Abstract
Purpose
Employees' 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/approach
A 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).
Findings
The 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 implications
Based 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/value
To 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.
Keywords
Citation
Umar, R.M. and Saleem, S. (2022), "Employee emotional competence and service recovery satisfaction: the mediating role of consumer forgiveness", British Food Journal, Vol. 124 No. 13, pp. 445-459. https://doi.org/10.1108/BFJ-04-2022-0386
Publisher
:Emerald Publishing Limited
Copyright © 2022, Rana Muhammad Umar and Salman Saleem
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/ legalcode
1. Introduction
Companies use a wide range of strategies for service recovery (Yang and Hu, 2021). However, it is alarming that scholars and practitioners have stringent challenges in service recovery. For instance, the US economy alone is at the risk of losing a staggering 496 billion dollars due to wrong customer recovery strategies (CCMC, 2022). Thus, more research is needed on the determinants of successful service recovery outcomes (Van Vaerenbergh et al., 2019). Customer emotions play a big role in service failure and recovery (Smith et al., 1999). Negative feelings associated with service failures, such as post-failure irritation, wrath, and embarrassment (Yang and Hu, 2021), may have adverse consequences for service firms (Mattila, 2001). In recent literature, service recovery scholars have emphasized on consumer forgiveness as a coping mechanism that helps consumers relinquish their negative feelings (Lin and Chou, 2022; Muhammad and Gul-E-Rana, 2020).
Since customers' post-service positive emotions increase their satisfaction (Liu et al., 2019) thus employee emotional competence (EEC) (i.e. employee's ability to perceive, understand, and regulate customer's emotions), is gaining considerable attention (Delcourt et al., 2016; Matute et al., 2018; Liu et al., 2019; Fernandes et al., 2018). In the service failure context, scholars have linked perceived EEC to positive recovery outcomes such as post-recovery satisfaction, trust, WOM, repurchase intention (Fernandes et al., 2018), and perceived interactional and informational fairness (McQuilken et al., 2020).
The service failure literature shows that emotional recovery strategies (e.g. apology and explanation) outperform economic strategies for obtaining consumer forgiveness (Van Vaerenbergh et al., 2019; Wei et al., 2020). Therefore, we can argue that perceived EEC is too crucial to relinquish negative feelings of service failure. However, little is known whether and how in a service failure context consumers' perceived EEC influences consumer forgiveness. Moreover, the underlying mediating role of consumer forgiveness between perceived EEC and consumer response remains under-researched.
According to theory of emotional contagion people “automatically mimic and synchronize expressions, vocalizations, postures, and movements with those of another person and, consequently, to converge emotionally” (Hatfield et al., 1993, p. 153). For instance, during service encounters customers' and employees' emotions mutually influence each other (Liu et al., 2019). Based on emotional contagion theory, that is people “catch” others' emotion (Hatfield et al., 1993), we argue that when service failure occurs, emotionally competent employees' positive emotional state is reciprocated by customers with forgiveness. In other words, EEC influences consumer forgiveness. Moreover, the affect infusion theory states that affect leads to judgment (Forgas, 1995), thus consumer's perception of EEC influence their service recovery evaluations too. Furthermore, we argue that consumer forgiveness is an underlying mechanism such that perceived EEC influences customer forgiveness (emotional contagion theory) which effect recovery satisfaction (affect infusion theory).
Since the failure type cause, different losses to the consumer, process failure (e.g. unreasonably slow service) threatens customers' social and self-esteem needs, whereas in event of outcome failure (e.g. an overcooked steak) consumer faces economic losses (Huang et al., 2020). Therefore, consumer responses to service recovery efforts are also affected by failure type (Luo and Mattila, 2020; Ma et al., 2020). For instance, studies have shown that the nature of a service failure influences how customers perceive the warmth of employees (Huang et al., 2020) and recovery evaluations (Ma et al., 2020). To authors' best knowledge prior research has overlooked the effect of perceived EEC on service recovery outcomes in the face of distinct service failures.
