Mobile applications in government services (mG-App) from user's perspectives

A predictive modelling approach

Sujeet Kumar Sharma, Ali Al-Badi, Nripendra P. Rana, Laila Al-Azizi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Mobile applications are becoming a preferred delivery method for the government sector and contributing to more convenient and timely services to citizens. This study examines the intention to use mobile applications for the government services (mG-App) in Oman. This study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) model by including two constructs namely trust and information quality. Data were collected from 513 mobile application users across Oman. The research model was analysed in two stages. First, structural equation modelling (SEM) was employed to determine significant determinants affecting users’ acceptance of mG-App. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of determinants of acceptance of mG-App. The findings revealed that trust and performance expectancy are the strongest determinants influencing the acceptance of mG-App. The findings of this research have provided theoretical contributions to the existing research on mG-App and practical implications to decision-makers involved in the development and implementation of mG-App in in Oman.

Original languageEnglish
JournalGovernment Information Quarterly
DOIs
Publication statusAccepted/In press - Jan 1 2018

Fingerprint

Oman
acceptance
determinants
neural network
decision maker
citizen
performance

Keywords

  • Information quality
  • M-government
  • Mobile apps
  • Oman
  • Trust
  • UTAUT

ASJC Scopus subject areas

  • Sociology and Political Science
  • Library and Information Sciences
  • Law

Cite this

Mobile applications in government services (mG-App) from user's perspectives : A predictive modelling approach. / Sharma, Sujeet Kumar; Al-Badi, Ali; Rana, Nripendra P.; Al-Azizi, Laila.

In: Government Information Quarterly, 01.01.2018.

Research output: Contribution to journalArticle

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