Technology Acceptance Model 3 and a ... - …

1 Decision SciencesVolume 39 Number 2 May 2008C 2008, The AuthorJournal compilationC 2008, Decision Sciences InstituteTechnology Acceptance Model 3and a Research Agenda on InterventionsViswanath venkatesh Department of Information Systems, Walton College of Business, University of Arkansas,Fayetteville, AR 72701, e-mail: Bala Operations and Decision Technologies, Kelley School of Business, Indiana University,Bloomington, IN 47405, e-mail: research has provided valuable insights into how and why employees make a de-cision about the adoption and use of information technologies (ITs) in the an organizational point of view, however, the more important issue is how man-agers make informed decisions about interventions that can lead to greater acceptanceand effective utilization of IT.

2 There is limited research in the IT implementation liter-ature that deals with the role of interventions to aid such managerial decision , there is a need to understand how various interventions can influence theknown determinants of IT adoption and use. To address this gap in the literature, we drawfrom the vast body of research on the Technology Acceptance Model (TAM), particularlythe work on the determinants of perceived usefulness and perceived ease of use, and: (i)develop a comprehensive nomological network (integrated Model ) of the determinantsof individual level (IT) adoption and use; (ii) empirically test the proposed integratedmodel; and (iii) present a research agenda focused on potential pre- and postimplemen-tation interventions that can enhance employees adoption and use of IT.

3 Our findingsand research agenda have important implications for managerial decision making on ITimplementation in Areas: Design Characteristics, Interventions, Management Sup-port, Organizational Support, Peer Support, Technology Acceptance Model (TAM), Technology Adoption, Training, User Acceptance , User Involvement,and User great progress has been made in understanding the determinants of employ-ees information Technology (IT) adoption and use ( venkatesh , Morris, Davis, &Davis, 2003), trade press still suggests that low adoption and use of IT by em-ployees are still major barriers to successful IT implementations in organizations(Overby, 2002; Gross, 2005).

4 As ITs are becoming increasingly complex and central Corresponding author. Effective July 1, Acceptance Model 3 and a Research Agenda on Interventionsto organizational operations and managerial decision making ( , enterprise re-source planning, supply chain management, customer relationship managementsystems), this issue has become even more severe. There are numerous examplesof IT implementation failures in organizations leading to hugefinancial high-profile examples of IT implementation failures are Hewlett-Packard s(HP) failure in 2004 that had afinancial impact of $160 million (Koch, 2004a) andNike s failure in 2000 that cost $100 million in sales and resulted in a 20% dropin stock price (Koch, 2004b).

5 Low adoption and underutilization of ITs have beensuggested to be key reasons for productivity paradox that is, a contradictoryrelationship between IT investment andfirm performance (Landauer, 1995; Sichel,1997; Devaraj & Kohli, 2003). This issue is particularly important given that recentreports suggest that worldwide investment in IT will increase at a rate of ayear from 2004 to 2008 compared to from 2000 to 2004 (World Informa-tion Technology and Service Alliance, 2004). It has been suggested in both theacademic and trade press that managers need to develop and implement effectiveinterventionsin order to maximize employees IT adoption and use (Cohen, 2005;Jasperson, Carter, & Zmud, 2005).

6 Therefore, identifying interventions that couldinfluence adoption and use of new ITs can aid managerial decision making onsuccessful IT implementation strategies (Jasperson et al., 2005).The theme of interventions as an important direction for future research isdocumented in recent research. For instance, venkatesh (2006) reviewed prior re-search on IT adoption and suggested three avenues for future research that arepertinent to the editorial mission ofDecision Sciences: (i) business process changeand process standards; (ii) supply-chain technologies; and (iii) services. Withineach of these three avenues, he noted interventions as a critical direction for futureresearch that had significant managerial implications and the potential to enhanceIT implementation success.

7 More recently, other researchers have provided newdirections in individual-level IT adoption research with a particular focus on inter-ventions that can potentially lead to greater Acceptance and effective utilization ofIT (Benbasat & Barki, 2007; Goodhue, 2007; venkatesh , Davis, & Morris, 2007).Our objective is to present a brief literature review, propose an integrated modelof employee decision making about new ITs, empirically validate the Model , andpresent a research agenda that identifies a set of interventions for researchers andpractitioners to investigate to further our understanding of IT research on individual-level IT adoption and use is mature and has pro-vided rich theories and explanations of the determinants of adoption and use deci-sions ( , venkatesh et al.)

8 , 2003; Sarker, Valacich, & Sarker, 2005 for group-levelIT adoption research). Notwithstanding the plethora of IT adoption studies, therehas been limited research on the interventions that can potentially lead to greateracceptance and use of IT ( venkatesh , 1999). The most widely employed modelof IT adoption and use is the Technology Acceptance Model (TAM) that has beenshown to be highly predictive of IT adoption and use (Davis, Bagozzi, & Warshaw,1989; Adams, Nelson, & Todd, 1992; venkatesh & Davis, 2000; venkatesh &Morris, 2000). One of the most common criticisms of TAM has been thelack ofactionable guidanceto practitioners (Lee, Kozar, & Larsen, 2003).

9 Many leadingresearchers have noted this limitation in interviews reported in Lee et al. (2003).For example, Alan Dennis, a leading scholar in thefield of information systems, venkatesh and Bala275commented, imagine talking to a manager and saying that to be adopted technol-ogy must be useful and easy to use. I imagine the reaction would be Duh! Themore important questions are what [sic] makes Technology useful and easy to use (Lee et al., 2003, p. 766). Some work has been done to address this limitation byidentifying determinants of key predictors in TAM, namely,perceived usefulnessandperceived ease of use. Some researchers have developed context-specific de-terminants to the two TAM constructs for instance, Karahanna and Straub (1999)for electronic communication systems ( , e-mail systems), Koufaris (2002) fore-commerce, Hong and Tam (2006) for multipurpose information appliances, Raiand Patnayakuni (1996) for CASE tools, and Rai and Bajwa (1997) for executiveinformation systems that have immense value in theorizing richly about the spe-cific IT artifact (type of system) in question and identifying determinants that arespecific to the type of Technology being studied.

10 Others have developed generaland context-independent determinants that span across a broad range of systems( , venkatesh , 2000; venkatesh & Davis, 2000). While each of these approacheshas merits, and it is not our goal to debate generality versus context specificityin theorizing (Bacharach, 1989; Johns, 2006), in this article, we are choosing thegeneral set of determinants of TAM as a basis for the identification of broadlyapplicable interventions that can fuel future and Davis (2000) identified general determinants of perceivedusefulness and venkatesh (2000) identified general determinants of perceived easeof use.