Global Technology, Local Adoption: A Cross-Country Investigation of Internet Adoption by Companies...

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A b s t r a c t

To gain a better understanding of the globaldiffusion of e-business among organizationsin developed and developing countries andto investigate the relationships amonge-business contexts, economic environment,and organizational adoption, we conducteda firm-level survey in two countries — theUnited States and China — and tested aresearch framework built upon the techno-logy-organization-environment framework.Empirical data from 262 US firms and 175Chinese firms provided evidence about theextent of organizational adoption of e-business. Major findings include: 1) Chinesefirms lag in using e-business-related tech-nologies, especially interorganizational tech-nologies; 2) US firms make more extensiveuse of the Internet; and 3) governmentregulation plays a more important role inChina than in the US. Moreover, using struc-tural equation modelling, we further teasedout four adoption facilitators in general —technology competence, enterprise integra-tion, competition intensity, and regulatoryenvironment. These factors played differentroles in different economic environments.The paper concludes with a discussion of themajor results and implications.

Keyword: Internet, electronic business,adoption, innovation diffusion, global envi-ronment, cross-country study, technology-organization-environment framework

A u t h o r s

Sean Xu([email protected]) is a doctoralstudent of Information Systems in theGraduate School of Management at theUniversity of California, Irvine.His research focuses on e-businessadoption/diffusion in a globalenvironment and the business value ofIT and e-business.Kevin Zhu([email protected]) received his PhD fromStanford University and is currently anAssistant Professor of InformationSystems in the Graduate School ofManagement at the University ofCalifornia, Irvine. His research focuseson e-business, global electronic markets,strategic IT investments, andeconomic/organizational impacts of IT.Jennifer L. Gibbs([email protected]) is Senior ResearchFellow at the Center for Research onInformation Technology andOrganizations (CRITO), at theUniversity of California, Irvine. Herresearch focuses on social impacts ofinformation technology in globalteams and organizations. She is currentlyresearching global e-commercediffusion across numerous countries.

Global Technology, Local Adoption:A Cross-Country Investigation of InternetAdoption by Companies in the United Statesand China

SEAN XU, KEVIN ZHU, AND JENNIFER GIBBS

INTRODUCTION

Electronic business (e-business orEB, defined as business activities con-ducted over the Internet) has beenone of the most remarkable infor-mation technology (IT) innovationsin the last decade. Despite the burstof the dot.com bubble, many com-panies, e.g., Cisco, Wal-Mart, andCapital One, continue to deploye-business extensively in their enter-prise value chains (Clemons and Hitt2001; Kraemer and Dedrick 2002).Yet, with respect to the academicresearch, several gaps can be iden-tified. First, firms face a series ofobstacles in adopting e-business,particularly their ability to transcendsignificant technical, managerial, andcultural issues (IBM 2001; Sato etal 2001). Puzzled by the mixed evi-dence, researchers and practitionersare calling for studies investigatingcontexts for e-business adoption.However, the e-business researchlacks reliable empirical data that arebased on large-scale surveys andcan show how contextual factors mayshape e-business adoption.

Second, as shown by recentcountry-level statistics, e-businessis spreading quickly in developingcountries (UNCTAD 2002). Much

14 Sean Xu, Kevin Zhu and Jennifer Gibbs � Global E-Business Adoption

of the previous research, however, focused on companiesin developed countries, predominantly in the UnitedStates. To the best of our knowledge, no cross-countrystudies have been conducted based on firm-level datafrom multiple countries. As a result, this area is lacking anoverall view of the global diffusion of e-business amongorganizations. We believe that it is valuable to add aninternational dimension to the study of e-business, com-paring e-business adoption in developed and developingcountries.

Third, although e-business usage has been conceptual-ized as a complex procedure with potential applicationsin various value-chain processes (Kauffman and Walden2000), much of the existing research on e-business adop-tion has been restricted to a dichotomous measure of‘adoption vs. non-adoption’. Although this is helpful tounderstand adoption decisions, such a restrictive viewdoes not completely capture the reach and richness of theuse of IT innovations (Tornatzky and Klein 1982). Thus,it is important to move forward to studying the extentof e-business adoption, rather than yes-or-no adoptiondecisions.

This study attempts to fill in these gaps. We seek to:

1 investigate the extent of organizational adoption ofe-business;

2 study the relationships between e-business adoptionand contextual factors; and

3 examine how these relationships vary across differenteconomic environments (developed vs. developingcountries).

The Internet is a technology with global reach; theWWW has no national boundaries. Yet, its adoption inorganizations may be shaped by various local factorsassociated with the organization and its environment.

