The Price of Good Friendships: Examining the Roles of Relationship Norms and Perceived Controllability in Service Failure Encounters

Abstract

Despite companies’ efforts to cultivate positive relationships with their consumers, negative relational episodes such as customer service failures are inevitable. This study examines how perceived controllability of a service failure determines responses from consumers who have previously formed quality relationships with the company. Specifically, it distinguishes two types of quality relationships: communal and exchange relationships. It investigates how these two types of relationships interact with different levels of perceived service failure controllability, and collectively influence consumers’ emotional, cognitive, and behavioral responses (i.e., anger, perceived betrayal, and negative WOM intention) to the failure encounters. Results of an online experiment (N = 140) show that consumers experience a greater level of anger and perceived betrayal when they consider the service failure as highly controllable (vs. uncontrollable) by the company. More important, this effect pattern only occurs when prior company-consumer relationships are communal rather than exchange. The results of this study enrich our body of knowledge on the role of company-consumer relationships in service failure encounters and provide useful guidelines for company-consumer relationship development and service failure management and recovery.

Keywords

controllability service failure organizational-public relationships communal relationships exchange relationships

For decades, relationship management has served as a guiding theory and a paradigmatic focus of the public relations discipline (Ferguson, 2018). The relationship management theory posits that “public relations balances the interests of organizations and publics [such as consumers] through the management of organization-public relationships” (Ledingham, 2003, p. 181). Within the relationship management literature, quality relationships between an organization and its consumers have been repeatedly documented to generate positive attitudinal and behavioral outcomes, including but not limited to consumers’ increased intention to support the organization and to spread positive word-of-mouth (WOM) about the organization (Hong & Yang, 2009; Ki & Brown, 2013). However, when a negative event such as the organization’s service failure strikes, will quality relationships buffer the organization against the reputational and relational damage brought by the failure, or will they backfire and result in punitive responses among consumers toward the organization? Exactly how will consumers respond emotionally, cognitively, and behaviorally to the negative relational episode with a company they previously loved?

The main theoretical framework that has been widely adopted to explain consumer responses to service failure situations is attribution theory (Weiner, 2012), which suggests that when encountering a failure situation, consumers will cognitively infer the cause of the failure and form their responses accordingly. Applying attribution theory, this study focuses on the causal dimension of controllability, which refers to consumers’ belief about whether the cause of the failure can be controlled by the company and if the company is to be blamed for the failure. Past research has found that perceived controllability negatively affected consumer evaluations in failure situations. When consumers perceive the failures can be easily prevented by the company, they tend to feel angry and initiate negative behaviors such as spreading negative WOM (Xie & Heung, 2012). Moreover, when the failure is situated in a context when consumers have established positive relationships with the company, it may lead to an acute sense of betrayal (Grégoire et al., 2009). This backfiring effect of positive relationships, however, was not evident when low controllability is inferred (Grégoire & Fisher, 2006).

Although a few scholars have examined the impact of relationship quality on perceived controllability and failure evaluations (e.g., Grégoire & Fisher, 2006; Xie & Heung, 2012), very limited insights have been provided to inform whether and how different types of positive relationships interact with perceived controllability and collectively influence consumer responses. Meanwhile, social exchange theory and marketing research suggest that consumers’ relational experiences with a company are guided by underlying relationship norms (Aggarwal & Larrick, 2012). Broadly speaking, relationship norms refer to expectations that relationship partners (e.g., consumers and companies) hold toward each other regarding how they should behave (Valta, 2013). It functions as guidelines for appropriate behavior in a relationship and serves as reference points to evaluate the conformity of a relationship partner’s actions with the established expectations (Valta, 2013). In the current context, adherence to or violations of these relationship norms determines consumers’ assessment of brands after service failure encounters. To fill in the gap and extend previous insights (e.g., Grégoire & Fisher, 2006, 2008), this study distinguishes two types of positive relationships between a company and its consumers: exchange relationships, which center on the norm of reciprocating comparable benefits between relationship partners, and communal relationships, which focus on the norm of sincere or even unconditional care for relationship partners (Huang & Zhang, 2015). The study aims to examine whether and how these two types of relationships would interact with varied levels of perceived controllability of failure encounters, and jointly influence consumer responses toward the failure. Furthermore, this study intends to unveil the underlying psychological process that governs this predicted interaction effect. Three crucial outcomes—anger, perceived betrayal, and negative WOM intention—are investigated, such that consumers’ emotional, cognitive, and behavioral reactions can be simultaneously captured.

In this study, an online experiment was conducted with 140 U.S. consumers. Results show that whether positive relationships would mitigate or aggravate the failure is dependent on the specific nature of the relationships (exchange or communal) and the perceived controllability of the failure (low or high). This study connects the relationship management framework from public relations with attribution theory from social psychology to form a deep understanding of the underlying psychological process that influences consumer responses to service failure encounters. From a managerial perspective, these results offer useful guidelines for company-consumer relationship development and service failure management and recovery.

