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The purpose of this study was to examine the mediating effect of three coping strategies (i.e. active, expressive, and denial coping) in the relationships between service failures (i.e. high- and low-contact service failures) and negative behavioral intentions (i.e. switching intention).

The critical incident technique (CIT) was used to identify the conceptually categorized service failure types in the fitness industry, and then confirmatory factor analysis (CFA) and structural equation modeling (SEM) were performed to examine the mediating effect of coping strategies among high-contact service failure and switching intention (study 1) and the mediating effect of coping strategies among low-contact service failure and switching intention (study 2).

While the mediating effect of coping strategies was significant in the relationship between high-contact service failures (study 1) and negative behaviors (i.e. switching intention and complaints), it was not significant in the relationship between low-contact service failures (study 2) and switching intention. Out of the three coping strategies, the impact of active coping was significant.

This study extends the understanding of the mediating effect of coping strategies in the relation between high- and low-contact service failures and switching intention.

The present study undertakes an extensive review of the causes of service failures in artificial intelligence (AI) technology literature.

A hybrid review has been employed which includes descriptive analysis, and bibliometric analysis with content analysis of the literature approach to synthesizing existing research on a certain topic. The study has followed the SPAR-4-SLR protocol as outlined by Paul et al. (2021). The search period encompasses the progression of service failure in AI from 2001 to 2023.

From identified theories, theoretical implications are derived, and thematic maps direct future research on topics such as data mining, smart factories, and among others. The key themes are being proposed incorporates technological elements, ethical deliberations, and cooperative endeavours.

This research study makes a valuable contribution to understanding and reducing service defects in AI by providing insights that can inform future investigations and practical implementations. Six key future research directions are derived from the thematic and cluster discussions presented in the content analysis.

While many studies have focused on the effectiveness of service recovery after encountering service failure, few have considered for pre-recovery opportunities. Drawing on service guarantee research and the inoculation theory, this study examines the effect of pre-recovery strategy on customer’s satisfaction when faced with possible service failure. This study takes into consideration the uncertainty of service failure, including specific or unpredicted failures.

Three experimental studies were conducted to examine our research hypotheses, which include a total of 1203 subjects recruited from online and offline platforms.

The findings reveal that service guarantees and inoculation messages both effectively mitigate the negative consequences of a service failure. Specifically, the pre-recovery strategy is particularly effective for specific service failures. In addition, we thoroughly examined the mediating role of customer attribution.

This research significantly contributes to the existing literature on service research by delving into the potential positive impact of proactive measures undertaken by service enterprises. Furthermore, the findings of this research offer valuable insights for practitioners.

As opposed to conventional promotional methods, Word-of-Mouth (WOM) communication, especially when negative, significantly shapes customers’ repurchase decisions and preferences. Therefore, this study aims to examine the interplay between negative WOM and bank service failures, with a focus on the mediating role of customer switching intentions and the moderating role of switching costs in this relationship.

Using an online semi-structured questionnaire survey, a dataset comprising 411 responses was gathered from retail bank customers in China. This dataset was subsequently analyzed using SPSS PROCESS.

Consistent with the social exchange theory, our study revealed a significant relationship between service failure and both bank customers’ intention to switch and negative WOM communication. Additionally, we observed that switching intentions significantly influence negative WOM communications, acting as a mediator between service failures and negative WOM. Furthermore, our findings indicated that switching costs moderate the direct effect of service failures on negative WOM and moderate the indirect effect of service failures on negative WOM through switching intentions.

This study provides significant policy implications aimed at minimizing bank service failures and subsequent negative WOM communications among bank customers.

This study empirically investigates the role of service failures in promoting negative WOM communication, demonstrating a partial mediation effect of switching intentions in this relationship. Moreover, the study highlights that switching costs moderate service failures’ impact on customers’ switching intentions.

The purpose of this study is twofold: first, to identify the categories of artificial intelligence (AI) chatbot service failures in frontline, and second, to examine the effect of the intensity of AI emotion exhibited on the effectiveness of the chatbots’ autonomous service recovery process.

We adopt a mixed-methods research approach, starting with a qualitative research, the purpose of which is to identify specific categories of AI chatbot service failures. In the second stage, we conduct experiments to investigate the impact of AI chatbot service failures on consumers’ psychological perceptions, with a focus on the moderating influence of chatbot’s emotional expression. This sequential approach enabled us to incorporate both qualitative and quantitative aspects for a comprehensive research perspective.

The results suggest that, from the analysis of interview data, AI chatbot service failures mainly include four categories: failure to understand, failure to personalize, lack of competence, and lack of assurance. The results also reveal that AI chatbot service failures positively affect dehumanization and increase customers’ perceptions of service failure severity. However, AI chatbots can autonomously remedy service failures through moderate AI emotion. An interesting golden zone of AI’s emotional expression in chatbot service failures was discovered, indicating that extremely weak or strong intensity of AI’s emotional expression can be counterproductive.

This study contributes to the burgeoning AI literature by identifying four types of AI service failure, developing dehumanization theory in the context of smart services, and demonstrating the nonlinear effects of AI emotion. The findings also offer valuable insights for organizations that rely on AI chatbots in terms of designing chatbots that effectively address and remediate service failures.