To understand these issues better, we conducted alarge-scale survey in a developed country and a develop-ing country. We choose the United States, the largestdeveloped economy, as a representative of developedcountries, and China, the largest developing economy,as a representative of developing countries. These twocountries have obviously distinct contexts for e-business,including economic development levels, national envi-ronment, and IT infrastructure. Compared to the UnitedStates, China seems to lag behind in using informationtechnologies, especially the Internet. However, Chinamay catch up relatively quickly, since China has been ableto take advantage of newer technologies. On the otherhand, we expected that the lack of regulation support(e.g., supportive business laws and legal protection ofInternet commerce) might retard e-business diffusion inChina. Moreover, China is undergoing a transformationfrom a planned economy to a market-oriented economy,while the United States has relatively mature markets anda supportive institutional environment. These differenteconomic and national environments may lead to

different adoption patterns. These expectations soundtheoretically plausible, but we wish to empirically testthem by using survey data. The next section describes thetheoretical background, followed by our research frame-work, the survey, and the results. The paper concludeswith a discussion of the major results and implications.

THEORETICAL BACKGROUND

Although showing recent signs of advancement, thee-business adoption/diffusion literature still seems frag-mented. A major reason is the lack of an overarchingframework to unify various factors that may affecte-business adoption. In response to this problem, wereviewed the existing e-business literature, as well as priorstudies of IT implementation and innovation diffusion.We found that the technology-organization-environment(TOE) framework developed by Tornatzky and Fleischer(1990) was comprehensive for identifying factors shapinginnovation adoption, and could serve as a conceptualguideline for our research.

The TOE framework posits three aspects of anorganization’s context that influence the process bywhich it adopts and implements a technological innova-tion: technological context, organizational context, andenvironmental context. Technological context describesboth the internal and external technologies relevant tothe firm. These include existing technologies inside thefirm, as well as the pool of available technologies in themarket. Organizational context is defined in terms ofseveral descriptive measures: firm size and scope; the cen-tralization, formalization, and complexity of its manage-rial structure; the quality of its human resources; andthe amount of slack resources available internally. Envi-ronmental context is the arena in which a firm conducts itsbusiness — its industry, competitors, access to resourcessupplied by others, and dealings with government(Tornatzky and Fleischer 1990: 152–4).

The TOE framework has been examined by a numberof empirical studies on various information systems (IS)innovations (for a literature review of empirical supportfor the TOE framework, see Zhu et al 2003). FollowingTornatzky and Fleischer (1990), Iacovou et al (1995)developed a model formulating three aspects of EDIadoption — technological factors, organizational factors,and environmental factors — as the main drivers forEDI adoption, and examined the model using sevencase studies. Their model was further tested by otherresearchers using larger samples (e.g., Kuan and Chau2001). These studies demonstrated the usefulness of theTOE framework for identifying facilitators and inhibitorsof e-business adoption. Since the TOE framework hasa solid theoretical basis and consistent empirical support(e.g., Chau and Tam 1997; Iacovou et al 1995; Zhu etal 2003), we adopted it as our theoretical background.Yet, as a significant differentiation from prior research,

15Electronic Markets Vol. 14 No 1

this study focuses on the extent of e-business adoption —the degree to which organizations have migratedvarious value-chain processes onto the Internet platform(i.e., using Internet technology in combination withexisting information technologies) — rather than thedichotomous adoption decisions.

Within the environmental context of the TOEframework, we wanted to understand how nationalenvironments might shape adoption patterns. A nationalenvironment embeds many environmental factors(e.g., economic, legal, cultural, business and consumermarkets) that may influence IT diffusion. In the litera-ture, several environmentally imposed obstacles thatmanagers face in implementing information technologiesin less developed countries were identified, including ascarcity of managerial, technical, and financial resourcesat the firm level (Dasgupta et al 1999); the inadequacyof basic infrastructure at the national level (Dewan andKraemer 2000; UNCTAD 2002); and other institutionalfactors such as culture and politics (Jarvenpaa andLeidner 1998; Kshetri and Dholakia 2002). Yet, theexisting literature lacks reliable empirical evidence basedon large-scale surveys. Thus, we incorporated an inter-national dimension into the environmental context ofthe TOE framework, and sought to demonstrate varyingadoption patterns across developed and developingcountries, hence examining the role of local factors in theadoption of a global technology.

RESEARCH FRAMEWORK

Drawing upon the technology-organization-environ-ment framework, we developed a conceptual framework,as shown in Figure 1, that incorporates six TOE factors

affecting the extent of e-business adoption: technologycompetence; firm size; global scope; enterprise integra-tion; competition intensity; and regulatory environment.This framework is applied to both the United States andChina. Key elements of this framework are discussedbelow.

