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Grounding Information Technology Project Critical Success Factors Within the Organization

Applying Rough Sets

  • Chapter
Rough Sets: Selected Methods and Applications in Management and Engineering

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

Abstract

This chapter presents the idea of employing Rough Set Theory to assess risk and assist in reducing the complexity of managing IT-projects. There are many generic lists of critical success factors. Initially, these factors should be grounded within the specific organization. Then an early warning system, proposed here, may be employed based upon Rough Set Theory to assess the risk of specific IT-projects. The identification of risk will lead the project manager to focus on specific issues that must be resolved in order to contribute to the success of the project. We also show how DRSA-Dominance based Rough Set Approach can be utilized to analyze IT-projects.

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Notes

  1. 1.

    The structure of the example has been adapted from the college student example presented by Greco et al. [54].

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Author information

Authors and Affiliations

  1. Faculty of Management, University of Lethbridge, Lethbridge, Alberta, T1K 3M4, Canada

    M. Gordon Hunter

  2. Department of Computer Science and Mathematics, Munich University of Applied Sciences, 80335, Munich, Germany

    Georg Peters

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  1. M. Gordon Hunter
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  2. Georg Peters
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Correspondence to M. Gordon Hunter .

Editor information

Editors and Affiliations

  1. Munich University of Applied Sciences, Lothstrasse 34, Munich, 80335, Germany

    Georg Peters

  2. Dpt. of Mathematics and Computer Science, St. Mary's University, Halifax, B3H 3C3, Nova Scotia, Canada

    Pawan Lingras

  3. University of Warsaw, Banacha 2, Warsaw, 02-097, Poland

    Dominik Ślęzak

  4. Department of Computer Science, University of Regina, Regina, S4S0A2, Saskatchewan, Canada

    Yiyu Yao

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Hunter, M.G., Peters, G. (2012). Grounding Information Technology Project Critical Success Factors Within the Organization. In: Peters, G., Lingras, P., Ślęzak, D., Yao, Y. (eds) Rough Sets: Selected Methods and Applications in Management and Engineering. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-2760-4_8

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  • DOI: https://doi.org/10.1007/978-1-4471-2760-4_8

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2759-8

  • Online ISBN: 978-1-4471-2760-4

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