Venkatesh et al./User Acceptance of IT Qarterly RESEARCH ARTICLE USER ACCEPTANCE OF INFORMATION TECHNOLOGY: TOWARD A UNIFIED VIEW^ Abstract By: Viswanath Venkatesh Robert H. Smith School of Business University of Maryland Van Munching Hall College Park, MD 20742 U.S.A. wenkate@rhsmith.umd.edu Michael G. Morris Mcintire School of Commerce University of Virginia Monroe Hall Charlottesville, VA 22903-2493 U.S.A. mmorrls@virginia.edu Gordon B. Davis Carlson School of Management University of Minnesota 321 19'^ Avenue South Minneapolis, MN 55455 U.S.A. gdavis@csom.umn.edu Fred D. Davis Sam M. Walton College of Business University of Arkansas Fayetteville, AR 72701-1201 U.S.A. fdavis@walton.uark.edu Cynthia Beath was the accepting senior editor for this paper. Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the United Theory of Acceptance and Use of Technology (UTAUT). was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R^ of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted f^ of 70 percent). UTAUT thus provides a useful tool for managers needing to MIS Quarterly Vol. 27 No. 3. pp. 425-478/September 2003 425 Venkatesh et at./User Acceptance of IT assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement ofthe core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use. Keywords: Theory of pianned behavior, innovation characteristics, technology acceptance model, sociai cognitive theory, unified model, integrated modei Introduction The presence of computer and information technologies in today's organizations has expanded dramaticaiiy. Some estimates indicate that, since the 1980s, about 50 percent of all new capital investment in organizations has been in information technology (Westland and Clark 2000). Yet, for technologies to improve productivity, they must be accepted and used by employees in organizations. Explaining user acceptance of new technology is often described as one of the most mature research areas in the contemporary information systems (IS) literature (e.g , Hu et al. 1999). Research in this area has resulted in several theoretical models, with roots in information systems, psychology, and sociology, that routinely explain over 40 percent ofthe variance in individual intention to use technology (e.g., Davis et al. 1989; Taylor and Todd 1995b; Venkatesh and Davis 2000). Researchers are confronted with a choice among a multitude of models and find that they must "pick and choose" constructs across the models, or choose a "favored model" and largely ignore the contributions from alternative models. Thus, there is a need for a review and synthesis in order to progress toward a unified view of user acceptance. 426 MIS Quarterly Vol. 27 No. 3/September 2003 The current work has the following objectives: (1) To review the extant user acceptance models: The primary purpose of this review is to assess the current state of knowledge with respect to understanding individual acceptance of new information technologies. This review identifies eight prominent models and discusses their similarities and differences. Some authors have previously observed some of the similarities across models.^ However, our review is the first to assess similarities and differences across all eight models, a necessary first step toward the ultimate goal of the paper: the development of a unified theory of individual acceptance of technology. The review is presented in the following section. (2) To empirically compare the eight models: We conduct a within-subjects, longitudinal validation and comparison of the eight models using data from four organizations. This provides a baseline assessment of the relative explanatory power of the individual models against which the unified model can be compared. The empirical model comparison is presented in the third section. (3) To formulate the Unified Theory of Acceptance and Use of Technology (UTAUT): Based upon conceptual and empirical similarities across models, we formulate a unified model. The formulation of UTAUT is presented in the fourth section. (4) To empirically validate UTAUT: An empirical test of UTAUT on the original data provides preliminary support for our contention that UTAUT outperforms each of the eight original models. UTAUT is then cross-validated using data from two new organizations. The empirical validation of UTAUT is presented in the fifth section. Forexample, Moore and Benbasal (1991) adapted the perceived usefulness and ease of use items from Davis et al.'s (1989) TAM to measure relative advantage and complexity, respectively, in their innovation diffusion model. Venkatesh et aL/User Acceptance of IT t— • Individual reactions to using information technology 1 1 Intentions to use information technology 1 Actual use of information technology Figure 1. Basic Concept Underiying User Acceptance Modeis Review of Extant User Acceptance Models Description of Models and Constructs IS research has long studied how and why individuals adopt new information technologies. Within this broad area of inquiry, there have been several streams of research. One stream of research focuses on individual acceptance of technology by using intention or usage as a dependent variable (e.g., Compeau and Higgins 1995b; Davis et al. 1989). Other streams have focused on implementation success at the organizational level (Leonard-Barton and Deschamps 1988) and tasktechnology