The DOI matches its Crossref record; 81 of the 81 references it cites were found in a registry or an index.
Self-efficacy as an antecedent of cognition and affect in technology acceptance
Abstract
Purpose – This paper aims to examine whether self-efficacy plays an important role in shaping the effect of cognition and affects in high technology adoption. It also examines whether cognition and affect mediate the effect of self-efficacy on attitude toward adoption. Design/methodology/approach – Using an experimental survey to collect data, subjects performed two different tasks (utilitarian and hedonic) to make sure that they had cognitive and affective experiences to draw upon as they developed attitudes toward the focal innovation. Structural equation modeling was used to analyze the model. Findings – The result shows that self-efficacy influenced cognitive perceptions and emotional reactions. Specifically, self-efficacy was found to play a substantive role in shaping individuals’ attitudes via a cognitive route (perceived usefulness and ease-of-use) and an affective one (pleasure, arousal and dominance). Research limitations/implications – The study of self-efficacy as an external variable provides further insights into the process and is expected to increase the explained variance of the theoretical model. Practical implications – This study confirms that a belief about something besides the product also plays a key role; it is the confidence consumers have in their own abilities to understand and effectively use a new piece of technology. Originality/value – The research makes important contributions to our understanding of technology acceptance and has implications for marketing managers.
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“SE may reduce uncertainty when students interact with AR interfaces, allowing them to focus more on therapeutic activities, such as simulated social exposure and cognitive restructuring, rather than on the complexity of the technology itself [96,97,98,99].”
Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.191 · Cited by 43,925
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
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
Comparative fit indexes in structural models.
Bentler, P. M. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.107.2.238 · Cited by 25,266
Significance tests and goodness of fit in the analysis of covariance structures.
Bentler, P. M., & Bonett, D. G. (1980) · Psychological Bulletin · doi:10.1037/0033-2909.88.3.588 · Cited by 20,015
Research works printed but not linked: 3
- Colkin, E. (2002), “Teens ace IT shortcuts”, Information Week, Vol. 879 No. 11, p. -.
- Hoyle, R.H. (1995), Structural Equation Modeling: Concepts, Issues and Applications, Sage Publications, Inc. Thousand Oaks, CA.
- Nunnally, J.C. and Bernstein, I. (1994), Psychometric theory, 3rd ed., McGraw-Hill, New York, NY.
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Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.12.013 · Cited by 956
Understanding academics' adoption of learning technologies: A systematic review
Liu, Q., Geertshuis, S., & Grainger, R. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103857 · Cited by 279
Predicting consumer responses to a chatbot on facebook
Zarouali, B., Van den Broeck, E., Walrave, M., & Poels, K. (2018) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2017.0518 · Cited by 229
Ritz, W., Wolf, M., & McQuitty, S. (2019) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-04-2018-0062 · Cited by 219
Priya, B., & Sharma, V. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107912 · Cited by 167
Metadata
- Authors
- Kulviwat, S., C. Bruner II, G., & P. Neelankavil, J.
- Affiliations
- Hofstra University (US)
- Venue
- Journal of Consumer Marketing
- Publisher
- Emerald
- Published
- 2014-05-06
- Volume
- 31
- Issue
- 3
- Pages
- 190-199
- ISSN
- 0736-3761 (ISSN-L)
- OpenAlex
- W2063919763
- Cited by
- 144
- References
- 78
- Citations by year
- 2026: 14 · 2025: 22 · 2024: 25 · 2023: 18 · 2022: 16 · 2021: 7 · 2020: 8 · 2019: 10 · 2018: 12 · 2017: 5 · 2016: 3 · 2015: 4
- FWCI
- 7.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Consumer Marketing (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Gender Studies › Gender and Technology in Education
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- self-efficacy, technology acceptance, perceived usefulness, perceived ease of use, pleasure, arousal, dominance, consumer technology adoption
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