The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Inhibitors and Enablers as Dual Factor Concepts in Technology Usage
Abstract
Information systems (IS) research has focused extensively on the factors that foster adoption and usage. A large body of work explores overall beliefs about system usage, antecedents of system satisfaction, and other perceptions that enable system success, create positive attitudes, and encourage usage. However, much less attention has been given to what perceptions uniquely inhibit usage. In large part, this is due to the implicit assumption that the inhibitors of usage are merely the opposite of the enablers. This paper proposes a theory for the existence, nature, and effects of system attribute perceptions that lead solely to discourage use. I posit that usage inhibitors deserve an independent investigation on the basis of three key arguments. One, there exist perceptions that serve solely to discourage usage, and these are qualitatively different from the opposite of the perceptions that encourage usage. Two, these inhibiting and enabling perceptions are independent of one another and can coexist. Three, inhibiting and enabling perceptions have differing antecedent and consequent effects.. As unique beliefs, inhibiting perceptions can add to our understanding of the antecedents of usage or outright rejection. Further, such inhibitors may not only be important to the IS usage decision, they may be more important than enabling beliefs.
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Citations
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
(1980) · Medical Entomology and Zoology · Cited by 25,810
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
A 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
A feature-integration theory of attention.
Treisman, A. M., & Gelade, G. (1980) · Cognitive Psychology · doi:10.1016/0010-0285(80)90005-5 · Cited by 12,366
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
(2003) · Journal of Management Information Systems · doi:10.1080/07421222.2003.11045748 · Cited by 11,791
Design Science in Information Systems Research1
Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004) · MIS Quarterly · doi:10.2307/25148625 · Cited by 10,707 · cited 1×
“The design, development, and functionality of a system is presumably driven by an overall purpose (Ba et al., 2001; Hevner et al., 2004) and one oriented to achieving positive perceptions of quality, whether in terms of information, system, or service.”
BackgroundInformation Systems Success: The Quest for the Dependent Variable
DeLone, W. H., & McLean, E. R. (1992) · Information Systems Research · doi:10.1287/isre.3.1.60 · Cited by 10,697
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
Cited by
Synthesizing information systems knowledge: A typology of literature reviews
Paré, G., Trudel, M.-C., Jaana, M., & Kitsiou, S. (2015) · Information & Management · doi:10.1016/j.im.2014.08.008 · Cited by 1,987
Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11816-3 · Cited by 637
“Moreover, most of the TAM-related studies have ignored users’ negative (inhibiting) perceptions in favor of focusing only on their positive (enabling) ones (Dou et al., 2017; Cenfetelli, 2004).”
BackgroundConsumers’ Resistance to Digital Innovations: A Systematic Review and Framework Development
Talwar, S., Talwar, M., Kaur, P., & Dhir, A. (2020) · Australasian Marketing Journal · doi:10.1016/j.ausmj.2020.06.014 · Cited by 348
Consumer's decision to shop online: The moderating role of positive informational social influence
Lee, M. K. O., Shi, N., Cheung, C. M. K., Lim, K. H., & Sia, C. L. (2011) · Information & Management · doi:10.1016/j.im.2010.08.005 · Cited by 315
Cenfetelli, R. T., Benbasat, I., & Al-Natour, S. (2008) · Information Systems Research · doi:10.1287/isre.1070.0163 · Cited by 272
Self-citation
Metadata
- Authors
- University of British Columbia, C., & Cenfetelli, R.
- Venue
- Journal of the Association for Information Systems
- Publisher
- Association for Information Systems
- Published
- 2004-12
- Volume
- 5
- Issue
- 11
- Pages
- 472-492
- ISSN
- 1536-9323 (ISSN-L)
- OpenAlex
- W1547749156
- Cited by
- 388
- References
- 75
- FWCI
- 5.98
- Type
- journal article
- Language
- en
- Open access
- closed
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