Literature Review

Service Failure and Organization-Public Relationships

Public relations is seen as a relationship management function “that establishes and maintains mutually beneficial relationships between an organization [e.g., a company] and the publics [e.g., consumers] on whom its success or failure depends” (Cutlip et al., 1994, p. 2). Relationship management has been a central framework for public relations research (Ferguson, 2018). For example, public relations researchers have identified various relationship cultivation and maintenance strategies for companies to develop positive relationships with consumers, such as open communication and networking with consumers (e.g., O’Neil, 2014). Researchers have also identified trust, satisfaction, and commitment as key factors in developing company-consumer relationships (e.g., Kang, 2013). Numerous studies have demonstrated the essential role of quality relationships in promoting positive attitudinal and behavioral outcomes among consumers (e.g., Hong & Yang, 2009; Ki, 2013; J. Kim & Sung, 2016). Even in the event of a crisis, positive relationships were found to protect companies from negative consequences (Ki & Brown, 2013). For example, many studies (e.g., Coombs, 2007; Coombs & Holladay, 2006; J. Kim, 2017) contended that a company’s positive relationships with its consumers functioned as a reservoir of goodwill, which can be withdrawn from in crisis time to buffer the company against negativity. That is, with positive precrisis relationships, consumers tend to doubt the alleged cause of the crisis, consider the crisis as a one-time mistake, and attribute less responsibility to the company (J. Kim, 2017). According to these studies, a “halo” or “buffering” effect of positive relationships often occurs. Yet a number of recent studies have challenged the belief of this buffering effect of positive prior relationships (e.g., Sohn & Lariscy, 2015; Tao, 2018). That is, they evidenced a backfiring effect of quality relationships after a failure situation, as committed consumers reacted negatively and punished the organization even more (Grégoire et al., 2009).

In view of these discrepant findings, this study aims to identify the boundary condition that determines when positive company-consumer relationships would remain and when it would fade. Specifically, this study focuses on a negative context when consumers encounter a negative experience, or a service failure, in their day-to-day interactions with service providers (aka consumer businesses). Service failure herein refers to service performance that falls short of a consumer’s expectations and requirements (Li & Stacks, 2017). For business-to-consumer companies, service failures are difficult to avoid because of “the involvement of customers and the considerable role of employees in the process” (Choi & Mattila, 2008, p. 25). The labor intensive nature of many consumer businesses and the involvement of third-parties contribute to the variability of consumer experiences (Hess et al., 2003). Yet these inevitable failures may lead to negative or extreme consumer reactions, which can easily overthrow hard-earned consumer trust and cast broader negative impact on the business (Grégoire & Fisher, 2008). Therefore, it is critical for public relations scholars and practitioners alike to pay close attention to such failure encounters at the individual level (Li & Stacks, 2017).

This study represents an effort to answer public relations scholars’ call for more empirical investigations at the individual level in general (Walden, 2016). Public relations practice needs to be understood not only in relation to society (macrolevel) and organizations (mesolevel) but also from the perspective of individuals (microlevel; Ihlen & Van Ruler, 2009). Echoing this proposition, this study adopts an individual-oriented approach and investigates individual consumers’ cognitive, affective, and behavioral responses after a service failure encounter. In the following sections, we first introduce the study framework built upon attribution theory and relationship norms, and then present the interplay between these two theories.

Perceived Controllability of Service Failure

Perceived controllability of service failure refers to the extent to which consumers interpret the cause of the failure as controllable or uncontrollable (Sinha & Lu, 2016). It concerns consumers’ inferences regarding whether the service provider (i.e., the company) could prevent or affect the occurrence of dissatisfactory service episodes (Grégoire & Fisher, 2006). Viewed from a broader perspective, perceived controllability is a key dimension of causal attributions that people make when exposed to negative situations such as service failures or crises (Albrecht et al., 2016; Coombs, 2007). According to attribution theory (Weiner, 2012), human beings are social perceivers who make cognitive efforts to infer the causes and consequences of events that they observe and/or experience. During this attributional process, three dimensions of causal attributions are assessed: controllability, locus, and stability (Weiner, 2012). Closely related to controllability attribution, locus attribution involves whether consumers perceive the cause of the failure originating within the company (i.e., an internal cause) or outside the company (i.e., an external cause) in the service failure context. Stability attribution concerns consumer beliefs regarding the cause of the failure as perpetual or temporary. Moreover, owing to the close conceptual tie between controllability and locus, many studies (e.g., S. Kim, 2013) have found that the two dimensions of causal attributions are highly correlated and easily conflated. As Coombs (1995) noted, research has consistently showed a substantial overlap between controllability and locus because they both reflect intentionality of an act. Indeed, in their meta-analysis of 45 articles on service failure attributions, Van Vaerenbergh et al. (2014) acknowledged that consumers’ interpretations of service failures differ mainly in terms of controllability and stability attributions. Additionally, it is noteworthy that these causal attributions do not need to be grounded in objective evidence (Weiner, 2012). Instead, they are often established upon consumers’ subjective interpretations of available information relevant to the failure situation. For example, an uncontrollable failure internally located may nevertheless be subjectively interpreted as controllable by consumers. Moreover, consumers tend to consider that most service failures originate from the company, resulting in unambiguous locus attributions (Xie & Heung, 2012). Therefore, this study opts not to differentiate the locus dimension as a separate factor.

In this study, we chose to focus on the controllability dimension of causal attributions for temporary failures. This is because controllability perceptions “link to inferences regarding personal responsibility, moral judgments, and moral emotions, including anger, sympathy, and gratitude, so that they are at the very heart of social behavior” (Weiner, 2000, p. 385). Furthermore, these perceptions are most directly tied to the service context of interest in this study (Varela-Neira et al., 2010). Compared with other attribution dimensions, controllability perceptions are likely to provoke stronger negative emotions and retaliations among consumers (Van Vaerenbergh et al., 2014). These response tendencies are particularly relevant to the service failure outcomes examined herein: anger, perceived betrayal, and negative WOM intention, as discussed later.

