Betrayed by the favorite brand: rise and consequences of brand shame Open Access

Only very few long-term consumer–brand relationships exist without problems. Brand transgressions, which refer to a brand’s “violation of the implicit or explicit rules guiding relationship performance and evaluation” (Aaker et al., 2004, p. 2), are a tremendous threat to brands’ relationships with their customers. Examples of such incidents include the accidental erasure of products (Aaker et al., 2004), an unexpected price increase (Montgomery et al., 2018; Rotman et al., 2018), or offering products harmful for health (Khamitov et al., 2016). While brand transgressions come – as the examples illustrate – in all types and varying levels of intensity, they are all symbolic negative incidents, which have the potential to negatively impact customers’ experience (Khamitov et al., 2020), but also the nature of the relationship between customers and brands (Aaker et al., 2004). In this research, we aim to examine how feelings of brand shame and betrayal arising from transgressions of consumers’ favorite brands influence their desire for retaliation and negative word-of-mouth, thereby shedding light on the respective emotional mechanisms.

Yet, brand transgressions and consumers’ reactions to them have received quite some attention (Aaker et al., 2004; Davvetas et al., 2024; Montgomery et al., 2018). Recently, Khamitov et al. (2020) have reviewed the empirical literature on brand transgressions and conclude that these events have been shown to trigger a multitude of brand-adversarial cognitions (e.g. betrayal) and feelings (e.g. anger). However, behaviors (e.g. revenge) have been rarely examined (Khamitov et al., 2020). Most importantly, the literature on brand transgressions and consumer–brand relationships has scarcely researched transgressions of consumers’ favorite brands (Khamitov et al., 2020). These are consumers’ most beloved brands, which are typically preferred over other competing brands (Jain and Sharma, 2019). Consumers derive satisfaction through greater mental attachment to such brands (Arnould and Thompson, 2005; Johnson et al., 2011), which makes them develop strong, favorable relationships with them (Fournier and Avery, 2011).

The lack of research on favorite brands’ transgressions is surprising, as the negative consequences after such transgressions as compared to faults of ordinary brands can be even more extreme (Lisjak et al., 2012): The “dark side” of strong consumer–brand relationships has become a particular topic of interest in recent research (e.g. Japutra et al., 2022; Liao et al., 2020). Earlier findings in the brand transgression literature suggest that consumers in a strong – as compared to weak – relationship become more annoyed and more prone to show unfavorable consequences, even after relatively minor failures (Craighead et al., 2004; Li and Fumagalli, 2022; Riquelme et al., 2019). For consumers in a strong brand relationship, a problem with a service represents not only a bad consumption experience but is also evidence of the brand’s inability to further satisfy their inherent motives of self-enhancement (Hedrick et al., 2007). This is because when consumers’ sense of self intertwines with their favorite brand, negative events that happen with a brand take on a larger significance (Webster and Sundaram, 1998). Transgressions of consumers’ favorite brand convey a high level of symbolic meaning and harm the connected consumers’ self and can cause distress beyond the unpleasantness of an unsuccessful exchange process (Johnson et al., 2011; White and Argo, 2009). In such a situation, consumers are likely to feel remorse for having relied on the wrong favorite brand, which might lead to negative emotions, potentially stimulating customer retaliation and revenge. Still, only limited research has investigated the mental backgrounds of consumers’ extreme reactions to transgressions of their favorite brands.

While earlier transgression research has put much emphasis on explaining the well-established link between customer dissatisfaction and desire for retaliation, none of this research has recognized the potential important role of the concept of brand shame, which is likely to occur when consumers experience a transgression by their favorite brand. Brand shame is a negative affective reaction that typically arises after consumers have realized that they have chosen a faulty favorite brand, which makes them perceive their consumer-self as flawed or inferior (Weitzl et al., 2024). While the current literature on brand transgressions fails to acknowledge the existence and role of this concept for consumers, psychologists have long recognized the importance of shame for individuals following self-relevant problems (e.g. Blythin et al., 2020; Carden et al., 2018;). The objective of our research is to demonstrate the brand shame can be an important mediator between customers’ dissatisfaction and their desire to retaliate following a transgression of their favorite brand. Additionally, it should be shown why such transgressions make consumers feel brand shame. Specifically, this research strives to answer the following research question:

This research provides several theoretical contributions enriching the consumer–brand relationship literature, the betrayal literature and the shame literature. Specifically, while prior research has primarily examined dissatisfaction and anger as key emotional responses to brand transgressions, the present study contributes to a more nuanced understanding by foregrounding the role of shame, a deeply social and self-conscious emotion. By demonstrating that brand-induced shame – especially when experienced in the context of favorite brands – can lead to retaliatory behaviors and negative word-of-mouth, this research extends the emotional landscape considered in consumer behavior. Furthermore, by linking shame to perceived betrayal, our findings provide a theoretically grounded mechanism through which strong brand attachments can backfire. This insight not only fills a critical gap in the literature, but also offers a novel perspective on how emotional investments in brands may amplify negative reactions when expectations are violated. Thus, the study moves the field forward by highlighting the double-edged nature of brand love and offering implications for managing consumer trust and recovery strategies in times of brand crisis. In addition, this research furnishes practitioners with four managerial implications on how to act after customers experience a small, symbolic transgression of their favorite brand. First, marketers should realize that such a transgression can have a devastating impact on customer–brand relationships. Second, ideally, brands should strive to avoid brand transgressions. Third, if brand transgressions occur, marketers should try to reduce dissatisfied customers’ perception of brand betrayal and brand shame. Finally, marketers should provide customers with alternative ways to express their detrimental statements after brand transgressions.

The remainder of this article is structured as follows. First, we present the theoretical background of our research and outline our guiding hypotheses, which are summarized in a conceptual model. Next, we describe the methodological approach and report the findings from two empirical studies – Study 1 (an online survey) and Study 2 (a scenario-based online experiment) – both of which support our theoretical assumptions. Finally, we discuss the results, outline implications for both scholars and practitioners and suggest directions for future research.

There is a growing interest in empirically studying consumers’ reactions after transgressions involving a favorite brand. By reviewing these studies, one can identify the central elements responsible for extreme consumer reactions after such negative incidents (see Table 1).

