FROM HERO TO ZERO: BRAND LOVE'S MODERATING EFFECT
ON BRAND HATE ANTECEDENTS AND OUTCOMES
Bruno Tiago Barbosa Ribeiro
Dissertation
Master in service Management
Oriented by
Amélia Maria Pinto da Cunha Brandão Co-Oriented by
Teresa Maria Rocha Fernandes Silva
Agradecimentos
Em primeiro lugar, um grande obrigado à Professora Amélia que, especialmente nesta última fase, foi incansável e super atenciosa.
Em segundo lugar, outro grande obrigado à Professora Teresa por toda a disponibilidade que demonstrou e por me ter ajudado a encontrar o rumo certo para este projeto.
Era muito mau se não agradecesse aos meus pais? Era, pois. No entanto, apesar de eles não saberem o tema desta dissertação nem sequer do mestrado que escolhi tirar, foram eles que pagaram as propinas. Além disso, fizeram o favor de me educar da melhor maneira possível e sempre colocaram o meu bem à frente do resto. “Acaba o mestrado e depois vai trabalhar, não sejas burro.”, ai, como eles tinham razão.
Não esquecendo o resto dos membros da família, obrigado Bea! Sem a tua lasanha e o teu gelado nunca teria cruzado a meta!
Aos meus avós, que apesar de desejarem que tivesse estudado para médico, são uns chatinhos que prezo muito.
À Catarina, por me aturar quando mais ninguém me atura e por estar sempre disponível para os meus devaneios.
A todos os meus amigos, e ainda são alguns, além dum obrigado uma grande desculpa por ter, muitas vezes, falhado com eles e mesmo assim encherem o meu dia com a melhor disposição possível.
Abstract
The evolution and growing relevance of consumer-brand relations have made the study of this theme dynamic and in constant metamorphosis, with the emergence of new perspectives and approaches at an incessant pace. Love for a brand is the treasure that all managers seek, and its unpleasant counterpart, hatred for it, is, on the other hand, largely responsible for the insomnia they suffer.
As such, the present study focuses on the hateful relationships formed between a consumer and a brand, with special attention to those that were formed after the existence of a close affinity with the brand, in the past. This study aims to ascertain whether the formation and consequent repercussions of a hate relationship with a brand, present substantial differences if the consumer has nurtured love for the brand in the past. To this end, a research model was developed based on studies that focused on the Brand Hate concept, its antecedents and consequences, and created an online survey, where each respondent answered some questions about their relationship with a brand they currently hate. Thus, 207 valid answers were obtained, later used for analysis.
The results show that participants with higher Brand Love values in the past are more resilient to corporate wrongdoings and violation of expectations episodes. However, it was not possible to verify the moderating impact of Brand Love on behaviors derived from the established hate relationship, namely negative word of mouth, consumer complaints and patronage reduction/cessation.
In a world where people use brands to express their feelings and to present themselves to their peers, using them as an integral part of themselves, this study contributes to the understanding of the polarizing power that emotions such as love and hate take and the implications, they may have in a business context. The results provide some interesting conclusions, however, given the high complexity and constant mutation of this theme, it is important that further studies are done to test new perspectives and update previously tested ones, allowing brands to make their decisions in a sustainable way, enhancing the good relationship with its consumers.
Keywords: Brand Hate; Brand Love; Corporate Wrongdoings; Violation of Expectations; Negative Word of Mouth; Consumer Complaining; Patronage Reduction/Cessations.
Resumo
A evolução e crescente relevância das relações consumidor-marca têm tornado o estudo desta temática dinâmico e em constante metamorfose, verificando-se o nascimento de novas perspetivas e abordagens a um ritmo incessante. O amor à marca é o tesouro que todos os gestores procuram e, a sua contraparte desagradável, o ódio à mesma, é, por sua vez, o grande responsável pelas insónias que sofrem.
Como tal, o presente estudo foca-se nas relações de ódio formadas entre um consumidor e uma marca, com especial atenção para aquelas que foram formadas após ter existido um vínculo de estreita afinidade com a dita marca, no passado. Este estudo tem o objetivo de averiguar se a formação e consequentes repercussões de uma relação de ódio para com uma marca, apresentam diferenças substanciais caso o consumidor tenha nutrido amor pela marca no passado. Para tal, foi desenvolvido um modelo de investigação com base em estudos que se debruçam sobre o conceito de Brand Hate, os seus antecedentes e consequentes e realizado um inquérito online, onde cada inquirido respondeu a algumas questões sobre o seu relacionamento com uma marca que atualmente odeiem. Deste modo, obtiveram-se 207 respostas válidas, posteriormente utilizadas para análise.
Os resultados mostram que os participantes com valores mais elevados de Brand Love registados no passado, apresentam uma maior resistência a más práticas por parte das marcas e a episódios de violação de expetativas. No entanto, o mesmo não foi possível verificar quanto ao impacto moderador do Brand Love nos comportamentos derivados da relação de ódio estabelecida, nomeadamente word of mouth negativo, reclamações de consumidores e redução/cessação do consumo de produtos/serviços da marca.
Num Mundo onde as pessoas se servem das marcas para expressarem o que sentem e se apresentarem aos seus pares, utilizando-as como parte integrante delas mesmas, este estudo contribui na medida em que permite entender o poder polarizador que emoções como o amor e ódio tomam e as implicações que podem ter num contexto comercial. Os resultados fornecem algumas conclusões interessantes, no entanto, dada a alta complexidade e constante mutação desta temática é importante que sejam feitos mais estudos de modo a testar novas perspetivas e atualizar as previamente testadas, permitindo que as marcas tomem as suas decisões de forma sustentada, potenciando o bom relacionamento com os seus consumidores.
Keywords: Ódio às marcas; Amor às marcas; Más práticas corporativas; Violação de expetativas; Word of mouth negativo; Reclamações de consumidores, Redução/cessação do consumo.