Given the above background, this study aims to contribute to the hospitality literature in several ways. First, we examine the effect of perceived EEC on the recovery satisfaction of casual dining restaurant consumers. Second, the study explores the underlying mechanism of consumer forgiveness linking perceived EEC and customer satisfaction in hospitality service failure encounters. Third, the study examines the moderating impact of service failure types in the relationship between perceived EEC on recovery satisfaction. In doing so the study offers several managerial implications. Using emotionally competent frontline employee's managers can obtain consumers' forgiveness, which can in turn elevate consumers' recovery satisfaction. Moreover, in emerging markets, the process failures are less forgiven and reduce recovery satisfaction than outcome failure.
2. Literature review
2.1 Employee emotional competence and recovery satisfaction
Customers' perception of service employees' performance is a significant predictor of satisfaction (Delcourt et al., 2017). Therefore, the success of service companies lies in understanding the expectations of customers from service employees (Huang, 2008). According to Delcourt et al. (2016) EEC, (i.e. employees' abilities to identify, interpret, and manage the emotions of their selves and others) is a key consideration in service encounters. For instance, consumers' perception of EEC results in several positive outcomes for service providers, including customers' loyalty to the firm and employees (Matute et al., 2018), and customer satisfaction (Delcourt et al., 2016). Recent research shows that emotionally competent employees can essentially better address the emotional needs of customers aroused due to service failure (Fernandes et al., 2018).
According to affect infusion theory, individuals' affective state influences their judgments (Forgas, 1995). Therefore, the customers' positive affective state induced by emotionally competent employees leads them to be less critical and more satisfied (Delcourt et al., 2012). Drawing upon above discussion, we have hypothesized that
There is a positive relationship between perceptions of EEC and recovery satisfaction.
2.2 Employee emotional competence and consumer forgiveness
According to Muhammad and Gul-E-Rana (2020, p. 2) “a service failure is said to be forgiven if a customer let go the revengeful destructive behaviour and respond in a constructive way towards the service firm on perceiving recovery efforts”. Moreover, in service failure context, forgiveness is regarded as a fundamental human emotion that commonly results in satisfaction and repurchase intention (Wei et al., 2020). Forgiveness has emerged through a complex reaction of negative emotions elicited due to service failure followed by positive emotions aroused by service recovery (Ma et al., 2020). Service managers endeavor to mitigate negative service experiences by expressing empathy (Xie and Peng, 2009), offering apology (Riek and DeWit, 2018) showing concern, and efforts (Wei et al., 2020) to convert negative emotions into positive ones. Thus, acknowledging mistake, apologizing, and expression of repentance by frontline employees can help to earn consumer forgiveness (Bath and Bawa, 2020). Moreover, expression of emotions by employees are essential for successful realization of emotional recovery strategies (e.g. apology) (Hareli and Eisikovits, 2006).
In other words, emotionally competent employees more efficacious in their interaction with customers (Delcourt et al., 2012) and are better in implementing emotional recovery strategies (Delcourt et al., 2016). Drawing upon emotional contagion theory (Hatfield et al., 1993) we argue that emotionally competent employees induce a positive affective state, which relinquishes negative emotions of consumers through a contagious effect. Based on the above discussion we hypothesize that
There is a positive relationship between perceptions of EEC and consumer forgiveness.
2.3 Consumer forgiveness and recovery satisfaction
Recovery satisfaction is referred to “customers' overall satisfaction with the secondary service (remedial action) of a service provider after a service failure” (Kuo and Wu, 2012, p. 129). The purpose of service recovery is to repair mistakes, patronize unhappy consumers and re-establish satisfaction (Ma et al., 2020). Maxham and Netemeyer (2002) argue that a consumer who receives proper recovery develops more favorable feelings toward the firm than a customer who has not encountered service failure. Therefore, an appropriate recovery strategy is inevitable for service managers. This research put particular emphasis on consumer forgiveness that results from the right recovery strategy. Scholars have argued that consumer forgiveness is crucial in the service recovery process as it leads to numerous favorable outcomes for service firms (Harrison Walker. 2019). For instance, several previous studies have documented a significant positive relationship between consumer forgiveness and recovery satisfaction (Ma et al., 2020; Muhammad and Gul-E-Rana, 2020). Based on this converging evidence we propose that consumer forgiveness has a significant and positive relationship with recovery satisfaction.
