Safe E-scooter operation alternative prioritization using a q-rung orthopair Fuzzy Einstein based WASPAS approach


E-scooters globally have proven an increasingly popular form of dockless micro-mobility, while also contributing to sustainable urban transportation forms. However, some safety issues arise with e-scooter use in the cities. This study aims to propose a decision-making model based on q-rung orthopair fuzzy sets for prioritizing the safe e-scooter operation alternative. The proposed model consists of two stages; weighting the criteria and ranking the alternatives. First, a fuzzy logarithmic additive assessment of the weight coefficients methodology and fuzzy Einstein weighted averaging operator were applied to define the reference relationships between the criteria and determine their weights. Second, a q-rung orthopair fuzzy sets based decision-making model integrating q-rung orthopair fuzzy Einstein average and q-rung orthopair fuzzy Hamacher geometric mean operator was used to rank the alternatives. A fictional case study is presented to show the practicality of the proposed model. The contribution of the work is as a decision-support system for evaluating safe e-scooter strategies, including infrastructure placement, user behavior and how e-scooters interact with other transportation means, showing that applicability of the proposed model to real-world problems.

In the Journal of Cleaner Production (JCP)
Dr Eleni Papadonikolaki
Dr Eleni Papadonikolaki
Associate Professor in Management of Engineering Projects

Researcher and consultant at the intersection of management and digital economy