Service Failure Types Research Articles

Are companies better off with AI? The effect of AI service failure events on firm value

PurposeAs more firms adopted AI-related services in recent years, AI service failures have increased. However, the potential costs of AI implementation are not well understood, especially the effect of AI service failure events. This study examines the influences of AI service failure events, including their industry, size, timing, and type, on firm value.Design/methodology/approachThis study will conduct an event study of 120 AI service failure events in listed companies to evaluate the costs of such events.FindingsFirst, AI service failure events have a negative impact on the firm value. Second, small firms experience more share price declines due to AI service failure events than large firms. Third, AI service failure events in more recent years have a more intensively negative impact than those in more distant years. Finally, we identify different types of AI service failure and find that there are order effects on firm value across the service failure event types: accuracy > safety > privacy > fairness.Originality/valueFirst, this study is the initial effort to empirically examine market reactions to AI service failure events using the event study method. Second, this study comprehensively considers the effect of contextual influencing factors, including industry type, firm size and event year. Third, this study improves the understanding of AI service failure by proposing a novel classification and disclosing the detailed impacts of different event types, which provides valuable guidance for managers and developers.

Can service robots recover themselves? The effect of service recovery agents and robot service failure types on customer response

As service robots become more widely deployed, the risk of service failures has increased, making it crucial to understand how service enterprises can effectively recover from such failures. Drawing on role congruity theory, we explore the performance of different recovery agents across various robot failure contexts. Through three experiments, we demonstrate that customer forgiveness and satisfaction improve for process failures caused by robots when service recovery is handled by human staff or a warm robot. Conversely, recovery efforts by human staff or a competent robot boost customer forgiveness and satisfaction in response to outcome failures triggered by robots. In addition, perceived role congruity acts as a mediator in the above interaction effects. Moreover, proactive recovery moderates these effects. This study offers a nuanced understanding of service recovery by refining robot service failure and recovery agent typologies, thereby enriching research in robot service recovery.

It’s all your fault! restaurant vs. platform blame attribution in food delivery service failures

PurposeWhile third-party food delivery continues to increase in popularity, surveys suggest nearly a quarter of deliveries suffer from service failures. With the limited research on third-party food delivery, we explore the important questions of (1) where customers place blame in the case of service failures with third-party food delivery (i.e. the platform or the restaurant) and (2) does this depend on the type of service failure? Drawing on blame attribution theory, signaling theory, and an exploratory study, we demonstrate that customers typically perceive such mishaps to be the responsibility of the restaurant rather than the delivery platform itself. We also examine the effect of visible service failure preventative actions taken by the restaurant on blame attribution and re-order intention.Design/methodology/approachWe conducted two online scenario-based studies to explore customer blame attribution in the case of third-party food delivery service failure. First, an exploratory study approach (NStudy1 = 512) was taken to provide additional support for the hypothesis development. An experiment (NStudy2 = 252) was then conducted to examine the hypothesized effects.FindingsFirst, the results of an exploratory study demonstrate that customers attribute service failures such as wrong items, missing items, cold food, or leaking containers to restaurants over third-party food delivery platforms. Second, the results of an experimental study suggest inclusion of an observable cue indicating preventative action, such as time-stamp information indicating when an order was received and packaged for delivery, increases customer re-order intention through the underlying mechanism of blame attribution.Originality/valueWe contribute to the underexplored area of third-party food delivery service failure and to our understanding of blame attribution in service failure scenarios. Further, we demonstrate a practical method to shift the blame away from restaurants for service failures that are outside of the establishment’s control.

