetitionwithin the industryas ‘Not At All Fierce’, ‘Not Fierce’, ‘Fierce’ and ‘Very Fierce.’ ‘RequirementPressure’is also estimatedin four levels (1–4), namely ‘Totally Insignificant’,‘Insignificant’, ‘Significant’ and‘Very Significant’.

c. SamplingDesign

The researchsubjectsof this papercomprisethe manufacturingand serviceindustriesin Taiwan. The samplingis basedon the Top 500 CorporationsinTaiwan (China Credit Information Service Ltd., 1999), including 2,239manufacturingfirms (1,909 large firms and 330 small and mediumfirms) and1,611 serviceproviders(excluding financing firms; 1,103 large firms and 508smallandmediumsizedfirms).5 It wasnecessaryto choosethispublicationasthebasisfor creatingan appropriatesamplingframesincethe generalpopulationistoo massive and hardly any clear list is available. Although the Top 500Corporationsin Taiwan is by definition, relatively limited, the findings of thisstudyarestill representativewhenassumingthatsmallfirms areunlikely to adopte-commercedueto resourceconstraints.

3 For more informationon usingproxy variables,seeMaddala(1991,pp. 461–66).4 After adoptinge-commerce,firms may upgradethepositioningof their informationdepartment,therefore‘readiness’may be theoreticallyconsideredasan endogenousvariable.For this reason,thequestionnaireaskedfirms aboutthepositioningof their informationdepartmentbothbeforeandafter the adoptionof e-commerce.In the empirical analysis,the datausedis the position of theinformation departmentprior to e-commerceadoption, hencereadinessdoes not representanendogenousvariable in the analysis.Our data also revealsthat almost all of the firms had notchangedthe positioningof their informationdepartmentsafter e-commerceadoption.5 Businessscalerefersto thenumberof employees.Accordingto theMOEA (Small andMediumEnterpriseAdministration,MOEA, 2000),theterm‘small andmediumenterprises’definesfirms ashavingfewer than200 employeesin the manufacturingindustry,or 50 employeesor fewer in theservicesector.Althoughthereareotherindicatorsof firms’ scale,i.e. salesandcapital,thenumberof employeesis generallyacceptedasthe major indicator.



Undera threeper cent limit of error and95 per centconfidence-interval, thesamplenumbershouldbeat least836 (Cochran,1977,pp. 75–76).Accordingtothe ratio of manufacturingfirms to servicefirms, 486 manufacturingfirms (414largefirms and72 smallandmediumfirms) and350serviceproviders(240largefirms and110smallandmediumfirms) shouldbesampled.Oncethenumberwasdecided,a mailing list of questionnaireswascreatedby meansof simplerandomsampling.

d. Data Collection

Data collection was basedon a questionnairewith the subsequentscaleofmeasurementcomprisingfour levels.In orderto avoid any ‘middle of the road’responses,noneutralpoint is providedin theoptions;however,thishasno impactuponthe reliability of the results(Churchill andPeters,1984).Sincethescaleofmeasurementis notassumedto beordinal,theCooil andRust(1995)methodwasapplied to the calculationof reliability in this paper,with the reliability levelshownto beover90 percentin all items.This suggeststhat thesequestionsmayfunction as indicatorsfor the researchfocus.

Thetargetedrecipientsweremanagersof informationunitswithin enterprises.One week after the questionnaires were dispatched,follow-up telephonecallsweremadeto requestthereturnof completedquestionnaires. In orderto promotetherecallrate,therecipientswereinformedthatall respondentswould receivethefinal report at a later date.Thosethat did respondreceiveda telephonecall tothankthemfor thereturnof theirquestionnaires.Thecallersalsocheckedthroughthe questionsand discussedany missingdatawith the respondentsin order tomakesurethat it wasin fact the managercompletingthe questionnaireandthatthe datawerecomplete.

e. TheModel

According to the conceptualframework outlined in Figure 1, the statisticalmodel in this papercanbe expressedas:6

y� �1PB� �2PC� �3RD� �4PV� �5ES� �6CP� �7RP

�� ÿ� �� ÿ� �� wherey� a firm’s decisionon the adoptionof e-commerce;PB � PerceivedBenefitsfrom theadoptionof e-commerce;PC� PerceivedCostsof adoptinge-commerce;RD� Readiness;PV� ProductVariety; ES� ExchangeSafety;

6 Sinceour modelwasdevelopedfrom theexistingliterature,it shouldhavegenerality,andshouldthereforebe applicableto the empiricalanalysesof otherdevelopingcountries.



