Country of product origin as a determinant influencing typology of Czech consumers in the beverages market

Original Research SAGE Open April-June 2024: 1–16 ÓThe Author(s) 2024 DOI: 10.1177/21582440241255552 journals.sagepub.com/home/sgo Country of Product Origin as a Determinant Influencing Typology of Czech Consumers in the Beverages Market S ˇa ´rka Velc ˇovska ´ 1 and Lucie Waliszewska ´ 1 Abstract This paper aims to propose a typology of Czech consumers with respect to their attitudes toward the country of origin when purchasing beverages. Attention is paid to four commonly purchased beverage categories: beer, wine, tea and coffee. Using the Computer Assisted Web Interviewing method, the total number of fully completed questionnaires obtained was 396. The selection of respondents was determined by gender and age quotas. The measurement of attitudes involved utilizing a set of 22 statements concerning the beverage origin which were evaluated on a five-point scale. As confirmed by the research results, in each beverage category, the country of origin influences consumers’ purchasing decisions differently. When purchasing wine, Czech consumers most commonly verify the country from which it originates. The origin is also important to them when it comes to beer, with the strongest preference for beer produced in their own country. The country from which the beverage originates has a considerably lower importance for coffee and is the least important when buying tea. Based on respondents’ attitudes toward the country of beverage origin, four consumer segments were identified, namely ‘‘Experimenters,’’ ‘‘Picky consumers,’’ ‘‘Patriots,’’ and ‘‘Pro-European consumers.’’ Factor and cluster analysis were used for this purpose. Keywords beverage market, cluster analysis, consumer attitudes, consumer segments, consumer typology, country of origin, survey Introduction Consumer behavior in the beverage market is a very broad topic that offers many possibilities for investigation. In the current globalized environment, consumers encounter various factors when purchasing beverages, and one of the significant aspects is the country of product origin. Consumers care about the product’s origin as it guarantees a certain product quality and safety, some of them want to support domestic products or avoid products from specific countries. Consumer interest in the country of product origin issues is growing, and engagement in this area has increased during the Covid19 pandemic. A thought-provoking perspective involves developing a consumer typology that portrays consumer attitudes toward the country from which a beverage originates, as current approaches to beverage market segmentation do not consider this factor. Previously published studies focus mainly on subtypologies in a sub-market, examples being typologies in the wine market (Lockshin et al., 2000; Lockshin & Corsi, 2012) or typologies in the beer market (CalvoPorral et al., 2018; Go ´mez-Corona et al., 2016; Jaeger et al., 2020). However, the average consumer does not buy just one beverage category, there are usually several categories of beverages in their shopping basket. Moreover, these typologies are based on different criteria, such as the consumer’s shopping habits 1 VSB – Technical University of Ostrava, Czech Republic Corresponding Author: S ˇa ´rka Velc ˇovska ´, Department of Marketing and Business, VSB – Technical University of Ostrava, Faculty of Economics, Sokolska tr. 33, Ostrava 702 00, Czech Republic. Email: [email protected] Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). (Tokinomo, 2022) or the consumer’s responsibility for family food purchases (The Food Industry Association, 2015). There is no other previous segmentation study that focuses directly on the extent to which the country of origin affects the consumer’s decision-making process when purchasing beverages. Consequently, this paper aims to fill the research gap in this field and to find out different segments of Czech consumers in the beverage market based on the influence of the country of beverage origin. The four beverage categories, namely beer, wine, coffee and tea were selected for this study as the four most regularly and frequently purchased beverage categories by Czech consumers. In addition, these categories were chosen as it makes sense to examine for them the influence of the country of origin in purchasing decisions. In contrast, for juices or mineral waters, the country of origin is usually not so diverse and determinant. The scientific contribution of this study is mainly connected with the extension of the existing research methodology, the development of a new methodology and the associated creation of statements used in the questionnaire focused on the relationship between the country of origin and the four beverage categories. The research therefore provides