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

58 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

Fingerprint

Dive into the research topics of 'Predicting drivers of mobile entertainment adoption: A two-stage sem-artificial-neural-network analysis'. Together they form a unique fingerprint.

Cite this