Index
1. Introduction and Topic Relevance ... 1
2. Literature Review... 4
2.1. Brand Love ... 4
2.2. Brand Hate ... 5
3. Hypotheses Development ... 8
3.1. Antecedents of Brand Hate ... 8
3.2. Outcomes of Brand Hate ... 9
3.3. Antecedents of Brand Love ... 10
3.4. Outcomes of Brand Love ... 11
4. Methodology ... 14 4.1. Research model ... 14 4.2. Methodology ... 15 4.3. Data Collection ... 15 4.4. Questionnaire’s structure ... 15 4.5. The Sample ... 16 4.6. Data Analysis ... 17 4.7. Sample Characterization ... 17 4.8. Descriptive Analysis ... 20 4.9. Model Validation ... 22 4.9.1. Factor analysis ... 22
4.10. Structural Model Validation ... 29
4.11. Hypothesis Test Results and Discussion ... 30
5. General Considerations ... 40
6. Contributions, Limitations and Future Research Suggestions ... 41
7. Bibliographic References ... 42
8. Attachments ... 48
8.1. Annex 1 - Questionnaire ... 48
8.2. Annex 2 – Hate target brands ... 49
8.3. Hated brands – Word Cloud ... 51
8.4. Annex 4 – Brand Hate SPSS Output ... 52
8.5. Annex 5 – Brand Love SPSS Output ... 53
8.6. Annex 6 – Corporate Wrongdoings SPSS Output ... 55
8.7. Annex 7 – Violation of Expectations SPSS Output ... 56
8.8. Annex 8 – Negative Word of Mouth SPSS Output ... 57
8.9. Annex 9 – Patronage Reduction/Cessation SPSS Output ... 58
Index of Figures
Figure 1 – Antecedents and Outcomes of Brand Hate Model ... 14
Figure 2 – Research Model... 14
Figure 3 – Reasons that lead respondents to hate the brands they mentioned ... 20
Index of Tables
Table 1 – Brand Hate definitions ... 7
Table 2 – Brand Love Outcomes ... 11
Table 3 – Sociodemographic Data ... 18
Table 4 – Hated brands mentioned by respondents ... 18
Table 5 – Type of product related to the hated brands mentioned by respondents ... 19
Table 6 – Dimension item analysis of: Brand Hate, Experienced Brand Love, Brand Hate Antecedents and Brand Hate Outcomes ... 21
Table 7 – Cronbach’s Alpha value description ... 23
Table 8 – Cronbach’s Alpha, Composite Reliability and Average Variance Extracted Analysis ... 24
Table 9 – Discriminant validity Test ... 25
Table 10 – Factor Analysis ... 27
Table 11 – Hypothesis Results ... 30
Table 12 – Model Summary for H1 and H6... 31
Table 13 – Direct effect coefficient for H1 ... 31
Table 14 – Moderation coefficient analysis for H6 ... 32
Table 15 – Model Summary for H2 and H7... 33
Table 16 – Direct effect coefficient for H2 ... 33
Table 17 – Moderation coefficient for H7 ... 34
Table 18 – Model summary for H3 and H8 ... 35
Table 19 – Direct effect coefficient for H3 ... 35
Table 20 – Model summary for H4 and H9 ... 36
Table 21 – Direct effect coefficient for H4 ... 36
Table 22 – Model summary for H5 and H10 ... 37
1
1. Introduction and Topic Relevance
Relationships between consumers and brands are a topic that is in an incessant discussion, due to rapid technological innovation and the ease of information sharing. This will be an ever-changing interaction that will never find an optimal approach. Offering a good product is no longer enough. The buying process no longer starts at the time the value exchange happens, it begins way earlier than this practical part. The utilitarian content of acquiring a product/service is increasingly seen as secondary, to the detriment of its hedonic counterpart (Hirschman and Holbrook 1982).
Brands play a big part here. All their effort revolves in pleasing and making them more desired than the rest of the field. They aim to take their consumers to such a high level of affinity that, for some authors, can be compared to interpersonal love(Shimp and Madden 1988, Whang, Allen et al. 2004, Sirianni and Lastovicka 2011). This threshold is what is more commonly referred to as brand love, a very actual topic of research (Sirianni and Lastovicka 2011, Batra, Ahuvia et al. 2012, Rossiter and Bellman 2012).
It is of greater interest on the part of the brands to focus their efforts in this direction because some of the advantages of a "passionate consumer” may be manifested in the form of: a greater predisposition to rebuy (Carroll and Ahuvia 2006), positive word of mouth (Carroll and Ahuvia 2006, Munnukka, Karjaluoto et al. 2016) and also, a greater willingness to pay a premium price (Bauer, Heinrich et al. 2009, Albert and Merunka 2013).
The term "anthropomorphism" comes from psychology and is the phenomenon of imbuing non-human agents with human characteristics (such as emotions, intentions, or motivations)(Epley, Waytz et al. 2013). Although this term is used in a perspective of recognizing certain characteristics to inanimate objects (as in the shape of a car’s headlights who looks like a pair of eyes), there is another concept that derives from the previous one: mentalizing (Willard and Norenzayan 2013). Mentalizing is the tendency to attribute human characteristics to several things that are not human. Curiously, human beings love to atrribute human features to brands (Kiesler 2006, Aggarwal and McGill 2007, Delbaere, Phillips et al. 2011).
Even more curious is that, one of the catalysts of brand love is, when a brand, through its strategic plan, successfully promotes the values by which its consumers are driven, making them identify even more with it (Batra, Ahuvia et al. 2012). Therefore, if consumers "bring
2 their favourite brands to life”, they are to some extent comparable to humans. And if there is one thing that is intrinsic to the human condition is error: to err is human.
When we like a person and that person hurts us, it is much more intense than if we were a person with whom we do not share as much affinity (Grégoire and Fisher 2008). When we really like something and it fails us, we are doubly disappointed. The barrier between love and hate is extremely tenuous, and what we love in one moment, we might be hating in the next. Psychologically, hatred is not the absence of love, nor its opposite, as is commonly discussed. In fact, love and hate are highly related and this can be seen in the ease with which a loving relationship can turn into disproportionate hatred (J. Sternberg 2003). It is highly desirable for brands to build good relationships with their consumers (Keller 2001). However, this can be a double-edged sword. Research on whether creating good relationships can lead to anti-brand behavior by consumers presents very disparate results (Johnson, Thomson et al. 2011). Whilst good relations with consumers can offer advantages for brands, the risks to which they are exposed are still relatively unknown topics (Johnson, Thomson et al. 2011). A consumer who once was one of the biggest lovers of a brand, can easily become his worst enemy and not only a marginal decrease in sales volume. One of the consequences of brand love is the willingness and predisposition to invest resources other than money, such as time or energy (Batra, Ahuvia et al. 2012). In this sense, if a consumer with this level of commitment is confronted with a side of the brand that is not accustomed or with which is unable to relate to (ideological differences) (Kozinets and Handelman 2004) or even the brand’s own personality (Aaker, Fournier et al. 2004)), it is normal that this consumer does not respond well and even, in extreme cases, feels betrayed. The good relationship that has been built could be the root of many undesirable problems (Grégoire, Tripp et al. 2009) and contrarily to what is expected, the brand is in a delicate position, dealing with a consumer who feels insecure and ashamed (Johnson, Thomson et al. 2011), ready to retaliate much more pro-actively than any consumer with a weaker consumer-brand relationship.
According to (Grégoire and Fisher 2006), when the consumer-brand relationship is strong and the brand commits some kind of error, consumer reaction may take two forms: on the one hand, the consumer does not take what has happened as relevant and stands on the side of the brand, event ("love is blind"); on the other hand, when the brand fails to correct its
3 error, the consumer takes what happened to heart and starts to hate the brand ("love becomes hate").
Given that a lot of studies focus on the recovery relationship that can be built on a customer who hates a brand and ways to make him fall in love again, this research will go on an opposite direction. The main questions this study aims to answer are:
• Does Brand Love previously experienced softens the creation of a Brand Hate Relationship?
• When there is a Brand Hate relationship, does previously experienced Brand Love alleviate the repercussions?
