User Acceptance Enablers in Individual Decision Making About Technology: Toward an Integrated Model

By V. Venkatesh, Cheri Speier, Michael G. Morris. Decision Sciences, 2002

962 citations recorded by the source corpus.

Building on recent unique, yet potentially complementary, approaches to understanding the formation of user perceptions about technology (Venkatesh, 1999; Venkatesh & Speier, 1999), the present work reanalyzes the data from both studies to develop an integrated model of technology acceptance. The integrated model specifically examines the influence of pre-training and training environment interventions (termed user acceptance enablers) to understand how user perceptions are formed prior to system implementation. The model is then further extended and tested using longitudinal data in a field setting. The results indicate that the integrated model emerged as a better predictor of user behavior when compared to the existing models.

Subfields: Communication, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/ddf5096da715245605b7213bd43b424101e3b5b1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

In Information Systems and Management

In Sociology and Political Science

Citations in the corpus

How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance (2007, background): “Addressing this issue, Venkatesh et al. (2002) reported that when they included short-term usage (prior usage behavior) as an additional antecedent, all other determinants (including behavioral intention, inherent motivation, etc.) became insignificant.”
Technology acceptance model (TAM) and social media usage: an empirical study on Facebook (2014, neutral): “Such simplification of the theoretical framework of the TAM model for behavioral beliefs and behavior intention has become common in researches (Davis, et al. 1992; Klobas, 1995; Venkatesh and Davis, 2000; Venkatesh et al., 2002; Thong, Hong, and Tam, 2002; Lee et al, 2007; etc.).”
ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists (2007, neutral): “[58].”
Impact of media richness and flow on e-learning technology acceptance (2009, background): “PU and PEU have a direct inﬂuence on intended technology use (Lu, Yu, & Liu, 2005; Seyal, Rahman, & Rahim, 2002; Venkatesh & Davis, 1996; Venkatesh, Speier, & Morris, 2002) and well as actual technology use (Yi, Wu, & Tung, 2005/2006) across varied organisational contexts and general business…”
Modeling patients' acceptance of provider-delivered e-health. (2004, methodology): “15,16,21 Items measuring satisfaction with medical care were drawn from Marshall et al., 40 and items measuring information-seeking preference came from Ende et al. 32 Items for health care knowledge, Internet dependence, and health care need were developed within the current study.”
What drives consumers' continuance intention to e-shopping?: Conceptual framework and managerial implications in the case of Saudi Arabia (2011, background): “Enjoyment Enjoyment in using a web site significantly affects intentions to use (Davis et al., 1992; Igbaria et al., 1995; Teo et al., 1999; Venkatesh et al., 2002).”
Where To Go From Here? Thoughts on Future Directions for Research on Individual-Level Technology Adoption with a Focus on Decision Making (2006, background): “For example , Venkatesh et al. (2002) examined how different training types—for example, game-based training versus traditional training—influenced system-related perceptions and concluded that system-related perceptions and intentions were more favorable when game-based training was used.”
Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation (2008, background): “In fact, research incorporating intrinsic motivation constructs, such as perceived enjoyment has been conducted [43] [46].”
Affective Processes in Human–Automation Interactions (2011, background): “Although intentions are significant predictors of behavior (e.g., Venkatesh, Speier, & Morris, 2002), there is not an exact correspondence.”
Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation (2005, methodology): “[39] Virtual workplace system (game-based”
The effects of perceived risk and technology type on users' acceptance of technologies (2008, background): “[25] emphasized the importance of training and developed an integrated model of longitudinal perspective, examining the influence of preand post-training environments over time.”