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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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
Self-efficacy mechanism in human agency
Bandura, A. (1982) · American Psychologist · doi:10.1037/0003-066x.37.2.122 · Cited by 15,975
Flow: the psychology of optimal experience
(1990) · Choice Reviews Online · doi:10.5860/choice.28-0597 · Cited by 12,654
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1978) · Advances in Behaviour Research and Therapy · doi:10.1016/0146-6402(78)90002-4 · Cited by 10,586
Social Foundations of Thought and Action
Bandura, A. (2002) · SAGE Publications Ltd eBooks · doi:10.4135/9781446221129.n6 · Cited by 9,948
Understanding information technology usage: a test of competing models
Taylor, S., & Todd, P. A. (1995) · Information Systems Research · doi:10.1287/isre.6.2.144 · Cited by 8,815
Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior 1
Ajzen, I. (2002) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.2002.tb00236.x · Cited by 7,629
(1974) · Medical Entomology and Zoology · Cited by 7,295
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664
Computer Self-Efficacy: Development of a Measure and Initial Test
Compeau, D. R., & Higgins, C. A. (1995) · MIS Quarterly · doi:10.2307/249688 · Cited by 6,553
Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations
Hoffman, D. L., & Novak, T. P. (1996) · Journal of Marketing · doi:10.2307/1251841 · Cited by 5,740
Csíkszentmihályi, M. (1975) · Cited by 5,690
Hedonic Consumption: Emerging Concepts, Methods and Propositions
Hirschman, E. C., & Holbrook, M. B. (1982) · Journal of Marketing · doi:10.1177/002224298204600314 · Cited by 5,616
Multivariate Data Analysis with Readings.
Jolliffe, I. T., Hair, J. F., Anderson, R. E., & Tatham, R. L. (1988) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.2307/2983017 · Cited by 5,106
Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Third Edition
Byrne, B. M. (2016) · doi:10.4324/9781315757421 · Cited by 4,653
Book Review: Structural Equation Modeling: Concepts, Issues, and Applications
Rigdon, E. E., & Hoyle, R. H. (1997) · Journal of Marketing Research · doi:10.2307/3151904 · Cited by 4,088
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb00860.x · Cited by 4,068
Byrne, B. M. (2013) · doi:10.4324/9780203805534 · Cited by 4,016
Byrne, B. M. (1998) · Cited by 3,873
A Model of the Antecedents of Perceived Ease of Use: Development and Test
Venkatesh, V., & Davis, F. D. (1996) · Decision Sciences · doi:10.1111/j.1540-5915.1996.tb01822.x · Cited by 3,802
Self-Efficacy: A Theoretical Analysis of Its Determinants and Malleability
Gist, M. E., & Mitchell, T. R. (1992) · Academy of Management Review · doi:10.5465/amr.1992.4279530 · Cited by 3,713
Hedonic and utilitarian motivations for online retail shopping behavior
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001) · Journal of Retailing · doi:10.1016/s0022-4359(01)00056-2 · Cited by 3,219
Measuring the Customer Experience in Online Environments: A Structural Modeling Approach
Novak, T. P., Hoffman, D. L., & Yung, Y. (2000) · Marketing Science · doi:10.1287/mksc.19.1.22.15184 · Cited by 3,201
Kaplan, B., DeGross, J. I., Wood-Harper, A. T., Wastell, D. G., & Truex, D. P., III (2004) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/b115738 · Cited by 3,139
A Meta-Analysis of Cronbach's Coefficient Alpha
Peterson, R. A. (1994) · Journal of Consumer Research · doi:10.1086/209405 · Cited by 3,028
Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study1
Compeau, D., Higgins, C. A., & Huff, S. L. (1999) · MIS Quarterly · doi:10.2307/249749 · Cited by 2,631
Measuring the hedonic and utilitarian sources of consumer attitudes
Batra, R., & Ahtola, O. T. (1991) · Marketing Letters · doi:10.1007/bf00436035 · Cited by 2,225
Representing and Testing Organizational Theories: A Holistic Construal
Bagozzi, R. P., & Phillips, L. W. (1982) · Administrative Science Quarterly · doi:10.2307/2392322 · Cited by 2,064
Comparative Fit Indices in Structural Models
Bentler, P. M. (1990) · eScholarship (California Digital Library) · Cited by 2,044
Dabholkar, P. A., & Bagozzi, R. P. (2002) · Journal of the Academy of Marketing Science · doi:10.1177/0092070302303001 · Cited by 1,898
Structural Equation Modeling with LISREL
Hayduk, L. A. (1988) · Johns Hopkins University Press eBooks · doi:10.56021/9780801834783 · Cited by 1,874
Flow. The Psychology of Optimal Experience. New York (HarperPerennial) 1990.
