Customer Rage Back-Story: Linking Needs-Based Cognitive Appraisal to Service Failure Type

Journal of Retailing 89 (1, 2013) 72–87

Customer Rage Back-Story: Linking Needs-Based Cognitive Appraisal to Service Failure Type Jiraporn Surachartkumtonkun a,1 , Paul G. Patterson b,∗ , Janet R. McColl-Kennedy c,2 a b

Department of Marketing, Griffith University, Gold Coast, QLD 4222, Australia School of Marketing, University of New South Wales, Sydney, NSW 2052, Australia c UQ Business School, University of Queensland, Brisbane, QLD 4072, Australia

Abstract The back-story of customer rage, that is, what is behind a rage episode, specifically the customer’s cognitive appraisal processes that trigger extreme negative emotions, and the customer’s background (culture) is not well understood. This study involving 435 adult customers, investigates over two time periods (Episode 1: initial failure, and Episode 2: ineffective recovery), the association between the initial service failure type, subsequent ineffective service recovery attempts, and customers’ cognitive appraisals. Our two country research clearly shows that service failure types are differentially associated with different forms of cognitive appraisals (i.e., perceived threats to resources, self-esteem, justice, control, and physical well-being), irrespective of the customer’s home country. However, US and Thai customers appear to place different relative importance on cognitive appraisal types. Marketing managers can use this study to identify triggers of customer rage thus equipping them to implement strategies designed to mitigate this potentially harmful behavior. © 2012 New York University. Published by Elsevier Inc. All rights reserved. Keywords: Customer rage; Service failure and recovery; Psychological needs; Cognitive appraisal

Introduction “I purchased . . . [a] used vehicle and found that the A/C was not working. . . [A] manager . . . assured me that they would fix it. . . [But] it would cost me $175. I took the car back [45 minutes drive] for the repairs . . . [but] the A/C still was not working. I felt very upset . . . [They] told me that . . . parts needed to be fixed . . . it would cost me a couple of hundred more . . . I felt very angry and indignant. . .I was outraged. . .. We had a quarrel . . . I yelled back. . . . I left without paying. I am determined to never use this dealership again and to tell anyone . . . that they were not honest in their dealing.” (female, 40, US, car dealership) “. . . It was annoying that my cell phone received a poor signal . . . I tried to call the customer service number but it was ∗

Corresponding author. Tel.: +61 2 9385 3385, fax: +61 2 9663 1985. E-mail addresses: [email protected] (J. Surachartkumtonkun), [email protected] (P.G. Patterson), [email protected] (J.R. McColl-Kennedy). 1 Tel.: +61 7 555 28713; fax: +61 7 555 28085. 2 Tel.: +61 7 334 68178; fax: +61 7 334 68166.

difficult to get connected. . . . After several attempts, I got to talk to a service employee. . . . She told me that it happened because of my cell phone and it has nothing to do with their company. . . . I was already upset about having to call them several times and this kind of response really drives me mad. . . . She told me I need to change my cell phone. . . . I got very angry so I yelled at her and demanded an apology. . . .I reported this incident to the manager . . .” (female, 27, Thai, cell phone service) Customer rage episodes are occurring across the globe in store, online, over the phone and in the air with potentially serious consequences not only for the front-line employee facing the brunt of the outburst, but also for the brand, even other customers, such that rage episodes can incur significant economic and social costs (Febrina 2009; Horovitz 2011; Villigram 2006). Prior research (e.g., DeWitt and Brady 2003; Fitness 2000; Harris and Reynolds 2003) has focused on the harmful consequences of customer rage following a service failure, including violent behaviors, verbal or nonverbal attacks, exiting, and negative word of mouth. However, the back-story of customer rage, that is, what led up to the rage episode, particularly the customer’s cognitive appraisal processes that trigger

0022-4359/$ – see front matter © 2012 New York University. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jretai.2012.06.001

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extreme negative emotions and their background (culture), is still not well understood (Hess, Ganesan, and Klein 2007; Reynolds and Harris 2009). Few studies have attempted to explain the psychological drivers of customer rage. Earlier conceptual work (Schneider and Bowen 1999) proposed that rage incidents originate from mishandling customers’ basic human needs, such as justice and self-esteem which are deeply ingrained in the customer’s psyche. The importance of fundamental human needs becomes more apparent when the needs are deprived driving a customer to react with extreme negative emotions and rage behaviors (Patterson et al. 2009). Several studies in psychology (e.g., Baumeister and Leary 1995; Shapiro, Schwartz, and Astin 1996) also support the view that an individual’s cognitive appraisal process can act as a trigger of aggressive and destructive behaviors. Although prior studies have provided critical knowledge of the psychological link to customer rage, more remains to be done to better understand the cognitive appraisal processes leading to customer rage following a service failure and the variables that influence this cognitive appraisal. This gap in our understanding of customer rage leaves several important questions unanswered. For example, little is known about whether different cognitive appraisals (e.g., threat to self-esteem or threat to justice) are associated with a certain type of service failure, such as core service failure or unresponsive employee behavior. It is also unclear whether associations vary across East-West cultures as customers from collectivist Eastern countries (e.g., China or Thailand) and individualist Western societies (e.g., USA or Australia) interpret and evaluate consumption experiences differently (Chan, Yim, and Lam 2010). We employ the theory of stress and coping (Lazarus and Folkman 1984) to offer insights into the link between cognitive appraisal and type of service failure among Western and Eastern customers over two time periods: following an initial service failure (Episode 1), and an ineffective (or non-existent) service recovery (Episode 2). We address two key research questions: (1) What is the association between type of service failure and customers’ cognitive appraisals that trigger rage incidents?; and (2) To what extent does culture (East/West) moderate the association between service failure type and cognitive appraisal? Our study contributes in at least three important ways. First, to our knowledge, this is the first empirical study of customer rage to delve into the customer’s cognitive appraisal process at two time points (Episode 1: initial service failure and Episode 2: ineffective or non-existent service recovery). Second, we establish a clear empirical link between type of service failure (e.g., core service, unresponsive, inappropriate behavior) and cognitive appraisals (e.g., perceived threats to self-esteem, justice need, security) that trigger rage. Third, we demonstrate the extent to which a customer’s cognitive appraisal process may be generalized across Western–Eastern cultures. Conceptual development

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experience (McColl-Kennedy et al. 2009). The consequences of customer rage are known to create an economic loss for the firm involved (Grove, Fisk, and John 2004), severe psychological strain for front-line service employees (Dormann and Zapf 2004; Grandey, Dickter, and Sin 2004), and a ripple effect of emotional contagion in the service encounter (Dallimore, Sparks, and Butcher 2007). In order to understand the psychological process that drives customer rage, we draw on affective events theory (AET) incorporating the theory of stress and coping (Lazarus and Folkman 1984). Affective events theory Affective events theory posits that individuals react to a negative event through a two stage process (appraisal and emotion) (Weiss and Cropanzano 1996). According to AET, individuals make an initial cognitive appraisal of events in their life that elicit emotions. The valence (positive or negative) is related to whether the encounter is perceived by the individual to be a threat (or beneficial) to one’s well-being. For example, a situation such as discrimination has been appraised by African Americans as a threat to their self-esteem and sense of control, which then triggers negative emotions such as withdrawal or depression (Outlaw 1993). The theory of stress and coping (Lazarus and Folkman 1984) further posits that during negative emotional responses, individuals experience a psychological state of disequilibrium and are driven to return to their normal state through coping. Coping strategies may be grouped into either problem-focused coping or emotion-focused coping. Typical coping behaviors include rational planning, confrontation and seeking social support. Rage behaviors such as verbal or physical aggression are a form of coping strategies customers employ to deal with the source of stress. The current study further explores the cognitive appraisal process but not coping strategies. Service failure types In the context of service provision, negative events that create a threat to a customer’s well-being, may take several forms of service failure, and can be divided broadly into initial service failure and ineffective service recovery (Bitner 1990) and further categorized into several broad failure types (Bitner, Booms, and Tetreault 1990; Keaveney 1995). In a “core service failure”, the firm does not fulfill its promise of providing the core service. It involves all critical incidents due to mistakes or technical problems with the service itself (e.g., billing error, failure to provide the promised service/physical good). The next category relates to “how” the service is delivered, labeled “unresponsive” employee behavior. A third category is “inappropriate” behavior, such as rude and impolite employee behavior. A fourth is “slow speed of service”, and a fifth category is “unethical” behavior such as illegal, immoral, dishonest, unsafe or unhealthy behavior. Cognitive appraisal process

