Consumer response to failure by service robots: the role of anticipatory guilt

业务 服务(商务) 营销 服务补救 机器人 服务营销 过程管理 心理学 服务质量 计算机科学 人工智能
作者
Lifang Shu,Yueyan Wu,Kui Wang,Sirui Li
出处
期刊:Journal of Services Marketing [Emerald Publishing Limited]
卷期号:39 (7): 800-815 被引量:2
标识
DOI:10.1108/jsm-05-2024-0237
摘要

Purpose This study aims to investigate how service agent type (human vs robot) influences consumers’ punishment intentions following service failure. Moreover, it examines the mediating mechanism of anticipatory guilt and the boundary condition imposed by consumer relationship orientation (exchange vs communal). Design/methodology/approach Four online experiments (N = 978) systematically test the hypotheses: Study 1 uses an experience recall task to establish baseline effects. Study 2 uses a controlled experiment comparing human and robot service failure scenarios. Study 3 probes the mediating role of anticipatory guilt through a moderated causal chain analysis. Study 4 assesses the moderating effect of relationship orientation using a 2 (agent type) × 2 (orientation) factorial design. Findings The results reveal that consumers exhibit significantly lower punishment intentions toward human service agents than toward their robotic counterparts, primarily because of greater anticipatory guilt. This effect is particularly pronounced among consumers with communal (vs exchange) relationship orientations. Alternative explanations based on perceived warmth, competence and retaliation risk are empirically ruled out, demonstrating the robustness of the findings. Originality/value This research extends service failure scholarship by investigating how consumers’ advanced awareness of punitive outcomes influences their punishment intentions toward service agents (robots and human employees). While the literature predominantly focuses on dimensions of robot agency as conceptual mechanisms, this research pioneers an affective mediation framework, using empirical validation to establish anticipatory guilt as the critical psychological mediator. This research also demonstrates how relationship orientations (exchange and communal) modulate such effects, thereby advancing human–computer interaction studies through an emotional lens.
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