Service recovery strategies: mitigating negative word-of-mouth in the hotel industry through enhanced customer engagement

Abstract

Purpose

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.

Design/methodology/approach

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

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.

Originality/value

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.

Citation

Sukhu, A. and Bilgihan, A. (2023), "Service recovery strategies: mitigating negative word-of-mouth in the hotel industry through enhanced customer engagement", International Hospitality Review, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IHR-05-2023-0025

1. Introduction

Consumers consistently share information with others, and social media platforms such as Facebook, Snapchat, Instagram, Twitter and TripAdvisor have become popular channels for these exchanges (Balabanis & Chatzopoulou, 2019). Through these platforms, consumers engage daily in discussions about various consumption topics, ranging from restaurant dining experiences to electronics, music concerts and clothing. As a result, brands have increasingly allocated resources to word-of-mouth (WOM) marketing (Glover, 2021), and researchers have endeavored to provide guidance for marketers to maximize WOM's potential (Bastos & Moore, 2021).

Historically, research in the WOM domain has primarily focused on its valence, such as positive or negative reviews stemming from customers' experiences with brands (Dellarocas, Zhang, Michael, & Awad, 2007; Sweeney, Soutar, & Mazzarol, 2014). This study contributes to the existing body of knowledge by examining negative WOM (NWOM) and its underlying mechanisms, which have been relatively underexplored (Laczniak, DeCarlo, & Ramaswami, 2001) despite their significance.

NWOM can quickly spread and inflict substantial harm on businesses, impacting brand reputation and revenue (Chen, Law, & Yan, 2022). It can also lead to decreased traffic, financial support and available resources (Blake, 2017). A survey of 1,046 customers found that approximately half of the participants shared unsatisfactory experiences with more than five individuals, while only 33% shared positive experiences with a similar number of people (Dimensional Research, 2013). Consequently, the propensity to disseminate NWOM exceeds that of positive WOM. Companies must therefore minimize NWOM to enhance profitability and foster positive brand equity perceptions (Sweeney et al., 2014). Social media in the context of this study serves as a primary platform for the rapid dissemination of information, including the spread of NWOM. The ease of communication amplifies the potential impact of NWOM on businesses and brands. Recent research highlights the role of social media in the propagation of NWOM. For example, a study by Xiao, Luo, & Ke (2022) demonstrated that NWOM shared through social media platforms can significantly influence consumer decision-making, leading to a decrease in brand trust and purchase intentions. Another study by Lee, Kim, & Lim (2021) revealed that negative emotions resulting from unsatisfactory experiences are more likely to be shared on social media, leading to a wider reach of NWOM. The authors also found that NWOM on social media can generate a “ripple effect,” wherein the negative sentiments expressed by dissatisfied customers can influence the opinions of other consumers in their social networks, further exacerbating the damage caused by NWOM. Furthermore, research by Azemi, Ozuem and Howell (2020) emphasized the importance of engaging with consumers on social media platforms, as a lack of engagement can create a breeding ground for NWOM. By proactively addressing consumer complaints and concerns on social media, businesses can mitigate the spread of NWOM and foster a more positive online brand image.

A key question is what determines WOM valence. Customers are less likely to engage in NWOM following a positive service experience (Jeong & Jang, 2011), while they tend to propagate NWOM after a negative service experience (Tsai, Yang, & Cheng, 2014). However, timely intervention by management can transform a negative experience into a satisfactory recovery, reducing NWOM (Tax, Brown, & Chandrashekaran, 1998). Properly addressing service failures is crucial, as inadequate handling may result in customers disengaging or perpetuating NWOM (Kalia & Paul, 2021). Prior research has shown that satisfactory recovery efforts can mitigate the adverse effects of service failures (Xu, Liu, & Gursoy, 2019) and even generate more positive feedback than positive experiences alone (Zoghbi-Manrique-de-Lara, Suárez-Acosta, & Aguiar-Quintana, 2014).

This study explores the relative influence of positive, negative and satisfactory recovery service experiences on negative word-of-mouth (NWOM). Utilizing a scenario-based experimental design and one-way ANOVA analysis, it provides a nuanced understanding of the factors that can either exacerbate or mitigate the spread of NWOM. The research delves into the psychological factors that drive consumers to engage in NWOM and the mediating mechanisms that come into play during the process. Preliminary findings suggest that effective service recovery can significantly reduce the spread of NWOM. This approach provides a deeper understanding of the consumer mindset, allowing marketers and businesses to tailor their strategies for addressing service failures and customer dissatisfaction more effectively. Refer to Figure 1 for the proposed model of this research.

2. Theoretical background and hypotheses development

While several theories aim to understand the dynamics of service failures and recovery, this study primarily draws upon the Justice Theory and the Service Recovery Paradox. The choice of these theories is motivated by their comprehensive approach to investigating service failure, recovery efforts and their effects on consumer behaviors such as satisfaction, WOM and loyalty.

Justice Theory forms the backbone of this study, guiding us to explore service recovery efforts' influence on customers' justice perceptions after they experience a service failure.

