How consumer animosity drives anti-consumption: A multi-country examination of social animosity

Krüger, Tinka et al. Article — Published Version How consumer animosity drives anti-consumption: A multi-country examination of social animosity Journal of Retailing and Consumer Services Provided in Cooperation with: Kiel Institute for the World Economy – Leibniz Center for Research on Global Economic Challenges Suggested Citation: Krüger, Tinka et al. (2024) : How consumer animosity drives anti-consumption: A multi-country examination of social animosity, Journal of Retailing and Consumer Services, ISSN 1873-1384, Elsevier BV, Amsterdam, Vol. 81, pp. 1-12, https://doi.org/10.1016/j.jretconser.2024.103990 This Version is available at: https://hdl.handle.net/10419/302042 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Journal of Retailing and Consumer Services 81 (2024) 103990 Available online 13 July 2024 0969-6989/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). How consumer animosity drives anti-consumption: A multi-country examination of social animosity ☆ Tinka Krüger a , Stefan Hoffmann a , * , Ipek N. Nibat b , Robert Mai c , Olivier Trendel c , Holger G¨ org d , Wassili Lasarov e a Kiel University, Westring 425, 24118 Kiel, Germany b Sabanci Business School, Sabanci University, Orta Mahalle, 34956 Tuzla, Istanbul, Turkey c Grenoble Ecole de Management, 12 Rue Pierre S´ emard, 38000 Grenoble, France d Kiel University and Kiel Institute for the World Economy, Kiellinie 66, 24105 Kiel, Germany e Audencia Business School, 8 Route de La Joneli` ere, 44312 Nantes, France ARTICLE INFO Handling Editor: Prof. H. Timmermans Keywords: Consumer animosity Boycott Anti-consumption Social animosity Ethnocentrism ABSTRACT In times of uncertainty, the study of consumer animosity and how it affects anti-consumption behavior becomes more important for both academics and practitioners. This study focuses on the social nature of boycotts and contributes to the literature by analyzing the influence of normative components. The paper introduces and empirically validates the concept of social animosity as a moderator of animosity’s negative effect on product judgments and boycotts. The cross-country study uses data from six countries to measure animosity effects on two target countries: Russia and the U.S. Results confirm that consumers’ social animosity influences how animosity shapes their boycott intentions. 1. Introduction Current incidents, such as Russia’s attack on Ukraine, growing tensions between China and the West, the UK’s exit from the European Union, and the rise of populist parties across Europe (e.g., Lubbers and Coenders, 2017), depict the concurrent tenet of rising nationalism and protectionism across countries, which can reactivate consumer animosity between countries. Especially in times of uncertainty, skepticism toward political measures, media, and established institutions is prevalent across societies. As a result, people constantly scrutinize official statements as well as the intentions of governmental actions. Those recurring crises and societal developments can lead to situational animosity between countries, which can develop into stable animosity over time (Jung et al., 2002). Consumer animosity constitutes the antipathy toward a certain country—hereafter target country—due to previous or contemporary military, political, or economic events independently of consumers’ product judgments (Klein et al., 1998). Animosity is versatilely detrimental for countries by, for example, triggering boycotts of products and services from the target country (e.g., Ettenson and Klein, 2005; Kim et al., 2022). Consumers can use boycotts—a form of anti-consumption (Hoffmann and Lee, 2016; Hutter and Hoffmann, 2013; Lee et al., 2009)—as a weapon against behavior perceived as undesired (Hoffmann and Müller, 2009), and hence as a form of political consumerism (e.g., Neilson and Paxton, 2010). Animosity and its effect on boycotts are therefore of special relevance to internationally operating business leaders and decision makers. Furthermore, animosity is of particular relevance to practitioners in marketing, sales, and retailing, to gain grounded evidence about what drives individuals’ consumption decisions. While there is a plethora of research studies investigating why consumers participate in boycotts (Yuksel, 2013), this investigation aims to extend the literature by answering how normative components—such as the influence of social norms and perceived expectations of others—- shape the impact of animosity on consumers’ boycott participation. Therefore, we introduce the construct of social animosity. This construct ☆ This work was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft; DFG) [grant number: HO 5738/3-1] and the French National Research Agency (Agence Nationale de la Recherche; ANR) [ANR-18-FRAL-0012]. * Corresponding author. E-mail addresses: [email protected] (T. Krüger), [email protected] (S. Hoffmann), [email protected] (I.N. Nibat), robert.mai@ grenoble-em.com (R. Mai), [email protected] (O. Trendel), [email protected] (H. G¨ org), [email protected] (W. Lasarov). Contents lists available at ScienceDirect Journal of Retailing and Consumer Services journal homepage: www.elsevier.com/locate/jretconser https://doi.org/10.1016/j.jretconser.2024.103990 Received 5 July 2024; Accepted 5 July 2024 Journal of Retailing and Consumer Services 81 (2024) 103990 2 refers to an individual’s perceptions about its social environment’s animosity toward a particular country. This new construct is distinct from other established constructs, such as people animosity—the dislike of the mentality of people from a specific country (Nes et al., 2012). We introduce the social animosity scale to measure an individual’s perceived social environment’s animosity and test its moderating role on the relation between consumer animosity and consumers’ boycott participation and product judgments. Furthermore, we