IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-030-23665-6_13.html
   My bibliography  Save this book chapter

(Digital) Learning Models and Organizational Learning Mechanisms: Should Organizations Adopt a Single Learning Model or Multiple Ones?

In: Exploring Digital Ecosystems

Author

Listed:
  • Leonardo Caporarello

    (Bocconi University)

  • Beatrice Manzoni

    (Bocconi University)

  • Lilach Trabelsi

    (SDA Bocconi School of Management)

Abstract

Creating effective learning experiences matters for both employees and employing organizations as these experiences generate positive outcomes (e.g. improved performance). Organizations can create effective learning experiences by designing and implementing organizational learning mechanisms (OLMs). Yet, in many cases, they fail to do so. In this paper, we explore how employees perceive learning and their company’s efforts in providing OLMs. We also investigate whether the learning models (i.e. face-to-face vs. online vs. blended) that employees use to learn have an impact on their satisfaction and enjoyment, as well as their perceptions of the OLMs. We surveyed 67 employees and discovered that respondents that learn using multiple learning models, instead of just one, tend to be more satisfied with their learning experiences, and have a more positive perception of their company’s ability to put in place effective OLMs.

Suggested Citation

  • Leonardo Caporarello & Beatrice Manzoni & Lilach Trabelsi, 2020. "(Digital) Learning Models and Organizational Learning Mechanisms: Should Organizations Adopt a Single Learning Model or Multiple Ones?," Lecture Notes in Information Systems and Organization, in: Alessandra Lazazzara & Francesca Ricciardi & Stefano Za (ed.), Exploring Digital Ecosystems, pages 179-191, Springer.
  • Handle: RePEc:spr:lnichp:978-3-030-23665-6_13
    DOI: 10.1007/978-3-030-23665-6_13
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:lnichp:978-3-030-23665-6_13. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.