Csíkszentmihályi, M. (1990) · Cited by 1,864
Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W., III (2005) · Journal of Marketing · doi:10.1509/jmkg.69.2.61.60759 · Cited by 1,799
Empirical Evaluation of the Revised Technology Acceptance Model
Szajna, B. (1996) · Management Science · doi:10.1287/mnsc.42.1.85 · Cited by 1,656
Self-efficacy: implications for organizational behavior and human resource management
Gist, M. E. (1987) · The Academy of Management Review · doi:10.5465/amr.1987.4306562 · Cited by 1,447
Testing the Determinants of Microcomputer Usage via a Structural Equation Model
Igbaria, M., Guimãrães, T., & Davis, G. B. (1995) · Journal of Management Information Systems · doi:10.1080/07421222.1995.11518061 · Cited by 1,184
Microcomputer Playfulness: Development of a Measure With Workplace Implications
Webster, J., & Martocchio, J. J. (1992) · MIS Quarterly · doi:10.2307/249576 · Cited by 1,153
The effects of self-efficacy on computer usage
Igbaria, M. (1995) · Omega · doi:10.1016/0305-0483(95)00035-6 · Cited by 1,064
Task Characteristics and the Experience of Optimal Flow in Human—Computer Interaction
Ghani, J. A., & Deshpande, S. P. (1994) · The Journal of Psychology · doi:10.1080/00223980.1994.9712742 · Cited by 1,048
Explaining consumer acceptance of handheld Internet devices
Bruner, G. C., & Kumar, A. (2003) · Journal of Business Research · doi:10.1016/j.jbusres.2003.08.002 · Cited by 1,028
Gist, M. E., Schwoerer, C. E., & Rosen, B. (1989) · Journal of Applied Psychology · doi:10.1037/0021-9010.74.6.884 · Cited by 910
Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000) · Information Systems Research · doi:10.1287/isre.11.4.418.11876 · Cited by 834
Hill, T., Smith, N. D., & Mann, M. F. (1987) · Journal of Applied Psychology · doi:10.1037/0021-9010.72.2.307 · Cited by 831
White, K., Mesler, R. M., & Dahl, D. W. (2011) · Journal of Marketing Research · doi:10.1509/jmkr.48.3.472 · Cited by 810
Assessing computer anxiety: Development and validation of the Computer Anxiety Rating Scale
HEINSSEN, R. K., Glass, C. R., & Knight, L. A. (1987) · Computers in Human Behavior · doi:10.1016/0747-5632(87)90010-0 · Cited by 806
Book Review: Innovative Behavior and Communication
Leavitt, C., & Robertson, T. S. (1972) · Journal of Marketing · doi:10.2307/1250439 · Cited by 584
Multivariate data analysis with readings (2nd ed.)
