Human versus robot service agents : a comparative study on feedback types and interaction frequency

Abstract

Purpose – Unlike complaints with intense dissatisfaction that typically focus on specific failures, customer feedback stemming from milder dissatisfaction with constructive comments tends to be more beneficial for a company’s success. This study aims to address this gap by exploring how AI service robots might enhance feedback collection, compared to human approaches across various scenarios. Design/methodology/approach – Conceptualized on the commitment-trust theory, this research delves into the relationship between motivation and willingness to share customer feedback catalyzed by three factors: feedback type (self-related vs non-self-related), agent type (robot vs human) and interaction frequency that refers to the sequence of interactions with the same or varied agents. Progressively, these three factors were tested in three studies accordingly using the scenario-based experiment approaches. Findings – Through juxtaposing a series of three empirical studies, the results show that the interplay of the three examined factors leads to findings that challenge conventional assumptions; especially when customers share non-self-related feedback, a robot can generate higher customer trust and perceived utility than a human agent, and when feedback from customers encompasses both self-related and non-self-related aspects, customer trust mediates the moderating effect of interaction frequency on the influence of perceived utility. Originality/value – This study provides nuanced insights into the optimal service agent type for collecting distinct feedback categories. Additionally, it elucidates how the sequence of agent interactions shapes divergent customer cognitive responses. 研究⽬的 – 不同于源⾃强烈不满、集中于特定失误的投诉, 带有建设性意⻅的轻度不满反馈往往更 有助于企业的⻓期成功。本研究旨在探讨⼈⼯智能服务机器⼈在反馈收集⽅⾯与⼈类服务⽅式的差 异, 填补现有研究空⽩, 并分析不同情境下的效果表现。 研究⽅法 – 基于承诺–信任理论(Commitment-Trust Theory),本研究考察了顾客反馈意愿的形成机制, 重点分析三项关键因素：反馈类型（与⾃我相关 vs 与⾮⾃我相关）、服务代理类型（机器⼈ vs ⼈ 类）以及互动频率（与同⼀或不同代理的连续互动)。研究通过三个基于情境的实验逐步检验上述三 因素的作⽤与交互影响。 研究发现 – 通过三项实证研究的对⽐分析, 结果显⽰三因素之间的交互作⽤产⽣了颠覆传统假设的 发现：当顾客提供与⾮⾃我相关的反馈时, 机器⼈相⽐⼈类代理能激发更⾼的信任感与感知效⽤; ⽽ 当反馈同时包含与⾃我相关和⾮⾃我相关内容时, 顾客信任在互动频率对感知效⽤影响的调节效应 中起中介作⽤。 研究创新 – 本研究明确揭⽰了在不同类型反馈收集中, 哪类服务代理更具优势。同时, 对顾客在不同 互动顺序下的认知反应机制进⾏了深⼊剖析, 为企业优化⼈机协作式服务提供了理论与实践启⽰。