contrast this impact against the effect of ethnocentrism as another normative influence. We investigate animosity toward Russia and the U.S., respectively, and test our model on a rich dataset covering six countries—two Western countries (Germany and the U.S.) and four BRICS states (Brazil, Russia, India, and South Africa). Measuring animosity toward the same target countries in multiple countries enables us to examine how animosity effects vary across countries. This study contributes to the literature in two ways: First, we examine the effect of consumers’ social animosity, which constitutes an often-overlooked array within the literature on animosity. By doing so, we provide answers to Krautz et al.’s (2014) call for investigating consumers’ social environment and its influence on animosity effects. Accordingly, we extend the knowledge on animosity by integrating normative, cognitive, and affective mechanisms within country-of-origin (COO) effects (Verlegh and Steenkamp, 1999) and contrast the moderating effects of social animosity and ethnocentrism. We develop and validate a new scale to measure social animosity. Second, we extend the knowledge of anti-consumption by investigating whether the conscious consumption reduction caused by animosity differs across countries and how anti-consumption behavior is shaped by perceptions about one’s social environment’s animosity. 2. Theoretical background Stimulated by Klein et al.’s (1998) seminal study 25 years ago, research on consumer animosity has steadily increased. According to Klein et al. (1998, p. 90), consumer animosity constitutes the “antipathy towards previous or ongoing military, economic, or political events.” This widely adopted definition highlights the heterogeneity of animosity-evoking events. Further research approaches corroborated that cultural and religious disputes can elicit animosity too (Kalliny and Lemaster, 2005; Kalliny et al., 2017; Nes et al., 2012). Scholars preponderantly examine animosity in a binational country context including a home country (the country in which animosity mounts due to the negative incident) and a target country (the target of the animosity). Studies confirmed that consumer animosity impacts consumers’ behavioral reactions in various national settings, including the animosity between China and Japan (e.g., Antonetti et al., 2019; Klein et al., 1998), Netherlands and Germany (Nijssen and Douglas, 2004), Greece and Turkey (Nakos and Hajidimitriou, 2007), Spain and Korea (Jim´ enez and San Martín, 2010), and Ukraine and Russia (Gineikiene and Diamantopoulos, 2017). In total, past studies within the animosity research stream investigated more than 150 different country dyads (Krüger et al., 2022). Emphasizing the relevance of studying the phenomenon of consumer animosity in a diverse set of countries, researchers confirmed the moderating role of Hofstede’s (2001) cultural values on animosity’s detrimental effects (e.g., Leonidou et al., 2019; Westjohn et al., 2021). Thereby, information about a product’s country-of-origin relates to consumers’ emotions, identity, pride, and memories (Botschen and Hemettsberger, 1998; Verlegh and Steenkamp, 1999) and can, subsequently, elicit affective connotations and strong emotional reactions to this product (Fournier, 1998). 2.1. The influence of animosity on boycott and product judgments Anti-consumption received considerable attention in the marketing research field and within consumer animosity in particular (García-de-Frutos and Ortega-Egea, 2015) and can be generally understood as the “resistance to, distaste of, or even resentment or rejection of consumption” (Zavestoski, 2002, p. 121). Iyer and Muncy (2009) distinguished between the object and purpose of anti-consumption. In the animosity context, the object refers to products from or associated with the animosity target country. Aiming to identify different reasons for anti-consumption, Hoffmann and Lee (2016) proposed that anti-consumption can—despite the decision for consumption rejection—relate to consumer well-being. In that sense, the purpose of anti-consumption can essentially be societal (macro) or personal (micro) (Iyer and Muncy, 2016). Boycotts are, in general, politically motivated (Yuksel and Mryteza, 2009) and defined as purchase rejections aiming to change or at least punish critical behavior (Friedman, 1985) of, for instance, companies or governments. Focusing on personal purposes, Lee et al. (2009) identified different reasons to boycott, such as aiming to avoid symbolically incompatible products and brands originating from the target country (identity avoidance). In other words, consumers may boycott certain products or brands originating from or associated with the animosity target country to avoid undesired self-perceptions or disidentification with the brand. Boycotts are not merely non-consumption; they are anti-consumption executed “for political or ethical reasons” (Yuksel and Mryteza, 2009). Triggered by ethical concerns as well as symbolic concerns associated with certain products (Chatzidakis and Lee, 2013; Muncy and Iyer, 2021), anti-consumption can help consumers behave in accordance with their underlying ideology (Kozinets et al., 2010). Previous research confirms animosity’s effects on consumers’ product avoidance (e.g., Narang, 2016; Shoham et al., 2006) such as boycotts and hence refers to country-related forms of anti-consumption (García-de-Frutos and Ortega-Egea, 2015). Animosity triggers specific emotions, such as anger or fear (e.g., Harmeling et al., 2015), which, in turn, provokes consumers’ anti-consumption, for example, increased unwillingness to buy products (e.g., Klein et al., 1998; Shoham et al., 2006), or boycott intentions (e.g., Ettenson and Klein, 2005; Hoffmann et al., 2011). The positive relationship between animosity and boycott was confirmed in different country settings (e.g., Chinese consumers boycotting products from Japan; Smith