Four central elements have repeatedly drawn scholars’ attention: negative emotions, brand betrayal, brand retaliation and negative word-of-mouth. First, quite a few of those studies examined a variety of consumers’ emotions, including the outward-directed feelings of anger and hate (e.g. Japutra et al., 2021), but only Weitzl et al. (2024) examined brand shame, an inward-directed affective reaction hardly associated with extreme consumer reactions in earlier consumer research. They show that brand shame can cause strongly connected consumers’ anger. It is speculated that a single, self-relevant, symbolic brand transgression in which the performance of a brand falls below a customer’s consumption expectations (e.g. dissatisfying service quality) can ultimately result in a perceived threat for a customer’s identity (Wolter et al., 2019). This threat should trigger shame. While earlier research repeatedly demonstrated that inward negative emotions (e.g. guilt, embarrassment) often have a mitigating effect on consumer vengeance (Soscia, 2007; Wu and Mattila, 2013), we argue that after transgressions involving a favorite brand, rising brand shame makes consumers retaliate.

Second, only two papers (Jabeen et al., 2022; Jain and Sharma, 2019) examined brand betrayal, although the majority of empirical studies on brand transgression examine relational mediators (Khamitov et al., 2020). While existing research shows betrayal’s important role in unfavorable consumer reactions following major negative incidents (e.g. service failures) (Grégoire and Fisher, 2006, 2008), its role in minor brand transgressions – of rather small objective failure size but of large subjective symbolism – remains unclear. Specifically, no research has so far investigated the rise of perceived brand betrayal following minor transgressions involving consumers’ favorite brand as well as its role as a determinant of consumers’ shame.

Third, only a few studies examined retaliation (e.g. Japutra et al., 2021), and so far, only hate, dissatisfaction and anxiety have been studied as affective drivers of retaliation (e.g. Sarkar et al., 2021). Thus, no study has considered brand shame as an antecedent of consumers’ desire for retaliation after a minor brand transgression involving a favorite brand. Fourth, negative word of mouth (NWOM) is only studied by Weitzl et al. (2024). This is surprising, given that spreading NWOM is a very common way that consumers retaliate (Grégoire and Fisher, 2008; Riquelme et al., 2019), which strongly damages the involved brand’s reputation (Grégoire and Fisher, 2008; Wangenheim, 2005).

To completely understand the role of the outlined constructs in situations following a brand transgression, we develop a conceptual model (see Figure 1), of which we discuss the key concepts and their relationships in the following.

Customer dissatisfaction. According to the expectancy-disconfirmation model (Oliver, 1977), a person’s (dis)satisfaction originates from a subjective comparison of a referent (i.e. a previously constructed expectation) and the perceived performance. More specifically, dissatisfaction is created if prior expectations fall below the actual post-purchase outcomes (Ferguson and Johnston, 2011). Another stream of research (e.g. Shaver et al., 1987) states that dissatisfaction should not be conceptualized as a result of a cognitive judgment process but as a distress emotion. According to this view, dissatisfaction arises as a relatively undifferentiated negative emotion, stemming from unpleasant events that obstruct involved persons’ goals or needs (Li and Stacks, 2017).

In this research, we follow this perspective and refer to customer dissatisfaction as the transient negative feeling that customers experience after a self-relevant, symbolic transgression involving a favorite brand when personal expectations – which tend to be higher among consumers of favorite brands (Wolter et al., 2019) – remain unmet (Weitzl et al., 2024). Extant literature on the consumption of favorite and other brands (e.g. Bougie et al., 2003; Sánchez-García and Currás-Pérez, 2011) consistently demonstrates that consumers are typically dissatisfied following unexpected performance problems.

Desire for retaliation. Negative experiences make consumers develop an urge to punish the brand in some way (Funches et al., 2009). Punitive actions are multifaceted and can include behaviors such as boycotting, signing an online petition or sabotage (Fetscherin, 2019). While some scholars treat these concepts as interchangeable, there exists some evidence that indirect (e.g. switching the service provider) and direct manifestations of aggression (e.g. brand retaliation, brand revenge) are different behavioral constructs (Valor et al., 2022; Zarantonello et al., 2016) with different meanings, antecedents and consequences. Grégoire et al. (2010), among others, acknowledge that dissatisfied customers can fight back and take direct actions against the brand involved.

According to Zourrig et al. (2009), two main forms of direct vengeance exist, which they believe to be different in terms of rationality, effects and behavior: retaliation and revenge. The former relates more to short-term actions, while revenge is a mental state to harm the opponent (e.g. brand) in the long run (Fetscherin, 2019). Retaliation is fueled by consumers’ dissatisfaction arising after mistakes are made or promises are not kept by another party (Funches et al., 2009). It is often defined as consumers’ actions and efforts to punish and cause inconvenience to a brand as a response to the damage it has caused them (Bechwati and Morrin, 2003; Grégoire and Fisher, 2008; Riquelme et al., 2019). This research follows Thomson et al.’s (2012) view by conceptualizing brand retaliation as acute and intentionally destructive behaviors directed toward a specific brand and the desire for retaliation as dissatisfied customers’ impulsive willingness to execute such actions (Weitzl and Hutzinger, 2019).

Effect of customer dissatisfaction on desire for retaliation. After negative, dissatisfying experiences, consumers can desire retaliation to restore fairness (Beugré, 2005; Funches et al., 2009) or to get even with a brand (Bechwati and Morrin, 2003). Retaliation is based on equity theory, where the restoration of justice rather than the long-term harm of the brand is viewed as consumers’ main goal (Kähr et al., 2016). It gives avengers relief from being treated unfairly (Bechwati and Morrin, 2003; Zourrig et al., 2009) and is motivated by the desire to (temporarily) “bring down” a brand. Consequently, retaliation has a strong impulsive, punitive nature and is a direct outcome of unfair situations (Grégoire and Fisher, 2008). Retaliation is known to be a likely outcome of the unpleasant, negative feeling harbored by customers – such as dissatisfaction (Grégoire et al., 2009; Marticotte et al., 2016) with which they need to cope (Jabeen et al., 2022). Desiring retaliation is an active, emotional coping strategy regularly used by individuals to reduce distress and restore a sense of justice (Bechwati and Morrin, 2003; Bonifield and Cole, 2007; Grégoire et al., 2009; Weitzl and Hutzinger, 2019). Based on these arguments and earlier findings on consumer reactions to transgressions involving a favorite brand (Sarkar et al., 2021), we hypothesize the following:

Negative word-of-mouth. According to Huefner and Hunt (2000), six different actions allow consumers to retaliate following a dissatisfying experience: cost/loss, vandalism, trashing, stealing, personal attack and voicing negative word-of-mouth (NWOM). Spreading NWOM is a very common way that consumers retaliate (Grégoire and Fisher, 2008; Hibbard et al., 2001; Huefner and Hunt, 2000; Riquelme et al., 2019). When consumers share their poor experiences, unfavorable opinions and negative feelings with others, they hope to damage the involved brand’s reputation and encourage other shoppers to not patronize it (Grégoire and Fisher, 2008; Wangenheim, 2005).