Controllability has been found to negatively influence consumers’ reactions in negative situations such as service failures or crises. Service failure literature has documented that when the failure was due to controllable actions of a company, consumers reacted negatively by showing greater anger and greater desire to hurt the business (e.g., Choi & Mattila, 2008). Conversely, consumer responses were more favorable when the failure was triggered by uncontrollable causes (Albrecht et al., 2016). Similarly, crisis communication literature has emphasized the importance of perceived controllability of a crisis in classifying crisis types and determining consumer responses to the crisis. For example, when the cause of the crisis is viewed as highly controllable by a company, the crisis is often interpreted as a preventable type of crisis and the company is often attributed with a high level of crisis responsibility (Coombs, 1995; Coombs & Holladay, 1996; S. Kim, 2013). As a result, consumers react to the company unfavorably (Jin, 2010). In other words, when perceived controllability is high (vs. low), consumers tend to evaluate the company more negatively (Coombs & Holladay, 2002; J. Kim, 2019), express more negative emotions such as anger (Ngai & Jin, 2016), spread negative WOM (Austin & Jin, 2018), and reduce purchase intention to a greater extent (S. Kim, 2013).

Furthermore, a few scholars have investigated the impact of prior relationship quality on perceived controllability and failure evaluations (e.g., Xie & Heung, 2012). Grégoire and Fisher (2006) found that when low controllability was inferred, consumers with high relationship quality experienced a lesser desire for revenge and spreading negative WOM than those with low relationship quality. To extend Gregoire and Fisher’s (2006) investigation, the present study focuses on the context of high-quality relationship only. It aims to address what factors influence consumer evaluations besides controllability attributions. It posits that the effect of controllability on consumer judgments is contingent upon the specific types of positive relationships that consumers have established with the companies prior to the failure encounter.

Communal and Exchange Relationship Norms

Two types of relationships have been conceptualized in public relations and consumer research: exchange relationship and communal relationship (Hung, 2005; Liu & Chang, 2017). According to social exchange theory, the distinction between the two is based on the norms of giving and receiving benefits (Clark & Mills, 2012). In an exchange relationship, people give each other benefits expecting receiving comparable benefits in return (i.e., quid pro quo). The receipt of benefits presents an obligation to reciprocate. As such, people’s interactions are mainly structured around the principle of how much they gain in exchange for how much they offer (Johnson & Grimm, 2010). Relationships between strangers and business partners are generally considered exchange relationships. In contrast, a communal relationship imposes no obligation for an equal benefit in return. Instead, the benefits are given out to meet relationship partners’ needs and requirements, which reflects a genuine concern for their well-being. In such a relationship, people tend to take each other’s perspectives and their relational tie transcends a focus on self-interest alone (Aggarwal & Law, 2005). Family relationships, romantic relationships, and friendships are typically communal in nature (Miller et al., 2017).

A list of distinctive relationship norms has been given in interpersonal communication literature to further explicate the differences between the two types of relationships: exchange relationships and communal relationships. For example, individuals in an exchange relationship were found more likely to keep track of inputs and outputs in a joint task, split up rewards in proportion to each party’s contributions, and anticipate to receive compensation for offering help (Clark & Mills, 2012). Comparatively, people in a communal relationship tend to keep track of their partners’ needs, distribute rewards according to the partners’ needs, and are less likely to expect comparable benefits in return (Clark & Mills, 2012).

Inspired by these insights from social exchange theory, public relations researchers proposed that publics may anthropomorphize an organization and form relationships with it in ways that mirror social relationships (Men & Sung, 2019). As a result, an exchange or communal relationship may be developed with the organization and affect publics’ subsequent interaction with and evaluation of the organization (J. Kim & Sung, 2016). Echoing the findings in public relations, consumer research also provided strong evidence that confirmed the critical role of relationship norms in determining consumers’ information processing and assessment of brands. For example, Aggarwal and colleagues’ renowned line of research showed that consumers’ evaluation of a brand is hinged upon whether their interaction with the brand adheres to or violates previously established relationship norms. In an experimental setting, these relationship norms, communal or exchange, could be made salient through a direct prime technique (e.g., experimental participants read a scenario that describes how a consumer interacts with a brand, and they are asked to assume the role of the consumer in the scenario; Aggarwal & Larrick, 2012) or an indirect prime technique (e.g., experimental participants read a scenario that describes how a person interacts with his or her friends, and the scenario or the person is unrelated to the participants; Aggarwal & Law, 2005).

