Fuel cell electric long-haul truck evaluation for sustainable transport via a novel Pythagorean fuzzy sets-driven tool

Fossil fuel-powered trucks and vehicles used in road freight transportation play a notable role in the emission of greenhouse gases. Although the road vehicle industry's use of renewable energy is promising in terms of sustainability, the vehicle manufacturing industry's initiatives are still in their infancy. Moreover, existing studies on using electric and renewable energies in transportation have primarily focused on electric automobiles. Considering these research and practice gaps, this work investigates the selection of the most proper fuel cell electric long-haul trucks (FCETs) to restructure the Turkish fleet of long-haul trucks operating nationwide concerning sustainability. However, assessing these vehicles is challenging, as they are produced based on new and advanced technology, with severe and highly complicated uncertainties. Thus, this paper suggests a Pythagorean fuzzy distance measure-based weighted integrated sum product (WISP) with the integration of the symmetry point of criteria (SPC) and relative closeness coefficient (RCC)-based weighting methods. Surprisingly, and unlike the findings of earlier works, the acquired conclusions indicate that refueling time (0.1161) is the most influential factor for FCET selection, followed by range (0.0837) and torque (0.0785) among the 14 criteria. Besides, the first alternative (R1) outperforms the other options, followed by R5 and R7. Finally, robustness and validity checks ensured the consistency, stability, and practicality of the conclusions. The research can guide manufacturers who produce FCETs and aim to enhance the quality and desirability of their products. Furthermore, practitioners and researchers can utilize the proposed model to solve challenging decision-making problems.