| Abstrakt: |
The ride-sharing business model derived from the digital sharing economy offers promise as a sustainable transportation possibility. This study analyzes the factors affecting ride-sharing services to propose a novel decision support framework, conduct a comparative study, evaluate the findings' resilience, and validate the constructed model via sensitivity analysis. EDAS is used for ranking the business models, and intervalvalued spherical fuzzy (IVSF) sets model decision-maker uncertainty. Unlike previous research, the proposed IVSFS EDAS handles membership, hesitancy, and non-membership in an independent way for larger interval types. A solution set with an IVSF TOPSIS checks the proposed methodology's robustness. This research reveals the same ranking to be valid for both EDAS and TOPSIS approaches (sharing a hired vehicle via a mobile application, sharing a private vehicle with the neighbors, sharing a private vehicle with a stranger going to the same direction). This study's contribution is that it implements a new IVSF EDAS compared with TOPSIS and provides a sensitivity analysis to illustrate and validate the findings. In addition, the study observes a sample of Generation Z generating marketing and sales strategies. [ABSTRACT FROM AUTHOR] |