and Li, 2010; Iraqi consumers boycotting Turkish products; Ali, 2021; South Korean consumers boycotting Japanese products; Lee and Chon, 2021; Kim et al., 2022). Only few studies found a non-significant effect of animosity on boycotting (e. g., Malaysian consumers boycotting products from Denmark; Abayati et al., 2012; Chinese consumers boycotting French products; Mrad et al., 2013). Kozinets and Handelman (1998) experimentally showed that boycott participation can serve as consumers’ emotional expression. Transferred to country contexts, consumers need to be aware of and need to show a certain level of egregiousness to engage in boycotts (John and Klein, 2003; Klein et al., 2004). Considering that animosity provokes high levels of egregiousness, we conclude that consumer animosity positively affects individuals’ boycott participation. H1a. The higher the level of animosity, the stronger consumers’ intention to boycott. In their initial study, Klein et al. (1998) tested the effect of animosity on product judgments. Following animosity research replicated the conceptual model from Klein et al. (1998) in different country settings (e.g., Ishii, 2009) and in different product settings (e.g., hybrid products; Cheah et al., 2016) or investigated animosity’s effect on product evaluations (e.g., Gineikiene and Diamantopoulos, 2017; Hoang et al., 2022). Thereby, previous research on consumer animosity reveals heterogeneous findings with regard to animosity’s effect on product judgments (Krüger et al., 2022). While some studies corroborate a non-significant effect between the two variables (e.g., Chinese consumers evaluating Western products (Heinberg, 2017) or Chinese consumers evaluating Japanese products (Klein et al., 1998)), other studies found a significant negative effect (e.g., Ukrainian consumers evaluating Russian products (Gineikiene and Diamantopoulos, 2017) or Pakistani T. Krüger et al. Journal of Retailing and Consumer Services 81 (2024) 103990 3 consumers evaluating Indian products (Chaudhry et al., 2020)). These mixed findings emphasize the country-sensitivity of animosity’s detrimental effects. Westjohn et al.’s (2021) and Krüger et al.’s (2022) meta-analytic approaches confirm the negative effect of animosity on product judgments on an aggregated level of examination. Thus, consumers’ negative emotions evoked by the negative events triggering animosity spill over to their product evaluation. Consumers are, therefore, not able to distinguish between their affective reactions and cognitive evaluations of products from the animosity target country. Accordingly, we propose that animosity negatively influences product judgments. H1b. The higher the level of animosity, the more negative consumers’ product judgments. 2.2. Social animosity Boycotts are considered as collective actions, which are a form of consumer movement (e.g., Benford and Snow, 2000; Friedman, 1996; Kozinets and Handelman, 2004). Boycotters can be viewed as “market activists” who avoid specific products or brands because of societal values (Iyer and Muncy, 2009) and they often use the digital sphere for social interactions and, for instance, for e-petitions participation (Yuksel et al., 2020). Sen and Bhattacharya (2001) proposed that consumers balance their subjective costs of boycotting against their normative influence, perhaps because those consumer movements affect society’s well-being (Witkowski, 1989) and can be directed toward a societal purpose (Iyer and Muncy, 2016). Boycotts are, therefore, strongly interpersonally connected with and dependent on normative factors. Farah and Newman (2010) showed that the question of whether or not consumers participate in boycotts depends on consumers’ perceived subjective norms. Drawing on the Theory of Reasoned Action (Fishbein and Ajzen, 1975) and the Theory of Planned Behavior (Ajzen, 1991), behavioral intentions are influenced by an individual’s subjective norms that depend on the individuals’ normative beliefs and the motivation to comply with these believes. Both theories are often used within the animosity literature (e.g., Abraham and Reitman, 2018; Kim et al., 2022; Maher and Mady, 2010) and offer a theoretical perspective on how normative components affect behavioral intentions and, subsequently, behavior. These normative influences may stem from familial and official socialization processes (e.g., formal education and politics) and arguably affect animosity (Bahaee and Pisani, 2009). In a state-of-the-art review of the animosity literature, Krautz et al. (2014) emphasize the lack of interest in the consumers’ social environment and its influence on animosity effects, stressing the need for acknowledging social influences within animosity research. An individual’s social animosity refers to descriptive norms—the perception of what most people do (Cialdini et al., 1991). Descriptive norms guide individuals toward a shortcut in the decision-making process as they presume the perceptions of a majority of individuals to be a signal for a good way of thinking or believing and, hence, leads to adaptive behaviors (Cialdini et al., 1991). Especially for consumers with a high social animosity—that is, consumers who perceive their peers’ and fellow citizens’ animosity toward a particular country as high—it is likely that their peers’ or the general society’s view on the target country affects how strongly they react to their animosity feelings. In particular, we assume that high social animosity fosters consumers’ perceived moral obligation to society which should trigger individuals to act upon their own animosity feelings and drive boycott participation (Hoffmann, 2013; Hoffmann et al., 2018). Consumers are, hence, more likely to act upon their animosity feelings if they perceive others to be hostile toward the same target country (and high social animosity provides such a license to boycott products from the target country). Because the negative military, economic, or