Abstract
Purpose
The purpose of this study is to place the antecedents and consequences of brand hate in the context of negative consumer–brand relationship in the telecommunication industry. It provides a response to the existing gap in the research on brand hate in consumer behavior in service brands.
Design/methodology/approach
A survey-based data was modeled after theory that aims to apply concepts to the telecommunications industry. With a solid model grounded and context-adapted, a mediation analysis of the role of brand hate in negative antecedents and consequences toward brands was performed.
Findings
Brand hate was found to mediate all the negative relationships proposed, while showing to be especially significant in mediating negative word of mouth. This model appropriately fits the services' marketing brand and revealed new insights into the function of brand hate in negative relationships that are specific to service marketing consumer brands.
Research limitations/implications
Branding theory may benefit from deeper insights into the negative side of consumer–brand relationships. A broader illustration of its constituents in different industries and the recovery of the management approach to these circumstances bring innovation and a richer understanding, specially to the role of brand hate in the mediation context as seen in the literature (Hegner et al., 2017; Zarantonello et al., 2016)
Practical implications
Managerial implications include assessing brands in analyzing and relating to different emotions and concepts from customers, allowing to prioritize and mapping the customer relationship touchpoints.
Originality/value
The present study presents a first insight of brand hate in the context of the service industry of telecommunications in southern Europe while testing brand hate as a mediator involving negative predictors leading to negative outcomes in consumer–brand relationships.
Keywords
Citation
Pinto, O. and Brandão, A. (2021), "Antecedents and consequences of brand hate: empirical evidence from the telecommunication industry", European Journal of Management and Business Economics, Vol. 30 No. 1, pp. 18-35. https://doi.org/10.1108/EJMBE-04-2020-0084
Publisher
:Emerald Publishing Limited
Copyright © 2020, Olavo Pinto and Amélia Brandão
License
Published in European Journal of Management and Business Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
In the context of brand management, consumer negativity and the emergence of brand hate consumer relationships (Bryson et al., 2013; Fetscherin, 2019; Hegner et al., 2017; Hu et al., 2018; Kucuk, 2019; Zarantonello et al., 2018) are increasingly under research and oblige companies to better understand these phenomena. This motivation is additionally justified by the growing power of consumers to positively or negatively influence others (Hegner et al., 2017; Johnson et al., 2011; Kucuk, 2015; Romani et al., 2012a; Veloutsou and Guzmán, 2017; Zarantonello et al., 2016).
However, the literature is still scarce regarding the negative consumer–brand relationships and prioritizes investigations into positive rather than negative characteristics (Fetscherin, 2019; Romani et al., 2012a; Veloutsou and Guzmán, 2017). The research on negative consumer–brand relationships has been tested to luxury brands (Bryson et al., 2013) and food chains (Islam et al., 2018).
Regarding brand hate, the most recent studies deal mainly with the antecedents and consequences of the phenomenon (Bryson et al., 2013; Hegner et al., 2017; Zarantonello et al., 2016) in order to understand this most extreme negative brand feeling. Brand hate is triggered by three antecedents (negative experience, symbolic incongruity and ideological incompatibility), which leads to three behavioral consequences (brand avoidance, negative word of mouth and brand retaliation) (Hegner et al., 2017).
Many of the studies on brand hate focus on consumers selecting the brand for which they nurture negative feelings or attitudes. In those previous researches, in which the consumer can choose the hated brand, telecommunication brands figure as one of the top industries cited (Fetscherin, 2019; Johnson et al., 2011). Moreover, previous research on brand hate describe this phenomenon at a specific period of time, which calls for need of adopting a longitudinal perspective to understand how brand hate develops over time and which is its relationship to previous positive feelings (Zarantonello et al., 2016).
In this context, one theoretical question that remains without empirical answer is: how does brand hate impact on active retaliation toward a service brand? Thus, the aim of this paper is to place the antecedents and consequences of brand hate in the context of negative consumer–brand relationship in the telecommunication industry. It goes beyond the previous research as it advances the knowledge on the key antecedents and consequences of brand hate, in a new context, that is telecommunication industry.
The theoretical importance of this paper lies in the attempt to answer the recent literature requests to further examine the increased negativity toward brands (Osuna Ramírez et al., 2019; Veloutsou and Guzmán, 2017) and to service marketing (Zarantonello et al., 2016). Moreover, this paper answers the call for new brand hate research and its application to different industries, locations and universes (Fetscherin, 2019; Kucuk, 2019).
From a practical standpoint, this study provides insights for companies to evaluate brand hate and, in turn, create effective defense mechanisms in light of the detriment consumer hostility causes to companies and their brands (Fournier and Alvarez, 2013; Krishnamurthy and Kucuk, 2009; Kucuk, 2019).
The structure of the paper is as follows. First, the relevant literature on negative consumer–brand relationship and brand hate which is followed by an explanation of the antecedents and consequences of brand hate under investigation. Further, the methodology section and findings. Lastly, the discussion of the findings and the conclusion on academic and managerial implications, directions for future research and limitations.
Negative consumer–brand relationships
Relationship marketing has now completely replaced the transactional views of marketing (Fournier, 1998), becoming a popular research area in the past years, creating and establishing concepts as to how consumers relate to brands and consumer products or services (Fetscherin and Heinrich, 2015).
