基于车站画像的智慧客服终端配置方案研究

Configuration Scheme for Intelligent Customer Service Terminals Based on Station Portrait

随着城市轨道交通网络化运营的不断深入,乘客对城市轨道交通服务的自助化程度有了更高的要求,客服终端设备智能化水平随之不断提升,但其现有配置多根据经验确定,缺乏理论方法支撑。针对上述问题,研究提出面向数据驱动的智慧客服终端配置方案,在建立车站画像的基础上,运用K-means聚类划分车站类型,结合排队论将各类智慧客服终端服务能力与不同类型车站的乘客服务需求相匹配,从而解决需求和能力的精准匹配问题,最终以北京市城市轨道交通站点为例给出智慧客服终端配置方案。研究结果表明,所提出的基于车站画像的智慧客服终端配置方案更具经济性,有助于实现车站在无人值守运作模式下与乘客需求的精准对接,为城市轨道交通运营企业进行智慧客服终端配置提供决策参考。

With the development of metro network operation, the metro self-service faces higher requirements from passengers. The configuration of customer service terminals, despite its continuously improved intelligent level, is largely determined by experience, lacking theoretical support. Therefore, a data-driven configuration scheme for intelligent customer service was proposed. It utilized K-means clustering to classify stations based on station portraits. The service capabilities of various intelligent customer service terminals were matched with the passenger needs in different types of stations through queuing theory to achieve an accurate connection between needs and capabilities. Finally, the Beijing metro station was taken as an example to verify the configuration scheme for intelligent customer service terminals. The results show that the configuration scheme for intelligent customer service terminals based on station portrait is more economical and conducive to the satisfaction of passenger needs in unattended mode, providing decision-making reference for metro operation enterprises during the configuration of intelligent customer service terminals.