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Spatial Markov equilibrium models for taxi services: driver decision, search friction, and locational pricing
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DOI：10.1016/j.trb.2026.103491.png)
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Abstract
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• Proposes a Markov equilibrium framework for modeling stochastic multi-agent taxi systems. • Models drivers’ trip acceptance as a probabilistic response to perceived long-term values. • Captures spatial competition, search frictions, and endogenous state transitions in a unified framework. • Develops tractable algorithms for computing equilibrium values and locational fares. • Demonstrates the framework using a case study based on Chicago taxi trip data.
Keywords:
Markov equilibrium
taxi services
driver decision-making
search frictions
locational pricing
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