E-business adoption

As we pointed out earlier, it seems helpful to extend theyes-or-no adoption decisions to the extent of e-businessadoption (Chin and Marcolin 2001; Tornatzky andKlein 1982). We measure two aspects of the extent ofe-business adoption: breadth and depth. Breadth refersto the reach of e-business along the value chain, i.e.,whether the various value-chain activities (e.g., sales,service, coordination, and procurement) have beenmoved to the Internet. Depth refers to the percentage of asingle value-chain activity that has been migrated ontothe Internet platform. Together, breadth and depthallow us to gain a deeper understanding of the extent ofe-business usage in organizations.

Technology competence

Drawing upon previous studies (Kwon and Zmud 1989),we posit technology competence as an enabler or facili-tator for e-business adoption. Technology competencerefers to the use of e-business-related technologies, suchas website, electronic data interchange (EDI), and elec-tronic fund transfer (EFT). These technologies con-stitute a platform on which e-business can be built;the experience of using EDI may facilitate e-business

Figure 1. Research framework


implementation. Therefore, firms with greater technol-ogy competence tend to enjoy greater readiness to adopte-business (Zhu 2003). Compared to US firms, Chinesefirms lack technological resources and prior experiencewith related technologies such as EDI (UNCTAD2002). Thus, we expect that, at the current stage, acquir-ing e-business-related technologies would be a morecritical determinant of e-business adoption in China thanin the United States.

Firm size

Firm size, defined as the number of employees in thewhole organization, is one of the most commonly stud-ied factors in the innovation literature (see Damanpour(1992) for a meta-analysis). Yet, different opinions existas to the role that firm size plays in the process of innova-tion adoption. On the one hand, large firms often possessmore slack resources that can facilitate innovation adop-tion — the so-called resource advantages (Schumpeter1950). On the other hand, large firms tend to be lessagile than small firms. The greater structural inertia asso-ciated with large firms may entail more effort and costsfor innovation implementation (Nohria and Gulati1996). Thus, our study considers the influence of firmsize on e-business adoption as a mix of resource advan-tages and structural inertia, but expects that resourceadvantages would be more significant for firms in China,as firms in developing countries often face a scarcity ofmanagerial, technical, and financial resources (Dasguptaet al 1999).

Global scope

The influence of global scope (i.e., global expansion)on e-business adoption also involves different opinions.First, firms with greater scope tend to have more incen-tives to adopt e-business, which could be explained froma transaction costs perspective. In general, companiesface a steep rise in transaction costs when they expandinto heterogeneous markets (Gurbaxani and Whang1991). Since e-business may help reduce transactioncosts including search costs, communication costs,contractual costs, and monitoring costs (Garicano andKaplan 2001; Malone et al 1987), firms with greaterglobal scope may have stronger incentives to make use ofe-business.

Second, complexity in implementing e-business mayincrease with global scope (Duncan 1976). That is,greater global scope incurs more effort, in the implemen-tation process, for coordination among establishmentsscattered in different regions. In addition, firms operat-ing in different countries face different cultural, regula-tory and national environments, a barrier for formingan integrated e-business system working across country

boundaries. We expect that this issue is more pro-nounced for Chinese firms, since China, to some extent,has a different economic and regulatory environmentthan most Western countries, which may increase costsfor Chinese firms to achieve higher levels of e-businessadoption in establishments in China and abroad.

Enterprise integration

It is difficult for innovators to pursue sustained businessvalue by investing in information technologies per se, ascompetitors may appropriate value by imitation (Barney1991). As a result, technologies may become necessities,rather than value creators (Clemons and Row 1991).E-business adopters should pay particular attention tothis issue, as many e-business activities are visible onthe Internet and the wide connectivity of the Internetin itself accelerates information and resource mobility.Thus, e-business adopters need to commit to ‘deepusage’ of the Internet technologies (Chin and Marcolin2001).

A key strategy of ‘deep usage’ is to integrate separatedatabases and heterogeneous information systems toimprove responsiveness and reduce incompatibilityamong IS applications (Zhu and Kraemer 2002). Thiscan help unleash the hidden value of complementaryresources (Zhu 2003). Although the individual com-ponents that go into the e-business platform arecommodity-like, the process of integrating the com-ponents to develop a coherent e-business system tailoredto a firm’s strategic context is complex and imperfectlyunderstood (Zhu and Kraemer 2002). Thus, enterpriseintegration — defined as the extent to which separatedatabases and technologies are connected within andbeyond firm boundaries — can hardly be imitated bycompetitors and thereby has the potential to createsignificant e-business value, thus driving continued usageof e-business in organizations (Zhu, 2003). Thus, wehypothesize a positive association between enterpriseintegration and the extent of e-business adoption.

