IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-030-94617-3_13.html
   My bibliography  Save this book chapter

Best Regional Practices for Digital Transformation in Industry: The Case of the Industry 4.0 Program in Portugal

In: Digital Transformation in Industry

Author

Listed:
  • Luciana Peixoto Santa Rita

    (Federal University of Alagoas)

  • Joaquim Ramos Silva

    (University of Lisboa)

  • Reynaldo Rubem Ferreira Junior

    (Federal University of Alagoas)

Abstract

The Portuguese government, through its program for Industry 4.0, Portugal I4.0, has been supporting projects aimed at the digital transformation of the economy by mobilizing European funds and governmental subsidies from the Portugal 2020 Program. The objective of this study is to analyze the best regional practices for digital transformation in the industry 4.0 in this context. The following research questions arise: which are the best practices for digital transformation in Portugal under this Program and what was the impact on the competitiveness of Portuguese industries after the implementation of these technologies through the Incentive Value from 2017 to 2019? The methodological approach is correlational, and it establishes a relationship between the I4.0 Incentive Value and Competitiveness in order to identify the best regional practices for digital trans-formation in the Portuguese industry. The hypothesis of this study is accepted for the period 2017–2019, since the factors that make up the industry 4.0—European Fund—Incentive Value dimension are associated to the degree of competitive-ness, which was measured by a set of related variables. Further studies are necessary for longer periods and with a broader scope, the result shows the relevance of the Program.

Suggested Citation

  • Luciana Peixoto Santa Rita & Joaquim Ramos Silva & Reynaldo Rubem Ferreira Junior, 2022. "Best Regional Practices for Digital Transformation in Industry: The Case of the Industry 4.0 Program in Portugal," Lecture Notes in Information Systems and Organization, in: Vikas Kumar & Jiewu Leng & Victoria Akberdina & Evgeny Kuzmin (ed.), Digital Transformation in Industry, pages 163-181, Springer.
  • Handle: RePEc:spr:lnichp:978-3-030-94617-3_13
    DOI: 10.1007/978-3-030-94617-3_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:978-3-030-94617-3_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.