IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v07y2008i03ns0219622008003022.html
   My bibliography  Save this article

An Excel-Based Decision Support System For Scoring And Ranking Proposed R&D Projects

Author

Listed:
  • ANNE DE PIANTE HENRIKSEN

    (Integrated Science and Technology Department, James Madison University MSC 4102, Harrisonburg, VA 22807, USA)

  • SUSAN W. PALOCSAY

    (Computer Information Systems and Management Science Department, James Madison University, MSC 0202, Harrisonburg, VA 22807, USA)

Abstract

One of the most challenging aspects of technology management is the selection of research and development (R&D) projects from among a group of proposals. This paper introduces an interactive, user-friendly decision support system for evaluating and ranking R&D projects and demonstrates its application on an example R&D program. It employs the scoring methodology developed by Henriksen and Traynor to provide a practical technique that considers both project merit and project cost in the evaluation process, while explicitly accounting for trade-offs among multiple decision criteria.1The framework of the Excel-based system, PScore, is presented with an emphasis on the potential benefits of using this methodology with computer-automated extensions that facilitate and enhance managerial review and decision-making capabilities.

Suggested Citation

  • Anne De Piante Henriksen & Susan W. Palocsay, 2008. "An Excel-Based Decision Support System For Scoring And Ranking Proposed R&D Projects," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 529-546.
    • Handle: RePEc:wsi:ijitdm:v:07:y:2008:i:03:n:s0219622008003022
    DOI: 10.1142/S0219622008003022
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622008003022
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219622008003022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Lean Yu & Shouyang Wang & Fenghua Wen & Kin Lai, 2012. "Genetic algorithm-based multi-criteria project portfolio selection," Annals of Operations Research, Springer, vol. 197(1), pages 71-86, August.

    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:wsi:ijitdm:v:07:y:2008:i:03:n:s0219622008003022. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.