实测零售机器人如何影响顾客进店，发现它吸引停留却难促转化。
From Metrics to Meaning: Insights from a Mixed-Methods Field Experiment on Retail Robot Deployment
- 通过对比无机器人、仅机器人、机器人+展台三种场景，分析顾客行为变化。
- 机器人使路人停留率上升（展台加持下最高），但店员引导成交步骤下降。
- 揭示店员因避干扰、对话延迟和儿童吸引力而调整互动策略的深层原因。
我们在一家真实运营的床上用品商店开展了为期12天的混合方法实地实验，考察在日常人员调度下对话式服务机器人的部署效果。实验交替设置三个条件：基准（无机器人）、仅机器人、机器人+展台，并对从路过的顾客到最终购买的完整服务流程进行视频标注。随后采用解释性顺序设计，通过六次实验后店员访谈解读量化结果。定量结果显示，机器人显著提升了路人的停留率（展台组合时最高）；然而，每名停留者后续的店员引导环节——包括主动接近、进入店铺、协助体验和完成购买——均出现下降。访谈揭示了这一背离现象的原因：店员避免打断正在进行的机器人与顾客对话，难以把握对话延迟带来的模糊时机，且注意到儿童导向的吸引力常在门口即满足好奇心。展台增强了可见性，但也使互动固定于入口区域，形成一个明确的微空间，在此可“闭环”需求而无需入店。本文整合多条线索，从顾客初始兴趣到进店行为建立综合性解释框架，并提出可操作的部署建议。研究深化了对顾客、店员与机器人三者交互的理解，为高接触零售场景中服务机器人的落地提供实践指导。
原文摘要 · Abstract (English)
We report a mixed-methods field experiment of a conversational service robot deployed under everyday staffing discretion in a live bedding store. Over 12 days we alternated three conditions--Baseline (no robot), Robot-only, and Robot+Fixture--and video-annotated the service funnel from passersby to purchase. An explanatory sequential design then used six post-experiment staff interviews to interpret the quantitative patterns. Quantitatively, the robot increased stopping per passerby (highest with the fixture), yet clerk-led downstream steps per stopper--clerk approach, store entry, assisted experience, and purchase--decreased. Interviews explained this divergence: clerks avoided interrupting ongoing robot-customer talk, struggled with ambiguous timing amid conversational latency, and noted child-centered attraction that often satisfied curiosity at the doorway. The fixture amplified visibility but also anchored encounters at the threshold, creating a well-defined micro-space where needs could ``close'' without moving inside. We synthesize these strands into an integrative account from the initial show of interest on the part of a customer to their entering the store and derive actionable guidance. The results advance the understanding of interactions between customers, staff members, and the robot and offer practical recommendations for deploying service robots in high-touch retail.
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