The DOI matches its Crossref record; 134 of the 134 references it cites were found in a registry or an index.
Moving Beyond Intentions and Toward The Theory of Trying: Effects of Work Environment and Gender on Post-Adoption Information Technology Use1
Abstract
Grounded in the theory of trying, this study examines the influence of the work environment and gender on trying to innovate with information technology. The study extends the innovation diffusion literature by offering a theory-driven explanation for examining trying to innovate with IT and a parsimonious measure for this construct. Drawing on the theory of reasoned action, we argue that work environment impediments render intentions inadequate for examining post-adoption IT use. Instead of examining intentions, we introduce the goal-based construct of trying to innovate with IT as an appropriate dependent variable for examining post-adoption IT use. Statistical analysis supports the reliability and validity of a parsimonious measure of trying to innovate with IT. The study focuses on two research questions. First, do perceptions of the work environment such as overload and autonomy influence individuals’ trying to innovate with IT? Second, does gender influence the relationship between perceptions of the environment and trying to innovate with IT? The model articulates how perceptions of the environment moderated by gender may influence trying to innovate with IT. Results provide evidence that overload and autonomy are antecedents to trying to innovate with information technology. Further, findings confirm that autonomy interacts with overload to determine trying to innovate with IT and that these relationships vary by gender. Implications for research and practice are offered.
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“Furthermore, based on evidence indicating that workload and autonomy influence innovation adoption [35], low job control and high job demands were also introduced as moderators.”
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An investigation of the effects of reciprocal peer tutoring
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“While Ahuja and Thatcher (2005) contended that differences exist across gender when it comes to innovating with technology, further examinations can build on this study to compare the effects gender might have on RPT involving technology.”
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“, 2005) to enhance innovative usage of a system (Ahuja and Thatcher, 2005; Burton-Jones and Straub, 2006).”
InfluentialSink or Swim: Empowering Leadership and Overload in Teams' Ability to Deal with the Unexpected
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Examining Student Satisfaction and Gender Differences in Technology-Supported, Blended Learning.
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Unlocking the smart home: exploring key factors affecting the smart lock adoption intention
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“PLS is a component-based structural equation modeling approach that has been widely adopted in the existing literature (e.g. Ahuja & Thatcher, 2005; Xiang et al., 2016).”
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“A transition from routinization to extended use is a strong indication that the online service under investigation has begun to be embedded within a person's day-to-day activities (Ahuja and Thatcher 2005, Hsieh and Wang 2007, Saga and Zmud 1994).”
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Lee, A., Liu, Y., Murtinu, S., & Wei, Z. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.113322 · Cited by 66
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BackgroundArtificial Intelligence and Groups: Effects of Attitudes and Discretion on Collaboration
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Johnston, A. C., & Warkentin, M. E. (2010) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.2010070101 · Cited by 51
“As such, the successful implementation of IT within the firm rests largely on the interactions that occur between end users and systems and the degree to which these activities match the desires of management or the needs of the firm as a whole (Ahuja & Thatcher, 2005; Warkentin & Johnston, 2008).”
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Chung, N., Tyan, I., & Chung, H. (2017) · Sustainability · doi:10.3390/su9112102 · Cited by 56
“The PLS is a multivariate technique to test structural models, which estimates the model parameters minimizing the residual variance of the whole model dependent variables, does not require an parametric conditions and is appropriate for a small sample size [100].”
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“PLS regression analysis has several advantages, including small sample size, and few assumptions about measurement scale and normal distribution (Ahuja & Thatcher, 2005).”
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“IS users experiencing techno-mastery will be more focused on learning how to use different IS features to improve their work skills and make their work more efficient, and thus will less feel overwhelmed by the features (Ahuja & Thatcher, 2005; Bloom et al., 2014).”
Köffer, S., Ortbach, K., Junglas, I. A., Niehaves, B., & Harris, J. G. (2015) · Business & Information Systems Engineering · doi:10.1007/s12599-015-0387-z · Cited by 50
“IS research has investigated determinants of IT innovation in the context of post adoption behavior, suggesting that the work environment influences the degree to which users create additional value with technology (Ahuja and Thatcher 2005; Jasperson et al. 2005; Li et al. 2013).”
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Ng, D., Kauffman, R. J., Griffin, P., & Hedman, J. (2021) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2020.101018 · Cited by 55
Shao, Z., Li, X., Luo, Y., & Benitez, J. (2022) · European Journal of Information Systems · doi:10.1080/0960085x.2022.2147456 · Cited by 56
“We also measured task autonomy (TA) (Ahuja & Thatcher, 2005; Morris & Venkatesh, 2010) and perceived usefulness (PU) (Davis, 1989; Venkatesh et al., 2003) that potentially affect employee digital performance as control variables (Shao & Li, 2022).”
MethodDeveloping Structural Integrated Stressor–Stress Models for Clients’ and Contractors’ Cost Engineers
Leung, M., Chan, Y.-S., Chong, A. M. L., & Sham, J. F. C. (2008) · Journal of Construction Engineering and Management · doi:10.1061/(asce)0733-9364(2008)134:8(635 · Cited by 48
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“2015) and PIIT (Ahuja and Thatcher 2005) influence the trial-period technostress creator-strain relationship (Figure 2).”