Concepts and constructs of negative brand relationships have been studied, as desire for retaliation (Grégoire and Fisher, 2006), brand avoidance (Lee et al., 2009), brand divorce (Sussan et al., 2012) and attachment–avoidance (Park et al., 2013). Recent literature focuses on the study of the concept of brand hate (Hegner et al., 2017; Zarantonello et al., 2016). Currently, more deep conceptualizations of hate within brand relationships (Fetscherin, 2019) have been presented, demonstrating its multidimensionality (Kucuk, 2019) as with other negative consequences like brand avoidance (Odoom et al., 2019). Moreover, there are increasingly new insights around negative relationships and its origins, whether its rooted in the brand as a receptor of different emotions from consumers (Hu et al., 2018) or try to go deeply and contextualizes the consumer as an individual with emotions toward a brand (Fetscherin, 2019; Kucuk, 2019). Of great contribution to consumer–brand relationship are the approaches to brand love and brand loyalty concepts (Batra et al., 2012; Carroll and Ahuvia, 2006). However, a bad experience may have more impact in further actions and memories of a consumer than the good ones (Hegner et al., 2017) highlighting their interest in managerial application.
Brands are perceived as an entity with multiple attributes given by the consumers or their publics. Positive relations are seen as more of utilitarian value tending to be “strong and long lasting” (Johnson et al., 2011, p. 110) drawing from interpersonal relationship research that proved to be appropriate in brand–consumer relationships contexts (Fetscherin, 2019). The tendencies that are observed in human relationships can be useful in predicting consumer behavior (Thomson et al., 2012) as the combination of emotions found in psychology can be linked to some behavioral responses toward brands.
Also note that emotions in regard to products in its utilitarian sense do not suffice and do not fully correspond to those related to brands as they are built by a visual, marketing activities and corporate image (Alba and Lutz, 2013; Romani et al., 2012a). Additionally, what constitutes a brand is generated through sources controlled and not controlled by the company (Romani et al., 2012a), although the commoditization and tangibility of a product or service can blur this distinction, relevant in the affective but maybe tendentially indistinguishable in terms of cognition.
The state of the art of negative relationships with brands studies spreads itself through many concepts and branches that should be considered, as anti-brand communities, the determinants and managerial implications of anti-branding (Krishnamurthy and Kucuk, 2009), negative word of mouth, trash-talk (Marticotte et al., 2016) and boycott (Ettenson and Klein, 2005; Thelen and Shapiro, 2012), the discourse used in negative content produced by the consumers (Marticotte et al., 2016) or producing more broaden descriptions of the phenomena as either the attachment–aversion relationship (Alba and Lutz, 2013) or the approach–avoidance (Zarantonello et al., 2016).
Although some streams of research have studied the negative emotions throughout the years, it is often called as a priority in future research as it is a hot topic nowadays (Fetscherin and Heinrich, 2015; Zarantonello et al., 2016). The main studies are not distant in methodologies and approaches from the conceptualization of emotions and constructs, with its own exploratory research, aiming to strengthen the psychology established definition of concepts, used interchangeably with brands and interpersonal relationships, found in positive relationship studies (Batra et al., 2012), and in the field of negative emotions (Zarantonello et al., 2016).
Most of the literature relates to the brand and managerial expectations of the relationship with the brand, not focusing in the “consumer self-transformation” (Sussan et al., 2012, p. 521) or the activity relationship frame (Mickelsson, 2017). This surpasses the frame of the person as a consumer, where multiple exogenous influences take place. Examples of this are the concepts of the self (Sussan et al., 2012) and the relationship between a user and its activities (Mickelsson, 2017) that may shed new lights in the relationship approach in which brand may not play a main role.
The greater the brand value or company success, the more likely the negative responses from consumers, either active or passive, which could be related to dissatisfaction in the same way as avoidance, negative word of mouth or even boycotting (Krishnamurthy and Kucuk, 2009; Lee et al., 2009). Positive relationships and the service provided to the customers are rapidly spread and determine not only its customer success but also implies the whole of the organization (Payne and Frow, 2017).
Brand hate
Brand hate is presented as the mediator of a set of triggers that predicts negative word of mouth, brand avoidance or brand retaliation, a set of consequences that are widely studied and harmful to brands.
Although the research built on the consumer–brand relationship concept has been engaged by many authors, the negative pole of the relationship seems to have been less studied in favor of the positive concepts of the relationship (Park et al., 2013). The relationship that consumers establish with brands is one that is based on the psychology and human behavior research, and, as such, concepts of brand love (Carroll and Ahuvia, 2006), brand divorce (Sussan et al., 2012) and brand hate draw parallels to a human dimension (Aaker et al., 2004; Fetscherin and Heinrich, 2015; Johnson et al., 2011; Sussan et al., 2012; Thomson et al., 2012). A set of predictors is known to lead to hateful emotions and attitudes in consumers, their context or marketing experience (Hegner et al., 2017).
Two potential antecedents of brand hate established in the literature are negative experience and symbolic incongruity. The former is referred to as one of the strongest predictors according to some authors (Hegner et al., 2017), and the latter pertains to a significant difference between the brand symbolic meaning and the consumer self-image.