The Service Recovery Paradox complements this study by emphasizing the positive outcomes that can arise from effective service recovery efforts, even when a service failure has occurred. This theory is pivotal to our research as it highlights the potential for successful recovery strategies to not only mitigate the adverse effects of service failure but also to enhance customer satisfaction and loyalty, possibly to levels higher than if the failure hadn't happened. We aim to investigate this paradox further, advancing the research on the possible inconsistencies present within this theory. The Expectancy Disconfirmation Theory (EDT) and Attribution Theory, while not forming the main theoretical foundation of our study, offer valuable insights into customer satisfaction dynamics and failure attribution, respectively. Their principles have been considered while framing our hypotheses and understanding the context of service failure and recovery. Subsequent sections discuss these theories in detail.

2.1 Service failure theories

Several theories in the services marketing failure theories aim to understand the underlying causes and consequences of unsatisfactory service experiences. Respective theories have been developed to explain service failure and its effects on consumer behavior. The prominent theories include:

2.1.1 Expectancy disconfirmation theory (EDT):

EDT is a widely used theory to explain consumer satisfaction and dissatisfaction with services. According to this theory, consumers form expectations about a service before experiencing it. After receiving the service, they compare the actual performance with their initial expectations (Abrate, Quinton, & Pera, 2021). If the service meets or exceeds expectations, they feel satisfied. Conversely, if the service falls short of expectations, they feel dissatisfied, which is considered a service failure (Oliver, 1980). The current research adopts the customer satisfaction as a construct to understand the impact of the recovery attempts.

2.1.2 Attribution Theory:

Attribution theory focuses on how consumers attribute the cause of service failure to different factors, such as the service provider, external circumstances, or themselves (Fu et al., 2021). This theory suggests that consumers are more likely to be dissatisfied when they attribute the service failure to the service provider's internal factors (e.g. lack of competence or effort) rather than external factors (e.g. uncontrollable circumstances). Understanding the attributions consumers make can help businesses design effective service recovery strategies. The current research focuses on the service provider’s internal factors to investigate the service recovery efforts.

2.1.3 Justice theory:

Justice theory comprises three dimensions: distributive justice, procedural justice and interactional justice (Tax et al., 1998). Distributive justice refers to the fairness of the outcome (e.g. compensation) in response to service failure. Procedural justice pertains to the fairness of the process followed by the service provider to resolve the issue. Interactional justice involves the interpersonal treatment customers receive during the service recovery process. According to this theory, if customers perceive the recovery efforts as fair across all three dimensions, they are more likely to feel satisfied and less likely to spread NWOM. The current research uses the justice theory as a theoretical lens to investigate the influence of recovery efforts on customers’ justice perceptions after they experience a service failure.

2.1.4 Service recovery paradox:

The service recovery paradox posits that a well-handled service recovery can result in higher customer satisfaction and loyalty than if the service failure had never occurred (Van Vaerenberg et al., 2019). This theory emphasizes the importance of effective service recovery efforts in mitigating the adverse effects of service failure and reducing the spread of NWOM. This research attempts to advance the inconsistencies in the service recovery paradox research.

2.2 Negative word of mouth

Consumers engage in negative WOM for various reasons. The reviewer is perceived as more competent and intelligent when they write negative reviews compared to positive reviews (Amabile, 1983). Expressing a negative experience to others can provide consumers support and consolation (Rimé, 2009). Research suggests that NWOM is a form of venting as angry and dissatisfied consumers engage in more negative WOM (Bougie, Pieters, & Zeelenberg, 2003). Hospitality consumers may engage in vindictive NWOM as a result of an experience of service failure (He & Harris, 2014; Moon et al., 2017).

In the exploration of online NWOM behavior, El-Manstrly et al. (2021) delve into the concept of online vindictive WOM, which emerges in response to severe service failures. They bring forward the novel idea of examining online vindictive WOM as a coping mechanism. Their survey of restaurant customers emphasized the significance of both psychological and situational factors that propel customers towards adopting NWOM behavior as a strategy to cope with harsh service failures. Such insights provide a new dimension to the understanding of NWOM behavior, including its development, underlying processes and ramifications such as damaging a firm's image, loyalty and market share. This study serves as an essential reference for our research as it explores the dynamic landscape of WOM, particularly in the context of service failures and recoveries.

NWOM can occur in a private setting where customers express grievances to family members, friends and acquaintances or also in a public setting where customers complain to a broader audience (Goetzinger, 2007). Irrespective of the setting, NWOM leads to more negative behaviors (Relling et al., 2016) such as a drop in sales and market share.

NWOM is critical for hotel performance and success (Kim et al., 2015). NWOM adversely affects the hotel business. For example, negative reviews can damage a hotel’s reputation (Rose & Blodgett, 2016) leading to a decrease in occupancy rate. However, timely management interference can reduce the negative effects caused by a bad service experience (Min et al., 2015; Rose & Blodgett, 2016).

