IDEAS home Printed from https://ideas.repec.org/a/ids/ijbpma/v17y2016i2p161-183.html
   My bibliography  Save this article

Towards developing a business performance management model using causal latent semantic analysis

Author

Listed:
  • Muhammad Muazzem Hossain
  • Victor R. Prybutok

Abstract

Business performance management (BPM) helps organisations achieve improved effectiveness and competitiveness by bridging the gap between strategy and execution. Though several industry-specific practitioner BPM frameworks exist, there is little research in the academia on BPM. This study fills this void by developing and testing a generic BPM model using causal latent semantic analysis on textual data obtained from both practitioner and academic sources. The BPM model developed in this study provides a structure for enhancing responsiveness and flexibility because it embodies the process of managing an organisation's strategy. Since the BPM process embodies a closed-loop process with the objective of continuously adjusting business strategies, it helps organisations to enhance their agility. Therefore, with the implementation of the BPM framework, organisations can quickly adapt to changes. This study posits that the proposed BPM model will help managers create an agile organisation that is capable of developing and increasing competitive advantage.

Suggested Citation

  • Muhammad Muazzem Hossain & Victor R. Prybutok, 2016. "Towards developing a business performance management model using causal latent semantic analysis," International Journal of Business Performance Management, Inderscience Enterprises Ltd, vol. 17(2), pages 161-183.
    • Handle: RePEc:ids:ijbpma:v:17:y:2016:i:2:p:161-183
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=75537
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijbpma:v:17:y:2016:i:2:p:161-183. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=3 .

    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.