In the same way, the literature identifies brand avoidance, brand retaliation and negative word of mouth as possible consequences of brand hate. Being the first two opposite manifestations of hate, one predominantly passive and the second predominantly active, (Grégoire et al., 2009; Hegner et al., 2017; Romani et al., 2012a) and the last one more prone to attack manifestations (Fournier and Alvarez, 2013).
Brand avoidance
Brand avoidance is defined as switching or ceasing to use a brand or to interact with it (Hegner et al., 2017) and is associated with flight strategies (Grégoire et al., 2009) being a more passive action toward a brand. It is considered as a strategy to cope with levels of hate for the brand, defined as avoidance strategies in psychology (Zarantonello et al., 2016), that do not reveal themselves in other ways than by stopping using the brand and being related to it.
Negative word of mouth
Grounded in the behavioral literature, brand hate predicts complaining, negative word of mouth and switching (Romani et al., 2012b) complaining, protest, patronage reduction or cessation (Zarantonello et al., 2016); brand switching, private and public complaining, brand retaliation and revenge (Fetscherin, 2019). Negative word of mouth has been found to be highly correlated with brand avoidance or even with action similar to boycotting (Thelen and Shapiro, 2012). The present construct lays on questions that try to assess the extensively researched negative word of mouth and includes acts like referencing negative things about the brand, either to friends or strangers (Johnson et al., 2011).
Brand retaliation
Brand retaliation measures a construct that has different degrees within itself. It can be simultaneous or complemented by negative word of mouth and the spread of these complaints online (Abney et al., 2017). Since it can include many types of actions and attitudes that seek to cause damage or hurt a brand (Hegner et al., 2017), this construct can range from the most damaging to the brand, to a simple complaining. Recently, the literature has identified it as “willingness to make financial sacrifices to hurt the brand” (Fetscherin, 2019, p. 3; Kucuk, 2019), the last one providing a new and more complex artifact to quantify the evilness of the customer. Third-party complaining was also included as some authors consider complaining either to the brand or to regulatory institutions or others , aside from other hatred activities that seek to damage or break the brand or even actions like stealing (Johnson et al., 2011).
Besides, brand hate has been identified as a strong predictor of negative emotions and a mediator for them, as well as a predictor of negative outcomes that stem from this relationship. It was driven by the conceptualization of its determinants, with negative experience and symbolic incongruity being the constructs adapted from Hegner et al. (2017).
Negative experience
Negative experience is represented by the product or service-related failures (Grégoire and Fisher, 2006; Johnson et al., 2011), but also the marketing environment (Hogg et al., 2009), packaging or information, its quality (Krishnamurthy and Kucuk, 2009) or even a reaction to the country of origin (Bryson et al., 2013; Bryson and Atwal, 2018). A vast spectrum of these items, adapted to the service-oriented brands, has been included. In fact, when an expectation toward a service is not met, in the brand touchpoints, it is known to be associated with “complaining, negative WOM and protest” (Zarantonello et al., 2016, p. 21) that fall in the used characterization as negative experience. Since it is product-oriented and occurs when negative consumption experiences take place (Zarantonello et al., 2016), we propose that:
Negative experience influences the proposed outcomes.
Negative experience influences brand avoidance;
Negative experience influences negative word of mouth;
Negative experience influences brand retaliation.
Brand hate is a known factor in the three proposed outcomes (Lee et al., 2009). The analysis is complete with brand hate performing mediation on negative experience, stating that:
Brand hate mediates the relation between negative experience and the outcomes;
Brand hate mediates the relation between negative experience and brand avoidance;
Brand hate mediates the relation between negative experience and negative word of mouth;
Brand hate mediates the relation between negative experience and brand retaliation.
Symbolic incongruity
Symbolic incongruity happens when the consumer does not want to be associated with a brand and is linked to brand avoidance (Hegner et al., 2017; Lee et al., 2009; Zarantonello et al., 2016). It is a personal form of communicating and using the brand to define one's own identity by avoiding or opposing to the concepts of the brand (Bryson et al., 2013; Khan and Lee, 2014; Lee et al., 2009; Sussan et al., 2012). Since it is known to predict negative outcomes, it's stated that:
Symbolic incongruity influences the proposed outcomes.
Symbolic incongruity influences brand avoidance;
Symbolic incongruity influences negative word of mouth;
Symbolic incongruity influences brand retaliation.
Symbolic incongruity is a trigger of brand hate (Hegner et al., 2017), which can increase the occurrence of negative outcomes; thus, it is stated that:
Brand hate mediates the relation between symbolic incongruity and the outcomes;
Brand hate mediates the relation between symbolic incongruity and brand avoidance;
Brand hate mediates the relation between symbolic incongruity and negative word of mouth;
Brand hate mediates the relation between symbolic incongruity and brand retaliation.
A series of EFA tests was run as a way to assess high correlation (>0.9) between factors in order to obtain a valid and reliable model.
Brand hate plays a role of mediator between the causes here presented, (Romani et al., 2012b; Zarantonello et al., 2016) which are vastly studied in the literature, and has many outcomes that can be troublesome to brands.