WOM is considered the most effective and cheapest way of marketing hotels. Today, hotels have to offer more than a clean room in a good location. Hotels need to be buzzworthy to get good business. People telling other people about their good experiences in hotels is a powerful tool to get more customers (Ting, 2017). On the other hand, NWOM has the opposite detrimental effect on losing customers, reducing daily rates and eventually losing business. Therefore, hotel businesses need to understand the sources of NWOM and the psychological process behind it.

2.3 Service experience (positive, negative, satisfactory recovery) and negative WOM behavior

In the realm of service management, service recovery is crucial to maintaining customer satisfaction and loyalty, especially in the face of a negative service experience. Bitner, Booms and Tetreault (1990) provide valuable insights into the factors that contribute to positive and negative service encounters from a customer's perspective. This research is relevant to the topic of service recovery, as it sheds light on the specific events and behaviors of contact employees that lead to customer dissatisfaction, which in turn necessitates service recovery efforts. Consumers generally evaluate service experience as positive or negative. In the event of a positive service experience, consumers typically engage less NWOM (Jeong & Jang, 2011). Positive experiences evoke positive emotions which reduces the chance of NWOM. When customers experience a positive service from a hotel, restaurant, or bar, they tend to engage in positive WOM than negative WOM (Ferguson et al., 2010).

Consequently, when the experience is negative, consumers tend to engage in negative WOM. Service experience is a holistic mix of various factors. When one or some of these factors fail at the time of service experience it results in negative WOM (Tsai et al., 2014). For example, the customer can evaluate a service experience as negative due to an impatient server or receptionist. However, in the event of a service recovery package, customers’ negative feelings are ameliorated due to the timely actions by the management (Tax et al., 1998). Problems are bound to happen in any service industry. Resolving failures and reassuring customer faith in the provider results in less negative WOM compared to a negative service experience (Tax & Brown, 2012). A timely service recovery, therefore, has the potential to transform an angry and upset customer into a happy one. A service recovery strengthens the emotional bonding between the customer and service provider and customers will engage in less negative WOM after a satisfactory service recovery experience (Choi & Choi, 2014). According to the study conducted by (Whatling, 2017) customers who had a negative experience tend to spread negative WOM more than customers who received a positive experience.

Additionally, meaningful recovery efforts such as timely apology and compensation help to reduce negative WOM. Aureliano-Silva, Spers, Lodhi and Pattanayak (2022) found that recovery actions taken by a company to after a service strengthens the customers’ trust in the brand as well as their purchase intention. In the realm of digital customer service, a study conducted by Yun and Park (2022) highlighted the important role of chatbots in shaping customer satisfaction, repurchase intention and positive word-of-mouth by utilizing service recovery strategies. The implications of these findings extend beyond the scope of digital customer service interactions; they demonstrate the crucial impact of customer satisfaction on driving repurchase intentions and generating positive word-of-mouth. These insights are relevant to our current study as we examine how service recovery efforts and perceived justice following a service failure influence customer satisfaction and, subsequently, word-of-mouth communication. Based on the above, it is posited that:

H1.

In the event of a negative service experience, consumers’ negative WOM will be significantly higher compared to a positive and satisfactory recovery service experience.

H2.

In the event of a positive service experience, consumers’ negative WOM will be significantly lower compared to a negative and satisfactory recovery service experience.

H3.

In the event of a satisfactory recovery experience, consumers’ negative WOM will be significantly higher compared to a positive service experience but lower compared to a negative service experience.

2.4 Mediation

2.4.1 Negative service experience, emotional responses and WOM

A negative experience or a service failure represents a contrast with customer expectations resulting in customers engaging in coping mechanisms (Smith et al., 1999). Customers go through various internal processes to cope with the disconfirmation and unpleasant experience (Sarkar Sengupta et al., 2015). Consumer evaluations or appraisals of events create specific emotions (Lazarus, 1991). For example, when service failure happens some service providers are more likely to elicit positive emotional and behavioral reactions from consumers compared (Liu & Li, 2022). These emotions are elicited based on whether “the outcome is good or bad concerning one’s well-being” (Watson & Spence, 2007), p. 491). Service failures or negative service experiences lead to the formation of negative emotional responses (Sugathan et al., 2017). Service failure research conducted in various settings such as scenario-based experiments and field studies further confirmed that service failure leads to negative emotions such as anger and discontent (Kim & Jang, 2014). Such negative emotions lead to negative WOM (Moon et al., 2017). Customers who experience negative emotions as a result of a negative service experience tend to complain or engage in negative WOM (Mattila & Ro, 2008; Xie & Heung, 2012). Based on these discussions, the below hypotheses are posited.

H4.

The relationship between negative service experience and negative WOM is mediated through consumers’ negative emotional responses.

H4a.

Higher negative service experience leads to higher negative emotional responses.

H4b.

Higher negative emotional response leads to higher negative WOM.