There is a positive relationship between consumer forgiveness and recovery satisfaction.
2.4 Mediating role of consumer forgiveness
Extent research regards consumer forgiveness as an outcome of service recovery (Ma et al., 2020; Muhammad and Gul-E-Rana, 2020). Harrison-Walker (2019) claims that the right recovery strategy promotes consumer forgiveness, which mediates the relationship between service recovery strategies and their outcomes. Following the above, consumer forgiveness is considered as a salient mediator of the service recovery process. For example, extant studies verify that consumer forgiveness underlies perceived recovery justice and relationship satisfaction (Muhammad and Gul-E-Rana, 2020), transparency in service recovery and switchover intention (Honora et al., 2022), recovery strategies (e.g. apology, compensation, voice) and positive recovery outcomes (Harrison-Walker, 2019), and recovery strategies (e.g. apology, compensation, combined recovery, no recovery) and recovery satisfaction (Ma et al., 2020). However, to the authors' best knowledge, the mediating effect of consumer forgiveness on perceived EEC and recovery satisfaction is overlooked in the hospitality literature.
Previous studies suggest that a service failure essentially results in anger and disappointment (Luo and Mattila, 2020). Therefore, customers expect effective service recovery (McCollough et al., 2000), to let go of negative feelings and respond in a constructive way (Muhammad and Gul-E-Rana, 2020). Emotionally competent employees are good at regulating their own and customers' emotions (Delcourt et al., 2016). An employee's positive emotions have a significant effect on customers' positive emotions (Giardini and Frese, 2008; Liu et al., 2019). Emotional contagion theory poses the notion that the emotions of one individual affect another person (Hatfield et al., 1993). Based on the above, we argue that the positive affect induced by employees is likely to result in consumer forgiveness. Accordingly, based on affect infusion theory (Forgas, 1995), a positive affect (i.e. consumer forgiveness) infuses consumer recovery satisfaction. Hence, based on contagion theory and affect infusion theory, we expect that consumer forgiveness mediates the relationship between perceived EEC and recovery satisfaction. Hence, we hypothesize that
Consumer forgiveness mediates the relationship between perceived EEC and recovery satisfaction.
2.5 Moderating role of failure type (process vs outcome failure)
In a restaurant setting service failure refers to host of issues, namely foreign objects in food, improperly cooked food, rude/discourteous behavior by employees, inattentive employees, slow service, disordered delivery of food items (Kim and Jang, 2014), disorderly food delivery is when customer is served later than late-arriving customers (Kim et al., 2021). Above-mentioned service failures have been further categorized into two broader types called outcome failure and process failure. From customers' point of view when customers do not get what they pay for is outcome failure (e.g. out of the stock menu, overbooking, overcooked food and a bug in the food). Process failure, on contrary, refers to deficiencies in the delivery of core service (e.g. inattentive, or rude employees and slow services) (Luo and Mattila, 2020). Various empirical studies argue that failure type moderates' customers' evaluation of the service recovery process. Huang et al. (2020) demonstrate that hospitality employees need low warmth and high competence to manage outcome failure, while high warmth and low competence are required in process failure. Moreover, employee consciousness has a stronger influence on consumer dissatisfaction with a process failure than outcome failure (Chan et al., 2007). Similarly, empathic apology has stronger effect on recovery satisfaction for process failure than to outcome failure (Roschk and Kaiser, 2013). According to Borah et al. (2020), consumers in emerging markets are more conscious of process failure vs outcome failure and consequently develop higher recovery expectations from process failures. As casual dining restaurants usually serve moderately priced food in a casual atmosphere (Cai and Qu, 2018), previous studies claim that casual dining restaurants may not focus on the personal attention in services that prevails in fine dining restaurants (DiPietro and Partlow, 2014). The context of the present study is casual dining restaurants operating in emerging markets. Considering the context of the study, we assume that casual dining consumers in emerging markets have more concerns about how they are treated at the restaurant. A process failure may create more negative emotions as compared to outcome failure. Therefore, we expect that the effect of perceived EEC on recovery satisfaction will be weak after a process failure as compared to outcome failure (see Figure 1).
The positive relationship between perceived EEC and recovery satisfaction will be weaker for process failure than for outcome failure.
