IDEAS home Printed from https://ideas.repec.org/a/igg/jeis00/v16y2020i2p54-72.html
   My bibliography  Save this article

Predictors of Perceived Learning Outcomes, Satisfaction, and Continued Use Intention in SAP ERP-Enabled Courses

Author

Listed:
  • Yu Zhao

    (Lamar University, USA)

  • Kakoli Bandyopadhyay

    (Lamar University, USA)

  • Cynthia Barnes

    (Lamar University, USA)

Abstract

Enterprise resource planning (ERP) systems allow businesses to achieve high performance through distinctive capabilities and are one of the fastest growing areas within information systems. Many universities have adopted ERP in their management information systems (MIS) curriculum to increase the marketability of their students. Drawing on the IS success model and several constructive learning theories, this study develops a model that is predictive of students' continued ERP software use intention, satisfaction, and perceived learning outcomes. SAP is the ERP system used in this study. Business students at four mid-sized state universities in the United States were surveyed. The universities are members of the SAP University Alliance. There were 373 usable responses. Partial least squares structural equation modeling (PLS-SEM) was used to empirically test the model. The findings indicate that student motivation, perceived instructor support, and ERP system quality are strong predictors of student satisfaction, and learning outcomes. Student motivation and ERP system quality, but not perceived instructor support, are also significant predictors of continued use intention.

Suggested Citation

  • Yu Zhao & Kakoli Bandyopadhyay & Cynthia Barnes, 2020. "Predictors of Perceived Learning Outcomes, Satisfaction, and Continued Use Intention in SAP ERP-Enabled Courses," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 16(2), pages 54-72, April.
    • Handle: RePEc:igg:jeis00:v:16:y:2020:i:2:p:54-72
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEIS.2020040104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jeis00:v:16:y:2020:i:2:p:54-72. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.