Interplay Between Relationship Norms and Perceived Controllability

One primary proposition of this study is that consumers’ responses to a service failure are determined by the interplay of two factors: the type of relationship norms that they have developed with the company prior to the failure and the perceived controllability of the failure. Consumer responses herein include their emotion of anger, cognitive appraisal of perceived betrayal, and behavioral intention of negative WOM. The first response outcome, anger, is a negative emotion resulted from the belief that the company could and should have done something to prevent the service failure (Grappi & Romani, 2015). It is an immediate product of consumers’ perceptions of responsibility or blame that the company holds for the failure situation (Weiner, 2012). Consumer anger is a crucial outcome to examine because it can motivate consumers to end their relationships with the company (Coombs & Holladay, 2008). The second outcome, perceived betrayal, refers to “a customer’s belief that a firm has intentionally violated what is normative in the context of their relationship” (Grégoire & Fisher, 2008, p. 250). When consumers believe that the company has broken its promise, breached their trust, and violated their relationship norms, an elevated sense of betrayal will emerge, especially for committed consumers (Mattila, 2004). Relatedly, negative WOM represents negative informal communication among consumers regarding evaluations of a company and/or its products and services (Moon et al., 2016). “Organizations value word-of-mouth because of the benefits associated with positive word-of-mouth and the harm inflicted by negative word-of-mouth” (Coombs & Holladay, 2008, p. 253). Previous studies have frequently observed that highly dissatisfied consumers engage in negative WOM to vent their negative emotions (e.g., anger) so that a feeling of relief can be obtained and a sense of equity can be restored (e.g., Kähr et al., 2016). This negative behavior can “take the form of proving worth, gaining revenge, or getting others to act against the organization” (Austin & Jin, 2018, p. 166). It is especially pronounced among consumers who have positive relationships with the firm when a failure occurs (Grégoire & Fisher, 2006). Given that the aforementioned three response outcomes are theoretically correlated, this study predicts that relationship norm type and service failure controllability will produce the same interaction effect pattern on them, as elaborated below.

Research on relationship norms posits that consumers’ evaluations of a company are largely determined by whether their interaction with the company conforms to or violates already-established relationship norms (Aggarwal, 2004). Exchange norms emphasize an equal trade of comparable benefits (Liu & Chang, 2017). Therefore, consumers of exchange relationships expect an equivalent exchange of their patronage with quality service from the business. When a service failure occurs, consumers would regard the service they pay for not worth the money. This holds true for both controllable and uncontrollable service failures. In other words, regardless of the perceived controllability of the failure, consumers who have established exchange relationships with the company will consider such a failure a violation of cost-benefit-based relational norms. As a result, they will respond to the service failure, controllable and uncontrollable, equally negatively. Under such a circumstance, the norm violation lessens the buffering effect of good prior relationships such that consumers of exchange relationships will demonstrate similar levels of anger, perceived betrayal, and negative WOM intention in failure situations of varied controllability.

For communal relationships, when perceived controllability of the service failure is low (i.e., uncontrollable), it does not impair the communal norm because communal relationships do not impose equal benefit exchange. Therefore, consumers with communal relationships will forgive the company when the cause of the failure is perceived to fall out of the company’s control. When perceived controllability of the failure is high (i.e., controllable), however, the communal relationship norm is undermined because the company fails to look after the consumers’ interests and needs by avoiding a situation that could have been prevented. Given that the communal relationship norm is established to ensure that consumers feel secure and fulfilled in their relationships (Algoe, 2012), we can expect that a controllable failure breaches consumer trust and leads to greater levels of anger, perceived betrayal, and negative WOM intention than an uncontrollable failure. To summarize, the following hypotheses are proposed:

Hypothesis 1: There is an interaction effect between relationship norms and service failure controllability on consumer anger: (a) Under exchange relationship norms, there will be no difference in consumer anger between high and low failure controllability conditions; however, (b) under communal relationship norms, high failure controllability will generate a higher level of anger than low failure controllability.

Hypothesis 2: There is an interaction effect between relationship norms and service failure controllability on consumers’ perceived betrayal: (a) Under exchange relationship norms, there will be no difference in perceived betrayal between high and low failure controllability conditions; however, (b) under communal relationship norms, high failure controllability will produce a higher level of perceived betrayal than low failure controllability.

Hypothesis 3: There is an interaction effect between relationship norms and service failure controllability on consumers’ negative WOM intention: (a) Under exchange relationship norms, there will be no difference in negative WOM intention between high and low failure controllability conditions; however, (b) under communal relationship norms, high failure controllability will generate a higher level of negative WOM intention than low failure controllability.

Relationship Norm Violation as the Mediator

In addition to the proposed interaction effect of relationship norms and perceived failure controllability, this study suggests that relationship norm violation mediates such an interaction effect on consumer responses. To wit, in a social or interpersonal relationship context, norms serve as benchmarks against which an individual develops expectations and make evaluations of his or her relationship partners’ behavior (Clark & Mills, 2012). In a similar vein, when consumers form a certain type of relationships with a company, they assess the company’s actions in much the same fashion as they evaluate the conduct of other members of the society, that is, based on the norms of social behavior (Aggarwal, 2004). Depending on whether the company’s actions infringe or uphold the norms of its relationships with consumers, consumers provide either positive/rewarding or negative/punishing responses toward the company (Wan et al., 2011).

As specified earlier, exchange and communal relationships have their own distinct norms of behavior (Aggarwal & Larrick, 2012). Given that a failure occurrence violates the exchange and communal relationship norms to different extents and in different ways under high- and low-perceived controllability, we can expect norm violation mediates the interaction effect of relationship norms and service failure controllability. To summarize, this study posits:

Hypothesis 4: Relationship norm violation mediates the interaction effect of relationship norms and service failure controllability on (a) consumer anger, (b) perceived betrayal, and (c) negative WOM intention.

Method

An online experiment was conducted with a 2 (relationship norm types: exchange vs. communal) × 2 (service failure controllability: low vs. high) between-participants factorial design. Participants were randomly assigned to one of the four experimental conditions.

