A Novel Technique of the MARCOS Method for q-Rung Orthopair Fuzzy Information and E-Transport for Urban Mobility Explorations

Due to the lack of adequate public transportation in developing countries, ride-hailing services are becoming more popular to satisfy the need for urban travel. As far as we are aware, there is a dearth of research on how passengers behave and feel about the quality of ride-hailing services, especially when it comes to studies conducted in developing countries. Ride-hailing services were introduced to accommodate the transport needs of people living in urban areas. E-transportation in urban areas can be optimized through various mathematical models and decision-making frameworks that address complex challenges like traffic flow, energy consumption, and infrastructure placement. Multi-criteria decision analysis and simulation techniques help balance costs, environmental impacts, and efficiency. Decision-makers must evaluate factors like charging station locations and vehicle routes to maximize sustainability and minimize congestion. This article articulates a novel decision-making model of the MARCOS method under the system of q-rung orthopair fuzzy (q-ROF) information. A q-ROF set (q-ROFS) is an extended and well-known mathematical model for handling uncertain human information. Additionally, we established a decision algorithm of the MARCOS method for the multi-attribute group decision-making (MAGDM) problem. This decision analysis technique ranks alternatives by computing the utility function and credibility degrees of alternatives in the MARCOS method. To prove the validity of diagnosed theories, we discuss an application related to the E-transportation system with the help of numerical examples. Furthermore, a comprehensive contracting technique is stated to verify the results of pioneering approaches with existing mathematical terminologies. At the end, concluding remarks summarize the whole article.