Competition intensity

Competition intensity refers to the degree that the com-pany is affected by competitors. Porter and Millar (1985)analysed the strategic rationale underlying the relation-ship between competition intensity and IS innovations.They suggested that, by adopting IS, firms might be ableto alter the relative positions of competition, affect theindustry structure, and leverage new ways to outperformrivals, thus changing the competitive landscape (Zhu2002). Therefore, firms facing a greater degree of com-petition intensity may face more pressure to adopt, andtend to achieve higher levels of adoption. We apply thisargument to the Internet domain, and expect a positive


association between competition intensity and e-businessusage.

Regulatory environment

Within the TOE framework, regulatory environment hasbeen recognized as a critical environmental factor affect-ing innovation adoption (Kraemer et al 2002; Kshetriand Dholakia 2002). Governments could encouragee-business adoption by institutionalizing supportivebusiness and tax laws to facilitate e-business adoption,and regulating the Internet to make it a trustworthy busi-ness platform (e.g., dealing with fraud and credit cardmisuse). Although regulatory support is important forboth developed and developing countries, we expect thatit has more significant influence in a developing countrysuch as China given the relatively immature markets andmore frequent government interventions.

RESEARCH METHODOLOGY

Drawing upon the theoretical framework discussedabove, we designed a questionnaire and refined it viaseveral runs of pretests and revisions. Each of the itemson the questionnaire was reviewed by an expert panel forits content, scope, and purpose (content validity). Afterthe questionnaire was finalized, the survey was executedby a professional survey firm that specializes in large-scalesurvey research and has accumulated considerableexperience and a well-connected network of corporateexecutives.

The survey was conducted in the United States andChina. The United States is the worldwide leader ine-business applications and has mature markets and rela-tively comprehensive e-business legislation (Kraemer et al2002). China is a rising producer of computer hardware,but it has been slow to use information technology. NowChina is encouraging local firms to use IT innovationsto strengthen their global ties to firms in advancedcountries, and to restructure their organizations to bemore competitive in the global market, partly drivenby China’s entry into the World Trade Organization(WTO). E-business is one of these IT innovations thathave been enthusiastically promoted. Our study attemptsto examine how Chinese firms are faring, using theUnited States as a benchmark.

The survey was conducted at the establishment level(physical location or site) during the period February toApril 2002. The sampling was a stratified random sampleby size, with sites selected randomly within each size cell.The survey covered three major industry sectors includ-ing manufacturing, retail/wholesale distribution, andfinancial services. The sampling frame was obtained froma list source representative of the entire local market.1

Our final dataset contains 175 Chinese firms and 262 US

firms.2 Distribution of firm size measured by employeenumber reflects a balance of large and small businesses.Most respondents are CIOs, CEOs and IS managersor directors, which suggests a good quality data source.We also examined non-response bias and no statisticallysignificant differences were found in terms of revenueand firm size.

Then, using the survey data, we conducted a two-stepanalysis. First, to understand the status of e-businessdiffusion and the nature of e-business contexts in theUnited States and in China, we compared key variablesin our research framework in the two countries (calledthe ‘US–China comparison’ in the rest of this paper).Second, we utilized structural equation modelling(SEM) to test relationships between e-business adoptionand contextual factors. SEM serves as a complementarytest for the robustness of the results obtained at thefirst step, while findings from the US–China comparisonhelp to explain SEM results. Thus, combined together,the cross-sample comparisons and SEM enable us tocross check our conclusions about the relationshipsamong economic environment, e-business contexts, andorganizational adoption.

SURVEY RESULTS: THE US–CHINA COMPARISON

As shown in the research framework in Figure 1,our survey investigated the extent of organizationaladoption of e-business and influential factors within thetechnology-organization-environment contexts. We listsummary statistics of these variables in Tables 1 to 5. Togain a better understanding of these items, we comparedtheir mean values across the two samples. For thesecomparisons, ANOVA (t-statistic reported), x2 test, or

Table 1. Technology competence: US–China comparison

US China Comparison

Use of e-business technologies% of firms using email 99.6 97.7 x2 = 1.89% of firms having a website 86.2 73.6 x2 = 10.91***% of firms using an intranet 65.6 69.5 x2 = 0.72% of firms using an extranet 38.1 42.8 x2 = 0.96% of firms using EDI 53.8 30.2 x2 = 22.07***% of firms using EFT 67.5 37.2 x2 = 36.01***% of firms using a call centre 54.8 31.8 x2 = 22.18***IT professionals, as % of totalemployeesSmall establishment 5.23 9.20 t = 2.99***(≤ 500 employees)Large establishment 6.19 1.88 t = 2.70**(> 500 employees)

***p < 0.01; **p < 0.05; *p < 0.10


Mann-Whitney U-test (Z-score reported) was used withappropriate consideration about the nature of the data(Johnson and Wichern 1992; Morrison 1990).3 The nullhypothesis of each comparison is that the variable ofinterest has the same mean in the two samples. Accord-ingly, a significant test statistic leads to a rejection of theequal-mean hypothesis.

