The European e-Business Report 2004 - Berlecon Research GmbH

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The European E-Business Report 20043.2 What Drives E-Business Diffusion among Firms?Evidence from European Companiesby Kenneth L. Kraemer, Kevin Zhu & Sean Xu (University of California, Irvine), and WernerB. Korte and Karsten Gareis (empirica GmbH) 863.2.1 IntroductionAs Internet-enabled electronic business (e-business 87 ) has been widely adopted by firms in a varietyof industries to support value chain activities (Zhu et al. 2003), there is a growing need to betterunderstand the factors that drive organizational adoption of e-business. We investigated this issuefrom three perspectives. Firstly, viewing e-business as a technological innovation (Rogers 1983), weexamined impacts of e-business characteristics on organizational adoption from an innovationdiffusion perspective. Secondly, since the success of innovation adoption might be affected by thecontexts in which it is adopted (Tornatzky and Fleischer 1990), we also incorporated influences ofcontextual (i.e., technological, organizational, environmental) factors. Thirdly, as features of theinnovation and the adoption environment often interact to reinforce one another (Tornatzky and Klein1982), we felt it was important to study the interaction effects of the innovation characteristics andcontextual factors, which we defined as the “fit” between the innovation and its adoption contexts.We integrated the three perspectives into a conceptual framework for studying e-business adoption,and examined the following research question: How do e-business characteristics, adoption contexts,and the fit between them affect organizational adoption of e-business? In the next section, we presenthypotheses about the adoption drivers, followed by our research method and empirical results. Weconclude with a discussion on major findings and implications for both managers and policy-makers.3.2.2 Theoretical DevelopmentThe dependent variable is e-business adoption, which refers to whether or not a firm uses Internettechnologies for e-business (e.g., for online selling, procurement, or supply chain co-ordination).Drawing upon the conceptual framework, we examine three groups of factors influencing e-businessadoption.(1) On the e-business characteristics side, we choose four of the commonly studied innovationfeatures (Rogers 1983; Tornatzky and Klein 1982): relative advantage (including revenue advantageand cost advantage), compatibility, and adoption costs. We also add a new feature unique for the e-business phenomenon, security concerns, because security concerns are found to be a key barrier toe-business diffusion (UNCTAD 2002).(2) On the adoption context side, we focus on three dimensions: technological context, organizationalcontext, and environmental context (Tornatzky and Fleischer 1990). Drawing upon the technologyorganization-environmentcategorization, we incorporate six specific variables with consistent literature8687Kenneth L. Kraemer is a Professor, Kevin Zhu is an Assistant Professor, and Sean Xu is a doctoral student atthe Center for Research on Information Technology and Organizations (CRITO), University of California,Irvine. This research has been supported by grants from the U.S. National Science Foundation (CISE/ISS/ITRand DST, grant numbers 0085852 and 0132911 respectively) and by the European Commission (ProjectsSIBIS, STAR). Data were provided by Empirica, GMBH, Bonn, Germany. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the authors and do not necessarilyreflect the views of the National Science Foundation or the EC. The research has benefited from thecomments of Jason Dedrick, Shutao Dong, Deborah Dunkle, Jennifer Gibbs, and seminar participants atCRITO.E-business is defined as using the Internet to support or conduct business activities along the value chain,including marketing, selling, procurement, and supply chain co-ordination (CRITO, GEC Survey, 2002).195
The European E-Business Report 2004support (Zhu et al. 2003): technology competence, firm size, firm scope, consumer readiness,competitive pressure, and partner readiness.(3) Further, we hypothesize five interaction effects to represent the influence of “fit” (Tornatzky andKlein 1982). These factors, as well as associated hypotheses, are elaborated below.E-business characteristicsThe relative advantage of an innovation (Rogers 1983) has been widely examined in the innovationdiffusion literature. Previous studies have consistently demonstrated the positive influence ofinnovation’s relative advantage on its diffusion. We decomposed the relative advantage of e-businessinto two categories: revenue advantage and cost advantage. The former refers to the potential of e-business to help increase sales, and the latter the potential to reduce costs. These benefits shouldprovide incentives for e-business adoption, which leads to the following hypotheses:H1a: Firms facing greater revenue advantage of e-business are more likely to adopt.H1b: Firms facing greater cost advantage of e-business are more likely to adopt.To study the influence of compatibility, we draw upon Roger’s (1983) conceptualization. That is,innovation compatibility is defined as the degree to which the innovation to be adopted is consistentwith organizational skills, distribution channels, and corporate culture. Choosing compatibleinnovations may help to minimize the organizational adjustments required and thereby reduce thepotential resistance to innovation adoption (Rogers 1983). In line with Rogers’conceptualization, wefocus on the compatibility of e-business with the firm’s skills, distribution channels, and culture ofpotential users. Firms that can better provide required skills, achieve channel synergy, and those thathave compatible corporate culture are more likely to successfully adopt e-business. Hence, we putforward the following hypothesis:H1c: Firms with greater compatible skills, distribution channels, and corporate culture are more likelyto adopt.In the innovation literature, costs have been consistently identified to be a factor inhibiting innovationadoption (Tornatzky and Klein 1982). We included adoption costs in our conceptual frameworkbecause adopting e-business requires substantial investments in hardware, software, systemintegration, and employee training. We expect these adoption costs to be a barrier to e-businessadoption and hypothesize:H1d: Firms facing greater adoption costs are less likely to adopt.We also propose an additional factor unique for e-business – security concerns, which refer to thedegree to which organizations deem e-business insecure for confidential data and online transactions.Potential users might have security concerns due to the open standards of the Internet and theimmaturity of the institutional framework regarding contracts, financial transactions, and privacyprotection (UNCTAD 2002). Such concerns might retard the adoption decision and therefore wehypothesize:H1e: Firms with greater security concerns about e-business are less likely to adopt.Adoption ContextsTechnological contextFirms’technology competence is an important factor within the technological context. To study theinfluence of technology competence, we conceptualise two underlying dimensions – – IT infrastructureand Internet skills. IT infrastructure refers to technologies that enable Internet-related businesses;Internet skills are defined as employees’skills in using the Internet and related technologies. Ourworking hypothesis in this context is:H2a: Firms with higher levels of technology competence are more likely to adopt e-business.196
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