To this end, the study was developed by asking respondents to answer an online survey. In order to analyze the data obtained from 207 valid answers, a quantitative methodology based on a model that relates previous behaviors to a hating relationship with a given brand and the consequences that these behaviors may cause, adding Brand Love as moderator for those relationships. The model in question was presented by (Zarantonello, Romani et al. 2016). This study is divided in four parts. Initially, the introduction and pertinence of the theme is presented, addressing the relevance of the theme, the gap found in the literature regarding relationships of this kind and its main objectives. Following the first chapter, the literature review will be presented regarding the concepts of Brand Hate and Brand Love, their antecedents and consequences. In the third part, the sample is described and the factor analysis of the variables is made. On the same point, we will also explain the empirical study, which exposes the questions and the research context, the respective theoretical model and the research methodology. Finally, chapter four presents and discusses the conclusions and limitations of the present study, as well as suggestions for future investigations.
4
2. Literature Review
Relationships that consumers establish with brands are dynamic (Langner, Bruns et al. 2016, Zarantonello, Romani et al. 2018), contrarily to what several studies, with meritorious contributions to the matter of branding, that were formulated based on a more static assumption of these relationships (eg. (Batra, Ahuvia et al. 2012, Rossiter and Bellman 2012, Zarantonello, Romani et al. 2016, Hegner, Fetscherin et al. 2017). The first impression with a brand is different for each consumer. Each person values different things and perceives this initial contact differently, which causes different consumers to have different levels of brand affection, from the start. However, after this initial contact, the relationship continues to develop and, over time, becomes more complex and the attitude towards the brand begins to take a more defined shape.
Like A. Fishbein and Ajzen (1975) said, attitude is the amount of affection that nourishes for or against something. This attitudes, as A. Krosnick and Petty (1995) referred, have four characteristics: they are persistent over time, resist change, have a strong impact on information processing and behavior. The stronger the attitude of a consumer towards a brand, the more pronounced and obvious these characteristics are. In the context of this study, the attitudes that interest us are the most intense, that is, the most positive and the most negative, brand love and brand hate, respectively. It is also important to mention that attitude towards the brand is different from the feelings caused by it. Feelings are transitory while attitude is lasting (Spears and Singh 2004).
2.1. Brand Love
Since Shimp and Madden (1988) introduced the topic of brand love to the World, this has been under the radar of several brand managers (Albert and Merunka 2013). The study of Thomas Shimp e Thomas Madden, among others, more recently like Langner, Bruns et al. (2016), have established a comparison between a loving relationship between two human beings with the relationships that consumers establish with brands, through the triangular love theory (J. Sternberg 1986). However, according to Batra, Ahuvia et al. (2012), there are different kinds of love, and while it is possible, for example, to associate the desire created by the products/services offered by a certain brand we love, parental love is a completely different kind of love that cannot be replicated. Love as emotion is a singular feeling similar to affection (Richins 1997). When we talk about a loving relation we are referring to something that endures, does not have a momentary aspect and is imbued with several
5 affective, cognitive and behavioural episodes that happen over time (Fournier 1998). The problem with this analysis is that, while some studies focus on love as an emotion, others mention love as the one that exists on a lover’s relationship. It’s also important to point that the distinction between the two is rarely pointed out (Batra, Ahuvia et al. 2012).
Beyond this theoretical current based on triangular theory, other approaches define that Brand Love consists of passion, belonging, positive emotions and declarations of love towards the brand (Carroll and Ahuvia 2006). However, this conceptualization is one-dimensional and may not be able to comprise all the complexity that a feeling like love entails (Albert, Merunka et al. 2008).
Finally, we have the chain of thought that considers Brand Love as something multidimensional and that must be analysed in several layers. Batra, Ahuvia et al. (2012) points out that a consumer's love for a brand consists of 7 dimensions: perceived functional quality – there are no customer that can feel love towards a brand if he does attribute good qualities to the brands’ products/services; self-related cognitions – if a brand is able to make the customer self-relate with their offer they are aiming straight to his heart; positive affections and negative affections (the reverse of the first one) – a brand that is capable of generating good affectivity in a consumer (and the absence of bad cognitions on the other side) will have an above average level of intimacy compared to the competition; satisfaction – you can have a satisfied customer that does not feel love for a brand but you can’t have a customer in love with a brand without feeling satisfied; attitude strength – a brand must make the customer have intense feeling towards their products/services, otherwise they won’t ever make it out of the neutral undesired threshold; loyalty – a consumer with preferential on a brand over the rest is a good indicator that he is in love.
Regarding this study, we will be using this last definition when addressing Brand Love related topics.
2.2. Brand Hate
While marketing research has focused heavily on the phenomenon of positive feelings that consumers share with brands (such as brand liking (Spears and Singh 2004), brand devotion (Pichler and Hemetsberger 2007), brand passion (Albert, Merunka et al. 2013) and brand love (Carroll and Ahuvia 2006, Batra, Ahuvia et al. 2012, Rossiter and Bellman 2012)), the negative counterpart does not share the same spotlight (Fetscherin and Heinrich 2015),
6 despite the research provided by different areas (such as consumer behaviour (Banister and Hogg 2004), neuroscience (Zeki and Romaya 2008) and psychology (A. Ito, Larsen et al. 1998)). A person is more likely to remember a negative event over a positive one, and also to be more prompt to share negative experiences rather than positive experiences (Baumeister, Bratslavsky et al. 2001).
To understand what the brand hate is, it is necessary to analyse hatred as a feeling, through the lens of psychology. Roughly 50 years, the literature on emotions, rarely regarded hatred as a primary emotion (Arnold 1960). Few years after that, an article where 525 different terms for emotions are taken into account shows up and we can finally find hatred as a subcategory of hostile, abhor and antipathy (Storm and Storm 1987). Recently, an approach that takes hatred as a more powerful emotion, we are told that it is constituted by three components: repulsion and aversion, anger and fear, disdain (J. Sternberg 2003).
This feeling can arise in several different ways. According to J. Sternberg (2003), any form of hatred is created by combining any of the three components. It may come up due to a violation of the rights relating to the freedom of an individual or a community. Although this is one of the main catalysts of hate, other scholars point out some more possible causes. Aumer (2007) points out 6 main causes for hate: unpleasant personality – a personality whose drivers and values don’t correlate with the ones shared by the hatting individual; lack of respect – inconsideration and misconduct; treason; psychological or physical attacks; hate target – reciprocating hate because individuals perceived inequity or that the target hated them first; injury susceptibilities – when individuals get into a situation where they could have been hurt.
The ways in which people digest this emotion are also quite distinct. According to (Zarantonello, Romani et al. 2016), 3 types of strategy can be identified as ways of managing hate: attack strategies, detachment strategies and confrontation strategies.
Attack strategies occur when hate is associated with the desire for destruction, with the purpose of harming and devaluing the target (J. Sternberg 2003, Tileaga 2015).
In detachment strategies, hate is seen as a waste of time and an unnecessary energy expenditure. The individual tries to suppress the feeling and deal with the situation as if nothing happened (Aumer 2007).
7 Confrontation strategies approaches use hate as justification to confront the target and seek for the justice they deserve (Aumer 2007). The main difference between confrontation and attack strategies is that, even though in both strategies the individual is looking for some kind of brand devaluation, in confrontation strategy the hating subject confronts directly the brand, without fear of them recognizing him and making sure they know who he is and what he is looking for; in attack-like strategies, the individual acts behind the scenes.
The definition of brand hate is recent and, since 2009, several definitions have been presented by different researchers, as we can notice in the Table 1.
