IDEAS home Printed from https://ideas.repec.org/a/ids/ijidsc/v8y2016i3p284-304.html
   My bibliography  Save this article

Decision support systems for IT service management

Author

Listed:
  • Aileen Cater-Steel
  • Raul Valverde
  • Anup Shrestha
  • Mark Toleman

Abstract

Group decision support systems (GDSS) and knowledge-based systems (KBS) have the potential to assist information technology service managers make sound decisions. We use narrative enquiry and reflective processes to review two recent projects that designed decision support system (DSS) tools for IT service management. The software mediated process assessment project includes a GDSS module to enable the selection of processes for assessment. The decision support recommendation system for IT service operation used a knowledge base to provide recommendations specific to the problem domain of IT service support. From the use of prior literature, rigorous methods and empirical evidence, contributions are made to ITSM theory and practice. The process selection decision model is a novel and effective combination of balanced scorecard, SERV-QUAL and the IT infrastructure library (ITIL) guidelines. In terms of methodology, the incorporation of task-technology theory in design science research enables design principles to be articulated. Outcomes from projects of this nature demonstrate exemplary cases of success stories where the primary research objective is to develop innovative solutions that work in practice and are grounded in academic rigour.

Suggested Citation

  • Aileen Cater-Steel & Raul Valverde & Anup Shrestha & Mark Toleman, 2016. "Decision support systems for IT service management," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 8(3), pages 284-304.
    • Handle: RePEc:ids:ijidsc:v:8:y:2016:i:3:p:284-304
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=78588
    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. Lorenzo Ricciardi Celsi & Andrea Caliciotti & Matteo D'Onorio & Eugenio Scocchi & Nour Alhuda Sulieman & Massimo Villari, 2021. "On Predicting Ticket Reopening for Improving Customer Service in 5G Fiber Optic Networks," Future Internet, MDPI, vol. 13(10), pages 1-16, October.

    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:ijidsc:v:8:y:2016:i:3:p:284-304. 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=306 .

    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.