Research suggests that there are inherent and strong connections between service experience and customer satisfaction (Xiang et al., 2015). Studies in the services and hospitality fields suggest that a positive service experience leads to higher customer satisfaction (Ali, Kim, Li, & Jeon, 2016; Ladhari et al., 2017). In service contexts, customer evaluates the quality of the experience by the experience leading to their satisfaction (Chen & Chen, 2010). There is an inextricable link between customer perceptions of service and satisfaction level (Pizam et al., 2016). Customer satisfaction consequently generates positive behavioral intentions (Chen & Chen, 2010) and lower negative WOM. Higher customer satisfaction generated by high-quality service experiences results in positive recommendations and reduces negative WOM (Cevdet altunel & Erkut, 2015). This leads to the below hypotheses.

H5.

The relationship between positive service experience and negative WOM is mediated through customer satisfaction.

H5a.

Higher positive experience leads to higher customer satisfaction.

H5b.

Higher customer satisfaction leads to lower negative WOM.

In the event of a service failure, companies offer monetary compensations, discounts, apologies and prompt responses to reassure customer-service provider bonding (Chou, 2015; Jung & Seock, 2017). Such recovery efforts increase customers’ justice perceptions after they experience a service failure (Choi & Choi, 2014). Therefore, service recovery strategies are tools to increase perceived justice and they usually result in favorable brand outcomes (Mostafa et al., 2015). A satisfactory recovery experience is positively related to customer perceptions of justice (Nikbin et al., 2015). Perceived justice is a key concept in the service recovery literature that refers to the extent to which customers perceive the outcome of a service recovery effort as fair and equitable (Leclercq et al., 2020). It plays a crucial role in determining customer satisfaction, loyalty and subsequent word-of-mouth following a service failure. Higher perceptions of justice resulted from satisfactory recovery efforts, which in turn, lead to favorable outcomes (Park & Ha, 2016). Recovery efforts, direct to regain the damaged customer-firm relation resulting from the service failure, lead to perceptions of justice followed by customer-brand bonding (Xu, Marshall, Edvardsson, & Tronvoll, 2014). Hence customers who experience a satisfactory recovery experience tend to have higher perceptions of justice, leading to lower negative WOM (Ha & Jang, 2009). This leads to the following hypotheses.

H6.

The relationship between a satisfactory recovery service experience and negative WOM will be mediated through consumers’ perceptions of justice for the recovery.

H6a.

Higher satisfactory recovery experience leads to higher perceptions of justice.

H6b.

Higher perceptions of justice lead to lower negative WOM.

See Figure 2 for the proposed research model and hypotheses.

3. Methodology

Our study adopted a quantitative approach, leveraging a scenario-based experiment and a web-based survey to gather data. Data analysis involved a range of statistical techniques, including manipulation checks, one-way ANOVA and mediation analysis using PROCESS Model 4 (Hayes, 2012). The study involved two distinct stages: a pre-test and a main study.

3.1 Survey development

After conducting an extensive review of the literature in the relevant fields, we proceeded to develop a survey to gather data. The survey questions were primarily adapted from previous studies to ensure their validity and reliability. However, necessary modifications were made to ensure that the questions were suitable for the specific context and objectives of the current study. The majority of the survey questions utilized a Likert-type scale, which is a widely used method for measuring respondents' attitudes or perceptions. In this case, a 5-point Likert scale was employed, with scale points ranging from “strongly disagree” (1) to “strongly agree” (5). This scale allowed the participants to express their level of agreement or disagreement with the statements presented in the survey. Before administering the survey to the target population, we conducted a small pilot study (N = 10) to assess the readability and flow of the survey questions. This preliminary study aimed to ensure that the survey was clear, easy to understand and coherent for the respondents. The pilot study involved a small group of participants who represented the target demographic, enabling the researchers to gather valuable feedback on the survey's structure, language and design. Based on the feedback received during the pilot study, we identified several areas for improvement. Some survey items were found to be unclear or confusing to the participants, prompting us to reword them to enhance their clarity and comprehensibility. By refining the language and phrasing, we ensured that the revised questions and scenarios accurately captured the desired information and were easily understood by the respondents (See Table 1 for measurement items and Appendix for the scenarios). The survey included a set of screening questions at the beginning to confirm that respondents are 18 or older, they have stayed in hotels in the past two years and they are familiar with WOM. Upon the satisfactory completion of the screening questions, respondents were presented with three service experience scenarios (See appendix). The scenarios were adapted from (Li, Qiu, & Liu, 2016) and slightly modified for the study. The survey included two attention check questions and included questions measuring the self-reported usage of WOM and demographic question items at the end.

3.2 Design

A scenario-based experimental design on the web-based data collection tool Qualtrics was used for the study. Research involving service encounters, scenario-based experiments were found to be appropriate because they ‘‘permit examination of the variable of most concern and often allow the best theory testing by enabling the investigator to gather all the needed responses.’’ (Weiner, 2000). Additionally, previous service encounter research found that scenario-based experiments offer ecological validity (Wirtz & Mattila, 2004). Contrary to the self-reporting method, scenario-based experiments reduce memory bias (Swanson & Hsu, 2011) and individual differences in data collection. It also offers improved variability in responses to in-service failure research (Wirtz & Mattila, 2004) provided that service encounters can be manipulated effectively. It also offers internal validity by the manipulation of variables and reduces noise on the dependent variable (Creswell, 2013). Scenario-based experiments are a viable and efficient research tool, particularly when studying service failures and recoveries.