Customer rage is defined as furious, overwhelming, extreme anger accompanied by its expression and potentially harmful behaviors towards the firm following a dissatisfactory service

The cognitive appraisal process goes a long way in explaining why people have strong emotional reactions to stressful life

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events such as daily personal problems, community relocations, sexual abuse of children, and dissatisfactory service encounters. Appraisal refers to a cognitive process through which a person interprets or evaluates an event as a challenge, harm or threat (Lazarus 1984). Studies in psychology point out that subjective appraisal of an event is a key determinant of emotional responses (e.g., Ellsworth and Smith 1988; Frijda 1993). Challenge refers to a sense of difficulty that blocks the achievement of personal goals or needs although the person has confidence in his or her ability to overcome the hindrance. Harm or threat appraisal refers to damage of personal values and needs, or threat to the security of a loved one. Harm and threat appraisals of events in the context of fundamental human needs are fertile ground for extreme negative emotions (McColl-Kennedy and Smith 2006). Threats to fundamental human needs Essentially, individuals strive to satisfy fundamental human needs in their life. This directs the cognitive appraisal process and has an impact on emotional reactions (Baumeister and Leary 1995). When needs are blocked, individuals strive to find ways of fulfilling their needs because these are inherent motivations in human behaviors in the person–environment interaction (Markus and Wurf 1987). Fundamental needs fulfillment is critical to one’s psychological well-being and the construal of self (Markus and Kitayama 1991). A mismatch of the meaning in the situation (e.g., perceived violation of one’s self-esteem due to poor service) and the internal meaning of self (e.g., needs for self-esteem) can result in considerable distress (Burke 1991). If needs are persistently withdrawn, it can lead to severe negative reactions (Baumeister and Leary 1995). Thus, in service settings, violation of customers’ fundamental human needs can lead to extreme emotional and negative behavioral responses. In line with prior studies (e.g., Patterson et al. 2009; Schneider and Bowen 1999), we propose that cognitive appraisals that lead up to rage incidents would entail threats to customers’ fundamental human needs for physical well-being (safety), resources, self-esteem, justice, and control arising from a range of service failure types. In addition to, the needs for security (physical well-being and economic well-being), esteem and need for justice (Schneider and Bowen 1999) we include a sense of control as another fundamental need during a service encounter (Hui and Bateson 1991; Langer and Rodin 1976) The next section discusses each of these fundamental needs and accompanying hypotheses linking specific types of service failure to various forms of cognitive appraisal. Resource needs (money and time) Resource needs refer to a desire to protect one’s economic well-being such as financial security (Schneider and Bowen 1999). Financial security, the effective use of time in various activities, or whether money is well spent are the typical economic well-being issues that people deal with in their daily life. When a service failure occurs, especially in the area of a core service mistake, it is likely to create a perceived loss of customers’ resource needs (Smith, Bolton, and Wagner 1999) and could potentially drive customers to exit (Keaveney 1995).

As we expect a core service failure only to occur at the initial failure, we predict that it will only be associated with a threat to resources at Episode 1, but not at Episode 2 (recovery stage). Hence our first hypothesis H1: Core service failure at Episode 1 is positively associated with a threat to a customer’s resources. Further, slow speed of service, such as an excessively long wait in a call center line or in person in a retail bank, for example, is perceived as a loss of resources (time). For many customers time is one of their most precious resources. Several studies have empirically linked slow speed of service to customer dissatisfaction (e.g., Tax, Brown, and Chandrashekaran 1998; Wirtz and Mattila 2004), and specifically to a one’s resources (Smith, Bolton, and Wagner 1999). Hence, slow speed of service can trigger the initial failure as well as being a violation of customers’ needs at the recovery stage (Episode 2). Hence H2: Slow speed of service is positively associated with a threat to resources at Episodes 1 and 2. At the service recovery stage unresponsive behavior by employees (e.g., ignoring the complaint, displays of uncaring behavior) is also likely to be perceived as a threat to customers’ resources as such behavior signals that: (a) customers are wasting their time complaining; and (b) there is still no restitution for the initial core service failure. Hence, our next hypothesis H3: Unresponsive employee behavior at the recovery stage (Episode 2) is positively associated with a threat to resources. Self-esteem needs Self-esteem refers to a person’s view of his or her own self-worth (Rosenberg 1965). Feeling good about oneself can potentially have a positive impact on mental well-being (Caplan 1974). Self-esteem plays an important role in a consumer’s decision to purchase. For example, Sirgy (1982) shows that customers are motivated to buy a good or service that maintains or enhances their self-esteem and often avoid consumption that has the potential to harm it. The quality of interpersonal interactions of service employees in listening, displaying empathy, apologizing and being responsive – i.e., displaying respect, is a central factor in either enhancing or damaging customers’ feelings of self-worth (Patterson et al. 2009). Schneider and Bowen (1999) go further to suggest that failure to gratify a customer’s selfesteem will result in negative emotions and vengeful behaviors, but enhance it and they will love you. Or as Blodgett, Hill, and Tax (1997, p. 203) note, “a customer complaint could be disastrous if . . .an employee acts rudely”. Accordingly, we expect H4a: Unresponsive employee behavior is positively associated with threats to customers’ self-esteem at both Episodes 1 and 2 and H4b: Inappropriate employee behavior is positively associated with threats to customers’ self-esteem at both Episodes 1 and 2. Sense of justice (fairness) needs Justice refers to a need that one should receive no less than one deserves (Lerner 2003), derived from an implicit psychological contract of being treated fairly (Seiders and Berry 1998). The prominent view of fairness in service recovery has centered on justice theory (Tyler 1994). Justice or fairness