a deeper and more comprehensive insight into consumer decision-making. Knowledge of consumer segments in the beverage market based on their attitudes toward the origin of the product can be a basis for retailers to make decisions about the product assortment offered. This will allow retailers to select the beverage portfolio that the consumers will be most interested in, which will help sellers potentially reduce inventory and increase turnover as well as profit. Therefore, this paper aims to create consumer typology on the beverage market in the Czech Republic and describe the differences between individual consumer segments with respect to the importance of the beverage origin. Literature Review In light of the paper’s objective, an explanation is provided of how consumer purchasing behavior is affected by the country of origin. Furthermore, the specificities of the country of origin effect with regard to product categories are described, with a focus on the abovementioned beverage categories. Attention is also paid to the typologies of consumers in the market under study. Country-of-Origin Effect The country of origin (COO) effect explains the impact that the origin country of a product, including its manufacturing, assembly, or design, has on how consumers perceive and assess the product. (Javed & Hasnu, 2013; Morton et al., 2004). ‘‘This phenomenon occurs when consumers infer that the characteristics of a country transfer onto a product or a brand’’ (Velc ˇovska ´& S ˇvajdova ´, 2022). However, the concept of the COO effect is becoming increasingly complex. Consumers often associate certain countries with specific product quality or product characteristics, which may influence their attitudes and behavior. The impact of a COO differs according to several variables involving the perception of the country image, prevailing national stereotypes, consumer ethnocentrism, familiarity and experience with the brand or product category, and the level of involvement with the product (Lee & Lee, 2009, in: Pharr, 2005; Rezvani et al., 2012; Velc ˇovska ´& S ˇvajdova ´, 2022; Yang et al., 2016). Some studies have proven that consumers exhibit a tendency to either favor or avoid products based on the country they associate those products with, due to the influence of the country image (Oberecker et al., 2008). Based on consumers’ associations or stereotypes with a given country, they often assign positive or negative characteristics to specific products (Astapchyk & Strezhnev, 2016). In general, products manufactured in less developed countries are often considered as having higher risks and inferior quality when compared to products produced in more developed countries (Huddleston et al., 2001; Kalicharan, 2014). Thus, the likelihood of buying a product produced in a country with a favorable reputation is greater (Kalicharan, 2014). The connection between the image associated with the country of origin, the perceived quality and price of a product, and the intention to purchase it was confirmed in a study by Merabet (2020). The country of origin can influence the pricing of the product and the resulting willingness of the consumer to pay that price. Zhang et al. (2020) revealed in their study that both macro and microlevel dimensions of the country-of-origin image (COI) affect Chinese consumers’ willingness to pay (WTP) for milk beverages. They confirmed that three dimensions (macropolitical, microtechnology/quality, and microdesign/package) have a positive impact on evaluating milk from different countries, with the higher the perceived COI, the higher the consumer’s WTP. It is clear that the impact of the country where a product originates has noticeable effects on the attitudes of consumers and their purchasing decisions. A positive COO effect can enhance the perceived quality, value, and credibility of a product, while a negative COO effect can lead to skepticism, doubt, and avoidance of buying the product. However, although certain countries are generally viewed positively, there are still consumers who exhibit ethnocentrism and favor their country’s products 2SAGE Open because they wish to contribute to the local economy or hold the belief that domestic brands possess superior quality, greater credibility, and better align with consumer needs and preferences (Astapchyk & Strezhnev, 2016; Kalicharan, 2014; Velc ˇovska ´&S ˇvajdova ´, 2022; Yang et al., 2016). Yang et al. (2022) found that ‘‘the importance of country-of-origin in product evaluation is not necessarily driven by consumer ethnocentrism or animosity.’’ Only in the case of frequent buyers, a stronger degree of favoring products from their own country and rejecting products from other countries correlates with a greater emphasis on the country of origin in assessing products. Vrontis and Basile (2022) focused on how social media can improve and enhance the connection between the country-of-origin effect and consumer behavior. They conclude that consumer’s experiences are essential variables when considering the COO conditions. Therefore, to build a relationship between consumers and products coming from abroad, it is necessary to integrate digital forms and live events. Another aspect related to the COO effect concerns the so-called hybrid or multinational products that arise in the context of open borders, international trade, and globalization. These are products whose development and production take place in more than one country (Crouch et al., 2016; Rezvani et al., 2012; Zamazalova ´, 2010). Therefore, within the European Union (EU), one can often encounter a scenario in which a product is marked with the label ‘‘Made in the EU.’’ However, due to the diverse nature of EU members, this label often leaves consumers with somewhat ambiguous information about the product’s actual origin. This label is often used by countries with lower quality standards, and with this unspecific origin, they minimize the potential risks that the origin of the product will discourage consumers from buying it (S ˇtrach, 2009). The Relationship Between Product Category and the Country of Origin Role To understand the influence of the country of origin, it is crucial to differ between different product categories (Velc ˇovska ´&S ˇvajdova ´, 2022). This is because the COO effect is not universal (Javed & Hasnu, 2013). The heritage, culture, or lifestyle of certain countries are inherently linked to specific products, resulting in an automatic perception of them as premium quality, for example, French wine, Czech beer, German cars, Netherland cheese, or Belgian chocolate. Hence, consumers’ perceptions and expectations vary based on the product category and the country of origin, leading to a preference for products originating from specific countries. Conversely, preconceived stereotypes associated with certain countries may dissuade consumers from making a purchase if there is a mismatch with the product category (Crouch et al., 2016). This phenomenon is referred to as a product-country image by Roth and Diamantopoulos (2009). In terms of product categories, consumers from some countries show a strong preference for foreign products, while consumers from other countries are more loyal to local products. (Astapchyk & Strezhnev, 2016; Papadopoulos et al., 1990) According to The Nielsen Company (US)’s (2017) global research, consumers from various regions worldwide, especially in the tea, mineral water and coffee categories, are inclined to buy global brands instead of locally produced products. In the category of alcoholic beverages (including beer), the survey revealed a preference for local brands among Czech residents. The degree of ethnocentrism in beer in the Czech Republic has also been investigated by Wanninayake and Chovancova (2012). The research clearly showed that Czech consumers prefer Czech beers to foreign brands. The degree of preference for local products and the rejection of foreign products is therefore influenced by the type of product. Khan et al. (2017) conducted a study on the COO effect within the beer market, specifically examining how the demographic characteristics of consumers in New Zealand impacted their perception of the quality of imported beer. Several foreign studies have been carried out to examine the COO role in consumer wine-buying behavior. Bruwer et al. (2024) investigated the effects of several independent factors on COO product category assessment when buying wine. They found out that consumer ethnocentrism, product involvement, purchasing experience and travel exposure strongly affect COO product category ratings. Deans et al. (2014) discovered that, for UK consumers, the country from which a wine originates is the second most crucial factor (after price). Crouch et al. (2016) hypothesized that if a positive perception is associated with a certain country, it would positively affect the evaluation of wines from that particular country. The assumption was confirmed, as it was found that respondents rated wines from those countries with which they have associated positive emotional reactions better. People from different countries around the world consider France and Italy to be the best wine producers. Based on his research, Tamasx(2016) reached similar findings, namely that France, Italy, and Spain are perceived as the best wine producers in the eyes of consumers. The study conducted by Vesela ´and Zich (2015) aimed to understand the factors that influence Generation Y when purchasing wine, specifically examining the significance of the country of origin. The research showed that the majority of respondents base their purchasing decisions on three main factors: country of origin, wine Velc ˇovska ´and Waliszewska ´3 brand, and