3.3 Pre-test

3.3.1 Pre-test data collection and sample

Before conducting the main study using Amazon’s Mechanical Turk (MTurk) platform, a pre-test was conducted using a sample of 200 staff and faculty from a large Northeastern university. They were asked to complete the survey via email. This method aimed to prevent interview biases and time pressure on respondents.

3.3.2 Pre-test procedure

Upon passing the screening questions, participants were randomly assigned to one of the three service experience scenarios (i.e. positive, negative and satisfactory recovery). Following the presentation of scenarios, respondents were presented with manipulation check questions followed by measures of negative WOM, satisfaction, negative emotional responses and perceived justice.

3.3.3 Pre-test results

A total of 58 responses were collected with a response rate of 29%. All respondents were 18 years or older and stayed in hotels in the past two years. Fourteen respondents were deleted because they answered that they are not familiar with WOM. From the remaining 44 responses, nine responses were deleted due to missing values. The remaining 33 responses were used for the pre-test. Cronbach’s alphas for all the measurement items used for the study exceeded the recommended threshold of 0.70 (Bagozzi & Yi, 1988; Nunnally & Bernstein, 1994) (negative WOM was 0.85; negative emotional responses were 0.92; customer satisfaction was 0.96 and perceived justice was 0.83). Additionally, survey design, wording, question order, visual layout, survey content, difficulty and time were inspected, and the results seemed acceptable.

3.4 Main study

3.4.1 Data collection and sample

The data for the main study was collected using the data collection tool MTurk. Data collected from MTurk is as reliable and valid as other traditional data collection methods (Buhrmester, Kwang, & Gosling, 2011; Mason & Suri, 2012). MTurk data include workers from the entire USA and shows only minor differences from a random sample drawn from the US community (Ipeirotis, 2010). M-Turk sample is representative of a traditional US sample in terms of demographic backgrounds including age, gender, ethnicity, education and socio-economic characteristics (Buhrmester et al., 2011). MTurk offers a varied, nationwide selection of consumers and yields reliable data (Buhrmester et al., 2011; Kim & Baker, 2020).

3.4.2 Procedure

The survey used for the pre-test was posted on the MTurk website where workers can find the survey for participation. Upon the completion of screening questions, respondents were randomly presented with one of the three service experience scenarios and prompted to answer the questions.

3.4.3 Results

A total of 191 respondents completed the survey. A total of 169 responses were used for the final data analysis. First, a manipulation check was conducted using the chi-square test of independence. The results showed a significant difference X² ((4, N = 169) = 181.29, p < 0.000)) between the groups of negative, positive and satisfactory recovery. A post hoc test revealed that 77.8% of the respondents from the negative condition self-selected their experience as negative compared to 2.2% from the positive condition and 20% from the satisfactory recovery conditions. The adjusted residual for the people in negative conditions choosing their experience as negative was also significantly different (7.2) from positive and recovery conditions. A total of 95% of the respondents from the positive condition self-selected their experience as positive compared to 3.3 % from the negative condition and 1.7% from the recovery condition. The adjusted residual for the people in positive conditions choosing their experience as positive was also significantly different (12.2) from negative and recovery conditions. A total of 65.6% of the respondents from the recovery condition self-selected their experience as satisfactory recovery compared to 32.8 % from the negative condition and 1.6% from the positive condition. The adjusted residual for the people in recovery condition choosing their experience as satisfactory recovery was also significantly different (7.7) from the negative and positive conditions. Hence, the manipulations were successful such that people perceived the positive condition as a positive experience, the negative condition as a negative experience and the recovery condition as a satisfactory recovery experience.

To understand how positive, negative and recovery service experience influences negative WOM, a one-way ANOVA was conducted with three service experience conditions as the independent variables (positive, negative, recovery) and negative WOM as the dependent variable. The ANOVA revealed a significant difference (F_{2, 166} = 89.01, p < 0.000) in how the three service experience conditions influence negative WOM. A Tukey HSD post hoc test revealed that negative condition is significantly different from positive (p < 0.000) and recovery (p < 0.003) conditions. The positive condition is also significantly different from the recovery condition (p < 0.000). The mean (M) negative WOM was 3.83 for the negative condition; the mean (M) negative WOM was 1.50 for the positive condition; the mean (M) negative WOM was 3.21 for the recovery condition. These results provide statistical support for H1. After experiencing a negative service experience, consumers’ negative WOM is significantly higher compared to a positive and satisfactory recovery service experience. After experiencing a positive service experience, consumers’ negative WOM will be significantly lower compared to a negative and satisfactory recovery service experience, providing support for H2. Finally, after experiencing a satisfactory recovery service experience, consumers’ negative WOM is higher compared to a positive service experience but lower compared to a negative service experience, providing support for H3. Figure 3 shows the influence of positive, negative and satisfactory service experiences on negative WOM.

