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Open AccessJournal ArticleDOI

Technology Acceptance Model 3 and a Research Agenda on Interventions

Viswanath Venkatesh, +1 more
- 01 May 2008 - 
- Vol. 39, Iss: 2, pp 273-315
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TLDR
This work draws from the vast body of research on the technology acceptance model (TAM) to develop a comprehensive nomological network of the determinants of individual level IT adoption and use and present a research agenda focused on potential pre- and postimplementation interventions that can enhance employees' adopted and use of IT.
Abstract
Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre- and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations.

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References
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TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.

Perceived Usefulness, Perceived Ease of Use, and User

TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.
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Perceived usefulness, perceived ease of use, and user acceptance of information technology

TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
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Multiple Regression: Testing and Interpreting Interactions

TL;DR: In this article, the effects of predictor scaling on the coefficients of regression equations are investigated. But, they focus mainly on the effect of predictors scaling on coefficients of regressions.
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