price. As expected, French wines were rated as high quality, with similar results for Czech wines. In another study, authors examined how the country-oforigin effect influences millennials’ wine preferences (Foroudi et al., 2019). The results show that many participants who preferred a particular wine at the beginning of the experiment (especially on the basis of the COO reputation), moved their preference to another wine in the end, after having more knowledge about it. The authors consequently suggest that increasing knowledge could help to change former prejudice. In their systematic review, Giacomarra et al. (2020) aimed to investigate how geographical cues and country of origin influence wine consumers’ behavior, with reference to the New and Old Worlds. The authors concluded that geographical cues and country of origin alone are not enough of a factor in purchasing decisions. Consumers from both worlds consider also other factors together such as wine knowledge, socio-ethnodemographic factors, consumption habits, labeling strategies and the use of medals and awards on labels. In addition to these findings, Galati et al. (2018) revealed in their study that wine origin (COO), identified in particular through the Designation of Controlled Origin (DOC) information, has a significant influence on the pricing of the wine, especially on premium price. The link between the country of origin and consumer coffee and tea purchasing behavior has received comparatively little attention. The majority of the research conducted in this field has addressed factors such as the effect of these beverages on people’s health, taste, aroma, quality, price, brand, etc. However, there are still references and information available in the literature that discuss the country of origin and its significance in the selection of coffee and tea. Studies on beverage purchasing behavior have revealed that while coffee quality remains a primary consideration in the decision-making process (Foret, 2005), country of origin information also holds significant importance for many consumers, with a preference for single-origin coffee, that is, coffee that comes from only one country or region (Minchin, 2022). Cok (2016) analyzed the significance of the country of origin for coffee in Italy and concluded that quality is the most crucial aspect in evaluating coffee. Brand, price, and country of coffee origin are comparatively less influential. If we focus on Czech consumers, they consider Czech products to be as good as foreign ones, one-fifth perceive them as having a higher quality. Czechs prefer groceries from domestic, regional or local producers and believe in their quality (Velc ˇovska ´& Valec ˇkova ´, 2018). However, it is not known to what extent these domestic product preferences vary by product category, specifically in the beverage market. Consumer Typologies The typology of consumers in food and/or beverage markets is also the subject of research studies. To create typologies, authors consider different perspectives, such as customers’ shopping habits (Tokinomo, 2022), or consumer’s responsibility for family food purchases (The Food Industry Association, 2015). Other authors then elaborated on specific typologies in the food market, for example in terms of attitudes toward organic food (Gumber & Rana, 2021; Pes ˇtek et al., 2018). Most typologies, however, focus on food, rather than beverages separately. Regarding beer consumer typology, Jaeger et al. (2020) examined craft beer flavor preference. In this context, they defined beer consumers who desire richer and more intricate flavors, as well as consumers who prefer more traditional flavors. Calvo-Porral et al. (2018) used consumption behavior, patterns and preferences as segmentation criteria and categorized beer consumers into five distinct groups (‘‘beer lovers,’’ ‘‘circumspect seniors,’’ ‘‘social drinkers,’’ ‘‘homelike women,’’ and ‘‘beer to fuddle’’). In another study, Go ´mez-Corona et al. (2016) classified beer consumers into ‘‘craft,’’ ‘‘industrial’’ and ‘‘occasional’’ based on their demographic characteristics and beer consumption habits. Calvo-Porral et al. (2020) focused their segmentation study on the beer market as well and created three main clusters based on the level of involvement with beer (‘‘highly involved consumers,’’ ‘‘medium involved consumers,’’ and ‘‘low involved consumers’’). There are also several studies focusing on consumer segmentation and typology in the wine market. Lockshin and Corsi (2012) explored gender differences among customers in the wine market. Lockshin et al. (2000) refer to McKinna’s study, which utilized benefit-based criteria for segmenting wine consumers and work with four distinct segments of wine consumers (‘‘connoisseurs,’’ ‘‘aspirational drinkers,’’ ‘‘new wine drinkers,’’ and ‘‘beverage wine consumers’’). Spa ´c ˇil et