IDEAS home Printed from https://ideas.repec.org/a/arp/tjssrr/2018p815-824.html
   My bibliography  Save this article

Verifying Theoretical Concepts of Performance Management Framework

Author

Listed:
  • Reno Renaldi Tibyan*

    (School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia)

  • Dermawan Wibisono

    (School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia Universitas Pertamina)

  • Mursyid Hasan Basri

    (School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia)

Abstract

Purpose – This paper aims to discuss the verification process of the theoretical concepts of the proposed performance management (PM) framework in practice. Design/methodology/approach – A case study based on a focus group discussion (FGD) method is used to describe the application a PM framework and the implementation of a PM system in a case organisation. Findings – The findings show that the case organisation has been applying the Balanced Scorecard framework and show that it needs to add some important aspects to the framework to support the better implementation of its PM system. Research limitations/implications – This paper is based on a single case study due to the need for an effective FGD in a selected organisation. Originality/value – The study drives the development of PM research in the use of a theoretical verification method to confirm the application of the theoretical concepts of PM framework in practice.

Suggested Citation

  • Reno Renaldi Tibyan* & Dermawan Wibisono & Mursyid Hasan Basri, 2018. "Verifying Theoretical Concepts of Performance Management Framework," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 815-824:6.
    • Handle: RePEc:arp:tjssrr:2018:p:815-824
    as

    Download full text from publisher

    File URL: https://www.arpgweb.com/pdf-files/spi6.175.815-824.pdf
    Download Restriction: no
    File URL: https://www.arpgweb.com/journal/7/special_issue/12-2018/6/4
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ward, Michael J. & Marsolo, Keith A. & Froehle, Craig M., 2014. "Applications of business analytics in healthcare," Business Horizons, Elsevier, vol. 57(5), pages 571-582.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ali, Abdul & Mancha, Ruben & Pachamanova, Dessislava, 2018. "Correcting analytics maturity myopia," Business Horizons, Elsevier, vol. 61(2), pages 211-219.
    2. Yu, Wantao & Zhao, Gen & Liu, Qi & Song, Yongtao, 2021. "Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. McIver, Derrick & Lengnick-Hall, Mark L. & Lengnick-Hall, Cynthia A., 2018. "A strategic approach to workforce analytics: Integrating science and agility," Business Horizons, Elsevier, vol. 61(3), pages 397-407.
    4. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    5. Marcel Goic & Mirko S Bozanic-Leal & Magdalena Badal & Leonardo J Basso, 2021. "COVID-19: Short-term forecast of ICU beds in times of crisis," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-24, January.
    6. Jing Wu & He Li & Zhangxi Lin & Khim-Yong Goh, 2017. "How big data and analytics reshape the wearable device market – the context of e-health," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5168-5182, September.
    7. Wang, Yichuan & Hajli, Nick, 2017. "Exploring the path to big data analytics success in healthcare," Journal of Business Research, Elsevier, vol. 70(C), pages 287-299.
    8. Singha, Sumanta & Arha, Himanshu & Kar, Arpan Kumar, 2023. "Healthcare analytics: A techno-functional perspective," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    9. Pham, Xuan & Stack, Martin, 2018. "How data analytics is transforming agriculture," Business Horizons, Elsevier, vol. 61(1), pages 125-133.

    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:arp:tjssrr:2018:p:815-824. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Managing Editor (email available below). General contact details of provider: http://arpgweb.com/?ic=journal&journal=7&info=aims .

    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.