Negative Spillover Effects of Other-Customer Failure in Airline Context

Abstract

Purpose - Other customers within the same service environment do influence a customer' attitude and behavior toward a service firm. Specially, other customers' misbehaviour and various service problems stemmed from them could make the other customers suffer some bad experiences. However, there are few studies to answer how the spillover effect of a service failure arisen from other customers' misbehavior. This study is aimed to examine how service failure due to the dysfunctional behavior of other customers has negative effects on customer evaluation with the service provider. Research design, data, and methodology - Data were collected from a survey based on consumers' retrospective experiences in airline service context. The hypothesized relationships were tested conducting structural equation modeling. Results - Our results show that the attribution of a firm responsibility for other-customer failure has a positive influence on customer's recovery expectation, in turn, it is negatively related to customer satisfaction. Furthermore, perceived service provider's efforts positively influence customer satisfaction. Conclusions - Although a service failure was caused by other customer's misbehavior, employees should be able to alleviate any bad feelings of the affected customers. Furthermore, service providers should provide proper recovery efforts for solving problems caused by the other customers for the wounded customers.

1. Introduction

A customer in a service encounter generally experiences various interactions with contact personnel, physical surroundings and other customers (Kim & Lee, 2012; Potluri et al., 2015). In service encounters, other customers are influenced directly or indirectly by the others (Martin & Pranter, 1989; Moore et al., 2005). In this regard, Korea Heralds (2015) reported that a growing number of child-free venues in South Korea are appearing recently. Many of them restrict children access by putting up signs like ‘No children under age 7 allowed’ on their doors. The emergence of child-free venues dates back a few years, when restaurants and cafes in the capital’s hip districts, mostly due to growing complaints about noisy kids in the public space. The literature notes that other customers within the same service environment do influence a customer’ attitude and behavior toward a service firm (Bitner et al., 1992). Specially, recent several studies (e.g., Grove & Fisk, 1997; Hung, 2010; Huang & Wang, 2014; Moore et al., 2005; Schaefers et al., 2016) have shown that the dysfunctional behaviors of other customers (e.g., cutting the queue, talking too loudly, crowding, and so on) reflect negatively on a customer’s overall evaluation of the service provider.

Other customers’ misbehaviour and various service problems stemmed from them could make the other customers suffer some bad experiences. But, the topic ‘other customers in a service encounter’ has received relatively less attention than the other topics in the marketing literature (Kim & Lee, 2012). In particular, there are few studies to answer how the spillover effect of a service failure arisen from other customers’ misbehavior (Huang, 2008). Therefore, this study aims to examine how customers in the airline service sector respond to the service failure arose from to the misbehavior of other customers and the responses consequentially turn out to have a negative impact on customer satisfaction with the service provider.

2. Research Background and Hypotheses

2.1. Previous Research on Other-customer Failure

The term of ‘other-customer failure’ is defined as service failure caused by other-customer misbehavior (Huang, 2008). As mentioned earlier, the literature has overlooked the topic of other customers in a same service environment. Recently, several researchers (e.g., Hung 2010; Huang & Wang, 2014; Moore et al., 2005; Schaefers et al., 2016) have examined empirically the impacts of service failure caused by other customers. [Table 1] provides an overview of previous studies on other-customer misbehavior.

[Table 1] Previous empirical studies about other-customer misbehavior

Although previous researches provided some significant finds and implications about other customers’ misbehaviour and service failure results from them, those studies are limited to explain how customers respond to the service failure caused by other customers’ misbehavior and the responses lead to have a negative impact on customer satisfaction with the service provider.

2.2. Hypotheses

In service failure contexts, consumers are apt to search to someone to blame. How a customer’s attribution for responsibility to the service failure does leads to customer dissatisfaction? Our research focuses on the effects of the attribution for responsibility to the service failure due to the other-customer misbehaviors on customer’ recovery expectation and satisfaction. Attribution theory deals with how a customer utilizes information to form a causal judgment for a specific event. The locus of causality is related to the customer’s perception of where the responsibility for the failure rests (Chebat et al., 1995). For example, whose responsibility is it that someone who smokes in a smoke-free zone of a restaurant? Is it the smoking customer or the service provider who did not control the customer? Several studies (Hess et al., 2003; Swanson & Kelley, 2001; Huang, 2008) showed that the more customers attribute a firm’s responsibility for the failures, the more they believe a refund and/or an apology are deserved. A firm’s assumed responsibility regarding other customer failure will lead to customers’ recovery. Recovery expectations are related to the customer’s belief that some level of reparation is appropriate after an experience of other-customer failure. Swanson and Kelley (2001) found that responsibility attribution for failure influenced the customers’ service recovery expectations. Also, Wirtz and Mattila (2004) demonstrated that a customer’s perception of a firm’s responsibility has a significant influence of his or her satisfaction evaluations (Huang, 2008). Based on the preceding discussion, we advance the following hypothesis:

