Multicriteria Decision-Making in Public Security: A Systematic Review

Jefferson Costa () and Maisa Silva
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Jefferson Costa: Department of Management Engineering, Federal University of Pernambuco, Recife 50670-901, Brazil
Maisa Silva: Department of Management Engineering, Federal University of Pernambuco, Recife 50670-901, Brazil

Mathematics, 2024, vol. 12, issue 11, 1-21

Abstract: The Multiple Criteria Decision-Making/Analysis (MCDM/A) methods have been widely used in several management contexts. In public security, their use enhances managerial decision-making by considering the decision-maker’s preference structure and providing a multidimensional view of problems. However, methodological support for their applications in this field lacks clarity, including selecting appropriate methods, addressing pertinent problematics, and identifying alternatives and criteria. To address this gap, this article conducts a Systematic Literature Review (SLR) to diagnose the state of the art and identify the main directions of the research in multicriteria models applied to public security management. The research methodology involves five main research questions, and the extraction and analysis of data from 51 articles selected through a structured filtering process. The analysis includes identifying the number of publications and citations, as well as listing the MCDM/A approaches and issues employed. Furthermore, the criteria used and the number of criteria considered are discussed, as well as the method employed. Finally, the identification of the main research directions in MCDM/A models applied to public security is presented. The findings suggest that prioritization and classification are common problematics, social criteria are frequently considered, and the AHP method is widely used, often employing fuzzy sets and hybrid models.

Keywords: multicriteria models; decision making; public security; systematic literature review (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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