It’s better than nothing: The influence of service failures on user reusage intention in AI chatbot

Artificial intelligence (AI) chatbot have become increasingly popular as a tool for improving employee productivity over the last few years. In the early stages of AI chatbot development, exploring the impact of AI chatbot service failures on user reusage intention is useful for coordinating human–computer interaction and optimizing AI chatbot service mechanisms. The extant literature on AI service failures focuses on service recovery and anthropomorphism. There is less literature comparing different types of service failures and their effects. The article includes three studies. First, a randomized group experiment was conducted with 120 respondents. The results showed significant differences in the impact of different AI chatbot service failures on user reusage intentions. Second, an online questionnaire was completed by 386 respondents, the results found specific impact mechanisms of service failures on user reusage intentions. Third, an interview survey was conducted with 15 customers using AI chatbots to verify the findings of Study 1 and Study 2. Furthermore determine the boundary conditions for the unsupported hypotheses through meta-inference. The research enriches the literature on relationship marketing and expands the attribution theory of service failures. In addition, which provides theoretical basis and practical support for companies to reduce adverse effects of service failures.

How does AI agent (vs. IVR system) service failure impact customer purchase behavior: mediating effect of customer involvement

ABSTRACT In recent years, the use of artificial intelligence (AI) agents in customer service has become a prominent area of study, focusing on their influence over consumer behavior. However, there is a noticeable gap in the current literature regarding AI agent service failures during product information consultations and their effects on customer purchase behavior. The present study, grounded in attribution theory, investigates the effects of various types of self-service failures in both Interactive Voice Response (IVR) systems and AI agents on customer involvement and subsequent purchase behavior. The findings indicate that customers experiencing service failures with AI agents during the consultation stage are more inclined to make purchase behavior after human-led recovery compared to those encountering IVR system failures. Additionally, customer involvement is found to play a pivotal role as a mediator between types of service failures and purchase behavior. The results of this work may offer valuable theoretical and practical insights.

Recourse strategy for the routing problem of mobile parcel lockers with time windows under uncertain demands

It is expected that mobile parcel lockers (MPLs) will provide more responsive and flexible service to the increasing variation of demand than fixed parcel lockers. However, the service provided by MPLs following planned routes can be degraded and even fail due to the demand uncertainty, such as demand volume and pickup time. In this study, we propose an optimization approach integrated with the recourse strategies to overcome this barrier. Three types of uncertain demands and two types of service failures are addressed in this study, with consideration of uncertain demands and time window constraint. To optimally determine the a priori routes for a set of MPLs, we propose a tailored tabu search algorithm by taking into account the recourse cost. A series of numerical experiments were conducted to examine the effectiveness of the proposed approach in enhancing route reliability with a comparison to ordinary express vehicles. The results reveal that the service reliability can be significantly improved with only a marginal increase in the operational cost by the proposed approach.

Airline Social Media Recovery Satisfaction: Has COVID Changed Everything?

This study deals with airlines’ handling of customer complaints pre- and post-Covid 19. Authors extracted airlines’ responses regarding redress, timeliness, apology, credibility, facilitation, and attentiveness and analyzed them pre- and post-pandemic. The results indicate the differential impacts of organizational responses on recovery satisfaction pre- and post-pandemic. Attentiveness (timeliness) had a significant role only pre- (post-) pandemic. Redress, credibility and facilitation remained crucial in both scenarios. Further, pre-pandemic results showed that the impact of organizational responses (credibility, timeliness, and facilitation) on recovery satisfaction was greater for failures associated with core rather than augmented elements of airline service. In the post-pandemic scenario, the impact of organizational responses on consumers’ recovery satisfaction was the same for both categories of service failures. Thus, post-pandemic, airlines may emphasize redress, credibility, timeliness, and facilitation responses in their social media posts for both service failure types.

Linking employee voice to service recovery performance in the hotel sector: The mediating role of tacit knowledge sharing and employee innovation

