Web-Based DSS for Resource Allocation in Higher Education

Carolina Lino Martins, Pascale Zaraté, Adiel Teixeira de Almeida, Jônatas Araújo de Almeida and Danielle Costa Morais
Additional contact information
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

International Journal of Decision Support System Technology (IJDSST), 2021, vol. 13, issue 4, 1-23

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.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJDSST.2021100105 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:13:y:2021:i:4:p:1-23

Access Statistics for this article

International Journal of Decision Support System Technology (IJDSST) is currently edited by Shaofeng Liu

More articles in International Journal of Decision Support System Technology (IJDSST) from IGI Global
Bibliographic data for series maintained by Journal Editor ().