The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index.
A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology
Abstract
The acceptance of new information technologies by their intended users persists as an important issue for researchers and practitioners of information systems. Several models have been developed in the literature to facilitate understanding of the process by which new information technologies are adopted. This paper proposes a new construct that further illuminates the relationships explicit in the technology acceptance models and describes an operational measure for this construct that possesses desirable psychometric properties. The construct, personal innovativeness in the domain of information technology, is hypothesized to exhibit moderating effects on the antecedents as well as the consequences of individual perceptions about a new information technology. The construct was developed and validated in the context of the innovation represented by the World-Wide Web. Implications for theory and practice are discussed.
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
“Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”
From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Agarwal and Prasad,1998
In the citing paper
“Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”
From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Agarwal and Prasad,1998
In the citing paper
“Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”
From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Agarwal and Prasad,1998
In the citing paper
“Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”
From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Agarwal and Prasad,1998
In the citing paper
“the extensive focus of TAM on technology to the neglect of social and psychological parameters (Agarwal & Prasad, 1998;Venkatesh & Bala, 2008) limits its explanatory and predictive utilities, and therefore demands its integration with other frameworks”
From Using T-O-E theoretical framework to study the adoption of ERP solution (2016) · cites this paper as Agarwal & Prasad, 1998
In the citing paper
“Personal innovativeness (PI) has been acknowledged as important factor that impact technology adoption and usage (Agarwal & Prasad, 1998).”
From Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology (2024) · cites this paper as Agarwal & Prasad, 1998
Citations
Cites
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
(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
Structural Equations with Latent Variables
Bollen, K. A. (1989) · Wiley series in probability and statistics · doi:10.1002/9781118619179 · Cited by 17,944
Structural Equations with Latent Variables.
Clogg, C. C., & Bollen, K. A. (1991) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2072165 · Cited by 17,475
Convergent and discriminant validation by the multitrait-multimethod matrix.
Campbell, D. T., & Fiske, D. W. (1959) · Psychological Bulletin · doi:10.1037/h0046016 · Cited by 17,116
Testing Structural Equation Models.
Mueller, C. W., Bollen, K. A., & Long, J. S. (1994) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2074955 · Cited by 14,211
(2025) · doi:10.53555/acr.v2i2 · Cited by 13,486
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
Flagged first, then by citations
1 of the 34 references couldn’t be matched to a known paper.
Research works printed but not linked: 9
- Brancheau J. C., 1990, Inform. Systems Res., 1, 41
- Carroll J., 1996, Comput. Canada, 22, 33
- Delmonico D., 1996, Comm. Week, 592, 46
- Jackson D. N. A., 1976, Jackson Personality Inventory Manual
- Joreskog K. G., 1993, Lisrel 8, User's Reference Guide
- Nunnally J. C., 1978, Psychometric Theory
- Rogers E. M., 1971, Communication of Innovations
- Rogers E. M., 1983, Diffusion of Innovations
- Wexler J., 1993, Computerworld, 27, 71
Cited by
Sorted by citations
Items 401–500 of 1,007
Mombeuil, C., & Uhde, H. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102384 · Cited by 123
Nguyen, D., Pietsch, M., & Gümüş, S. (2021) · Teaching and Teacher Education · doi:10.1016/j.tate.2021.103463 · Cited by 153
Can I show my skills? Affective responses to artificial intelligence in the recruitment process
Köchling, A., Wehner, M., & Warkocz, J. (2022) · Review of Managerial Science · doi:10.1007/s11846-021-00514-4 · Cited by 171
