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Ask me no questions: increasing empirical evidence for a qualitative approach to technology acceptance

Ask me no questions: increasing empirical evidence for a qualitative approach to technology acceptance
Ask me no questions: increasing empirical evidence for a qualitative approach to technology acceptance
The Technology Acceptance Model and its derivatives position Perceived Ease of Use, sometimes mediated by Perceived Usefulness, as the primary indicator of an intention to adopt. However, an initial study cast doubt on such a causal relationship: poor ease-of-use scores using a standard instrument did not necessarily correspond to poor usefulness comments from users. We follow up in this paper to explore reproducibility and generalizability. Using secondary review of results from testing and validation activities, we find confirmation that the post hoc measurement of Perceived Ease of Use is less important to participants than their concern for task-oriented usefulness. An ambivalent relationship obtains, therefore, between quantitative measures of Perceived Ease of Use and qualitative review of comments on Perceived Usefulness across three sites in Italy, Spain and the UK. Participants seem to prioritize their professional responsibilities and focus on how the technology under test might support them in their role. We therefore offer an explanation based on psychological theories of work and suggest a controlled follow-on study exploring the narrative content of technology acceptance.
technology acceptance, User adoption, Mixed methods, System usability, Technology affordance, job characteristics model, job demand-control model
0302-9743
125-136
Springer
Pickering, Brian
225088d0-729e-4f17-afe2-1ad1193ccae6
Bartholomew, Rachael
baab0690-95a9-4cf1-8a6b-a78d1d1d5e5a
Nouri Janian, Mariet
15459fc9-c9ee-4e83-9593-e05960a7f8c3
Lopez Moreno, Borja
a85d997d-cf50-485e-8396-bf09f159015e
Surridge, Mike
3200ba8b-b2df-462b-8c98-d0eb2aa13931
Pickering, Brian
225088d0-729e-4f17-afe2-1ad1193ccae6
Bartholomew, Rachael
baab0690-95a9-4cf1-8a6b-a78d1d1d5e5a
Nouri Janian, Mariet
15459fc9-c9ee-4e83-9593-e05960a7f8c3
Lopez Moreno, Borja
a85d997d-cf50-485e-8396-bf09f159015e
Surridge, Mike
3200ba8b-b2df-462b-8c98-d0eb2aa13931

Pickering, Brian, Bartholomew, Rachael, Nouri Janian, Mariet, Lopez Moreno, Borja and Surridge, Mike (2020) Ask me no questions: increasing empirical evidence for a qualitative approach to technology acceptance. In Human-Computer Interaction. Design and User Experience. HCII 2020. Lecture Notes in Computer Science. vol. 12181, Springer. pp. 125-136 . (doi:10.1007/978-3-030-49059-1_9).

Record type: Conference or Workshop Item (Paper)

Abstract

The Technology Acceptance Model and its derivatives position Perceived Ease of Use, sometimes mediated by Perceived Usefulness, as the primary indicator of an intention to adopt. However, an initial study cast doubt on such a causal relationship: poor ease-of-use scores using a standard instrument did not necessarily correspond to poor usefulness comments from users. We follow up in this paper to explore reproducibility and generalizability. Using secondary review of results from testing and validation activities, we find confirmation that the post hoc measurement of Perceived Ease of Use is less important to participants than their concern for task-oriented usefulness. An ambivalent relationship obtains, therefore, between quantitative measures of Perceived Ease of Use and qualitative review of comments on Perceived Usefulness across three sites in Italy, Spain and the UK. Participants seem to prioritize their professional responsibilities and focus on how the technology under test might support them in their role. We therefore offer an explanation based on psychological theories of work and suggest a controlled follow-on study exploring the narrative content of technology acceptance.

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Pickering_etal_AskNoQuestions - Accepted Manuscript
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e-pub ahead of print date: 10 July 2020
Keywords: technology acceptance, User adoption, Mixed methods, System usability, Technology affordance, job characteristics model, job demand-control model

Identifiers

Local EPrints ID: 443247
URI: http://eprints.soton.ac.uk/id/eprint/443247
ISSN: 0302-9743
PURE UUID: 3738bc97-c2dc-4c70-b788-76833a5365b7
ORCID for Brian Pickering: ORCID iD orcid.org/0000-0002-6815-2938

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Date deposited: 19 Aug 2020 16:31
Last modified: 20 Aug 2020 01:40

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Contributors

Author: Brian Pickering ORCID iD
Author: Rachael Bartholomew
Author: Mariet Nouri Janian
Author: Borja Lopez Moreno
Author: Mike Surridge

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