Participants

A convenience sample of 140 U.S. residents were obtained from Amazon Mechanical Turk (MTurk) to participate in this study with $1.00 compensation per person. Among them, 63.6% (n = 89) were male and 36.4% (n = 51) were female. The mean age was 34.61 years (SD = 10.30). As for race, 87.1% (n = 122) were White, 5.7% (n = 8) were African American, 3.6% (n = 5) were Asian, 2.1% (n = 3) were American India or Alaska Native, and 1.4% (n = 2) reported themselves as “other.” As for education, 46.4% (n = 65) had a Bachelor’s degree, 17.1% (n = 24) had some college credit, 10.7% (n = 15) had a high school diploma, 10.0% (n = 14) had an associate degree, 7.9% (n = 11) had a master’s degree, 2.9% (n = 4) had a professional degree, 2.9% (n = 4) had trade/technical/vocational training, and 2.1% (n = 3) had a doctoral degree.

Stimulus Materials and Pretests

Following previous research (Aggarwal & Larrick, 2012), this experiment featured a fictitious automobile service company named Bill’s Auto Service. To manipulate relationship norms (exchange vs. communal), two different scenarios of similar length were created, describing positive interactions between a customer and the company (see the appendix). In the exchange norm scenario, the company was described as “an ideal business partner—prompt, efficient and good value for money.” In the communal norm scenario, the company was described as “a caring friend” who “genuinely care[s] about you and treat[s] you like family.” To strengthen the manipulation, participants were asked to assume the role of the customer depicted in the scenario. According to Aggarwal (2004, p. 91), “even without actual long-term relationships, the effects of relationship norms may nevertheless be observed—suggesting that these norms can indeed be triggered in laboratory studies.” Such a manipulation approach of relationship norms (i.e., priming) has been widely adopted by existing research in consumer psychology (e.g., Aggarwal & Larrick, 2012; Li & Li, 2014).

A pretest among 48 MTurk participants who did not participate in the main experiment was conducted to check the manipulation of relationship norms. Participants were randomly assigned to read one of the scenarios and then answered 12 questions of which five tapped into exchange norms (e.g., “Bill’s Auto Service provides good service to get more business.”) and seven tapped into communal norms (e.g., “Bill’s Auto Service shows a genuine concern for my needs.”). Following the procedure in previous studies (e.g., Aggarwal, 2004), the five exchange norm questions were reversed coded and combined with the seven communal norm questions to form a Net Communality Score. These questions were measured on a 7-point scale adopted from Aggarwal (2004) and Hon and Grunig (1999). The results confirmed that the manipulation was successful. Participants in the communal norm condition (M = 4.88, SD = 0.62) scored higher on Net Communality than those in the exchange norm condition (M = 4.34, SD = 0.56), t(46) = 3.00, p < .01. Moreover, the manipulation did not have effects on confounding checks: perceived relationship quality, t(46) = 1.20, p > .05, perceived service quality, t(46) = .42, p > .05, or mood, t(46) = .72, p > .05.

To manipulate service failure controllability (low vs. high), another two different scenarios of almost identical length were developed (see the appendix). These scenarios depicted a service delay experienced by a customer of the company (i.e., the same customer from the relationship norm scenario). In the low controllability condition, the service delay was due to the fact that “the tire manufacturer accidentally sent the wrong tires” and the company “had to reorder.” In the high controllability condition, the service delay resulted from the fact that “their staff made a mistake ordering the wrong tires and they had to reorder.”

To check the manipulation of service failure controllability, a pretest was conducted among another 52 MTurk participants who did not take the main experiment. These participants were randomly assigned to read one of the service failure scenarios and then rated perceived controllability using three 7-point items adopted from Hess et al. (2003; e.g., “The cause of the service delay is controllable by Bill’s Auto Service”). The results confirmed that the manipulation was successful. Participants in the high controllability condition (M = 5.31, SD = 1.48) perceived the business had greater control over the service delay than participants in the low controllability condition (M = 3.92, SD = 1.31), F(1, 50) = 12.68, p < .01, ω²_p = .18. Moreover, the manipulation did not have effects on confounding checks, including perceived failure stability, F(1, 50) = 2.51, p > .05; perceived failure severity, F(1, 50) = .08, p > .05; or mood, F(1, 50) = .04, p > .05.¹

Variable Measures

Anger was measured using a three-item, 7-point scale adopted from Grégoire and Fisher (2008). Perceived betrayal was measured using a four-item, 7-point scale adopted from Grégoire et al. (2009). Negative WOM intention was measured using a three-item, 7-point scale adopted from Grégoire and Fisher (2006). Norm violation was measured using a seven-item, 7-point scale adopted from Aggarwal (2004), and Aggarwal and Larrick (2012). To ensure that the experiment results were not attributed to the difference of participants’ perceived relevance of the service category, service involvement was measured as a covariate using a 10-item, 7-point scale adopted from Zaichkowsky (1994). Additionally, to ensure that the experiment results were not caused by participants’ illusion of having previous knowledge of the fictitious company, brand familiarity was measured as a covariate using a three-item, 7-point scale adopted from Kent and Allen (1994). Please see Table 1 for specific items.

Table 1.

Measurement Items and Convergent Validity.

Variable	Item	CR	AVE
Anger	Outraged	.93	.88
Anger	Resentful	.93	.88
Perceived betrayal	I felt cheated.	.87	.70
	I felt betrayed by Bill’s Auto Service.
	Bill’s Auto Service broke the promise made to me.
Negative WOM intention	I would want to spread negative WOM about Bill’s Auto Service.	.91	.78
	I would want to denigrate Bill’s Auto Service to my friends.
	When my friends were looking for recommendations, I would tell them not to go to Bill’s Auto Service.
Norm violation	Bill’s Auto Service fulfilled its promises to me.	.92	.63
	Bill’s Auto Service met my expectations.
	Bill’s Auto Service behaved appropriately.
	I felt cornered by Bill’s Auto Service’s behavior.
	I felt exploited by Bill’s Auto Service’s behavior.
Service involvement	Important/Unimportant	.93	.60
	Relevant/Irrelevant
	Exciting/Unexciting
	Appealing/Unappealing
	Fascinating/Mundane
	Not needed/Needed
Brand familiarity	Familiar/Unfamiliar	.89	.73
	Inexperienced/Experienced
	Knowledgeable/Not knowledgeable

Note. CR = composite reliabilities; AVE = average variance extracted; WOM = word-of-mouth.