To test the mediating role of emotional responses in the relationship between negative service experience and negative WOM, a bias-corrected mediation analysis (Zhao et al., 2010) was conducted using the statistical tool PROCESS Model 4 (Hayes, 2012). The mean indirect effect of emotional responses was positive (0.53) for the negative service experience and the negative WOM and the 95% confidence interval did not include zero (Boot LLCI = 0.43, Boot ULCI = 0.65), indicating a significant mediation effect.

Next, to test the mediating role of satisfaction in the relationship between positive service experience and negative WOM, a bias-corrected mediation analysis (Zhao et al., 2010) was conducted using the statistical tool PROCESS Model 4 (Hayes, 2012). The mean indirect effect of satisfaction was negative (−0.41) for positive service experience and negative WOM and the 95% confidence interval did not include zero (Boot LLCI = −0.57, Boot ULCI = −0.29), indicating a significant mediation.

Finally, to test the mediating role of perceived fairness in the relationship between recovery service experience and negative WOM, a bias-corrected mediation analysis (Zhao et al., 2010) was conducted using the statistical tool PROCESS Model 4 (Hayes, 2012). The mean indirect effect of emotional responses was negative (−0.25) for recovery service experience and negative WOM and the 95% confidence interval did not include zero (Boot LLCI = −0.39, Boot ULCI = −0.15) indicating a significant mediation.

The results of mediation analyses provide statistical support for H4 that the relationship between negative service experience and negative WOM is mediated through consumers’ negative emotional responses. Higher negative service experience leads to higher negative emotional responses (H4a). Higher negative emotional responses lead to higher negative WOM (H4b); H5 that the relationship between positive service experience and negative WOM will be mediated through consumers’ satisfaction. A higher positive experience leads to higher customer satisfaction (H5a). Higher customer satisfaction leads to lower negative WOM (H5b); and H6 that the relationship between a satisfactory recovery service experience and negative WOM will be mediated through consumers’ perceptions of fairness of the recovery. A higher satisfactory recovery experience leads to higher perceptions of justice (H6a). Higher perceived fairness leads to lower negative WOM (H6b).

4. Discussion and conclusions

The current study delved into the dynamics of word-of-mouth (WOM) communication in the context of negative service experiences. Our focus was on understanding the psychological motives and mediating mechanisms that drive consumer engagement in negative WOM across positive, negative and satisfactory recovery service experiences. Service failures are an inevitable part of daily business operations, making it crucial to explore this area. The literature on services marketing substantiates the notion that while service failures can tarnish a hotel's image in the eyes of guests and negatively impact its bottom line, effective recovery strategies can yield the opposite effect.

Our investigation into the influence of positive, negative and recovery service experiences on negative WOM revealed distinct patterns. Notably, after encountering a negative service experience, guests' engagement in negative WOM is significantly higher compared to both positive and satisfactory recovery service experiences. This finding reinforces the importance of service recovery strategies for hotels. When service failures are adequately addressed and resolved, satisfaction with the recovery process encourages customers to reduce their negative WOM intentions.

However, our study also found that customer engagement in negative WOM remains higher in satisfactory recovery experiences compared to positive service experiences, which is contrary to some previous research (e.g. Zoghbi-Manrique-de-Lara et al., 2014). This result highlights the complexity of customer reactions to service experiences and suggests that even well-executed recovery efforts may not completely eliminate negative WOM. It underscores the need for businesses to consistently strive for exceptional service quality and to invest in proactive measures that prevent service failures from occurring in the first place. Further research may be needed to explore the nuances of customer perceptions and the factors that can help minimize negative WOM across various service contexts.

The mediating role of emotional responses in the relationship between negative service experiences and negative WOM is substantiated in our study. Our findings indicate that heightened negative service experiences result in more intense negative emotional responses, which, in turn, lead to increased engagement in negative WOM. Hotel guests who experience negative emotions due to unsatisfactory service are more likely to voice their complaints or participate in negative WOM communication. Conversely, customer satisfaction is associated with reduced negative WOM. This observation emphasizes the importance of providing a satisfying service experience to minimize the occurrence of negative WOM, which could be detrimental to a hotel's reputation and bottom line.

Additionally, our study demonstrates that the relationship between a satisfactory recovery service experience and negative WOM is mediated by consumers' perceptions of the fairness of the recovery process. When customers perceive the recovery efforts as fair, they are more likely to have a positive emotional response and reduce their engagement in negative WOM. This finding highlights the crucial role of fairness in shaping customers' reactions to service recovery efforts, and underscores the need for businesses to prioritize equitable treatment when addressing service failures.

By understanding these mediating factors and the complex interplay between service experiences, emotional responses and customer satisfaction, hoteliers can develop more effective strategies for managing service failures and mitigating the negative impact of WOM. This insight can help businesses foster long-term customer loyalty, maintain a positive brand image and ultimately enhance their overall performance in the competitive hospitality industry.