[H1] A service firm’s responsibility for other-customer failures has a positive impact on customer’s recovery expectation.

[H2] A service firm’s responsibility for other-customer failures has a negative impact on customer satisfaction.

Expectation confirmation theory suggested by Oliver (1980) notes that disconfirmation of expectation and perceived performance directly influences customer satisfaction. Consistent with the expectancy disconfirmation theory, the higher a customer’s service recovery expectation, the lower their level of satisfaction with the firm will be. Therefore, we expect that a customer’s recovery expectations have a negative effect on customer satisfaction. Based on the expectation confirmation theory, we advance the following hypothesis:

[H3] Customer’s recovery expectation has a negative impact on customer satisfaction.

Perceived recovery effort is related to the amount of energy a customer believes the service provider has invested to remedy a negative behavior (Mohr & Bitner, 1995). Previous research found that the behavior of employees who come into direct contact with the customer is essential to customer’s evaluations on service providers (Huang, 2008). Therefore, it is reasonable to expect that a customer’s evaluation for the service will be affected not only by the other-customer’s failure but also by how the employees respond to help solve the problem caused by the other-customer failure. Conversely, when a customer perceives a lack of service provider’s efforts to help solve the problem, he or she might not be satisfied with the service firm. Based on the before-mentioned discussion, we formulate the following hypothesis:

[H4] Customer’s perceived recovery effort has a positive impact on customer satisfaction.

3. Methodology

3.1. Data Collection and Samples

For this study, surveys have been conducted based on actual customer experience with the airline service context. We selected the airline industry. An airline service is one of typical high-contact services in which customers interact with frontline employees in a high degree (Ahmed et al., 2016) as well as representative services that various service failures occur most frequently (Allen et al., 2015). Each respondent to the survey participated using self-reporting method. After presented with service failure types, each respondent was asked to select service-related problems he or she has experienced most recently. Then, a minute or so was given to allow the respondent to recall the case of other-customer service failure in order to refresh the memory of the case. For the final analysis, a total of 297 questionnaires were used, excluding 17 questionnaires with inadequate and/or insincere answers.

The convenience samples of 297 consumers have a high proportion of women (56.1%), and the ages range from 20 to 35 years, with a median of 28 years. The job of the sample is varied, with 52.8% holding the students, 25.2% the office workers, 12.5% professionals, 4.7% service/sales, and 1.2% self-employers. Income tends toward higher levels; 58% makes about fifty million won or more annually.

3.2. Measures

All the items in this study were measured on a 7-point scale (1=strongly disagree, 7=strongly agree). Firm responsibility was measured using a two-item scale developed from the study by Yen et al. (2004). Recovery expectations were measured by adapting and modifying the scales used by Hess et al. (2003). To measure perceived recovery effort of service provider, two items adapted from the scale used by Mohr and Bitner (1995) were used. Satisfaction with the service firm was adapted from the scale used by Reynolds and Beatty (1999). The measurement items used in this study are shown in [Table 1].

4. Results

4.1. Measurement Model Assessment

The measurement model in this study for convergent validity and discriminant validity is assessed by conducting confirmatory factor analysis (CFA). The measurement model results and construct correlations are provided in [Table 2] and [Table 3]. The results (χ2 =60.256(29) (p<0.01), GFI= 0.929, AGFI=0.906, CFI=0.915, RMSEA=0.054) suggested a good fit of the model to the data (Hair et al., 2006). As shown in [Table 1], for all constructs, all item loadings are statistically significant, and the composite reliability (CR) and the average variance extracted (AVE) values are greater than 0.70 and 0.5, respectively (Hair et al., 2006). This indicates that each construct is accepted for the convergent validity.