CP� CompetitivePressure;RP� RequirementPressure.Parameters�� denotetheextentof the impactof eachexplanatoryvariable;�=ÿ in parenthesesrefersto the predicted influential tendencyof each explanatoryvariable; y is thedependentvariable,whilst the remainderare explanatoryvariables.It is worthnoting that the model does not include any interception parameterssinceinterceptionmakeslittle sensewhenthe scaleof measurementof all variablesisordinal (JoreskogandSorbom,1993).

Therewould, therefore,beobviousbiasif the resultswereanalysedby meansof traditionalregressionanalysis,irrespectiveof whetherthiswasestimatedvalueor standarderror(Maddala,1983,pp.160–62).It would evenbeinappropriatetoanalysethe resultswith logistic, probit or logit analyses,sincethe scaletype ofthe independent variableswould not matchthemodel.7 In theory,thecorrelation(correlationmatrix) betweenordinal scalesshouldbe the polychloric correlationcoefficient rather than a product-moment correlation (Olsson, 1979).Accordingly, this paper follows the suggestionsof Joreskog and Sorbom(1993)by undertakingtransformationof thescaleprior to estimation.Themethodof estimationusedis weightedleastsquare(WLS), for two reasons;first of all, itis unaffectedby the data distribution hypothesis,and secondly,the estimatedresult is asymptotically efficient, as comparedwith other methods(Browne,1984).

6. ANALYSIS AND DISCUSSION

a. Analysis

A total of 241questionnaires werecollected,which represented29 percentofthe targetsamples.Amongstmanufacturingfirms, largefirms returneda total of61 questionnaires(25.3percentof thesamplesreceived)andsmall andmediumfirms returned56 questionnaires (23.24percentof the samplesreceived).In theserviceindustry, 46 questionnaireswere receivedfrom large firms (19.09 percent)and78 from small andmediumfirms (32.37per cent).In a comparisonofthe total numberof questionnairescollected,the majority camefrom small andmediumenterprises(55.60percent).A possiblereasonmaybethat it waseasierto track down managersof informationunits in small andmediumfirms.

It wasfound that 30 per centof the firms hadadoptede-commerce,of which69percentwerelargefirms, aproportionwhichwasconsiderably higherthanthesmall and mediumfirms adoptinge-commerce�p< 0:05�. Of all firms which

7 As mentionedin the literaturereview, the Likert scaleis often regardedasan interval scaleinempirical researchso the logistic (logit) analysisis applied to statistics.However, in researchmethodology,the Likert scaletendsto be viewedasan ordinal scale(seeChurchill, 1995,p. 474;andZikmund, 1991,p. 275).



hadnot adoptede-commerce,the proportionof small andmediumfirms was61per cent,muchhigher than that of large firms � p< 0:05�. This result indicatesthat large firms in Taiwan are more likely to adopt e-commerceand hencesupportsthe argumentthat since they have adequatetechnical personnelandfinancial resources,large firms are likely to be the first to apply IT innovation(Raymond, 1985; Grover and Goslar, 1993; and Thong and Yap, 1995).Comparingthe ratio of all firms adoptinge-commerce,the numberof serviceproviderswas similar to that of manufacturers,there was also no significantdifference betweenthe service and manufacturingsectorsin terms of scale�p> 0:05�. This indicates that in comparison to developed countries, e-commerceis not yet so popular in Taiwan. It shouldalso be noted that thosefirms which had adoptede-commercemight be more willing to completethequestionnaire thanthosethathadnot, thusit couldbethat lessthan30 percentofdomesticfirms havein fact adoptede-commerce.

Table 1 showsthe estimatedpolychloric correlationcoefficient betweenthevariablesof thecollectedsamples.Thecorrelationbetweeneachindependentanddependentvariables indicates that product variety, perceived benefits andreadinessare,to a greaterextent,correlatedto e-commerce.

Next, theparametersin themodelwereestimatedby WLS, with theestimationrejecting the null hypothesis,namely, at least one parameterwas not zero��2 � 74:71; df � 7; p< 0:05�. In otherwords,thereweresomevariableswitha significantimpacton the firms’ decisionto adopte-commerce.In termsof co-alignmentvalue,R2 � 0:38, which showsthat the estimationmodelhascertainexplanatorypowerasfar ascross-sectionestimationis concerned.8 SeeTable2for the estimationof parametersin the model.

