Fuzzy Einstein WASPAS approach for the economic and societal dynamics of the climate change mitigation strategies in urban mobility planning

The twin challenges posed by biodiversity loss and climate change compel public authorities to transform their traditional policies to take climate action via urban mobility planning. However, the interests of the stakeholders may differ so that the development and the implementation of the required action become challenging. In this study, we trace how an optimal action plan should take the societal dynamics into account and how the actions taken can reshape the societal dynamics. To illustrate and analyze the complex forces that drive the decision-making process in urban mobility planning, we develop a scenario, which bunches three small-scale urban mobility planning alternatives that are frequently proposed in the literature and practiced in cities. Alternatives are assessed under twelve criteria reflecting economic, environmental, technical, and political dimensions of the decision problem. In solving the problem, we propose an improvement of the Weighted Aggregated Sum Product Assessment (WASPAS) approach by applying Einstein norms in a fuzzy environment over triangular fuzzy numbers to evaluate and rank the prioritization of climate change mitigation strategies. The proposed method comprises two stages. In the first stage, the weight coefficients of the criteria are calculated. In the second stage, the fuzzy Einstein WASPAS approach is applied to select the most suitable alternative among the three alternatives. Testing and validation of the model are done through a comparison with existing decision making methods in the literature. The results show that the best plan should be inclusive and equitable as well as economically efficient. Although the economic dimension is highly significant to the decision-making process, choosing the most suitable urban mobility planning option requires the consideration of other societal dynamics, too.