Table 1 – Brand Hate definitions
Brand Hate Definitions Authors
"The need for a consumer to punish and harm companies for the damages they caused". Here, the term prejudice is seen as "the need for a consumer to cut off all interactions with the company".
(Grégoire, Tripp et al. 2009)
Brand Hate is a strong opposition to a brand by a consumer that is mostly manifested by vindictive actions derived from critical incidents experienced.
(Johnson, Thomson et al.
2011) “True brand disgust”. Brand Hate is used to describe a situation in
which, the consumer is obliged to use a particular brand, to be a customer of a certain company because there aren’t any other options, being unable to change a rival company (for example, when a company detains a monopoly over some type of service).
(Alba and Lutz 2013)
"The deliberated intention to avoid or reject a brand, evidencing
this aversion" (Hultén, Bryson et al. 2013)
Brand Hate consists of two components: active Brand Hate (fed by anger, aversion and contempt) and passive Brand Hate (which is driven by fear, shame, dehumanization, and frustration).
(Zarantonello, Romani et al.
2016)
For the purposes of this study, we will be using the last definition present on the table above when addressing Brand Hate related topics, given that it is formulated on the basis of a multidimensional study, offering a broader view on the subject.
8
3. Hypotheses Development
3.1. Antecedents of Brand Hate
In the literature concerning brand hate antecedents we can find 3 main drivers.
Corpoate Wrongdoings
Ideological incompatibility, as presented by Hegner, Fetscherin et al. (2017), is related to badly perceived behaviors by the brand. This can be related to moral misconducts, badly perceived communication or a bad brand set of values. The corporate wrongdoings are very contextual-dependent, given that they are highly sensitive to the set of values present within a specific society (Lee, Motion et al. 2009). That said, consumers perceive ideological incompatibility regarding subjects like human rights’ disrespect , environment hurting actions and unethical practices (Sandıkcı and Ekici 2009). All of those behaviors go against the intrinsic social responsibility that brands should be promoting (Zarantonello, Romani et al. 2016). Hegner, Fetscherin et al. (2017) points out that ideological incompatibility is the strongest propeller of brand hate.
Therefore, we hypothesize that:
H1: Corporate Wrongdoings has a positive effect on Brand Hate.
Violation of Expectations
When consumers try a new product or service, they always do it with some kind of expectations in mind. Consumers chose brands for a lot of different reasons but, the main one, is that they expect that, given their budget, that brand will have a better performance than the others on display (Lee, Conroy et al. 2009). If the consumer expectations meet or exceed the actual performance of what he bought he will often be satisfied. On the other hand, when negative disconfirmation occurs he will be really unpleased (Lee, Conroy et al. 2009) and that might be the start of a Brand Hate relationship (Zarantonello, Romani et al. 2016).
Therefore, we hypothesize that:
9
Symbolic Incongruity
Symbolic Incongruity or “Taste System”, as Zarantonello, Romani et al. (2016) presents in his article, is the third antecedent of Brand Hate mentioned in this study. Taste system is the negative perception of a brand (i.e., negative brand image) and the people that use that brand, the incongruity between the symbolic meanings of a brand and the prospects of a consumer (Hegner, Fetscherin et al. 2017). The theory of disidentification suggests that people can develop a self-concept by disidentifying themselves with brands that are inconsistent with their own image (Lee, Motion et al. 2009).
Given that this is a very subjective and complex subject to analyze, we are not going to include it in our research, focusing on the other two antecedents mentioned.
3.2. Outcomes of Brand Hate
With regard to the literature concerning the consequences of the brand hate we can identify three different emerging behaviours.
Negative Word of Mouth
Negative word of mouth is the extent to which an individual speaks or writes poorly about a brand, motivated by negative feelings that make him feel the need to externalize due to bad treatment (Bonifield and Cole 2007). This concept can be divided in two types: private complaining (in those cases where the consumer only talks negatively about the brand to his family and circle of friends) and the public complaining (where the consumer manifests his negative opinion on website or social media for everyone to see) (Zeithaml, Berry et al. 1996). Therefore, we hypothesize that:
H3: Brand Hate has a positive effect on nWOM.
Negative Consumer Complaints
The customer manifests in direct actions and complaints to brand’s employees, stealing from the brand or damaging the brand’s property. J. Sternberg (2003) argues that, hate triggers people to shorten the distance to the object of hate and to retaliate for the wrongdoings the brand has committed. Therefore and, in line with other researches, we consider negative consumer complaints as an outcome for Brand Hate (Grégoire, Laufer et al. 2010, Zarantonello, Romani et al. 2016).
10 The main cause for this, is not a service failure or the product itself, it’s actually the failed service recovery. Things don’t go right 100% of the time, there are things brands can’t control and, most of the time, the consumer is aware of that. That said, he is also expecting the companies to come through and reward their consumers for the failed experience (Ward and Ostrom 2006).
Therefore, we hypothesize that:
H4: Brand Hate has a positive effect on Consumer Complaining.
Cease/Decrease interactions
This type of behaviour implies two different approaches: brand avoidance and brand switching. Even though the concepts are distinct, both of them lead to non-consumption (Hegner, Fetscherin et al. 2017). The first one is conceptualized as “a desire for avoidance is defined as customers’ need to withdraw themselves from any interactions with firms” (Grégoire, Tripp et al. 2009). The second one, unlike brand avoidance where the consumer completely ceases consumption of that type of product/service due to the bad relations cultivated with the brand, he simply changes to a competing brand (A. Dodson, Tybout et al. 1978).
Therefore, we hypothesize that:
H5: Brand Hate has a positive effect on Patronage Reduction/Cessation.
3.3. Antecedents of Brand Love
A key criterion for a consumer to feel passionate about a brand is satisfaction. Although not all satisfied consumers are in love, there is no passionate consumer who is not satisfied(Carroll and Ahuvia 2006, Roy, Eshghi et al. 2013). Gammoh and Long‐Tolbert (2012) argues that a successful service delivery experience has a strong impact on the formation of brand love because this good impression results in a feeling of gratitude and camaraderie, a good impression that is achieved through good communication between the consumer and the employee who attended the customer (Yim, Tse et al. 2008). Not only in services, but in general, positive experiences with good emotional load are good drivers of brand love (Roy, Eshghi et al. 2013). Ahuvia (2006) states that, pleasure, confidence, esteem and achievement predict Brand Love. In order for a brand to be loved, it must be valued and taken in high regard (Batra, Ahuvia et al. 2012).
11 Most consumers have a long history with brands that they love (Albert, Merunka et al. 2008, Ahuvia, Batra et al. 2009) and it is possible to see the importance of these when analysing the time that consumers spend thinking and getting in touch with those same brands (Batra, Ahuvia et al. 2012). They help consumers expressing their identity (Munnukka, Karjaluoto et al. 2016) and, when the brand demonstrates sharing the same values as the consumer concerned, their relationship becomes more solid (Carroll and Ahuvia 2006, Ahuvia, Batra et al. 2009). Brands can reflect what the consumer is, what he aspires to be and what he desire to become (Batra, Ahuvia et al. 2012). It is also important to note that higher levels of brand love are registered when the consumer is part of a community of other brand lovers (Albert and Merunka 2013).
3.4. Outcomes of Brand Love
Different authors reported different behaviours associated with the outcomes of Brand Love, as can be seen in the Table 2.