[Table 2] Measurement model results

Notes: CR=Construct Reliability, AVE=Average Variance Extracted, ***p<0.01

As shown in [Table 3], the results of the correlations among first-order constructs of service convenience show that no pair of correlations was above 0.80, suggesting no multi-collinearity and the confirmation of discriminant validity (Hair et al., 2006).

[Table 3] Correlations and Descriptive Statistics

**p<0.05,***p<0.01

4.2. Structural Model Assessment

We assessed the relationship among firm responsibility for other-customer failure, customer recovery expectation, perceived recovery effort, and customer satisfaction by structural equation modeling (SEM). The structural model results are provided in [Table 4]. The fit statistics show that the research model has a good fit with the data (GFI=0.908, CFI=0.912, and RMSEA=0.051).

[Table 4] Structural Model Results

*** p<0.01​​​​​​​

Results in [Table 5] show that, consistent with previous research, firm responsibility for other-customer failure has a positive effect on recovery expectation (path coefficient=0.617, t-value=7.961, p<0.01), indicating support for [H1]. There is support for [H3], which suggests that recovery expectation has a negative effect on customer satisfaction (path coefficient=-0.347, t-value=-4.231, p<0.01). Customer’s perceived recovery effort of service provider has a positive influence on customer satisfaction (path coefficient =0.104, t-value=1.721, p<0.1), indicating support for [H4]. However, firm responsibility attribution for other-customer failure has no direct and significant effect on customer satisfaction (path coefficient=0.076, t-value=0.877, p>0.1). Thus, [H2] is not supported. This finding showed that recovery expectation seems to mediate fully the direct impact of firm responsibility attribution on customer satisfaction.

[Table 5] Results of hypothesis testing

** p<0.05, ***p<0.01​​​​​​​

5. Discussion

5.1. Theoretical and Managerial Implications

The results of this study provide a strong evidence that interpersonal interactions with employees and with other customers are a critical determinant of customer satisfaction. Our results showed that when customers attribute the firm with responsibility for other-customer misbehavior, they expect service providers to offer remedy and mitigate their ill feelings and losses. Furthermore, it was found that the efforts of service providers to redress customers’ bad experience when other customers behaved in common manners affect their satisfaction evaluations. Based on these findings, this study broadens the discussion of the impacts of other-customer failure on a customer’s overall satisfaction with a service firm. Especially, our results add to the mounting literature that suggests that not only other customer’ misbehaviour and but also how service providers react to the situation determine customers’ satisfaction evaluation.

irms. Our findings highlight that customer’s satisfaction with services is affected by not only how customers perceive the other customer’s misbehaviour but also how the service firms react it. To prevent the service failure come from other-customer’s misbehavior, service firms should make efforts to manage that all their customers behave in acceptable manners. As some researchers (Huang, 2008; Huang & Wang, 2014; Wirtz & Kum, 2004) offered, service providers need to offer specific courses of action such as blacklisting customers who routinely are dysfunctional and preventive solutions. For example, employees of a restaurant can seat families with little kids in a separate area to eat other customers uninterrupted by kids’ disturbance. Service firms should train frontline employees to occasionally be a “police officers” to make certain that their customers behave in acceptable manners with courteous and sympathetic communication for more appropriate behaviors (Huang, 2008; 2010). For example, employees can politely say “Please stay on the line and we will offer services to you in the order in which it was received as quickly as possible.” Furthermore, service providers can take failure recovery strategies suggested by Huang and Wang (2014) and Miao et al. (2011), providing unpleasant customers with problem-solving skills for misbehaving customers and satisfactory coping. Concretely, to appease customers’ anger caused by other-customer failure and raise their level of satisfaction, employees need to be trained to offer the sincerest apologies for their poor experiences to express sympathy with disagreeable feeling of them and even consider some tangible compensation such as a free or discount price.

5.2. Limitations and Research Directions

The results of this study is limited to generalize into other service industry firms. We focused on only one service industry-airline service. Future studies will consider replicating and extending this study across industries to provide a more solid understanding of how service failure caused by other-customer’s misbehavior influences customer’s evaluation on the overall services. Moreover, some prior researches suggested that the customer’s allocentric-idiocentric orientation affects the attribution process in a poor service encounter (Huang, 2008). Future study will examine how the customer’s cultural difference influence the attribution process in the context of other-customer failure to improve the generalizability of the findings.