The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Assessing IT Usage: The Role of Prior Experience
Abstract
A variety of models that incorporate attitudinal, social, and control factor have been advanced to explain IT usage, of which the Technology Acceptance Model (TAM) is the most well know. One goal of such models is to develop diagnostic tools to predict information systems acceptance and facilitate design changes before users have experience with a system. However, empirical tests of these models have generally focused on either systems that were already in use by the study participants, or systems that the participants were familiar with, such as word processing packages and spreadsheets. Given this, it is unclear (1) whether models such as TAM are predictive of behavior for inexperienced users and, more importantly, (2) whether the determinants of IT usage are the same for experienced and inexperiened users of a system.
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
“Subjective norms tend to be more influential during early stages of innovation implementation when users have limited direct experience from which to develop attitudes (Taylor and Todd, 1995).”
From An Analysis of Factors Affecting on Online Shopping Behavior of Consumers (2012) · cites this paper as Taylor and Todd, 1995
In the citing paper
“The role of intention as a predictor of behavior is well established in the literature (e.g. Sheppard etal. 1988; Taylor and Todd 1995).”
From Understanding the determinants of novel technology adoption among teachers: the case of 3D printing (2020) · cites this paper as Taylor and Todd 1995
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
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
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
(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
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
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
Self-citation(1993) · Medical Entomology and Zoology · Cited by 7,690
Structural model evaluation and modification: An interval estimation approach
Steiger, J. H. (1990) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2502_4 · Cited by 7,408
Flagged first, then by citations
Research works printed but not linked: 2
- Barclay, 1996, The Partial Least Squares Approach to Causal Modelling, Technology Studies
- Eagly, 1993, The Psychology of Attitudes
Cited by
Sorted by citations
Items 401–500 of 1,001
Wutz, M., Hermes, M., Winter, V., & Köberlein–Neu, J. (2023) · Journal of Medical Internet Research · doi:10.2196/46548 · Cited by 117
Wu, J., Tsai, R. J., Chen, C. C., & Wu, Y. (2006) · NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) · doi:10.71889/5fylantbak.30804620 · Cited by 103
Srite, M. (2006) · AJIS. Australasian journal of information systems/AJIS. Australian journal of information systems/Australian journal of information systems · doi:10.3127/ajis.v14i1.4 · Cited by 102
Jou, M., Tennyson, R. D., Wang, J., & Huang, S.-Y. (2015) · Computers & Education · doi:10.1016/j.compedu.2015.10.004 · Cited by 103
Islamic marketing and consumer behavior toward halal food purchase in Bangladesh
Ashraf, M. (2019) · Journal of Islamic marketing · doi:10.1108/jima-03-2018-0051 · Cited by 115
Modeling Customers' Intention to Use E-Wallet in a Developing Nation
Soodan, V., & Rana, A. K. (2019) · Journal of Electronic Commerce in Organizations · doi:10.4018/jeco.2020010105 · Cited by 111
A modified UTAUT model for the acceptance and use of digital technology for tackling COVID-19
Akinnuwesi, B. A., Uzoka, F.-M. E., Fashoto, S. G., Mbunge, E., Odumabo, A. T., Amusa, O. O., Okpeku, M., & Owolabi, O. (2021) · Sustainable Operations and Computers · doi:10.1016/j.susoc.2021.12.001 · Cited by 134
An alternative model of self-service retail technology adoption
Kaushik, A. K., & Rahman, Z. (2015) · Journal of Services Marketing · doi:10.1108/jsm-08-2014-0276 · Cited by 116
Lee, J., Bharosa, N., Jing, Y., Janssen, M., & Rao, H. (2010) · Decision Support Systems · doi:10.1016/j.dss.2010.10.002 · Cited by 107