Experimental Procedure

At the start, participants read one scenario featuring the exchange or communal norms. Next, participants were presented with a service failure scenario of high or low controllability. Then they provided ratings on anger, perceived betrayal, negative WOM intention, and norm violation, followed by service involvement and brand familiarity as the two covariates. Finally, they reported their demographic information, including age, gender, race, and education.

Results

Measurement Validation

A confirmatory factor analysis (CFA) was conducted using SPSS Amos to check the validity of the measures in the main experiment. The initial model fit for the CFA model was not good, so the standardized regression weight was examined for each item. One anger item, one perceived betrayal item, two norm violation items, and four service involvement items were removed because of low regression weights (see Table 1 for the retained items). The revised CFA model had satisfactory model fit (χ²/degrees of freedom = 1.69, comparative fit index = .94, Tucker-Lewis index = .93, incremental fit index = .94, root mean square error of approximation = .07) based on the recommendation from Hair (2010). Composite reliabilities (CR) and average variance extracted (AVE) estimates were used to assess reliability and convergent validity of the measures. CRs varied from .87 to .93, all exceeding the acceptable threshold of .70 (Hair, 2010). AVE estimates ranged from .60 to .88, all exceeding the recommended threshold of .50 (Fornell & Larcker, 1981). Therefore, all variables in the measurement model had sufficient reliability and convergent validity.

To examine the measures’ discriminant validity, the square root of AVE was calculated for each variable and was compared with its correlation coefficients with other variables (see Table 2). Results showed that all the diagonal numbers (i.e., the square root of AVE) were larger than the corresponding off-diagonal numbers (i.e., correlation coefficients), indicating adequate discriminant validity.

Table 2.

Factor Correlation Matrix and Discriminant Validity.

Variable	Anger	Perceived betrayal	Negative WOM intention	Norm violation	Service involvement	Brand familiarity
Anger	.94^a
Perceived betrayal	.81**	.84^a
Negative WOM intention	.71**	.69**	.88^a
Norm violation	.45**	.52**	.25**	.79^a
Service involvement	−.34**	−.30**	−.29**	−.22**	.71^a
Brand familiarity	−.03	−.06	.06	−.24**	.20*	.85^a

Note. WOM = word-of-mouth.

The square root of average variance extracted.

p < .05. **p < .01.

Interaction Effects Between Relationship Norms and Service Failure Controllability

Anger

A two-way analysis of covariance (ANCOVA) test was conducted with anger as the dependent variable, and product involvement and brand familiarity as the covariates. The results indicated that service failure controllability had a significant main effect on anger, such that participants in the high controllability condition (M = 3.61, standard error [SE] = .19) expressed greater anger than participants in the low controllability condition (M = 2.75, SE = .19), F(1, 134) = 10.16, p < .01, ω²_p = .06. The results also revealed a significant interaction effect between relationship norms and service failure controllability on anger, F(1, 134) = 6.28, p < .05, ω²_p = .04 (see Figure 1). That is, under the exchange relationship norm, participants in high (M = 3.52, SE = .28) and low (M = 3.33, SE = .25) controllability conditions expressed similar levels of anger, p > .05, which supported Hypothesis 1a. Under the communal relationship norm, participants in the high controllability condition (M = 3.69, SE = .25) expressed greater anger than those in the low controllability condition (M = 2.17, SE = .28), p < .001, which supported Hypothesis 1b). Therefore, Hypothesis 1 was supported.

Figure 1.

Interaction effect between relationship norm and service failure controllability on anger.

Perceived Betrayal

A two-way ANCOVA test was conducted with perceived betrayal as the dependent variable, and product involvement and brand familiarity as the covariates. The results indicated that service failure controllability had a significant main effect on perceived betrayal, such that participants in the high controllability condition (M = 3.90, SE = .17) perceived greater betrayal than participants in the low controllability condition (M = 2.91, SE = .17), F(1, 134) = 17.25, p < .001, ω²_p = .11. More important, there was also a significant interaction effect between relationship norms and service failure controllability on perceived betrayal, F(1, 134) = 4.77, p < .05, ω²_p = .03 (see Figure 2). Specifically, under the exchange relationship norm, participants in both high (M = 3.83, SE = .25) and low (M = 3.36, SE = .22) service failure controllability conditions perceived similar levels of betrayal, p > .05, which supported Hypothesis 2a. Under the communal relationship norm, participants in the high controllability condition (M = 3.96, SE = .22) perceived greater betrayal than participants in the low controllability condition (M = 2.47, SE = .25), p < .001, supporting Hypothesis 2b. Thus, Hypothesis 2 was supported.

Figure 2.

Interaction effect between relationship norm and service failure controllability on perceived betrayal.