political events that cause animosity (Klein et al., 1998) trigger negative emotions (e.g., Harmeling et al., 2015), consumer animosity and the reluctance to buy products from the animosity target country strongly relate to the affective component of COO effects (García-de-Frutos and Ortega-Egea, 2015), carrying the symbolic and emotional meaning to consumers (Verlegh and Steenkamp, 1999). Building on these conclusions, we assume that consumers’ perceptions about their social environment’s animosity (social animosity) influence consumers’ boycott participation through normative and affective COO mechanisms. Given that social animosity does not refer to the cognitive mechanisms of COO effects, it does not moderate the effect of animosity on product judgments. The normative facets guide consumers to behave in an acceptable manner without influencing how animosity affects product evaluations. Moreover, at least for some products and services, consuming products (that is, not to boycott) is an overt behavior that others can observe, while product judgments are not observable. Therefore, it seems reasonable that social animosity moderates the influence on boycotting, but not the influence on product judgments. H2. Social animosity moderates the relationship between animosity and boycott participation. The higher social animosity, the stronger the effect of animosity on boycott participation. 2.3. Consumer ethnocentrism The concept of animosity is related to but distinct from the construct of consumer ethnocentrism (Klein and Ettenson, 1999) defined as the “beliefs about the appropriateness, indeed morality, of purchasing foreign made products” (Shimp and Sharma, 1987). Consumer ethnocentrism includes consumers’ aversion to foreign products in general due to denigrated quality perceptions of foreign products (Shimp and Sharma, 1987). Accordingly, ethnocentrism refers to the cognitive mechanism of COO effects (Sharma, 2015) as information of the COO is used as “a signal for overall product quality and quality attributes” (Li and Wyer, 1994; Steenkamp, 1989). While consumer ethnocentrism opposes any foreign country, consumer animosity refers to one specific foreign country due to a negative incident (Klein and Ettenson, 1999). Ethnocentric consumers feel obliged to support the domestic economy by buying domestic products, as they assume that purchasing imported goods causes unemployment in the long term (Shimp and Sharma, 1987). Subsequently, consumer ethnocentrism also relates to COO’s normative mechanisms and determines the right way of conduct (Shimp and Sharma, 1987; Verlegh and Steenkamp, 1999). Contrary to social animosity that is assumed to function as a descriptive norm, consumer ethnocentrism can be viewed as an injunctive norm—the perception of what most people would approve or disapprove of (Cialdini et al., 1991). Following Cialdini et al. (1991), injunctive norms create moral rules that lead to social rewards (or informal sanctions if not following those norms). Subsequently, ethnocentrism is based on the COO effect’s cognitive and normative mechanism. To contrast different COO-related mechanisms against each other, we include consumer ethnocentrism as a moderator in our model. Although included within the Animosity Model of Foreign Product Purchase (Klein et al., 1998) and examined in most animosity studies, academics have not investigated ethnocentrism as a moderator of animosity effects thus far. In particular, we assume that ethnocentrism fosters consumers’ perceived moral obligation which should trigger individuals to act upon their own animosity feelings and drive boycott participation and product judgments. H3a. Consumer ethnocentrism moderates the relationship between animosity and boycott participation. The higher the ethnocentrism, the stronger the effect of animosity on boycott participation. H3b. Consumer ethnocentrism moderates the relationship between animosity and product judgments. The higher the ethnocentrism, the stronger the effect of animosity on product judgments. Fig. 1 visualizes the conceptual model of our study. T. Krüger et al. Journal of Retailing and Consumer Services 81 (2024) 103990 4 3. Material and methods 3.1. Procedure To test our hypotheses, we applied a survey-based research approach. We recruited participants in a diverse country dyadic context with six home countries of participants (the U.S., Germany, Brazil, Russia, India, and South Africa) and two target countries (Russia and the U.S.). We selected Russia and the U.S. as suitable target countries, as academics often examine both of these countries in an animosity context (e.g., Russia as the target country: Harmeling et al., 2015; Hoffmann et al., 2011; the U.S. as the target country: Amine, 2008; Russell and Russell, 2006) due to political discords and perceived economic dominance (the U.S.), or due to perceived military threat and previous wars (Russia). In addition, the countries selected are of practical relevance because of their large trade volumes and strong bilateral trade interdependencies with the two target countries, Russia and the U.S. Data were collected in 2020 by use of Amazon Mechanical Turk (MTurk) and with the help of the professional panel provider TGM (https://tgmrese arch.com/), which distributed our online survey to their nationwide panels. We acknowledge the criticism of using MTurk in behavioral science (e.g., Aguinis et al., 2021). However, researchers stress that the concerns about the possibility of low-quality data are overstated (e.g., Buchheit et al., 2018). Accordingly, we followed scientists within animosity research using MTurk (e.g., Angell et al., 2021; Magnusson et al., 2019) because of MTurk’s accessibility of a variety of subjects (Hunt and Scheetz, 2019; Mason and Suri, 2012) and its suitability for conducting cross-national studies, especially (Lee et al., 2018). We used TGM for collecting data in Russia and South Africa to warrant comparable