1. Introduction

In recent years, marketers and academic researchers identified that political ideology can affect not only voting intentions but also consumer decisions, choices, and judgments (Chan & Ilicic, 2019; Irmak et al., 2020). Thus, studies that address political ideology in the context of marketing have increased (Jost, 2017). This is because political ideologies have become more polarized in several countries worldwide, including in Brazil.

In some cases, the association, which may be voluntary or involuntary, of the brand with a politician can lead to boycotts by opposing consumers (In a Brazilian example, the decline in sales of the Madeira chain, or the cancellation of Smart Fit network subscriptions) (Brito, 2020). However, in other cases, the brand that explicitly supports a politician may come out unscathed (e.g., Havan) (Pires, 2018). It is not known for sure how this process occurs, and more studies on this subject must be conducted.

Previous studies identified the positive effects of engagement on consumer behavior (McClure & Seock, 2020; Wen, 2021). However, we believe that the involvement of an individual with a brand can arouse strongly negative feelings (such as hatred or contempt) (Hung & Lu, 2018) in scenarios where the brand adopts a social posture divergent from that which they understood as correct (Zarantonello et al., 2016). This process would cause a reduction in the consumer’s purchase intention. The characteristics of consumers influence their responses in different contexts (Pantano et al., 2017; Pentina et al., 2018). In this paper, we tested the moderating effect of regulatory focus on the described social phenomena linked to purchasing decision-making in contexts of political idealization.

The relevance of studying this personal characteristic in this context is justified since individuals with a preventive regulatory focus have more conservative characteristics, and those with a promotional regulatory focus can make more choices based on greater openness to new experiences (Pentina et al., 2018). We based our hypotheses on social identity theory (Tajfel et al., 1979; Hetherington, 2009) and on findings from previous studies that identified that individuals with a conservative political profile are more traditional, prefer to remain in known territory, are more resistant to change, and avoid uncertainty (Jost et al., 2003; Lewis et al., 2021). Furthermore, conservatism is related to a greater attachment to tried-and-true brands (Chan & Ilicic, 2019; Lewis et al., 2021). Likewise, more liberal individuals (left-wing polarized) will present a greater intention to switch the brand for another, in contexts of asymmetry regarding the political support expressed by a brand in relation to their personal beliefs.

To test the hypotheses, we conducted a survey with stimulus which aimed to identify the moderating effect of the individual regulatory focus on the relationship between ideological polarization and the intention to purchase a brand in a context of transgression, that is, the association of the brand with political opposition to the declared consumer’s ideology. Moreover, we tested the mediation of brand involvement and brand hatred generated by the incongruity between the two ideologies.

2. Theoretical framework and hypotheses

In this section, we present the constructs of this study and the hypotheses tested empirically.

2.1. Political polarization: conservative versus liberal

Henri Tajfel’s greatest contribution to psychology was the social identity theory. Social identity is an individual’s sense of who we are, based on affiliation(s) to one or more groups. Tajfel et al. (1979) proposed that all groups (e.g., social class, family, soccer team, etc.) to which people belong are an important source of pride and self-esteem. Groups give us a sense of social identity: a sense of belonging to the social world.

We usually divide the world into “them” and “us” through a process of social categorization (for example, we classify people into social groups). Tajfel et al. (1979) found that stereotyping (classifying people into groups and categories) is based on a natural human cognitive process. We have a natural tendency to group things together. In doing so, we often tend to exaggerate the differences among groups, and the similarities of characteristics in the same group.

This categorization is known as in-group (us) and out-group (them). The central hypothesis of social identity theory is that members of a group will seek to find negative aspects of an individual outside their group of belonging, improving their self-image (Islam, 2014).

Social identity theory claims that polarization of an individual (or group) is more an emotional characteristic than ideological. Moreover, self-identity, understood as being congruent with a particular group, may a produce positive sentiment for the group with which the person identifies, and a negative one, sometimes even fiercely so, for distinct and oppositional groups (Hetherington, 2009).

The relationship between social identity theory and consumption is already established identifying that ownership of a particular product can symbolically extend the consumer’s self (Belk, 1988). Thus, people may hold the belief that their identity is the sum of their possessions. The more consumers believe in and value their material possessions, the more part of the self these objects become (Belk, 1988). The greater the perceived congruence between aproduct's brand and the consumer’s self, the stronger the slef concept of the individual becomes (Santos & Santos, 2017). Consumers increasingly understand that the self is built through consumption, and that consumption expresses their true self (Ramalho & Ayrosa, 2009).

Often, the effect of personal ideologies on the politics of individuals reveal in turn their personality tendencies and psychological characteristics. Thus, individuals can manifest higher political ideological tendencies towards conservatism, being more resistant to change. Furthermore, more conservative people are more likely to find justifications for the system and the social order than individuals who are more liberal (Jung et al., 2017).

Regarding decision-making, such as purchase process, conservative individuals (politically right-wing) are more resistant to switching brands, for example. However, liberals (left-wing people) are more likely to complain about the brand when facing some dissatisfaction (Jost, 2017; Jung et al., 2017). Thus, the first hypothesis of this research is:

H1. Individuals who declare themselves to belong to left-wing ideology (versus that of the right) will present lesser (versus greater) purchase intention, in the case of brand support for an ideologically opposing politician.

Possibly, political polarization will bring about different results in brand evaluation, depending on the self-congruence of the individual and their involvement with the brand.