Determinants of firms' knowledge management system implementation: An empirical study
Wang, Y.-M., & Wang, Y.-C. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.055 · Cited by 113
Jariyapan, P., Mattayaphutron, S., Gillani, S. N., & Shafique, O. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.814087 · Cited by 102
Callen, J. L., Braithwaite, J., & Westbrook, J. I. (2007) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2468 · Cited by 99
The Role of Impulsiveness in a TAM-Based Online Purchasing Behavior
Zhang, X., Prybutok, V. R., & Koh, C. E. (2006) · Information Resources Management Journal · doi:10.4018/irmj.2006040104 · Cited by 102
Kim, B., & Oh, J. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.07.107 · Cited by 109
The impact of personality type on purchasing decisions in virtual stores
Barkhi, R., & Wallace, L. G. (2007) · Information Technology and Management · doi:10.1007/s10799-007-0021-y · Cited by 108
Assessing regional digital competence: Digital futures and strategic planning implications
Alam, K., Erdiaw‐Kwasie, M. O., Shahiduzzaman, M., & Ryan, B. (2018) · Journal of Rural Studies · doi:10.1016/j.jrurstud.2018.02.009 · Cited by 106
Drivers and barriers of the digitalization of local owner operated retail outlets
Bollweg, L. M., Lackes, R., Siepermann, M., & Weber, P. (2019) · Journal of Small Business & Entrepreneurship · doi:10.1080/08276331.2019.1616256 · Cited by 100
Tourists’ intention to use location-based services (LBS)
Meng, B., & Choi, K. (2019) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-09-2018-0734 · Cited by 100
A Model of the Determinants of Purchasing from Virtual Stores
Barkhi, R., Bélanger, F., & Hicks, J. (2008) · Journal of Organizational Computing and Electronic Commerce · doi:10.1080/10919390802198840 · Cited by 101
Qi, J., Li, L., Li, Y., & Shu, H. (2009) · Systems Research and Behavioral Science · doi:10.1002/sres.964 · Cited by 105
The influence of teachers’ conceptions of teaching and learning on their technology acceptance
Teo, T. P., & Zhou, M. (2016) · Interactive Learning Environments · doi:10.1080/10494820.2016.1143844 · Cited by 122
Digital divide at individual level: Evidence for Eastern and Western European countries
Chipeva, P., Cruz‐Jesus, F., Oliveira, T., & Zahir Irani, A. (2018) · Government Information Quarterly · doi:10.1016/j.giq.2018.06.003 · Cited by 111
ESG and FinTech: Are they connected?
Galeone, G., Ranaldo, S., & Fusco, A. (2024) · Research in International Business and Finance · doi:10.1016/j.ribaf.2024.102225 · Cited by 99
Yang, C., Hsu, Y.-C., & Tan, S. (2009) · CyberPsychology & Behavior · doi:10.1089/cyber.2009.0105 · Cited by 108
Understanding factors affecting e-reverse auction use: An integrative approach
Gümüşsoy, Ç. A., & Çalışır, F. (2009) · Computers in Human Behavior · doi:10.1016/j.chb.2009.04.006 · Cited by 102
Investigating gameplay intention of the elderly using an Extended Technology Acceptance Model (ETAM)
Wang, Q., & Sun, X. S. (2016) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2015.10.024 · Cited by 102
Laumer, S., Maier, C., Eckhardt, A., & Weitzel, T. (2016) · European Journal of Information Systems · doi:10.1057/ejis.2016.1 · Cited by 100
Huang, K.-L., Liu, Y., & Dong, M.-Q. (2024) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2024.101508 · Cited by 112
Luo, Y., Lin, J., & Yang, Y. (2021) · Zeitschrift für Erziehungswissenschaft · doi:10.1007/s11618-021-01042-3 · Cited by 139
Liu, Y., Lu, X., Zhao, G., Li, C., & Shi, J. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.944976 · Cited by 110
Technology acceptance in the banking industry
Anandarajan, M., Igbaria, M., & Anakwe, U. P. (2000) · Information Technology and People · doi:10.1108/09593840010359491 · Cited by 100
Einwiller, S. A. (2003) · Electronic Markets · doi:10.1080/1019678032000092246 · Cited by 97
Gallivan, M. J. (2003) · Information & Management · doi:10.1016/s0378-7206(02)00039-3 · Cited by 98
Consumers’ anti-consumption behavior toward organic food purchase: an analysis using SEM
Ashraf, M., Joarder, M. H. R., & Ratan, S. R. A. (2018) · British Food Journal · doi:10.1108/bfj-02-2018-0072 · Cited by 100
