本研究旨在探討服務失敗歸因（內部歸因或外部歸因）及客服種類（真人客服或人工智慧客服）對服務恢復滿意度的影響；並透過2 x 2的因子設計進行實驗，分析社會批判、社會支持與社會交換三個中介變量，在上述不同情境下如何作用。
研究結果顯示，在內部歸因（消費者自身錯誤）情境下，消費者更傾向於選擇AI客服，以降低社會批判壓力，然而社會批判感知與服務恢復滿意度存在負相關；而在外部歸因（公司錯誤）情境下，消費者更傾向於選擇真人客服，以滿足社會支持需求，社會支持感知與服務恢復滿意度存在正相關。此外，社會交換理論顯示，在內部歸因情境下，消費者更傾向於選擇真人客服，以滿足社會交換預期（更多的交涉空間）；而在外部歸因的情境下，社會交換對付物恢復滿意度則無顯著影響。
本研究的理論貢獻在於揭示了社會心理因素在服務恢復過程中的關鍵作用，實務意涵則在於提供企業如何在不同情境下靈活運用AI客服與真人客服，以提升服務恢復策略的有效性。
綜上所述，本研究不僅豐富了服務管理領域的理論基礎，也為企業在面對服務失敗時的恢復策略提供了實踐指導，期望能夠為提升消費者滿意度和企業競爭力提供助益。

This study aims to investigate the effects of service failure attribution (internal attribution or external attribution) and customer service type (live customer service or AI customer service) on service recovery satisfaction; and conducts experiments through a 2 x 2 factorial design to analyze how the three mediating variables, namely, social criticism, social support, and social exchange, work in the above mentioned different contexts.
The results show that under internal attribution (consumers' own mistakes), consumers prefer AI customer service to reduce the pressure of social criticism, however, there is a negative correlation between the perception of social criticism and service recovery satisfaction; while under external attribution (company's mistakes), consumers prefer real human customer service to satisfy the need for social support, and there is a positive correlation between the perception of social support and service recovery satisfaction. Perceived social support is positively related to satisfaction with service recovery. In addition, social exchange theory shows that in the internal attribution context, consumers are more likely to choose a live customer service agent to fulfill the social exchange expectation (more room for negotiation), while in the external attribution context, social exchange has no significant effect on payment recovery satisfaction.
The theoretical contribution of this study is to reveal the key role of psychosocial factors in the service recovery process, and the practical implication is to provide a flexible way for enterprises to utilize AI customer service and live customer service to enhance the effectiveness of their service recovery strategies in different contexts.
In summary, this study not only enriches the theoretical foundation of the service management field, but also provides practical guidance for the recovery strategy of enterprises in the face of service failure, which is expected to help enhance consumer satisfaction and enterprise competitiveness.

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