In Table 1, we compare firms in the two countries withrespect to their use of e-business-related technologiesand IT professionals as a percentage of total employees.As predicted earlier, Chinese firms lag behind in usinge-business-related technologies (e.g., website, EDI andEFT), as indicated by the significant x2 statistic. Thegap between Chinese firms and US firms is particularlynoticeable for traditional technologies connecting com-panies with their suppliers and business partners, e.g.,EDI and EFT. With regard to IT human resources, thereis a significant imbalance between large firms and small

Table 2. Global scope and firm size: US–China comparison

US China Comparison

Global scope% of firms with more than 78.2 66.3 x2= 7.70***one establishment% of firms with 33.5 33.9 x2= 0.01establishments abroad% of firms with 7.7 19.2 x2= 7.40***headquarters abroadMean % of total sales 6.7 10.1 t = 1.67*from abroadMean % of total 7.7 15.8 t = 3.34***procurement from abroad

Firm sizeMean number of employees 18,400 13,800 t = 0.43worldwide2001 revenue 330 32 t = 1.97**(in million US dollars)

***p < 0.01; **p < 0.05; *p < 0.10

Table 3. Enterprise integration: US–China comparison

US China Comparison

Extent Web applications 2.86 2.74 Z = −0.77electronically integrated withback-office informationsystems (5-point Likert scale)Extent company databases 2.11 2.24 Z = −1.29 electronically integrated withsuppliers (5-point Likert scale)

***p < 0.01; **p < 0.05; *p < 0.10

Table 5. E-business adoption: US–China comparison

US China Comparison

Breadth: % of firms usingthe Internet for…

Advertising and marketing purposes 72.3 49.7 x2= 22.83***Making sales online 41.9 27.0 x2= 10.01***After sales services and support 60.9 50.0 x2= 4.98**Making purchases online 77.6 24.4 x2= 118.9***Exchanging data with suppliers 48.6 44.2 x2= 0.82Exchanging data with business 62.3 47.4 x2= 9.25***partnersFormally integrating the same 39.7 30.3 x2= 2.81*business processes with businesspartners

Depth: % of businesses conductedonline…

B-to-C sales 4.63 3.01 t = 1.26B-to-B sales 5.31 3.58 t = 1.14B-to-C services 8.54 9.03 t = 0.26B-to-B services 10.72 11.26 t = 0.25Procurement of goods for 11.49 2.28 t = 12.98***production (manufacturing)Procurement of goods for 9.55 5.64 t = 1.12resale (retail)Procurement of supplies for 20.27 1.54 t = 8.49***doing business

***p < 0.01; **p < 0.05; *p < 0.10

Table 4. Environment: US–China comparison

US China Comparison

Competition intensityDegree to which the establishmentis affected by competitors. . .(5-point Likert scale)

In your local area 3.10 3.05 Z = −0.40Inside your country 3.90 3.12 Z = −6.31***Outside your country 2.00 2.48 Z = −4.13***

Regulatory environmentDegree to which e-businessadoption is affected by. ..(5-point Likert scale)

Required for government 1.45 2.39 Z = −7.53***procurementGovernment provided incentives 1.21 2.12 Z = −9.27***Support from business laws 1.82 3.18 Z = −9.81***Legal protection for online 1.89 3.40 Z = −10.87***purchase

***p < 0.01; **p < 0.05; *p < 0.10


firms in China: Small firms have a much higher per-centage of IT professionals in their workforce. One plau-sible explanation is that, while many small businessesare privately owned, most large firms in China arestate-owned and they have operated for several decadesin a planned economy, in which the need for processingmarket information was limited. As a result, these firms ingeneral are characterized by low information intensityand tend to hire fewer IT professionals.

Table 2 shows the global scope of US and Chinesefirms. It is surprising to find that Chinese firms aremore global than US firms, in the sense that moreChinese firms have establishments abroad and headquar-ters abroad (x2 significant), and that international trade(including both sales and purchases) accounts for agreater portion of total trade for Chinese firms than USfirms (t-stat significant). Such differences may reflectthe rapid globalization of the Chinese economy, partlydriven by China’s entry into the WTO and position as aproduction platform for foreign multinational corpora-tions. However, recall that Chinese firms in our sampleare located in the coastal area (more advanced) and repre-sent advanced firms rather than average firms in China(see note 1). We thus need to be cautious when attempt-ing to generalize this result. As hypothesized earlier,greater global scope may have mixed influence onthe extent of e-business adoption, which will be formallytested later using structural equation modelling. We alsocompared firm size. It is not surprising that US firmson average have significantly greater annual revenue(t-statistic significant), although firms in these two coun-tries do not differ significantly in terms of number ofemployees.