country coverage and similar sample structures. In addition, at the time of the data collection MTurk did not provide a suitable large database for Russia and South Africa so that it was necessary to rely on another professional panel provider that covers these countries of interest. To ensure sufficient data quality, we included an attention check question within the survey (e.g., “How often have you had a heart attack in the last few weeks?”, 5-point Likert-scale). We used this question following researchers that used questions on heart attack as an attention check question in prior research studies (e.g., Albert and Smilek, 2023; Borkowska et al., 2023; Lasarov et al., 2023; Paolacci et al., 2010). Respondents were rewarded for participating in our study when passing the attention check question. We eliminated cases from our initial sample due to missing values or incomplete surveys (N US =38, N GER = 29, N BRA =22, N RUS =53, N IND =157, N SAF =166 1 ), due to nationalities different from the home country investigated (N US =15, N GER =17, N BRA =9, N RUS =25, N IND =10, N SAF =23), and due to attention check failures (N US =50, N GER =0, N BRA =0, N RUS =12, N IND =76, N SAF =5). In total, we received a rich dataset of N =1142 fully completed questionnaires: N =215 valid cases for the U.S., N =208 for Germany, N = 224 for Brazil, N =131 for Russia, N =150 for India, and N =214 for South Africa (response rates U.S.: 67.61%, Germany: 81.89%, Brazil: 87.84%, Russia: 59.28%, India: 38.17%, South Africa: 52.45% 2 ). The national samples differ only slightly with regard to demographic characteristics, which enables comparison between the countries (see Table 1). Noteworthy, respondents were randomly assigned to one of the two target countries under investigation (U.S. and Russia) and answered the questions solely for one of these target countries. 3.2. Material and measures We structured the questionnaire as follows. First, we welcomed participants and informed them that their participation is voluntary and that we treat the data confidentially and anonymously without inferences about the participant. Apart from these measures, and to further limit common method variance (CMV) concerns, we also measured the independent and dependent variables in separate sections of the questionnaire (Podsakoff et al., 2003). We used Klein’s (2002) two items for measuring consumer animosity that specifically capture the negative attitude toward a particular country. The third original, positively valanced, item “I like Japan” used by Klein (2002) has mostly been neglected when measuring general animosity (e.g., Alden et al., 2013; Funk et al., 2010; Latif et al., 2019) as general animosity is usually operationalized with a negatively valanced item such as “I do not like a Fig. 1. Conceptual model. 1 In the South African dataset, 166 cases needed to be eliminated due to incomplete surveys; additional 351 cases did not start the survey, but were reported by our professional panel provider TGM. 2 The response rate for South Africa refers inter alia to the incomplete data (N =166) and differs from the response rate including individuals that did not start the survey (39.27%). T. Krüger et al. Journal of Retailing and Consumer Services 81 (2024) 103990 5 particular country” (Leonidou et al., 2019). To measure consumers’ boycott participation, we used the four-item scale adapted and extended from Hoffmann et al. (2011), which covers consumers’ self-reported boycott participation. In particular, we adjusted the item “I often boycott products from [country]” by adding “due to political reasons” to further emphasize boycotts as a form of political consumerism (e.g., Neilson and Paxton, 2010). We added two more items, one that particularly focuses on the boycott of services and the other stressing ethical values as a common stimulation for anti-consumption behavior (e.g., Chatzidakis and Lee, 2013; Muncy and Iyer, 2021; Lee et al., 2009). We adopted three items of Klein et al.’s (1998) scale to measure consumers’ product judgments and used four items of Shimp and Sharma’s (1987) CETSCALE to measure consumer ethnocentrism. Both product judgments and consumer ethnocentrism scales are widely adopted within the animosity research field (e.g., Ettenson and Klein, 2005; Nijssen and Douglas, 2004). All scales were rated on a seven-point Likert scale ranging from 1 (“totally disagree”) to 7 (“totally agree”) (items for all measures are available in Table 5). Ultimately, we asked the respondents for socio-demographical information (i.e., age, gender, level of education, household income). All questionnaires were translated back to the local language of the country under examination to ensure semantic equivalence of the constructs (Brislin, 1970). 3.3. Social animosity scale We introduce a new social animosity scale with eight items, containing assumed perceptions of the people closest to the respondent as well as assumed perceptions of the society. This new social animosity scale refers to descriptive norms, that is, consumers’ perceptions about what people do (Cialdini et al., 1991). We followed established scale development procedures (Churchill, 1979) through a five-step approach (see Table 2). In a first step, using Bearden et al.’s (1989) work on normative influences and social contexts, our international team of researchers systematically brainstormed about social layers that may be relevant to our particular research question. Three different layers were identified that may shape an individual’s social environment (fellow citizens from the same country; people close to the individual, such as family members, friends, colleagues; and people the individual merely knows). The items generated referred to these three social layers and included antipathy related (affective connotated) items (“most of the people closest to me don’t like [country]” and “most of the people closest to me are angry towards [country]”) following