2.2. Self-congruence and involvement with the brand

The notion of self-concept is defined as the sum of each person’s thoughts and feelings about themselves and can be taken in two forms: the “real self” and the “ideal self”. The real self describes how an individual perceives him/herself (“I as I am”), while the ideal self-concept explains how an individual wants to perceive him/herself (“the perfect self”) (Choi & Rifon, 2012; Jeong & Koo, 2015). Self-congruence occurs when there is a high level of consistency between the “ideal self” and the “real self”.

Individuals can be led to use a brand to express a self-concept or a concept that they consider ideal forthemselves (Japutra et al., 2019). For example, a person can use a brand that promotes environmental sustainability to show their own agreement with sustainable development (the real self-concept), or use another brand which is considered luxurious to express an ideal for their social life (ideal self-concept) (Islam et al., 2019). In this way, perceived self-congruence, whether real or ideal, leads the consumer to greater involvement with the brand, and to a tendency to defend and choose to purchase that brand.

The expectation of social belonging leads to the creation of greater affective bonds with a brand, when the consumer realizes that other individuals from groups to which he or she wants to belong also admire and consider themselves self-congruent with the same brand (Wallace et al., 2017). This phenomenon generates the most involvement with the brand and may lead to brand loyalty.

Probably, consumers have favorable attitudes towards brands whose images are congruent with their self-images (Richins, 1994), so the greater the perceived self-congruence with the brand, the greater the consumer’s involvement with it (Xu, 2008). Based on this, we elaborated the second hypothesis of this study:

H2a. Self-congruence has a positive effect on brand involvement.

Literature shows that hatred towards the brand can be greater when there is a detachment in the perception of self-congruence, than in a person who did not identify as self-congruent to the brand (Islam et al., 2019). Because of this, there are hypotheses 2b and 2c.

H2b. Self-congruence has a positive effect on brand hatred in the case of brand support for an ideologically opposed politician.

H2c. Self-congruence has a negative effect on brand PI, in the case of brand support for an ideologically opposed politician.

2.3. Self-congruence, involvement, and brand hate

Strong consumer self-congruence can generate greater involvement, which evokes involvement with a brand (Japutra et al., 2018). Managers of different brands hope their consumers establish affective and identificative bonds with their products and services, as these bonds tend to create longer term brand loyalty. However, in the case of transgression, as perceived by the consumer in relation to the brand with which he or she finds themselves self-congruent, the feeling of betrayal can generate brand hate (Hung & Lu, 2018).

Hate is essentially a primary emotion. However, on some occasions, it can be a secondary emotion (Zarantonello et al., 2016). Plutchik (1991), for example, describes hate as a secondary emotion, resulting from the combination of disgust and anger, which are considered primary emotions. According to Sternberg (2003), hate is a multifaceted emotion, based on three components: devaluation, anger, and denial of intimacy.

For most psychologists, hate results from the violation of moral codes (Zarantonello et al., 2016). Sternberg (2003) argues that all the emotions that combine to form hate (disgust, dislike, anger, fear, and contempt) can arise after the violation of individual or community rights. Therefore, these emotions can be perceived as imminent threats to people, to their freedom, their well-being, and their preservation.

Several aspects of this negative emotion have been discussed in marketing (Kucuk, 2016; Zarantonello et al., 2016; Hegner et al., 2017; Zarantonello et al., 2018). Brand hate can result in the desire for revenge, brand avoidance (Grégoire et al., 2009), and the non-purchase of products in the future (Banerjee et al., 2020). Considering these, we hypothesize that:

H3. Individuals with more (versus less) brand hate will declare a lower (versus greater) PI of the brand, in the case of support of the brand to an ideologically opposed politician.

Even though individual self-congruence has a direct effect on hate, we believe that involvement with the brand can also influence this relationship.

2.4. Brand involvement and hate

Consumers distinctly the same product and/or brand based on their levels of involvement (Zaichkowsky, 1985), and self-congruence can lead to greater consumer engagement with the brand. However, there are studies indicating that real congruence (which is related to individual self-concept and real personality characteristics), unlike ideal congruence (related to the social construction of the self), may not influence the generation of attachment and involvement (Huang et al., 2017; Japutra et al., 2019).

With that we propose:

H3a. Individuals more (versus less) involved with the brand will declare lesser (versus greater) brand hate, in the case of the brand supporting an ideologically opposed politician.

H3b. Individuals more (versus less) involved with the brand will declare lesser (versus greater) PI of the brand, in the case of the brand supporting an ideologically opposed politician.

Seminal studies have already established that the influence of personality traits affects consumer behavior (Kassarjian, 1971; Haugtvedt, Petty, & Cacioppo, 1992). Several studies reveal the regulatory focus structure (Higgins, 1997, 1998), which has gained increasing interest in academic literature, as it is related to an impressive diversity of consumption behaviors (see Higgins & Spiegel, 2004). In this study, we sought to verify the effect of the individual’s regulatory focus as a moderator of the process among self-congruence, involvement and hate in the purchase intention of a brand with political polarization antagonistic to consumer’s belief.

2.5. Regulatory focus

The regulatory focus theory is a theory of motivation and self-regulation with significant prominence in consumer research. This theory explains a variety of consumer decision behaviors (Silbiger et al., 2021). According to regulatory focus theory (Higgins 1997), consumers vary in how they see their goals and adopt different ways to try to achieve them (Brockner et al., 2004). Specifically, regulatory focus theory posits two separate types of regulatory guidance, promotion and prevention focus, which consumers adopt while pursuing goals.