With respect to enterprise integration (Table 3), firmsin these two countries do not appear to differ signifi-cantly (Z-score insignificant). It is possible that hiddendifferences or relationships exist but may require moresophisticated methods to discover. Hence, we will fur-ther explore relationships among technology com-petence, enterprise integration and e-business usage laterusing structural equation modelling.

Table 4 contains comparisons of the two countries’environments in which firms conduct e-business. USfirms generally perceive greater rivalry from domesticmarkets, while Chinese firms are more likely to be affec-ted by international competitors (Z-score significant).This may result from the fact that Chinese firms in thecoastal area have frequent interactions with internationalcompetitors, given that a higher percentage of their salesand procurement is international. Another plausibleexplanation is that China’s entry into the WTO hascaused the Chinese government and businesses to regardinternational competition as more significant.

In terms of the regulatory environment, significantMann-Whitney tests demonstrate that, at the currentstage, government regulation plays a far more criticalrole in e-business diffusion in China than in theUnited States. The greater influence of government

requirements (use of e-business for government pro-curement) and government-provided incentives seemto reflect more frequent government interventions inChina. In addition, the greater need for business lawsand legal protection for online purchases seems to implythat Chinese firms are in urgent need of supportive legaland institutional environments to facilitate e-businessgrowth, which are currently lacking.

Finally, we compare organizational usage of e-businessin the two countries in Table 5. It is clear that, comparedto US firms, fewer Chinese firms use the Internet forselling, purchasing, serving customers and exchangingdata with business partners (see the first half of Table 5).However, the second half of the table demonstratesan interesting pattern. On average, firms in the UnitedStates and China do not differ significantly in termsof percentages of sales and services conducted online(t-stat insignificant). This seems to suggest that advancedChinese firms are performing e-business proactively, andChinese firms may be able to catch up relatively quicklyby taking advantage of newer technologies.

Yet, in one area, Chinese firms lag significantly behindthe United States, namely online procurement. US firmspurchase on average 20.27% of total business suppliesand 11.49% of total goods for production on theInternet, while the figures are only 1.54% and 2.28%for Chinese firms. This finding is consistent with thegap shown in Table 1, that Chinese firms fall behindin using interorganizational technologies such as EDIand EFT. This finding also shows that the successof interorganizational systems depends heavily on coor-dination among business partners and is contingent onthe extent of innovation diffusion in the whole valuechain, which goes beyond individual companies (Teoet al 2003). Thus, it is more difficult for China to catchup in the B-to-B area than in the B-to-C area. China’sB-to-B e-business may not take off until China reaches acritical mass when e-business adoption becomes broadacross the value chains.

In summary, cross-sample comparisons between USfirms and Chinese firms in the coastal areas shown inTables 1 to 5 demonstrate the following key differenceswith respect to organizational adoption of e-business andinfluential factors:

• Chinese firms lag in using e-business-related technolo-gies, especially interorganizational technologies suchas EDI and EFT.

• Government plays a far more critical role in China thanin the United States, perhaps due to the fact that Chinalacks a legal and institutional environment to supporte-business.

• Fewer Chinese firms are using the Internet for selling,offering services, purchasing and exchanging data withbusiness partners, compared with US firms.

• Chinese firms may be able to catch up by takingadvantage of newer technologies. Our survey seems to


suggest that advanced Chinese firms are performinge-business proactively. Yet, Chinese firms significantlyfall behind in B-to-B online procurement, partly dueto the imbalance of e-business diffusion in China.

• Chinese firms on average have greater global scope andtend to perceive greater pressure from internationalcompetitors than US firms.

These results help us to understand the differences andsimilarities of e-business adoption in the United Statesand China, yet finer-grained relationships may exist. Wewill further test the robustness of some of these findingsby using structural equation modelling. As a more rigor-ous method, SEM may offer a more holistic pictureof e-business adoption, as relationships between allTOE factors and e-business adoption can be examinedsimultaneously in one unified model.

