IDEAS home Printed from https://ideas.repec.org/a/ids/ijbisy/v4y2009i5p542-563.html
   My bibliography  Save this article

A hybrid GA-ant colony approach for exploring the relationship between IT and firm performance

Author

Listed:
  • A. Azadeh
  • A. Keramati
  • H. Panahi

Abstract

Several studies were conducted during recent years on exploring the impact of Information Technology (IT) on the performance of the organisation. It is quite important to find a robust technique to identify the relationship between IT and organisational performance. A hybrid Genetic Algorithm (GA) Ant Colony Optimisation (ACO) approach is proposed for data clustering. This is because of the need for the application of metaheurisitic algorithms parallel to deterministic approaches. This study discusses and analyses data from 90 companies in a unique supply chain. The data includes 26 indices about IT and 11 indices about performance. The companies are classified with respect to the IT and performance indices (indicators). Then, IT clusters and performance clusters are mapped to one another and, consequently, the relationship between them is explored. In general, the result shows that there is a linear relationship between the IT status and performance of the companies, with few exceptions. This is the first study which integrates ant colony approach and GA for exploring the relationship between IT and firm performance.

Suggested Citation

  • A. Azadeh & A. Keramati & H. Panahi, 2009. "A hybrid GA-ant colony approach for exploring the relationship between IT and firm performance," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 4(5), pages 542-563.
    • Handle: RePEc:ids:ijbisy:v:4:y:2009:i:5:p:542-563
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=25206
    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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Manojit Chattopadhyay & Sourav Sengupta & B.S. Sahay, 2016. "Visual hierarchical clustering of supply chain using growing hierarchical self-organising map algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(9), pages 2552-2571, May.

    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:ijbisy:v:4:y:2009:i:5:p:542-563. 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=172 .

    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.