Individuals with a promotional focus tend to consider the gain objective, leaning towards risk-taking to achieve this objective (Higgins, 1998; Hüttermann et al., 2018). Contrary to this, , individuals with a preventive regulatory focus aim on “not to lose”, which can make them have a greater intention to stay in inertia or to make the safest possible decisions (Lin & Chen, 2015).

Despite being a personal characteristic, regulatory focus can be activated according to the circumstances (Boldero & Higgins, 2011; Westjohn et al., 2016). Even though Sengupta and Zhou (2007) state that regulatory focus cannot be considered a characteristic of the individual’s personality, there are indications (both theoretical and empirical) that the regulatory focus is a condition that can be both a personality trait, and, depending on a situation, induced into a momentary state (Pham & Avnet, 2004; Kim et al., 2021). Regarding this divergence, a current theoretical line believes that, depending on how the process of socialization and cognitive formation took place, there will be a predominance of one of the conditions. With that, the individual will tend to have a more promotional or a more preventive behavior (Higgins, 1997; Binswanger, 2001).

As already established, consumers can be classified into one of the types of regulatory focus. Accordingly, it is believed that the regulatory focus can be a good moderating variable regarding the purchasing decision relationships to which consumers are exposed (Dodoo & Wu, 2021). Thus, we built the following hypotheses:

H4. In a situation of brand support in preference to an ideologically opposed politician, the individual’s regulatory focus will moderate...

H4a: ...positively (versus negatively) the relationship between self-congruence and PI in promotional individuals (versus preventive).

H4b: ... positively (versus negatively) the relationship between involvement and PI in promotional individuals (versus preventive).

H4c: ... negatively (versus positively) the relationship between brand hatred and PI in promotional individuals (versus preventive).

Figure 1 presents the conceptual model of this research.

Figure 1.
Conceptual model
Source: theauthors

3. Study - The role of political polarization

The main objective of this study was to demonstrate the effect of ideological polarization (before and after political support) on the intention to purchase a brand. To that end, we carried out a stimulated survey, with the presentation of a narrative (storytelling), and measurement of the levels of self-congruence, involvement, brand hate, and regulatory focus of the individual, along with the purchase intention.

3.1. Stimuli

The stimulus of the scenario occurred in two moments. In the first, participants were asked to indicate the brand they most admired, and with which they had a good relationship, with the guidancee “Think of a brand. A brand you admire, with which you have a good relationship and which you buy whenever possible. Now write the name of this brand and two features you admire about it”.

Then, we asked the participants to assess self-congruence, after stimulating ideological polarization. The guidance was “Now, think about the following situation: you saw a [true] news story about your favorite brand. The news said that your favorite brand is funding a politician you don’t like, a politician who goes against all your ideals, meaning a politician who would never get your vote. This politician’s ideas are so contrary to your own that you would never vote for anyone in his or her party!). Finally, participants were asked to answer the remaining items of the scales and fill in their demographic profiles.

3.2. Measures

For all items on the scales of self-congruence (three items by Sirgy et al., 1997), hate (measured through six items by Hegner, 2017), purchase intention (three items also by Hegner, 2017) and involvement (10 items from the personal involvement inventory scale revised by Zaichkowsky, 1994), we used a seven-point Likert scale (anchored on 1=strongly disagree and 7=strongly agree) for measuring. These scales were adopted because: a) they are suitable for measuring the model’s constructs; b) they showed good psychometric consistency in the original studies; and c) they have already been replicated in later studies, with the same consistency levels.

The individual’s regulatory focus was measured through 18 items (proposed by Higgins, 1997), with nine items to measure the promotional regulatory focus and nine items to estimate the preventive regulatory focus. For the measurement, we used the sum of the options performed (-1 for preventive statements and +1 for promotional statements). The Higgins’ scale (1997) is the most used in academic studies in order to estimate the regulatory focus.

Finally, we measured political ideology with one item, using a 4-point categorical scale (1 = clearly left; 2 = more left than right; 3 = more right than left; 4 = clearly right). All items used can be seen in Table 1.

Table 1

Scale items

Source: Adapted by the authors

3.3. Data collection procedures

We sent the data collection instrument online to participants through the QuestionPro platform. The link to access the data collection instrument was sent through the research authors’ virtual social networks. The instrument did not ask for the respondent’s identification, which resulted in the voluntary participation of all. Respondents were also asked to send the link access to their network of contacts. Thus, the sample is considered as non-probabilistic for convenience, and collected using the snowball technique (Silva et al., 2014). Even though non-probabilistic samples do not allow the generalization of results, the collection strategy resulted in an adequate sample, as all participants are voters and are responsible for their purchasing decisions (100%) and most for the home purchases (77.18%).

Data collection occurred in February 2021.

3.4. Data analysis procedures

We used descriptive statistics to analyze the distribution of sample characteristics, and exploratory factor analysis for the identification of the unidimensionality of the items and the multidimensionality of the constructs (Sousa & Herrero, 2021). Therefore, as recommended in the literature, we sought to identify a Kaiser-Meyer-Olkin (KMO) criteria greater than .60, a significant Bartlett’s sphericity test (p<.05), factor loadings greater than .50, and cross-loads less than .40 (Levin & Fox, 2004). As for the internal consistency of the scales, we used Cronbach’s Alpha, with a critical limit of .60 (Malhotra et al., 2014).

We performed the test of difference between the constructs using Student’s t test for independent samples. Finally, for the analysis of direct relationships, moderations, and mediations, we used model 89 of the PROCESS macro (Hayes, 2017). For all analyzes, we used the software SPSS for Windows version 23.