FURTHER TEST: STRUCTURAL EQUATION MODELLING

Structural equation modelling was conducted as follows:First, we formed reflective constructs of the extent ofEB adoption and the six TOE factors using indicatorsshown in Tables 1 to 5. We also included an intermediateconstruct — incentive to adopt EB,4 which was hypo-thesized to be affected by the TOE factors, and then

determined the extent of EB adoption. Instrumentvalidation was performed by confirmatory factor analysis,as implemented in AMOS 4.0, a covariance-based SEMsoftware package. All constructs passed the tests for con-struct reliability, convergent validity and discriminantvalidity, and thus they could be used for testing relation-ships specified in the structural model (Straub 1989).Then, we estimated the structural model shown in Figure2 using the full sample (the US and China), and evalu-ated the structural model in terms of normed x2 (<3,Anderson 1987), incremental fit indices (>0.9, Hair et al1998), RMSEA (<0.08, Browne and Cudeck 1993), andstatistical power (>0.8, Baroudi and Orilkowski 1989).Our structural model satisfied all these criteria, indicatinga good model fit with the empirical data and sufficientstatistical power. Finally, we fitted the structural modelon the US sample and on the China sample separately.Again, all fit indices were satisfied. The estimation resultsof the full sample and the two subsamples are shown inFigure 2.

A positive and significant path associated with a con-textual factor suggests the role of an adoption facilitator;while a negative and significant path suggests aninhibitor. Thus, the full sample result demonstrates fouradoption facilitators — technology competence, enter-prise integration, competition intensity, and regulatoryenvironment. Results of the US sample and the China

Figure 2. Results of SEM


sample demonstrate different roles of five factors acrossthe two countries, as suggested by differences in pathestimates: firm size and enterprise integration have differ-ent significance levels, global scope has a different pathsign, and technology competence and regulatory envi-ronment have clearly different path magnitudes. Someof our earlier results from the cross-country comparisonare confirmed by SEM, such as the more critical role ofgovernment regulation in China. SEM also offeredseveral new findings that the cross-sample comparisondid not reveal. New findings include the different rolesplayed by firm size, global scope, and enterprise inte-gration across the two samples, which will be discussedsoon. These empirical results, combined with goodmodel fit, strong statistical power, and sufficient datavariance explained, indicate that the TOE research frame-work in Figure 1 is appropriate for explaining factorsshaping e-business adoption. Yet, reflected by the R2

in Figure 2, this framework seems to work better for theUS sample than the China sample, suggesting that someadditional factors might be at work in the China sample.

DISCUSSIONS AND IMPLICATIONS

Drawing upon the results of the structural equationmodelling and the US–China comparison, we summa-rized four major empirical results. We discuss them in thissection and offer explanations and implications.

1 While technologies are more critical for Chinese firms,enterprise integration becomes far more important inthe United States. This seems to suggest that, as firmsmove into deeper stages of e-business transformation, thekey determinant shifts from technology infrastructure toorganizational capabilities.

The empirical results demonstrate the differingsignificance of technology competence and enterpriseintegration for the two countries. E-business-relatedtechnologies exhibit greater impacts on e-businessadoption in China (SEM path 0.52***) than in theUnited States (SEM path 0.31***). This is consistentwith our earlier finding shown in Table 1 that Chinesefirms face a scarcity of technology resources. Enter-prise integration is significant in the United States(SEM path 0.29***) but is insignificant in China.Developed countries and developing countries are atdifferent stages of e-business development (UNCTAD2002). The difference across the two samples seems tosuggest that, as e-business evolves, the key determi-nant of its usage shifts from technology infrastructureto organizational capabilities, especially enterpriseintegration that helps to leverage existing informationsystems and databases, thus creating resource com-plementarities (Zhu and Kraemer 2002).

2 The effect of firm size is a mix of resource advantagesand structural inertia. In the United States, structural

inertia associated with large firms tends to retard e-business migration; while in China, resource advantagesseem to moderate the negative effect of structural inertia.

In the United States, firm size has been shownto retard e-business adoption (SEM path −0.10*),reflecting the negative effect of structural inertia asso-ciated with large firms (Nohria and Gulati 1996). Thisnegative effect of structural inertia, in contrast, seemsto be neutralized by the resource advantages associ-ated with large firms in China. Large firms tend toenjoy a more pronounced advantage than small firmsin developing countries where the playing field seemsto be less even than in developed countries(UNCTAD 2002). Drawing upon our earlier argu-ment that the influence of firm size is a mix of resourceadvantages and structural inertia, this result impliesthat in developing countries, resource advantages(e.g., large firms tend to have more slack resources)tend to be offset by the negative role of structuralinertia. On balance, these two effects seem to canceleach other out; hence we see the insignificant pathfrom firm size to e-business adoption in China.

3 Global scope also shows a mixed effect: In the UnitedStates, greater scope is an adoption facilitator due to thegreater potential benefits offered by e-business, while inChina, increased complexity associated with greater scopetends to inhibit e-business adoption.