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concerns perceptions when individuals compare the ratio of their outputs (what they receive) to inputs (what they pay – financial and non-financial) to the ratio of the other party. The theory predicts that when there are differences the person concerned will seek to bring about a state of equilibrium. Service marketing scholars argue that to maintain and enhance the customer’s sense of justice, firms must deliver justice on three dimensions: distributive justice, procedural justice, and interactional justice (Smith, Bolton, and Wagner 1999; Sparks and McColl-Kennedy 2001; Tax, Brown, and Chandrashekaran 1998). When firms fail to provide a sense of fairness to their customers (e.g., breaking a promise), it can lead to the perception of being cheated (Dunn, Brown, and Maguire 1995), as well as giving rise to negative responses such as switching behaviors, complaining, having strong negative emotions, and even aggressive behavior (Chebat and Slusarczyk 2005; Mattila and Patterson 2004; Schoefer and Ennew 2005). Hence, we expect H5a: Unresponsive employee behavior is positively associated with threats to justice in Episodes 1 and 2 and H5b: Unethical employee behavior is positively associated with threats to justice in Episodes 1 and 2. Control needs A need for control refers to a need for the belief in oneself of being able to achieve a goal, deal with a problem, or control a situation (White 1959). Need for some control in one’s life is regarded as basic (Skinner 1996). Individuals feel and behave positively when they perceive that they are competent and able to freely make decisions (Hui and Bateson 1991; Proshansky, Ittelson, and Rivlin 1970). In contrast, lacking a sense of control could result in a perception of helplessness and subsequently maladaptive behaviors (Bowen and Johnston 1999). A need for some degree of control is essential for any satisfying relationship (Hui and Bateson 1991) and is known to influence customer satisfaction and positive emotional reaction (Langer and Rodin 1976). Our critical incident descriptions suggest that a lack of control, a sense of helplessness or of “feeling cornered” only becomes manifest when there is a ‘double deviation’ – i.e., an initial service failure coupled with an ineffective service recovery, and then not knowing where to turn. In other words, at the time of experiencing the initial failure the consumer is entitled to believe they have a degree of control over the issue being resolved, but not so subsequently when there is an unsatisfactory (or no) recovery (Episode 2). Hence, when employees are unresponsive in the face of a complaint we expect customers to perceive that they have a lack of control over the recovery situation. Hence H6: Unresponsive employee behavior at Episode 2 is positively associated with a threat to customers’ need for control. Physical well-being (security needs) Physical well-being needs or the need to be free from physical harm is the most basic of Maslow’s (1943) hierarchical needs and the most important of all human needs. Customers cannot be satisfied with service encounters unless they feel secure in their lives. Service firms must be aware of security issues for the protection of both their employees and customers.

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Failure to provide a safe service environment can result in public outrage (Schneider and Bowen 1999). In fact, individuals typically avoid involvement in situations that can harm their physical well-being. Following the September 11 attack, for example, many people feared being in an airport or taking a flight and hence tended to travel by plane less during that time. In the context, very few respondents reported threats to their physical security and therefore we do not develop a hypothesis around this appraisal. The above discussion of fundamental human needs predicts that if customers’ needs are threatened through a range of service failure types, customers can be expected to experience strong negative emotions, including customer rage. However, to fully understand customer rage we argue that the cultural background of customers should also be examined. Culture Kluckhohn (1962, p. 25) defines culture as the part of human makeup that “is learned by people as the result of belonging to a particular group, and is that part of learned behavior that is shared by others.” Indeed, Ringberg, Odekerken-Schroder, and Christensen (2007) argue that customers have cultural models that organize much of how they see the world. These cultural models govern most daily interactions, including social, professional and personal dealings with others. Cultural models help people respond to the world around them and create their sense of self. Ringberg et al. (2007) propose that customers tend to adopt one of three cultural models; relational, oppositional and utilitarian in Western societies (their study did not extend to Eastern societies). They argue that cultural models are particularly relevant when customers experience self-relevant breaches. Albeit in a Western society, Ringberg et al. (2007) associate the relational cultural model with security, love affection, self-esteem and respect, while an oppositional view focuses on control and resources, and a utilitarian view focuses on resources (time and finance). These findings lend further support to the importance of delving deeper into customer cognitive appraisals of threats to or violations of needs, as well as culture, in explaining the back-story to customer rage. National culture is important in the context of this study because of the way in which individuals from high context collectivist societies such as Thailand or China establish and maintain relationships, and express their emotions and dissatisfaction. There is evidence in cross-cultural studies that individuals from collectivist societies and individualist societies (e.g., United States, United Kingdom, Australia) process information and behave differently following service failures (Patterson and Smith 2003). Furthermore, Eastern customers are known to have different views to Western customers on what constitutes good customer service (Zeithaml and Bitner 1996). For example, Japanese consumers view Western “friendly” style of a front-line employee who may greet and chat in a casual way as disrespectful (Winsted 1997). In this study, we examine customer rage in two highly dissimilar cultures (i.e., the US and Thailand). The cultures of the US and Thailand represent polar extremes in cognition and behavior.

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Hofstede’s (1980, 1991) cultural framework reports four key dimensions along which nations are rated – individualism/collectivism; uncertainty avoidance; masculinity/femininity; and power distance. The clearest division between West and East is evidenced on the dimension of individualism/collectivism. On this dimension the US has an index score of 91 indicating a highly individualist culture, whereas Thailand rates only 17 on the index (Hofstede 1980). In collectivist societies, such as Thailand, people tend to value interdependence, social hierarchies, and conformity to social norms more so than in individualist society (such as the US) where individuals tend to emphasize independence, achievement, and uniqueness. Members of collectivist cultures tend to belong to few social or ingroups but tend to have stronger ingroup bonds compared to members of individualistic cultures who tend to belong to a greater number of social groups that have relatively weak ingroup bonds (Hui, Triandis, and Yee 1991). In fact, individualistic culture members’ willingness to interact with strangers (outgroup) is a feature of individualistic, egalitarian societies. The differences in interacting with ingroup and outgroup have implications for how Eastern versus Western customers perceive an interaction with a front-line service employee. Matsumoto, Yoo, and Chung (2010, p. 132) suggested that “collectivist cultures are associated with relatively more dissatisfaction toward outgroups, because doing so enables greater distancing between ingroups and outgroups and reinforces group identity”. Next, on the uncertainty avoidance dimension, the US rates 43 on the index suggesting a weak uncertainty-avoidance culture, while Thailand has a score of 66. Eastern cultures are characterized by uncertainty avoidance behaviors, that is, the degree to which people resist change, are less risk taking, feel threatened by ambiguous situations, and are considerate of others ‘face’ (Triandis 1995). In Thailand for example, the core cultural concept of Kreng Jai (which literally means that one will readily inconvenience themselves to avoid inconveniencing, disturbing, or contradicting another) suggests that consumers are less likely to complain or go into rage than their Western counterparts. Femininity (vs. masculinity) is the degree to which quality of life, maintenance of warm personal relationships and personal services prevail over values of assertiveness, performance, success and competition. This depicts the relationship-rich nature of Eastern, Asian societies. On this dimension the US has an index score of 62, indicating a high masculine culture, whereas, Thailand scores 32 on the index. Finally, regarding power distance, the US only rates 39 on the index suggesting a small power distance society, whereas Thailand has a relatively high index score of 66. Power distance is the extent to which less privileged members of a society expect and indeed accept that power and influence are distributed unequally in society. In these societies, it might therefore be reasonably expected that in service encounters between “unequal” actors, there will be reluctance by one actor to complain or express their unhappiness to the more powerful actor. Accordingly, we expect that Thais living in a high power distance society will be less forgiving of inappropriate