4. Results

The sample of this study consisted of 206 respondents, of which 123 (59.7%) were women. The mean age of the sample is 25.9 years (σ=8.22), and 127 (61.7%) participants were university students. The declared political ideology of the respondents was 126 (61.2%) individuals from the left-wing and 80 (38.9%) from the right-wing.

The most mentioned politicians were President Jair Bolsonaro (n=143), former President Lula (n=23), and São Paulo State Governor João Dória (n=16). The most remembered brands were Nike (n=41), Adidas (n=16), Coca-Cola (n=14) and Apple (n=13). Table 2 shows the results

Table 2

Descriptive analysis of the sample

Source: research data

As expected, because we used previously validated psychometric scales, the exploratory factor analysis of the items proved adequate. The scales of self-congruence, involvement, brand hate and purchase intent were one-dimensional (Table 3).

Table 3

Exploratory Factor Analysis

Source: reesearch data

The analysis conducted using the Student t test for independent samples indicated that there was a significant difference for PI (M_left=4.11; M_right=5.39; t₍₂₀₄₎₌4.927; p<.01), brand hate (M_right=3.32; M_left=2.53; t₍₂₀₄₎₌3.564; p<.01) and involvement (M_right=5.29; M_left=4.42; t₍₂₀₄₎₌4.629; p<.01). This result demonstrated that left-wing individuals reported less involvement with the brand, greater hate and less PI towards the brand in a context of politically oriented asymmetry.

On the other hand, as expected, there was no significant difference in the means of self-congruence (M_left=3.83; M_right=3.91; t₍₂₀₄₎₌.774; p=.440=n.s.) and the regulatory profile (M_left=5 .20; M_right=5.50; t₍₂₀₄₎₌1.084; p=.279=n.s.).

The results still showed no significant difference for PI (M_promotional=4.70; M_preventive=4.43; t₍₂₀₄₎₌0.985; p=.326=n.s.), brand hate (M_promotional=2.88; M_preventive= 3.27; t₍₂₀₄₎₌1.674; p=.096=n.s.), involvement with the brand (M_promotional=4.84; M_preventive=4.59; t₍₂₀₄₎₌1.253; p=.212=ns) and self-congruence (M_promotional= 3.85; M_preventive=3.87; t₍₂₀₄₎=.201; p=.841=n.s.) between the promotional and preventive groups. These results confirm H2a.

To test the other hypotheses, we analyzed the double mediation (involvement and hatred of the brand) in series, moderated by regulatory focus, on the relationship between self-congruence and PI, in the context of a brand’s support to a politician who opposes the ideology of the consumer.

The regressions indicated a direct effect between self-congruence and involvement (β=.288; SE=.1336; 95%CI [.025; .551]; p<.05), corroborating hypothesis H1. The direct effect of self-congruence on brand hatred was also identified (β=.282; SE=.111; 95%CI [.062; .502]; p<.01), confirming H2b. However, H2c was not confirmed (β=.168; SE=.774; 95%CI [-.110; .447]; p=n.s.), as there was no direct effect of self-congruence on CI.

Confirming hypotheses 3a and 3b, we identified the direct negative effects of involvement in brand hatred (β=-.835; SE=.057; 95%CI [-.949; -.721]; p<.01), and positive in PI (β=0.812; SE=0.102; 95%CI [0.609; 1.014]; p<0.01). As expected, we also identified a direct negative effect on the relationship between brand hate and PI (β=-.338; SE=.081; 95%CI [-.497; -.178]; p<.01).

The moderation analysis indicated that individuals who were more promotional (versus more preventive) had lower PI in relation to the brand, in a context of support for a politician who was ideologically opposed to the consumer’s ideology. That is, the regulatory focus moderated both the relationship between involvement and PI (β=-.807; SE=.023; 95%CI [-.126; -.0353]; p<.01), and the relationship between brand hate and PI (β=-.080; SE=.019; 95%CI [-.120; -.041]; p<.01). However, the regulatory focus did not moderate the relationship between self-congruence and intention to purchase the brand (β=.307; SE=.301; 95%CI [-.022; .096]; p=n.s.).

Figure 2 shows the final model of this study.

Figure 2.
Final model
Source: research data

The floodligtht analysis (Spiller et al.,2013) showed that, for individuals with a promotional focus at high levels (JN point= 6.919; 11.65% of the sample), there is no effect on the involvement in PI. Furthermore, the same was observed for highly preventive individuals (JN point= -1.611; 18.44% of the sample), in relation to the effect of brand hate on PI.

5. Results discussion

This paper aimed to identify the effect of ideological polarization on purchase intention and on the generation of brand hate. In short, the objective was to identify the effects of associating the brand with a political opponent of the consumer’s political ideology. Through a stimulated survey, we provide evidence of the direct effect of ideological polarization on purchase intention, in the context of a brand associating themselves with a political opponent of the consumer's ideology. Our study also provides evidence on the effect of self-congruence, brand involvement, and regulatory focus.

The results identified that individuals who politically declare themselves to be more left-wing, in a context of ideological transgression of a brand, tend to hate the brand more and declare less PI than self-declared more right-wing individuals. This is because conservative, right-wing individuals are more resistant to change (Jost et al., 2007), avoid uncertainty and can demonstrate greater involvement with brands (Chan et al., 2019; Jost, et al., 2013).

Furthermore, after the transgression, individuals with a high level of evident involvement can mitigate the feeling of hatred and negative purchase intention. That is, more involved consumers generally commit more resources to the relationship (e.g., money, time, effort) (Lau, & Ng, 2001). Thus, they are more willing to accept compensation, showing less disposition to break the relationship (Sharma et al., 2010; Shiue, et al., 2013).

