Cited by 3,575Technology Adoption and User BehaviourInnovation Diffusion and ForecastingGender and Technology in Education

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

Agarwal, Ritu, Prasad, Jayesh·1998·Information Systems Research

DOI 10.1287/isre.9.2.204

Open this paper in CoChat — free account

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.

Integrity signals

Registry

Crossref · 10.1287/isre.9.2.204

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations
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
Untitled work
(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
Advances in Consumer Research
(2025) · doi:10.53555/acr.v2i2 · Cited by 13,486
Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation
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

Show all 34 references

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

Sorted by citations

Items 801–900 of 1,007

Augmented Virtual Doctor Office: Theory-based Design and Assessment
Zahedi, F. M., Walia, N., & Jain, H. K. (2016) · Journal of Management Information Systems · doi:10.1080/07421222.2016.1243952 · Cited by 51
Predicting IoT Service Adoption towards Smart Mobility in Malaysia: SEM-Neural Hybrid Pilot Study
Ahmed, W., Muhamad, S., Sentosa, I., Akter, H., Yafi, E., & Ali, J. (2020) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2020.0110165 · Cited by 49
Data-driven modeling of technology acceptance: A machine learning perspective
Alwabel, A. S. A., & Zeng, X. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115584 · Cited by 64
Determinants of individuals’ intentions to use central bank digital currency: evidence from China
Liu, X., Wang, Q., Wu, G., & Zhang, C. (2022) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2022.2131517 · Cited by 48
An empirical examination of guests' adoption of interactive mobile technologies in hotels
Zhu, W. W., & Morosan, C. V. (2014) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-09-2013-0029 · Cited by 48
Sustainable IS Initialization Through Outsourcing: A Theory-Based Approach
Nedbal, D., Wetzlinger, W., Auinger, A., & Wagner, G. (2011) · Journal of the Association for Information Systems · Cited by 48
Mobile Libraries: Librarians’ and Students’ Perspectives
Aharony, N. (2014) · College & Research Libraries · doi:10.5860/crl12-415 · Cited by 48
Users' intrinsic and extrinsic drivers to use a web-based educational environment
Sánchez‐Franco, M. J., Peral, B. P., & Ramos, Á. F. V. (2014) · Computers & Education · doi:10.1016/j.compedu.2014.02.001 · Cited by 53
New technology in personnel selection: How recruiter characteristics affect the adoption of new selection technology
Oostrom, J. K., van der Linden, D., Born, M. P., & van der Molen, H. T. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.05.025 · Cited by 58
A Conceptual Model of e-Government Acceptance in Public Sector
Sang, S., & Lee, J. (2009) · International Conference on the Digital Society · doi:10.1109/icds.2009.30 · Cited by 49
A Study of Behavioral Intention for 3G Mobile Internet Technology: Preliminary Research on Mobile Learning
Phuantgthong, D., & Malisuwan, S. (2005) · The International Journal of the Computer, the Internet and Management · Cited by 48
Innovativeness: a bibliometric vision of the conceptual and intellectual structures and the past and future research directions
Marchiori, D. M., Popadiuk, S., Mainardes, E. W., & Rodrigues, R. G. (2020) · Scientometrics · doi:10.1007/s11192-020-03753-6 · Cited by 48
Effect of personal innovativeness on technology acceptance and use
Rosen, P. A. (2005) · SHAREOK (University of Oklahoma; Oklahoma State University; Central Oklahoma University) · Cited by 47
Trial-Period Technostress: A Conceptual Definition and Mixed-Methods Investigation
Maier, C., Laumer, S., Thatcher, J. B., Wirth, J., & Weitzel, T. (2022) · Information Systems Research · doi:10.1287/isre.2021.1047 · Cited by 56
Service innovation and usage intention: a cross-market analysis
