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- Manufacturing companies Industry 4.0 maturity level: A multivariate analysisPublication . Fonseca, Luís Miguel Ciravegna Martins da; Pereira, Teresa; Oliveira, Marisa; Ferreira, Fernanda; Busu, MihailThis research investigates Portuguese manufacturing companies’ Industry 4.0 (I4.0) maturity perception level and proposes an index to measure that aim. The research results show that the most critical factors in evaluating the perception level of I4.0 Perception Maturity (IPM) are strategy, leadership, and customer experiences. The result for the Global Index was 53.50%. Hence, the global Index companies’ perception of the level of maturity of I4.0 in Portugal is medium.
- Multicriteria Methodology for Selection of a Personal Electric VehiclePublication . Gomes, Carlos Francisco Simões; Sousa, Francisco; Pereira, Teresa; Oliveira, Marisa; Miranda Torres, Luís NorbertoA methodology that can support the decision process for selecting an Electric Vehicle (EV) is crucial. Considering the quantity, diversity, and complexity of existing EV models, their advantages and disadvantages, and people's increasing concern for sustainability, selecting and buying a personal EV appropriate to one's needs and requirements is not a simple task. Currently, criteria such as price, consumption per 100 km, range, comfort, brand, safety, and technology can be used to analyse available EV models. In this context, the decision-making process can be supported by the Multicriteria Decision Analysis (MCDA), “a method that clearly structures and evaluates complex problems with several alternatives, conflicting criteria, and complex scenarios. The novelty of this paper is to present a hybrid MCDA approach, combining two powerful methods (AHP and PROMETHEE) into a single framework to assist EV selection by any given person who has no multicriteria knowledge. A survey was conducted to define relevant criteria for a private person selecting an EV. The approach was validated for EV selection, considering the available offer within a target value, based solely on available public data, and excluding qualitative criteria. The paper discusses a case study whereby the proposed approach, using both quantitative and qualitative criteria, assists a decision-maker in selecting an EV from a set of alternatives, validated by the decision-maker, proving the importance and relevance of supporting the decision-making process.