Methodology
Data collection
The survey was published online through relevant web forums where themes like technology, telecommunication, home care and finance are discussed. It was also shared along via the university's e-mail. It was available from December 2018 to February 2019 in Portugal. With 636 responses, 51% were female and 48% aged between 18 and 25, 29% between 25 and 35 and 21% between 35 and 65. 18.4% of the respondents never changed telecommunications operator, and 46% switched two or more times.
Validation
A multivariate-procedure exploratory factor analysis (EFA) was carried out to describe the elements found in the literature. Although previous information guided the relations between the latent and the observed variables, they were revalidated through existing models in the literature and, at the same time, proposing different specifications of the relationships (Byrne, 2013). An assessment of the normality and of multivariate outliers was performed, through analyzing extreme outliers in the Mahalanobis distance and re-specifying the model to address covariance errors spotting high scores of modification indices (M.I.) (Byrne, 2013).
After modifying and re-estimating, the model has reached what is considered an adequate goodness-of-fit and confirmed the plausibility of the relations between variables, obtaining validity by empirical and theoretical evidence as is required to an effective confirmatory factor analysis (CFA) which can be seen in annex 1 (Brown, 2015).
To achieve the best model possible, an EFA was performed, conducting a principal component analysis (PCA) with varimax with Kaiser normalization as the rotation method, allowing to provide evidence of the interrelation inside factors. The components were all highly correlated, with brand hate (>0.817), negative experience (>0.696) and symbolic incongruity (>0.647). Multiple tests were run for the model, in order to achieve a solid representation. To obtain a model with statistical significance, the constructs were analyzed with PCA, having obtained a high correlation between uncorrelated constructs, with the items found in previous studies (Hegner et al., 2017; Zarantonello et al., 2016).
In terms of validity and reliability of the model, the composite reliability, convergent validity and discriminant validity were calculated, within the recommended values found in the literature (Brown, 2015; Field, 2000). All the constructs present a CR > 0.64. For the brand hate and every other antecedent construct, all the CR > 0.90 and the Cronbach's α > 0.90. The average variance extracted (AVE) was always greater than 0.7, meeting the required convergent and discriminant validity between all constructs.
AVE was high on the outcomes and around 0.50 on brand avoidance and brand retaliation (Table 1). Cronbach α is reported to be in the low end, with brand avoidance going as low as 0.63, within acceptable threshold. There is discriminant validity since all the constructs are not intercorrelated outside their factor. These items were obtained after a EFA that allowed to test for the relationships present and were based on a valid model grounded in the literature (Grégoire and Fisher, 2006; Johnson et al., 2011; Johnson, 2006; Romani et al., 2012a; Zarantonello et al., 2016). Worth to mention that the dichotomous application of the outcomes' questions implies that the respondent performed the requested action.
The mediation analysis was performed with PROCESS model 4, an add-on for SPSS that aids the mediation analysis. This analysis resulted in testing the hypothesis regarding the mediating role of brand hate and further analysis on the effect of the antecedents in the outcomes.
We obtained VIF of 2.4 in the analysis between brand hate and the antecedents and 2.1 and 2.9 between the outcomes and all the independent variables (those being brand hate, negative experience and symbolic incongruity). These values are within range to not represent a problem of multicollinearity (Field, 2000).
The model showed an excellent fit: χ2 (156) = 459.313, p-value < 0.001; CFI = 0.972; NNFI = 0.959; RMSEA = 0.056. These values (Table 4) assess the statistical adequacy of our model (Figure 1), as based on our theoretical and practical account of the variables analyzed (Byrne, 2013). All the constructs presented, as well as the behavioral outcomes, are significantly related to their own components, with ps < 0.001.
Findings
After defining the model, in which brand hate acts as the mediating factor in this process (Romani et al., 2012a; Zarantonello et al., 2016) all the conditions of mediation in the paths were verified between every proposed antecedent and outcome (Field, 2000; Marôco, 2014).
In order for brand hate to be a mediator in the proposed model, it achieved the following steps: (1) the three antecedents (X variables), significantly predict the outcomes (Y variables); (2) the three antecedents (X) significantly predict brand hate (M mediator); (3) the mediator brand hate (M) significantly predicts each one of the outcomes (Y); and (4) all the antecedents (X) variables, are annulated or lessened predicting the (Y) variables, the brand hate outcomes. All of these steps are necessary to consider the mediation complete (Field, 2000).
OLS regression for negative experience
In the first step (path c) of the mediation model, the regression of negative experience with brand avoidance, ignoring the mediator brand hate, was significant, β = 0.108, t(631) = 14.34, p < 0.001. It was also significant with negative word of mouth β = 0.072, t(631) = 9.37, p < 0.001 and with brand retaliation β = 0.082, t(631) = 8.68, p < 0.001. Path c is also known as total model effect, representing the total effect as c = c'+ab.
The regression of symbolic incongruity with brand avoidance, ignoring the mediator brand hate, was significant, β = 0.112, t(631) = 13.83, p < 0.001. It was also significant with negative word of mouth β = 0.075, t(631) = 9.06, p < 0.001 and with brand retaliation β = 0.083 t(631) = 8.10, p < 0.001.