al. (2022) confirmed these findings and demonstrated that the structure of wine consumers varies according to consumers’ attitudes and socio-demographic characteristics. They also revealed significant cross-cultural differences among customer segments. Typologies that focus on the coffee market are very rare. Carvalho et al. (2015) divided Brazilian consumers in the coffee market into three groups based on the factors that motivate respondents to consume coffee. ‘‘Group 1’’ is mostly driven by psychological, everyday manners and social factors, in contrast to ‘‘Group 2’’ which is unaware of social effects, and ‘‘Group 3’’ is motivated by daily habits and psychological outcomes. There is no previous recent study from reputable sources that focuses on the segmentation of the tea market. 4SAGE Open The list of previously assessed typologies on the beverage market according to major studies from the last 8 years (2015 until now) is visible in Table 1. There are not many available typologies on the beverage market from reputable journals over the last 8 years. Mentioned typologies focus only on specific foreign markets and specific beverage categories, none of them takes into account several beverage categories at the same time. Most of these segmentation studies consider the typical consumer of a certain type of beverage when selecting the sample of respondents, rather than the average consumer who purchases multiple types of beverages in a single household purchase. Moreover, no typology takes into consideration the country of beverage origin. In addition, it seems that there does not exist any methodology to fully rely on, each author uses different sampling approaches and different sizes of the sample. Nevertheless, all authors used a questionnaire (online or paper) to collect data for their segmentation study. Consumer typologies in the Czech market do not directly target the beverage market but generally focus on the food or FMCG category, which includes beverages. In the typology of Czech consumers according to the Focus Agency from 2015, the segments are profiled primarily based on quality preference or low food prices and also on the degree of interest in information on the origin of purchased food with an emphasis on interest in organic food (Czech Agriculture and Food Inspection Authority, 2016). The GfK Shopper Typology 2018 study on the FMCG market monitors consumer attitudes to shopping, key factors when choosing a store, and their relationship to Czech and regional food (GFK, 2022). Velc ˇovska ´(2018) and Sadı´lek (2019) proposed a typology of consumers coming from consumer perception of quality labels in the food market. None of the typologies specifically focus on the beverage market or take into account the COO role. Based on the aforementioned findings, it can be concluded that no consumer typology within the beverage market considers multiple beverage categories and explores the COO role in consumer purchase behavior. Therefore, this study aims to fill this research gap in this field, to determine several different segments of Czech consumers in the four-category beverage market based on the influence of country of product origin and to bring new methodology with respect to already existing methodologies in this market, including the formulation of the statements in the questionnaire, which will enable the fulfilment of the research objective. Methods The objective of the research study was to segment Czech consumers in the beverage market and suggest a consumer typology that considers the COO role in their purchasing decisions. Four beverage categories (beer, wine, tea, and coffee) as representative beverages commonly consumed in the Czech beverage market were selected for the research. Country of origin was mainly divided into three branches—the Czech Republic, the EU, and outside EU-made beverages. To obtain primary data, quantitative research was used. Data were attained through an online questionnaire survey, more precisely using the Computer Assisted Web Interviewing method. The questionnaire was distributed using e-mail and social networks, mainly to specified online forums and groups concerning beverage and grocery shopping. This method was chosen to secure a larger sample of respondents resulting in better explanatory power of the obtained information. The structured questionnaire included a battery of 22 statements concerning the beverage origin. These statements were partially created according to the CETSCALE (Consumer Ethnocentrism Scale), which is a unique multi-item scale that is used to measure consumer’s ethnocentric tendencies that are related to the purchase of domestic and foreign products. The CETSCALE was first introduced and validated by Shimp and Sharma (1987). The statements were subsequently modified according to the needs of this research to measure consumer