IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v277y2024ics0925527324002408.html
   My bibliography  Save this article

Digitally powered solution delivery: The use of IoT and AI for transitioning towards a solution business model

Author

Listed:
  • Lafuente, Esteban
  • Sallan, Jose M.

Abstract

Digitalization has played a key role in enabling the delivery of service-based solutions by facilitating customer-oriented needs-finding and personalized problem-solving capabilities. Artificial intelligence (AI) and Internet-of-Things (IoT) are decisive technologies in this process. This study evaluates how the use AI and IoT platforms impact solution delivery business models among servitized and non-servitized businesses. By running regression models on a sample of 213 Spanish businesses for 2023, it was found that the use of IoT platforms, rather than AI platforms, significantly assist companies down the analyzed solution delivery dimensions (i.e., customer embeddedness, operational adaptiveness, offering integratedness, and organizational networkedness). Additionally, results indicate that the combined use of IoT platforms when servitizing leads to greater customer embeddedness, whereas the use of AI platforms among servitized firms significantly contributes to improving operational adaptiveness.

Suggested Citation

  • Lafuente, Esteban & Sallan, Jose M., 2024. "Digitally powered solution delivery: The use of IoT and AI for transitioning towards a solution business model," International Journal of Production Economics, Elsevier, vol. 277(C).
  • Handle: RePEc:eee:proeco:v:277:y:2024:i:c:s0925527324002408
    DOI: 10.1016/j.ijpe.2024.109383
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527324002408
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2024.109383?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
    ---><---

    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:eee:proeco:v:277:y:2024:i:c:s0925527324002408. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.