Negative WOM Intention

A two-way ANCOVA test was conducted with negative WOM intention as the dependent variable, and product involvement and brand familiarity as the covariates. The results indicated that service failure controllability had a significant main effect on negative WOM intention, such that participants in the high controllability condition (M = 3.03, SE = .19) expressed greater negative WOM intention than participants in the low controllability condition (M = 2.26, SE = .20), F(1, 134) = 7.88, p < .01, ω²_p = .05. However, there was no interaction effect between relationship norms and service failure controllability on negative WOM intention, F(1, 134) = .32, p > .05. Hence, neither Hypothesis 3a nor Hypothesis 3b were supported.

Moderated Mediation Analyses

Anger

A moderated mediation analysis with 5,000 bootstrapped samples was conducted using Model 58 of the PROCESS macro for SPSS (Hayes, 2012). Service failure controllability was the independent variable, relationship norm was the moderator, anger was the dependent variable, norm violation was the mediator, and product involvement and brand familiarity were the covariates. The results indicated that the moderated mediation was not significant (Β = −.07, SE = .26, 95% confidence interval [CI: −.56, .44]). In particular, we only found a simple mediation effect through which norm violation mediated the relationship between controllability and anger under both the exchange norm (Β = .41, SE = .20, 95% CI [.04, .82] and the communal norm conditions (Β = .34, SE = .17, 95% CI [.07, .71]). Hence, Hypothesis 4a was rejected.

Perceived Betrayal

A similar moderated mediation analysis was conducted with perceived betrayal as the dependent variable. The results indicated that the moderated mediation was not significant (Β = .01, SE = .25, 95% CI [−.47, .52]). In particular, we only found a simple mediation effect through which norm violation mediated the relationship between controllability and perceived betrayal under both the exchange norm (Β = .39, SE = .19, 95% CI [.04, .77]) and the communal norm conditions (Β = .40, SE = .17, 95% CI [.10, .78]). Thus, Hypothesis 4b was rejected.

Negative WOM Intention

A similar moderated mediation analysis was conducted with negative WOM intention as the dependent variable. The results indicated that the moderated mediation was not significant (Β = −.24, SE = .22, 95% CI [−.74, .13]). Similarly, we only found a simple mediation effect: norm violation mediated the relationship between controllability and negative WOM intention under the exchange norm condition (Β = .26, SE = .18, 95% CI [.01, .70]), but not under the communal norm condition (Β = .02, SE = .15, 95% CI [−.30, .32]). Hypothesis 4c was rejected. Please see Figure 3 for an illustration of the study results.

Figure 3.

The model of our experimental results.

Discussion

This study investigated the interplay between relationship norms and perceived service failure controllability on consumers’ emotional (i.e., anger), cognitive (i.e., perceived betrayal), as well as behavioral responses (i.e., negative WOM intention), before any interventions (i.e., service recovery efforts) took place. The attribution theory suggested that after encountering a service failure, consumers would infer the cause of the failure and form their initial judgment. This study focused on a key dimension of causal attributions, perceived controllability, and studied the interactions of different types of positive relationships with perceived controllability. It connected the attribution theory and the organization-public relationships framework to form a better understanding of consumer responses to failure encounters. Furthermore, this study extended previous research by identifying the boundary condition that determines when positive company-consumer relationships may lessen the failures’ negative impact and when such a buffering effect may not hold.

The results indicated that a low level of service failure controllability as perceived by consumers led to lesser anger and reduced feelings of betrayal than a high level of perceived controllability under the communal relationship norms but not under the exchange norms. However, such interaction effects were not observed on consumers’ negative WOM intentions, likely because the study used a fictitious company in the experiment. Compared with emotional and cognitive responses, behavioral intentions were more difficult to trigger given that no real interactions with the company were experienced by the study participants. In addition, the main effects of perceived failure controllability were confirmed across all the dependent variables and norm violation accounted for such effects in both relationship norm conditions.

In line with previous research (e.g., Aggarwal & Larrick, 2012), this study found that consumers’ company evaluations were based on the adherence to or violation of their formerly established relationship norms with the company. Specifically, exchange norms emphasize the principle of quid pro quo (Liu & Chang, 2017). Thus, consumers would expect a service they pay for to be worth the money (Wan et al., 2011). When a service failure occurs, the mere existence of a service failure breaches the exchange norm regardless of the perceived controllability of the failure. This perceived violation of exchange norms in turn leads to negative responses from the consumers. Contrarily, communal norms focus on relationship partners’ unique needs, independent of any benefit involved (Johnson & Grimm, 2010). Therefore, consumers would expect the company to be sensitive to their needs and interests (Aggarwal & Law, 2005). When an uncontrollable service failure occurs (i.e., low-perceived controllability), given that the company does not intentionally ignore consumers’ needs, consumers would attribute the cause of the failure to situational factors and therefore are unlikely to blame the company. However, in the case of a controllable service failure (i.e., high-perceived controllability), consumers would interpret the company’s action as an intentional violation of the communal norms in that the company could have prevented the failure if it had considered consumers’ needs and interests. As a consequence, this perceived norm violation would bring forth more negative responses among communal consumers.

Furthermore, the results of the moderated mediation analyses indicated that relationship norm types (exchange vs. communal) did not moderate the indirect effects of norm violation between perceived controllability and the dependent variables (i.e., anger and perceived betrayal). In fact, norm violation accounted for the impact of perceived controllability under both the exchange norm and communal norm conditions. In other words, regardless of the relationship norm types developed between consumers and the company, a high level of perceived failure controllability would lead to greater anger and perceived betrayal owing to consumers’ increased perceptions of norm violation. It is highly possible that other mediators in addition to norm violation existed and these potential mediators offset the impact of norm violation, especially in the exchange norm condition. However, the results revealed the simple mediation effects through which norm violations were experienced in both the exchange and communal scenarios. This result supported our proposition that relationship norm violation influences consumer evaluations of their service failure encounters. Future research may further explore the underlying mechanisms that explain the effects of perceived failure controllability when consumers adopt the exchange relationship norms.