front-line employee behavior (e.g., impolite, rude) than their US counterparts as this reinforces the differences between ingroup and outgroup, and maintain differences in social status. For unresponsive employee behaviors (e.g., unresponsive, unknowledgeable), however, we expect that US customers who usually demand for quality service are more likely than Thais to perceive unresponsive employee behavior as a service failure. Hence H7: Eastern customers are more likely than Western customers to appraise inappropriate behavior as a cause of service failure at Episodes 1 and 2, and H8: Western customers are more likely than Eastern customers to appraise unresponsive behavior as a cause of service failure at Episodes 1 and 2. The difference in cultural value orientation between the two societies will influence customers’ sensitivity to violation of fundamental human needs. An individualist society places more emphasis on autonomy with people encouraged to be independent and to pursue their own goals. Hence, customers from an individualist society will need a greater sense of control than customers from a collectivist society particularly in a situation where something has gone wrong in order to manage a solution to the problem. In contrast, a customer living in a high power distance, collectivist society (Hofstede 1983) tends to rely on service providers whose duty it is to get the service right and solve the problem, and hence tend to be less sensitive to a loss of control. Indeed, Sastry and Ross (1998) show that Asians have a lower need for control than non-Asians and this need for control has less impact on psychological distress among Asians. Accordingly, we expect US customers to have a greater need for a sense of control than their Thai counterparts. Hence H9: Western customers are more likely than Eastern customers to appraise an ineffective service recovery as a threat to their sense of control. Finally, as noted earlier collectivist Asian cultures are “relationship rich” (Triandis 1995) where interpersonal relations are paramount in any transaction, and one’s satisfaction in life comes by and large from the respect of one’s in-group. By contrast, in Western societies, materialism and threats to one’s resources dominate. With this in mind, we propose H10: Western customers are more likely than Eastern customers to appraise initial service failure as a threat to their resources.

Control variables We include age, gender and criticality of the service transaction as control variables. Criticality of the service transaction refers to the perceived importance of the transaction as viewed by the customer. There is evidence supporting the view that the criticality of the consumption has an impact on the customer evaluation process (Garbarino and Johnson 1999; Hoffman and Kelley 2000; Webster and Sundaram 1998) because a customer’s resources (time and money) are often at stake. Furthermore, Ostrom and Iacobucci (1995) showed that in a service context, criticality has an influence on customers’ evaluation of what service attributes are important. Hence, we include criticality as a control variable. The inclusion of these control variables provides a more robust test of our hypotheses.

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Method Our research employs the critical incident technique (CIT) to uncover types of initial service failure, types of ineffective service recovery and customers’ cognitive appraisal processes. CIT is a qualitative method that facilitates the investigation of significant incidents (Chell and Pittaway 1998; Flanagan 1954). CIT has been used in prior studies related to cognitive appraisal processes and emotion elicitation (e.g., Ruth, Brunel, and Otnes 2002; Weiner, Russell, and Lerman 1979). In service contexts, CIT has proved useful in understanding customers’ cognition, emotion, or behavior (Bitner, Booms, and Tetreault 1990; van Dolen et al. 2001) as this method enables deep insights to be obtained from respondents’ narratives of their own thoughts and emotions. It also helps reduce interviewer bias and selective listening or recording (Keaveney 1995). Therefore, given that the cognitive appraisal process that precedes rage expressions is poorly understood in both initial service failure and failed recovery contexts, CIT is an ideal method to explore and refine key themes and then examine the nature of the association between cognitive appraisal and type of service failure (and subsequent service recovery efforts). Data collection The population of interest is customers who have experienced an extreme form of negative emotion accompanied by some form of rage expression (yelling, slamming the telephone, threatening, etc.) subsequent to a service failure. An explanation of customer rage (e.g., extreme anger, fury, rage, etc. and accompanying rage expressions) was given in the instructions section of the questionnaire. Only respondents who said that they had experienced rage in the past 6 months were included in the sample. Respondents were then asked to recall a recent customer rage incident that resulted from a failed service encounter on the part of the firm and describe their experiences and emotions in detail in their own words. Respondents provided the following information: 1) the situational context (e.g., retail, health care service); 2) the specific circumstances surrounding the incident (the customer’s story of what happened to trigger their negative emotions and how the situation worsened over time); 3) thoughts (appraisal process), emotions and behaviors (expressions) after the initial service failure and after the organization’s ineffective recovery efforts. These accounts served as confirmation of customer rage. Data were collected in Bangkok, Thailand and in two major east coast cities in the USA by local professional market research companies using self-administered questionnaires. To ensure meaning equivalence, the English-version questionnaire was translated into Thai and then back-translated into English. A convenience sample of consumers who had experienced a rage incident in the past 6 months made up the sample in each country. Sample 1 comprised 223 adult-American respondents and Sample 2, 212 adult-Thai respondents. A wide range of service organizations were represented including department stores, hotels, health care providers, utilities, and airlines. The mean age of the Thai sample is 31 years, with 51 percent female

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while the mean age of the US sample is 41 years, with 57 percent female. The two country samples were similar in terms of education with the US sample including 16.6 percent with high school only education and 69 percent with a college degree, compared to 14.6 percent and 74 percent in the Thai sample. Content analysis Data were analyzed using content analysis. Following standard content analysis procedures (Kassarjian 1977; Weber 1990), we first defined the unit of measurement as the critical incident (rage incident), classifying according to a priori categories derived from the literature and the exploratory indepth interviews. The coding scheme for cognitive appraisal was derived from previous work in psychology literature (e.g., Ellsworth and Smith 1988; Folkman et al. 1986), while the classification scheme of initial service failure and failed service recovery is based on Keaveney’s (1995) study. Consistent with Keaveney’s (and other service scholars e.g., Bitner, Booms, and Tetreault 1990; Kelley, Hoffman, and Davis 1993) categories, core service failure is defined as critical incidents due to mistakes or technical problems with the service itself (e.g., billing errors or mistakes). Unresponsive behavior included uncaring, unresponsive unknowledgeable employee behavior (“We went out to dinner. . . but the waitress did not care to serve us”). Inappropriate behavior included rude and impolite behaviors. Unethical behaviors included incidents that described illegal, immoral, unsafe or unhealthy behaviors, or behaviors that deviated from social norms (“The company lied to me about a program they offered”). The data were coded independently by three trained judges. Despite a priori classification scheme, judges were encouraged to develop new categories, as appropriate. This resulted in a “slow speed of service” category being included. Inter-judge reliability was 87 percent, exceeding the accepted benchmark of 80 percent (Latham and Saari 1984). Incidents that could not be resolved were given to a fourth judge, who made the final decision. Results Service failure types From the content analysis, we confirmed five main categories of failed service encounters and five fundamental human needs being threatened. The following sections discuss the categories of failed service encounters and threats to fundamental human needs. The total sample size in Episode 1 (n = 435) and Episode 2 (n = 415) is different because some respondents only reported rage incidents during initial service failure (Episode 1) and then the issue was either resolved or information was incomplete. The results in Table 1 show five main categories of initial service failure. The two largest categories are core service failure and employee unresponsive behavior, cited by 49.4 percent and 27.4 percent of respondents, respectively. For Table 2, there are only four main categories of ineffective service recovery (Episode 2). As expected, core service failure, which is the

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Table 1 Types of initial service failure (Episode 1). Types of initial service failure Core service failure Billing or system error Service mistake or outcome failure Employee unresponsive behavior Uncaring/ignorant Unresponsive Unknowledgeable Employee inappropriate behavior Rude/impolite Slow speed of service Slow service Long queue Transferring calls Employee unethical behavior Dishonesty Hard sell Others Total a ***

Total incidentsa

% of incidents

% of N (435)

% of total US (n = 223)

% of total Thai (n = 212)

Pearson Chi-square test

215

41.5

49.4

52.9

45.8

2.23

119

23

27.4

30.5

24.1

2.27

52

10.1

12.0

5.4

18.9

18.78***

15.3

18.2

17.5

18.9

0.14

9.9

11.7

12.6

10.9

0.31

0.2

0.0

0.47

N/A

79

51 1

0.2

517

100

Note: Number of incidents (517) exceeds the sample size (435) because multiple responses were allowed. p < 0.01.

