IDEAS home Printed from https://ideas.repec.org/a/spr/jknowl/v15y2024i3d10.1007_s13132-023-01696-w.html
   My bibliography  Save this article

Economic Effects of Idea Generation and Idea Management System in Automotive Industry: a Quantitative Case Study for Romania

Author

Listed:
  • Cristina Veres

    (University of Medicine, Pharmacy, Science and Technology of Targu Mures)

  • Sebastian Cândea

    (University of Medicine, Pharmacy, Science and Technology of Targu Mures)

  • Manuela Rozalia Gabor

    (University of Medicine, Pharmacy, Science and Technology of Targu Mures
    University of Medicine, Pharmacy, Science and Technology of Targu Mures)

  • Laura Elly Naghi

    (Bucharest University of Economic Studies)

Abstract

In the dynamic landscape of the automotive industry, innovation is the key driver of success. Companies that actively engage in idea generation and have efficient idea management systems in place often gain a competitive edge. This article explores the importance and necessity of idea generation in the context of the automotive industry in Romania, shedding light on the economic effects it can have. Based on a review of scientific literature, the paperwork adds value by filling in a gap on continuous improvement process, idea management, and idea management system concepts, by describing in detail how Idea Management System can be introduced, and by performing a quantitative analysis, using complex statistical methods and machine learning on big data collected to observe the effects of Idea Management System use on the results and the level of employee involvement, as well as finding out a predictor of potential savings for automotive company. Very few academic papers take into consideration the economic effect of Idea Management System especially for the company’ performance (KPIs), focusing rather on performance metrics for idea management.

Suggested Citation

  • Cristina Veres & Sebastian Cândea & Manuela Rozalia Gabor & Laura Elly Naghi, 2024. "Economic Effects of Idea Generation and Idea Management System in Automotive Industry: a Quantitative Case Study for Romania," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 15094-15128, September.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:3:d:10.1007_s13132-023-01696-w
    DOI: 10.1007/s13132-023-01696-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13132-023-01696-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13132-023-01696-w?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.

    More about this item

    Keywords

    Idea management; Idea generation; Suggestion system; Continuous improvement; Company performance; Automotive industry; Inferential statistics methods; Regression model; Decision tree; Machine learning;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation

    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:spr:jknowl:v:15:y:2024:i:3:d:10.1007_s13132-023-01696-w. 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.