Does the technology acceptance model predict actual use? A systematic literature review

The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of behavioural intention to use (BI) rather than actual usage. This review examines the evidence that the TAM predicts actual usage using both sub...

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Published inInformation and software technology Vol. 52; no. 5; pp. 463 - 479
Main Authors Turner, Mark, Kitchenham, Barbara, Brereton, Pearl, Charters, Stuart, Budgen, David
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.05.2010
Elsevier Science Ltd
Subjects
Online AccessGet full text
ISSN0950-5849
1873-6025
DOI10.1016/j.infsof.2009.11.005

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Abstract The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of behavioural intention to use (BI) rather than actual usage. This review examines the evidence that the TAM predicts actual usage using both subjective and objective measures of actual usage. We performed a systematic literature review based on a search of six digital libraries, along with vote-counting meta-analysis to analyse the overall results. The search identified 79 relevant empirical studies in 73 articles. The results show that BI is likely to be correlated with actual usage. However, the TAM variables perceived ease of use (PEU) and perceived usefulness (PU) are less likely to be correlated with actual usage. Care should be taken using the TAM outside the context in which it has been validated.
AbstractList The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of behavioural intention to use (BI) rather than actual usage. This review examines the evidence that the TAM predicts actual usage using both subjective and objective measures of actual usage. We performed a systematic literature review based on a search of six digital libraries, along with vote-counting meta-analysis to analyse the overall results. The search identified 79 relevant empirical studies in 73 articles. The results show that BI is likely to be correlated with actual usage. However, the TAM variables perceived ease of use (PEU) and perceived usefulness (PU) are less likely to be correlated with actual usage. Care should be taken using the TAM outside the context in which it has been validated.
The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of behavioral intention to use (BI) rather than actual usage. This review examines the evidence that the TAM predicts actual usage using both subjective and objective measures of actual usage. The authors performed a systematic literature review based on a search of six digital libraries, along with vote-counting meta-analysis to analyse the overall results. The search identified 79 relevant empirical studies in 73 articles. The results show that BI is likely to be correlated with actual usage. However, the TAM variables perceived ease of use (PEU) and perceived usefulness (PU) are less likely to be correlated with actual usage. Care should be taken using the TAM outside the context in which it has been validated.
Context The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of behavioural intention to use (BI) rather than actual usage. Objective: This review examines the evidence that the TAM predicts actual usage using both subjective and objective measures of actual usage. Methods: We performed a systematic literature review based on a search of six digital libraries, along with vote-counting meta-analysis to analyse the overall results. Results: The search identified 79 relevant empirical studies in 73 articles. The results show that BI is likely to be correlated with actual usage. However, the TAM variables perceived ease of use (PEU) and perceived usefulness (PU) are less likely to be correlated with actual usage. Conclusions: Care should be taken using the TAM outside the context in which it has been validated.
Author Brereton, Pearl
Budgen, David
Kitchenham, Barbara
Turner, Mark
Charters, Stuart
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  givenname: Mark
  surname: Turner
  fullname: Turner, Mark
  email: m.turner@cs.keele.ac.uk
  organization: School of Computing and Mathematics, Keele University, Keele, Staffordshire ST55BG, UK
– sequence: 2
  givenname: Barbara
  surname: Kitchenham
  fullname: Kitchenham, Barbara
  organization: School of Computing and Mathematics, Keele University, Keele, Staffordshire ST55BG, UK
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  givenname: Pearl
  surname: Brereton
  fullname: Brereton, Pearl
  organization: School of Computing and Mathematics, Keele University, Keele, Staffordshire ST55BG, UK
– sequence: 4
  givenname: Stuart
  surname: Charters
  fullname: Charters, Stuart
  organization: Department of Applied Computing, PO Box 84, Lincoln University, Lincoln 7647, Canterbury, New Zealand
– sequence: 5
  givenname: David
  surname: Budgen
  fullname: Budgen, David
  organization: School of Engineering and Computing Sciences, Durham University, Science Laboratories, South Road, Durham City DH1 3LE, UK
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Snippet The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a measure of...
Context The technology acceptance model (TAM) was proposed in 1989 as a means of predicting technology usage. However, it is usually validated by using a...
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SubjectTerms Acceptance
Actual usage
Behavioural
Correlation
Correlation analysis
Digital libraries
Digital systems
Evidence-based software engineering
Literature review
Literature reviews
Mathematical models
Meta-analysis
Searching
Studies
Systematic literature review
Systematic review
Technology Acceptance Model
Technology acceptance model (TAM)
Technology adoption
Technology utilization
Title Does the technology acceptance model predict actual use? A systematic literature review
URI https://dx.doi.org/10.1016/j.infsof.2009.11.005
https://www.proquest.com/docview/196423998
https://www.proquest.com/docview/1221873200
Volume 52
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