The DOI matches its Crossref record; 76 of the 78 references it cites were found in a registry or an index.
Toward Preprototype User Acceptance Testing of New Information Systems: Implications for Software Project Management
Abstract
Errors in requirements specifications have been identified as a major contributor to costly software project failures. It would be highly beneficial if information systems developers could verify requirements by predicting workplace acceptance of a new system based on user evaluations of its specifications measured during the earliest stages of the development project, ideally before building a working prototype. However, conventional wisdom among system developers asserts that prospective users must have direct hands-on experience with at least a working prototype of a new system before they can provide assessments that accurately reflect future usage behavior after workplace implementation. The present research demonstrates that this assumption is only partially true. Specifically, it is true that stable and predictive assessments of a system's perceived ease of use should be based on direct behavioral experience using the system. However, stable and behaviorally predictive measures of perceived usefulness can be captured from target users who have received information about a system's functionality, but have not had direct hands-on usage experience. This distinction is key because, compared to ease of use, usefulness is generally much more strongly linked to future usage intentions and behaviors in the workplace. Two longitudinal field experiments show that preprototype usefulness measures can closely approximate hands-on based usefulness measures, and are significantly pr…
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“Perceived ease of use has been theorized to be closely associated with individuals' self-efficacy beliefs and procedural knowledge, which requires handson experience and execution of skills (Davis et al., 1989;Venkatesh, 2000;Davis & Venkatesh, 2004).”
From Technology Acceptance Model 3 and a Research Agenda on Interventions (2008) · cites this paper as Davis & Venkatesh, 2004
Citations
Cites
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Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
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User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
Self-citationA Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
Self-citationSelf-efficacy mechanism in human agency
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2 of the 78 references couldn’t be matched to a known paper.
Research works printed but not linked: 6
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Sorted by citations
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
“…recent work has challenged the role of behavioral intention as the key predictor of technology use and introduced a new theoretical construct (i.e., habit) as another critical predictor of technology use (e.g., Davis and Venkatesh 2004; Kim and Malhotra 2005; Kim et al. 2005; Limayem et al. 2007).”
Self-citationTechnology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159
“Perceivedeaseofusehasbeentheorizedtobecloselyassociatedwith individuals’self-efficacybeliefsandproceduralknowledge,whichrequireshands-onexperienceandexecutionofskills(Davisetal.,1989;Venkatesh,2000;Davis &Venkatesh,2004).”
BackgroundMethodInfluentialSelf-citationA meta-analysis of the technology acceptance model
King, W. R., & He, J. (2006) · Information & Management · doi:10.1016/j.im.2006.05.003 · Cited by 2,906
Technology acceptance model: a literature review from 1986 to 2013
Marangunić, N., & Granić, A. (2015) · Universal Access in the Information Society · doi:10.1007/s10209-014-0348-1 · Cited by 2,458
“Usage measures: usage measures for operationalization of actual system usage like attitude toward technology [23], usage perception [37, 61, 77], and actual usage of technology [26].”
BackgroundDoes the technology acceptance model predict actual use? A systematic literature review
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010) · Information and Software Technology · doi:10.1016/j.infsof.2009.11.005 · Cited by 851
Metadata
- Authors
- Davis, F. D., & Venkatesh, V.
- Affiliations
- University of Arkansas at Fayetteville (US)
- University of Maryland, College Park (US)
- ORCID
- Davis, F.D.
- Venue
- IEEE Transactions on Engineering Management
- Published
- 2004-02
- Volume
- 51
- Issue
- 1
- Pages
- 31-46
- ISSN
- 0018-9391 (ISSN-L)
- OpenAlex
- W2130427181
- Cited by
- 582
- References
- 78
- Citations by year
- 2026: 16 · 2025: 31 · 2024: 28 · 2023: 29 · 2022: 41 · 2021: 32 · 2020: 29 · 2019: 36 · 2018: 30 · 2017: 30 · 2016: 24 · 2015: 32 · 2014: 35 · 2013: 37 · 2012: 18
- FWCI
- 40.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Engineering Management (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Keywords
- user acceptance testing, perceived usefulness, perceived ease of use, requirements verification, software project management, intention to use, information system development, requirements errors
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