IDEAS home Printed from https://ideas.repec.org/a/sae/manlab/v39y2014i3p249-274.html
   My bibliography  Save this article

An Analysis of Barriers for the Adoption of Cloud Computing in Education Sector

Author

Listed:
  • Tajinder Singh Sahdev
  • Murali Krishna Medudula
  • Mahim Sagar

Abstract

Cloud computing is an emerging field in information technology, aimed to have access to the IT services anytime, anywhere by authorized personnel. Having wide range of benefits for the organizations or institutes extending to diverse areas including like cost cutting, multi-tenancy, better management of business, highly automated, scalable to suite the ever-changing needs of the organizations or institutes. In the current scenario every emerging and established enterprise wants to implement cloud computing to fulfil their computing needs. If we look at the penetration of education in all regions, there is a dramatic shift from the traditional IT infrastructure offering towards cloud computing. If we go deeper it is evident that with the increase in the number of institutions offering education, cloud computing has come out as a very cost-effective solution for computing and infrastructure needs. This study is an attempt to identify and analyze the key barriers to the adoption of cloud computing in the education sector. Total interpretive structural modelling (TISM) has been used to further develop a hierarchy amongst the various key barriers to cloud adoption in the education sector. This model is intended to classify various barriers to the adoption of cloud computing and for planning of successful infusion of new technologies in the education sector.

Suggested Citation

  • Tajinder Singh Sahdev & Murali Krishna Medudula & Mahim Sagar, 2014. "An Analysis of Barriers for the Adoption of Cloud Computing in Education Sector," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 39(3), pages 249-274, August.
  • Handle: RePEc:sae:manlab:v:39:y:2014:i:3:p:249-274
    DOI: 10.1177/0258042X15572422
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0258042X15572422
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0258042X15572422?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sushil, 2018. "How to check correctness of total interpretive structural models?," Annals of Operations Research, Springer, vol. 270(1), pages 473-487, November.

    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:sae:manlab:v:39:y:2014:i:3:p:249-274. 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: SAGE Publications (email available below). General contact details of provider: http://www.xlri.ac.in/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.