Predicting Mobile Cross-Platform Adaptation Using a Hybrid Sem–ANN Approach
نویسندگان
چکیده
Owing to constant changes in user needs, new technologies have been introduced keep pace by building sustainable applications. Researchers and practitioners are keen understand the factors that create an attractive interface. Although use of cross-platform applications services is increasing, limited research has examined evaluated cross-platforms for developing mobile different operating systems. This study evaluates features, identifying main help adaptation when both Android iOS. Flutter React Native were selected so end-users could test their features using usability assessment model. Usability, satisfaction, navigation tested measure end-user experience. The data analyzed hybrid structural equation modeling (SEM) artificial neural network (ANN) approaches. results show a positive effect on Native, while satisfaction only Flutter. variable was also most significant predictor models. several implications makes contributions field, developers, end-users.
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ژورنال
عنوان ژورنال: Computer systems science and engineering
سال: 2022
ISSN: ['0267-6192']
DOI: https://doi.org/10.32604/csse.2022.022519