TABLE 1PolychloricCorrelationBetweenVariables

Variable y PV CP RP PB PC ES RD

y 1.00PV 0.33 1.00CP 0.20 0.37 1.00RP 0.10 0.10 0.05 1.00PB 0.39 0.09 0.09 0.03 1.00PC ÿ0.25 ÿ0.08 0.11 0.16 ÿ0.43 1.00ES ÿ0.25 0.00 0.29 0.17 ÿ0.09 0.33 1.00RD 0.33 0.09 ÿ0.05 0.18 0.07 0.01 ÿ0.04 1.00

Notes:y� a firm’s decisionon theadoptionof e-commerce;PV� ProductVariety;CP� CompetitivePressure;RP�Requirement Pressure;PB � PerceivedBenefits; PC � Perceived Costs of adopting e-commerce;ES �ExchangeSafety;RD � Readiness.

8 An empirical model of cross-sectiondata is regardedas having explanatorypower whenR2 > 0:25, especiallyin ordinal scaletypes.



As Table2 shows,thesignsof parameterestimationwereasexpected,but notall estimatesreachedthe level of significance(five percent,one-tailedtest).Thenull hypothesiswasnot rejectedby the testof �2 and�7, therefore,theresultsoftheempiricaldataanalysissupportedH1, H3, H4, H5 andH6, whilst rejectingH2

and H7. Overall, the results revealeda significant correlation betweenfirms’decisionsto adopte-commerceand factorssuchas the perceivedbenefitsfromthe adoptionof e-commerce�t � 2:53; p< 0:01�, a firm’s readiness�t � 3:39;p< 0:01�, productvariety �t � 2:04; p< 0:05�, the extentof exchangesafety�t � ÿ2:18; p< 0:01� and competitive pressure �t � 1:70; p< 0:05�. Theresultsalsosuggestthat thecostsinvolved in adoptinge-commerceandpressurefrom consumerdemandwould not have any significant impact �t � ÿ0:65;p> 0:05; t � 0:66; p> 0:05�.

Thescaleof firms tendsto be relevantto thequantityof technicalknowledgeresourcesor slack resources(Rosner,1968; and Dewar and Dutton, 1986).Previousstudieshavesuggestedthat large firms are able to afford the variouscosts involved in innovation (including the risk of failure) since there aregenerally more resourcesavailable to them (Dosi, 1991; Grover and Goslar,1993; Iacovouet al., 1995;ThongandYap, 1995;andBoekerandHuo, 1998).That is, the cost factor may indeedhavea muchsmaller impact on large firmsthanon small andmediumenterprises.

TornatzkyandKlein (1981)identified two issuesrelatingto scale.On theonehand,scalemay interferewith the correlationbetweencompetitivepressureandthe adoptionof innovation,whilst on the other hand,small and mediumfirmsmay tend to apply new technology to differentiate themselvesfrom theircompetitorssincethey are undergreatercompetitivepressurethan large firms.Thuscompetitivepressuremayhaveagreaterimpactonsmallerfirms thanlargerones.

Consequently,scaleis oftenusedasa moderatorin theanalysisof differencesin firms’ decisionsto innovate(Damanpour,1989 and 1991).The estimatesin

TABLE 2Resultsof Model Estimation(WLS)

Variable (Parameter) Estimate

PB��1� 0.28 (0.11)**PC��2� ÿ0.08 (0.12)RD��3� 0.28 (0.08)**PV��4� 0.20 (0.10)**ES��5� ÿ0.23 (0.10)**CP��6� 0.19 (0.11)*RP��7� 0.06 (0.09)

Notes:�2 � 74:71; df � 7; R2 � 0:38; �� p< 0:01; � � p< 0:05, one-tailed test; the value in parenthesesin thefield named‘Estimate’ is standarderror; the meaningof variablessignsis the sameasabove.



Table2, however,maycausesomedegreeof confusion,sincethisstudycollectedsamplesfrom organisationsof variousscales.The estimationexplainedearliermay leadto discrepancyin the resultsby ignoring the interactioneffect betweenthe scaleandothervariables.Hence,differencesbetweenlargefirms andsmall/mediumfirms, in termsof the impact from the adoptionof e-commerce,weretestedwithin thesamemodel.At a significancelevel of five percent,the resultsshowedthat there was no significant interaction betweenthe scaleand othervariables ��2 � 4:23; df � 7; p> 0:05�, which indicates that there were nosignificantdifferencesbetweenlarge firms andsmall/mediumfirms in termsofthefactorsinvolvedin theadoptionof e-commerce.Therefore,therewould seemto be no point in displayingthe estimatesin Table2 with thescaleof individualfirms.