3. Methodology
A critical incident technique (CIT) in conjunction with a self-administered online questionnaire was considered in this study. CIT is largely used in service failure and recovery research (Koussaifi et al., 2020). Previous researchers claimed that combining CIT with a structured questionnaire is appropriate to quantitatively examine unfavorable service experiences (e.g. Swanson et al., 2014). Following the above recommendations, we developed our survey as follows. Firstly, we explained to the respondents with concepts of service failure, service recovery, and casual dining restaurants, then asked them to recall and describe their most recent service failure and recovery experience at casual dining restaurants. Subsequently, participants were asked to refer to recalled and described the experience and respond to questions related to variables of this research.
The online survey was administered in a Google Form in the English language. Since English is the official language in Pakistan, respondents in previous service research studies reported no concern about language (Muhammad and Gul-E-Rana, 2020). Following previous studies (e.g. Marozzo et al., 2022) the questionnaire was distributed by using the virtual snowball sampling technique, which is a non-probability sampling technique in which research participants recruit other participants. Data collection was carried out between July 2021 and Feb 2022 and a sample of 204 consumers was considered for final analysis. Previous scholars recommended that the sample size for PLS-SEM should be five to ten cases per variable (Hair et al., 2018). Accordingly, our observations per variable are more than 40, which is higher than the minimum threshold (Oliveira et al., 2021). Therefore, the sample size was satisfactory for further analyses.
3.1 Measures
Five, three, and five items were adopted to measure employees' ability to perceive, understand, and regulate customer emotions respectively, adopted from Delcourt et al. (2016). For consumer forgiveness, a four-item scale was adopted from Hur and Jang (2019) and a three-item scale of recovery satisfaction from Fernandes et al. (2018). All variables were measured on a seven-point Likert scale ranging from 1 (strongly agree) to 7 (strongly disagree). Finally, following Swanson et al. (2014) study two judges sorted the all critical incidents into process failure and outcome failure. If the service providers' fails in providing appropriate food (e.g. improperly cooked, overcooked, or burnt food, out of the stock menu, a bug in the food, wrong food) was considered as outcome failure. On the other hand, service provider's failure in the delivery process of food (e.g. inattentive, or rude employees, disorderly service, and slow services) was sorted as process failure (Borah et al., 2020; Luo and Mattila, 2020; Smith et al., 1999; Warden et al., 2008; Yang and Mattila, 2012; Zhu et al., 2004). To calculate the level of agreement among judges, we used Perreault and Leigh's (1989) formula and the inter-rater reliability (Ir) value was 0.96, which was higher than the 0.70 rule of thumb (Rust and Cooil, 1994). Eight responses with which the judges disagree were resolved by discussion. Process failures were recorded in 121 critical events (59.31%) and outcome failures were documented in 83 critical occurrences (40.68%). Following previous studies, this study has ruled out considering several variables as controls. According to Lu et al. (2021), there is no significant effect of covariates such as age, gender, and income on service encounter evaluation and its outcomes among casual dining customers. Similarly, a recent study among casual dining customers by Hwang and Shin (2021) reported no significant influence of demographics on employee performance and consumer attitude towards the restaurant. Hence, this study did not introduce demographics as control variables in the statistical analysis.
4. Results
Table 1 shows the demographic characteristics of respondents. 60.8% of respondents were males, 55.4% of respondents had the aged between 25 and 39 years, 40.7% of respondents had a master's degree, 37.2% of respondents had a per month income between 40,000 and 99,999 PKR, and 45.1% of respondents have dined out frequency from one to two time per month.
We tested common method bias by using Harman's single-factor method. This research reported no common method bias. Our theoretical framework includes a higher-order construct of perceived EEC, mediating variable of consumer forgiveness, and multi-group moderating variable of service failure type. Therefore, we used PLS-SEM as an evaluation model as it is considered more appropriate for formative constructs, small sample sizes (Ramayah et al., 2018) complex models including moderations, and (Hair et al., 2014).
