π€ AI Summary
This study investigates the equilibrium joining decisions of strategic customers in an M/M/1 queue operating within a two-phase random environment. By integrating continuous-time Markov processes, game theory, and queueing theory, it systematically analyzes utility-based join-or-balk strategies across four information scenarios. Explicit solutions are derived for the observable-environment and fully unobservable cases under both fast-oscillation and slow-switching regimes, and the corresponding equilibrium conditions are established for each information structure. The findings reveal how the dynamic evolution of the random environment shapes customersβ equilibrium entry strategies, providing a theoretical foundation for information design and strategic optimization in stochastic service systems.
π Abstract
We study equilibrium joining strategies in an M/M/1-type queueing system with strategic customers operating in a two-phase random environment described as a continuous-time Markov process. Strategic customers, upon arrival, choose whether to join or to balk based on available information and anticipated utility, considering the trade-off between reward from service and waiting cost. Four observation scenarios are analysed: fully observable (both queue length and environment phase are disclosed to a customer upon arrival), queue-only observable, environment-only observable, and fully unobservable. In each case, equilibrium joining strategies are analysed. In the environment-only observable and fully unobservable cases, explicit solutions and equilibrium conditions are derived under rapid oscillations and under very slow transitions between environment phases.