Evaluating the Factors Affecting DSS Usage by Senior Managers in Local Authorities in Egypt
Elbeltagi, I. M., McBride, N. K., & Hardaker, G. (2005) · Journal of Global Information Management · doi:10.4018/jgim.2005040103 · Cited by 94
ROLE OF SELF-EFFICACY IN E-LIBRARY USAGE AMONG STUDENTS OF A PUBLIC UNIVERSITY IN MALAYSIA
Ramayah, T., & Aafaqi, B. (2004) · Malaysian Journal of Library & Information Science · Cited by 93
Internet Banking Adoption in an Emerging Economy: Indian Consumer's Perspective
Safeena, R., Date, H., & Kammani, A. (2011) · Int. Arab. J. e Technol. · Cited by 94
Ball, D. M., & Levy, Y. M. (2008) · Journal of the Association for Information Systems · Cited by 93
Nam, C. S., Bahn, S., & Lee, R. (2013) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2012.711990 · Cited by 94
Exploring the online buying behavior of specialty food shoppers
Liang, A. R.-D., & Lim, W. M. (2011) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2011.01.006 · Cited by 92
Sánchez‐Prieto, J. C., Cruz-Benito, J., Therón, R., & Peñalvo, F. J. G. (2020) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2020.11.009 · Cited by 106
Barchielli, C., Marullo, C., Bonciani, M., & Vainieri, M. (2021) · BMC Health Services Research · doi:10.1186/s12913-021-06628-5 · Cited by 80
Ong, A. K. S., Prasetyo, Y. T., Salazar, J. M. L., Erfe, J. J. C., Abella, A. A., Young, M. N., Chuenyindee, T., Nadlifatin, R., & Redi, A. A. N. P. (2021) · Nuclear Engineering and Technology · doi:10.1016/j.net.2021.08.032 · Cited by 92
Vanneste, D., Vermeulen, B., & Declercq, A. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-129 · Cited by 91
A Critical Review of Models and Theories in Field of Individual Acceptance of Technology
Al‐Mamary, Y. H., Al‐Nashmi, M. M., Hassan, Y. A. G., & Shamsuddin, A. (2016) · International Journal of Hybrid Information Technology · doi:10.14257/ijhit.2016.9.6.13 · Cited by 94
Al‐Shafi, S., & Weerakkody, V. (2009) · European Conference on Information Systems · Cited by 90
Gao, T., Rohm, A. J., Sultan, F., & Huang, S. (2012) · Thunderbird International Business Review · doi:10.1002/tie.21452 · Cited by 90
On data-driven decision-making for quality education
Kurilovas, E. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.11.003 · Cited by 90
A theory-grounded framework of Open Source Software adoption in SMEs
Macredie, R. D., & Mijinyawa, K. (2011) · European Journal of Information Systems · doi:10.1057/ejis.2010.60 · Cited by 90
Intention does not always Matter: The Contingent Role of Habit in IT Usage Behaviour.
Limayem, M., Hirt, S. G., & Chin, W. W. (2001) · European Conference on Information Systems · Cited by 89
Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study
Askari, M., Klaver, N. S., van Gestel, T. J., & van de Klundert, J. J. (2020) · Journal of Medical Internet Research · doi:10.2196/18080 · Cited by 82
Including subjective norm and technology trust in the technology acceptance model
Lee, C., & Wan, G. (2010) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/1899639.1899642 · Cited by 107
The Role of Internet Self-Efficacy in the Acceptance of Web-Based Electronic Medical Records
Ma, Q., & Liu, L. (2005) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.2005010103 · Cited by 89
Hamner, M. P., & Qazi, R.-U.-R. (2008) · Government Information Quarterly · doi:10.1016/j.giq.2007.12.003 · Cited by 89
Examining the Success of Websites beyond E-Commerce: An Extension of the is Success Model
Schaupp, L. C., Bélanger, F., & Fan, W. (2009) · Journal of Computer Information Systems · doi:10.1080/08874417.2009.11645339 · Cited by 89
Abbasi, M. S., Tarhini, A., Elyas, T., & Shah, F. (2015) · Journal of Enterprise Information Management · doi:10.1108/jeim-12-2014-0124 · Cited by 125
Iqbal, S., & Bhatti, Z. A. (2015) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v16i4.2351 · Cited by 96
An Assessment of E-Training Effectiveness in Multinational Companies in Malaysia
Ramayah, T., Ahmad, N. H., & Hong, T. S. (2012) · Educational Technology & Society · Cited by 88