b. Discussion

This sectiongoeson to discusstheestimationresults.First of all, the fact thatthetestof �2 failed to rejectthenull hypothesisindicatesthatthebenefitsbroughtaboutby e-commercemay count for morethanthe costsin a firm’s decisiontoadopte-commerce.As Table1 showed,however,PB washighly correlatedwithPC �rp � ÿ0:43; t � ÿ5:46; p< 0:01� so this resultmay be an illusion. When�1� �2 > 0 (the alternativehypothesis)was tested,the resultsalso failed torejectthenull hypothesis��2 � 1:08; df � 1; p> 0:05�, whichmeansthatthesetwo elementscouldbeequal.Whentheyweresetasequal,theestimationshowedthat a firm’s decisionto adopte-commercewasaffectedby both the perceivedbenefitsandthecosts�t � ÿ3:39; p< 0:01�. Thustheresultsshouldsupportthesecondhypothesis.

Secondly, the empirical results showed that customer demand had nosignificant impact on a firm’s decision,since the majority of firms (>90 percent)did not recogniseanypressurestemmingfrom customerdemand.Managersinterviewedsaid that they would considercustomers’needs,but they did notregardsuchneedsasa leadingfactor.This resultmaybe affectedby the typeofindustry since domestic information, telecommunications and semiconductorfirms aremore likely to adopte-commercein order to gain moreOEM orders,improve their supply chain and deal with the demandfrom major internationalenterprises(Wang et al., 2000: 31). When treating the type of industry as aninterference indicator, for the purpose of recalculating the results (withinformation, telecommunications andsemiconductorsasonegroup), the resultsstill failed to reject the null hypothesis.Therefore,the type of industry had noeffect on the empirical results; treating the servicesectoras anothertype ofindustryalsohadno impacton the findings.

Thirdly, the results showed that firms with greater recognition of theirinformationunitsweremorelikely to adopte-commercewhenthepositioningof



informationunits wassetasthe readinessindicator.9 The higherthe positioningof the information unit, the more the firm would tend to focus on informationmanagement.Thesefirms also had betterknowledgeand skills, and sincetheyhada higherstateof readiness,wereperhapsmorelikely to applyIT at anearlierstage,which supportsthe argumentof Iacovou et al. (1995). The resultsalsomeanthatthepositioningof informationunitsservesnot only asa usefulvariableof businessfeatures,indicating whetheror not a firm will decideto adopt e-commerce,but alsoasa goodindicatorof readiness.

Fourthly, similar to Damanpour’s (1991) findings on the adoption oforganisational innovation,firm scaledid not causesignificantinterference,sincescalemay havean impact on other variables.For example,larger firms haveahigher recognition of their information units with rich technical resources(Raymond,1985;MeyerandGoes,1988;andGroverandGoslar,1993).Hence,thereis a greaterlikelihood of thesefirms beingreadyto adopte-commerce.Itcannotbedeniedthat insignificantinterferencemaycomefrom thedifferenceinmethodsof scalemeasurement,asno empirically significantimpactof scalewasdetectedby BoekerandHuo (1998),who setout with the intentionof measuringbusinessscalewith log.

Finally, whilst firms have easy access to the e-commercemarket forinformation and customers,there are potential exchangerisks. The resultsofthis studyshowthatconcernsoverexchangeriskshada definite impact,in termsof reducingthepotentialnumberof firms adoptinge-commerce.Thecorrelationbetweenexchangerisksandthedevelopmentof e-commercesupportsthenotionsof Bhimani (1996)andCampandSirbu (1997).

7. CONCLUSIONS

This paper has establishedan empirical model to look at organisationaladoption of e-commerce.The model, which examines cost-effectiveness,organisationand pressurecausedby the externalenvironment,revealsthat thedecision to adopt e-commerceis a kind of investment,in which both cost-effectivenessandrisks (environmental andorganisational factors)areevaluated.A numberof factorsinvolved in a firm’s decisionto adopte-commercearealsodiscussed,suchasperceivedcosts,perceivedbenefits,readiness,productvariety,exchangerisk, competitivepressureandcustomerdemand.

9 On oneoccasion,we usedthe numberof IT personnelasan alternativeindicator,but the resultwas still significant, showingthat sucha changedid not affect the findings. The reasonfor thepositivecorrelationbetweenthesetwo variableslies in thefact thatfirms with higherrecognitionoftheir informationdepartmentfocusmoreon collectingandusinginformation,therefore,they hiremoreIT personnelto assurethe quality of information.



