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Determinants of users' intention to adopt wireless technology: An empirical study by integrating TTF with TAM

Authors:

Yu-Wen HuangAuthors Info & Claims

Computers in Human Behavior, Volume 26, Issue 5

Pages 906 - 915

https://doi.org/10.1016/j.chb.2010.02.005

Published: 01 September 2010 Publication History

Abstract

This paper reported the results of a survey study and provided evidences of empirically testing a model that integrates both technology acceptance model (TAM) and task-technology fit (TTF) model in understanding the determinants of users' intention to use wireless technology in organizations. Questionnaires were distributed to organizations that bring mobile commerce into practice through the wireless handheld devices. The results indicated that both technology acceptance model and task-technology fit model are robust models by themselves. First, both perceived usefulness and ease of use significantly influence users' behavior intention to utilize wireless technology. Perceived ease of use has significant effect on perceived usefulness. Second, characteristics of technology and task significantly predict the fit between these two constructs. Significant effect of characteristics of technology on perceived ease of use and usefulness were observed. Finally, significant relationships between TAM and TTF model were also observed. Task-technology fit is a significant direct predictor of technology adoption intention. Overall, users' intention to adopt wireless technology in organizations was determined directly by fit between characteristics of task and technology as well as users' perceived ease of use and usefulness.

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Cited By

Wijaya LNg KCheng KSihombing P(2024)Telemedicine Application Continuance Usage based on TTF and UTAUT Theories: An Empirical Study IndonesiaProceedings of the 2024 7th International Conference on Computers in Management and Business10.1145/3647782.3647807(165-172)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3647782.3647807
Almusawi HDurugbo C(2024)Linking task-technology fit, innovativeness, and teacher readiness using structural equation modellingEducation and Information Technologies10.1007/s10639-023-12440-x29:12(14899-14928)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10639-023-12440-x
Zuo MYan YMa YLuo H(2024)Modeling the factors that influence schoolteachers’ work engagement and continuance intention when teaching onlineEducation and Information Technologies10.1007/s10639-023-12186-629:8(9091-9119)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10639-023-12186-6
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Published In

cover image Computers in Human Behavior

Computers in Human Behavior Volume 26, Issue 5

September, 2010

439 pages

ISSN:0747-5632

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Copyright © Elsevier Ltd © 2010.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 September 2010

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Cited By

Wijaya LNg KCheng KSihombing P(2024)Telemedicine Application Continuance Usage based on TTF and UTAUT Theories: An Empirical Study IndonesiaProceedings of the 2024 7th International Conference on Computers in Management and Business10.1145/3647782.3647807(165-172)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3647782.3647807
Almusawi HDurugbo C(2024)Linking task-technology fit, innovativeness, and teacher readiness using structural equation modellingEducation and Information Technologies10.1007/s10639-023-12440-x29:12(14899-14928)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10639-023-12440-x
Zuo MYan YMa YLuo H(2024)Modeling the factors that influence schoolteachers’ work engagement and continuance intention when teaching onlineEducation and Information Technologies10.1007/s10639-023-12186-629:8(9091-9119)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10639-023-12186-6
Lee HChiu SChen YLin HLin T(2022)Determinants of Foreign Language Teachers’ Intention to Adopt Online Teaching: An empirical study by the combined model of TAM and TTFProceedings of the 6th International Conference on Digital Technology in Education10.1145/3568739.3568781(249-253)Online publication date: 16-Sep-2022
https://dl.acm.org/doi/10.1145/3568739.3568781
Fink ASpoden CFrey A(2022)Determinants of higher education teachers’ intention to use technology-based examsEducation and Information Technologies10.1007/s10639-022-11435-428:6(6485-6513)Online publication date: 17-Nov-2022
https://dl.acm.org/doi/10.1007/s10639-022-11435-4
Alarabiat AAlzyadat AWahbeh N(2021)The suitability of Facebook as a digital platform for constantly perform e-Participation activitiesProceedings of the 14th International Conference on Theory and Practice of Electronic Governance10.1145/3494193.3494307(381-390)Online publication date: 6-Oct-2021
https://dl.acm.org/doi/10.1145/3494193.3494307
Chaurasia PMcClean SNugent CCleland IZhang SDonnelly MScotney BSanders CSmith KNorton MTschanz J(2021)Modelling mobile-based technology adoption among people with dementiaPersonal and Ubiquitous Computing10.1007/s00779-021-01572-x26:2(365-384)Online publication date: 3-May-2021
https://dl.acm.org/doi/10.1007/s00779-021-01572-x
Sun SXiong CChang V(2019)Acceptance of Information and Communication Technologies in EducationInternational Journal of Enterprise Information Systems10.4018/IJEIS.201901010215:1(24-44)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.4018/IJEIS.2019010102
Alqatan SNoor NMan MMohemad R(2019)An empirical study on factors affecting the acceptance of M-commerce application among small and medium-sized tourism enterprises by integrating TTF with TAMInternational Journal of Business Information Systems10.1504/ijbis.2019.09952931:1(106-135)Online publication date: 1-Jan-2019
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Yu YChen Q(2019)An Empirical Study on the Influencing Factors of the Continued Usage of Fitness AppsSmart Health10.1007/978-3-030-34482-5_11(117-133)Online publication date: 1-Jul-2019
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