IDEAS home Printed from https://ideas.repec.org/a/isv/jouijm/v4y2015i2p135-161.html
   My bibliography  Save this article

Setting Organizational Key Performance Indicators in the Precision Machine Industry

Author

Listed:
  • Mei-Hsiu Hong

    (National Chung Hsing University, Taiwan)

  • Tzong-Ru (Jiun-Shen) Lee

    (National Chung Hsing University, Taiwan)

  • Ching-Kuei Kao

    (Hsing-Kuo University of Management, Taiwan)

  • Per Hilletofth

    (Jönköping University, Sweden)

Abstract

The aim of this research is to define (or set) organizational key performance indicators (KPIs) in the precision machine industry using the concept of core competence and the supply chain operations reference (SCOR) model. The research is conducted in three steps. In the first step, a benchmarking study is conducted to collect major items of core competence and to group them into main categories in order to form a foundation for the research. In the second step, a case company questionnaire and interviews are conducted to identify the key factors of core competence in the precision machine industry. The analysis is conducted based on four dimensions and hence several analysis rounds are completed. Questionnaire data is analyzed with grey relational analysis (GRA) and resulted in 5–6 key factors in each dimension or sub-dimension. Based on the conducted interviews, 13 of these identified key factors are separated into one organization objective, five key factors of core competence and seven key factors of core ability. In the final step, organizational KPIs are defined (or set) for the five identified key factors of core competence. The most competitive core abilities for each of the five key factors are established. After that, organizational KPIs are set based on the core abilities within 3 main categories of KPIs (departmental, office grade and hierarchal) for each key factor. The developed KPI system based on organizational objectives, core competences, and core abilities allow enterprises to handle dynamic market demand and business environments, as well as changes in overall corporate objectives.

Suggested Citation

  • Mei-Hsiu Hong & Tzong-Ru (Jiun-Shen) Lee & Ching-Kuei Kao & Per Hilletofth, 2015. "Setting Organizational Key Performance Indicators in the Precision Machine Industry," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 4(2), pages 135-161.
  • Handle: RePEc:isv:jouijm:v:4:y:2015:i:2:p:135-161
    as

    Download full text from publisher

    File URL: http://www.issbs.si/press/ISSN/2232-5697/4_135-161.pdf
    File Function: full text
    Download Restriction: no
    ---><---

    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:isv:jouijm:v:4:y:2015:i:2:p:135-161. 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: Alen Ježovnik (email available below). General contact details of provider: http://www.issbs.si .

    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.