Klein et al. (1998). Additionally, we added two behavioral connotated items (“it often happens that the people closest to me speak negatively about [country]” and “whenever possible, the people closest to me avoid buying products from [country]”; the latter inspired by Klein et al., 1998). In the second step, one social layer (4 items referring to people the individual knows) was eliminated due to lack of expert validity and vague country reference after group discussions with international researchers from the field of social psychology, animosity, and marketing. That is, this particular social layer could also include public figures or people from other countries, so these items do not sufficiently focus on an individual’s direct social environment. Subsequently, we had a set of eight items (see Table 3) capturing an individual’s perceptions about its social environment’s animosity. We pretested the social animosity scale with N = 80 U.S. participants recruited via MTurk in step three. The findings confirm the scale’s uni-dimensionality and internal consistency (all items loaded on the same factor with factor loadings greater than 0.78; Cronbach’s alpha =0.95). During our scale development process, we ran an additional validation study by adding items to an omnibus study (not reported in this manuscript), including the social animosity scale, Bearden et al. (1989) interpersonal influence scale, and Antonetti and Maklan’s (2016) scale to measure negative word-of-mouth ensuring convergence validity as well as nomological validity. In particular, we collected data in France (N =2324) and the UK (N =2424) in 2020. Multi-group confirmatory factor analyses (MG-CFA) with AMOS 29.0 confirmed discriminant validity according to Fornell and Larcker (1981) for both countries. In the final stage (step five), we conducted our main study and ran confirmatory factor analyses with AMOS (v. 29.0) that confirmed our proposed measurement model (see Table 5). Table 1 Sample characteristics. Characteristics U.S. GER BRA RUS IND SAF Age Mean (SD) 35.1 (10.0) 28.9 (8.5) 28.3 (7.9) 41.7 (12.2) 34.1 (8.6) 36.4 (12.2) Gender Male 86 (58.9) 60 (60.0) 137 (61.7) 60 (45.8) 100 (67.1) 101 (47.4) Female 60 (41.1) 38 (38.0) 82 (36.9) 71 (54.2) 49 (32.9) 112 (52.6) Diverse 0 (0.0) 2 (2.0) 3 (1.4) 0 (0.0) 0 (0.0) 0 (0.0) Education No SLC 0 (0.0) 1 (1.0) 1 (0.5) 2 (1.5) 1 (0.7) 6 (2.8) 12th Grade 33 (15.3) 40 (39.2) 1 (0.5) 32 (24.4) 1 (0.7) 84 (39.4) Bachelor 127 (59.1) 26 (25.5) 85 (38.2) 41 (31.3) 104 (69.3) 52 (24.4) Master 46 (21.4) 17 (16.7) 107 (48.2) 32 (24.4) 43 (28.7) 11 (5.2) Diploma 5 (2.3) 5 (4.9) 23 (10.4) 18 (13.7) 1 (0.7) 44 (20.7) Other 4 (1.9) 13 (12.7) 5 (2.3) 6 (4.6) 0 (0.0) 16 (7.5) Income* Above 30 (14.0) 16 (15.7) 28 (12.6) 16 (12.3) 23 (15.4) 28 (13.3) On 160 (74.4) 40 (39.2) 101 (45.3) 90 (69.2) 122 (81.9) 109 (51.7) Below 25 (11.6) 46 (45.1) 94 (42.2) 24 (18.5) 4 (2.7) 74 (35.1) Total 215 208 224 131 150 214 Notes: absolute numbers (percentage); percentages do not necessarily sum up to 100% due to missing values; *“Compared to other Americans/Germans/Brazilians/ Russians/Indians/South Africans your income is … the average”; BRA =Brazil; GER =Germany; IND =India; RUS =Russia; SAF =South Africa; SD =standard deviation; SLC =school leaving certificate. Table 2 Scale development procedure. Step Country N Method Focus 1 GER 3 group discussions face validity 2 FRA 6 group discussions expert validity 3 U.S. 80 Pretest uni-dimensionality & internal consistency 4 FRA, UK 4748 Omnibusstudy convergence validity & nomological validity 5 U.S., GER, BRA, RUS, IND, SAF 1142 Main study cross-validation Notes: BRA =Brazil; FRA =France; GER =Germany; IND =India; SAF =South Africa; UK =United Kingdom; U.S. =United States of America. T. Krüger et al. Journal of Retailing and Consumer Services 81 (2024) 103990 6 3.4. Validity, multi-country invariance, and common method variance We ran multi-group confirmatory factor analysis (MG-CFA) with Amos 29.0. See Table 4 for the means, standard deviations, and correlations, and Table 5 for the measurement model. Reliabilities (and average variances extracted (AVEs)) for all latent constructs exceeded the threshold of 0.60 (Bagozzi and Yi, 1988; Homburg et al., 2008) (and 0.50) (Fornell and Larcker, 1981) for both target countries, i.e., Russia and the U.S. The Fornell and Larcker (1981) test confirmed discriminant validity between all latent variables, as the AVEs, that is, the mean of the squared latent variables’ loadings, were greater than the corresponding latent variable’s maximum correlations (r 2 max ) with the other latent variables, for both target countries. To test for measurement invariance (configural, metric, and scalar invariance) across countries, we followed Steenkamp and Baumgartner (1998). The marginal changes in model fit after introducing equality constraints on the factor loadings suggest metric invariance between the two target countries, which allows us to compare the effects between the two target countries (Cheung and Rensvold, 2002). Likewise, the third model, in which the item intercepts are also constrained to be equal across the two target countries, shows suitable marginal changes in model fit as suggested by Cheung and Rensvold (2002) (ΔCFI =0.006, ΔTLI =0.001, ΔRMSEA =0.01) and therefore indicate scalar invariance. Thus, we allowed item intercepts to vary in the main analyses and did not compare latent means across countries. We also tested for measurement invariance across home countries, confirming configural, metric, and (partial) scalar invariance for the different home country models. This is sufficient, considering that partial scalar invariance stems from different animosity levels across the home countries. To control whether common method variance (CMV) is a potential bias for our results, we conducted the Harman’s Single Factor Test, which is a widely adopted technique to test for CMV (e.g., Fuller et al., 2016). A single factor for all items included in our model accounted for 38.64% of variance, that is below the common threshold of 50% as suggested by Podsakoff and Organ (1986). The five expected factors jointly account for 78.78 % of the variance. Accordingly, common method bias does not seem to be a threat to our analysis (Fuller et al., 2016). 