Publication:
An integrated model for the usage and acceptance of stickers in WhatsApp through SEM-ANN approach

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dc.citedby1
dc.contributor.authorAlhumaid K.en_US
dc.contributor.authorAlnazzawi N.en_US
dc.contributor.authorAkour I.en_US
dc.contributor.authorAl Khasoneh O.en_US
dc.contributor.authorAlfaisal R.en_US
dc.contributor.authorSalloum S.en_US
dc.contributor.authorid57211713050en_US
dc.contributor.authorid57190124338en_US
dc.contributor.authorid6504754448en_US
dc.contributor.authorid57852101700en_US
dc.contributor.authorid57254272400en_US
dc.contributor.authorid57195670894en_US
dc.date.accessioned2023-05-29T09:36:37Z
dc.date.available2023-05-29T09:36:37Z
dc.date.issued2022
dc.description.abstractThis analysis integrates the �technology acceptance model (TAM)� with the �use of gratifications theory (U&G)� to develop an embedded model that predicts the use and satisfaction of emotional icons called stickers through WhatsApp. The explanation for combining these two theories is that U&G offers accurate information and a thorough knowledge of use, while TAM theory has been firmly established in several technical implementations. A newly developed hybrid analysis proce-dure has been applied within this research. Using an artificial neural network (ANN), and the structural equation model (SEM) have been combined. The research also uses the importance-perfor-mance map analysis (IPMA) to present each factor�s performance as well as importance. The ANN and IPMA research have both indicated that for sticker use intention, a highly essential predictor is Socialization. An online questionnaire survey was developed to assess the recommended model. The intention to use stickers was significantly affected by �Socialization, Self Presentation, Enjoyment, Novelty, Unique Function, Perceived Ease of Use, and Perceived Usefulness�. The research's main achievement is the convergence of two separate theories into a single conceptualization to accurately calculate the TAM components when it comes to the usage of stickers in WhatsApp. Theoretically, the recommended model provides enough insight for aspects which affect the intention to use stickers with relevance to the socialization�s factors considering interpersonal aspects. Practically, the higher education decision-makers along with professionals would extract variables that are important as compared to others and policies would be developed accordingly. The deep ANN model compe-tence has been analyzed within the research to decide upon the non-linear associations between variables of the theoretical model, methodologically. � 2022 by the authors; licensee Growing Science, Canada. � 2022 by the authors; licensee Growing Science, Canada.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.5267/j.ijdns.2022.6.008
dc.identifier.epage1272
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85136251424
dc.identifier.spage1261
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85136251424&doi=10.5267%2fj.ijdns.2022.6.008&partnerID=40&md5=981c71a14e4183ab44aa7bfa036057ba
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26771
dc.identifier.volume6
dc.publisherGrowing Scienceen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleInternational Journal of Data and Network Science
dc.titleAn integrated model for the usage and acceptance of stickers in WhatsApp through SEM-ANN approachen_US
dc.typeArticleen_US
dspace.entity.typePublication
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