Multi-Model to Assess the Impact of Knowledge on High Complexity Spectrum Performance under Uncertainty and Unpredictability: Towards PPPs Projects
Selma Regina Martins Oliveira, Jorge Lino Alves

Abstract
This work intends to contribute to the planning guidelines in the field of high complexity spectrum. Thus, it develops a multi-model proposal to assess the impact of knowledge on public private partnerships projects performance under uncertainty and unpredictability, that considers a sequence of systematic procedures in the following phases: Phase 1: Modeling the needs of information in PPP under uncertainty and unpredictability. Phase 2: Modeling for the determination of critical knowledge in PPP projects under Uncertainty and Unpredictability. This research treated Brazil’s transportation infrastructure as the empirical targets. Several support instruments were used in the modeling elaboration in order to reduce subjectivity in the results: psychometric scales - Thurstone’s Law of Comparative Judgment (LCJ), multi-criteria Compromise Programming, Electre III, and Promethee II; Artificial Neural Networks (ANN); Neurofuzzy Intelligence. The results produced are satisfactory, validating the proposed procedure for PPP.

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