PURPOSE: In reality, service failures are inevitable. However, poor service recovery can decrease customer trust and exacerbate customer dissatisfaction. Previous studies have focused on service failure types, reasons for failure, and successful recovery actions from the customers’ perspective. Accordingly, this study aims to present adifferent view by investigating the factors that could improve hotel recovery performance from the employees’ perspective. Therefore, amodel was developed to study the influence of employees’ voice, tacit knowledge sharing, and employee innovation on service recovery performance. METHODOLOGY: This quantitative study used an online survey to gather data from employees in the hotel industry in Jordan. Atotal of 214 valid responses were obtained. Participants were targeted randomly, mainly through Facebook groups for hotel employees. PLS-SEM (Partial Least Squares Structural Equation Modeling) was employed in this research to analyze the data using Smart PLS 3 software. FINDINGS: The results indicated that employee voice is positively associated with tacit knowledge sharing. Furthermore, it was found that tacit knowledge sharing is positively related to employee innovation. The findings demonstrated that tacit knowledge plays apartial mediating role in the association between employee voice and employee innovation. Additionally, it was discovered that employee innovation has apositive association with service recovery performance. Finally, the results indicate that employee innovation partially mediates the relationship between tacit knowledge and service recovery performance. IMPLICATIONS: Hoteliers are suggested to create asupportive work climate where employees can express their thoughts, ideas, and concerns without fear of retribution. Furthermore, hotel managers are advised to establish clear expectations for employees regarding the significance of their opinions and insights, and recognize and reward innovative ideas that can hopefully enhance hotels’ performance. ORIGINALITY AND VALUE: This research provides new insights and contributes to the understanding of the role of employee voice, tacit knowledge sharing, and employee innovation in enhancing service recovery performance, particularly in acontext that has received little attention from researchers, which is the hotel sector, and in adeveloping country, Jordan. Compared to past studies, this study offers amodel that demonstrates how to leverage service recovery efforts in hotels by illustrating structured relationships between employee voice and service recovery performance through the mediation of tacit knowledge sharing and employee innovation.

You fooled me, so I’ll tell you about myself! personnel-related brand betrayal experiences and disclosure of personal information

Past research has extensively studied the negative effects of brand betrayals on consumer attitudes, but largely ignored their potential positive consequences. Also, while previous research has focused on betrayals made by the brand itself, it has paid less attention to betrayals by the brand’s personnel. This paper focuses on one potentially important positive consequence of brand personnel betrayal experiences (a consumer’s feeling of being betrayed by the brand staff members): the increased willingness of consumers to share personal insights and information with the brand after experiencing a brand personnel betrayal. A field data set and two online experiments show that consumers are more prepared to share personal information with the brand when experiencing brand personnel betrayals than when experiencing other types of service or brand failures. The effect is mediated by consumers’ social affirmation mindset and moderated by privacy concerns.

Research Status and Thinking of Service Failure and Service Recovery of Service Robot

With the development of intelligent technology, service robots have appeared in various service first-line environments, and consumers will inevitably encounter service failure of service robots. This paper analyzes the types of service failure by combing the relevant literature on service failure and service recovery, and based on the social cognitive theory, clarifies the remedial measures that should be taken after service robot fails. It is found that after process failure, the service robot makes emotional response such as apology or empathy, the service recovery effect is better; When the result fails, the service robot makes rational response such as explanation, the consumer's attitude is more positive. The research results provide practical enlightenment for enterprises to carry out service recovery.

I can feel AI failure: the impact of service failure type and failure assessment on customer recovery expectation

PurposeBased on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.Design/methodology/approachThree scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.FindingsNon-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.Originality/valueThe findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

A netnographic study with social media comments for investigating service failures

AbstractThis study demonstrates a netnographic study to investigate airline service failure types and to test differences of linguistic patterns among complaint types on social media user comments. User comments in an airline's Facebook community were scraped and service failure types were systematically classified with the measurement developed by thematic coding and literature review. The results presented frequently occurring service failure categories in airline service operations. A T‐Test was conducted to confirm the significant differences in linguistic characteristics between complaint comments and non‐complaint comments. Word frequency analysis showed distinctive word themes between the two comment groups. Research and managerial implications were provided.