Secondly, (path a) showed that the regression of the negative experience on the mediator, brand hate, was also significant, β = 0.817, t(631) = 25.23, p < 0.001 (see Figure 2).
Third step (path b), the mediator brand hate, controlling for negative experience, was significant, β = 0.074, t(630) = 8.36, p < 0.001 in the mediation toward brand avoidance. the mediator controlling for negative experience was also significant toward negative word of mouth β = 0.082, t(631) = 9.15, p < 0.001 and toward brand retaliation β = 0.042, t(630) = 3.59, p < 0.001 (see Figure 3).
Fourth, path c', the analyses revealed that, controlling for the mediator brand hate, the negative experience is a significant predictor of brand avoidance, β = 0.048, t(630) = 4.73, p < 0.001. When controlling for the mediator, negative experience is also a significant predictor of brand retaliation, β = 0.048, t(630) = 3.64, p < 0.001. These analyses revealed that, controlling for the mediator brand hate, negative experience is not a significant predictor of negative word of mouth, β = 0.006, t(630) = 0.55, p = 0.58.
From bootstrap method, with completely standardized values, the indirect effect of negative experience is significant for brand avoidance β = 0.276, 95% CI [0.200, 0.357], β = 0.322, 95% CI [0.244, 0.403] for negative word of mouth and β = 0.134, 95% CI [0.057, 0.211] for brand retaliation since the confidence intervals do not include 0.
Brand hate was found to partially mediate the relationship between negative experience and brand avoidance. It also partially mediates the relationship between negative experience and brand retaliation.
It was found that brand hate fully mediated the relationship between negative experience and negative word of mouth (see Table 2).
OLS regression for symbolic incongruity
In the first step (path c) of the mediation model, the regression of symbolic incongruity with brand avoidance, ignoring the mediator brand hate, was significant, β = 0.112, t(631) = 13.83, p < 0.001. It was also significant with negative word of mouth β = 0.075, t(631) = 9.06, p < 0.001 and with brand retaliation β = 0.083, t(631) = 8.10, p < 0.001.
It also shows the regression of symbolic incongruity on brand hate is significant β = 0.831, t(631) = 22.94, p < 0.001 (see Figure 4).
In the third step (path b), the mediation shows that the mediator brand hate, controlling for symbolic incongruity was significant, β = 0.076, t(630) = 9.07, p < 0.001 in the mediation toward brand avoidance. Besides, the mediator controlling for symbolic incongruity was also significant toward negative word of mouth β = 0.081, t(630) = 9.48, p < 0.001 and toward brand retaliation β = 0.048, t(630) = 4.31, p < 0.001 (see Figure 5).
Fourth, path c', the analyses revealed that, controlling for the mediator brand hate, the symbolic incongruity is a significant predictor of brand avoidance, β = 0.049, t(630) = 4.73, p < 0.001. When controlling for the mediator, symbolic incongruity is also a significant predictor of brand retaliation, β = 0.043, t(630) = 3.16, p < 0.01. The analyses demonstrated that, similarly to what happened with negative experience, controlling for the mediator brand hate, symbolic incongruity is not a significant predictor of negative word of mouth, β = 0.008, t(630) = 0.755, p = 0.450 (see Figure 6).
From the bootstrap method tests, with completely standardized values, the indirect effect of symbolic incongruity is significant for brand avoidance β = 0.272, 95% CI [0.205, 0.342], for negative word of mouth β = 0.304, 95% CI [0.236, 0.373] and for brand retaliation β = 0.147, 95% CI [0.078, 0.221] since it does not include 0 in any of the tests (see Table 3).
Data/mediation analysis
The paths from the present model can infer mediation in each of the two antecedents, negative experience and symbolic incongruity (X) significantly predicting each of the three of the proposed outcomes (Y), brand avoidance, negative word of mouth and brand retaliation, with ps < 0.001. Brand hate (M) is significantly predicted by the two antecedents (X) negative experience and symbolic incongruity. This is known as a path. In its turn, brand hate (M) significantly predicts three of the proposed outcomes (Y), with ps < 0.01. This is known as b path.
Completing the mediation inference, two X variables are lessened predicting two of three X variables, brand avoidance and brand retaliation, in what is known as path c'. Negative word of mouth is not statistically different from zero, which proves that it is completely mediated by brand hate to all the three antecedents (X) negative experience and symbolic incongruity. The effect size was similar around all antecedents for the same outcome, meaning that for brand avoidance, the R2 measure around 0.24 for the total effect to 0.32 of the indirect effect. For negative word of mouth, it went from around 0.12 for the direct effect to 0.22 accounting for the mediator. For brand retaliation showed a total variance explained of 0.10–0.12 in the Y variable.
Brand hate significantly and positively predicts the proposed outcomes, with brand avoidance and negative word of mouth being the most influential with similar values presented, with a value as high as β = 0.082 and ps < 0.001. Brand retaliation presented a lower β = 0.012 with a p < 0.01 when accounting for negative experience.
Thus, it is proved that brand hate influences brand avoidance, brand retaliation and negative word of mouth. This is also a conclusion for brand retaliation, either controlling for negative experience or controlling for symbolic incongruity, with small differences. Brand retaliation is a form of actively showing dislike to the brand, having an associated cost for the consumer to perform that retaliation (Fetscherin, 2019) presenting a very low effect, when compared with negative word of mouth or brand avoidance.