biggest category of initial service failure, was present at Episode 1 but not present in Episode 2. All categories found in Episode 2 relate to employees’ behaviors and the two main categories are employee unresponsive behavior (55.2 percent) and employee inappropriate response (40.5 percent). We used a series of Chi-square tests to examine differences in (a) type of service failures (Table 1) and (b) reasons for ineffective recovery (Table 2) between US and Thai customers. The only statistically significant difference in Episode 1 is employee inappropriate behavior, and was reported higher among Thai (18.9 percent) than US customers (5.4 percent) (p < 0.01). In

Episode 2, more Thais (45.5 percent) reported experiencing inappropriate behavior to their complaints than did their US counterparts (35.4 percent) (p < 0.05). Further, 66 percent and 12.1 percent of US customers versus only 44.5 percent and 3.4 percent of Thais reported unresponsive employee behavior and unethical behavior, respectively (p < 0.01). Next, when comparing across the two episodes the largest change was for unresponsive behavior (e.g., failing to take responsibility, ignoring the complaint) which in the US sample increased from 30.5 percent to 66 percent and for Thais from 24.1 percent to 44.5 percent.

Table 2 Types of ineffective service recovery (after customer complaint, service employees response ineffectively) (Episode 2). Reasons for ineffective recovery Employee unresponsive behavior Ignoring customers’ complaints Not taking responsibility for the problem Unable to explain or find solution Employee inappropriate response Rude response Impolite manner Slow speed of recovery Telephone call continually transferred Customer must continue to wait for a solution Employee unethical response Dishonesty Hard sell Others Total a ** ***

Total incidentsa

% of incidents

% of N (415)

% of total US (n = 206)

% of total Thai (n = 209)

Pearson Chi-square

229

51

55.2

66.0

44.5

19.43***

168

37.5

40.5

35.4

45.5

4.32**

17

3.8

4.1

5.8

2.4

3.11

32

7.1

7.7

12.1

3.4

11.25***

0.5

0.9

N/A

2

0.6

448

100

0.5

Note: Number of incidents (448) exceeds the sample size (415) because multiple responses were allowed. p < 0.05. p < 0.01.

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3.4 29.2 54.6 8.1 3.8 19.9 20.4 56.3 32.0 2.9 478

100.0

11.6 24.8 55.4 20.0 3.4 10.0 21.5 48.1 17.4 2.9 48 103 230 83 14 28.8 14.6 40.1 8 17.9 47.5 6.3 50.7 9.4 5.4

Multiple responses allowed. *

198 Total

100.0

38.4 10.3 45.5 8.7 11.5

% of total Thai (n = 212) % of total US (n = 223) % of total % of total incidents*

33.6 9.0 39.8 7.6 10.0 167 45 198 38 50

Total incidents* Total incidents*

% of total incidents*

Ineffective service recovery (Episode 2)

Threats to control needs This category involved failed service situations which were often described by respondents as one in which they felt helpless or had no control over the situation. For example, a US female, 58 years old, had been charged incorrectly: “. . .I got several overdraft charges. . . . I told the bank [that this is incorrect] but they insisted on the charge and would not do anything. . . . (I felt) powerless. . .there was nothing I could do . . .” About 8.7 percent of respondents cited threats to a sense of control as at least part of the appraisal in Episode 1. This percentage increases dramatically to 20 percent in Episode 2.

Threats to . . .

Threats to justice (fairness) needs Threats to justice were reported by respondents as being cheated, having a dishonest relationship, or encountering a service provider who acted against social norms or was unable to perform as promised or expected. The narratives included statements like, “I paid . . . on eBay . . . and the guy never shipped [it]. . .. I felt cheated. . .” (US male, 29 years). Threat to a sense of justice was the largest category of cognitive appraisals in Episodes 1 and 2, mentioned by 45.5 percent and 55.4 percent, respectively.

Table 3 Cognitive appraisals of initial service failure (Episode 1) and ineffective service recovery (Episode 2).

Threats to self-esteem needs Threats to self-esteem needs category involved situations where customers felt that service providers treated them as being unimportant, showed disrespect, or humiliated them in public. For example, a Thai customer who was about to leave the store was stopped for a bag inspection commented “[the staff] found my sunscreen which he thought I had stolen from the shop. He started to talk to me in a loud voice and acted as if I was a thief. . . It was embarrassing. I felt disgraced. . .” (Thai, female, 33 years). In Episode 1, threat to self-esteem was cited by only 10.3 percent of respondents but in Episode 2 it was the second largest category, cited by 24.8 percent.

Initial service failure (Episode 1)

Threats to resources Threats to resources included customers’ concerns related to an unforeseen payment and/or an ineffective use of time. For example, a US female purchased a second-hand car from a dealer, but the car had to be repaired several times, and she commented, “. . .I was wasting my time. I had to go to the repair shop several times. . .” Threat to resources was the second largest category in Episode 1, mentioned by 38.4 percent of respondents, whereas it is the second smallest category in Episode 2, cited by only 11.6 percent of respondents.

% of total

% of total US (n = 206)

Five key themes relating to cognitive appraisal emerged from the content analysis confirming the a priori categorization. The results in Table 3 show the set of fundamental human needs violated during an initial service failure and ineffective service recovery.

Resources Self-esteem Justice (fairness) Need for control Physical well-being (safety)

% of total Thai (n = 209)

Cognitive appraisal process

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Threats to physical well-being or safety needs This category included a situation in which the customers express their concerns on safety issues related to their (or loved one’s) life, health, or general well-being. The following quote illustrates a violation of physical well-being. “. . . The bus driver drove dangerously. . . it was not safe. I was scared that the bus might crash” (Thai male, 25 years). Only 11.5 percent claimed that their physical well-being had been threatened in Episode 1 and the percentage declined considerably to 3.4 percent in Episode 2. Results of hypothesis testing Tables 4 and 5 summarize the results of hierarchical logistic regression models designed to test our hypotheses at Episode1 and Episode 2, respectively. The dichotomous dependent variable in each model is coded 1 in instances where one fundamental need is threatened (e.g., self-esteem). We excluded physical well-being/safety as a cognitive appraisal category from the analysis because it only occurs in a specific service context (e.g., hospital, public transportation) that was seen as a potential health hazard. In addition, (threat to) physical well-being was only mentioned by 11.5 percent in Episode 1 and 3.4 percent in Episode 2. Dummy variables were also used for each type of initial service failure and ineffective service recovery (1 = present, 0 = absent). In addition, country was coded as 1 for Thailand and 0 for the US. The control variables include demographics (age and gender) and criticality of transaction which was measured on a 5-point scale where 1 = “not at all important” and 5 = “very important”. Gender was coded as 1 for female and 0 for male. To further examine relationship patterns in the data, we tested whether there is any significant change in cognitive appraisals for a given type of failed service encounter with a change in country. In summary, each model in Tables 4 and 5 have large Chi-squared values and small p-values indicating good overall fit (Erramilli 1991) and all models are statistically significant. The results in Model 1 revealed that a perceived threat to resources is significantly associated with core service failure (b = 1.11, p ≤ 0.01). Hence, H1 is supported. For H2, we hypothesized that slow speed of service is positively associated with a threat to resources at Episodes 1 and 2. Our results (Models 1 and 5) only support H2 in Episode 1 but not in Episode 2. Model 1 shows that a perceived threat to resources is statistically significantly associated with (slow) speed of service (b = 1.39, p ≤ 0.01) only during an initial service failure. Turning to H3, the results from Model 5 show that a customer’s resource needs are significantly influenced by unresponsive behavior of the service provider (b = 1.31, p ≤ 0.01) at the recovery stage, thus supporting H3. Next, our results from Models 2 and 6 support H4b (but not H4a) in that a threat to self-esteem is influenced by inappropriate employee response to customer requests in Episode 1 (b = 5.13, p ≤ 0.01) and in Episode 2 (b = 2.38, p ≤ 0.01). However, H4a, which predicts a positive association between a threat to self-esteem and unresponsive employee behavior in both episodes, is not supported. Turning to H5a, Models 3 and 7 show that threats to justice needs are associated with employees’

