Desenvolvimento de método multicritério linguístico para avaliação de desempenho e priorização de recursos

Abstract

Performance indicators are information collected at regular intervals to track the performance of organizations. With scarce resources and a high number of performance indicators, it is difficult to improve all organizational aspects simultaneously. At the same time, several types of indicators have a subjective character with measurement expressed in words with present uncertainty. Management tools and multicriteria decision support methodologies (MCDM) have been used to evaluate the performance of organizations. However, there are limitations in traditional MCDM: independence of criteria and disregard for the collaborative environment. The main objective of this dissertation was to develop a linguistic multicriteria method for collaborative environments with performance evaluation based on subjective information aiming to prioritize resource allocation to generate greater impact on the organization. The proposed method was developed based on a systematic literature review and the adaptation of existing methodologies. It consists of assessing language performance, determining importance based on 2- Tuple Language Weight in determining language importance and capturing influence through DEMATEL 2-Tuple, all being operationalized in a 2-Tuple computational environment. The proposed method introduces the concept of 'Impact' which combines importance (perceived utility) and influence (causality) as different quantities acting on the same system or collaborative environment. The main steps of the method are Structuring, Evaluation, Processing, Result, and Revaluation. To verify the proposed method, the problem reported by Singh et al. (2018) with the contribution of data from Meksavang et al. (2019) referring to the same study, were adapted for application. As a result of the application, it was identified which priority Performance Indicators (PIs), with the highest potential impact, to develop a group of ecologically correct meat suppliers with economic viability, and it was observed that considering the comparative limitations, the suggestions of prioritization captured by the proposed method are in line with the method selection suggestions developed by Singh et al. (2018) and Meksavang et al. (2019) verifying that the steps developed by the proposed method are adequately structured and feasible.