Brand hate has proved to be at the center between a set of antecedents and negative outcomes for the brand (Zarantonello et al., 2016), and in the study this has been analyzed through a grounded theory model tested and specified for service brand telecommunications industry. Hate is a strong emotion, with great impact on a consumer approach to a brand. This interpersonal emotion or attitude has been studied when applied to brands and has been recently studied with multiple gradients, leading to different outcomes (Fetscherin, 2019). The mediation analysis allowed us to support or reject our hypothesis, as stated on Table 4, and a full analysis of the whole relationships data can be consulted in annex 1: PROCESS model 4 outputs.
H1 and H3 are both partially proved since negative experience and symbolic incongruity have influenced brand avoidance (H1a, H3a) and brand retaliation (H1c and H3c). However, it cannot support H1b – negative experience influences negative word of mouth – nor H3b – symbolic incongruity influences negative word of mouth – present in the c' path p > 0.5. Brand hate proved to be a complete mediator between negative word of mouth, negative experience and symbolic incongruity, fully supporting H2b and H4b. This means that negative word of mouth only occurs when a feeling of brand hate is true for the consumer. Although H1 and H3 are only partially proved, as predicted, all the outcomes will also have a direct effect on negative outcomes when not considering brand hate, the hypotheses theorized in H2 and H4 are still true: all the antecedents have a greater effect on the outcome when mediated by brand hate controlling for each predictor.
Since brand hate completely mediates the relationship between all the antecedents and negative word of mouth, completely proving H2b, with F (2, 630) = 91.54, p < 0.001, R2 = 0.225 brand hate mediates the relationship of past experience and negative word of mouth β = 0.082, t(630) = 9.15, p < 0.001 and completely proving H4b, F (2 , 630) = 91.71, p < 0.001, R2 = 0.226 where brand hate mediates the relation of symbolic incongruity and negative word of mouth β = 0.081, t(630) = 9.48, p < 0.001.
Brand hate mediates the relationship between both antecedents and brand avoidance, with brand hate mediating the relationship between brand avoidance and symbolic incongruity H4a, (F (2, 630) = 149, p < 0.001, R2 = 0.321), being the one with the highest effect from brand hate with β = 0.076, t(630) = 9.07, p < 0.001, followed by H2a, brand hate mediating the relationship of negative experience and brand avoidance (F (2, 630) = 148.98, p < 0.001, R2 = 0.321) predicting β = 0.074, t(630) = 8.36, p < 0.001.
It was also proved that brand hate mediates the effect between all the antecedents and brand retaliation. Thus, H2c is proved since negative experience (F (2, 630) = 44.81, p < 0.001, R2 = 0.125) has brand hate mediating its relationship with brand retaliation β = 0.042, t(630) = 3.59, p < 0.001, compared to H4c, symbolic incongruity (F (2, 630) = 43.00, p < 0.001, R2 = 0.120) with brand hate mediating the relationship with brand retaliation β = 0.048, t(630) = 4.31, p < 0.001.
Table 4 presents the hypothesis and whether they were supported.
Discussion
This study has shed light on the major antecedents and consequences of the most negative and consequent construct that had been studied in the past years (Hegner et al., 2017; Zarantonello et al., 2016).
What is new to this study is that brand hate proved to have a role in mediating negative word of mouth completely, either from a negative experience or a symbolic incongruity. These two key antecedents have proved to impact the proposed consequences. But the negative word of mouth has only occurred in the presence of brand hate's mediating role.
Brand retaliation, appears to be explained similarly by negative experience and symbolic incongruity, which corroborates the incongruence with the self-image, also leads to brand avoidance (Hegner et al., 2017; Kavaliauske and Simanaviciute, 2015; Lee et al., 2009)
Brand avoidance is highly mediated by brand hate by either negative experience or symbolic incongruence and is equally explained by the two antecedents.
Theoretical implications
Negative experience proved to be a predictor of brand hate. In fact, when a consumer has a negative experience with a brand, it can deteriorate their relationship and lead to a negative outcome (Zarantonello et al., 2018) It has also been documented as a predictor of experiential brand avoidance (Lee et al., 2009). In relation to brand avoidance, brand hate proves to be a strong mediator, through which an increase in the outcome takes place, also having a direct relationship. Brand hate, especially if it is felt more strongly, as it is suggested by the literature, leads to public complaining, a form of negative word of mouth (Fetscherin, 2019). In this analysis, the negative experience predicts negative word of mouth exclusively when mediated by brand hate emotions, in line with this suggestion. It has been reported that brand retaliation does not need to be motivated by a negative experience (Johnson et al., 2011), and in the present study, regarding brand retaliation, the total effect is smaller, although brand hate plays a mediating role.
Symbolic incongruity is a predictor of brand hate. When accounting for brand hate, it proves to influence brand avoidance, but it also shows that it affects the outcome without mediation. In fact, symbolic incongruity relates the identity of the consumer to the brand, and it has been linked to brand avoidance (Lee et al., 2009). It leads to negative word of mouth only when mediated by brand hate emotions. Negative word of mouth is expected to be an effect of all predictors (Hegner et al., 2017), a suggestion that the emotion is essential in mediating its incidence. Symbolic incongruity suggests effect on brand retaliation, whether it is mediated by brand hate or not.