unresponsive behavior at Episode 1 (b = 1.00, p ≤ 0.01) and at Episode 2 (b = 0.82, p ≤ 0.05). For H5b, Models 3 and 7 indicate that threats to justice needs are also associated with employees’ unethical behavior at Episode 1 (b = 2.66, p ≤ 0.01) and Episode 2 (b = 1.43, p ≤ 0.01). Thus, both H5a and H5b are supported. For H6, the results from Model 8 show that a need for control is likely to be under threat when an employee is unresponsive to customers’ complaints at Episode 2 (b = 1.09, p ≤ 0.01). Thus, H6 is supported. Concerning the cross-cultural hypotheses, the data in Tables 1 and 2 provide support for H7, that is, Eastern (Thai) customers were significantly (p < 0.05) more likely than their Western counterparts to view the failure as being due to inappropriate employee behavior. For H8, the data (Tables 1 and 2) show Western customers are more likely than Eastern customers to assess a failure as due to unresponsive employee behavior only at Episode 2 (US: 66.0 percent vs. TH: 44.5 percent, p < 0.01). Thus, H8 is partially supported. The results from Model 8 show that US customers (b = −1.29, p ≤ 0.01) are more likely than Thai customers to appraise an ineffective service recovery as a threat to their sense of control; thus H9 is supported. Finally, concerning H10, the results from Models 1 and 5 show that Western customers are more likely than Eastern customers to appraise an initial service failure and ineffective service recovery as a threat to their resources (b = −0.99, p ≤ 0.01; b = −1.73, p ≤ 0.01, respectively). The control variable, criticality of service transaction, was positively associated with a threat to justice (b = 0.29, p ≤ 0.01) and negatively associated with a threat to resources (b = −0.26, p ≤ 0.05). In other words, the greater the importance of the consumption occasion, the more likely that customers will appraise the initial failure as a threat to sense of justice but they are less likely to appraise the situation as a threat to resources. Interestingly in Episode 2, criticality in Model 5 has a significant positive relationship with a threat to resources (b = 0.40, p ≤ 0.05). The result suggests that when an organization fails to satisfactorily deal with a customer’s complaint, the greater the importance of that transaction, the more likely that the customer will appraise the ineffective recovery as a threat to their resources. For interaction terms, only the interaction of country with unresponsive employee behavior (Model 4) is significant (b = 1.51, p ≤ 0.05) in Episode 1. Thai customers are more likely than US customers to appraise unresponsive employee behavior as a threat to control needs. In Episode 2 (Model 5), the interaction of country with slow speed of service is significant (b = 3.04, p ≤ 0.05) suggesting that Thais are more likely than US customers to appraise slow speed of recovery as a threat to resources. A summary of hypotheses is provided in Table 6. Additional analysis and robustness checks To verify the results of the logistic regression analysis we ran a series of eight models using partial least squares (PLS) (see Appendix A). Given that our samples for the eight models range from 40 to 160, PLS is appropriate to verify parameter comparisons and minimize bias associated with dichotomous measures and non-normal distributions. Furthermore, we used a bootstrapping procedure to further assess the robustness of

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Table 4 Logistic regression estimation results (Episode 1: initial service failure). Independent variables

Initial service failure types Core service failure Unresponsive behavior Inappropriate behavior Slow speed of service Unethical behavior Country Control variables Criticality Age Gender Interaction variables Country × core service failure Country × unresponsive behavior Country × inappropriate behavior Country × speed of service Country × unethical behavior Model statistics χ2 (df) (sig) −2log likelihood Correct classification rate Correct classification by chance * ** ***

Dependent variables: cognitive appraisals (Threat to . . .) Model 1 Resources

Model 2 Self-esteem

Model 3 Justice (fairness)

Model 4 Control

1.11*** −0.98*** −1.51*** 1.39*** −0.77

−0.59 −0.59 5.13*** −2.62** 0.46

−0.36 1.00*** −0.95** −0.25 2.66***

−0.24 0.07 0.27 0.09 −1.69

−0.99***

−0.11

−0.21

−0.59

−0.26** 0.00 −0.28

−0.34* −0.05* −0.01

0.29*** −0.00 0.05

0.08 0.02 −0.53

ns ns ns ns ns

ns ns −1.33 ns ns

ns ns ns ns ns

ns 1.51** ns ns ns

114.58(9)*** 464.79 73.60% 52.70%

140.33 (10)*** 149.03 93.10% 81.45%

99.87(9)*** 499.66 71.50% 50.40%

19.35 (10)** 238.49 91.30% 84.05%

p ≤ 0.1. p ≤ 0.05. p ≤ 0.01.

Table 5 Logistic regression estimation results (Episode 2: ineffective service recovery following a customer complaint). Independent variables

Ineffective service recovery types Unresponsive behavior Inappropriate response Slow speed of service recovery Unethical response Country Control variables Criticality Age Gender Interaction variables Country × unresponsive behavior Country × inappropriate response Country × speed of recovery Country × unethical response Model statistics χ2 (df) (sig) −2log likelihood Correct classification rate Correct classification by chance ** ***

p ≤ 0.05. p ≤ 0.01.

Dependent variables: cognitive appraisals (threat, harm/loss to . . .) Model 5 Resource

Model 6 Self-esteem

Model 7 Justice (fairness)

Model 8 Control

1.31*** 0.52 0.78 0.76

−0.29 2.38*** 0.25 −0.14

0.82** −0.12 0.92 1.43***

1.09*** 0.28 0.23 0.53

−1.73***

0.03

0.01

−1.29***

0.40** 0.02 −0.70**

−0.21 −0.02 0.55

0.04 0.00 −0.18

0.25 0.01 −0.47

ns ns 3.04** ns

ns ns ns ns

0.69 ns ns ns

ns ns ns ns

57.13 (9)*** 240.17 88.20% 79.54%

109.75 (8)*** 355.34 80.20% 62.68%

45.42 (9)*** 525.00 66.30% 50.59%

56.79 (8)*** 358.54 80.00% 68.00%

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Table 6 Summary of hypotheses. Hypotheses

Results

H1: Core service failure at Episode 1 is positively associated with a threat to a customer’s resources. H2: Slow speed of service is positively associated with a threat to resources at Episodes 1 and 2. H3: Unresponsive employee behavior at the recovery stage (Episode 2) is positively associated with a threat to resources. H4a: Unresponsive employee behavior is positively associated with threats to customers’ self-esteem at both Episodes 1 and 2 H4b: Inappropriate employee behavior is positively associated with threats to customers’ self-esteem at both Episodes 1 and 2. H5a: Unresponsive employee behavior is positively associated with threats to justice in Episodes 1 and 2 H5b: Unethical employee behavior is positively associated with threats to justice in Episodes 1 and 2 H6: Unresponsive employee behavior at Episode 2 is positively associated with a threat to customers’ need for control. H7: Eastern customers are more likely than Western customers to appraise inappropriate behavior as a cause of service failure at Episodes 1 and 2. H8: Western customers are more likely than Eastern customers to appraise unresponsive behavior as a cause of service failure at Episodes 1 and 2. H9: Western customers are more likely than Eastern customers to appraise an ineffective service recovery as a threat to their sense of control. H10: Western customers are more likely than Eastern customers to appraise initial service failure as a threat to their resources.

