Author
Listed:
- Sumedha Chauhan
- Sandeep Goyal
- Amit Kumar Bhardwaj
- Bruno S. Sergi
Abstract
This study investigates and compares the continuance intention of full-time business school students and faculty in India and Italy who moved from traditional pedagogy style to the digital classroom due to the COVID-19 pandemic. The study integrates the Expectation Confirmation Model (ECM) and Task-Technology Fit (TTF) to examine their continuance intention. Survey data was collected from 396 business school students and 130 faculty members from India and Italy and analysed using SmartPLS 3 software. The study found that perceived usefulness, satisfaction, and task-technology fit significantly impact the continuance intentions of students and faculty. Multigroup analysis of students indicates that Italian students are more driven by task-technology fit as compared to Indian students in their continuance intention; in comparison, Indian students rely more on gaining experience and knowhow on technology. Finally, the multigroup study of faculty suggests that Italian educators have a comparatively stronger orientation towards the fit between digital classroom technology and a portfolio of related tasks. In comparison, their Indian counterparts rely more on the perceived usefulness of technology. The strength of relationship between task-technology fit and continuance intention is comparatively lower for faculty as compared to students in both countries. Finally, implications for theory and practice are discussed.
Suggested Citation
Sumedha Chauhan & Sandeep Goyal & Amit Kumar Bhardwaj & Bruno S. Sergi, 2022.
"Examining continuance intention in business schools with digital classroom methods during COVID-19: a comparative study of India and Italy,"
Behaviour and Information Technology, Taylor & Francis Journals, vol. 41(8), pages 1596-1619, June.
Handle:
RePEc:taf:tbitxx:v:41:y:2022:i:8:p:1596-1619
DOI: 10.1080/0144929X.2021.1892191
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tbitxx:v:41:y:2022:i:8:p:1596-1619. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.