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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Optimal dynamic pricing for public transportation considering consumer social learning.

Yihua Zhang1, Zhan Zhao2

  • 1Liuzhou Railway Vocational Technical College, Liuzhou, Guangxi, China.

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Dynamic pricing in public transportation, including metro, bus, and paratransit, is optimized using game and social learning models. Consumer behavior and service quality investments influence market share and pricing for sustainable urban development.

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Area of Science:

  • Urban planning and transportation economics
  • Behavioral economics and network theory
  • Computational social science

Background:

  • Effective public transportation pricing is crucial for managing urban traffic congestion and promoting sustainable development.
  • Understanding consumer choices and operator strategies is key to optimizing public transit systems.
  • Social learning significantly influences consumer adoption of different transportation modes.

Purpose of the Study:

  • To develop and simulate a dynamic game pricing model incorporating social learning for urban public transportation.
  • To analyze how consumer sensitivity and social learning affect market share and pricing across metro, bus, and paratransit.
  • To provide insights for optimizing public transportation pricing strategies and service improvements.

Main Methods:

  • Construction of a dynamic game pricing model for public transportation operators.
  • Development of a social learning network model for consumer behavior analysis.
  • Application of a reinforcement learning algorithm for model simulation and result analysis.

Main Results:

  • Increased consumer sensitivity to travel modes leads to adjustments in market share and pricing.
  • Consumer social learning behavior maintains high metro market share, while bus and paratransit shares remain lower.
  • Enhanced consumer sensitivity incentivizes operators to invest in service quality, impacting pricing.

Conclusions:

  • The study provides a framework for understanding the interplay between pricing, consumer behavior, and service quality in public transportation.
  • Optimal pricing strategies can be informed by considering social learning dynamics and consumer perception.
  • Findings support decision-making for sustainable urban mobility and efficient public transit management.