Table 2 – Brand Love Outcomes
Brand Love Outcome Authors
Increased Loyalty to the Brand. 2005, Kaufmann, Loureiro et (Thomson, MacInnis et al. al. 2016)
Greater repurchase commitment. (Carroll and Ahuvia 2006)
Strong desire for the brand and willingness to maintain
that affinity. (Batra, Ahuvia et al. 2012)
Higher predisposition for positive word of mouth.
(Carroll and Ahuvia 2006, Batra, Ahuvia et al. 2012, Munnukka, Karjaluoto et al.
2016) Promotion of positive attitudes towards the brand
through memories and nostalgia, making the consumer
dream. (Albert, Merunka et al. 2008)
Negative word of mouth resistance. (Ahuvia, Batra et al. 2009) Predisposition to forgive the brand for actions that are
not in line with the behaviour to which the consumer is
accustomed. (Bauer, Heinrich et al. 2009)
12 Willingness to invest non-monetary resources, such as
time or energy. (Ahuvia, Batra et al. 2009, Batra, Ahuvia et al. 2012) A consumer who achieves love for a brand, shows a greater predisposition to forgive the brand for its mistakes (Bauer, Heinrich et al. 2009) and also a greater resistance to bad critiques by third parties about the brand they value (Ahuvia, Batra et al. 2009), something that does not happen in consumers who take a neutral position before the brand. These consumers are building a relationship with the brand, spending time talking about it to those whom they cherish (Carroll and Ahuvia 2006), building memories and dreaming next to this (Albert, Merunka et al. 2008). As such, it is to be expected that to break a relationship with this level of intimacy requires something stronger than what could drive away a consumer without ties to the brand. That said, it is expected that consumers who demonstrate Brand Love, who identify with brand values, who have the brand in high consideration, might be sensitive to experiences where his usual expectations might not be fullfiled. This breach of expectations here might not be a one big terrible episode. It may also be the accumulation of several events of a smaller magnitude which, over time, become relevant when taken together (Johnson, Thomson et al. 2011).
One of the outcomes mentioned above is a greater predisposition on the part of consumers to invest their time and energy to promote the brand they love (Ahuvia, Batra et al. 2009, Batra, Ahuvia et al. 2012). Given the emotional and psychological bond that consumers can create with brands, it seems reasonable to suggest that the ending of such relationships may result in a long-standing bitterness that manifests itself in actions against the brand (Johnson, Thomson et al. 2011). When these consumers are confronted with actions that are not in line with what they are accustomed to, they will experience shame, humiliation and, in extreme cases, even anger, feelings that tend to lead to attack or confrontation strategies (J. Sternberg 2003). As such, it is expected that consumers with a greater meaningful involvement with brands (consumers that attained brand love previously) might adopt strategies of attack and confrontation, to the detriment of passive strategies, when a bad episode pops up (Johnson, Thomson et al. 2011). As such, the number of possible negative word of mouth events is expected to be higher in consumers who have felt embarrassed and humiliated and higher numbers of protests and complaints in those who have experienced rage. In consumers where emotional and psychological involvement is weaker or non-existent, it is to be expected that, if there is a turning point and the consumer starts to hate the brand, he does not have enough reasons to want revenge or even feel the need to express
13 himself negatively (Johnson, Thomson et al. 2011). For this type of consumer, it is easier to cease relationships and replace the brand with another and, as such, it is expected that the adoption of a passive strategy, in this case the cessation of relations with the brand, will be the most frequent behaviour.
Therefore, we hypothesize that:
H6: Experienced Brand Love has a moderating effect on Corporate Wrongdoings. H7: Experienced Brand Love has a moderating effect on Violation of Expectations. H8: Experienced Brand Love has a moderating effect on nWOM.
H9: Experienced Brand Love has a moderating effect on Consumer Complaining.
14
4. Methodology
4.1. Research model
The model presented in Figure 1 is the base model we will use in order to develop ou research model.
By adding the variable Brand Love as moderator for both, antecedents and outcomes of Brand Hate we were able to create our research model, as it is possible to see in Erro! A
origem da referência não foi encontrada..
Figure 1 – Antecedents and Outcomes of Brand Hate Model Source: Zarantonello, Romani et al. (2016)
15 .
4.2. Methodology
Since this study is based on a deductive approach, focusing on a theoretical basis to explain the relations (or non-relations) between the various proposed variables, the research will be based on a quantitative methodology. Respondents will answer a set of survey questions to understand their level of hatred for a mentioned brand, the reasons for that hatred and the way they dealt with it. Thus, it will be possible to verify the proposed relationships through hypotheses via statistical treatment.
To analyse and validate the theoretical model previously proposed, we used the IBM SPSS Statistics 26 software using Hayes' Process Macro, relying on the principles of ordinary least squares regression (Bolin 2014).
4.3. Data Collection
As mentioned, given the need to create correlations and in order to analyse the results from a wider angle, it was decided to use an online questionnaire, to obtain the sample we needed. The questionnaire contains closed response questions order to increase efficiency and speed as it is possible to collect many responses in a short time(Saunders, Lewis et al. 2000). This type of study is one of the most widely used (Malhotra and Df 2007). It also contains some open answer questions, in order to provide some additional insight over specific cases. These types of questions are very helpful in the way that, they provide some good examples to illustrate some specific behaviours. It is also proven that they increase the response rates of questionnaires, given that the respondent gets more involved with the topic he is being addressed and feels more freedom to express his feeling in a more concrete way (O'Cathain and Thomas 2004).
4.4. Questionnaire’s structure
The introduction to the questionnaire will be brief and incisive, without mentioning any kind of concept that is central to the study, thus preventing the occurrence of the common method bias (Podsakoff, MacKenzie et al. 2003)
In the survey, we instructed respondents to first think about a brand that they hate, preferably one that they loved in the past. After that, we asked them to rate three items on overall hate toward the brand (adapted from a four item scale used by Zarantonello, Romani et al. (2016)) by the use of 7-point Likert scales (1 = “strongly disagree” and 7 = “strongly agree”).
16 In the next part, if the respondents picked a brand they previously love, they would have to respond to an eight item scale adapted from Bagozzi, Batra et al. (2015) to validate if they actually felt love or merely liking for the brand by the use, once again, of 7-point Likert scale (1 = “strongly disagree” and 7 = “strongly agree”).
The third block is related to brand hate antecedents, where we’re only considering two main reasons, adapted from a three scale item from Zarantonello, Romani et al. (2016), using another 7-point Liker scale.
After the respondents rated the antecedents that led them to hating the brand they mentioned, they were asked to write a little summary of the episode, or episodes, that triggered their discontent.
The last block is related to the outcomes from the hate generated towards those brands and the type of behaviours consumers might adapt given their specific situation. We are considering three different behaviours and a three scale item for each one of them, all adapted from Grégoire and Fisher (2006).
To wrap up the survey, sociodemographic questions were asked, in this case: sex, age and school level. Even though the three variables we are taking into consideration are not very intrusive, some respondents might feel like they are intrusive and we don’t want to scare them away. Those questions are also easier to answer so the respondents don’t feel as much fatigue and that’s why they come up in the end (Albert, Tullis et al. 2010).
