IDEAS home Printed from https://ideas.repec.org/a/taf/rajsxx/v15y2023i1p89-106.html
   My bibliography  Save this article

Developing an improved reverse engineering adoption model towards the improvement of performance in metal engineering industries

Author

Listed:
  • Yichalewal Goshime
  • Daniel Kitaw
  • Frank Ebinger
  • Kassu Jilcha

Abstract

Purpose: This research aims to develop an improved model that promotes reverse engineering /RE/ practice in metal engineering industries (MEIs). RE is one cost-effective technology transfer /TT/ and innovation method that improves organizational performance. However, only a few scholars have written on the adoption of RE models, and no one has contextualized TT and innovation models as a means to adopt RE practice. Methodology: Primarily, the study conducted a systematic literature review based on previous works to develop a conceptual model for RE adoption. To do this, the researchers conducted an intensive literature review and identified factors contributing to the model. Contextualizing TT and innovation factors and models within the new RE adoption model is also a significant part of the work. After a comparative analysis, the researchers developed the improved RE adoption model that enhances the performance of MEIs. Finding: The majority of previous related literature focuses on RE hardware, with only a few authors acknowledging the soft aspects, i.e., managerial and legal issues of RE practice. Besides, no authors contextualized factors of TT and innovation within the RE adoption. In this study, the researchers identified and clustered RE adoption factors as organizational, technological, managerial, and resource-based from previous RE adoption models and contextualization of TT and innovation adoption factors. Originality: To the best of the writers’ knowledge, no previous authors have contextualized TT and innovation models within the adoption of RE. However, such models have a substantial impact on adopting the practice. Hence, the researchers developed an improved model by examining and contextualizing the existing models that can impact MEI performance through improving product, process, and technological capabilities.

Suggested Citation

  • Yichalewal Goshime & Daniel Kitaw & Frank Ebinger & Kassu Jilcha, 2023. "Developing an improved reverse engineering adoption model towards the improvement of performance in metal engineering industries," African Journal of Science, Technology, Innovation and Development, Taylor & Francis Journals, vol. 15(1), pages 89-106, January.
  • Handle: RePEc:taf:rajsxx:v:15:y:2023:i:1:p:89-106
    DOI: 10.1080/20421338.2022.2037178
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/20421338.2022.2037178
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/20421338.2022.2037178?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

    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:taf:rajsxx:v:15:y:2023:i:1:p:89-106. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rajs .

    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.