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

doi:10.1080/08874417.2016.1164497

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 Publication › Article › peer-review

88 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 language	English
Pages (from-to)	352-370
Number of pages	19
Journal	Journal of Computer Information Systems
Volume	56
Issue number	4
DOIs	https://doi.org/10.1080/08874417.2016.1164497
Publication status	Published - 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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10.1080/08874417.2016.1164497

Cite this

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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.",

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AU - Chong, Alain Yee Loong

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

Abstract

Keywords

ASJC Scopus subject areas

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