A Meta-analysis of Mobile Learning Adoption in Higher Education Based on Unified Theory of Acceptance and Use of Technology 3 (UTAUT3)

  • Farheen Mujeeb Khan
  • , Nidhi Singh
  • , Yuvika Gupta*
  • , Jaspreet Kaur
  • , Sandhya Banik
  • , Sangeeta Gupta
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Where past literature has studied the unified theory of acceptance and use of technology (UTAUT) model to a large extent, the research in the domain of UTAUT3 is limited. Further, different studies on m-learning acceptance in the higher education sector report different values of correlation among constructs of the model. This study fills this gap by conducting a meta-analysis to estimate the magnitude of relationships of the constructs of the UTAUT3 model from the past 20 years of study. Further, the study tries to explore the moderation effect variables, such as the influence of country, user type, data collection mode, sampling technique, sample size and publication date on the causal relationships of the constructs of UTAUT3. For the study, 39 articles reported an effect size of the five core constructs in UTAUT (performance expectancy, effort expectancy, social influence, facilitating conditions and behavioural intentions) and four extended constructs (hedonic motivation, personal innovativeness, price value and habit) have been studied and the results of the same have been consolidated. The results show a high impact of personal innovativeness, habit and performance expectancy on behavioural intention. Furthermore, a habit was found to be the strongest predictor of user adoption. The heterogeneity in data was examined by the moderator analysis. The moderators were found to have an influential impact on the relationships of the constructs of UTAUT3.The study will be crucial in bringing in new inputs to help governmental entities, education administrators and managers to formulate policies for the higher education sector that can assist in the proper and proactive adoption of innovative m-learning technologies.

Original languageEnglish
JournalVision
Early online date7 Jun 2022
DOIs
Publication statusE-pub ahead of print - 7 Jun 2022

Keywords

  • Behavioural Intention
  • Higher Education
  • M-learning
  • Meta-analysis
  • UTAUT

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management

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