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Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior1
Abstract
Using the Technology Acceptance Model (TAM), this research investigated gender differences in the overlooked context of individual adoption and sustained usage of technology in the workplace. User reactions and technology usage behavior were studied over a five-month period among 342 workers being introduced to a new software system. At all three points of measurement, compared to women, men's technology usage decisions were more strongly influenced by their perceptions of usefulness. In contrast, women were more strongly influenced by perceptions of ease of use and subjective norm, although the effect of subjective norm diminished over time. These findings were robust even after statistically controlling for key confounding variables identified in prior organizational behavior research (i.e., income, occupation, and education levels), and another possible confound from technology research, prior experience with computers in general. Thus, in addition to identifying key boundary conditions in the role of the original TAM constructs (perceived usefulness and perceived ease of use), this research provides the basis for the integration of subjective norm into the model. In light of these findings, implications for theory and practice are discussed.
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“Proposition 4. The greater the positive social influence a user perceives over algorithms, the higher the probability of building trust in AI algorithms over time.”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as Venkatesh & Morris, 2000
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Metadata
- Authors
- Venkatesh, V., & Morris, M. G.
- Affiliations
- Robert H. Smith School of Business, University of Maryland, College Park, College Park, MD, U.S.A.
- Air Force Institute of Technology, Wright-Patterson AFB, OH, U.S.A.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2000-03-01
- Volume
- 24
- Issue
- 1
- Pages
- 115-139
- ISSN
- 0276-7783
- 2162-9730
- Cited by
- 2,780
- References
- 17
- Language
- en
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