IDEAS home Printed from https://ideas.repec.org/a/igg/jisscm/v8y2015i1p60-84.html
   My bibliography  Save this article

A Case Study Using the Analytic Hierarchy Process for IT Outsourcing Decision Making

Author

Listed:
  • Mary Anne Atkinson

    (Department of Accounting, Central Washington University, Ellensburg, WA, USA)

  • Ozden Bayazit

    (Department of Finance & SCM, Central Washington University, Ellensburg, WA, USA)

  • Birsen Karpak

    (Department of Management, Youngstown State University, Youngstown, OH, USA)

Abstract

Decisions related to managing IT resources - which resources to keep in-house and which resources to outsource - are critical to business success. The goal of this paper is to show the usefulness of the Analytic Hierarchy Process (AHP) as a decision-making tool for IT sourcing decisions, based on an analysis of factors that recent literature found to be associated with IT sourcing risk. Although the AHP previously has been suggested for IT outsourcing decision making, this study is the first to consider evaluating the risks of offshore outsourcing, rural outsourcing, and in-sourcing IT processes by using the AHP. From the perspective of the expert decision maker, three IT sourcing strategies were evaluated with respect to 58 criteria. The case study example presented in this paper shows the effectiveness of the AHP to support management for this business decision. The authors' results show that a systematic approach to analyzing outsourcing can reduce the uncertainty and risk that is common in such decisions.

Suggested Citation

  • Mary Anne Atkinson & Ozden Bayazit & Birsen Karpak, 2015. "A Case Study Using the Analytic Hierarchy Process for IT Outsourcing Decision Making," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 8(1), pages 60-84, January.
    • Handle: RePEc:igg:jisscm:v:8:y:2015:i:1:p:60-84
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijisscm.2015010104
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Kim, Daewon & Kim, Seongcheol, 2017. "Newspaper companies' determinants in adopting robot journalism," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 184-195.
    2. Noam Koriat & Roy Gelbard, 2018. "Knowledge Sharing Motivation Among External and Internal IT Workers," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 1-24, September.

    More about this item

    Statistics

    Access and download statistics

    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:igg:jisscm:v:8:y:2015:i:1:p:60-84. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.