4. Results We ran covariance-based multi-group structural equation models (MG-SEM) with AMOS (v. 29.0) using the maximum-likelihood method. We used standardized values (manifest variables) for the interaction effects. In model 1, we did not distinguish between home and target countries. In model 2, we distinguished between the two target countries (Russia, and the U.S). Model 3 distinguishes between the two target countries (Russia, and the U.S.) and between the home countries (the U. S., Germany, Brazil, Russia, India, South Africa). Chi-squared difference tests between the three models show significant differences between all models, revealing that model 3 is superior compared to model 2 ( χ 2 diff = 223.850, df diff =80, p <0.001) and compared to model 1 ( χ 2 diff = 276.732, df diff =90, p <0.001). Hence, we focus on model 3 in the following. Table 6 summarizes the results obtained for model 3. The structural model’s overall model fit indicates suitable values ( χ 2 (10)/df =2.091, comparative fit index (CFI) =0.995, root mean square error of approximation (RMSEA) =0.031) and therefore exceeds common thresholds (Browne and Cudeck, 1993; Weber and Mühlhaus, 2010). Results show that consumer animosity negatively influences consumers’ product judgments, but only in Brazil, Russia, and South Africa (see Table 6). These heterogeneous findings are in line with the results of various animosity studies finding both negative effects (e.g., Gineikiene and Diamantopoulos, 2017; Shoham et al., 2006) and non-significant effects (e.g., Heinberg, 2017; Khan et al., 2019; Klein et al., 1998). More consistently across home and target countries, we found that animosity increases anti-consumption in terms of boycott participation. For all country dyads (except for South African consumers boycotting U. S. products, and Indian consumers boycotting U.S. and Russian products), our analyses show animosity’s positive influence on consumers’ boycott participation. We, therefore, stipulate partial support for H1a and H1b. As expected, the newly introduced social animosity construct Table 3 Indicators of the social animosity context scale. Indicators Most of the people closest to me don’t like [Russia/the U.S]. Most of the people closest to me are angry towards [Russia/the U.S]. It often happens that the people closest to me speak negatively about [Russia/the U.S]. Whenever possible, the people closest to me avoid buying products from [Russia/the U.S]. Most Germans* don’t like [Russia/the U.S]. Most Germans* are angry towards [Russia/the U.S]. It often happens that Germans* speak negatively about [Russia/the U.S]. Whenever possible, Germans* avoid buying products from [Russia/the U.S]. Notes: *Example for the German questionnaire and replaced by “Americans,” “Brazilians,” “Russians,” “Indians,” and “South Africans”. Table 4 Means, standard deviations, and correlations. TC =RUS M SD 1 2 3 4 5 1 Animosity 2.93 1.50 0.77 2 Ethnocentrism 3.94 1.21 0.25 0.65 3 Social Animosity 3.26 1.39 0.69 0.33 0.72 4 Product Judgments 4.72 0.99 −0.05 0.33 0.06 0.72 5 Boycott 2.51 1.53 0.62 0.48 0.66 0.19 0.82 TC ¼U.S. M SD 1 2 3 4 5 1 Animosity 2.79 1.57 0.73 2 Ethnocentrism 3.52 1.20 0.26 0.65 3 Social Animosity 3.03 1.41 0.71 0.30 0.65 4 Product Judgments 5.39 1.08 −0.55 −0.06 −0.38 0.72 5 Boycott 2.22 1.30 0.56 0.34 0.54 −0.34 0.70 Notes: The mean is assessed based on average factor scores; standard deviations (SD) and correlations are from the CFA output; the diagonal elements represent the average variance extracted (AVE); TC =target country. T. Krüger et al. Journal of Retailing and Consumer Services 81 (2024) 103990 7 moderates the extent to which animosity influences consumers’ boycott participation (see Table 6). In other words, the strength of animosity feelings that individuals surmise their peers and society moderates the relationship between animosity toward the particular target country and the individual’s boycott participation. This finding embraces the social sphere of boycotts as a form of anti-consumption driven by the perceived social pressure of an individual’s peers and society. However, the social animosity’s moderating effect is only significant for Brazil, India, and South Africa (and for the target country Russia), but not for the U.S. and Germany. Accordingly, we obtained partial support for H2. We additionally examined the moderating role of ethnocentrism on the relationship between animosity and product judgment. Results presented in Table 6 indicate that ethnocentrism strengthens the effect of animosity on product judgments, but only in the U.S. (toward Russian products), India, and South Africa (both toward products from the U.S.). Testing ethnocentrism’s moderating role on how animosity affects boycott participation proved to be not significant (except for India with regard to Russian products). We, therefore, found partial support for H3b, but not for H3a. Table 7 synthesizes our findings related to our hypotheses. 