Agent Recruitment Planning in Knowledge-Intensive Call Centers
针对呼叫中心座席流失问题，结合控制理论和机会约束规划，建立考虑座席学习的劳动力规划模型，以最小化总劳动力成本并满足随机需求的服务水平。
The key ingredient in a call center’s operational efficiency is labor. Agent turnover remains a major concern for call centers. The top three reasons for turnover are low salary, lack of career path, and burnout. On average, it costs about $10 to a call center for each call, and the cost to bring on a new agent is more than $6,000. The author treats call centers as knowledge-intensive operations that are characterized by extensive knowledge required for each agent, combines control theory and chance-constrained programming in a model for workforce planning that allows for agent learning, and derives steady state workforce levels for different knowledge groups within the call center to minimize total labor-related costs. The objective is to meet stochastic demands with a desired service level. The author applies his model to an actual call center situation in the high-tech industry with adjusted data and discusses the managerial implications.