This kind of punishment can be executed in private (e.g. by informing friends) or in public when the dissatisfied customers use, for example, social media (e.g. review website, discussion forum) or contact a third party to publish statements about their negative experience to reach a larger audience. Scholars agree that this public form of retaliation particularly deserves research’s attention, as it can be responsible for far-reaching damaging consequences for the criticized brand (e.g. decreased sales) (Khamitov et al., 2019; Weitzl and Einwiller, 2020).

Effect of desire for retaliation on negative word-of-mouth. Existing literature consistently suggests a strong relationship between consumers’ desire for retaliation and their willingness to voice NWOM (see Valor et al. (2022) for a review). For the sake of completeness concerning brand transgression-induced negative reactions, it is argued that among dissatisfied consumers the more general desire to retaliate transforms into a more specific intention to engage in public and private NWOM. Consequently:

This research elaborates on the well-acknowledged link between dissatisfaction and desire for retaliation by investigating the interplay of brand betrayal and brand shame as sequential mediators of this effect. One benefit of this approach is that it allows the assessment of the extent to which the dissatisfaction effect triggers inward emotions (such as shame) and not only negative outward emotions (such as anger), which have already received notable attention in extant research (e.g. Sánchez-García and Currás-Pérez, 2011).

Brand betrayal.Grégoire and Fisher (2008, p. 250) conceptualize perceived betrayal as “a customer’s belief that a firm has intentionally violated what is normative in the context of their relationship.” Consumers can feel betrayed when a brand lacks the ability to complete a psychological contract and hence violates relational rules. Furthermore, betrayal exists when companies undermine consumer trust by deceiving and lying (Lee et al., 2021). In both situations, betrayal arises as individuals have the perception that the relationship partner has engaged in egregious actions (Moors, 2010). This perception has negative effects on consumers’ attitudes, trust and purchase intention (Lee et al., 2013). Furthermore, perceived betrayal is linked to strong negative emotions such as outward-directed anger (Leonidou et al., 2018) and inward-directed regret (Sameeni et al., 2022).

It is shown that when consumers’ expectations about their favorite brands remain unmet, brands are viewed as guilty of transgressing agreed exchange rules, triggering feelings of betrayal (MacInnis and Folkes, 2017; Reimann et al., 2018). Earlier, brand betrayal was conceptualized as an unpleasant emotion evoked by a moral or ethical violation on behalf of the brand to which the individual has a strong connection (Reinikainen et al., 2021; Tan et al., 2021). In this research, we define brand betrayal as consumers’ perception that the favorite brand is not able to keep its promises to them, which creates conflicts in the relational exchange between them and the brand.

Effect of customer dissatisfaction on brand betrayal. Dissatisfaction and brand betrayal are both related to relational norm violations that elicit feelings of emotional distress (Boekhout et al., 1999). However, extant contributions in psychology (e.g. Boekhout et al., 1999) and organizational behavior (e.g. Caldwell et al., 2009) have demonstrated that betrayal is distinct from dissatisfaction, as betrayal is, for example, more associated with stronger negative emotions such as anger (Leonidou et al., 2018). With respect to consumer–brand relationships, both dissatisfaction and brand betrayal may result in the desire for revenge and retaliation (Grégoire and Fisher, 2008; Grégoire et al., 2009).

Other research suggests that the two concepts are causally related: A brand with a fallacious character (i.e. faulty, misleading), which dissatisfies loyal customers, is likely to evoke a feeling of betrayal. This aligns with the appraisal theory of emotions (Lazarus, 1991), according to which individuals appraise an event rather unconsciously as favorable or unfavorable for the achievement of their goal. In the case of a negative incident, this primary appraisal typically results in unspecific emotional reactions such as dissatisfaction. The secondary appraisal tends to lead to more specific emotions (Lazarus, 1991). These appraisals are not only driven by the circumstances of a specific situation (e.g. who is to blame) but also, for instance, by consumers’ relationship with the focal brand. When consumers have chosen a favorite brand, they regard it as a trusted partner with which they have a strong relationship (Fournier and Alvarez, 2012). Following a symbol-laden brand transgression, bonded consumers are inclined to automatically blame their favorite brand for causing the problem and exploiting their loyalty (Weitzl et al., 2024), which leads to the feeling that it had deliberately let them down.

In exchange relationships, betrayal arises from a brand’s inability to provide products or services adequate to the paid price (Aggarwal, 2004). In communal relationships, however, betrayal develops because of consumers’ perception of a brand’s lack of ability to complete a psychological contract and violation of relationship norms, such as that loyal consumers are better served than others (Aggarwal, 2004). A favorite brand that breaches the psychological contract by transgressing is regarded as undermining the trust of its most loyal customers by deceiving and lying (Su et al., 2022). This creates a perception of egregiousness and a sense of betrayal (Grégoire and Fisher, 2008; Tsai et al., 2014). Therefore:

Brand shame. Shame is an inward negative specific emotion that results from a particular moral transgression (Chun et al., 2007). More specifically, it refers to an affective response based on individuals’ evaluation when they perceive themselves as having failed to achieve certain personal standards, goals, or moral values (Sabini et al., 2001). Such negative judgments are undesirable and global, as the entire (consumer-) self is regarded as being inherently flawed, inadequate, or insufficient (Blythin et al., 2020; Carden et al., 2018; Chrdileli and Kasser, 2018; Tracy and Robins, 2004). Shame is a debilitating experience, which arises when individuals perceive that their flaws are exposed to themselves (i.e. internalized shame) or to others (i.e. external shame) (Miller and Tangney, 1994). When speaking of brand shame, this research refers to the former. It is an emotion arising when consumers feel that their consumer-self is flawed or inferior because of preferring a faulty favorite brand, with which the consumer strongly identified himself/herself. This conceptualization aligns with the literature’s current understanding (Weitzl et al., 2024).

