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A fuzzy approach to assess outsourcing risks in Brazilian navy industrial military organizations

Luiz Fernando do Nascimento Vieira (Marinha do Brasil, Rio de Janeiro, Brazil)
Igor dos Santos Caetano (Marinha do Brasil, Rio de Janeiro, Brazil)
Ricardo França Santos (Federal University of Rio de Janeiro, Rio de Janeiro, Brazil)

Journal of Modelling in Management

ISSN: 1746-5664

Article publication date: 14 June 2021

Issue publication date: 17 February 2022

161

Abstract

Purpose

This study assesses outsourcing risks using the fuzzy analytical hierarchy process (FAHP).

Design/methodology/approach

This descriptive research combines both qualitative and quantitative approaches. Risks identified in the literature review were classified with FAHP using questionnaire data from respondents in operations, procurement and risk management in Brazilian Navy Industrial Military Organizations (OMPS-I, by its Portuguese acronym).

Findings

The results indicate that FAHP is a method capable of producing relevant information to decision-making in the risk management process. A framework was created incorporating 16 major risks related to outsourcing. The results point to higher inherent risk levels related to outsourcing in the context of OMPS-Is: in order, hidden costs and unrealized savings; loss of knowledge/skills and/or corporate memory and difficulty in reacquiring a function; and loss of opportunities and reputation. The category of economic risk was revealed as the most important.

Originality/value

This study improves understanding of outsourcing risks and improves risk assessment by refining decision-making information and developing a system of decision analysis with several criteria. It also contributes to the development and implementation of a usable version of decision analysis with several criteria at a managerial level.

Keywords

Citation

Vieira, L.F.d.N., Caetano, I.d.S. and Santos, R.F. (2022), "A fuzzy approach to assess outsourcing risks in Brazilian navy industrial military organizations", Journal of Modelling in Management, Vol. 17 No. 1, pp. 177-205. https://doi.org/10.1108/JM2-07-2020-0197

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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