Predicting drivers of mobile entertainment adoption: A two-stage sem-artificial-neural-network analysis

Teck Soon Hew, Lai Ying Leong, Keng Boon Ooi, Alain Yee Loong Chong

    Research output: Journal PublicationArticlepeer-review

    99 Citations (Scopus)

    Abstract

    This study aims to understand users' motivations to adopt mobile entertainment (m-entertainment). Extending the Technology Acceptance Model (TAM), this study examined the effects of trust, perceived financial cost (PFC), and quality of the service on consumers' decision in adopting the m-entertainment. Survey data were collected from 524 mobile users and analyzed using both structural equation modeling (SEM) and neural network (NN) . The result showed that perceived usefulness (PU), perceived ease of use (PEOU), and quality of service (QS) are important predictors of m-entertainment adoption. The study contributes to the existing literature by extending the TAM model as well as examining m-entertainment, an important and emerging business model in mobile commerce. A new analytical approach using both SEM and NN was also employed in this study.

    Original languageEnglish
    Pages (from-to)352-370
    Number of pages19
    JournalJournal of Computer Information Systems
    Volume56
    Issue number4
    DOIs
    Publication statusPublished - 2016

    Keywords

    • Artificial neural networks
    • Mobile entertainment adoption
    • Perceived financial cost
    • Quality of service
    • Trust

    ASJC Scopus subject areas

    • Information Systems
    • Education
    • Computer Networks and Communications

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