5.1. Theoretical contributions

The main theoretical contribution of this study is the analysis of the effect of the individual’s regulatory profile - preventive versus promotional (Higgins, 1997; 1998) - as a moderator in the relationship between political polarization and the purchase intention declared by the consumer. Previous studies have shown that preventive individuals are more faithful to the brands they buy, while promotional individuals are more likely to adopt new consumption experiences and brand substitution (Lopes & Veiga, 2019). Thus, we verified whether the preventive (versus promotional) regulatory focus would increase (versus reduce) the PI of individuals declared to be left-wing (versus right), in situations of asymmetry between the political support of a brand and their beliefs individual (and vice versa).

Our findings go further. We found no evidence that consumer political ideology directly affects self-congruence. However, consumers who are self-congruent with the brands report greater involvement and greater hate. At first glance, this result may seem controversial. However, in situations of brand transgression, the individual with greater attachment may feel more betrayed (Hung et al., 2018), devalued (Sternberg, 2003), and may perceive symbolic incongruity, and ideological incompatibility (Hegner et al., 2017; Zarantonello et al., 2018), evoking emotions such as disgust, anger, and hatred (Hung et al., 2018; Plutchik, 1991; Zarantonello et al., 2018).

Previous research has linked individuals’ regulatory focus to their political ideology, linking the focus of prevention with liberalism (Janoff-Bulman, 2009), or conservatism (Chan et al., 2019), which, in our research, it makes more sense. Although there is no direct effect between regulatory focus and political ideology of individuals, our results reinforce the theory that people who are self-righteous, as well as individuals with a preventive focus, tend to need stability, avoiding uncertainties (Ashford & Cummings, 1983; Lanaj, Chang, & Johnson, 2012). Following this theoretical perspective, our study shows that the regulatory focus moderates both the relationship between involvement and purchase intention and the relationship between brand hate and purchase intention. Therefore, individuals with a focus on promotion, in a context of brand transgression, declared greater intention to abandon the brand.

Again, through the results obtained, the arduous task of managers and marketing practitioners becomes evident. Electoral sponsorship, or financing, can be a possible form of democratic participation for an organization, or even a form of “social support” given to a politician or public manager, through public relations actions and other marketing communications. However, as there is a strong rivalry in the ideological polarization in Brazil (and in much of the world, as can be seen in Ezzamel et al., 2007), these actions result in a managerial risk. Even though the individual’s regulatory focus can ease brand hate, aroused by an ideological asymmetry, there is no evidence that focus moderation can fully mitigate this emotion. With that, it is possible to recommend extreme caution in positioning and political support by a brand.

5.2. Management contributions

A brand's caution towards its political positioningis already a contribution that can help marketing managers and administrators in general. Furthermore, even if the moderation of the individual's regulatory focus has not resulted in a process of total mitigation of the hate effect in the PI process in the scenario we stimulated, we consider that the literature indicates the possibility of regulatory focus manipulation (adjustment regulatory framework, as presented by Cesario et al., 2004; Aaker & Lee, 2006) as a way to change, even temporarily, the individual regulatory focus. With this in mind, managers and practitioners can use environmental or communication stimuli as ways to influence regulatory adjustments, in order to enhance the moderating effects played by this variable to reduce the hate aroused by the ideological asymmetry of a possible action of political support.

5.3. Limits, proposal for future research and final considerations

We adopted procedures to guarantee the validity of this study. However, there are limits that must be recognized such as the characteristic of the non-probabilistic sample. Even if non-probabilistic samples are widely used in studies from the field of applied social sciences (Heckathorn & Cameron, 2017; Rahi, 2017), the observed results cannot be generalized. Even though our sample is adequate for analyzing the proposed model, the concentration of young individuals (≤ 25 years old) may have influenced the magnitude of the results. Therefore, one recommendation is the use of probabilistic samples or, if these are not possible, the analysis of data from an older sample as a way to verify any possible difference regarding our findings.

Evidently, hate may not be the only possible mediator of the relationship between involvement and PI. It would be interesting for future studies to analyze the effect of other emotional manifestations (such as frustration, disappointment, or contempt) on the same process.

Finally, with the maturity of the theoretical fields of applied social sciences, the dependent variables of the models studied must increasingly have behavioral characteristics. Hulland and Houstou (2021) reinforced the importance of behavior for academic studies in order to gain external validity. With that in mind, a recommendation for future studies is to replace the purchase intention with a behavioral variable resulting from the moderate mediation process analyzed in this research.

AKNOLEDGEMENTS

The authors are grateful for the relevant suggestions for improvement made by BBR reviewers/editors during the evaluation process of the initial versions of this study.