Understanding the role of user resistance on mobile learning usage among university students
Kim, H., Lee, J.-M., & Rha, J. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.05.015 · Cited by 140
Resistance to facial recognition payment in China: The influence of privacy-related factors
Liu, Y., Yan, W., & Hu, B. (2021) · Telecommunications Policy · doi:10.1016/j.telpol.2021.102155 · Cited by 121
Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance
Gao, T., Rohm, A. J., Sultan, F., & Pagani, M. (2013) · Journal of Business Research · doi:10.1016/j.jbusres.2013.05.046 · Cited by 134
Kwon, O., Choi, K.-W., & Kim, M. (2006) · Behaviour and Information Technology · doi:10.1080/01449290600709111 · Cited by 123
Adoption of travel e‐shopping in the UK
Kamarulzaman, Y. (2007) · International Journal of Retail & Distribution Management · doi:10.1108/09590550710773255 · Cited by 133
The impact of personalization and compatibility with past experience on e-banking usage
Wang, M. D., Cho, S., & Denton, T. (2017) · International Journal of Bank Marketing · doi:10.1108/ijbm-04-2015-0046 · Cited by 120
The moderating impact of gender on the acceptance of peer-to-peer mobile payment systems
Kalinić, Z., Liébana-Cabanillas, F. J., Muñoz‐Leiva, F., & Marinković, V. (2019) · International Journal of Bank Marketing · doi:10.1108/ijbm-01-2019-0012 · Cited by 120
A cross-country study of consumer innovativeness and technological service innovation
Truong, Y. (2012) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2012.10.014 · Cited by 120
Lin, Z., & Filieri, R. (2015) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2015.07.001 · Cited by 121
Consumer trust in e-commerce web sites
Beatty, P., Reay, I., Dick, S., & Miller, J. (2011) · ACM Computing Surveys · doi:10.1145/1922649.1922651 · Cited by 120
Adoption of mobile payment systems: a study on mobile wallets
Aydın, G. (2016) · Pressacademia · doi:10.17261/pressacademia.2016116555 · Cited by 131
Agogo, D., & Hess, T. J. (2018) · European Journal of Information Systems · doi:10.1080/0960085x.2018.1435230 · Cited by 121
An integrative approach for understanding Islamic home financing adoption in Malaysia
Amin, H., Abdul‐Rahman, A., & Abdul-Razak, D. (2013) · International Journal of Bank Marketing · doi:10.1108/ijbm-02-2013-0008 · Cited by 118
Employees’ Exploration of Complex Systems: An Integrative View
Liang, H., Peng, Z. C., Xue, Y., Guo, X., & Wang, N. (2015) · Journal of Management Information Systems · doi:10.1080/07421222.2015.1029402 · Cited by 126
Beza, E. A., Reidsma, P., Poortvliet, P. M., Belay, M. M., Bijen, B. S., & Kooistra, L. (2018) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2018.06.015 · Cited by 117
Alkawsi, G. A., Ali, N. B., & Baashar, Y. M. (2021) · Applied Sciences · doi:10.3390/app11083297 · Cited by 117
Analyzing the use of UTAUT model in explaining an online behaviour: Internet banking adoption
AlQeisi, K. (2009) · Brunel University Research Archive (BURA) (Brunel University London) · Cited by 118
User acceptance of Malaysian government multipurpose smartcard applications
Loo, W. H., Yeow, P. H. P., & Chong, S. (2009) · Government Information Quarterly · doi:10.1016/j.giq.2008.07.004 · Cited by 122
Crespo, A., & Martín, H. S. (2012) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2012.02.005 · Cited by 119
Jo, H. (2023) · Telematics and Informatics · doi:10.1016/j.tele.2023.102067 · Cited by 131
Testing an extended model of IT acceptance in the Chinese cultural context
Mao, E., & Palvia, P. (2006) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/1161345.1161351 · Cited by 120
Agarwal, N., & Brem, A. (2015) · International Journal of Technology Management · doi:10.1504/ijtm.2015.068224 · Cited by 115
Saprikis, V., Avlogiaris, G., & Katarachia, A. (2020) · Journal of theoretical and applied electronic commerce research · doi:10.3390/jtaer16030030 · Cited by 136
Engagement with information and communication technology and psychological well-being
O'Driscoll, M. P., Brough, P. A., Timms, C., & Sawang, S. (2010) · Research in occupational stress and well being · doi:10.1108/s1479-3555(2010)0000008010 · Cited by 122
Karimi, S. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.06.014 · Cited by 114
Kim, E., Park, M.-C., & Lee, J. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2017.08.006 · Cited by 117