Chiu, Y. H., & Hofer, K. M. (2015) · Journal of service management · doi:10.1108/josm-10-2014-0274 · Cited by 47
Users and Non-users of Smartphones for Travel: Differences in Factors Influencing the Adoption Decision
Meng, B., Kim, M.-H., & Hwang, Y. (2014) · Asia Pacific Journal of Tourism Research · doi:10.1080/10941665.2014.958508 · Cited by 50
Assessing Personality Differences in Human-Technology Interaction: An Overview of Key Self-report Scales to Predict Successful Interaction
Attig, C., Wessel, D., & Franke, T. (2017) · Interacción · doi:10.1007/978-3-319-58750-9_3 · Cited by 45
Consumer Acceptance Analysis of the Home Energy Management System
Park, E.-S., Hwang, B. Y., Ko, K., & Kim, D. (2017) · Sustainability · doi:10.3390/su9122351 · Cited by 47
Online learning usage and performance among students within public universities in Yemen
Aldholay, A. H., Abdullah, Z., Ramayah, T., Isaac, O., & Mutahar, A. M. (2018) · International Journal of Services and Standards · doi:10.1504/ijss.2018.091842 · Cited by 60
Adoption of 3D printing technology: an Innovation Diffusion Theory perspective
Marak, Z. R., Tiwari, A. K., & Tiwari, S. P. (2019) · International Journal of Innovation · doi:10.5585/iji.v7i1.393 · Cited by 48
Location selection using heat maps: Relative advantage, task-technology fit, and decision-making performance
Erskine, M. A., Khojah, M., & McDaniel, A. E. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.07.014 · Cited by 51
Determinants of individuals’ intention to use mobile health: insights from India
Pai, R. R., & Alathur, S. (2019) · Transforming Government People Process and Policy · doi:10.1108/tg-04-2019-0027 · Cited by 47
Determinants for Successful Digital Transformation
Oh, K., Kho, H.-S., Choi, Y., & Seogjun, L. (2022) · Sustainability · doi:10.3390/su14031215 · Cited by 47
The Drivers of Acceptance of Artificial Intelligence–Powered Care Pathways Among Medical Professionals: Web-Based Survey Study
Cornelissen, L., Egher, C., van Beek, V., Williamson, L., & Hommes, D. W. (2022) · JMIR Formative Research · doi:10.2196/33368 · Cited by 46
Effect of student responsiveness to instructional innovation on student engagement in semi-synchronous online learning environments: The mediating role of personal technological innovativeness and perceived usefulness
Gunness, A., Matanda, M. J., & Rajaguru, R. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104884 · Cited by 50
Technology in farming: Unleashing farmers’ behavioral intention for the adoption of agriculture 5.0
Mishra, N., Bhandari, N., Maraseni, T., Devkota, N., Khanal, G., Bhusal, B., Basyal, D. K., Paudel, U. R., & Danuwar, R. K. (2024) · PLoS ONE · doi:10.1371/journal.pone.0308883 · Cited by 68
See you on Facebook: exploring influences on Facebook continuous usage
Chen, Y. (2013) · Behaviour and Information Technology · doi:10.1080/0144929x.2013.826737 · Cited by 46
Brand image management for nonprofit organizations: Exploring the relationships between websites, brand images and donations
Huang, S., & Ku, H.-H. (2016) · Journal of electronic commerce research · Cited by 46
Effects of Stereoscopic Display on Learning and User Experience in an Educational Virtual Environment
Loup‐Escande, É., Jamet, É., Ragot, M., Erhel, S., & Michinov, N. (2016) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2016.1220105 · Cited by 46
Barriers to the development of temperate agroforestry as an example of agroecological innovation: Mainly a matter of cognitive lock-in?
Louah, L., Visser, M., Blaimont, A., & Cannière, C. D. (2017) · Land Use Policy · doi:10.1016/j.landusepol.2017.05.001 · Cited by 47
An investigation of a dynamic model of privacy trade-off in use of mobile social network applications: A longitudinal perspective
Koohikamali, M., French, A. M., & Kim, D. J. (2019) · Decision Support Systems · doi:10.1016/j.dss.2019.02.007 · Cited by 45
The ideological divide in public perceptions of self-driving cars
Peng, Y. (2020) · Public Understanding of Science · doi:10.1177/0963662520917339 · Cited by 46