Supported Partially supported (at Episode 1) Supported

Not supported

Supported

Supported

Supported

Supported

Supported

Partially supported (at Episode 2) Supported

Supported

the parameter estimates. The procedure provides an estimate of the shape, spread and bias of the sampling distribution of the parameter estimate. Bootstrap samples (5,000 samples in this case for each of the eight models) were created by randomly drawing cases with replacement from the original sample. The bootstrapping procedure confirmed the robustness of the parameter estimates in all eight models. For 64 of the 68 estimates for the main effect and control variables across the models, there was a very high degree of consistency in terms of whether a variable was statistically significant. For example, in Model 1 core service was statistically significant at p ≤ 0.01 in both the logistic and PLS models. Discussion This research is the first to explore the relationship between types of service failures and the customer’s cognitive appraisal that ultimately triggers rage incidents in both Western and Eastern contexts. Building on prior work the findings substantially expand our understanding of the cognitive appraisal process following an initial service failure coupled with ineffective service recovery. Our results provide interesting insights into what fundamental human needs are at risk when each type of

failed service encounter occurs. Furthermore, the results demonstrate that culture has an important influence on customers’ cognitive appraisal processes. The descriptive results in Tables 1 and 2 illustrate the types of failed service encounters that involve rage incidents at Episodes 1 and 2. In Episode 1, it is perhaps not surprising that core service failure was most prominent with 49.4 percent of respondents, while unresponsive employees was mentioned by 27.4 percent. At Episode 2, results indicate that how the service is delivered, particularly employees’ behavior (i.e., unresponsiveness, inappropriateness, unethical) is the main reason for customers to voice their concerns. Further, statistically significant differences were found across the countries with US customers reporting higher rates of unresponsive behavior (due to their higher service quality expectations), and Thais reporting higher rates of inappropriate responses (rude response, impolite manner, etc.) to their complaints. In the latter, the reason may be explained in part by the generally lower education levels of front-line employees and prominence of small business where consistent quality service is not a key priority in a developing economy. It can also be explained by Hofstede’s power distance dimension – i.e., power and influence are unequally shared in Eastern cultures and so customers of higher social status often demand higher than might be reasonably expected service levels of less powerful front-line service employees. Across the two episodes (Tables 1 and 2), there is a large increase in the number of reported failure incidents related to employee inappropriate behaviors (from 12 percent in Episode 1 to 40.5 percent in Episode 2). This may be due to poor service training with employees not being trained in how to respond appropriately to customer complaints. In addition, emotional contagion following the initial service failure might be another reason for the increase in the incident. Emotional contagion is a psychological phenomenon that occurs when one person tends to “catch” the emotions that another person displays in a social interaction (Hatfield, Cacioppo, and Rapson 1994). Dallimore, Sparks, and Butcher (2007) found that an angry expression by a customer can trigger the emotional contagion process in which the anger is transferred to the front-line employee, while more recently, Du, Fan, and Feng (2011) provided evidence of sequential occurrences of negative and positive emotional contagion in service recovery and failure episodes. Their results indicate that negative emotional displays lead to an increase in customers’ negative emotional states. Hence, when encountering an angry customer, it seems reasonable to expect that an employee might not respond to the customer in an appropriate manner, but instead respond with negative verbal or nonverbal expressions, or even ignore it. To avoid a ripple effect of emotion contagion, a manager or supervisor not directly involved in the original encounter should intervene. This finding also implies a challenge for service organizations to manage the standard of customer service and ensure that their employees, especially front-line employees, are aware of the impact of their actions which are seen and evaluated at every moment during service encounters. Service employees must demonstrate a high level of professionalism by being constantly attentive, and showing a

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willingness to assist customers, especially in a service recovery situation. Next, our results (Table 3) show five fundamental human needs – physical well-being (safety), self-esteem, resources, justice (fairness) and the need for control being threatened in rage incidents. In Episodes 1 and 2, customers mostly reported a threat to their sense of justice (45.5 percent and 55.4 percent, respectively) as a result of failed service encounters. Perhaps not a surprising result because a service failure that is perceived as a threat to justice frequently evokes more intense negative emotions than those that are not related to a sense of justice (Seiders and Berry 1998; Skarlicki, Folger, and Tesluk 1999). At Episode 1, threat to one’s resources was also prominent (38.4 percent of respondents), while at Episode 2 threats to self-esteem and a need for control were prominent (24.8 percent and 20 percent, respectively). However, perhaps the most interesting insights lie in the link between cognitive appraisals and types of failed service encounters. First, during Episode 1 customers appraise a threat to their resources when they experience a core service failure or they are forced to put up with slow speed of service. The result is consistent with Smith, Bolton, and Wagner’s (1999) study that showed that a core service failure could imply a potential loss of money and time (resources) because the service does not provide the basic outcome (e.g., a hotel room is unavailable due to overbooking). Customers perceived that they were wasting their time (another form of resource) when receiving slow service (such as a long wait in a queue or waiting due to multiple call transfers when dealing with a call center). Furthermore, we found that employees’ inappropriate manner, specifically an employee being rude or impolite, is likely to damage customers’ self-esteem in Episodes 1 and 2. This result is consistent with previous research showing the quality of customer-employee interaction, whether in a regular service encounter or service recovery situation, to be a key factor for customers’ sense of self-worth (Patterson et al. 2009). Third, in Episodes 1 and 2, unresponsive and unethical employee behaviors are positively associated with a threat to a sense of justice. Employees exhibiting responsive and ethical behavior are central to building customers’ perceptions of justice in the process of delivering the service or rectifying a problem (Folger and Bies 1989; Sparks and McColl-Kennedy 2001). However, when customers encounter employees whom they perceive intend to take advantage of them (e.g., deception, hidden agenda) and when there is a lack of accountability (e.g., denying responsibility, providing frequent service error), perceptions of injustice can arise (Seiders and Berry 1998). Our finding shows that a consequence of a perceived threat to one’s sense of fairness extends beyond cognitive evaluation to an extreme emotional and behavioral response, such as customer rage. Fourth, a threat to control is only associated with an unresponsive response in Episode 2 but not in Episode 1. This is perhaps not surprising because in Episode 1 many customers still believe that they can control the situation. They expect that an employee will take responsibility for the failure and fix the problem. However, when service employees deny their responsibility, offer no explanation of why the problem occurred or leave