4.5. The Sample
In order to be able to analyse different profiles, a sample must be used. This sample will provide data that can be used to draw conclusions about the behaviours under study. Non-probabilistic sampling was the chosen option. Although it does not guarantee a representative sample, it is a simple method to put in place and with little to no burden, both in time and resources (Malhotra and Df 2007).
The sampling technique chosen was convenience sampling, where the sample elements are selected for their convenience, and complemented with the snowball effect, where respondents share with individuals close to them, in order to increase the sample.
The sample used was obtained by sending the survey via email to all colleges of the University of Porto and making some individual contacts, between June 14 and 25, 2019.
17 It is recommended that the number of observations is, at least, 5 times the number of variables (F. Hair, Black et al. 2010). The survey has 26 questions, so the appropriate minimum number would be 130 valid answers. The final number was 207 valid answers obtained; therefore, the minimum value was exceeded.
4.6. Data Analysis
In order to answer the proposed research questions, a deductive approach was the chosen one. Focusing on the theoretical basis proposed by the literature to explain the relationships between the variables, the hypotheses of this study were formulated and later submitted to statistical test, thus, confirming (or not) the proposed hypotheses. A quantitative methodology was the chosen approach.
The data were gathered through a Google Form, and spread out via social networks and e-mail.
Initially, using the Excel software, a descriptive analysis, as well as a characterization of the sample, was performed in order to prepare a preliminary analysis of the data.
With that done, a factor analysis was performed. Consisting of an exploratory data analysis technique, it allows to determine the structure of a set of interrelated variables, reducing them to a single factor (Marôco 2014).
For analysis and validation of the proposed theoretical model, we opted for the software IBM - SPSS Statistics using the Hayes' Process macro, relying on the principles of ordinary least squares regression. This macro is extremely easy to use and model 1 is very well suited for moderation models, as is the case. In addition, unlike software that uses graphical demonstrations for structural equation models, this macro can provide results without having to create a path diagram. (Bolin 2014).
Finally, the results obtained were discussed.
4.7. Sample Characterization
Through a descriptive analysis of the demographic characteristics of the 207 respondents, it was possible to verify that the majority of respondents belonged to the female gender 61%, with only 39% being male, as can be seen in Table 3.
18 Regarding the age of respondents, the majority of respondents (75%) are between 18 and 25 years old, followed by the age group from 36 to 65 years of age with a percentage of 14% and, finally, the range of 26 to 35 (11%).
Regarding the educational level of the sample in question, 73% had higher education and 25% finished high school. There are no records of basic education level.
Table 3 – Sociodemographic Data
Sex Age School Level
Male Female 18-25 26-35 36-65 Basic High School
Higher Education
61% 39% 75% 11% 14% 0 27% 73%
In the initial question, also used as a filter question, subjects had to mention a brand they hated and thus, answer the rest of the questionnaire with that brand in mind. There was a great diversity of responses, with 106 different brands registered. The winner was Apple (19 entries), followed by MacDonald’s and Zara (10 entries for both of them). Table 4 shows the most frequently mentioned brands. The full list and also a word cloud, can be found on the attachments 2 and 3.
Table 4 – Hated brands mentioned by respondents
Chosen Brand Quantity
Apple 19 McDonald's 10 zara 10 Nestlé 7 NOS 7 Nokia 6 Adidas 5 MEO 5 Nutella 5 Primark 5 Bershka 4 Nike 4 Samsung 4
When we take a closer look at the full brand list, we can also notice that, some types of products are mentioned more often than others. We can see that, brands within the clothing or shoe industry get 25% of the hatred from our sample. The technology sector 21,26% and the food industry 15,94%, also relevant hate targets. Table 5 shows the sectors indicated more frequently.
19 Table 5 – Type of product related to the hated brands mentioned by respondents
Type of Product Quantity (%) Clothing/Shoes 25,12% Technology 21,26% Food Products 15,94% Cosmetics 9,18% Telecommunications 8,21% Retail 4,83% Other 15,46%
Figure 3 represents the reasons that led each respondent to hate the brand they initially chose. Those answers were analyzed and cataloged in 9 different categories. Each answer could be part of more than one category.
The category with the most weight is “Poor Quality”, with 22% of the overall sample. This category is mostly filled with episodes of bad purchases.
After that, with 16%, we have the “Social Inappropriate Attitudes” category. In this category we see two reprehensible attitudes by a large share of respondents: abuse of workers and child labour exploration.
The “Bad Working Politics” category (13%) is related to brands that operate in the service businesses and that left a bad image through unfriendly employees or because they failed to provide the service were hired to do. A good example of this is that of a participant who pointed out his hatred brand as “Espírito Santo - Autocarros de Gaia”, a public transport company operating in the city of Vila Nova de Gaia, who points out: “Unfriendly employees, constant delays and no good conditions for a comfortable trip.”.
In the “Lack of Environmental and Animal Zeal” category, most registrations relate to brands that test new products on animals. A good example of this is a participant who chose “Nars”, a cosmetic brand, as his hate brand, and says: “Nars was a brand known to be against animal testing, which is why it gained many followers in the US. However, when the opportunity to enter in the Chinese market appeared, by regional law, they had to perform tests on animals. And so, they did. They preferred to earn the money that this expansion would bring, and did not live up to the moral values on which the brand was based.”. This contribution, besides being considered as “Lack of environmental and Animal Zeal” was also included in the “Brand Identity Change” category.
20 The remaining categories are self-explanatory. However, it’s also appropriate to point out that in the “Bad Aftersales Services” category, most registrations are related to telecommunications companies and the poor service provided from the moment the subscription started, either due to long waiting queues or the inability to solve problems.
Figure 3 – Reasons that lead respondents to hate the brands they mentioned
4.8. Descriptive Analysis
In the first phase of data processing, a descriptive statistical analysis was performed, characterizing the variables by observing the mode, mean and standard deviation of the obtained answers. The sampling mode corresponds to the most common value found in a data set - in this case, the most frequent answer in each of the items. Looking at Table 6, we can see that “Brand Hate Antecedents” and “Brand Love Experienced” were the ones that brought together the most representative mode values, indicating that a considerable part of the participants had a high level of brand affection in the past. and also, that they were well aware of the reasons that led them to dislike the brand. In the “Brand Hate Outcomes” section we can see a high disparity, showing in 4 items, the maximum value and in the remaining 5, the minimum value, which leads us to conclude that there are brand hate behaviors that take place more often than others. In the “Brand Hate” part, we see that BH1 reaches the maximum value, BH2 a value of 5 and BH3 reaches the minimum value. This tells us that a considerable part of the participants is well aware that they do not like the
5% 6% 6% 7% 7% 8% 8% 13% 16% 22% 0% 5% 10% 15% 20% 25%
Reasons that lead to Hate
Violation of Expectations Bad AfterSales Service Brand Identity Change Misleading Communication Personal Taste Change Overpricing
Lack of Environmental and Animal Zeal Bad Working Politics Social Innapropriate Attitudes Poor Quality
21 brand, but a good amount of them does not actually dislike it that much to call it hate. Most participants also see no reason to feel the need for revenge on the brand.