4.1 Measurement model
Confirmatory factor analysis (CFA) was conducted to measure the validity of the constructs and to measure the psychometric properties (convergent and discriminant), the average variance extracted (AVE) and composite reliability (CR) of all constructs (Hair et al., 2014). Due to low CR value one item from recovery satisfaction scale was deleted. After re-assessment, the minimum threshold of all values was meet, as values of CR and Cronbach α were greater than 0.70 for all constructs. Moreover, value for the AVE for all variables was more than 0.50 (Hair et al., 2014). Thus, the convergent validity is acceptable (see Table 2). Table 3 shows that discriminant validity was acceptable too as all Heterotrait-Monotrait ratio (HTMT) values are less than 0.90 (Henseler et al., 2015).
4.2 Higher-order model of EEC
As can be seen in Figure 2, higher-order model of perceived EEC showed all three dimensions are statistically significant at p < 0.01 (Perceiving customers emotions: β 0.44, Understanding customers emotions: β 0.23 and Regulating customers emotions: β 0.56). According to Hair et al. (2014) the minimum threshold value for variance inflation factors (VIF) is 0.5. Our analysis shows that VIF values ranged between 1.5 and 2.99, thus there is no multicollinearity issue.
4.3 Structural model
We assess the structural model by evaluating the beta, t-values, effect sizes f2, predictive relevance Q2, and coefficient of determination (R2) (Hair et al., 2014). Impact of perceived EEC on recovery satisfaction (H1) was supported β = 0.53, p = 0.000. The effect of perceived EEC on consumer forgiveness (H2) was supported β = 0.64, p = 0.000. The effect of consumer forgiveness on recovery satisfaction (H3) was supported β = 0.33, p = 0.000 (see Table 4). We employed Preacher and Hayes (2008) approach with subsamples 5,000 bootstrapping procedure to evaluate t-values and confidence intervals for mediating hypothesis. Table 5 shows that H4 was supported as confidence intervals have no zero (Preacher and Hayes, 2008). Finally, a Multi-group analysis was performed to assess differences between failure types (Henseler et al., 2009). We found that process failure (β: 0.42) value is lower than outcome failure (β: 0.69) value and the difference (β: 0.27) is statistically significant (p-value of the multi-group analysis = 0.015). Thus, H5 is supported as effect of perceived EEC on recovery satisfaction was significantly weaker for process failure as compared to outcome failure.
5. Discussion
The objectives of the study were to examine the mediating effect of consumer forgiveness and moderating role of failure type between perceived EEC and recovery satisfaction. Emotional contagion theory was articulated that consumers perceiving high emotional competence in service employees tend to forgive service providers. Accordingly, findings support our theorizing that perceived EEC enhances consumer forgiveness by addressing the negative feelings resulting from service failure. These results support the suggestion that the critical role of service employees is to address the emotional needs of consumers (Matute et al., 2018) and that perceived EEC is a much-needed skill (Mattila and Enz, 2002). Results further demonstrate a direct effect of perceived EEC on recovery satisfaction. These findings are congruent with previous research that emotional service recoveries drive customer satisfaction (We et al., 2020; Fernandes et al., 2018).
Prior research has noted consumer forgiveness as an underlying mechanism in service recovery processes (Muhammad and Gul-E-Rana, 2020; Honora et al., 2022; Ma et al., 2020). Building upon emotional contagion and affect infusion theories we proposed an underlying mediating role of consumer forgiveness in relationship between perceived EEC and recovery satisfaction. The findings show that a direct effect of perceived EEC on recovery satisfaction and the indirect effect via customer forgiveness were significant. This suggests that obtaining customer forgiveness paves the way for perceived EEC to exert its influence on recovery satisfaction.
As we discussed earlier failure types represent different types of losses to consumers (Luo and Mattila, 2020; Ma et al., 2020). In the event of a process failure, customers' social and self-esteem needs are threatened however outcome failure causes economic losses (Huang et al., 2020). To this end, findings revealed that the relationship between perceived EEC and recovery satisfaction was weaker for process failure as compared to outcome failure. Such findings support the assumption that consumers in emerging markets are more conscious of process failure than outcome failure (Borah et al., 2020).