REFERENCES

Aaker, J. L., & Lee, A. Y. (2006). Understanding regulatory fit. Journal of marketing research, 43(1), 15-19. https://doi.org/10.1509%2Fjmkr.43.1.15

Ashford, S. J., & Cummings, L. L. (1983). Feedback as an individual resource: personal strategies of creating information. Organizational Behavior and Human Performance, 32(3), 370-398. https://doi.org/10.1016/0030-5073(83)90156-3

Banerjee, S., & Goel, P. (2020). Party brand hate in political market: antecedents and consequences. Asian Journal of Political Science, 28(2), 97-121. https://doi.org/10.1080/02185377.2020.1768417

Belk, R. W. (1988). Possessions and the extended self. Journal of Consumer Research, 15(2), 139-168. https://doi.org/10.1086/209154

Binswanger, M. (2001). Technological progress and sustainable development: what about the rebound effect?. Ecological economics, 36(1), 119-132. https://doi.org/10.1016/S0921-8009(00)00214-7

Boldero, J. M., & Higgins, E. T. (2011). Regulatory focus and political decision making: When people favor reform over the status quo. Political Psychology, 32(3), 399-418. https://doi.org/10.1111/j.1467-9221.2010.00814.x

Brito, S. (2020, July 19). Empresas que se posicionaram na política sofrem com ameaças de boicote. Veja. https://veja.abril.com.br/brasil/empresas-que-se-posicionam-na-politica-sofrem-com-ameacas-de-boicote/

Brockner, J., Higgins, E. T., & Low, M. B. (2004). Regulatory focus theory and the entrepreneurial process. Journal of Business Venturing, 19(2), 203-220. https://doi.org/10.1016/S0883-9026(03)00007-7

Cesario, J., Grant, H., & Higgins, E. T. (2004). Regulatory fit and persuasion: transfer from “feeling right.”. Journal of Personality and Social Psychology, 86(3), 388-404. https://doi.apa.org/doi/10.1037/0022-3514.86.3.388

Chan, E. Y., & Ilicic, J. (2019). Political ideology and brand attachment. International Journal of Research in Marketing, 36(4), 630-646. https://doi.org/10.1016/j.ijresmar.2019.04.001

Choi, S. M., & Rifon, N. J. (2012). It is a match: the impact of congruence between celebrity image and consumer ideal self on endorsement effectiveness. Psychology & Marketing, 29(9), 639-650. https://doi.org/10.1002/mar.20550

Dodoo, N. A., & Wu, L. (2021). Regulatory focus and choice: The impact of control perceptions on advertising effectiveness. Journal of Marketing Communications, 27(1), 69-92. https://doi.org/10.1080/13527266.2019.1671477

Ezzamel, M., Xiao, J. Z., & Pan, A. (2007). Political ideology and accounting regulation in China. Accounting, Organizations and Society, 32(7-8), 669-700. https://doi.org/10.1016/j.aos.2006.09.008

Grégoire, Y., Tripp, T. T., & Legoux, R. (2009). When customer love turns into lasting hate: The effects of relationship strength and time on customer revenge and avoidance. Journal of Marketing, 73(6), 18-32. https://doi.org/10.1509%2Fjmkg.73.6.18

Haugtvedt, C. P., Petty, R. E., & Cacioppo, J. T. (1992). Need for cognition and advertising: Understanding the role of personality variables in consumer behavior. Journal of Consumer Psychology, 1(3), 239-260. https://doi.org/10.1016/S1057-7408(08)80038-1

Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Publications.

Heckathorn, D. D., & Cameron, C. J. (2017). Network sampling: From snowball and multiplicity to respondent-driven sampling. Annual Review of Sociology, 43, 101-119. https://doi.org/10.1146/annurev-soc-060116-053556

Hegner, S. M., Fetscherin, M., & Van Delzen, M. (2017). Determinants and outcomes of brand hate. Journal of Product & Brand Management, 26(1), 13-25. https://doi.org/10.1108/JPBM-01-2016-1070

Hetherington, M. J. (2009). Putting polarization in perspective. British Journal of Political Science, 39 (2), 413-448. https://doi.org/10.1017/S0007123408000501

Higgins, E. T. (1997). Beyond pleasure and pain. American psychologist, 52(12), 1280-1300. https://doi.apa.org/doi/10.1037/0003-066X.52.12.1280

Higgins, E. T. (1998). Promotion and prevention: Regulatory focus as a motivational principle. In Advances in experimental social psychology (Vol. 30, pp. 1-46). Academic Press.

Higgins, E. T., & Spiegel, S. (2004). Promotion and prevention strategies for self-regulation. In R. F. Baumeister & K. D. Vohs (Eds.), Handbook of self-regulation: research, theory, and applications (pp. 171-187). The Guilford Press.

Huang, Z., Zhang, C., & Hu, J. (2017). Destination brand personality and destination brand attachment-the involvement of self-congruence. Journal of Travel & Tourism Marketing, 34(9), 1198-1210. https://doi.org/10.1080/10548408.2017.1330171

Hulland, J., & Houston, M. (2021). The importance of behavioral outcomes. Journal of the Academy of Marketing Science, 49(1), 437-440. https://doi.org/10.1007/s11747-020-00764-w

Hung, H. Y., & Lu, H. T. (2018). The rosy side and the blue side of emotional brand attachment. Journal of Consumer Behaviour, 17(3), 302-312. https://doi.org/10.1002/cb.1712

Hüttermann, S., Nerb, J., & Memmert, D. (2018). The role of regulatory focus and expectation on creative decision making. Human Movement Science, 62, 169-175. https://doi.org/10.1016/j.humov.2018.10.006

Irmak, C., Murdock, M. R., & Kanuri, V. K. (2020). When consumption regulations backfire: The role of political ideology. Journal of Marketing Research, 57(5), 966-984. https://doi.org/10.1177%2F0022243720919709

Islam, G. (2014). Social identity theory. Journal of Personality and Social Psychology, 67, 741-763.