Kuo, R., & Lee, G. (2010) · Behaviour and Information Technology · doi:10.1080/0144929x.2010.516018 · Cited by 119
The consumption values and consumer innovativeness on convergence products
Hur, W., Yoo, J., & Chung, T.-L. D. (2012) · Industrial Management & Data Systems · doi:10.1108/02635571211232271 · Cited by 119
Extending task technology fit with computer self-efficacy
Strong, D. M., Dishaw, M. T., & Bandy, D. B. (2006) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/1161345.1161358 · Cited by 113
E-learning adoption in the banking workplace in Indonesia
Purnomo, S. H., & Lee, Y. (2012) · Information Development · doi:10.1177/0266666912448258 · Cited by 113
Pateli, A. G., Mylonas, N., & Spyrou, A. (2020) · Sustainability · doi:10.3390/su12177132 · Cited by 132
Tian, Y., Chan, T. J., Sukı, N. M., & Kasim, M. A. (2023) · Human Behavior and Emerging Technologies · doi:10.1155/2023/5276406 · Cited by 192
Personality research in the organizational sciences
Perrewé, P. L., & Spector, P. E. (2004) · Research in personnel and human resources management · doi:10.1016/s0742-7301(02)21001-4 · Cited by 113
Examining the effects of cognitive style in individuals' technology use decision making
Chakraborty, I., Hu, P. J., & Cui, D. (2007) · Decision Support Systems · doi:10.1016/j.dss.2007.02.003 · Cited by 117
Predicting the Adoption of Location-Based Services: The Role of Trust and Perceived Privacy Risk
Xu, H., Teo, H., & Tan, B. C. Y. (2005) · Cited by 112
Predicting mobile network operators users m-payment intention
Leong, C., Tan, K., Puah, C., & Chong, S.-M. (2020) · European Business Review · doi:10.1108/ebr-10-2019-0263 · Cited by 121
Ray, S., Ow, T. T., & Kim, S. S. (2011) · Decision Sciences · doi:10.1111/j.1540-5915.2011.00316.x · Cited by 111
Xin, X., Venkatesh, V., Tam, K. Y., & Hong, S. (2010) · Management Science · doi:10.1287/mnsc.1090.1033 · Cited by 110
Tams, S., Thatcher, J. B., & Craig, K. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.07.004 · Cited by 118
Measuring e-commerce adoption behaviour among gen-Z in Jakarta, Indonesia
Lestari, D. (2019) · Economic Analysis and Policy · doi:10.1016/j.eap.2019.08.004 · Cited by 141
Gu, D., Khan, S., Khan, S. U., Khan, S. U., Xie, Y., Li, X., & Zhang, G. (2021) · SAGE Open · doi:10.1177/21582440211027565 · Cited by 123
Blockchain adoption: A study of cognitive factors underpinning decision making
Marikyan, D., Papagiannidis, S., RANA, O. F., & Ranjan, R. K. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107207 · Cited by 122
Nursing students’ behavioral intention to use online courses: A questionnaire survey
Tung, F.-C., & Chang, S.-C. (2008) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2007.09.011 · Cited by 109
Antecedents of computer self-efficacy: A study of the role of personality traits and gender
Saleem, H., Beaudry, A., & Croteau, A. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.04.017 · Cited by 114
Determinants of consumers’ intentions to use smartphones apps for flight ticket bookings
Jeon, H.-M., Ali, F., & Lee, S.-W. (2018) · Service Industries Journal · doi:10.1080/02642069.2018.1437908 · Cited by 113
Uses and gratifications of smart speakers: modelling the effectiveness of smart speaker advertising
Lee, H. J., & Cho, C.-H. (2020) · International Journal of Advertising · doi:10.1080/02650487.2020.1765657 · Cited by 117
A Framework of Mobile Banking Adoption in India
Kumar, A. R., Dhingra, S., Batra, V., & Purohit, H. K. S. (2020) · Journal of Open Innovation Technology Market and Complexity · doi:10.3390/joitmc6020040 · Cited by 160
Technology Readiness and Cryptocurrency Adoption: PLS-SEM and Deep Learning Neural Network Analysis
Alharbi, A., & Sohaib, O. (2021) · IEEE Access · doi:10.1109/access.2021.3055785 · Cited by 117
Factors Affecting Augmented Reality Adoption in the Retail Industry
Alam, S. S., Susmit, S., Lin, C., Masukujjaman, M., & Ho, Y. (2021) · Journal of Open Innovation Technology Market and Complexity · doi:10.3390/joitmc7020142 · Cited by 132
iSpy? Tailored versus Invasive Ads and Consumers’ Perceptions of Personalized Advertising
Gironda, J. T., & Korgaonkar, P. K. (2018) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2018.03.007 · Cited by 110
How functional and emotional ads drive smartwatch adoption
Krey, N., Chuah, S. H., Ramayah, T., & Rauschnabel, P. A. (2019) · Internet Research · doi:10.1108/intr-12-2017-0534 · Cited by 110