Rise of brand shame. The feeling of betrayal can not only lead to strong negative outward emotions such as brand hate (Bayarassou et al., 2021) but is also theorized to cause the inward emotion of brand shame (Sugathan et al., 2017; Weitzl et al., 2024). Consumers have an urge to regard themselves as having desired abilities, such as being competent, skilled and informed individuals who choose the right favorite brand (Dunn and Dahl, 2012). However, a symbolic transgression involving their favorite brand may make individuals question their abilities as “good decision-makers”. A betrayal experience can make consumers feel negative self-worth (Reimann et al., 2018) because they question their wisdom in investing in a self-relevant relationship with a brand that has now let them down (Tan et al., 2021). Such an event elicits feelings typical of shame, such as parting from personal or social norms and rules and having a strong feeling of being close to the undesired and unattractive self (e.g. being an exploited customer).

Accordingly, this research argues that consumers can experience brand shame after a self-relevant, symbolic transgression involving their favorite brand. Brand shame arises when consumers feel that their consumer-self is flawed or inferior because of being linked to a faulty or betraying brand. We propose that this negative feeling stems from consumers’ strong belief that they have been misguided in the past and have chosen the wrong brand, which has finally turned out to be incongruent with their self-concept and values, as demonstrated by a breach of the relational contract. Thus, brand shame develops when consumers experience a personal selection failure and regard their entire self as responsible for their flaw in ongoingly choosing a brand that – now surprisingly – countervails their personal norms and self-goals (Tangney and Fischer, 1995).

Consequence of brand shame. Feeling ashamed is considered a dissonance reaction (Lazarus, 1991). We know from psychological research that individuals have a strong urge to resolve both inconsistent cognitions (Festinger, 1962) and feelings of unease that occur when an emotion is evaluated as dissonant with respect to one’s identity concerns (Jansz and Timmers, 2002). Dissonance theorists (e.g. Abraham, 1998) suggest that as soon as the dissonance is manifest, individuals have to cope with unpleasant emotions to regain a comfortable mental state.

When previously loyal consumers are dissatisfied, they experience shame. They must overcome this inconvenient feeling by applying forms of self-affirmation to restore the disordered self-concept, and they are mentally urged to engage in patterns that help to achieve this goal (Cheng et al., 2012). In the case of a brand transgression, the externalization of blame (i.e. “It is not me who is responsible for this situation, but the brand.”) is one likely strategy to overcome the situational imbalance of the self. Blaming others for a problem instead of the self can have an ego-protective function (Tangney and Dearing, 2002). Consequently, one can argue that consumers who experience brand shame are likely to make the involved brand responsible for their inability to achieve their personal goals. In other words, these individuals tend to externalize inward-directed shame to overcome their cognitive dissonance and to restore self-worth (Tan et al., 2021). Even when such consumers know that their blame appraisal is irrational and unjust, they are likely to develop aggression toward others (e.g. Heaven et al., 2010), which can be expressed by their desire to retaliate against their involved favorite brand. Therefore, we propose the following direct and mediation effect:

To test of our research hypotheses, we collected empirical data by means of an online survey (Study 1) and – to cross-validate our findings and reduce methodological biases – an online experiment (Study 2).

Data were collected from a sample of 627 adult consumers (64% female; M_age = 28.4, SD_age = 9.4) by means of convenience sampling with a snowball technique via social media. Specifically, 15 students from a marketing research class recruited participants via various social media channels (Facebook, etc.), asking them to participate in an unspecified consumer study and to share this invitation with their friends and acquaintances online. The research instrument was a stimulus-based online survey. The research methodology was adopted from Davvetas and Diamantopoulos (2017) as well as Weitzl et al. (2024). Data collection took place in Central Europe, with most participants being from Austria (23%), followed by Germany and Slovakia (9% each). Many participants held a bachelor’s degree (48%) and were employed (43%). Overall, the original sample size was 685 participants, which was reduced because of data cleansing (e.g. identifying biased response patterns, satisficing and language proficiency) to obtain the final sample that was then used for hypotheses testing.

The survey (conducted in English) included three sections. In Section 1, participants were asked to mention their favorite brand in a product category, which they could freely select. No product category was specified beforehand to ensure adequate variation in both brands and products as well as to allow impulsive reactions. Finally, over 150 different brands in 90 product categories (including technology, fashion, cars, food, personal care products, etc.) were mentioned. Here, the most popular brand was Apple, but it only accounted for just 15% of all responses. Following mentioning their favorite brand, participants completed some questions pertaining to their pre-incident relationship with it (e.g. relationship length and quality).

In Section 2 of the questionnaire, a short scenario was presented. Here, the respondents were asked to imagine that they had recently bought their favorite brand. However, soon after their purchase, they realized that the purchased brand was a performance-wise worse choice as compared to another branded competitor (see  Appendix 1 for the scenario). Because of this procedure, all respondents experienced a comparable transgression of their favorite brand. Once the participants had read the scenario, they completed the last part of the questionnaire, which included measures taken from established academic research for this study’s key constructs, including dissatisfaction (DIS), brand betrayal (BET), brand shame (SHA), desire for retaliation (RET) and negative word-of-mouth (NWOM), as well as additional measures, including, among others, two items assessing the scenario believability (“The scenario was realistic.”; “I could easily put myself in the situation described in the scenario”). The additional items were used to distract the participants to safeguard this research against a potential common method bias (CMB). The sequence of all items was randomized. They were measured on seven-point scales (ranging from 1 = “I totally disagree” to 7 = “I totally agree”) using reflective indicators. Finally, respondents were asked to answer standard demographic questions.

A confirmatory factor analysis (CFA) was used to assess and demonstrate the appropriate psychometric properties of all included latent variables’ measures ( Appendix 2 provides the details of this assessment, while  Appendix 3 shows the means, standard deviations of the constructs and correlations among the variables). Discriminant validity for all constructs was established as demonstrated by average variance extracted (AVE) values exceeding corresponding squared correlations for all construct pairs (Fornell and Larcker, 1981) and significant chi-square difference tests for all construct pairs following the method by Anderson and Gerbing (1988) (see  Appendix 4). To ensure that CMB is not a major concern, this research took methodological countermeasures (e.g. enhancing participants’ general motivation through careful instructions and minimizing the repetitiveness of scales) and ensured its negligible influence empirically (see  Appendix 5 for details). To evaluate potential non-response bias, the extrapolation approach recommended by Armstrong and Overton (1977) was used. Here, the comparison of early and late responses to measurement items revealed homogeneous patterns, providing evidence that non-response bias was minimal.