preferences toward domestic beverages, the country of origin in general and finally to explore respondents’ perception of selected countries of origin (EU-made and outside EU-made beverages) in four beverage categories. To evaluate these statements, a five-point Likert-type scale of agreement was used, which allowed for the subsequent use of factor and cluster analysis and the creation of a typology. The research was carried out in 2022. The research population included individuals aged 20 and above residing in the Czech Republic. The sample was determined using a non-probability sampling method—a quota sampling technique according to the gender and age structure of the Czech population (aged 20 + ) in order to secure the representativeness of the sample. Also, the highest achieved education level of respondents was monitored in the research. A total of 396 respondents participated in the research (Table 2). Data analysis was conducted utilizing IBM SPSS. Additionally, to standard analytical procedures, factor and cluster analyses were applied to perform the segmentation and to create customer typology. Factor analysis is used to reduce data by creating a smaller number of new variables (factors) from many original ones. For factor analysis to be used, several conditions must be met. Firstly, the internal consistency of the battery must be verified to confirm whether the entire battery of items is continuous and whether these items are related to the battery. The resulting coefficient ranges from 0 to 1. A Velc ˇovska ´and Waliszewska ´5 Table 1. Typologies on the Beverage Market According to Major Studies (From 2015 Until Now). Authors Country year Product Data collection method/Sample Segmentation criteria Typology Calvo-Porral, C., OrosaGonza ´lez, J., & BlazquezLozano, F. A. Spain 2018 Beer Questionnaire, random sampling, N= 592 Consumption behavior, patterns and preferences Beer lovers, social drinkers, homelike women, circumspect seniors, beer to fuddle consumers Calvo-Porral, C., Rivaroli, S., & Orosa-Gonzalez, J. Spain 2020 Beer Online questionnaire, random sampling, N= 565 Classification based on level of involvement with beer Highly involved consumers, medium involved consumers, Low involved consumers Go ´mez-Corona, C., EscalonaBuendı ´a, H. B., Garcı ´a, M., Chollet, S., & Valentin, D. Mexico 2016 Beer Questionnaire, visitors of beer festival, N= 207 Beer consumption habits Industrial beer, Occasional, Industrial, Craft beer consumers Jaeger, S. R., Worch, T., Phelps, T., Jin, D., & Cardello, V.A. New Zealand 2020 Beer Questionnaire, sensory analysis, N= 120 Preference for craft beer flavor Craft-style likers, traditionalstyle likers Spa ´c ˇil, V., Hora ´kova ´, J., & Grendysa, D. Czech Republic, Germany 2022 Wine Questionnaire, N(CZ) = 458, N(DE) = 409 Attitudes toward wine consumption Average wine consumers, connoisseurs, innovators, aspirational drinkers Carvalho, N. B., RodriguesMinim, V. P., Nascimento, M., Ribeiro-Vidigal, M. C. T., Ferreira, M. A. M., Goncxalves, A. C. A., & Minim, L. A. Brazil 2015 Coffee Questionnaire, random sampling, N= 210 Factors that motivate respondents to consume coffee Group 1—motivated by psychological, everyday habits and social factors, Group 2— oblivious to social effects, Group 3—motivated by everyday habits and psychological effects Source. Own elaboration. 6 minimum value between 0.6 and 0.8 is recommended, and coefficients that are less than 0.5 are usually unacceptable (Goforth, 2015). Another condition is the value of the KMO index, which must be greater than 0.6, but ideally greater than 0.7. In the next step, the attention is focused on Bartlett’s Test of Sphericity. This test indicates whether factor analysis can be used—if there is a correlation between the variables (Malhotra, 2010). Among the basic approaches to factor analysis are principal component analysis and common factor analysis. The number of factors that will be created can be determined a priori, based on eigenvalues higher than one (Kaiser’s rule), scree plots, percentage of variance or significance tests. The output of the factor analysis and the basis to interpret the factors is a factor matrix. The initial unrotated factor matrix shows relationships between the factors and individual variables, but most factors cannot be easily interpreted using the unrotated solution. For this reason, rotation is applied to transform the factor matrix into a matrix that can be simpler and easier to interpret. The Varimax procedure is the most used method of rotation, it results in orthogonal factors (S€ ur€ uc€ u et al., 2022). The purpose of the cluster analysis is to group respondents into segments (clusters) based on their similarity. Objects with a smaller distance between them are more similar to each other than objects at larger distances. The most used measure of similarity (dissimilarity) is