Profiling early adopters of blockchain-based hotel booking applications: demographic, psychographic, and service-related factors
Strebinger, A., & Treiblmaier, H. (2022) · Information Technology & Tourism · doi:10.1007/s40558-021-00219-0 · Cited by 46
Moving beyond the direct impact of using CRM systems on frontline employees' service performance: The mediating role of adaptive behaviour
Chen, R. R., Ou, C. X., Wang, W. C., Peng, Z., & Davison, R. M. (2019) · Information Systems Journal · doi:10.1111/isj.12265 · Cited by 46
Do stressors stifle or facilitate employees' innovative use of enterprise systems: the moderating role of IT mindfulness
Wei, S., Zhu, F., & Chen, X. S. (2020) · Information Technology and People · doi:10.1108/itp-09-2019-0499 · Cited by 49
What drives consumers to use P2P payment systems? An analytical approach based on the stimulus–organism–response (S-O-R) model
Diéguez, A. I. I., Liébana-Cabanillas, F. J., Blanco‐Oliver, A., & Lara‐Rubio, J. (2023) · European Journal of Management and Business Economics · doi:10.1108/ejmbe-12-2022-0374 · Cited by 45
This (AI)n’t fair? Employee reactions to artificial intelligence (AI) in career development systems
Köchling, A., Wehner, M., & Ruhle, S. A. (2024) · Review of Managerial Science · doi:10.1007/s11846-024-00789-3 · Cited by 63
Use of Online Learning Resources in the Development of Learning Environments at the Intersection of Formal and Informal Learning: The Student as Autonomous Designer
Lebeničnik, M., Pitt, I. J., & Starčič, A. I. (2015) · Center for Educational Policy Studies Journal · doi:10.26529/cepsj.144 · Cited by 45
Disentangling Twitter’s Adoption and Use (Dis)Continuance: A Theoretical and Empirical Amalgamation of Uses and Gratifications and Diffusion of Innovations
Coursaris, C. K., Osch, W. V., Sung, J., Telecom, L., & Yun, Y. (2013) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00054 · Cited by 45
Using structural technology acceptance models to segment intended users of a new technology: Propositions and an empirical illustration
Althuizen, N. (2017) · Information Systems Journal · doi:10.1111/isj.12172 · Cited by 45
Factors affecting cloud computing adoption in the Indian school education system
Singh, J., & Mansotra, V. (2019) · Education and Information Technologies · doi:10.1007/s10639-019-09878-3 · Cited by 45
Empirical Investigation of Factors Influencing Consumer Intention to Use an Artificial Intelligence-Powered Mobile Application for Weight Loss and Health Management
Huang, C.-Y., & Yang, M. (2020) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2019.0182 · Cited by 45
PREDICTING BEHAVIOURAL RESISTANCE TO BIM IMPLEMENTATION IN CONSTRUCTION PROJECTS: AN EMPIRICAL STUDY INTEGRATING TECHNOLOGY ACCEPTANCE MODEL AND EQUITY THEORY
Wang, G., Wang, P., Cao, D., & Luo, X. (2020) · Journal of Civil Engineering and Management · doi:10.3846/jcem.2020.12325 · Cited by 45
Acceptance model for predicting adoption of Zakat, Infaq, and Sodaqoh (ZIS) digital payments in Generation Z
Oktavendi, T. W., & Mu’ammal, I. (2022) · Journal of Islamic accounting and business research · doi:10.1108/jiabr-09-2021-0267 · Cited by 45
Investigating the use of information technology in managing innovation: A case study from a university technology transfer office
Rampersad, G., Plewa, C., & Troshani, I. (2011) · Journal of Engineering and Technology Management · doi:10.1016/j.jengtecman.2011.09.002 · Cited by 47
Perceptions of chronically ill and healthy consumers about electronic personal health records: a comparative empirical investigation
Cocosila, M., & Archer, N. (2014) · BMJ Open · doi:10.1136/bmjopen-2014-005304 · Cited by 44
Validation of a TAM Extension in Agriculture: Exploring the Determinants of Acceptance of an e-Learning Platform
Jiménez, I. A. C., García, L. C. C., Marcolin, F., Violante, M. G., & Vezzetti, E. (2021) · Applied Sciences · doi:10.3390/app11104672 · Cited by 51
Understanding seller resistance to digital device recycling platform: An innovation resistance perspective
