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Fred D. Davis

Researcher at Texas Tech University

Publications -  101
Citations -  140802

Fred D. Davis is an academic researcher from Texas Tech University. The author has contributed to research in topics: Technology acceptance model & Cognitive neuroscience. The author has an hindex of 44, co-authored 97 publications receiving 120385 citations. Previous affiliations of Fred D. Davis include Massachusetts Institute of Technology & Sogang University.

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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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User acceptance of information technology: toward a unified view

TL;DR: The Unified Theory of Acceptance and Use of Technology (UTAUT) as mentioned in this paper is a unified model that integrates elements across the eight models, and empirically validate the unified model.
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User Acceptance of Computer Technology: A Comparison of Two Theoretical Models

TL;DR: In this article, the authors address the ability to predict peoples' computer acceptance from a measure of their intentions, and explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables.
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A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies

TL;DR: In this paper, the authors developed and tested a theoretical extension of the TAM model that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes, which was tested using longitudinal data collected regarding four different systems at four organizations (N = 156), two involving voluntary usage and two involving mandatory usage.
Posted Content

User Acceptance of Information Technology: Toward a Unified View

TL;DR: TAUT provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions targeted at populations of users that may be less inclined to adopt and use new systems.