Venkatesh, V., Davis, F. D., & Zhu, Y. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102644 · Cited by 99
User acceptance of SMS-based e-government services: Differences between adopters and non-adopters
Susanto, T. D., & Goodwin, R. (2013) · Government Information Quarterly · doi:10.1016/j.giq.2013.05.010 · Cited by 100
Liu, X. (2009) · Communication Education · doi:10.1080/03634520903431745 · Cited by 93
Deng, X. N., & Chi, L. (2012) · Journal of Management Information Systems · doi:10.2753/mis0742-1222290309 · Cited by 94
Cultural Factors in a Mobile Phone Adoption and Usage Model
van Biljon, J. V., & Kotzé, P. (2008) · Journal of universal computer science (Online) · doi:10.3217/jucs-014-16-2650 · Cited by 118
Review of relationships among variables in TAM
Li, Y., Qi, J., & Shu, H. (2008) · Tsinghua Science & Technology · doi:10.1016/s1007-0214(08)70044-0 · Cited by 91
An extended online purchase intention model for middle-aged online users
Law, M., Kwok, R. C.-W., & Ng, M. (2016) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2016.10.005 · Cited by 92
Mäntymäki, M., & Riemer, K. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2013.12.010 · Cited by 112
Understanding online social support and its antecedents: A socio-cognitive model
Lin, C., & Bhattacherjee, A. (2009) · The Social Science Journal · doi:10.1016/j.soscij.2009.03.004 · Cited by 87
User acceptance factors of hospital information systems and related technologies: Systematic review
Handayani, P. W., Hidayanto, A. N., & Budi, I. D. (2017) · Informatics for Health and Social Care · doi:10.1080/17538157.2017.1353999 · Cited by 96
Determinants of information system quality and data quality in management accounting
Knauer, T., Nikiforow, N., & Wagener, S. (2020) · Journal of Management Control · doi:10.1007/s00187-020-00296-y · Cited by 131
Exploring Gender Influence on Customer's Intention to Engage Permission-based Mobile Marketing
Karjaluoto, H., Lehto, H., Leppäniemi, M., & Jayawardhena, C. (2008) · Electronic Markets · doi:10.1080/10196780802265793 · Cited by 90
An empirical investigation of factors influencing the adoption of data mining tools
Huang, T. C.-K., Liu, C., & Chang, D.-C. (2011) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2011.11.006 · Cited by 90
Xu, J., & Quaddus, M. (2011) · Knowledge-Based Systems · doi:10.1016/j.knosys.2011.10.003 · Cited by 86
Hong, J.-C., Hwang, M.-Y., Hsu, H.-F., Wong, W.-T., & Chen, M.-Y. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.04.011 · Cited by 85
AN INTEGRATED APPROACH TO MEASURE WEB SITE EFFECTIVENESS IN THE EUROPEAN HOTEL INDUSTRY
Scharl, A., Wöber, K. W., & Bauer, C. A. (2003) · Information Technology & Tourism · doi:10.3727/1098305032781157 · Cited by 86
IT Feature Use over Time and its Impact on Individual Task Performance
Benlian, A. (2015) · Journal of the Association for Information Systems · doi:10.17705/1jais.00391 · Cited by 93
Stols, G., Ferreira, R., Pelser, A. J., Olivier, W. A., der Merwe, A. V., de Villiers, C., & Venter, S. J. (2015) · South African Journal of Education · doi:10.15700/saje.v35n4a1209 · Cited by 84
Determinants of Technology Acceptance: Two Model-Based Meta-Analytic Reviews
Feng, G. C., Su, X., Lin, Z. C., He, Y., Luo, N., & Zhang, Y. (2020) · Journalism & Mass Communication Quarterly · doi:10.1177/1077699020952400 · Cited by 111
Hsiao, C., & Chiou, J. (2012) · Information & Management · doi:10.1016/j.im.2012.09.002 · Cited by 84
Naspetti, S., Mandolesi, S., Buysse, J., Latvala, T., Nicholas, P., Padel, S., Loo, E. J. V., & Zanoli, R. (2017) · Sustainability · doi:10.3390/su9101805 · Cited by 84
Voice-Based AI in Call Center Customer Service: Evidence from a Field Experiment
Wang, L., Huang, N., Hong, Y., Liu, L., Guo, X., & Chen, G. (2020) · Production and Operations Management · doi:10.1111/poms.13953 · Cited by 112
Conjoint analysis of drivers and inhibitors of e-commerce adoption
Chaparro-Peláez, J., Agudo-Peregrina, Á. F., & Pascual-Miguel, F. J. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2015.10.092 · Cited by 83
Knabe, A. P. (2012) · e-Publications@Marquette (Marquette University) · Cited by 81
