What drives students to adopt m-learning apps? The role of e-WOM in signalling theory perspective

Sachin Kumar and Balbir Singh

Behaviour and Information Technology, 2023, vol. 42, issue 12, 2042-2059

Abstract: With the advent of smartphones, the means of information exchange have significantly changed. Technological innovations such as m-learning via smartphones are important for future education because they provide many benefits such as the ability to learn at any time and from any location. The study aims to investigate the student’s adoption intention of m-learning apps framed by e-WOM in the context of Signalling theory. A cross-sectional survey was conducted on university students in India. Smart-PLS 3.0 was used to analyse the data. The model explains 58.2% of the variance in user engagement from e-WOM (user-generated and marketer-generated) and 49% of the intention to use. The findings reveal that e-WOM as a signal moves from the sender (marketer in this study) to the receiver (students in the present context), which develops the m-learning app engagement, leading to trust. Furthermore, the findings confirm the impact of user trust on the adoption intention of m-learning Apps. The conclusion, implications and limitations are presented.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2022.2107950 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:42:y:2023:i:12:p:2042-2059

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2022.2107950

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().