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

103 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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/08874417.2016.1164497

Cite this

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

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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author = "Hew, {Teck Soon} and Leong, {Lai Ying} and Ooi, {Keng Boon} and Chong, {Alain Yee Loong}",

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T2 - A two-stage sem-artificial-neural-network analysis

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AU - Ooi, Keng Boon

AU - Chong, Alain Yee Loong

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Artificial neural networks

KW - Mobile entertainment adoption

KW - Perceived financial cost

KW - Quality of service

KW - Trust

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

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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