Tang, Z. R., & Chen, L. (2021) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2021.101114 · Cited by 51
Analyzing the adoption of online tourism purchases: effects of perceived tourism value and personal innovativeness
Hateftabar, F. (2022) · Current Issues in Tourism · doi:10.1080/13683500.2022.2071682 · Cited by 45
AI-Enabled Service Continuance: Roles of Trust and Privacy Risk
Salih, L., Tarhini, A., & Açikgöz, F. (2025) · Journal of Computer Information Systems · doi:10.1080/08874417.2025.2452544 · Cited by 59
Do I have to learn something new? Mental models and the acceptance of replacement technologies
Zhang, W. E., & Xu, P. (2010) · Behaviour and Information Technology · doi:10.1080/0144929x.2010.489665 · Cited by 44
The Introduction of a Novel Virtual Reality Training System for Gynecology Learning and Its User Experience Research
Chang, C.-W., Yeh, S., Li, M., & Yao, E. (2019) · IEEE Access · doi:10.1109/access.2019.2905143 · Cited by 44
The Influence of Personal Innovativeness and Price Value on Intention to Use of Electric Vehicles in Malaysia
Khazaei, H. (2019) · European Online Journal of Natural and Social Sciences · Cited by 44
Determinants and risks of intentions to use mobile applications in museums: an application of fsQCA
Carvajal-Trujillo, E., Molinillo, S., & Liébana-Cabanillas, F. J. (2020) · Current Issues in Tourism · doi:10.1080/13683500.2020.1780200 · Cited by 48
Getting in the path of the robot: Pedestrians acceptance of crossing roads near fully automated vehicles
Kaye, S.-A., Li, X., Oviedo-Trespalacios, Ó., & Afghari, A. P. (2021) · Travel Behaviour and Society · doi:10.1016/j.tbs.2021.07.012 · Cited by 44
Role of interaction quality and trust in use of AI-based voice-assistant systems
Lee, O.-K. D., Ayyagari, R., Nasirian, F., & Ahmadian, M. (2021) · Journal of Systems and Information Technology · doi:10.1108/jsit-07-2020-0132 · Cited by 44
Understanding the key antecedents of users’ continuance intention in the context of smart factory
Jo, H. (2021) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2021.1970130 · Cited by 44
What Drives Consumers’ Decisions to Use Intelligent Agent Technologies? A Systematic Review
Sidlauskiene, J. (2021) · Journal of Internet Commerce · doi:10.1080/15332861.2021.1961192 · Cited by 43
When Constructs Become Obsolete: A Systematic Approach to Evaluating and Updating Constructs for Information Systems Research
Compeau, D., Correia, J., & Thatcher, J. B. (2022) · MIS Quarterly · doi:10.25300/misq/2022/15516 · Cited by 43
Adoption of AI Chatbots in Travel and Tourism Services
Hanji, S. V., Navalgund, N. R., Ingalagi, S. S., Desai, S., & Hanji, S. S. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-3236-8_57 · Cited by 44
Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model
Sultana, N., Chowdhury, R. S., & Haque, A. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e20731 · Cited by 87
Adoption of shared autonomous vehicles: Combined effects of the external environment and personal attributes
Si, H., Duan, X., Cheng, L., & Vos, J. D. (2023) · Travel Behaviour and Society · doi:10.1016/j.tbs.2023.100688 · Cited by 43
Determinants inhibiting digital payment system adoption: an Indian perspective
Hussain, S., Gupta, S., & Bhardwaj, S. (2024) · Qualitative Research in Financial Markets · doi:10.1108/qrfm-09-2023-0223 · Cited by 54
Exploring the usage behavior of generative artificial intelligence: a case study of ChatGPT with insights into the moderating effects of habit and personal innovativeness
Wu, Q., Tian, J., & Liu, Z. (2025) · Current Psychology · doi:10.1007/s12144-024-07193-w · Cited by 49
Integrating AI in higher education: factors influencing ChatGPT acceptance among Chinese university EFL students
Moradi, H. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00530-4 · Cited by 43
Explaining factors affecting technological change adoption
Cœurderoy, R., Guilmot, N., & Vas, A. (2014) · Management Decision · doi:10.1108/md-10-2013-0540 · Cited by 43
Online complaining
Andreassen, T. W., & Streukens, S. (2013) · Managing Service Quality · doi:10.1108/09604521311287632 · Cited by 45