공연예술 서비스 실패 유형이 서비스 회복에 미치는 영향

The purpose of this study is to investigate the effect of performing arts service failure types on service recovery and the mediating effects of cognitive response and emotional response compensation between them. 312 subjects who experienced performing arts service failure within 5 years were the study subjects, and SPSS 26.0 and AMOS 26.0 statistical programs were used for analysis. As a result of the study, it was found that among the failure types of performing arts service, human failure had an effect on cognitive response compensation and emotional response compensation, respectively. In addition, the mediating effect of cognitive and emotional compensation in the relationship between human failure and service recovery was confirmed. The conclusion of this study explained the importance of compensation plans when human failure occurred during performing arts services and suggested a compensation manual for service recovery.

The Roles of Service Recovery and Perceived Justice on Post-Recovery Satisfaction in M-Commerce

Mobile commerce is a fast-growing industry expected to grow continuously thanks to the wide acceptance of mobile phones and the worldwide 4G infrastructure. Previous research on m-commerce mostly focused on theory, technology acceptance, and legal issues, while service failure and recovery in m-commerce have not yet been covered. However, service failure is inevitable as the service process is complicated, and successful service recovery can retain customers. This research adopts an experimental study to discover the relationship between service failure, service recovery strategy, perceived justice, and post-recovery satisfaction in mobile commerce. The results confirm that, for different types of service failure, the effect of satisfaction level would differ for a different recovery strategy. Moreover, perceived justice would be affected by the service failure magnitude and service recovery strategy and would further affect post-recovery satisfaction. This study will provide an essential reference for both academicians and professionals to conduct further empirical validation or develop appropriate programs to solve service recovery issues.

Employee emotional competence and service recovery satisfaction: the mediating role of consumer forgiveness

PurposeEmployees' emotional competence (EEC) is gaining increasing attention in service failure and recovery research. This study investigates the mediating role of consumer forgiveness between perceived EEC and recovery satisfaction among casual dining consumers. Additionally, this study examines the effect of perceived EEC on recovery satisfaction across process failure vs outcome failure.Design/methodology/approachA critical incident technique (CIT) in conjunction with a self-administered online survey was carried out. Using the snowball sampling technique, a total of 204 useable responses were collected. To test the hypotheses, this study used partial least squares structural equation modeling (PLS-SEM).FindingsThe study finds that perceived EEC influences service recovery satisfaction. Additionally, the study identifies the mediating role of consumer forgiveness in the relationship between perceived EEC and recovery satisfaction. Multi-group moderation analysis shows that the relationship between perceived EEC and recovery satisfaction is weaker in process failures as compared to outcome failures.Practical implicationsBased on obtained results, this study recommends that after service failure consumer forgiveness and subsequent recovery satisfaction can be obtained with perceived EEC. To do so, managers need to incorporate emotional competence while recruiting and training the employees. Moreover, managers need to train employees on failure types and respective recovery strategies. Lastly, the study suggests that in emerging markets managers should pay greater emphasis on process failure, because such failure decreases customer satisfaction greatly than outcome failure.Originality/valueTo the authors' knowledge, this is the first study that investigates the impact of perceived EEC on consumer forgiveness which subsequently determines the recovery satisfaction in the emerging markets. It extends the application of the emotional contagion and affect infusion theories by exposing the effect of perceived EEC on recovery satisfaction through consumer forgiveness. In addition, the study provides insights that the influence of perceived ECC on recovery satisfaction significantly varies across service failure types.

Responding to negative reviews? The interplay of management response strategy and service failure type

ABSTRACT Restaurants often struggle with their approach to respond to service failure online. In this scenario-based experiment, the researchers study the effectiveness of management response types along with two overarching types of service failure concerning three outcomes. Some of the significant results are that it is not important whether the restaurant offers compensation or apology; as long as management responds to negative reviews, company’s reputation management works and customers are willing to shop from the restaurant. However, interestingly, with respect to customers’ recovery satisfaction, the findings underscored that companies should either not respond at all or should compensate dissatisfied customers instead of only writing an apology. Concerning the simultaneous existence of the technical and functional dimensions of a service failure regarding customers’ recovery satisfaction and their willingness to purchase from the restaurant, the findings underlined the centrality of technical dimension that is in contradiction with prior research findings. A discussion on findings is presented along with recommendations for future research.