Islam, T., Attiq, S., Hameed, Z., Khokhar, M. N., & Sheikh, Z. (2019). The impact of self-congruity (symbolic and functional) on the brand hate. British Food Journal, 121(2), 71-88. https://doi.org/10.1108/BFJ-03-2018-0206

Janoff-Bulman, R. (2009). To provide or protect: Motivational bases of political liberalism and conservatism. Psychological Inquiry, 20(2-3), 120-128. https://doi.org/10.1080/10478400903028581

Japutra, A., Ekinci, Y., & Simkin, L. (2018). Tie the knot: building stronger consumers’ attachment toward a brand. Journal of Strategic Marketing, 26(3), 223-240. https://doi.org/10.1080/0965254X.2016.1195862

Japutra, A., Ekinci, Y., & Simkin, L. (2019). Self-congruence, brand attachment and compulsive buying. Journal of Business Research, 99, 456-463. https://doi.org/10.1016/j.jbusres.2017.08.024

Jeong, H. J., & Koo, D. M. (2015). Volunteering as a mechanism to reduce guilt over purchasing luxury items. Journal of Product & Brand Management, 24(7), 758-769. https://doi.org/10.1108/JPBM-01-2015-0784

Jost, J. T. (2017). Ideological asymmetries and the essence of political psychology. Political Psychology, 38(2), 167-208. https://doi.org/10.1111/pops.12407

Jost, J. T., Glaser, J., Kruglanski, A. W., & Sulloway, F. J. (2003). Political conservatism as motivated social cognition. Psychological Bulletin, 129(3), 339-375. https://psycnet.apa.org/doi/10.1037/0033-2909.129.3.339

Jost, J. T., Napier, J. L., Thorisdottir, H., Gosling, S. D., Palfai, T. P., & Ostafin, B. (2007). Are needs to manage uncertainty and threat associated with political conservatism or ideological extremity?. Personality and Social Psychology Bulletin, 33(7), 989-1007. https://doi.org/10.1177%2F0146167207301028

Jost, K., Stenger, D., Perez, C. R., McDonough, J. K., Lian, K., Gogotsi, Y., & Dion, G. (2013). Knitted and screen printed carbon-fiber supercapacitors for applications in wearable electronics. Energy & Environmental Science, 6(9), 2698-2705. http://doi.org/10.1039/C3EE40515J

Jung, K., Garbarino, E., Briley, D. A., & Wynhausen, J. (2017). Blue and red voices: Effects of political ideology on consumers’ complaining and disputing behavior. Journal of Consumer Research, 44(3), 477-499. https://doi.org/10.1093/jcr/ucx037

Kassarjian, H. H. (1971). Personality and consumer behavior: a review. Journal of Marketing Research, 8(4), 409-418. https://doi.org/10.2307/3150229

Kim, S. L., Cheong, M., Srivastava, A., Yoo, Y., & Yun, S. (2021). Knowledge sharing and creative behavior: the interaction effects of knowledge sharing and regulatory focus on creative behavior. Human Performance, 34(1), 49-66. https://doi.org/10.1080/08959285.2020.1852240

Kucuk, S. U. (2016). What is brand hate? In S. U. Kucuk (Ed.), Brand Hate (pp. 17-36). Springer International Publishing.

Lanaj, K., Chang, C. H., & Johnson, R. E. (2012). Regulatory focus and work-related outcomes: a review and meta-analysis. Psychological Bulletin, 138(5), 998-1034. https://doi.org/10.1037/a0027723

Lau, G. T., & Ng, S. (2001). Individual and situational factors influencing negative word‐of‐mouth behaviour. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l’Administration, 18(3), 163-178. https://doi.org/10.1111/j.1936-4490.2001.tb00253.x

Levin, J., & Fox, J. A. (2004). Estatística para ciências humanas. In Estatística para ciências humanas (pp. 15-497). Pearson Universidades.

Lewis, A. C., Cordero, A. M., & Xiong, R. (2021). Too red for crowdfunding: The legitimation and adoption of crowdfunding across political cultures. Entrepreneurship Theory and Practice, 45(3), 471-504. https://doi.org/10.1177%2F1042258720915574

Lin, C. H., & Chen, M. Y. (2015). “ Being hooked” by a brand story: a view of regulatory focus. European Journal of Marketing, 49(5-6), 692-712.

Lopes, E. L., & Veiga, R. T. (2019). Increasing purchasing intention of eco-efficient products: The role of the advertising communication strategy and the branding strategy. Journal of Brand Management, 26(5), 550-566. https://doi.org/10.1057/s41262-019-00150-0

Malhotra, N. K., Lopes, E., & Veiga, R. T. (2014). Structural equation modeling with Lisrel: an initial vision. Brazilian Journal of Marketing, 13(2), 30-46.

McClure, C., & Seock, Y. K. (2020). The role of involvement: Investigating the effect of brand’s social media pages on consumer purchase intention. Journal of Retailing and Consumer Services, 53, 101975.

Pantano, E., Rese, A., & Baier, D. (2017). Enhancing the online decision-making process by using augmented reality: a two country comparison of youth markets. Journal of Retailing and Consumer Services, 38, 81-95. https://doi.org/10.1016/j.jretconser.2017.05.011

Pentina, I., Bailey, A. A., & Zhang, L. (2018). Exploring effects of source similarity, message valence, and receiver regulatory focus on yelp review persuasiveness and purchase intentions. Journal of Marketing Communications, 24(2), 125-145. https://doi.org/10.1080/13527266.2015.1005115

Pham, M. T., & Avnet, T. (2004). Ideals and oughts and the reliance on affect versus substance in persuasion. Journal of Consumer Research, 30(4), 503-518. https://doi.org/10.1086/380285

Pires, B. (2018, December 31). Luciano Hang, o mais engajado empresário bolsonarista, casa marketing e militância. EL PAÍS. https://brasil.elpais.com/brasil/2018/12/28/politica/1546022364_646763.html

Plutchik, R. (1991). The emotions (revised edition). University Press of America.