Chinese firms seem to have greater global scope(Table 2), yet suffer from the increased complexity ofglobalization with respect to using e-business (SEMpath −0.20*). One plausible explanation is that Chinahas a very different economic and regulatory environ-ment than most Western countries. These gaps mayinduce higher costs to build an integrated e-businesssystem across country boundaries. As a comparison,the United States has a relatively compatible economicenvironment with most Western countries. US firmshave less difficulty handling the increased implementa-tion complexity associated with global expansion.Thus, for US firms, the main effect of greater scope isthe increased potential benefits offered by e-business,which drives organizational adoption of e-business(SEM path 0.16*).

4 Government regulation plays a more critical role inChina than in the United States.

The regulatory environment is more important forChinese firms (0.32***) than for US firms (0.19**),which is consistent with our earlier finding shownin Table 4. It is possible that this could be the casein other developing countries as well. In most develop-ing countries, markets are characterized by informa-tion asymmetry and immature institutional structure(Dewan and Kraemer 2000). Thus, government regu-lation (e.g., regulating monopoly power and dealingwith e-business fraud) tends to play a greater role indeveloping countries.


In summary, using a large-scale, cross-country survey,we have demonstrated the usefulness of our researchframework that incorporates technological, organiza-tional and environmental factors. This framework mightbe useful for other researchers to study various informa-tion system adoptions in different settings, such aswireless mobile commerce. Using a two-step analysisinvolving two mutually reinforcing and complementarymethods, we have shown different e-business adoptionpatterns across developed and developing countries, andidentified a series of influential factors that may playdifferent roles in different economic environments. Thissuggests that e-business is spreading globally, but differ-ent economic and national environments affect organiza-tional adoption. All of the relationships arising from ourdata analysis could help other researchers to build theirresearch models.

These results have several important implications formanagers and policy makers. First, our results suggestthat managers should assess the technological conditionsunder which e-business is used. More importantly, ase-business evolves, managers need to shift the focus fromtechnology investment per se to capabilities of integratingvarious technical components into a streamlined system.As Internet technologies diffuse and become necessities,these organizational capabilities become even morecritical.

Second, managers need to assess the appropriateness ofe-business to certain organizational characteristics (e.g.,firm size and global scope). That is, these structural vari-ables may affect the potential benefits of e-business andinfluence the readiness and complexity of e-businessadoption. Moreover, their influences may vary in differ-ent economic environments. Thus, managers need toadjust their assessments as the economic environmentevolves.

Third, environmental factors (e.g., competition inten-sity and government regulation) have emerged as impor-tant factors shaping e-business adoption. The regulatoryenvironment is even more important in developingcountries. Companies frequently cite significant obstaclesof doing e-business, including inadequate legal pro-tection for online business activities, unclear businesslaws, and security concerns. This points to the need forestablishing a legal and institutional framework support-ing e-business and online transactions. Governments,therefore, could accelerate e-business transformation byestablishing supportive business and tax laws to makethe Internet a trustworthy business platform. This isparticularly important in the early stages of e-businessdevelopment in an economy.

ACKNOWLEDGEMENTS

This research is a part of the Globalization and E-Commerce project of the Center for Research onInformation Technology and Organizations (CRITO) at

the University of California, Irvine. This material is basedupon work supported by the National Science Founda-tion under Grant No. 0085852. Any opinions, findings,and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarilyreflect the views of the National Science Foundation. Theresearch has benefited from the comments of SanjeevDewan, Debbie Dunkle, John Mooney, Paul Tallon, andparticipants at the CRITO seminar and ICIS conference.

Notes1. The Chinese companies were selected from a random

sample of firms from four cities — Beijing, Shanghai,Guangzhou and Chengdu. Most of them are in thecoastal area (except for Chengdu) which is moreadvanced in economic development, ties with theglobal economy, and the use of IT. Hence, our Chinasample represents the more advanced companies,rather than average companies in China.

2. After we received the dataset, which contained 204Chinese responses and 300 US responses, we checkedfor consistency and excluded 69 outliers based onsales, employee number and financial resources.

3. Different types of data require different methods. Forcontinuous data, such as the 2001 revenue in Table 2and the mean percentage of business conductedonline in Table 5, ANOVA was used; for discrete dataof ranking (i.e., 5-point Likert scale), Mann-WhitneyU-test was used; and for binary data, x2 test was used(Johnson and Wichern 1992; Morrison 1990).

4. This construct is measured by responses to the surveyitems — ‘the extent to which your firm expectede-business to help to reduce costs, expand markets forexisting products, enter new businesses, and improvecoordination with business partners’ (5-point Likertscale).

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