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Using a mixed-methods approach, the current research examines online incivility in relation to service recovery on social media. First, findings from a netnographic investigation suggest consumer-to-consumer (C2C) incivility results in some consumers holding the firm accountable to address uncivil exchanges on a firm-managed communication channel. Based on the netnographic findings, fairness theory, and justice theory, a follow-up experimental study assesses how online incivility negatively affects service recovery outcomes (firm–consumer justice) when a firm chooses (not) to respond to the incivility. Through these two studies, the current paper proposes a new form of justice (C2C interactional justice) and posits that online service recovery extends beyond direct victims of the incivility (first-party justice) to also include observers (third-party justice). This more nuanced view of justice associated with a service recovery is especially significant when considering the traditional relationships of justice with satisfaction, loyalty, positive word-of-mouth, and other desirable firm outcomes. For practitioners, this research suggests that firms must manage C2C interactional justice on corporate social media channels for both complainants and observers to avoid reputational damage and a loss of customers.

Purpose Artificial intelligence (AI) is currently having a dramatic impact on marketing. Future manifestations of AI are expected to bring even greater change, possibly ushering in the realization of the fourth industrial revolution. In accord with such expectations, this paper aims to examine AI’s current and potential impact on prominent service theories as related to the service encounter. Design/methodology/approach This paper reviews dominant service theories and their relevance to AI within the service encounter. Findings In doing so, this paper presents an integrated definition of service AI and identifies the theoretical upheaval it creates, triggering a plethora of key research opportunities. Originality/value Although scholars and practitioners are gaining a deeper understanding of AI and its role in services, this paper highlights that much is left to be explored. Therefore, service AI may require substantial modifications to existing theories or entirely new theories.

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This article offers a new perspective on customercompany identification (CCI) by focusing on CCI's underlying self-motives: self-uncertainty and self-enhancement. More precisely, an operationalization is proposed in which cognitive (CCI Cog ) and affective (CCI Aff ) dimensions of CCI are driven by different self-motives: CCI Cog by self-uncertainty and CCI Aff by self-enhancement. Focusing on these self-motives reveals that CCI Cog and CCI Aff affect some customer attitudes and behaviors in opposite ways but affect other attitudes and behaviors similarly. A cross-sectional survey that examines outcomes of CCI Cog and CCI Aff supports the proposed conceptualization of CCI and suggests the dimensions differ in how each impacts customer-company relationships. Furthermore, the study suggests that combining the dimensions together in higher order constructs or examining only one dimension can lead to misleading conclusions.