A Fuzzy Multi-Criteria and Cooperative Game-Theoretic Framework for Strategic Planning of Real-Time Adaptive On-Demand Public Transportation Systems

Abstract

Compared with a traditional fixed-route system, a demand-responsive transit system can respond to fluctuating demand and thereby avoid inefficiencies that would arise from traffic congestion. Yet there are several obstacles to the practical application of the approach. Objective: This paper develops a strategic decision-support framework for the implementation of Real-time Adaptive On-Demand Public Transportation (RT-ODPT) systems, aimed at addressing these challenges and supporting more informed strategy selection. Method: The study adopts a hybrid approach. First, SWOT analysis is used to structure the main internal and external factors. Then, FBWM is applied to weight these factors, followed by QSPM to compare alternative strategies. To better understand how strategies interact, a fuzzy cooperative game model based on a Taguchi orthogonal array (FGTOA) is introduced, which significantly reduces the number of required evaluations. Uncertainty in expert judgments is handled using fuzzy logic and GMIR. Results: The analysis shows that low-cost and scalable technologies (O2) play the most critical role (weight = 0.1611). Among the tested combinations, SO1–WO3–ST3–WT3 performs best, with a defuzzified value of 18.0731. At the same time, the FGTOA reduces the number of scenarios from 81 to just 9 without affecting the overall ranking. Conclusions: On the whole, the results indicate that integrating technical viability with adaptive approaches and risk awareness is central to the successful implementation of such systems. Impact: In essence, the model can facilitate the delivery of on-demand services in fringe locations and foster greater inclusivity regarding transportation, especially among individuals who have restricted access to mainstream modes of transportation.