Before assessing the research hypotheses, empirical realism (i.e. the extent to which the respondents regard a transgression of their favorite brand as imaginable) was evaluated by testing the plausibility of the presented scenario. Insights suggested that the participants could put themselves in the situation described in the scenario, as the mean score of the two combined check variables (r = 0.69, p < 0.001) was significantly higher than the scale’s midpoint (M = 4.16, SD = 1.73, t = 60.4, p < 0.001). By applying a similar approach, one could also show that the participants have correctly chosen a self-relevant favorite brand. Here, the mean score of a measure for the social benefits provided earlier by the favorite brand (four items from Grégoire et al., 2009; α = 0.815) was significantly higher than the scale’s midpoint (M = 4.47, SD = 1.39, t = 80.7, p < 0.001). This meant that prior to the brand transgression, the participants felt that they were important to and appreciated by their chosen favorite brand, which describes a relational consumer–brand relationship.

Testing the effect of customer dissatisfaction on desire for retaliation (H1) and the effect of desire for retaliation on negative word-of-mouth (H2). A structural model mirroring the conceptual model (see Figure 1) and including two control variables was estimated. In addition to the key constructs, the length of the consumer–brand relationship and the quality of this relationship before the brand transgression happened (assessed via earlier consumer–brand identification; Stokburger-Sauer et al., 2012) were included as control variables to rule out influences of the earlier customer–brand relationship (Hutzinger and Weitzl, 2023). The estimated model fitted the data well (χ² = 179.07, df = 63, RMSEA = 0.054, CFI = 0.980, SRMR = 0.040). Identified individual path coefficients corroborated the findings of earlier dissatisfaction research. More specifically, DIS had a strong positive effect on RET (β = 0.243, β_s = 0.255, p < 0.001), while RET had a strong positive impact on NWOM (β = 1.120, β_s = 0.844, p < 0.001). Thus, H1 and H2 were both supported. This led to a significant positive indirect effect of DIS on NWOM through RET (β_{DIS → RET → NWOM} = 0.503, p < 0.001), providing support for the existence of dissatisfaction-induced revenge reactions.

Testing the effect of customer dissatisfaction on desire for retaliation via brand betrayal and brand shame (H3, H4a, H4b and H5). Furthermore, the results supported the role of betrayal and brand shame as two sequential mediators of the DIS → RET effect. More specifically, the data supported the hypothesized positive link between DIS and BET (H3) (β = 0.879, β_s = 0.848, p < 0.001, R² = 0.894). Second, the data showed a significant positive effect of BET on SHA (β = 0.757, β_s = 0.863, p < 0.001, R² = 0.739), which, in turn, had a positive impact on RET (β = 0.278, β_s = 0.350, p < 0.001). Further tests revealed that BET had no direct impact on RET (β = 0.182, β_s = 0.254, p = 0.106), showing that SHA fully mediates between these two variables – supporting H4a and H4b. There was a significant positive indirect effect of DIS on RET via BET and SHA (β_{DIS → BET → SHA → RET} = 0.542, p < 0.001), supporting a sequential mediation. However, there was a significant positive impact of DIS on SHA (β = 0.433, β_s = 0.479, p < 0.001), implying that BET only partially mediates this relationship. This supported H5. An overview of the model estimation results is presented in Table 2.

Data was collected from a sample of 603 adult consumers (53% female; M_age = 30.0, SD_age = 12.8) by means of convenience sampling with a snowball technique via social media. A similar sampling approach to that used in the first study was used, with five other students sharing the invitation to participate with their diverse peers via their personal social media profiles. The research instrument was a stimulus-based online experiment. Most participants were from Austria (94%), followed by Germany (4%). A total of 34% of the participants held a bachelor’s or master’s degree, and 59% of the participants were employed. Overall, the original sample size was 714 participants, which was reduced through data cleansing (e.g. identifying biased response patterns and satisficing) to obtain the final sample that was then used for hypotheses testing.

The survey included three sections. In Section 1, participants were asked to indicate their favorite smartphone brand. Apple was mentioned most often and accounted for 74% of all responses. Following indicating their favorite smartphone brand, participants completed some questions pertaining to their pre-incident relationship with it (e.g. relationship length and quality). In Section 2 of the questionnaire, a short scenario was presented. In a between-subjects design, dissatisfaction (DIS; low dissatisfaction vs high dissatisfaction) with the participants’ favorite smartphone brand was manipulated. Participants were randomly assigned to either the low dissatisfaction condition (n = 296; 54% female; M_age = 30.1, SD_age = 12.9) or the high dissatisfaction condition (n = 307; 53% female; M_age = 30.0, SD_age = 12.8). In the low dissatisfaction condition, the ordered smartphone has been delivered in time for the birthday of the participants’ partner and thus represents no brand transgression. In the high dissatisfaction condition, the ordered smartphone has – although promised differently – not been delivered in time for the birthday of the participants’ partner and thus represents a brand transgression (see  Appendix 6 for the manipulation description).

Once the participants had read the scenario, they completed the last part of the questionnaire, which included measures taken from established academic research for the key constructs, including brand betrayal (BET), brand shame (SHA), desire for retaliation (RET), negative word-of-mouth (NWOM) and additional measures, including two items capturing scenario believability. The sequence of all items was randomized. They were measured on seven-point scales (ranging from 1 = “I totally disagree” to 7 = “I totally agree”) using reflective indicators. Similar to Study 1, respondents also provided standard demographics.

Again, a CFA was used to assess and demonstrate the appropriate psychometric properties of all included latent variables’ measures ( Appendix 7 provides the details of this assessment, while  Appendix 8 shows the means, standard deviations of the constructs and correlations among the variables).

Empirical realism. Before assessing the research hypotheses, empirical realism (i.e. the extent to which the respondents regard the described situation with their favorite brand as imaginable) was evaluated by testing the plausibility of the presented scenario. Insights suggested that the participants could put themselves in the situation described in the scenario, as the mean score of the two combined check variables (r = 0.65, p < 0.001) was significantly higher than the scale’s midpoint (M = 4.49, SD = 1.78, t = 6.7, p < 0.001). By applying a similar approach, one could also show that the participants have correctly chosen a self-relevant favorite brand. Here, the social benefits provided earlier by the brand [measured with a single item from Grégoire et al. (2009)] were significantly higher than the scale’s midpoint (M = 4.28, SD = 1.81, t = 3.8, p < 0.001). This meant that prior to the brand transgression, the participants felt that they were important for and appreciated by the chosen brand, which describes a relational consumer–brand relationship.