Theoretical Contributions and Practical Implications

This study contributes to current corporate public relations and company-consumer relationship management scholarships in several important ways. First, it presents a convincing case for incorporating the examination of consumers’ service experiences into research on company-consumer relationships. These service experiences are in essence building blocks of company-consumer relationships, which are conceptualized as “the patterns of interaction, transaction, exchange, and linkage between an organization [i.e., the service provider] and its publics [i.e., consumers]” (Broom et al., 2000, p. 18). They carry important implications for consumers’ attitudinal evaluations of and behavioral decisions regarding the company (e.g., decisions on whether to continue or exit the relationship with the company; Koermer, 2005; Li & Stacks, 2017). Fundamental as these experiences are, public relations scholars have taken relatively limited research to understand their nature and influence. This study addressed the research gap by examining a critical type of consumers’ service experiences: service failure encounters. Through revealing the emotional, cognitive, and behavioral consequences of service failure encounters, this study illuminated the necessity for public relations scholars to conduct research on service failures and other service experiences.

Second, service failures do not occur in vacuum. Contextual factors such as consumers’ relationships with the company prior to the failure matter. This study not only distinguishes two types of prior relationships, exchange and communal, but also tested their respective impacts on consumer responses to service failures with varied levels of perceived controllability. Although these two types of relationships have been emphasized in public relations literature, they are frequently discussed as products of public relations efforts (e.g., Lee & Kee, 2017) rather than antecedents that lead to other public relations outcomes such as consumers’ emotional, cognitive, and behavioral responses. Furthermore, few studies have theorized and empirically tested the divergent effects of the two types of relationships on these other outcomes (J. Kim & Sung, 2016). Thus, this study filled the voids by documenting how exchange versus communal consumers responded differently to a service failure, thus developing a fine-tuned understanding of organization-public relationships in the commercial context.

Third, perhaps the most important contribution of this study is its significant findings on the interactive influence of relationship norm type and perceived failure controllability. Such insights allude to the conclusion that good relationships may not always function as a reservoir of goodwill that buffers a company against negativity. Instead, these relationships, communal in particular, may impose extra burdens on the company once its act violates the specific relationship norms it has preestablished with its consumers. Such “dark” side of positive, communal relationships has not been identified by previous research in public relations. By providing strong empirical evidence on this counterintuitive effect, this study adds to our body of knowledge on company-consumer relationships.

Apart from the above theoretical contributions, the results of this study yield critical implications on company-consumer relationship management and service failure management practice. To elaborate, service failures occur frequently in nowadays’ marketplace. While incidents of uncontrollable service failures may be tolerable owing to the weakened attribution of blame to the company (Grégoire & Fisher, 2006), acts of controllable failures can put heavy pressure on a company’s relationships with its consumers. Therefore, preventive measures need to be taken to reduce the occurrence of service failures of high-perceived controllability. However, when such failures become inevitable, companies should reflect upon the specific relationship norms (i.e., communal or exchange) they have developed with their consumers and evaluate the extent of norm violations that the failures have posed. By doing so, companies can anticipate potential reactions (i.e., punitive or forgiving) from consumers.

Additionally, since different relationships lead to different expectations of how relationship partners should interact with each other (Clark & Mills, 2012), these relationships also generate distinct expectations regarding how companies should act and communicate to facilitate service recovery after the failure. Although service recovery is not the focus of this study, given the importance of relationship norm conformity evidenced herein, this study suggests the company to implement norm-appropriate service recovery strategies to restore consumer relationships.

Last, this study cautioned companies not to abuse the relationship capital they have accumulated with their consumers. Our results showed that not all good relationships work to protect the firm from the mistake it commits and that consumers who are “good friends” with the company may turn into its “enemies” after one preventable, dissatisfactory service encounter. Thus, companies should be vigilant in complying with relationship-appropriate norms and protect its consumer relationships in each service episode.

Limitations and Suggestions for Future Research

Despite the aforementioned contributions, this study has several limitations. First, it used a fictitious company and hypothetical scenarios to manipulate relationship norm types and perceived failure controllability. Although this approach eliminated potential confounds that are associated with using an existing company, which thereby secured the internal validity of the experimental results, future research can use a real company and examine how consumers’ existing relational experiences with the company affect their attributions of real service failure encounters and their reevaluation of the company. By doing so, the external validity of the observed effect patterns can be enhanced. Second, this study used a convenience sample from MTurk. Although previous research revealed numerous advantages of using MTurk participants (e.g., Kees et al., 2017), generalizing the results of this research to a different population should be exercised with caution. Third, this study focused on testing how perceived failure controllability functioned as a boundary condition that determined when good prior company-consumer relationships buffer or backfire. Future research can explore other boundary conditions that may produce similar effects. Identification of these boundary conditions will benefit corporate communication professionals in improving their relationship nurturing and service recovery practices.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Weiting Tao

Linwan Wu

Notes

Author Biographies

Zongchao Cathy Li is interested in studying the relationships between emotive and psychological variables and consumer behavioral outcomes.

Weiting Tao’s research interest lies in corporate public relations, particularly corporate social responsibility and crisis management.

Linwan Wu studies how communication technologies influence consumers’ responses to strategic communication.

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