BackgroundMethodInfluentialImpact of BYOD on organizational commitment: an empirical investigation
Doargajudhur, M., & Dell, P. (2019) · Information Technology and People · doi:10.1108/itp-11-2017-0378 · Cited by 50
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Gong, M., Xu, M., Luqman, A., Yu, L., & Masood, A. (2020) · Kybernetes · doi:10.1108/k-05-2019-0367 · Cited by 46
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How important is the “social” in social networking? A perceived value empirical investigation
Cocosila, M., & Igonor, A. (2015) · Information Technology and People · doi:10.1108/itp-03-2014-0055 · Cited by 47
“…a t-statistic of the absolute difference between the corresponding path coefficients in the two cases – i.e., full sample and reduced sample (Ahuja and Thatcher, 2005; Chin, 2000): t ¼ ðPath1 Path2Þ=½Spooled sqrt ð1=N1þ1=N2Þ Perceived Overall Value Behavioral Intention Utilitarian…”
BackgroundInnovation with IS usage: individual absorptive capacity as a mediator
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Althuizen, N. (2017) · Information Systems Journal · doi:10.1111/isj.12172 · Cited by 45
Why Wait? Modeling Factors that Influence the Decision of When to Learn a New Use of Technology
Loraas, T. M., & Wolfe, C. J. (2006) · Journal of Information Systems · doi:10.2308/jis.2006.20.2.1 · Cited by 45
Cocosila, M., & Archer, N. (2014) · BMJ Open · doi:10.1136/bmjopen-2014-005304 · Cited by 44
Compeau, D., Correia, J., & Thatcher, J. B. (2022) · MIS Quarterly · doi:10.25300/misq/2022/15516 · Cited by 43
Combining variance and process in information systems research: Hybrid approaches
de Guinea, A. O., & Webster, J. (2017) · Information and Organization · doi:10.1016/j.infoandorg.2017.06.002 · Cited by 43
Information technology and the autonomy–control duality: toward a theory
Tafti, A., Mithas, S., & Krishnan, M. S. (2007) · Information Technology and Management · doi:10.1007/s10799-007-0014-x · Cited by 43
Guo, W., Liang, R., Wang, L., & Peng, W. (2016) · Behaviour and Information Technology · doi:10.1080/0144929x.2016.1212402 · Cited by 42
“According to previous studies (Ahuja and Thatcher 2005; Hair et al.2006 ), the subgroup analysis approach is preferable to test the moderation effect when the subset of the subjects can be properly divided; thus, in this work, the subgroup analysis approach was applied to detect between-group…”
MethodResultExamining the Intervening Role of Age and Gender on mobile payment Acceptance in Ghana: UTAUT Model
Acheampong, P., Zhiwen, L., Hiran, K. K., Obobisa, E. S., Boateng, F. A., & Bediako, I. A. (2018) · Canadian Journal of Applied Science and Technology - Canadian Journal of Applied Science and Technology · Cited by 42
Luo, Y., & Ye, Q. (2019) · Journal of International Consumer Marketing · doi:10.1080/08961530.2018.1503987 · Cited by 42
“…moderating role in various aspects of online behavior, such as switching behavior (Zhang et al. 2009), acceptance of information technology (Ahuja and Thatcher 2005; Gefen and Straub 1997), e-loyalty (Melnyk, Van Osselaer, and Bijmolt 2009), online shopping (Zhang, Cheung, and Lee 2014),…”
BackgroundNa, T.-K., Lee, S.-H., & Yang, J.-Y. (2021) · Information · doi:10.3390/info12070280 · Cited by 42
“Research in the information and communication industry has shown that the gender of users affects various decision-making processes, such as information search and technology acceptance, thus emphasizing the importance of gender to marketing managers [20,35].”
BackgroundLee, G., Kim, T. T., Shin, S. H., & Oh, I. K. (2012) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2012.01.003 · Cited by 42
Shao, Z., & Li, X. (2022) · Information & Management · doi:10.1016/j.im.2022.103597 · Cited by 41
Valta, M., Hildebrandt, Y., & Maier, C. (2024) · Internet Research · doi:10.1108/intr-09-2022-0766 · Cited by 47
The Dynamic User Activities in Massive Multiplayer Online Role-Playing Games
Shin, D. (2010) · International Journal of Human-Computer Interaction · doi:10.1080/10447310903575473 · Cited by 41
“RETRACTED RETRACTED Referent identification occurs when individuals adopt an opinion held by people who are important to them: friends, peer groups, coworkers, and schoolmates (Ahuja & Thatcher, 2005; S. A. Brown & Venkatesh, 2005).”
BackgroundRetractedUnderstanding it Entrepreneurial Intention: An Information Systems View
Chen, L. (2014) · Journal of Computer Information Systems · doi:10.1080/08874417.2014.11645736 · Cited by 40
“Innovativeness is, thus, one of the most important personal characteristics for exploring a new world such as entrepreneurship [60, 72] and emerging technology adoption [5].”
BackgroundBehavioral Perspective on BIM Postadoption in Construction Organizations
Ma, P., Zhang, S., Hua, Y., & Zhang, J. (2019) · Journal of Management in Engineering · doi:10.1061/(asce)me.1943-5479.0000729 · Cited by 41
Metadata
- Authors
- Ahuja, M. K., & Bennett, J.
- Affiliations
- Indiana University Bloomington (US)
- Department of Management, College of Business and Behavioral Science, Clemson University, 101 Sirrine Hall, Clemson, SC 29634-1305, U.S.A.
- ORCID
- Ahuja, Manju K.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2005-09-01
- Volume
- 29
- Issue
- 3
- Pages
- 427-460
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1758167268
- Cited by
- 818
- References
- 133
- Citations by year
- 2026: 21 · 2025: 29 · 2024: 37 · 2023: 23 · 2022: 43 · 2021: 39 · 2020: 45 · 2019: 41 · 2018: 44 · 2017: 54 · 2016: 49 · 2015: 60 · 2014: 45 · 2013: 48 · 2012: 42
- FWCI
- 55.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- MIS Quarterly (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- work environment, gender differences, IT innovation, employee autonomy, diffusion of innovations, theory of reasoned action, moderating effect
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.
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