4.1 Theoretical implications

Our study primarily draws upon the Justice Theory and the Service Recovery Paradox in the context of word-of-mouth (WOM) communication, particularly focusing on the dynamics of negative WOM (NWOM) in service recovery situations. We extend the understanding of these theories by integrating them with the variables of interest in our research – service recovery, perceived justice, customer satisfaction and negative WOM. Building upon the Justice Theory, we identified a mediating role of perceived justice between successful recovery and NWOM. Our results suggest that service recovery efforts can enhance perceptions of justice after a service failure, which, in turn, impacts the NWOM. This provides a novel insight into the Justice Theory's application, extending its understanding in the context of service recovery and its effects on NWOM.

Marketing literature proposes post-recovery satisfaction is greater than that prior to the service failure when customers receive high recovery performance. Our results offer mix results to that the service recovery paradox theory in the WOM context. Effective service recovery affects negative WOM; however, it is not as effective compared to positive service experiences. Recovery encounters still mean an opportunity for service providers to reduce negative WOM, though, getting things right the first time is a more effective marketing strategy for hotels. Previous research lays a foundation on the notion that excellent service recovery has a direct impact on how much guests trust the hotel (e.g. Kau & Wan‐Yiun Loh, 2006). We contribute to services marketing theory by revealing the mediating role of perceived justice between a successful recovery and negative WOM. Service recovery efforts increase justice perception after experiencing a service failure, which in return impacts the negative WOM. Most studies investigate the service recovery for satisfaction and repurchase intentions (Grewal et al., 2008; Spreng et al., 1995). On a meta-analysis, De Matos, Henrique and Alberto Vargas Rossi (2007) found that the service recovery paradox works for satisfaction but not for repurchase intentions. Current research looked at the recovery phenomenon from a different perspective by adding negative WOM to a theoretical model, service recovery paradox also does not work for negative WOM. Services marketing literature argues that emotions mediate the relation between justice and customer behavior in the case of service recovery. The affect control theory (ACT) proposes that individuals behave in such a way that their emotions are appropriate to the situation. This theory suggests consumers who are proposed an unacceptable service recovery express their emotions. Consumers create events to confirm the sentiments that they have about themselves and others in the current situation. Our model provides further support for service experiences that trigger consumers’ psychological mechanisms that in return affect their WOM behavior. Finally, the equity theory is a vital framework for service recovery as guests feel unfairly treated in social exchange if the perceived inputs and outcomes are perceived to be unjust. The presence of inequity will result in negative WOM.

The proposed model in this study serves as a foundation for future research in the field of WOM and NWOM. By offering a clear and detailed framework, the study paves the way for additional investigations and refinements, leading to a more comprehensive understanding of the dynamics that influence WOM valence and its impact on businesses.

4.2 Practical implications

By understanding the factors that drive NWOM and the influence of different service experiences, businesses can develop strategies to minimize NWOM and its potential negative impacts. This knowledge is crucial for enhancing profitability and fostering positive brand equity perceptions (Sweeney et al., 2014). Understanding service recovery is particularly important for hotel managers as the unique nature of services (inseparability of production and consumption) makes it difficult to ensure error-free service (Fisk, Brown, & Bitner, 1993). We recommend hotel managers to make every effort to provide services correctly on the first time, rather than permitting failures and then trying to respond with superior recovery. Nevertheless, even the best companies struggle to achieve 100% service reliability and service failures happen on a regular basis. Hence, when failures occur, we suggest hotel managers to strive to provide a service recovery of high performance anyway because recovery efforts positively impact perceived justice and reduce negative WOM intentions. Hotel managers should also monitor guests’ WOM in various outlets such as TripAdvisor and social media and learn from aired failures. WOM could be very negative if a failure occurs and the hotel is not able to provide a satisfactory recovery (i.e. a “double deviation,” as termed by Bitner et al., 1990). Negative WOM resulting from unsatisfactory recoveries can push to competitors not only potential new customers but also existing customers (De Matos et al., 2007).

Recovery management has a significant impact on guests who experienced service failures because they are usually more emotionally involved and observant of service recovery effort (Kau & Wan‐Yiun Loh, 2006). Therefore, it was noteworthy to investigate the psychological mechanisms that mediate the service experience and WOM. When encountered with unpleasant experiences, guests go through various internal processes to cope up with the disconfirmation that forms specific emotions. Service failures or negative service experiences result in the formation of negative emotional responses leading to negative WOM. Also, customers’ complaints stem from a perceived injustice (Chebat & Slusarczyk, 2005). Our model captures the key mediating role of perceived justice in negative WOM. The perceived justice construct captures the fairness, timeliness and care components of a service recovery. Therefore, we recommend hoteliers to train the contact employees in charge of the complaints considering the guests’ emotional responses and perceived justice. Handling service recovery has a significant impact on customers who experienced service failures because they are usually more emotionally involved and observant of service recovery efforts. Therefore, such training should focus on the emotions of guests. Current research revealed that guests might feel angry, offended and disappointed when they experience a service failure and later, they will warn their friends and family about the service provider. Managers should consider guests’ emotions when handling service failures. In conclusion, our findings suggest that businesses can effectively manage NWOM by focusing on preventing negative service experiences, providing positive service experiences and ensuring fair and satisfactory service recovery experiences.