Manipulation check. To test whether our manipulation of dissatisfaction was successful, we ran an independent samples t-test comparing the two experimental groups with regard to dissatisfaction (three items adapted from Zarantonello et al. (2016), e.g. “I am disappointed because of buying this smartphone brand.”; α = 0.876). The results revealed that our manipulation was successful because participants in the high dissatisfaction condition (M_highDIS = 3.06; SD_highDIS = 1.75) were significantly more dissatisfied than participants in the low dissatisfaction condition (M_lowDIS = 1.56; SD_lowDIS = 0.99; t = 12.81; p < 0.001).

Checks of brand transgression-induced changes in the relationship. Furthermore, participants in the high dissatisfaction condition experienced significantly higher brand transgression severity (three items adapted from Hess et al. (2003), e.g. “For me, the situation is a minor (=1) – major (=7) problem”; α = 0.923; M_highDIS = 3.92; SD_highDIS = 1.72 vs M_lowDIS = 2.27; SD_lowDIS = 1.49; t = 12.53; p < 0.001), lower customer brand trust (four items adapted from Grégoire et al. (2009), e.g. “My favorite smartphone brand is very undependable (=1) – very dependable (=7)”; α = 0.946; M_highDIS = 4.62; SD_highDIS = 1.67 vs M_lowDIS = 5.80; SD_lowDIS = 1.25; t = −9.78; p < 0.001), and lower customer personality-brand fit (four items adapted from Knop (2022), e.g. “After the described situation, the values that my favorite smartphone brand represent are consistent with my personal values”; α = 0.928; M_highDIS = 3.60; SD_highDIS = 1.58 vs M_lowDIS = 4.17; SD_lowDIS = 1.71; t = −4.24; p < 0.001), than participants in the low dissatisfaction condition.

Testing the effect of customer dissatisfaction on desire for retaliation (H1) and the effect of desire for retaliation on negative word-of-mouth (H2). For assessing H1 and H2, we ran a mediation analysis with DIS (1 = low dissatisfaction; 2 = high dissatisfaction) as the independent variable, RET as mediator and NWOM as the dependent variable. The results revealed that DIS had a significant positive effect on RET (β = 0.257, βs = 0.199, p < 0.05), which supported H1. Furthermore, RET had a significant positive effect on NWOM (β = 0.898, βs = 0.712, p < 0.001). Thus, H2 was supported. This led to a significant positive indirect effect of DIS on NWOM via RET (β_{DIS → RET → NWOM} = 0.230, p < 0.05).

Testing the effect of customer dissatisfaction on desire for retaliation via brand betrayal and brand shame (H3, H4a, H4b and H5). A structural model mirroring the conceptual model (see Figure 1) and – as in Study 1 – including the two control variables, length of the consumer–brand relationship and prior relationship quality, was then estimated. The model fitted the data well (χ² = 221.64, df = 89, RMSEA = 0.050, CFI = 0.977, SRMR = 0.041). The results revealed that DIS had no direct effect on RET (β = −0.073, β_s = −0.034, p = 0.376) when introducing the mediators. The data supported the hypothesized positive link between DIS and BET (H3) (β = 1.554, β_s = 0.461, p < 0.001). In addition, the data showed a significant positive effect of BET on SHA (β = 0.503, β_s = 0.849, p < 0.001), which is in line with H4a. Furthermore, there was a positive impact of SHA on RET (β = 0.660, β_s = 0.616, p < 0.001). Thus, H4b was supported. Similar to Study 1, there was a significant positive indirect effect of DIS on RET via BET and SHA (β_{DIS → BET → SHA → RET} = 0.516, p < 0.001), supporting the proposed sequential mediation. Parallel to this mediation effect, a significant impact of DIS on SHA remained. This again implied that BET only partially mediated the relationship, which cross-validated H5. An overview of the model estimation results is presented in Table 3.

Brand transgressions (i.e. acts in which brands violate relationship rules between them and their customers; Aaker et al., 2004), such as, an unexpected price increase (Rotman et al., 2018), can be symbolic negative incidents, that can tremendously shock customer–brand relationships (Aaker et al., 2004). Brand transgressions and consumers’ reactions to them have been extensively studied by prior research (Davvetas et al., 2024; Khamitov et al., 2020). However, according to a recent literature review by Khamitov et al. (2020), consumers’ behavior (e.g. revenge) after transgressions of their favorite brands (i.e. consumers’ most beloved brands, which are typically preferred over other brands; Jain and Sharma, 2019) have been rarely examined. Existing research (see Table 1) has shown that consumers’ extreme reactions to transgressions of their favorite brand result in four central elements (i.e. emotions, brand betrayal, desire for retaliation and negative word-of-mouth. To the best of the authors’ knowledge, this paper is the first that simultaneously considers these four central elements. We show with two studies (Study 1: online survey; Study 2: online experiment), that dissatisfaction after a transgression of consumers’ favorite brand increases brand betrayal, which in turn leads to a rise in brand shame, which increases customers’ desire for retaliation. Furthermore, our results stress that customers’ desire for retaliation makes them talk more unfavorably about their favorite brand.

This research provides at least three theoretical contributions for the consumer–brand relationship, betrayal and shame literature.

First, regarding the literature stream on consumer–brand relationships, our research responds to calls for the study of the conditions that may endanger close consumer–brand relationships (Fournier and Alvarez, 2013). Here, a first important contribution concerns the investigation of the effects of transgressions of consumers’ favorite brand on specific affective reactions. Consumers mentally attach to their favorite brands to a larger extent (Arnould and Thompson, 2005; Johnson et al., 2011), which makes them develop strong, favorable relationships with them (Fournier and Avery, 2011). Prior research has almost exclusively focused on how consumers develop their preference for a favorite brand (e.g. Rhee and Johnson, 2012) or how they interact with their favorite brand on social media (e.g. Hajli et al., 2017; Hudson et al., 2016). Among the literature identifying the effects of strong customer–brand relationships (e.g. Tuškej et al., 2013), it is often claimed that they protect brands in situations of pronounced customer dissatisfaction. Our research, however, builds on prior relevant work showing that connected consumers react very sensibly to errors from brands that they admire (Wolter et al., 2019). We find that consumers develop intense dissatisfaction not only following a major brand event (e.g. product-harm crisis) but also that unfulfilled expectations after seemingly minor brand transgressions (e.g. service failures) have strong spillover effects on customer retaliation. Our findings align with earlier research in the context of the “love becomes hate” effect (Grégoire and Fisher, 2006) to which it adds an emotional explanation but also stands in contrast to existing research that claims that strong ties protect the brand against minor shortcomings (Davvetas and Diamantopoulos, 2017).

