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Web-Based DSS for Resource Allocation in Higher Education

Author

Listed:
  • Carolina Lino Martins

    (Production Engineering Department, Universidade Federal de Mato Grosso do Sul, Brazil)

  • Pascale Zaraté

    (Toulouse Capitole University, France)

  • Adiel Teixeira de Almeida

    (Production Engineering Department, Universidade Federal de Pernambuco, Brazil)

  • Jônatas Araújo de Almeida

    (Production Engineering Department, Universidade Federal de Pernambuco, Brazil)

  • Danielle Costa Morais

    (Universidade Federal de Pernambuco, Brazil)

Abstract

The allocation of scarce resources is a complex higher education decision problem, especially when it comes to budget constraints. Therefore, the authors propose a multicriteria web-based decision support system for resource allocation in higher education organizations. To do so, they define an MCDA/M resource allocation model, based on a project portfolio selection problem to set the percentage of the total budget that every alternative should receive. For the web-based DSS, they develop a database model to store and retrieve data, define the user's interface, and they use a web platform to transform the prototype into a web-based system. Also, they run an empirical analysis with an end-user to test the DSS. They show that the system can provide a clear vision of how the resource allocation system works; the mechanism as a whole becomes more transparent to those involved, enabling them to make efficient and reasonable decisions.

Suggested Citation

  • Carolina Lino Martins & Pascale Zaraté & Adiel Teixeira de Almeida & Jônatas Araújo de Almeida & Danielle Costa Morais, 2021. "Web-Based DSS for Resource Allocation in Higher Education," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 13(4), pages 1-23, October.
    • Handle: RePEc:igg:jdsst0:v:13:y:2021:i:4:p:1-23
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    References listed on IDEAS

    as
    1. Ahti Salo & Jeffrey Keisler & Alec Morton, 2011. "An Invitation to Portfolio Decision Analysis," International Series in Operations Research & Management Science, in: Ahti Salo & Jeffrey Keisler & Alec Morton (ed.), Portfolio Decision Analysis, chapter 0, pages 3-27, Springer.
    2. Frada Burstein & Clyde Holsapple, 2008. "Handbook on Decision Support Systems 1," International Handbooks on Information Systems, Springer, number 978-3-540-48713-5, November.
    3. Abu-Taleb, Maher F. & Mareschal, Bertrand, 1995. "Water resources planning in the Middle East: Application of the PROMETHEE V multicriteria method," European Journal of Operational Research, Elsevier, vol. 81(3), pages 500-511, March.
    4. Frada Burstein & Clyde Holsapple, 2008. "Handbook on Decision Support Systems 2," International Handbooks on Information Systems, Springer, number 978-3-540-48716-6, November.
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