5.1 Theoretical and managerial implications
The contribution of this research is three-fold. The first research provides empirical evidence that perceived EEC as a way of obtaining customer forgiveness. These results can be explained with help of the tenet that emotional contagion theory which postulates an emotional convergence among people (Hatfield et al., 1993). As emotionally competent employees, in event of service failure, not only regulate and maintain their own emotions (Giardini and Frese, 2008) but also their competence in understating the customer's emotional state (Delcourt et al., 2016) prompts customer forgiveness. In doing so we extend the emotional contagion theory in service recovery encounters by demonstrating that emotionally competent employees may invoke customer forgiveness.
Second, this research contributes to service recovery literature by considering consumer forgiveness as an underlying mechanism of perceived EEC and recovery satisfaction. Third, by focusing on the two failure types namely process failure (e.g. unreasonably slow service) and outcome failure (e.g. an overcooked steak), this research reveals the moderation effect of failure type in the relationship between EEC and recovery satisfaction.
This study supports the previous research efforts that provide insights to the managers on the significance of emotionally competent employees (Liu et al., 2019). Like previous studies (e.g. Delcourt et al., 2016), this study also suggests that EEC should be a crucial element in the recruitment process and that organizational-wide training programs for improving employee emotional competence skills are warned because customer forgiveness is a key variable that decreases customers’ negative service evaluations and promotes the positive ones (Muhammad and Gul-E-Rana, 2020; Ma et al., 2020; Honora et al., 2022). Therefore, managers must ensure that employees understand completely the vital role of consumer forgiveness in gaining recovery satisfaction.
Moreover, while addressing customer recovery satisfaction, managers must differentiate among that service failure types, specifically, in the context of casual dining restaurants in the emerging market, perceived EEC results in greater recovery satisfaction for outcome failure vs process failure. Therefore, managers should be more focused on service design that minimizes process failures. Also, consistent with Borah et al. (2020) suggestions this study highlights a need that employees should have rigorous training on the differentiation of service failure types and respective recovery strategies.
The present study also provides some additional insights for casual dining managers on food safety and food allergies. For example, service failure often happens due to food safety problems (Harris et al., 2021). Also, consumers' perceptions of food safety are key to service recovery (Bouranta et al., 2018). Among casual dining consumers, clean and protective clothing, employees' clean fingernails, and having gloves while handling food are key aspects of food safety (Liu and Lee, 2018). The implication is that emotionally competent employees complying with high food safety standards can better address consumers' concerns about food safety and thus improve service recovery outcomes. Similarly, food allergies also result in service failure (Wang et al., 2022). Thus, there is a great need for restaurant employees to have essential knowledge and training on food allergies (Lee and Sozen, 2016). Therefore, we suggest that employees with emotional competence along with handy knowledge of food allergies can help in addressing or even preventing service failure due to food allergies. To sum up, the present study suggests that casual dining managers should develop employees' both emotional competence and technical skills (e.g. food safety and allergies).
6. Limitations and future research
This study acknowledges several limitations. This study considered casual dining restaurant consumers in a developing country in Asia (e.g. Pakistan) with limited generalizability of results. Since consumer forgiveness is a universal phenomenon that prevails in fine dining consumers, and fast-food consumers, future studies may broaden the scope of this research in examining this model among other categories of consumers in developed countries. A limited sample may also limit the generalizability of research. Thus, future research should broaden the sample to expand the generalizability of the findings. To further validate our study future research may introduce some control variables such as service failure severity and demographic variable (Fernandes et al., 2018). Following previous studies, this study has ruled out the scenario-based experiment approach, as it is very hard to imagine oneself in a situation where one has not experienced employee emotions. However, the findings of this study can be further validated by video-based experiment studies (e.g. Delcourt et al., 2017) where the respondent can be shown videos of various service failures that are handled with varying levels of EEC. Besides, field experiments present a great opportunity to study actual consumer behavior in face of EEC (Matute et al., 2018). Moreover, perceived EEC may result in different customer experiences for different services such as personal services (e.g. hairdressing) and impersonal services (e.g. lawn mowing). Thus, perceived EEC may have different consequences on recovery satisfaction across process failure vs outcome failure. Hence, we recommend future researchers examine the moderating role of failure type across service industries.