Determinants of online shopping: Examination of an early‐stage online market
Liebermann, Y., & Stashevsky, S. (2009) · Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · doi:10.1002/cjas.121 · Cited by 45
Reexamining Relative Advantage and Perceived Usefulness
Wang, Y., Meister, D. B., & Wang, Y. (2011) · International Journal of Information and Communication Technology Education · doi:10.4018/jicte.2011010105 · Cited by 43
Librarians' attitudes towards mobile services
Aharony, N. (2013) · Aslib Journal of Information Management · doi:10.1108/ap-07-2012-0059 · Cited by 44
Personality Traits and Privacy Perceptions: An Empirical Study in the Context of Location-Based Services
Junglas, I. A. (2006) · International Conference on Mobile Business · doi:10.1109/icmb.2006.40 · Cited by 43
Factors affecting the adoption of cloud computing in small and medium enterprises
Safari, F., Safari, N., Hassanzadeh, A., & Ghatari, A. R. (2015) · International Journal of Business Information Systems · doi:10.1504/ijbis.2015.070894 · Cited by 46
The vision integration process: Applying Rogers’ diffusion of innovations theory to leader–follower communications
Kohles, J. C., Bligh, M. C., & Carsten, M. K. (2013) · Leadership · doi:10.1177/1742715012459784 · Cited by 43
Understanding the Determinants of Cloud Computing Adoption for High Performance Computing
Lynn, T., Liang, X., Gourinovitch, A., Morrison, J. P., Fox, G., & Rosati, P. (2018) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2018.489 · Cited by 45
Understanding and Predicting Behavioral Intention to Adopt Mobile Banking
Hong, I. B. (2019) · Journal of Global Information Management · doi:10.4018/jgim.2019070110 · Cited by 47
Does Consumers’ Intention to Purchase Travel Online Differ Across Generations?
Sharma, S., Singh, G., & Pratt, S. (2020) · AJIS. Australasian journal of information systems/AJIS. Australian journal of information systems/Australian journal of information systems · doi:10.3127/ajis.v24i0.2751 · Cited by 43
An assessment of equivalence between paper and social media surveys: The role of social desirability and satisficing
Fang, J.-M., Wen, C., & Prybutok, V. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2013.09.019 · Cited by 46
U-government: a framework for the evolution of e-government
Bélanger, F., Carter, L. D., & Schaupp, L. C. (2005) · Electronic Government an International Journal · doi:10.1504/eg.2005.008333 · Cited by 43
Diffusion of virtual innovation
Fuller, M. A., Hardin, A. M., & Scott, C. L. (2007) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/1314234.1314243 · Cited by 43
Intention to Adopt AI-Powered Online Service Among Tourism and Hospitality Companies
Ho, Y., Alam, S. S., Masukujjaman, M., Lin, C., Susmit, S., & Susmit, S. (2022) · International Journal of Technology and Human Interaction · doi:10.4018/ijthi.299357 · Cited by 53
Exploring factors influencing educators’ adoption of ChatGPT: a mixed method approach
Hidayat-ur-Rehman, I., & Ibrahim, Y. (2023) · Interactive Technology and Smart Education · doi:10.1108/itse-07-2023-0127 · Cited by 59
Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to Use
Zhan, X., Abdi, N., Seymour, W., & Such, J. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637339 · Cited by 46
Perceptions and drivers of the metaverse adoption: A mixed‐methods study
Adhini, N. V., & Prasad, C. V. V. S. N. V. (2024) · International Journal of Consumer Studies · doi:10.1111/ijcs.13069 · Cited by 44
The Impact of Digital Competence and Personal Innovativeness on the Learning Behavior of Students: Exploring the Moderating Role of Digitalization in Higher Education Quality
Pan, L., Haq, S. U., Shi, X., & Nadeem, M. (2024) · SAGE Open · doi:10.1177/21582440241265919 · Cited by 77
Technologically Reflective Individuals as Enablers of Social Innovation*
Schweitzer, F. M., Rau, C., Gassmann, O., & van den Hende, E. A. (2015) · Journal of Product Innovation Management · doi:10.1111/jpim.12269 · Cited by 42