With no settingof scaletype asinterval or normaldistribution,the resultsofthe model estimationshow that perceivedcosts,perceivedbenefits,readiness,product variety, exchangesafety and competitive pressurehave a significantimpact on the decision to adopt e-commerce.10 In other words, thesefactorsfunction as variablesin the decision-makingprocess.Since firms regard theadoptionof e-commerceas an economicinvestment,their concernsover thebenefitsand costsbroughtaboutby their decisionsare indeedsignificant. Thestudyalsoshowsthat firms with higherreadinesstakefewer risksandthat thosewith greaterproductvariety can reapgreaterrewardsin termsof economiesofscope,thus they are more likely to adopt e-commerce.In addition, the moreintensethe industrialcompetition,the morerapid will be the developmentof e-commerce.Thegovernmenthasalsohelpedin thedevelopmentof e-commerceinTaiwanthroughthe establishmentof appropriatelaws andregulations.

Althoughtherehasneverbeenanyempiricalstudyconcerningproductvarietyandexchangesafety,the findings in this papersupportthe resultsof Premkumaret al. (1994), the casestudy of Iacovouet al. (1995), and many of the TP/NPviewsofferedby ChauandTam (2000).The resultsof this studyalsoshowthatthesignificanceof thevariablesdoesnot vary in accordancewith businessscaleor the type of industry (manufacturing/service). There have been very fewempirical studiesof factorsin a firm’s decisionto adopte-commercesincethepreviousscholarlyeffort hastendedto focus on EDI. Throughthe review of anumberof theoreticalissues,this paperservesas the first attempt to conductempirical study of the adoption of e-commercein Taiwan. It contributesconsiderably to this areaof researchby providing a well-developedempiricalstructure and proper analytical methods.Nevertheless,there is no stratifiedsamplingof industriesundertakenin this paper,sotheresultsdo not provideanyfurther information concerninge-commercedevelopmentin various industries,how quickly it develops,or the differencein thecorrelationbetweenfactorsandtheir impact on adoptinge-commercefrom one sectorto another.All of theseissuesareworthy of further investigation.

10 The Electronic BusinessWhite Paper (2001), ranks Singapore,Hong Kong, South Korea,Taiwan and Japanas the leading group in Asia, in terms of e-readiness,whilst Thailand, thePhilippines,China,IndonesiaandIndia arefollowers in e-commercedevelopment,evenwith theirhugepotentialmarket,becauseof their level of povertyandlower educationallevels.Obviously,e-commerceadoptionis moreor lesslinked to nationalcompetitiveness.Most of the resultsin thispaperareconsistentwith the findings in theUSA, althoughTaiwanis far behindtheUSA in termsof e-commerceadoption.Therefore,our resultsshouldbeapplicableto othercountriesin which e-commerceadoptionis lower than in Taiwan if thosecountriescanimprove their infrastructuretofacilitate e-commerceapplication.Therefore,e-commercefollower countriesneedto strengthentheir information and communication infrastructure and improve their education levels. E-commercecan then serveas a greatequaliserfor them to subsequentlycatchup with the moreadvancedcountries.



APPENDIX

Questionnaire

I Basic data1. How manyemployeesare therein your company?

ú lessthan100 ú 101–200 ú over 2002. Hasyour companyalreadyadoptedelectroniccommerce?

ú Yes ú No3. How is theinformationunit positionedin yourcompany?Pleasecircle one

from the diagrambelow.

4. What type of electroniccommercehas your companyadopted?(if notadopted,pleaseskip the question)ú B2B ú B2C ú both



II Pleaseindicate your agreement or disagreement with the followingstatementsaccording to the current conditions within your company:

Strongly Disagree Agree StronglyDisagree Agree

1 As a direct resultof the adoptionof ú ú ú úe-commerce,my companyhasreceivedsubstantialgains(for instance,a reductionin paperwork,the facilitation of purchasingefficiency, instantresponseto customerneeds,etc.)

2 My companyhasspentsubstantialamounts ú ú ú úof moneyon e-commerceadoption(forinstance,investmentin hardwareandsoftware,maintenancecosts,manpowertraining costs,etc.)

3 Dataandmaterialsare likely to be stolen, ú ú ú úsabotaged,disclosed,tamperedwith, etc.,if a companyusese-commerceto carryout businesstransactions

4 As comparedto othercompetitorsin the ú ú ú úsameindustry,my companyproducesavery diversevariety of products

5 The marketcompetitionfor my company ú ú ú úis extremelyfierce

6 My company’sclientshaverequestedthe ú ú ú úcompanyto adopte-commerce

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Factors in Taiwanese Firms' Decisions to Adopt Electronic Commerce: An Empirical Study

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