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AuthorAl-Yafi, Karim
AuthorEl-Masri, Mazen
AuthorKamal, Muhammad Mustafa
Available date2022-10-30T08:39:29Z
Publication Date2022-03-30
Publication NameInformation Systems Frontiers
Identifierhttp://dx.doi.org/10.1007/s10796-022-10256-7
CitationEl-Masri, M., Al-Yafi, K., & Kamal, M. M. (2023). A task-technology-identity fit model of smartwatch utilisation and user satisfaction: A hybrid SEM-neural network approach. Information Systems Frontiers, 25(2), 835-852.
ISSN1387-3326
URIhttp://hdl.handle.net/10576/35582
AbstractSmartwatches are wearable devices intended to be smartphone companions that capture health data and ease access to notifications. They have also become personalisable standing as a fashion statement. This combination resulted in staggering adoption rates recently leading to question whether smartwatch users’ choice and use satisfaction emerge from utility features or from its fashion characteristics. This paper proposes and validates a fit theory to investigate the antecedents of adopters’ satisfaction. Besides evaluating fit with identity, the model assesses both perceived and actual task-technology fit of smartwatches. A questionnaire-based quantitative approach is used to collect data from about 300 smartwatch users in Qatar. To test the proposed model, data is analysed using structural equation modeling (SEM) and artificial neural networks (ANN). Furthermore, ANN sensitivity analysis ranks the importance of the fit factors affecting users’ choice during pre- and post-adoption stages. Both task-technology and technology-identity fit factors are quasi-equally important in explaining 62% of satisfaction variance. ANN analysis revealed that post-adoption satisfaction is primarily attributed to smartwatches’ ability to fit with users’ identity and secondarily to its perceived fit with tasks. Nevertheless, pre-adoption choice of smartwatches is mainly guided by their functionality. This paper is the first to propose and validate an integrated task-technology-identity fit model to explain smartwatch utilization and users’ satisfaction. The originality also lies in assessing actual task-technology fit and as perceived by users. Employing two modes of analysis revealed extra insights too.
Languageen
PublisherSpringer
SubjectSmartwatch
Task-Technology Fit
Technology-identity fit
Utilisation
Satisfaction
TitleA Task-Technology-Identity Fit Model of Smartwatch Utilization and User Satisfaction: A Hybrid SEM-Neural Network Approach
TypeArticle
Pagination835-852
ESSN1572-9419
dc.accessType Open Access


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