fit (Goodhue 1995; Goodhue and Thompson 1995), among others. While each of these streams makes important and unique contributions to the literature on user acceptance of information technology, the theoretical models to be included in the present review, comparison, and synthesis employ intention and/or usage as the key dependent variable. The goal here is to understand usage as the dependent variable. The role of intention as a predictor of behavior (e.g., usage) is critical and has been well-established in IS and the reference disciplines (see Ajzen 1991; Sheppard et al. 1988; Taylor and Todd 1995b). Figure 1 presents the basic conceptual framework underlying the class of models explaining individual acceptance of information technology that forms the basis of this research. Our review resulted in the identification of eight key competing theoretical models. Table 1 describes the eight 1 models and defines their theorized determinants of intention and/or usage. The models hypothesize between two and seven determinants of acceptance, for a total of 32 constructs across the eight models. Table 2 identifies four key moderating variables (experience, voluntariness, gender, and age) that have been found to be significant in conjunction with these models. Prior Model Tests and Model Comparisons There have been many tests of the eight models but there have only been four studies reporting empirically-based comparisons of two or more of the eight models published in the major information systems journals. Table 3 provides a brief overview of each of the model comparison studies. Despite the apparent maturity of the research stream, a comprehensive comparison of the key competing models has not been conducted in a single study. Below, we identify five limitations of these prior model tests and comparisons, and how we address these limitations in our work. Technology studied: The technologies that have been studied in many of the model development and comparison studies have been relatively simple, individual-oriented information technologies as opposed to more complex and sophisticated organizational technologies that are the focus of managerial concern and of this study. MIS Quarterly Vol. 27 No. 3/September 2003 All 1 1 0 o o to E 1 .0 o x> r- 0 CO 3 C CD tj ro 0 E S ro ro _c "a 03 0 •o c ro >, O3 o O3 H" (A E 5 0 CO 0 03 >, 1— "S < m '0 -D 0 ai XI O tj TO 0 c 3 "B t/3 Q. •n •2 _ro O) fD ro •§ 3 0 tr ° o 'r-'. d 2 "55 CD Q. ro CM o 0 0 0 to Q. 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(1989) apiDlied IKA to individuc ceptanee of technothati[he vairianc eexiplained was la eonsistent: with studi t hac ployed TRA in the 1 context of othe r behiaviors. k is one of the most ; of human belhavior. •• 0 LUI ^^M cial p:sychol Hi Drawn froi 1 ••lr 1 UJI re Const ^H Theory ol Rea sone d Acti Ver)katesh et al./User Acceptance of IT 0 CM '0 to ' ^ to CM" d 0 to > ro 03 0/ 0 ro TO ro .£ 03 0 0 0 Q. to to c 0 CO ro CO 0 to c o 0 Kip O [^ 0 C) o < C TJ 0 > "o _2 CO c n 1- «•o "c 0 ro X3 c ll Q- CD X 1— ro B a. B "Q. 0 TJ ro T3 < 0 XJ o .if CD 0 c o .^ ^t >•— o .0 > 0 CO E c c/3 ±j "TO c ro 0 0 CO ' o o ro CQ 0 T3 o "g f" n\ 0 c 0 X3 ro x: 0 O "g E ro 3 Z 0 > 0 a m\ b x; a; 0 ^> TJ 0 CO — TJ T- ^ O 0 Q r— CO .S c ro (0 0 CD Q. 'o c Q. B E 0 TJ o x: 0 • 1 o 0 0 Q 1. u 1H- T3 o a. _,_:, T— a o c f— 0 c < Q o xro: n C13 h 0 0 tn "o c 0' CU O 1 jf 0 - I l~ 0 Q. Q E o > 0 X3 C o 0 o Q- CJ c 0 g o o ro E E "0 — sn T3 H CO u LL. "5 Q- o E o 5 "AM. 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As diseussion "ro notei 0 C •o 0 TPB :he original 0 d h200C nonsti relatio nshi 1 bjective norm a nd bellavii lat subj' ive no !ss im portant th incr easi •f ex pener ice. Th IS simi lart tion of Ka rahann (tal. (1 sS was not > 0 UJJ 2 CN f ^ 0 ined E o ineorp rate d into TPBvi !orri!3 and Venkat Empiri videnice has experi nee modejrates tl K c ior H^ Votu ari inclu lHIi Experi nee was 1not exp licl tly inel udei the ori inal TPB or DTP It has • l o o 0 "o UJJC ; a c 0 JOLU 434 ro to tn 0 CO - ^ •(UO! ^•< ro "ro UJJ' 1 Volu 1 •r Bunc Exper •• • ooo; •del Ver^katesti et at./U$er Acceptance of tT tu 0 ro Z o < z •o ro e o » E ro 0 UJ ^ o E > 0 0 cn c 0 O m i_ Karahanna et al. (1999) conducted a between-subjects comparison to study the impact of innovation characteristics on adoption (no/low experience) and usage behavior (greater experience) and found differences in the predictors of adoption vs. usage behavior. The results showed that for adoption, the significant predictors were relative advantage, ease of use, trialability, results demonstrability, and visibility. In contrast, for usage, only relative advantage and image were significant. Innovation Diffusion Theory Social Cognitive Theory N/A N/A N/A Voluntariness was not tested as a moderator, but was shown to have a direct effect on intention. Thompson et al. (1994) found that complexity, affect toward use, social factors, and facilitating conditions were all more salient with less experience. On the other hand, concern about long-term consequences became increasingly important with increasing levels of experience. V/N V/N V/N V/N V/N V/N Model of PC Utilization Venkatesh et al./User Acceptance of IT MIS Quarterly Vol. 27 No. 3/September 2003 435 436 o B -O 1 >•- n CL ft c o E £ o o ' (A w (0 & o o o w 1- o Q > ro Ol o u o
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