Second, with regard to the betrayal literature, our work expands the list of situations known to cause a feeling of betrayal as well as the possible consequences of that feeling of betrayal. It is well established that perceived betrayal occurs after service failures (Grégoire and Fisher, 2006). Particularly, transgressions of consumers’ most favorite brands make consumers – because of their close psychological proximity to them – feel more betrayed (Gerrath et al., 2023). However, consumers can experience a great variety of transgressions such as ethical incidents, which are said to trigger even stronger negative emotions and lead to more serious consequences as compared to competence-based brand transgressions (Dawar and Pillutla, 2000). Our research implies that this betrayal also exists in situations that do not qualify as a consumption failure per se but represent a rather small, symbolic brand transgression (e.g. brands letting down their most loyal customers by providing an inferior price-quality ratio), eroding the consumer–brand fit. Brand transgressions of their favorite brand, provide evidence for customers that they were mistaken and baited by their earlier trusted relationship partner.

Third, our research contributes to shame literature by suggesting that symbolic transgressions of consumers’ favorite brands can elicit brand shame. Brand shame is a negative affective reaction which stems from consumers realizing that they have chosen a faulty favorite brand (Weitzl et al., 2024). This makes them perceive their consumer-self as flawed or inferior. By considering this important inward emotion, this research adds to the evolving string of literature suggesting that brand transgressions can trigger consumers’ internalized shame (Sugathan et al., 2017). Our work complements findings suggesting that negative brand events can harm consumers’ self-worth (Reimann et al., 2018) and cause emotional discomfort, as they question their ability to build relationships with the right brand, which does not betray them (Tan et al., 2021). In such situations, the huge emotional discomfort may not be compensated with a positive reappraisal of the favorite brand because of motivated reasoning (Haumann et al., 2014). In addition, while extant research demonstrates that brand shame increases the outward emotion of consumer anger (Weitzl et al., 2024), this study provides evidence that this moral emotion also facilitates emotion regulation (i.e. a shame-reduction process) by directly increasing consumers’ desire to retaliate. Dissatisfied customers’ inclination to retaliate against their betraying favorite brand translates into their willingness to take vengeance by voicing negative word-of-mouth. This finding aligns with psychologists’ earlier insights that internalized shame can turn into vengeance and victimization (Hockenberry, 1995).

This research provides at least four managerial implications. First, marketers should realize that even a small, symbolic transgression of customers’ favorite brand can have a devastating impact on customer–brand relationships. According to common sense and one central literature stream (e.g. Tuškej et al., 2013), strong customer–brand relationships are supposed to protect brands in situations of pronounced customer dissatisfaction. Quite on the contrary, our results show that such a transgression lowers customers’ trust in their favorite brand (as evidenced by perceiving it as less dependable) and reduces the fit in personality between customers and their favorite brand (because their personal values are considered as more inconsistent with the values of their favorite brand).

The good connection brands have built with their customers over the years can quickly be impaired by such minor transgressions, such as one delivery that goes wrong. Specifically, these brand transgressions cause dissatisfaction, which makes consumers feel betrayed by their favorite brand. The more consumers feel betrayed, the more they experience brand shame, which is a negative emotion stemming from realizing that they have trusted a faulty favorite brand (Weitzl et al., 2024). Our findings prove marketers wrong who believe that shameful consumers become silent and passive. In contrast, we show that the more consumers experience brand shame, the more they develop a desire to retaliate against their favorite brand, which ultimately translates into talking unfavorably about their favorite brand to others.

Second, ideally, brands should strive to avoid brand transgressions – even small ones – and perform flawlessly for all their customers by increasing product quality (Psarommatis et al., 2020) and service quality in all its three dimensions (i.e. reliability, being on time and stability) (Li et al., 2021). There has long been a call for more proactive behavior in organizations (Crant, 2000). Customers prefer brands that offer proactive interactions (Mikolon et al., 2015). In the service literature, proactive interactions aim at anticipating transgressions or preventing transgressions from occurring (Shin et al., 2017). To achieve that, brands must pay close attention to the needs and expectations of customers with the aim to reduce dissatisfactory events (Silva et al., 2020). Nevertheless, brand transgressions occur quite often, and recent research shows that in such times of conflict, the more brands increase their relationship marketing activities, the higher dissatisfied customers’ commitment is (Banerjee et al., 2023). However, when resources are scarce, brands could combine customer data-driven marketing (Sheth and Kellstadt, 2021) and artificial intelligence (AI) (Lv et al., 2022) to detect their most committed and loyal customers and put in extra effort to avoid or quickly detect brand transgressions.

In contrast, if a brand transgression could not be avoided, eight principles (Jain and Jain, 2024) to repair the customer–brand relationship should be applied. The first principle is do the right thing, which is basically all about taking responsibility for the transgression and providing adequate reparation by protecting the victims (e.g. brands can provide a personalized apology and compensate affected customers). The second principle is take accountability, by making victims clear that the transgression is not their fault, even if the brand is not responsible for the transgression (e.g. brands can avoid defensive strategies and provide an accommodative response, tailored to specific customer groups). The third principle is act with lightning speed, because it reflects respect and commitment (e.g. brands can devote enough employees and use artificial intelligence to swiftly reply to dissatisfied consumers). The fourth principle is communicate transparently, because half-truths, cover-ups and lies all reduce trust in the brand (e.g. brands should clearly state when they have done something wrong and make their transgressions public, promising to avoid them in the future). The fifth principle is choose principle over profit, which includes that a pure focus on short-term profit might lead to distorted decisions that harm the brand in the long run (e.g. brands should acknowledge the real cost of dissatisfied customers and overcompensate them in specific cases). The sixth principle is treat each life with dignity, which should remind brands to include all different groups of people in their communication (e.g. brands should also think about minorities and take care to not be disrespectful to anyone). The seventh principle is leadership sets the tone, which clarifies that brands require leaders that can judge the scope of brand transgressions and know and enforce the appropriate steps to resolve them (e.g. brands should make brand transgressions leaders’ priority and make sure that all victims are swiftly recovered). The eighth principle is build brand authenticity, which stresses the absolute necessity to (re-)build trust after a brand transgression not only with dissatisfied customers but also with suppliers, shareholders, the general public, etc. (e.g. brands should have a list of all stakeholders available indicating their main values to tailor recovery messages) (Jain and Jain, 2024).

