Implementing urban mobility strategies considering digital carbon footprint using a hybrid picture fuzzy decision-making framework

Transportation plays a key part in daily routines of people and the global economy, but it is also contributing vastly to the greenhouse gas emissions and climate change. Digital mobility solutions can improve the transport efficiency and enable carbon-free future with smart transport choices. In this manuscript, we develop a hybrid ‘Picture Fuzzy Euclidean Taxicab Distance-based Approach (PF-ETDBA)’ to evaluate the strategy implementation alternatives in urban mobility to reduce digital carbon footprint. This approach first computes the numeric significance of decision experts by picture fuzzy rank sum procedure. For this purpose, the new distance measure is presented to evade the limitations of some extant picture fuzzy measures. Next, an integrated approach for criteria weight is presented to estimate the criteria weights including the objective weight via picture fuzzy standard deviation (PF-SD) approach and subjective weight with picture fuzzy relative closeness coefficient (PF-RCC) model. Based on these processes, a hybrid algorithm is introduced to tackle with decision-making problems with picture fuzzy information, named as ‘PF-SD-RCC-ETDBA’. Furthermore, the developed model is implemented to rank the strategy implementation options across twelve diverse criteria, which demonstrating its superiority and applicability. It is found that an option “Progressive digital transition strategy” is the most suitable choice with minimum evaluation score (-0.0098), followed by Transformative smart mobility innovation strategy (0.002) and Policy-driven sustainable mobility governance strategy (0.0078). Moreover, sensitivity and comparative analyses are conducted to validate the stability and robustness of obtained results.