Intention to use mobile customer relationship management systems
Karjaluoto, H., Töllinen, A., Pirttiniemi, J., & Jayawardhena, C. (2014) · Industrial Management & Data Systems · doi:10.1108/imds-11-2013-0480 · Cited by 42
Examining the relationship of payment system characteristics and behavioural intention in e-payment adoption: a case of Indonesia
Hidayanto, A. N., Hidayat, L. S., Sandhyaduhita, P. I., & Handayani, P. W. (2015) · International Journal of Business Information Systems · doi:10.1504/ijbis.2015.069065 · Cited by 45
Are MIS research instruments stable? An exploratory reconsideration of the computer playfulness scale
Serenko, A., & Turel, O. (2007) · Information & Management · doi:10.1016/j.im.2007.08.002 · Cited by 42
VCR: Virtual community recommender using the technology acceptance model and the user’s needs type
Lee, H.-Y., Ahn, H., & Han, I. (2006) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.07.012 · Cited by 42
University Student Perceptions of Technology Use in Mathematics Learning
Zogheib, B., Rabaa’i, A. A., Zogheib, S., & Saheli, A. E. (2015) · Journal of Information Technology Education Research · doi:10.28945/2315 · Cited by 42
Science, Technology and Innovation through Entrepreneurship Education in the United Arab Emirates (UAE)
Hameed, I., Khan, M., Shahab, A., Hameed, I., & Qadeer, F. (2016) · Sustainability · doi:10.3390/su8121280 · Cited by 43
Contributions of mixed reality in a calligraphy learning task: Effects of supplementary visual feedback and expertise on cognitive load, user experience and gestural performance
Loup‐Escande, É., Frenoy, R., Poplimont, G., Thouvenin, I., Gapenne, O., & Mégalakaki, O. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.05.006 · Cited by 46
Are customers still with us? The influence of optimum stimulation level and IT-specific traits on mobile banking discontinuous usage intentions
Avornyo, P., Fang, J., Antwi, C. O., Aboagye, M. O., & Boadi, E. A. (2019) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.01.001 · Cited by 42
Understanding learners' completion intention of massive open online courses (MOOCs): role of personality traits and personal innovativeness
Gupta, K. P. (2021) · International Journal of Educational Management · doi:10.1108/ijem-01-2020-0042 · Cited by 44
How does personal innovativeness in the domain of information technology promote knowledge workers’ innovative work behavior?
Wu, W., & Yu, L. (2022) · Information & Management · doi:10.1016/j.im.2022.103688 · Cited by 44
An investigation of adoption intention of halal traceability system among food SMEs
Kamarulzaman, N. H., Muhamad, N. A., & Nawi, N. M. (2021) · Journal of Islamic marketing · doi:10.1108/jima-11-2020-0349 · Cited by 54
The influences of three task characteristics on innovative use of malleable IT: An extension of adaptive structuration theory for individuals
Shao, Z., & Li, X. (2022) · Information & Management · doi:10.1016/j.im.2022.103597 · Cited by 41
Technology readiness, mobile payments and gender- a reflective-formative second order approach
Mesías, J. F. T., van Klyton, A. C., & Zúñiga-Collazos, A. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2054729 · Cited by 41
Main theoretical consumer behavioural models. A review from 1935 to 2021
Paz, M. D. R., & Vargas, R. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e13895 · Cited by 62
Richness and dynamics: how to improve virtual reality tourism adoption with virtual social clues
Zhu, J., Jiang, Y., Wang, Y., Yang, Q., & Li, W. (2023) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-09-2022-0298 · Cited by 41

Authors: Agarwal, R., & Prasad, J.
Affiliations: Florida State University (US)
University of Dayton (US)
ORCID: Agarwal, Ritu
Venue: Information Systems Research
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Published: 1998-06
Volume: 9
Issue: 2
Pages: 204-215
ISSN: 1047-7047 (ISSN-L)
1526-5536
DOI: 10.1287/isre.9.2.204
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

A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks