Behavior-Aware Queueing: The Finite-Buffer Setting with Many Strategic Servers
研究策略性服务人员的工作速度选择受管理决策影响，发现人员配备或薪酬不足时，工作量超过临界点会导致系统性能骤降，为分析客户与服务人员均策略性的排队模型奠定基础。
In “Behavior-Aware Queueing: The Finite-Buffer Setting with Many Strategic Servers,” Zhong, Gopalakrishnan, and Ward develop a game-theoretic many-server Markovian queueing model with finite or infinite buffers to study the behavior of strategic servers whose choice of work speed depends on managerial decisions regarding (i) how many servers to staff and how much to pay them and (ii) whether and when to turn away customers. In order to predictably control system performance (e.g., lost demand, customer wait times, server burnout, etc.), they show that the system manager must either staff enough servers or pay them enough. For example, when servers are not paid enough, increasing their workload beyond a tipping point may result in a sharp drop in system performance because of server “rebellion.” Their work also establishes key foundational building blocks to advance the analysis of behavior-aware queueing models where both customers and servers are strategic and customers’ decisions endogenously induce a finite buffer.