In this case, it is shown that brand avoidance is especially mediated by brand hate, if the consumer has a negative experience but even more if there is symbolic incongruity. Symbolic incongruity influences brand avoidance through brand hate, but it can lead to it even when not mediated by hate feelings. On the other hand, brand hate proved to be a mediator of negative word of mouth, and this was shown to only occur if there is mediation of hate emotions.
Brand retaliation is less motivated by a negative experience than by a symbolic incongruity, but it proved to be always mediated by brand hate in either case. The brand retaliation was widely defined in the literature as a means by which a consumer damages a brand financially, in many forms such as complaining, attacking or trying to cause an inconvenience to the brand in general (Bryson et al., 2013; Fetscherin, 2019; Grégoire et al., 2009; Grégoire and Fisher, 2006; Hegner et al., 2017; Johnson et al., 2011; Romani et al., 2012b).
This research presented a new approach, compared to the best knowledge of the literature, as well as to other studies that analyze consumer brands in many industries, by focusing on a single industry. It also tested consumers and nonconsumer relations with telecommunication brands and presents new managing insights. It relates consumer–brand relationships to constructs grounded theoretically in interpersonal and psychology research that had been previously established (Fetscherin and Heinrich, 2015; Lee et al., 2009; Romani et al., 2012a).
The method applied in this study presented a good overview of the relationship between brand hate and some outcomes and antecedents. The proposed factors in the literature proved to be valid in specific context within the telecommunications industry and may be applied to other contexts as well as compared with the ones present in this study. In this context, the analysis of a consumer brand relation in the service industries comes as a complement to other studies in the brand hate research, that have been prominently about luxury brands (Bryson et al., 2013) or food service brands (Bryson and Atwal, 2018), but had not quite provided much insight into some more utilitarian brands. It was hence provided valuable insight into an industry, into service marketing consumers and into service marketing approaches to negativity and brand hate. Doing this in southwest Europe has made it possible to acquire insight to perform cross-cultural analysis in scholar research.
Practical implications
This study contributes and complements existing literature on the negative relationship between consumers and brands in three respects. Firstly, as mentioned, this study responds to the growing demand for research about the dark side of consumer–brand relationships (Veloutsou and Guzmán, 2017) because presently, the emphasis in the literature on the study of the positive brand–consumer relationships is lacking (Fetscherin, 2019). Secondly, this paper tests for the first time the effect on the telecommunication industry. Thirdly, it corroborates the previous studies on the impact of brand hate on brand avoidance.
In terms of practical implications, this research provides companies with insight into how hostility around the brand can lead to brand avoidance.
Companies and brands need to create effective defense mechanisms either to combat the phenomenon of brand hate, or more effectively, to try to reverse or neutralize as much as possible the pejorative results from the negative past experience of current consumers with the brand. Business needs to work with consumers to change practices, thereby improving their relationship with consumers, minimizing negative behaviors and creating control measures (Romani et al., 2013).
However, as noted by Hegner et al. (2017), any company can satisfy all current or potential consumers by being able to handle the most severe situations and by minimizing the negative impact of the most brand-hostile consumers.
The considerations made in this study can be used to investigate further dynamics present in the services brand–consumer relationship. Some of the constructs, like brand retaliation, can be analyzed under different scales of intensity, or occupying a wider range of constructs. Managerial implications of these recent studies on antecedents and outcomes are consistent with negative and brand hate research and show similarities with brand love and positive emotions, providing some recipes and strategies to deal with them. In the present study, a complete mediation of negative word of mouth proved by hate emotions was found, managing tense relationship occurrences with every customer can prove to be of upmost importance. Negative word of mouth tends to spread and can prove to be, especially in the digital age, a sensitive point for damaging a brand and affecting valuable customers (Grégoire et al., 2009; Krishnamurthy and Kucuk, 2009; Sreejesh et al., 2017). Brand retaliation, which usually translates into an extra cost in managing a customer, proved to be more motivated by a symbolic incongruity than a past experience (Lee et al., 2009). These customers may have to be targeted with different means of symbolism in order to channel their desire for revenge towards a brand, or even intensify this dichotomy into a marketing strategy after getting a whole view of its symbolic meanings (Hogg et al., 2009, pp. 9–10), being cautious about the practical implications of corporate brand image (Rindell, 2013).
The reason behind these managerial implications follows ethical behavior and also the incorporation of more consumer inspection toward an effective response (Zarantonello et al., 2016) and of past relationship (Hegner et al., 2017) as well as the proactive approach of the consumer. This also calls for an active and continuous evaluation of the relationship's nature with the consumers, as those with a higher “relationship quality” may have more tendency for retaliation (Grégoire and Fisher, 2006, p. 46). In building a relationship with consumers, a brand may face a different set of consequences when hate emotions or feelings are involved, and something, either from the brand or the consumer, changes (Sussan et al., 2012).
