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

Department of Entrepreneurship, Marketing and Management Systems

Research output: Journal Publication › Article › peer-review

67 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

Access to Document

10.1080/08874417.2016.1164497

Cite this

@article{45f90175865c419ca1a726eec0160de0,

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.",

keywords = "Artificial neural networks, Mobile entertainment adoption, Perceived financial cost, Quality of service, Trust",

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

year = "2016",

doi = "10.1080/08874417.2016.1164497",

language = "English",

volume = "56",

pages = "352--370",

journal = "Journal of Computer Information Systems",

issn = "0887-4417",

publisher = "Taylor and Francis Ltd.",

number = "4",

}

TY - JOUR

T1 - Predicting drivers of mobile entertainment adoption

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

AU - Hew, Teck Soon

AU - Leong, Lai Ying

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

UR - http://www.scopus.com/inward/record.url?scp=85006377668&partnerID=8YFLogxK

U2 - 10.1080/08874417.2016.1164497

DO - 10.1080/08874417.2016.1164497

M3 - Article

AN - SCOPUS:85006377668

SN - 0887-4417

VL - 56

SP - 352

EP - 370

JO - Journal of Computer Information Systems

JF - Journal of Computer Information Systems

IS - 4

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this