Abbas, H. A., & Hamdy, H. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.03.035 · Cited by 73
Cheng, Y., Yu, T. F., Huang, C. F., Yu, C., & Yu, C. C. (2011) · iBusiness · doi:10.4236/ib.2011.32021 · Cited by 81
User Acceptance of Voice Recognition Technology
Simon, S. J., & Paper, D. J. (2007) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.2007010102 · Cited by 82
Why Do Consumers Go Internet Shopping Again? Understanding the Antecedents of Repurchase Intention
Chen, Y. (2012) · Journal of Organizational Computing and Electronic Commerce · doi:10.1080/10919392.2012.642234 · Cited by 81
Exploring the impact of online service quality on portal site usage
Lin, C.-K., & Wu, S. (2003) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2002.994223 · Cited by 80
Meng, B., & Han, H. (2016) · Asia Pacific Journal of Tourism Research · doi:10.1080/10941665.2015.1129979 · Cited by 86
Implementing innovations within organizations: a systematic review and research agenda
Kim, J. S., & Chung, G. H. (2017) · Innovation · doi:10.1080/14479338.2017.1335943 · Cited by 91
Perceived system performance: a test of an extended technology acceptance model
Liu, L., & Ma, Q. (2006) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/1161345.1161354 · Cited by 80
Factors influencing the adoption of internet banking: a case study of commercial banks in Mauritius
Juwaheer, T. D., Pudaruth, S., & Ramdin, P. (2012) · World Journal of Science Technology and Sustainable Development · doi:10.1108/20425941211250552 · Cited by 80
Enabling agile adoption practices through network organizations
Hovorka, D. S., & Larsen, K. R. T. (2006) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000606 · Cited by 80
Chorpita, B. F., Park, A. L., Tsai, K. H., Korathu-Larson, P. A., Higa-McMillan, C. K., Nakamura, B. J., Weisz, J. R., & Krull, J. L. (2015) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0039301 · Cited by 81
Consumer’s webrooming conduct: an explanation using the theory of planned behavior
Arora, S., & Sahney, S. (2018) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-08-2017-0185 · Cited by 99
Ameen, N., Willis, R., & Shah, M. H. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.07.045 · Cited by 83
Binyamin, S. S., & Hoque, M. R. (2020) · Sustainability · doi:10.3390/su12229605 · Cited by 79
User acceptance of wireless technology in organizations: A comparison of alternative models
Wu, C.-S., Cheng, F.-F., Yen, D. C., & Huang, Y. (2010) · Computer Standards & Interfaces · doi:10.1016/j.csi.2010.03.002 · Cited by 90
The determinants of customer interactions with internet-enabled e-banking services
Liao, Z., & Wong, W. (2007) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2602429 · Cited by 82
Diffusion of ICT and SME Performance
Azam, M. S. (2015) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1069-096420150000023005 · Cited by 100
Determinants adoption of computer-assisted auditing tools (CAATs)
Pedrosa, I., Costa, C. J. D. C., & Aparício, M. (2019) · Cognition Technology & Work · doi:10.1007/s10111-019-00581-4 · Cited by 100
Metadata
- Authors
- Taylor, S., & Todd, P.
- Affiliations
- Queen's University (CA)
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 1995-12-01
- Volume
- 19
- Issue
- 4
- Pages
- 561-570
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1503436739
- Cited by
- 2,891
- References
- 25
- Citations by year
- 2026: 63 · 2025: 96 · 2024: 107 · 2023: 109 · 2022: 130 · 2021: 157 · 2020: 124 · 2019: 132 · 2018: 137 · 2017: 110 · 2016: 128 · 2015: 175 · 2014: 182 · 2013: 147 · 2012: 156
- FWCI
- 19.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- MIS Quarterly (publishedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Gender Studies › Gender and Technology in Education
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Keywords
- information technology use, technology acceptance model, prior experience, user experience, user behavior prediction, inexperienced users, social influence, controlling factors, attitudinal factors
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