Limitations and future research
Further research should fully and more extensively determine the role played by the context of the brand, like industries or types of brands, in explaining the negative relationships. Comparative methodologies across industries and cultures, with multicultural research and regarding customers and noncustomers relationships with consumer brands can also prove to be of great interest, especially in understanding the managerial effects in different settings.
Longitudinal studies, which can test conditions of time like other studies in the field (Grégoire et al., 2009) are other critical points that indicate the relationship in the negative realm (Aaker et al., 2004).
Figures
Reliability and validity tests
| Cronbach’s α (>0.7) | CR (>0.6) | AVE (>0.5) | |
|---|---|---|---|
| BH | 0.97 | 0.97 | 0.8 |
| NE | 0.90 | 0.91 | 0.7 |
| SI | 0.90 | 0.90 | 0.7 |
| BA | 0.63 | 0.64 | 0.5 |
| NWM | 0.72 | 0.73 | 0.5 |
| BR | 0.65 | 0.65 | 0.5 |
Model Coefficients for the brand hate study with negative experience
| Antecedent | Consequence | |||||||
|---|---|---|---|---|---|---|---|---|
| M (brand hate) | Y (brand avoidance) | |||||||
| Coeff. | SE | p | Coeff. | SE | p | |||
| X (neg. exp.) | a | 0.813 | 0.032 | <0.001 | c’ | 0.048 | 0.010 | <0.001 |
| M (brand H.) | – | – | – | b | 0.074 | 0.009 | <0.001 | |
| Constant | iM | −0.421 | 0.152 | 0.0057 | iY | −0.186 | 0.034 | <0.001 |
| R2 = 0.502 | R2 = 0.321 | |||||||
| F (1, 631) = 636.46, p < 0.001 | F (2,630) = 148.98, p < 0.001 | |||||||
| Y (neg. word of mouth) | Y (brand retaliation) | |||||||
| X (neg. exp.) | c’ | 0.006 | 0.010 | 0.582 | c’ | 0.048 | 0.013 | <0.001 |
| M (brand H.) | b | 0.082 | 0.009 | <0.001 | b | 0.042 | 0.012 | <0.001 |
| Constant | iY | −0.084 | 0.034 | 0.015 | iY | 0.094 | 0.044 | 0.034 |
| R2 = 0.225 | R2 = 0.125 | |||||||
| F (2, 630) = 91.54, p < 0.001 | F (2,630) = 44.81, p < 0.001 | |||||||
Model coefficients for the brand hate study with symbolic incongruity
| Antecedent | Consequence | |||||||
|---|---|---|---|---|---|---|---|---|
| M (brand hate) | Y (brand avoidance) | |||||||
| Coeff. | SE | p | Coeff. | SE | p | |||
| X (simb. Inc.) | A | 0.831 | 0.036 | <0.001 | c’ | 0.049 | 0.010 | <0.001 |
| M (brand H.) | -- | -- | -- | b | 0.076 | 0.008 | <0.001 | |
| Constant | iM | −1.03 | 0.191 | <0.001 | iY | −0.231 | 0.041 | <0.001 |
| R2 = 0.455 | R2 = 0.321 | |||||||
| F (1, 631) = 526.20, p < 0.001 | F (2,630) = 149.00, p < 0.001 | |||||||
| Y (neg. word of mouth) | Y (brand retaliation) | |||||||
| X (simb. Inc.) | c’ | 0.008 | 0.011 | 0.450 | c’ | 0.043 | 0.014 | 0.002 |
| M (brand H.) | b | 0.081 | 0.009 | <0.001 | b | 0.048 | 0.011 | <0.001 |
| Constant | iY | −0.096 | 0.042 | 0.022 | iY | 0.070 | 0.054 | 0.202 |
| R2 = 0.225 | R2 = 0.120 | |||||||
| F (2, 630) = 91.71, p < 0.001 | F (2,630) = 43.00, p < 0.001 | |||||||
The tested results of hypotheses
| Hypothesized relationship | Path coefficient | Test result |
|---|---|---|
| H1a - Negative experience influences brand avoidance; | 0.048*** | Supported |
| H1b - Negative experience influences negative word of mouth | 0.006ns | Not Supported |
| H1c - Negative experience influences brand retaliation | 0.048*** | Supported |
| H2a - Brand hate mediates the relation between negative experience and brand avoidance | 0.074*** | Supported |
| H2b - Brand hate mediates the relation between negative experience and negative word of mouth | 0.082*** | Supported |
| H2c - Brand hate mediates the relation between negative experience and brand retaliation | 0.042*** | Supported |
| H3a - Symbolic incongruity influences brand avoidance | 0.049*** | Supported |
| H3b - Symbolic incongruity influences negative word of mouth | 0.008ns | Not Supported |
| H3c - Symbolic incongruity influences brand retaliation | 0.043** | Supported |
| H4a - Brand hate mediates the relation between symbolic incongruity and brand avoidance | 0.076*** | Supported |
| H4b - Brand hate mediates the relation between symbolic incongruity and negative word of mouth | 0.081*** | Supported |
| H4c - Brand hate mediates the relation between symbolic incongruity and brand retaliation | 0.048*** | Supported |
Note(s): ***indicates p-value < 0.001, **indicates p-value < 0.01
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