Table 6 – Dimension item analysis of: Brand Hate, Experienced Brand Love, Brand Hate Antecedents and Brand Hate Outcomes
Questions Mode Mean Standard Deviation Brand Hate
BH1: I don’t like this brand. 7 5,52 1,51
BH2: I hate this brand. 5 4,03 1,77
BH3: I would like to get revenge on this brand. 6 4,97 1,45
Experienced Brand Love
BL1: Using products/services from this brand used to
show something of me as a person. 5 4,48 1,79
BL2: Using products/services from this brand used to
make me feel good. 6 4,90 1,74
BL3: Using products/services of this brand used to give
my life meaning. 6 3,86 1,89
BL4: Without noticing, I caught myself daydreaming about
this brand. 1 3,37 1,94
BL5: I was willing to spend more money than what should
be reasonable to be able to use this brand over another. 6 4,07 2,15 BL6: I used to wish to use this brand’s products/services. 6 3,85 1,91 BL7: The products/services of this brand used to be a
perfect fit for my taste and preferences. 6 4,49 1,85
BL8: I used to feel emotionally connected to this brand. 4 3,92 1,88
Brand Hate Antecedents
CWD1: The products/services of this brand are
produced/provided in a reprehensible manner. 7 4,96 2,19
CWD2: This brand had improper conduct regarding the
preservation of the environment and its sustainability. 1 3,06 2,26 CWD3: This brand had improper conduct regarding social
issues. 7 4,15 2,57
VEX1: Given the brand in question, I expected better of
the products/services they featured. 7 4,96 2,07
VEX2: The products / services of this brand had an
inappropriate price for their quality. 7 4,35 2,04
VEX3: Given what I knew from the competition, I
expected more from this brand’s produtcts/services. 7 4,97 2,49
Brand Hate Outcomes
NW1: I told my family and friends how bad I feel this
brand is. 7 4,46 2,05
NW2: I did negative reviews of this brando n on-line
platforms. 1 3,77 2,51
NW3: When I noticed my friends or family were about to buy products/services from this brand I tried to change their mind.
1 3,16 2,44
PR1: I don’t want to spend any more money on this
brand. 7 6,14 1,58
PR2: I try to have no connection of any kind with this
brand (publicity, for example). 7 6,03 1,51
PR3: If I must user products/services from this brand, I’ll
22 CP1: I felt the need to make the brand representatives
have a hard time. 1 2,15 1,85
CP2: I felt the need to be unpleasant to the brand
representatives. 1 2,06 1,83
CP3: I felt the need to make someone of the brand pay
for their bad performance. 1 1,76 1,56
The sample mean indicates where respondents' answers are concentrated on each item, and is calculated by dividing the sum of responses by the number of participants. The items where the respondents came closer to full agreement were: BH1 (5.52) PR1 (6.14), PR2 (6.03) and PR3 (5.63). With the lowest values, stand out BH3 (1.88), CP1 (2.15), CP2 (2.06) and CP3 (1.76). The sample standard deviation, in turn, is a measure of data dispersion relative to the sample mean. In this investigation, this measure assumes a certain relevance, telling us that the answer to some items are quite heterogeneous. The items with the highest standard deviation values are: CWD3 (2.57), VEX3 (2.49), NWM2 (2.51) and NWM3 (2.44). Considering the sample mean, the results show that, for “Patronage Reduction”, individuals share the highest agreement. The 3 items related to “Patronage Reduction” have the highest mean values and the lowest standard deviations values. It can also be inferred that, in the “Brand Love Experienced” is where there is the greatest heterogeneity of answers, where the mean values are not high for most items and standard deviations assume significant values.
4.9. Model Validation
4.9.1. Factor analysis
After the descriptive analysis, it is necessary to analyse the quality of the adjustment of the study model to the structure of the variables and their correlations. In order to do this, we will run a factor analysis, a pertinent analysis for Structural Equation Models which allows to determine the structure of a set of variables that relate to each other, reducing them to just one factor (Marôco 2014). Through this analysis it is possible to understand if the proposed variables for each of the model dimensions interrelate and form a latent common factor, that is, the respective dimension.
Initially, a reliability analysis was performed through IBM SPSS Statistics 26, using Microsoft Excel 2010 to obtain certain values that couldn’t be directly extracted from SPSS. In order to confirm the reliability of the results, the internal consistency of the variables organized by groups was tested by calculating: Cronbach's Alpha, Extracted Mean Variance (AVE) and Composite Reliability (CR), obtaining the values that can be found in Table 8.
23 Cronbach's Alpha values range between 0 and 1, and only values equal to or greater than 0.6 should be considered. (Pestana 2003).
Pestana (2003) present a reliability scale, associating the range of values that the alpha of Cronbach takes with the quality of internal consistency, as we can see in Table 7.
Table 7 – Cronbach’s Alpha value description
Coeficient Values α Quality of Internal Consistency 0,9 - 1,0 Very Good 0,8 - 0,9 Good 0,7 - 0,8 Acceptable 0,6 - 0,7 Weak < 0,6 Disconsider
As we can see in the table Table 8, “Brand Hate” and “Complaining” variables have a very good consistency quality, with values of 0.903 and 0.924, respectively. Next, with good consistency we have “Negative Word of Mouth” and “Patronage Reduction / Cessation” with 0.806 and 0.893, respectively. In the reasonable consistency range, with 0.751 we have the variable “Corporate Wrongdoings”. Finally, the only variable left is “Violation of Expectations”. The Cronbach’s alpha value of this variable is 0.58, which is, unfortunately, unacceptable. Cronbach's alpha is an indicator that is highly sensitive to the number of items on the scale and generally tends to underestimate the reliability of internal consistency. In non-exploratory studies, we would discard this variable, given that the Cronbach’s Alpha minimum value is not reached. However, when we are performing an exploratory study, it is valid to opt for the composite reliability coefficient (Nunnally 1994). This coefficient offers acceptable values when its result is between 0.6 and 0.7 and it provides a great alternative option for situations like this. (Nunnally 1994). As such, we will support our reliability analysis for the “Violation of Expectations” variable in the composite Reliability value and the Average Variance Extracted, as we will see below.
Composite Reliability is a measure of internal consistency in scale items, much like Cronbach’s alpha (Netemeyer, Bearden et al. 2003). It is an indicator of the shared variance among the observed variables used as an indicator of a latent (Bagozzi 1981). Values for Composite Reliability are acceptable when they are above 0.7 (F. Hair, Black et al. 2010).
24 All values meet this requirement, even the problematic variable, “Violation of Expectations”, which scores a very high value of 0.974, validating this variable for reliability.
That said, we will also consider Average Variance Extracted. AVE is the average amount of variance in indicator variables that a construct is managed to explain (Bagozzi 1981). The values for this coefficient must be greater than 0.5, where AVE indicates the percentage of total variance that is explained by the latent variable. When a factor scores a value of 0.8, this means that the referred variable explains 80% of the variance of the indicators. (F. Hair, Black et al. 2010). All variables under analysis presented values above the 0.5 cutoff, ranging from 52.1% to 97.1%.