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customers with no choice but the failure, having their sense of control threatened makes customers feel helpless in dealing with the organization. Such thoughts may the customer to express their rage in public. Furthermore, in a double deviation situation a customer is likely to experience strong negative emotions (Priluck and Lala 2009) and subsequently is likely to retaliate or demand reparation from the offending organization (Grégoire and Fisher 2008). Our results explain why customers respond more negatively and want compensation after an ineffective service recovery as their fundamental needs are repeatedly under threat. Cultural differences Cultural differences exist in the cognitive appraisal process. US customers are more likely than Thais to appraise an initial service failure as a threat to their resource needs. A threat to resources is reported more by US (Episode 1: 47.5 percent, Episode 2: 19.9 percent) than Thai customers (Episode 1: 28.8 percent, Episode 2: 3.4 percent) during an initial service failure and ineffective service recovery. Hofstede (1983) noted that a ‘masculine’ society such as the US tends to emphasize one’s performance, money (wealth), and achievement, whereas a ‘feminine’ society, such as Thailand, tends to put greater focus on relationships with other people rather than economic gain. Another difference between the two samples lies in the violation of physical well-being. From Table 3 (Episode 1), threat to physical well-being is more commonly reported by Thai consumers (17.9 percent) than US customers (5.4 percent). This result reflects the safety standard of service firms in both countries. Thailand is a developing country where the enforcement of consumer protection laws and regulations is much less effective than in the US. Hence, there is a higher probability that Thai customers will experience a service failure that poses a threat to their physical well-being, such as unhygienic food being served in restaurants or substandard mass transportation that could put their lives at risk. Next, US customers are more likely than Thais to appraise an ineffective service recovery as a threat to their sense of control. From Table 3, a violation of control was reported by 32 percent of US customers and only 8 percent of Thai customers during an ineffective service recovery. This difference may be explained by the individualist characteristic of US culture. An individualist society places more emphasis on autonomy with people encouraged to be independent and to pursue their own goals (Sastry and Ross 1998). Thus, US customers are likely to require a sense of control when something has gone wrong so that they can manage a solution to the problem. In contrast, Thais living in a high power distance and collectivist society (Hofstede 1983) tend to rely on service providers whose duty it is to solve the problem and hence they are less sensitive to a loss of control. Managerial implications Customer rage is a growing problem for retailers across the globe (Febrina 2009; Horovitz 2011). Our study provides the

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first insights into the back-story of customer rage, providing important directions to help firms prevent the onset of customer rage. As suggested by Smith, Bolton, and Wagner (1999), firms could provide an effective service recovery by offering a recovery that matches the customer’s psychological and economic loss in a service failure. For example, self-esteem could be enhanced by offering an apology and being courteous (e.g., sincerely listening to a customer’s problem and being supportive) (Smith, Bolton, and Wagner 1999; Goodwin 1988). In another example, offering a customer justification and referential explanations can help restore their sense of justice (Sparks and Fredline 2007). Customers’ psychological states or cognitive appraisal processes are not easily observable. However, by linking the type of failed encounters to customer threats to fundamental needs enables managers to implement strategies designed to mitigate customer rage and even prevent it. Indeed, the service failure types can be used as situational cues for front-line employees to be alert to potential damage to customers’ fundamental needs and helps identify how best to respond. For example, customers who complain about core service failure or slow speed of service tend to have the perception that their resources are under threat. Front-line employees could prevent customers’ emotions from escalating beyond surprise, embarrassment or disappointment to boiling point by quickly providing solutions to the problems or offering reasonable compensation. Future research First, while we focus on a set of fundamental needs that are at stake or threatened in rage incidents, it may be useful to examine customers’ emotional and behavioral reactions when these needs are enhanced. Identifying fundamental human needs that enhance positive consequences and prevent negative repercussions could be beneficial to front-line employees and firms. Second, it would be useful to study the relationships between types of failed service encounters, cognitive appraisal process, and service recovery strategies for low, moderate, and high intensity negative emotions. Such a comparison would provide service organizations with a more comprehensive understanding of which service recovery strategies would be suitable for different levels of customers’ negative emotions. Third, it would be interesting to explore possible contagion effects of negative emotional displays by employees on customers as well as the influence of negative emotional displays by other customers on customers present in the servicescape. In conclusion, we contend that firms cannot truly understand emotionally charged customer reactions such as customer rage unless they first consider customers’ fundamental psychological needs (e.g., resources, self-esteem, sense of justice, sense of control, and physical well-being). Front-line employees and their supervisors need to have a mindset that customers are first

and foremost people who seek fulfillment of a set of psychological needs from service encounters. This means that firms need to understand and avert the circumstances of failed service encounters that may trigger a violation of fundamental human needs. Learning from past experiences, paying attention to the service failure type, and responding quickly and effectively should prevent customers from experiencing rage and associated expressions and behaviors, and avoid potentially disastrous consequences for firms. Executive summary Customer rage is a growing problem for retailers across the globe. Increasingly, customers from both Eastern and Western cultures are expressing their rage. For example, witness the Chinese Lamborghini customer who was so furious about the service that he smashed his car in public, or the American customer whose request had been denied by a McDonald’s employee and who then expressed her rage by breaking the store window and trying to hit the employee. The phenomenon has caught the attention of the media with several national news programs running stories on customer rage and offering tips for dealing with it. We provide insights into customer rage incidents, specifically the back-stage of customer rage, that is, what is behind a rage episode in both Eastern (Thailand) and Western (US) cultures. We investigate what goes wrong during the incident both in terms of the initial service failure and failed recovery attempts, and the customers’ cognitive interpretations (cognitive appraisals) of the circumstances. Our study involves 435 adult customers’ actual rage incidents across a range of services including retailing, banking, restaurants, airlines, department stores, utilities, Telco and hotels. In our study, we found that common mistakes, such as core service failures or unresponsive employees, can potentially result in customers interpreting these service failures or ineffective service recovery as threats to their fundamental human needs (i.e., physical well-being, resources, self-esteem, sense of justice, and sense of control) and propelling them into rage. Further, we link service failure types (e.g., core service failure, employee inappropriate behavior, slow speed of service) to each of these fundamental human needs. Importantly, we highlight that service failure types can be used as situational cues for front-line employees to be alert to potential damage to the customer’s fundamental needs and thus assist front-line employees in identifying how best to respond, thus mitigating and even preventing the onset of customer rage. Acknowledgements The authors thank Dr Liem Viet Ngo for his kind assistance during the revision round and the anonymous JR reviewers for their constructive comments, which considerably improved the manuscript.

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Appendix A. Partial least square results for the theoretical models (Episode 1 and Episode 2)

Episode 1. Initial service failure types (Episode 1)

Core service failure Unresponsive behavior Inappropriate behavior Slow speed of service Unethical behavior Country Control variables Criticality Age Gender R2 ** ***

PLS (path weights) Model 1 (resources)

Model 2 (self-esteem)

Model 3 (justice)

Model 4 (control)

0.19*** −0.19*** −0.16*** −0.19*** −0.12** −0.19***

−0.08 −0.06 0.64*** −0.10*** −0.01 −0.05

−0.08 0.21*** −0.12*** −0.04 0.32*** −0.04

−0.04 0.11 0.01 0 −0.09 0.01

−0.1** 0.02 −0.05 0.23

−0.06 −0.06 −0.00 0.46

0.13*** −0.03 0.01 0.21

0.02 0.08 −0.07 0.03

t > 1.96. t > 2.58.

Episode 2. Ineffective service recovery types (Episode 2)

Unresponsive behavior Inappropriate response Slow speed of service recovery Unethical response Country Control variables Criticality Age Gender R2 ** ***

PLS (path weights) Model 5 (resources)

Model 6 (self-esteem)

0.14***

Model 7 (justice)

0.06 0.13 0.04 0.09

−0.05 0.45*** 0.01 −0.00 −0.00

−0.03 0.08 0.19*** 0.09

0.17*** 0.04 0.02 0.03 −0.21***

0.09*** −0.08 −0.16 0.12

−0.08 −0.07 0.09** 0.25

0.03 0.01 −0.05 0.1

0.09** 0.06 −0.08 0.13

0.28***

Model 8 (control)

t > 1.96. t > 2.58.

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