Rahi, S. (2017). Research design and methods: A systematic review of research paradigms, sampling issues and instruments development. International Journal of Economics & Management Sciences, 6(2).

Ramalho, R., & Ayrosa, E. A. T. (2009). Subcultura Tuning: a identidade estendida na personalização de automóveis. Revista de Ciências da Administração, 11(24), 169-194. https://doi.org/10.5007/2175-8077.2009v11n24p169

Ramos, G., Vieites, Y., Jacob, J., & Andrade, E. B. (2020). Orientação política e apoio ao isolamento social durante a pandemia da COVID-19: evidências do Brasil. Revista de Administração Pública, 54(4), 697-713.

Richins, M. L. (1994). Special possessions and the expression of material values. Journal of Consumer Research, 21(3), 522-533. https://doi.org/10.1086/209415

Santos, A. W., & Santos Gomes, A., Filho. (2017). As Relações entre o Self/Eu estendido e o consumo de marcas de Smartphones: um estudo com universitários da Região do Cariri cearense. ID on line Revista de Psicologia, 11(38), 42-56. https://doi.org/10.14295/idonline.v11i38.876

Sengupta, J., & Zhou, R. (2007). Understanding impulsive eaters’ choice behaviors: The motivational influences of regulatory focus. Journal of Marketing Research, 44(2), 297-308. https://doi.org/10.1509%2Fjmkr.44.2.297

Sharma, P., Marshall, R., Alan Reday, P., & Na, W. (2010). Complainers versus non-complainers: a multi-national investigation of individual and situational influences on customer complaint behaviour. Journal of Marketing Management, 26(1-2), 163-180. https://doi.org/10.1080/02672570903512502

Shiue, Y. C., & Li, L. S. H. (2013). Brand involvement in retaining customers despite dissatisfaction. Social Behavior and Personality: an international journal, 41(4), 643-650. https://doi.org/10.2224/sbp.2013.41.4.643

Silbiger, A., Barnes, B. R., Berger, R., & Renwick, D. W. (2021). The role of regulatory focus and its influence on the cultural distance-Adjustment relationship for expatriate managers. Journal of Business Research, 122, 398-410. https://doi.org/10.1016/j.jbusres.2020.09.021

Silva, D., Lopes, E. L., & Braga, S. S., Junior. (2014). Pesquisa quantitativa: elementos, paradigmas e definições. Revista de Gestão e Secretariado, 5(1), 01-18.

Sirgy, M. J., Grewal, D., Mangleburg, T. F., Park, J. O., Chon, K. S., Claiborne, C. B., Kohar, J. S., & Berkman, H. (1997). Assessing the predictive validity of two methods of measuring self-image congruence. Journal of the academy of marketing science, 25(3), 229-241. https://doi.org/10.1177/0092070397253004

Sousa, E. M., & Herrero, E. (2021). Uma revisão dos impactos dos atributos de loja. Retail Management Review, 1(1), e6. https://doi.org/10.53946/rmr.v1i1.6

Spiller, S. A., Fitzsimons, G. J., Lynch, J. G. , Jr. , & McClelland, G. H. (2013). Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression. Journal of Marketing Research, 50(2), 277-288. https://doi.org/10.1509%2Fjmr.12.0420

Sternberg, R. J. (2003). A duplex theory of hate: Development and application to terrorism, massacres, and genocide. Review of General Psychology, 7(3), 299-328. https://doi.org/10.1037%2F1089-2680.7.3.299

Tajfel, H., Turner, J. C., Austin, W. G., & Worchel, S. (1979). An integrative theory of intergroup conflict. Organizational identity: A reader, 56-65.

Wallace, E., Buil, I., & de Chernatony, L. (2017). Consumers’ self-congruence with a “liked” brand: cognitive network influence and brand outcomes. European Journal of Marketing , 51(2), 367-390. https://doi.org/10.1108/EJM-07-2015-0442

Wen, T. J. (2021). Congruity between mood and brand involvement enhances the effectiveness of message appeals: dual processing model perspective. Journal of Marketing Communications, 27(6), 651-669. https://doi.org/10.1080/13527266.2020.1755884

Westjohn, S. A., Arnold, M. J., Magnusson, P., & Reynolds, K. (2016). The influence of regulatory focus on global consumption orientation and preference for global versus local consumer culture positioning. Journal of International Marketing, 24(2), 22-39. https://doi.org/10.1509%2Fjim.15.0006

Xu, Y. (2008). The influence of public self‐consciousness and materialism on young consumers’compulsive buying. Young Consumers, 9(1), 37-48. https://doi.org/10.1108/17473610810857309

Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341-352. https://doi.org/10.1086/208520

Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revision, and application to advertising. Journal of advertising, 23(4), 59-70. http://doi.org/10.1080/00913367.1943.10673459

Zarantonello, L., Romani, S., Grappi, S., & Bagozzi, R. P. (2016). Brand hate. Journal of Product & Brand Management, 25(1), 11-25. https://doi.org/10.1108/JPBM-01-2015-0799

Zarantonello, L., Romani, S., Grappi, S., & Fetscherin, M. (2018). Trajectories of brand hate. Journal of Brand Management, 25(6), 549-560. https://doi.org/10.1057/s41262-018-0105-5

Author notes

du.mesq@gmail.com evandro.lopes@espm.br eliane.herrero@yahoo.com.br

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