Hair, J. F., Anderson, R. E., & Tatham, R. L. (1986) · Macmillan Publishing Co., Inc. eBooks · Cited by 534
Toward a unified theory of consumer acceptance technology
Kulviwat, S., Bruner, G. C., Kumar, A., Nasco, S. A., & Clark, T. W. (2007) · Psychology and Marketing · doi:10.1002/mar.20196 · Cited by 527
Adoption of Mobile Internet Services: An Exploratory Study of Mobile Commerce Early Adopters
Pedersen, P. E. (2005) · Journal of Organizational Computing and Electronic Commerce · doi:10.1207/s15327744joce1503_2 · Cited by 499
Consumer psychology for marketing
(1995) · Choice Reviews Online · doi:10.5860/choice.32-3392 · Cited by 498
The “Shaken Self”: Product Choices as a Means of Restoring Self-View Confidence
Gao, L., Wheeler, S. C., & Shiv, B. (2008) · Journal of Consumer Research · doi:10.1086/596028 · Cited by 373
Ellen, P. S., Bearden, W. O., & Sharma, S. (1991) · Journal of the Academy of Marketing Science · doi:10.1007/bf02726504 · Cited by 362
Self-Efficacy Beliefs and Sales Performance
Barling, J. I., & Beattie, R. (1983) · Journal of Organizational Behavior Management · doi:10.1300/j075v05n01_05 · Cited by 353
Yim, C. K., Chan, K. W., & Lam, S. S. K. (2012) · Journal of Marketing · doi:10.1509/jm.11.0205 · Cited by 334
Johnson, R. D., & Marakas, G. M. (2000) · Information Systems Research · doi:10.1287/isre.11.4.402.11869 · Cited by 321
Do older adults underestimate their actual computer knowledge?
Marquié, J.-C., Jourdan-Boddaert, L., & Huet, N. (2002) · Behaviour and Information Technology · doi:10.1080/0144929021000020998 · Cited by 275
Assessing User Competence: Conceptualization and Measurement
Marcolin, B. L., Compeau, D., Munro, M. C., & Huff, S. L. (2000) · Information Systems Research · doi:10.1287/isre.11.1.37.11782 · Cited by 264
Customer Self-Efficacy and Response to Service
McKee, D., Simmers, C. S., & Licata, J. W. (2006) · Journal of Service Research · doi:10.1177/1094670505282167 · Cited by 257
Ellen, P. S., Bearden, W. O., & Sharma, S. (1991) · Journal of the Academy of Marketing Science · doi:10.1177/009207039101900401 · Cited by 251
Self-efficacy expectations and coping with career-related events
Stumpf, S. A., Brief, A. P., & Hartman, K. (1987) · Journal of Vocational Behavior · doi:10.1016/0001-8791(87)90037-6 · Cited by 222
Henry, J. W., & Stone, R. W. (1994) · Information Resources Management Journal · doi:10.4018/irmj.1994070102 · Cited by 221
Fu, F. Q., Richards, K. A., Hughes, D. E., & Jones, E. (2010) · Journal of Marketing · doi:10.1509/jmkg.74.6.61 · Cited by 218
Taylor, E. L. (2013) · Research World · doi:10.1002/rwm3.20033 · Cited by 145
Tsarenko, Y., & Strizhakova, Y. (2013) · European Journal of Marketing · doi:10.1108/03090561311285466 · Cited by 124
Reluctance to use technology‐related products: Development of a technophobia scale
Sinkovics, R. R., Stöttinger, B., Schlegelmilch, B. B., & Ram, S. (2002) · Thunderbird International Business Review · doi:10.1002/tie.10033 · Cited by 90
Fear appeals in anti-smoking advertising: How important is self-efficacy?
Manyiwa, S., & Brennan, R. (2012) · Journal of Marketing Management · doi:10.1080/0267257x.2012.715092 · Cited by 74
A model of adolescents' online consumer self-efficacy (OCSE)
Hill, W. W., & Beatty, S. E. (2011) · Journal of Business Research · doi:10.1016/j.jbusres.2010.11.008 · Cited by 65
Structural Equation Modeling Concepts
Bowen, N. K., & Guo, S. (2011) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195367621.003.0002 · Cited by 59
The CAT model: Extensions and moderators of dominance in technology acceptance
Nasco, S. A., Kulviwat, S., Kumar, A., & Bruner, G. C. (2008) · Psychology and Marketing · doi:10.1002/mar.20249 · Cited by 50
Stewart, A. E. (2015) · Journal of Marine Science and Engineering · doi:10.3390/jmse3030630 · Cited by 34
de Camargo, K. R., Guedes, C. R., Caetano, R., Menezes, A., & Trajman, A. (2015) · BMC Health Services Research · doi:10.1186/s12913-015-0941-x · Cited by 11
Bennett, R. (2011) · Journal of Brand Management · doi:10.1057/bm.2010.55 · Cited by 11
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.
Cited by
Sorted by citations
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review