5. Discussion By focusing on consumers’ anti-consumption, and in line with previous animosity research (e.g., Hoffmann et al., 2011), our results show that animosity increases boycott participation. However, animosity does not affect South Africans’ or Indians’ boycott participation when it comes to U.S. products, nor does animosity affect Indians’ boycott participation with regard to Russian products; thus, we could partially confirm H1a. We conjecture these countries’ special economic dependence on U.S. products as a possible explanation. For instance, in 2020, the U.S. was India’s second largest import partner and even the first most important export partner (Worldbank, 2020). Similarly, the U.S. was South Africa’s third largest import and second most important export partner. Therefore, it is likely that due to the BRICS states’ strong trade interdependencies on the U.S., animosity has no effect on boycott participation. These results match prior research confirming that a lack of domestic alternatives influences whether anti-foreign attitudes guide consumer behavior (Nijssen and Douglas, 2004). In addition, the non-significant effects for India can potentially stem from their low uncertainty avoidance levels, implying the general suppression of emotions (Hofstede, 2001). Accordingly, due to their low uncertainty avoidance, Indians’ animosity does not spill over to their consumption behavior and therefore, does not affect boycott participation (neither toward American nor toward Russian products). As confirmed by anti-consumption researchers, a certain level of egregiousness is needed to elicit boycott behavior (John and Klein, 2003; Klein et al., 2004). Subsequently, the non-significant results in South Africa and India could also stem from the lower level of egregiousness triggered by the animosity-evoking event. Previous research findings diverge when it comes to animosity’s impact on product judgments. In their initial study, Klein et al. (1998) corroborated animosity’s unrelatedness to consumers’ product judgments, confirming non-significant effects between the two variables. Many studies replicated Klein et al.’s (1998) study design in different country contexts and could confirm the non-significant effect of animosity on product judgments (e.g., Ettenson and Klein, 2005; Heinberg, 2017; Li et al., 2012). However, other studies identified a negative Table 5 Measurement model of the CFA. Construct Measurement items TC =Russia TC =U.S. λ CA λ CA Consumer Animosity (1) I am angry towards [Russia/the U.S]. 0.90 0.88 (2) I do not like [Russia/the U.S]. 0.86 0.83 Source: Klein (2002) 0.87 0.84 Ethnocentrism (1) Only those products that are unavailable in [home country] should be imported. 0.64 0.63 (2) It is not right to purchase foreign products, because it puts [people from home country] out of work. 0.88 0.89 (3) We should purchase products manufactured in [home country] instead of letting other countries getting rich at our expense. 0.82 0.83 (4) [People from home country] should not buy foreign products, because it damages the [home country] economy and causes unemployment. 0.87 0.87 Source: Shimp and Sharma (1987) 0.88 0.88 Social Animosity (1) Most of the people closest to me don’t like [Russia/the U.S.]. 0.86 0.83 (2) Most of the people closest to me are angry towards [Russia/the U.S.]. 0.89 0.86 (3) It often happens that the people closest to me speak negatively about [Russia/the U.S.]. 0.87 0.81 (4) Whenever possible, the people closest to me avoid buying products from [Russia/the U.S.]. 0.82 0.73 (5) Most [people from home country] don’t like [Russia/the U.S.]. 0.84 0.84 (6) Most [people from home country] are angry towards [Russia/the U.S.]. 0.88 0.86 (7) It often happens that [people from home country] speak negatively about [Russia/the U.S.]. 0.80 0.82 (8) Whenever possible, [people from home country] avoid buying products from [Russia/the U.S.]. 0.84 0.95 0.70 0.94 Product Judgments Products from [Russia/the U.S.] are … (1) reliable. 0.75 0.79 (2) technically advanced. 0.86 0.84 (3) excellently manufactured. 0.93 0.92 Source: Klein et al. (1998) 0.88 0.88 Boycott (1) I have already boycotted products from [Russia/the U.S.]. 0.94 0.88 (2) I have already boycotted online services from [Russia/the U.S.]. 0.94 0.87 (3) I often boycott products from [Russia/the U.S.] due to political reasons. 0.95 0.89 (4) My ethical values keep me from buying products from [Russia/the U.S.]. 0.80 0.71 Source: Hoffmann et al. (2011) 0.95 0.90 Notes: MG-CFA model fit: χ 2 (358) =2813.232; CFI =0.88; RMSEA =0.08; λ =standardized factor loadings; CA =Cronbach’s Alpha; the results correspond to the final specification (equal factor loadings, free item intercepts) after excluding one item due to insufficient loadings; the corresponding scales’ content validity was unaffected; countries in brackets refer to the home country or the target country (either the U.S. or Russia); respondents answered questions solely for one target country. T. Krüger et al. Journal of Retailing and Consumer Services 81 (2024) 103990 8 Table 6 Results of the structural equation modeling. Model paths TC =RUS TC =U.S. U.S. GER BRA IND SAF GER BRA RUS IND SAF β p β p β p β p β p β p β p β p β p β p DV: Product Judgments Direct path CA → PJ −0.13 0.10 ¡0.32 * −0.14 ¡0.54 *** −0.21 ¡0.45 *** ¡0.75 *** −0.26 †¡0.32 ** Moderated paths SA → PJ 0.18 * −0.14 0.06 −0.08 0.15 −0.18 −0.06 0.18 †0.02 ¡0.25 ** SA ×CA → PJ −0.14 −0.02 −0.16 †0.09 0.01 −0.10 0.05 0.17 0.06 0.04 ETH → PJ 0.27 *** −0.08 0.09 0.02 0.14 −0.02 0.13 0.22 ** −0.25 † − 0.01 ETH ×CA → PJ 0.34 *** 0.08 0.06 0.16 0.10 0.15 0.02 0.09 ¡0.38 * 0.21 * DV: Boycott Direct path CA → BOY 0.25 *** 0.35 *** 0.22 †0.14 0.25 ** 0.27 * 0.43 *** 0.42 *** −0.04 0.17 Moderated paths SA → BOY 0.34 *** 0.26 ** 0.28 ** 0.34 ** 0.32 *** 0.29 ** 0.33 *** 0.13 0.61 *** 0.31 ** SA ×CA → BOY 0.11 †0.06 0.20 * ¡0.22 * 0.25 ** −0.04 0.32 *** −0.02 ¡0.21 * 0.10 ETH → BOY 0.36 *** 0.22 ** −0.10 0.24 * 0.16 †0.16 †0.22 * 0.11 0.36 *** 0.04 ETH ×CA → BOY −0.03 0.18 † − 0.11 0.31 * 0.06 −0.14 0.12 0.13 0.19 †0.07 N 215 106 108 83 118 102 116 131 67 96 χ 2 (df) 2.091 CFI/RMSEA 0.995/0.031 Notes: The reported coefficients are standardized; statistically significant coefficients (at the p <0.05 level) appear in bold; ***p <0.001; **p <0.01; *p <0.05; †p <0.10; BOY =boycott; BRA =Brazil; CA =consumer animosity; CFI =comparative fit index; ETH =ethnocentrism; GER =Germany; IND =India; PJ =product judgments; RMSEA =root mean square error of approximation; RUS =Russia; SA =social animosity; SAF = South Africa; U.S. =United States of America. T. Krüger et al.