Human-AI collaborative recovery: How recovery sequence and strategy order drive consumer forgiveness

Guangmei Yang and Bingjia Shao

Journal of Retailing and Consumer Services, 2025, vol. 87, issue C

Abstract: Collaboration between artificial intelligence (AI) robots and human employees in service recovery is becoming increasingly prevalent. However, the impact of human-AI collaborative recovery on consumer forgiveness and its underlying mechanisms remain unclear. Drawing on role congruity theory and dual-process theory, we propose and validate a theoretical model examining how the human-AI collaborative recovery sequence (human employees before AI robots vs. AI robots before human employees) and recovery strategy order (emotional before economic vs. economic before emotional) influence consumer forgiveness. Three experimental studies with 1011 participants demonstrated that when human employees are present before AI robots, implementing the emotional before economic recovery strategy order can increase consumers' expected responsibility of the corporation, thereby promoting forgiveness. Conversely, when AI robots are used before human employees, adopting the economic before emotional recovery strategy order can increase consumers' emotional empathy toward the enterprise and promote forgiveness. This study contributes to the theoretical understanding of human-AI collaboration in AI service marketing and offers practical advice for optimizing recovery strategies in AI service failures.

Keywords: Human-AI collaboration; Service recovery; Recovery sequence; Recovery strategy order; Consumer forgiveness; Dual-process theory; Role congruity theory (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:87:y:2025:i:c:s0969698925002310

DOI: 10.1016/j.jretconser.2025.104452

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