Figures
Demographics
| Demographic characteristics | Frequency | Percent | Cumulative percent |
|---|---|---|---|
| Gender | |||
| Females | 80 | 39.2 | 100 |
| Males | 124 | 60.8 | 60.8 |
| Age | |||
| 18–24 years | 68 | 33.3 | 33.3 |
| 25–39 years | 113 | 55.4 | 88.7 |
| 40–64 years | 23 | 11.3 | 100 |
| Education | |||
| High school | 15 | 7.4 | 7.4 |
| Intermediate | 19 | 9.3 | 16.7 |
| Bachelor | 19 | 9.3 | 26 |
| Masters | 83 | 40.7 | 66.7 |
| MS/M.Phil | 55 | 27 | 93.7 |
| PhD | 13 | 6.3 | 100 |
| Income (PKR per month) | |||
| 0–19,999 | 72 | 35.3 | 35.3 |
| 20,000–39,999 | 27 | 13.2 | 48.5 |
| 40,000–59,999 | 36 | 17.6 | 66.1 |
| 60,000–99,999 | 40 | 19.6 | 85.7 |
| 100,000–14,9000 | 16 | 7.8 | 93.5 |
| 150,000 or above | 13 | 6.5 | 100 |
| Dine out frequency/month | |||
| Less than once | 69 | 33.8 | 33.8 |
| 1–2 times | 92 | 45.1 | 78.9 |
| More than 3 times | 43 | 21.1 | 100 |
Results of measurement model
| Constructs | Indicator | Outer loading | Cronbach`s Alpha | rho_A | Composite reliability (CR) | Average variance extracted (AVE) |
|---|---|---|---|---|---|---|
| Perceiving customer emotions | PCE1 | 0.68 | 0.90 | 0.90 | 0.90 | 0.64 |
| PCE2 | 0.81 | |||||
| PCE3 | 0.96 | |||||
| PCE4 | 0.73 | |||||
| PCE5 | 0.78 | |||||
| Understanding customer emotions | UCE1 | 0.66 | 0.87 | 0.89 | 0.86 | 0.68 |
| UCE2 | 0.79 | |||||
| UCE3 | 0.98 | |||||
| Regulating customer emotions | RCE1 | 0.65 | 0.89 | 0.90 | 0.90 | 0.63 |
| RCE2 | 0.82 | |||||
| RCE3 | 0.85 | |||||
| RCE4 | 0.86 | |||||
| RCE5 | 0.80 | |||||
| Consumer forgiveness | CF1 | 0.82 | 0.88 | 0.88 | 0.88 | 0.66 |
| CF2 | 0.82 | |||||
| CF3 | 0.81 | |||||
| CF4 | 0.79 | |||||
| Recovery satisfaction | RS1 | 0.90 | 0.88 | 0.88 | 0.88 | 0.79 |
| RS2 | 0.87 |
Note(s): N = 204
Discriminant validity of measure model Heterotrait-Monotrait ratio (HTMT) of correlations
| Constructs | CF | PCE | RCE | SAT | UCE |
|---|---|---|---|---|---|
| CF | |||||
| PCE | 0.42 | ||||
| RCE | 0.72 | 0.58 | |||
| SAT | 0.76 | 0.48 | 0.83 | ||
| UCE | 0.34 | 0.79 | 0.52 | 0.44 |
Results of structural model analysis (Hypothesis testing)
| Hypotheses | Relationships | β | t-values | p- values | f2 | R2 | Q2 | Decision |
|---|---|---|---|---|---|---|---|---|
| H1 | EEC → SAT | 0.53 | 8.76 | 0.000 | 0.44 | 0.62 | 0.54 | Supported |
| H2 | EEC → CF | 0.64 | 12.75 | 0.000 | 0.69 | 0.41 | 0.29 | Supported |
| H3 | CF → SAT | 0.33 | 4.99 | 0.000 | 0.17 | 0.62 | 0.54 | Supported |
Mediation analysis
| Hypotheses | Relationships | β | t-value | p-value | CI. 95 | Decision | |
|---|---|---|---|---|---|---|---|
| 2.50% | 97.50% | ||||||
| H4 | EEC → CF → SAT | 0.21 | 4.6 | 0.000 | 0.125 | 0.305 | Supported |
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