Table 8 – Cronbach’s Alpha, Composite Reliability and Average Variance Extracted Analysis Cronbach's Alpha Composite Reliability Average Variance Extracted (AVE) Brand Hate 0,903 0,906 0,764 Brand Love 0,918 0,888 0,636 Consumer Complaining 0,924 0,922 0,798 Corporate Wrongdoings 0,751 0,76 0,527 Negative Word of Mouth 0,806 0,811 0,603 Patronage Recuction/Cessation 0,893 0,918 0,799 Violation of Expectations 0,58 0,974 0,971
After testing the quality of the extracted factors, we moved to the discriminant validity test. Discriminant validity shows that two measures that are not supposed to be related are, in fact, unrelated. If correlations between factors do not exceed the value of .85 (Bagozzi and Yi 1989) and the AVE of each construct is greater than the correlations between them (Bagozzi 1981), discriminant validity is supported (Anderson and Gerbing 1988). Analyzing
25 Table 9, the discriminant validity is confirmed because both criteria are met, i.e. the variables do not overlap.
Table 9 – Discriminant validity Test
Brand Hate Consumer Complaining Corporate Wrongdoings Negative Word of Mouth Patronage Reduction/ Cessation Violation of Expectations Brand Hate 0,874 Consumer Complaining 0,183 0,894 Corporate Wrongdoings 0,501 0,243 0,726 Negative Word of Mouth 0,431 0,279 0,396 0,777 Patronage Reduction/Cessation 0,221 -0,002 0,153 0,102 0,894 Violation of Expectations 0,145 0,145 0,199 0,214 0,104 0,985
Next, in order to gauge the quality of the analysis, we will consider the values of the factor weights (Loadings), the Bartlett Sphericity Test and the Kaiser-Meyer-Olkin Sampling Adequacy Test (KMO). Those tests were performed for each construct on SPSS, with a Varimax rotation. This rotation type is adequate to our study given that the Varimax method aims to obtain a factorial structure in which, one and only one of the original variables is strongly associated with a single factor and little associated with the rest (Marôco 2014). The factor weights must be greater than 0.7 for the structure to be considered well defined, where values above 0.6 are already considered acceptable (F. Hair, Black et al. 2010). The Bartlett Sphericity Test compares an observed correlation matrix to the identity matrix. Essentially, it checks to see if there is a certain redundancy between the variables that we can summarize with a few numbers of factors. The null hypothesis of the test states that the variables are not correlated; the alternative hypothesis states that the variables are correlated enough to where, the correlation matrix diverges significantly from the identity matrix (Marôco 2014). We are looking for a p-value < 0.05, so we can reject the null hypothesis (Marôco 2014).
26 The Kaiser-Meyer-Olkin Measure of Sampling Adequacy is a statistic that indicates the proportion of variance in your variables that might be caused by underlying factors. If the value is less than 0.50, the results of the factor analysis probably won't be very useful (Marôco 2014).
Moving on to factor extraction, we resorted to Eigenvalue. This indicator should have values greater than 1. If so, we can conclude that one (or more) variables explain the total variance of the original variables (Marôco 2014).
We also took into consideration the communalities value. Communalities indicate the amount of variance in each variable that is accounted for. Initial communalities are estimates of the variance in each variable accounted for by all components or factors. For principal components extraction, this is always equal to 1.0 for correlation analyses. Said that, we are interested in the values of the extraction communalities. This value is an estimate of the variance in each variable accounted for by the components. The bigger the values, the better the extracted components represent the variables. According to literature, a value over 0.5 is a good enough indicator (Marôco 2014).
27 Table 10 – Factor Analysis
Constructs Questions KMO Measure of Sampling Adequacy Bartlett’s Test of Sphericity Factorial
weight Eigenvalues Communalities
Requirements > 0.5 < 0.001 > 0.7 > 1 > 0.5
Brand Hate
BH1: I don’t like this brand.
.521 .000
0.865
2.522
0.748
BH2: I hate this brand. 0.886 0.786
BH3: I would like to get revenge on this
brand. 0.994 0.989
Brand Love
BL1: Using products/services from this brand used to show something of me as a person.
.841 .000
0.813
5.110
0.86 BL2: Using products/services from this brand
used to make me feel good. 0.801 0.723
BL3: Using products/services of this brand
used to give my life meaning. 0.864 0.868
BL4: Without noticing, I caught myself
daydreaming about this brand. 0.726 0.722
BL5: I was willing to spend more money than what should be reasonable to be able to use this brand over another.
0.721 0.553
BL6: I used to wish to use this brand’s
products/services. 0.867 0.894
BL7: The products/services of this brand used to be a perfect fit for my taste and preferences.
0.81 0.875
BL8: I used to feel emotionally connected to
this brand. 0.777 0.643
Corporate Wrongdoings
CWD1: The products/services of this brand are produced/provided in a reprehensible manner.
28 CWD2: This brand had improper conduct
regarding the preservation of the environment and its sustainability.
0.748 0.559
CWD3: This brand had improper conduct
regarding social issues. 0.884 0.781
Violation of Expectations
VEX1: Given the brand in question, I
expected better of the products/services they featured.
.628 .000
0.729
1.631
0.531 VEX2: The products / services of this brand
had an inappropriate price for their quality. 0.768 0.59
VEX3: Given what I knew from the competition, I expected more from this brand’s produtcts/services.
0.714 0.509
Negative Word of Mouth
NW1: I told my family and friends how bad I feel this brand is.
.676 .000
0.898
2.166
0.806 NW2: I did negative reviews of this brand on
on-line platforms. 0.825 0.681
NW3: When I noticed my friends or family were about to buy products/services from this brand I tried to change their mind.
0.824 0.679
Patronage Reduction/Cessation
PR1: I don’t want to spend any more money on this brand.
.658 .000
0.958
2.482
0.919 PR2: I try to have no connection of any kind
with this brand (publicity, for example). 0.946 0.894
PR3: If I must user products/services from
this brand, I’ll use them as little as possible. 0.818 0.669
Consumer Complaining
CP1: I felt the need to make the brand representatives have a hard time.
.688 .000
0.967
2.609
0.935 CP2: I felt the need to be unpleasant to the
brand representatives. 0.958 0.918
CP3: I felt the need to make someone of the
29 To get a better visualization of the values presented for the various items of the analysis described above, this table was compiled with all the relevant values. Outputs extracted from SPSS can be found on attachments, from annex 4 through 10.
Starting with the quality analysis, we can see that all the necessary requirements have been met, and it can be stated that: the definition of the structure is good, there is a good correlation between the variables and also a good homogeneity.
Regarding data extraction and the respective Eigenvalue, values greater than 1 were verified in all constructs, validating that the extracted values justify a considerable proportion of the total variable of the original variables.
Finally, the values of communalities are all greater than 0.5 and as such, all extracted components represent well the variables to which they refer.
Finally, we are clear to move forward with the analysis of the proposed model.
4.10. Structural Model Validation
In this chapter we tested the study hypotheses previously presented. For this, we used the SPSS plug-in Hayes’ Process. This plug-in includes 76 different models for moderation and moderation analysis (Bolin 2014). This said, we ran our hypothesis tests via model 1, given that the relationships we are trying to explain are all of the same kind: an independent variable impacting directly on the outcome variable with a third one (the moderation variable) moderating this relationship (as can be seen in the Figure 4).
Figure 4 – Moderation Model 1 Source: Bolin (2014)
