IDEAS home Printed from https://ideas.repec.org/a/vrs/ecoman/v16y2024i3p15-28n1002.html
   My bibliography  Save this article

Innovation processes: from linear models to artificial intelligence

Author

Listed:
  • Szymanska Elzbieta

    (Bialystok University of Technology, Wiejska 45A, 15-351 Bialystok, Poland)

  • Berbel-Pineda Juan Manuel

    (University in Sevilla, De Utrera 1, 41013 Sevilla, Spain)

Abstract

This study aims to map scientific publications, intellectual structure and research trends in the development of innovation process models and to characterise and compare them. Specifically, to identify the innovation process models and their characteristics, comparative analysis of the models, and predict the direction of development. A hybrid method was used, which involved many years of in-depth literature monitoring and comparative analysis based on a set of parameters developed by the authors. The results made it possible to identify and classify 15 various theoretical models of the innovation process (from M1 — linear to M15 with the AI contribution) development through categorisation according to five main features: C1 — complexity, C2 — openness, C3 — the role of technology, C4 — the participation of the market/users, and C5 — the form of presentation. This study identifies, explores, analyses and summarises the main ideas of innovation processes by identifying their models and characterising those specifics that can ensure international standards of excellence. The study provides an objective view of the existing innovation process models and the relevant studies that can guide managers in their decision-making innovation processes. This study is a first attempt at unveiling the evolution of knowledge in the field of existing innovation processes and their characteristics and comparative analysis. The presented models of innovation processes should constitute an indication for practitioners who can choose a model to be used in the economic practice of their organisation.

Suggested Citation

  • Szymanska Elzbieta & Berbel-Pineda Juan Manuel, 2024. "Innovation processes: from linear models to artificial intelligence," Engineering Management in Production and Services, Sciendo, vol. 16(3), pages 15-28.
  • Handle: RePEc:vrs:ecoman:v:16:y:2024:i:3:p:15-28:n:1002
    DOI: 10.2478/emj-2024-0021
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/emj-2024-0021
    Download Restriction: no

    File URL: https://libkey.io/10.2478/emj-2024-0021?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
    ---><---

    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:vrs:ecoman:v:16:y:2024:i:3:p:15-28:n:1002. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.