With the increasing use of robots in service scenarios in hospitality industries, service failure frequently occurs during the service process, and consumers may react differently toward humanoid vs. nonhumanoid robots due to different performance expectancies. This study focuses on consumers' reactions to service failures by humanoid vs. nonhumanoid robots and the different impacts on brand forgiveness and revisit intentions through performance expectancy for different genders.

The study used a sample of 280 participants to test the moderated chain mediation model. The participants were instructed to report their performance expectancies for humanoid/nonhumanoid robots and imagine a hotel check-in scenario in which a service failure occurs. Brand forgiveness, brand revisit intention and other demographic information were assessed.

The results show that consumers have higher performance expectancy for nonhumanoid robots. This performance expectancy generates brand forgiveness and revisit intentions for male consumers but does not affect female consumers' forgiveness and revisit behaviors.

This study contributes to the literature by taking a long-term perspective to investigate the outcomes after service failure, providing evidence for pending questions in previous studies and enriching studies of gender differences. Additionally, this study provides practical implications to consider the use of anthropomorphism in robots, advocate for functional confidence in robots and target consumers across genders.

The purpose of this paper is to investigate the moderating role of cultural factors (concern for face and stability of attribution) in the relationships among service recovery quality, postrecovery satisfaction and repurchase intention. Based on the politeness theory, this paper proposes a theoretical model for understanding how concern for face and stability of attribution may affect collectivists’ consumption behavior.

Data were collected in a field survey of 600 Hong Kong consumers who had experienced a telecommunications service failure. Partial least squares structural equation modeling (PLS-SEM) was used to test the theoretical hypotheses.

A cultural factor of concern for face is found to negatively moderate the relationship between service recovery quality and postrecovery satisfaction. Face also positively influences the relationship between postrecovery satisfaction and repurchase intention. Another cultural factor, stability of attribution, is found to negatively moderate the relationship between service recovery quality and postrecovery satisfaction and to negatively moderate the relationship between postrecovery satisfaction and repurchase intention.

This study contributes to the understanding of the relevance of concern for face and stability of attribution in collectivists’ consumption behavior. The findings have significant implications for managers in a position to exploit the cultural value mechanisms of collectivist consumers.

To the best of the authors’ knowledge, this has been the first research to examine the impact of concern for face and stability of attribution among service recovery quality, postrecovery satisfaction and repurchase intention.

This study aims to explore whether seeking recommendations for doctors from offline word-of-mouth or online reviews influences patient satisfaction after treatment, and how the source of recommendation affects this effect.

Using a unique dataset of more than three million reviews from a popular Chinese online health community, this study used the coarsened exact matching method and built fixed-effect models to conduct empirical analysis.

The results suggest that selecting doctors according to recommendations can improve patient satisfaction and mitigate their dissatisfaction when encountering service failures. However, online recommendations were found to be less effective than offline sources in improving patient satisfaction.

This study provides important insights into patient satisfaction and doctor-patient relationships by revealing the antecedents of satisfaction and the potential for improving this relationship. It also contributes to the understanding of how recommendations in the healthcare context can improve patient satisfaction and alleviate the negative impact of service failures.

As a company’s corporate social responsibility (CSR) image can protect from the backlash of a service failure, it is important to remind customers of the company’s CSR commitment when a service failure occurs. One novel mechanism for doing so is through a prosocial service recovery. However, explorations of such service recovery strategies are relatively unknown. Thus, this paper aims to examine how recoveries including prosocial elements compare to those only utilizing monetary compensation strategies and to explore boundary conditions for such effects.

This research utilizes an experimental design approach across three studies. Participants were recruited from Amazon’s Mechanical Turk.

This research demonstrates that a recovery including prosocial (vs only monetary) elements can positively impact purchase intent through the firms’ CSR perceptions. The authors show that the benefits of prosocial compensation are contingent on the motivation for visiting a company (e.g. hedonic vs utilitarian) as well as the degree to which the company is perceived as luxurious.

The series of studies provides important theoretical contributions to services marketers by advancing the understanding of novel recovery strategies and demonstrating when companies should initiate such strategies. Implications of the findings and directions for future research are explored.

The purpose of this research is to investigate the effects of service recovery experiences on customer engagement in negative word-of-mouth (WOM) in the hotel industry and explore the psychological motives and mediating mechanisms driving consumer behavior.

A scenario-based experimental design on Qualtrics was used, with a pre-test (N = 200). The main study data were collected using Amazon's Mechanical Turk platform.

Findings reveal that negative service experiences lead to higher engagement in negative WOM compared to positive and satisfactory recovery service experiences. Even well-executed recovery efforts may not completely eliminate negative WOM. The mediating role of emotional responses is substantiated, as heightened negative service experiences result in more intense negative emotional responses, leading to increased engagement in negative WOM.

The study emphasizes the importance of service recovery strategies and the need for businesses to consistently strive for exceptional service quality. It also highlights the complexity of customer reactions to service experiences, suggesting that further research is needed to explore the factors that minimize negative WOM across various service contexts.