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Despite the availability of qualified research personnel, up-to-date researchfacilities and experience in developing applied research and innovation, manyworldwide research institutions face difficulties when managing contractedResearch and Development (R&D) projects due to expectations from Industry(private sector). Such difficulties have motivated funding agents to createevaluation processes to check whether the operational procedures of fundedresearch institutions are sufficient to provide timely answers to demand forinnovation from industry and also to identify aspects that require qualityimprovement in research development. For this purpose, several multiplecriteria decision-making approaches can be applied. Among the availablemultiple criteria approaches, sorting methods are one prominent tool toevaluate the operational capacity. However, the first difficulty in applyingmultiple criteria sorting methods is the need to hierarchically structuremultiple criteria in order to represent the intended decision process.Additional challenges include the elicitation of the preference information andthe definition of criteria evaluation, since these are frequently affected bysome imprecision. In this paper, a new sorting method is proposed to deal withall of those critical points simultaneously. To consider multiple levels forthe decision criteria, the FlowSort method is extended to account forhierarchical criteria. To deal with imprecise data, the FlowSort is integratedwith fuzzy approaches. To yield solutions that consider fluctuations fromimprecise weights, the Stochastic Multicriteria Acceptability Analysis is used.Finally, the proposed method is applied to the evaluation of researchinstitutions, classifying them according to their operational maturity fordevelopment of applied research.

Multiple criteria hierarchy process for sorting problems under  uncertainty applied to the evaluation of the operational maturity of research  institutions