5. Limitations and future studies

Although the above results and discussions have contributed further to our understanding of the service recovery in the lodging context, there are certain limitations of our research. Data for this research were collected online. Our sample was limited to US consumers and MTurk participants are generally younger (Berinsky, Huber, & Lenz, 2012), so future studies may consider collecting empirical data from more diverse samples of respondents. Another limitation of this research is the experimental design based on scenarios. Future research may consider collecting data from hotel guests who actually encountered service failures. Hotels involve higher levels of social interactions among guests and employees, future research may consider testing the model in different contexts, such as retail. This research lays the groundwork for further exploration into the complexities of WOM and NWOM. Future studies could employ experimental designs to examine how various dimensions of justice affect customer behavior, or could focus on understanding how different types of service failures influence the effectiveness of service recovery strategies. The proposed model serves as a foundation for future research in WOM and NWOM dynamics. By providing a detailed theoretical framework, our study opens avenues for further investigation that can lead to a more nuanced understanding of WOM's influence on hospitality businesses. Finally, we did not test any moderating variables. Future research may consider some significant moderating variables such as personality traits, the length of relationship with the hotel, number of nights that the guest stayed in the hotel, purpose of travel, the hotel type and whether the guest holds a loyalty program.

Figures

Figure 1

The relationship between the valence of service experience and negative WOM and the psychological mechanisms in the process

Figure 2

Directions and mediators of the relationship between negative WOM and negative service experience, positive service experience and satisfactory recovery experience

Figure 3

The difference in mean negative WOM in three service experience conditions

Table 1

Construct measurement items and sources used for the study

Question items	Source
Negative emotional responses	Xie and Heung (2012)
How likely you would have felt the following emotions?
angry
offended
disappointed
(with scale points from 1 = “very unlikely” to 5 = “very likely”)
Customer satisfaction	McCollough et al. (2000)
Overall, how satisfied or dissatisfied did this experience leave you feeling?
How well did this service experience meet your needs?
Overall, I am very satisfied with this experience
Perceived justice	Ha and Jang (2009)
Given the inconvenience caused by the problem, the outcome I received from the hotel was fair
The hotel employee handled the problem in a timely manner
During the effort to resolve the problem, the hotel employees seemed to care about me
Negative WOM	Athanassopoulos, Gounaris and Stathakopoulos (2001), Bansal, Irving and Taylor (2004)
I will warn my friends and/or family about this experience
I will convince my friends and/or family not to go to this hotel
I will warn my friends and/or family to ensure they do not have the same experience

Source(s): Created by the authors

Appendix

Positive, negative and satisfactory recovery service experience scenarios

Positive service experience scenario

One day while traveling you decide to stay at the hotel you just selected. You arrive at the hotel at 7 pm and go to the front desk to check-in. You wait in the queue for a brief moment. As you wait in the queue, a front desk clerk notices you and offers to check you in. When you get to the desk, the front desk clerk gives you their undivided attention and quickly checks you in. During the checking in process, you request a particular room type and the front desk clerk accommodates your request. You thought the clerk acted in a very professional and respectful manner. When you enter your room, you realize it is exactly what you requested.

Negative Service Experience Scenario

One day while traveling you decide to stay at the hotel you just selected. You arrive at the hotel at 7 pm and go to the front desk to check-in. You wait in the queue for 15 minutes. When you get to the desk, the front-office clerk answers a telephone call while you are trying to check-in. You wait for two minutes until the call finishes. The front office clerk neither gives you any explanation nor apologizes to you. She barely smiles at you. You request a particular room type but the front office clerk ignores you until you repeat your request again and again. When you enter your room, you realize that the room isn’t ready. You call the front desk to request a room change and the clerk quickly arranges you to another room which is satisfactory. But the representative neither gives you any explanation nor apologizes you to you.

Satisfactory recovery experience scenario

One day while traveling you decide to stay at the hotel you just selected. You arrive at the hotel at 7 pm and go to the front desk to check-in. You wait in the queue for 15 minutes. When you get to the desk, the front-office clerk answers a telephone call while you are trying to check-in. You wait for two minutes until the call finishes. The front office clerk neither gives you any explanation nor apologizes to you. She barely smiles at you. You request a particular room type but the front office clerk ignores you until you repeat your request again and again. When you enter your room, you realize that the room isn’t ready. You call the front desk to request a room change and the clerk quickly arranges you to another room which is satisfactory. After the service failure occurred, the hotel gave you a 10% discount on your room rate as compensation; at the same time, the hotel duty manager went to your room to deliver a personal apology. Moreover, you received a letter of apology signed by the hotel’s general manager when you checked out.