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The emergence of a variety of digital devices has changed the way people interact with digital services. Continuous interaction is considered to be one of the important interactions in multi-screen services. Therefore, this study aims to identify the factors affecting people's acceptance of multi-screen services in continuous interaction. A research model was constructed based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) to conceptualize continuous interaction with user intention and to reveal significant relationships with behavioral constructs. Data collected from 203 multi-screen users were used to test the proposed research model. The result identified perceived synchronization and perceived seamless migration in continuous interaction as two important determinants in continuous interaction. Also, the model in this study demonstrated how continuous interaction affects user intention and the results indicated that among all factors, perceived seamless migration, perceived usefulness and user attitude are the strongest predictors that influence the decision to use multi-screen services. To conclude, this study is important in finding the gaps between continuous interaction and user intention, as well as in identifying areas for improvement when designing effective multi-screen services.
Keywords:
Continuous interaction, Multi-screen service, Synchronization, Seamless migration, User intention, Technology acceptance model, Theory of planned behavior
Cite Article:
"Factors affecting user intention in continuous interaction: A structural model", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.5, Issue 6, page no.50 - 63, June-2020, Available :http://www.ijrti.org/papers/IJRTI2006009.pdf
Downloads:
000204833
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator