Mobile learning key influencing factors adoption based on analytic hierarchy process

Mohamed Sarrab*, Hafedh Al-Shihi, Ibtisam Nasser Said Al Shib

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

From innovation adoption perspective, this paper studies learner's perceptions and willingness toward M-learning adoption and investigates the key factors affecting M-learning adoption behaviour in Oman and the Arab Gulf Region. Despite a large amount of research in the field of M-learning, there is so much research focused on analysing the relationship between the perceived innovative characteristics and willingness of M-learning adoption. Using analytic hierarchy process (AHP), 28 factors of perceived innovative characteristics have been analysed to examine the relationship among the perceived innovative characteristics and willingness of M-learning adoption. The results of a total of 806 learners from different institutes in Omani higher education that participated in this research showed that some factors of perceived innovative characteristics, such as enjoyment, flexibility, suitability, social, economic, and efficiency have more influence on learners' adoption of M-learning. The effort is part of the Omani-funded research project investigating the development, adoption and dissemination of mobile learning in Oman.

Original languageEnglish
Pages (from-to)387-404
Number of pages18
JournalInternational Journal of Information and Decision Sciences
Volume9
Issue number4
DOIs
Publication statusPublished - 2017

Keywords

  • AHP
  • Analytic hierarchy process
  • Economic
  • Efficiency
  • Enjoyment
  • Flexibility
  • M-learning
  • Mobile learning
  • Social
  • Suitability
  • Theory of innovation diffusion.

ASJC Scopus subject areas

  • Computer Science Applications
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

Fingerprint

Dive into the research topics of 'Mobile learning key influencing factors adoption based on analytic hierarchy process'. Together they form a unique fingerprint.

Cite this