Anwar, A., Thongpapanl, N., & Ashraf, A. R. (2020) · Journal of Strategic Marketing · doi:10.1080/0965254x.2020.1786847 · Cited by 117
Examining knowledge contribution from the perspective of an online identity in blogging communities
Kim, H., Zheng, J. R., & Gupta, S. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.03.003 · Cited by 106
Mobile payment service usage: U.S. consumers’ motivations and intentions
Jung, J.-H., Kwon, E., & Kim, D. H. (2020) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2020.100008 · Cited by 117
Hari, H., Iyer, R., & Sampat, B. H. (2021) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2021.1988487 · Cited by 111
Dai, H., Luo, X. R., Liao, Q., & Cao, M. (2014) · Decision Support Systems · doi:10.1016/j.dss.2014.12.003 · Cited by 110
Understanding the emergence of wearable devices as next-generation tools for health communication
Park, E., Kim, K. J., & Kwon, S. J. (2016) · Information Technology and People · doi:10.1108/itp-04-2015-0096 · Cited by 105
Sharifzadeh, M. S., Damalas, C. A., Abdollahzadeh, G., & Ahmadi-Gorgi, H. (2017) · Crop Protection · doi:10.1016/j.cropro.2017.01.014 · Cited by 108
Developing and validating a technology upgrade model
Wang, Y.-Y., Wang, Y.-S., & Lin, T. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.07.003 · Cited by 112
Khasawneh, O. Y. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.07.007 · Cited by 122
Role of trust in customer attitude and behaviour formation towards social service robots
Corte, V. D., Sepe, F., Gürsoy, D., & Prisco, A. (2023) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2023.103587 · Cited by 115
Acceptance and use of ChatGPT in the academic community
Strzelecki, A., Cicha, K., Rizun, M., & Rutecka, P. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12765-1 · Cited by 105
Effects of innovativeness and trust on web survey participation
Fang, J., Shao, P., & Lan, G. (2008) · Computers in Human Behavior · doi:10.1016/j.chb.2008.08.002 · Cited by 106
Validation of Haptic Enabling Technology Acceptance Model (HE-TAM): Integration of IDT and TAM
Oh, J., & Yoon, S. (2014) · Telematics and Informatics · doi:10.1016/j.tele.2014.01.002 · Cited by 109
Ambient Information Visualisation and Visitors’ Technology Acceptance of Mixed Reality in Museums
Hammady, R., Ma, M., & Strathearn, C. (2020) · Journal on Computing and Cultural Heritage · doi:10.1145/3359590 · Cited by 104
How Individual Differences Influence Technology Usage Behavior? Toward an Integrated Framework
Yi, Y., Wu, Z., & Tung, L. L. (2005) · Journal of Computer Information Systems · doi:10.1080/08874417.2006.11645883 · Cited by 105
Crespo, A., & Rodríguez, I. A. R. D. B. (2007) · Interacting with Computers · doi:10.1016/j.intcom.2007.11.005 · Cited by 113
Successful System-use: It’s Not Just Who You Are, But What You Do
Gaskin, J. E., Godfrey, S., & Vance, A. (2018) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00104 · Cited by 107
Early versus potential adopters
Chiu, Y. H., Fang, S., & Tseng, C. (2010) · International Journal of Retail & Distribution Management · doi:10.1108/09590551011045357 · Cited by 103
Examining faculty and student perceptions of generative AI in university courses
Kim, J., Klopfer, M., Grohs, J. R., Eldardiry, H., Weichert, J., Cox, L. A., & Pike, D. (2025) · Innovative Higher Education · doi:10.1007/s10755-024-09774-w · Cited by 109
Jokisch, M. R., Schmidt, L. I., Doh, M., Marquard, M., & Wahl, H. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106408 · Cited by 127
Abubakre, M., Zhou, Y., & Zhou, Z.-Y. (2020) · Information Technology and People · doi:10.1108/itp-01-2020-0002 · Cited by 84
Acceptance of Virtual Reality Exergames Among Chinese Older Adults
Xu, W., Liang, H., Yu, K., Wen, S., Baghaei, N., & Tu, H. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2098559 · Cited by 107
Park, M. J., Kang, D., Rho, J. J., & Lee, D. H. (2015) · Public Management Review · doi:10.1080/14719037.2015.1066418 · Cited by 111
Perspectives and Dimensions of Consumer Innovativeness: A Literature Review and Future Agenda
Kaushik, A. K., & Rahman, Z. (2014) · Journal of International Consumer Marketing · doi:10.1080/08961530.2014.893150 · Cited by 101
Tussyadiah, I. P. (2015) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2015.1068263 · Cited by 108