Are you willing to forgive AI? Service recovery from medical AI service failure

PurposeAs an emerging technology, medical artificial intelligence (AI) plays an important role in the healthcare system. However, the service failure of medical AI causes severe violations to user trust. Different from other services that do not involve vital health, customers' trust toward the service of medical AI are difficult to repair after service failure. This study explores the links among different types of attributions (external and internal), service recovery strategies (firm, customer, and co-creation), and service recovery outcomes (trust).Design/methodology/approachEmpirical analysis was carried out using data (N = 338) collected from a 2 × 3 scenario-based experiment. The scenario-based experiment has three stages: service delivery, service failure, and service recovery. The attribution of service failure was divided into two parts (customer vs. firm), while the recovery of service failure was divided into three parts (customer vs. firm vs. co-creation), making the design full factorial.FindingsThe results show that (1) internal attribution of the service failure can easily repair both affective-based trust (AFTR) and cognitive-based trust (CGTR), (2) co-creation recovery has a greater positive effect on AFTR while firm recovery is more effective on cognitive-based trust, (3) a series of interesting conclusions are found in the interaction between customers' attribution and service recovery strategy.Originality/valueThe authors' findings are of great significance to the strategy of service recovery after service failure in the medical AI system. According to the attribution type of service failure, medical organizations can choose a strategy to more accurately improve service recovery effect.

Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots

The increasing application of artificial intelligence to online retailing and the rapid deployment of online robots have made online robot service failures common. This study explores consumer response mechanisms to different types of service failures and recovery strategies of chatbots based on role congruity theory and psychological accounting theory. Questionnaires were used to collect data and test hypotheses. The study found the following. First, chatbot service failures can affect consumers' choice of different recovery strategies. After the functional failure of chatbots, consumers are more inclined for the chatbot to be involved in service recovery. After the nonfunctional failure of chatbots, consumers are more inclined toward human involvement in service recovery. Second, different service recovery strategies affect the level of perceived governance. Compared with humans involved in service recovery, robots have a higher level of perceived governance. Third, the level of perceived governance affects consumers’ willingness to forgive. Fourth, the level of robot intelligence plays a moderating role in the types of service failures affecting the choice of recovery strategies. The findings of this study can enrich the response mechanisms and boundary conditions of online robot service failure and provide important insights for online retail enterprises to effectively respond to robot service failure and make reasonable use of human-robot collaborative work.

An Investigation of Customers’ Recovery Expectations after Service Failure: Evidence from e-Commerce Settings at Different Stages of Maturity

Although recovery strategy literature is developing rapidly, less is known about e-commerce customers’ recovery expectations in settings at different stages of e-commerce maturity. Using a grounded theoretical paradigm and drawing on the decoy effect and paradox of choice theories, we explore customers’ recovery expectations by analyzing 110 interviews with e-commerce customers and e-commerce managers in two settings at different stages of e-commerce maturity: Kosovo and the USA (Study 1). We propose a framework with three types of customers whose emotions during service failure and recovery (indicated by their recovery language), and the type of service failure experienced are cues to their recovery expectations. Utilizing exploratory factor analysis, this framework is validated through a survey of 171 randomly selected e-commerce customers (Study 2). The findings expand theoretical understanding, and provide managers with guidelines for the alignment of customers’ expectations and e-commerce recovery delivery.

Service failure in peer-to-peer accommodation

A two-stage study using text-mining and critical incident techniques was conducted to identify the service failure type in peer-to-peer accommodation and recovery strategies adopted to address them. Guests experience new types of service failure in peer-to-peer accommodation compared with traditional accommodations and online travel websites. Four service failure clusters have emerged from negative reviews sourced online: guest-host interaction, customer service, room and amenity, and payment. In-depth interviews further identified three dimensions of service failure, tangible, informational, and relational, with some incidents representing combinations of these dimensions. Service recovery strategies discussed in this study (compensation, substitution, apology, and no actions) are relatively similar to those adopted by hotels. Theoretical and practical implications are also provided.