Third, if brand transgressions occur, marketers should try to reduce dissatisfied consumers’ perception of brand betrayal and brand shame. Brand betrayal is consumers’ perception that their favorite brand is not able to keep its promises to them. Research has shown that the more consumers experience helplessness (e.g. feeling unable to demand and receive an adequate recovery from the brand), the more they perceive betrayal both in situations of outcome transgressions and process transgressions (Obeidat et al., 2017). To reduce dissatisfied consumers’ feeling of helplessness, marketers can provide clear and transparent information on how consumers can receive recovery after a brand transgression. Ideally, as soon as the brand transgression happens, this information is publicly available. Marketers should empower consumers not to be shy to claim the recovery that they deserve. Consequently, consumers will feel less helpless and, in turn, less betrayed by their favorite brand.

In addition, recovery messages can also be used to frame a brand transgression as a non-symbolic, competence-based negative event instead of a symbolic, moral negative event. This positive disposition is likely to lead to more effective recovery interactions, as it should make consumers more open to explanations, apologies, etc. provided by the company after the brand transgression. Research has shown that exclusive brand offers – which consumers perceive as unique and different from other brands – after brand transgression (e.g. six months of 60-minute VIP early access to limited-quantity flash sales) make betrayed consumers even develop a positive attitude toward the brand (Tan et al., 2021). In addition, marketers should try to reduce dissatisfied consumers’ perception of brand shame after a transgression of their favorite brand. Brand shame is a negative emotion consumers experience when realizing that they have selected a favorite brand, which is faulty (Weitzl et al., 2024). Extant research suggests that shame is an extremely painful and humiliating experience of negative self-evaluation (Chrdileli and Kasser, 2018), which also gives rise to other negative emotions such as self-criticism (Lazarus and Shahar, 2018). After brand transgressions, consumers feel ashamed to have invested in a relationship with an erroneous favorite brand (Platt and Freyd, 2015).

Therefore, marketers should strive to rebuild the damaged relationship with their favorite customers. One first step is to communicate to consumers affected by the brand transgression that there is no need to feel ashamed. Marketers can openly communicate that the transgression is the brand’s fault and shift shame to themselves. Making special offers (e.g. a very generous, nicely written, personal recovery message) after brand transgressions is assumed to reduce consumers experience of brand shame (Brakus et al., 2009).

Fourth, marketers should provide customers who consider their brand as their favorite with alternative ways to express their detrimental statements after brand transgressions. As our results reveal, these customers’ brand shame translates into a desire for retaliation. Although consumers’ inclination to retaliate against the brand is an impulsive desire to only take short-term vengeance (Zourrig et al., 2009), our results stress that it still leads to publicly criticizing their favorite brand. Therefore, brands are well advised to offer their revengeful consumers alternative channels to vent their frustration after brand transgressions. Relationships between customers and their favorite brand have especially become increasingly relational, giving increased room for the development and expression of emotions (Jain and Sharma, 2019). We suggest that companies treat these special customers accordingly. Thus, instead of waiting until they publicly badmouth the brand, companies can offer them a video call to express their discomfiting feelings right away. Such a personal setting in which these customers feel respected and taken seriously provides a true chance for rebuilding the broken relationship. While this approach is definitely more cost-intensive in the short run, it might still be a wiser strategy, given that the short- and long-run financial loss companies experience through negative word-of-mouth is gigantic (Luo, 2009).

While this research bears several implications for theory and practice, these insights should be interpreted by considering some limitations, providing interesting directions for future research. First, this research measured (online survey – Study 1) and manipulated (online experiment – Study 2) customers’ dissatisfaction after a transgression with their favorite brand. While this approach aligns with common empirical procedures (e.g. Zhang et al., 2025), future research should aim to cross-validate our findings by using more ecologically valid ways to stimulate customers’ dissatisfaction and, in turn, brand betrayal, brand shame and so on. Here, a field experiment – as recommended by Gneezy (2017) – would provide a setting that resembles more accurately the actual situation in which consumers experience a transgression with their favorite brand. Such an approach would also enable researchers to introduce moderating variables (e.g. consumer–brand identification; Weitzl et al., 2024) that may alter the observed effects.

Second, this study only considered brand shame as an inward emotion elicited after a transgression involving a consumer’s favorite brand. However, following such a brand transgression, consumers are inclined to simultaneously experience multiple negative emotions, including inward emotions (e.g. guilt, regret, embarrassment) and outward emotions (e.g. anger) (Haj-Salem and Chebat, 2014). In future studies, other researchers should investigate the relative importance of a more complete set of emotions (Valentini et al., 2020) on consumer retaliation after transgressions of their favorite brand and hence help to understand brand shame’s role better.

Finally, future research could enrich our understanding of the negative spillover effect of internalized brand shame on the desire to retaliate and other coping strategies (e.g. revenge-taking) by further exploring the psychological underpinnings of the identified effects. A variety of psychological mechanisms could potentially underlie aggressive reactions to shame, such as an intensified brand attribution following a mental separation from the brand (Liang et al., 2024). Consequently, questions such as the following appear particularly insightful: When do dissatisfied consumers take responsibility for their bad choices and not externalize them? – a question that contributes to the further development of the moral disengagement theory (Bandura, 1999). Can brand transgressions not only trigger internalized brand shame but also external brand shame, which may reduce consumers’ retaliatory behaviors? What role do recovery messages play in mitigating the detrimental effects of brand betrayal and brand shame? Answers to these questions would further improve our understanding of consumers’ reactions after transgressions of their favorite brands.

To assess a potential common method bias (CMB), three statistical methods were applied to control for its influence (Podsakoff et al., 2003). First, Harman’s single-factor test showed that the largest factor accounted for 23.45% of the total variance extracted, which is well below the recommended threshold of 50%. Second, the variance inflation factors (VIFs) were all below the recommended standard of 3, which indicated a low collinearity (Hair et al., 2021). Finally, the unmeasured latent marker variable (ULMC) approach (Chin et al., 2012) demonstrated that the average substantive variance (0.70) was substantially greater than the average method variance (0.01). The substantive-to-method variance ratio was approximately 105:1. Furthermore, most factor loadings were not significant. Taken together, the three conducted statistical tests provided no cue that a CMB affected the results of Study 1.