Behavior intention of animation usage among university students
Dajani, D., & Hegleh, A. S. A. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e02536 · Cited by 121
An empirical study of consumers' intention to use biometric facial recognition as a payment method
Moriuchi, E. (2021) · Psychology and Marketing · doi:10.1002/mar.21495 · Cited by 108
Al‐Okaily, M. (2022) · EuroMed Journal of Business · doi:10.1108/emjb-05-2022-0100 · Cited by 104
Qu, K., & Wu, X. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12598-y · Cited by 164
Travelers' Intent to Use Mobile Technologies as a Function of Effort and Performance Expectancy
Oh, S.-J., Lehto, X. Y., & Park, J. (2009) · Journal of Hospitality Marketing & Management · doi:10.1080/19368620903235795 · Cited by 103
PDA usage in healthcare professionals: testing an extended technology acceptance model
Liang, H., Xue, Y., & Byrd, T. A. (2003) · International Journal of Mobile Communications · doi:10.1504/ijmc.2003.003992 · Cited by 98
(2012) · Cited by 100
Does it matter being innovative: Teachers’ technology acceptance
Akar, S. G. M. (2019) · Education and Information Technologies : Official Journal of the IFIP technical committee on Education · doi:10.1007/s10639-019-09933-z · Cited by 81
Towards a Cashless Society: The Imminent Role of Wearable Technology
Loh, X.-M., Lee, V., Tan, G. W., Hew, J.-J., & Ooi, K. (2019) · Journal of Computer Information Systems · doi:10.1080/08874417.2019.1688733 · Cited by 107
An empirical analysis of the determinants of 3G adoption in China
Chong, A. Y., Ooi, K., Lin, B., & Bao, H. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.10.005 · Cited by 101
Turan, A., Tunç, A. Ö., & Zehir, C. (2015) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2015.11.327 · Cited by 119
Consumer innovativeness, product innovation and smart toys
Zhang, F., Sun, S., Liu, C., & Chang, V. I. C. (2020) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2020.100974 · Cited by 101
Trust, Expertise, and E-Commerce Intermediary Adoption
Chircu, A. M., Davis, G. B., & Kauffman, R. J. (2000) · Journal of the Association for Information Systems · Cited by 98
Understanding digital entrepreneurial intentions: A capital theory perspective
Mir, A. A., Hassan, S., & Khan, S. J. (2022) · International Journal of Emerging Markets · doi:10.1108/ijoem-05-2021-0687 · Cited by 87
Elnadi, M., & Gheith, M. H. (2023) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2023.101236 · Cited by 116
Unlocking future learning: Exploring higher education students' intention to adopt meta-education
Al‐Adwan, A. S., Alsoud, M. A., Li, N., Majali, T., Smedley, J., & Habibi, A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e29544 · Cited by 111
Wang, T., Jung, C.-H., Kang, M.-H., & Chung, Y.-S. (2014) · Behaviour & Information Technology · doi:10.1080/0144929x.2013.781221 · Cited by 95
Bubou, G. M., & Job, G. C. (2020) · Journal of Research in Innovative Teaching & Learning · doi:10.1108/jrit-12-2019-0079 · Cited by 95
Yaprak, A., Uuml, Kılıç, F., & Okumuş, A. (2021) · Technological forecasting & social change · doi:10.1016/j.techfore.2021.120829 · Cited by 92
Gallivan, M. J. (2003) · Information & Management · doi:10.1016/s0378-7206(02)00039-3 · Cited by 98
Agbemabiese, G. C., Anim, P. A., & Nyanyofio, J. G. T. (2015) · Journal of Computer and Communications · doi:10.4236/jcc.2015.32001 · Cited by 107
Metadata
- Authors
- Agarwal, R., & Prasad, J.
- Affiliations
- Florida State University (US)
- University of Dayton (US)
- ORCID
- Agarwal, Ritu
- Venue
- Information Systems Research
- Published
- 1998-06
- Volume
- 9
- Issue
- 2
- Pages
- 204-215
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2162061662
- Cited by
- 3,575
- References
- 34
- Citations by year
- 2026: 213 · 2025: 256 · 2024: 262 · 2023: 231 · 2022: 234 · 2021: 233 · 2020: 206 · 2019: 146 · 2018: 173 · 2017: 128 · 2016: 143 · 2015: 178 · 2014: 165 · 2013: 161 · 2012: 149
- FWCI
- 29.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Systems Research (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- personal innovativeness, information technology adoption, technology acceptance model, moderating effect, operational measurement, psychometric validation, World Wide Web, user perception, construct definition
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