the Euclidean distance according to Hendl (2009). Clustering procedures are divided into hierarchical and non-hierarchical. For hierarchical clustering the development of a treelike structure is characteristic. Hierarchical methods are agglomerative or divisive. Agglomerative methods are more commonly used in marketing research, they include linkage methods, variance methods and centroid methods. The most frequently used is the variance method, more precisely Ward’s procedure. The non-hierarchical methods are also called K-means clustering (K= number of clusters). As main disadvantages of the non-hierarchical clustering can be considered a fact, that the number of clusters must be pre-specified, and that the selection of cluster centers is arbitrary. It is possible to combine hierarchical and non-hierarchical methods, first using hierarchical clustering and then continuing with a nonhierarchical procedure (Everitt et al., 2011). The final number of clusters should be validated based on the results of the ANOVA test. Using factor analysis, original statements were reduced to a just few new factors. The principal components method and the Varimax procedure were used to obtain the minimum number of rotated factors and to explain the maximum variance in the data. After defining new factors, the cluster analysis method was employed to establish distinct consumer clusters based on responses to the attitudinal questions. Firstly, hierarchical clustering was applied, specifically Ward’s method (the Euclidean square distance). This was followed by non-hierarchical clustering (K-means method), where the determination of the cluster number was set according to the outcomes of hierarchical clustering. The resulting number of clusters was validated through the ANOVA test. The dependencies between the consumer segments and the sociodemographic characteristics of the respondents were examined by Pearson’s chi-square test. All testing was performed at a 5% level of significance. Table 2. Structure of the Sample and the Czech Population (%). Czech population percent Sample percent Sample frequency Gender Men 49.0 49.0 194 Women 51.0 51.0 202 Age 20–34 20.9 23.2 92 35–44 18.6 18.2 72 45–54 19.2 17.7 70 55–64 15.3 16.2 64 65 and more 26.1 24.7 98 Highest education level Compulsory education 14.0 24.2 96 High school diploma 65.7 44.9 178 College degree 20.3 30.8 122 Net monthly income a 0–10,000 CZK - 10.1 40 10,001–20,000 CZK - 26.3 104 20,001–30,000 CZK - 37.9 150 30,001–40,000 CZK - 18.7 74 40,001 CZK and more - 7.1 28 Source. Czech Statistical Office (2023) and own research. a Not monitored by the Czech Statistical Office. Velc ˇovska ´and Waliszewska ´7 Results In the first section of the research results, consumer attitudes toward the beverage origin are analyzed. Then in the second part, respondents are divided into several segments (clusters) based on their expressed attitudes. Characteristics of consumer segments according to sociodemographic factors are presented in the third section. Consumer Attitudes Regarding the Beverage Origin Respondents evaluated a total of 22 statements concerning their attitudes toward the beverage origin. For the evaluation, a Likert five-point scale was used (1 means strong agreement, 5 is strong disagreement). The mean scores indicating the level of agreement with the claims are shown in Table 3. The respondents most strongly agreed with the statements indicating their preference for beer that is made in the Czech Republic (average value 1.3) and that they consistently consider the country of origin when purchasing wine (average value 1.8). Respondents also mostly agreed with claims that they prefer buying wine which is made in the Czech Republic, they are open to trying coffee and tea produced abroad, and when buying a beer, they always check its origin. They also exhibited a tendency to agree that the country from which the beverage originates is an indication of its quality. On the contrary, participants in the survey were more likely to disagree with claims that they would like to try a beer made abroad (average value 3.5) and that they would buy wine that is made outside the EU with confidence (average value 3.6). Respondents disagreed to the biggest extent with the statement concerning buying beer that is made outside the EU with confidence. Consumer Typology by the Attitudes Toward the Beverage Origin First, a factor analysis was performed on a set of 22 statements related to beverage origin. The purpose was to simplify the statements into a smaller number of factors making it more convenient to apply and interpret ongoing cluster analysis. Also, the conditions for the use of factor analysis were verified through the calculation of Cronbach’s Alpha coefficient, the Kaiser-Meyer-Olkin (KMO) index, and Bartlett’s sphericity test. The Cronbach’s Alpha coefficient is .626, which can be considered a satisfactory result. The initial requirement for conducting factor analysis was fulfilled. Subsequently, the KMO index value was calculated. Its value was equal to 0.682, which is an acceptable result (see Table 4). Lastly, it was needed to verify the result of Bartlett’s Sphericity Test, which indicates whether factor analysis can be utilized or not. The resulting significance was equal to .001 (Table 4), confirming the presence of a correlation between the Table 4. KMO Measure and Bartlett’s Sphericity Test. Kaiser-Meyer-Olkin measure 0.682 Bartlett’s test of sphericity Approx. Chi-square 1,039.552 df 231 Sig. .001 Source. Own research. Table 3. Mean Scores of Agreements With the Statements Related to the Beverage Origin. Statement Mean score I always prefer to buy beer that is made in the Czech Republic. 1.3 I consistently consider the country of origin when purchasing wine. 1.8 I always prefer to buy wine that is made in the Czech Republic. 2.1 I like to try coffee that is made abroad. 2.1 I consistently consider the country of origin when purchasing beer. 2.2 The country from which the beverage originates is a quality indication. 2.3 I like to try tea that is made abroad. 2.3 I would rather buy a beverage with a certification of origin than one without. 2.4 I like to try wine that is made abroad. 2.4 I will purchase wine produced within the EU with confidence. 2.8 I will purchase tea produced outside the EU with confidence. 2.9 I will purchase beer produced within the EU with confidence. 2.9 I will purchase coffee produced within the EU with confidence. 2.9 I will purchase coffee produced outside the EU with confidence. 3.0 I consistently consider the country of origin when purchasing coffee. 3.0 I always prefer to buy coffee that is made in the Czech Republic. 3.1 I consistently consider the country of origin when purchasing tea. 3.1 I always prefer to buy tea that is made in the Czech Republic. 3.1 I will purchase tea produced within the EU with confidence. 3.3 I like to try beer that is made abroad. 3.5 I will purchase wine produced outside the EU with confidence. 3.6 I will purchase beer produced outside the EU with confidence. 4.2 Source. Own research. Note. The darker the shading of the cell with mean score, the stronger the disagreement of respondents with the statement. 8SAGE Open variables. Therefore, it can be affirmed that factor analysis can be employed. The principal component method, Varimax rotation, and Kaiser’s rule (the value of ‘‘Eigenvalues’’ is greater than 1) were utilized to perform the factor analysis. The initial set of 22 statements was transformed into six new factors (see Table 4). These six factors explain more than 60% of the variance of the entire battery. As can be seen in Table 5, the rotated matrix contains several cross-loadings. A ‘‘cross-loading occurs when variable loads at 0.32 or higher on two or more factors’’ (Costello & Osborne, 2005). In this case, a complex structure is formed. All variable loads higher than 0.3 in absolute value were shaded in order to see occurring cross-loadings, these shaded entries are visible in Table 5. There are several ways how to deal with cross-loadings and create a more simple structure. According to Hair et al. (2010), cross-loadings lower than 0.35 (in some cases lower than 0.4) are not significant, especially when there is a difference of 0.1 or more between the crossloads. Therefore variable ‘‘I like to try coffee that is made abroad’’ was assigned to Factor 2 and the variable ‘‘I will purchase coffee produced outside the EU with confidence’’ was allocated to Factor 5. S€ ur€ uc€ u et al. (2022) suggest that when the cross-loading value is more significant and there is not a difference of 0.1 or more between the cross-loads, it is recommended to remove the problem variable from the analysis. However, the Table 5. Rotated Component Matrix With Factor Loadings. F1 F2 F3 F4 F5 F6 I will purchase wine produced within the EU with confidence. 0.897 0.048 20.003 20.031 20.022 0.097 I will purchase coffee produced within the EU with confidence. 0.871 20.038 0.096 0.001 20.129 20.093 I will purchase beer produced within the EU with confidence. 0.862 0.195 20.111 20.023 0.106 0.130 I will purchase tea produced within the EU with confidence. 0.831 20.107 20.138 20.097 20.021 20.087 I like to try beer that is made abroad. 0.044 0.785 20.026 20.152 20.064 20.010 I like to try tea that is made abroad. 20.058 0.744 20.255 0.086 0.128 0.115 I like to try coffee that is made abroad. 20.078 0.667 20.343 0.021 0.118 0.066 I like to try wine that is made abroad. 0.079 0.638 20.280 0.060 20.028 20.091 I will purchase beer produced outside the EU with confidence. 0.137 0.575 0.092 0.040 0.480 20.186 I will purchase wine produced outside the EU with confidence. 0.026 0.573 0.125 0.016 0.567 20.217 I always prefer to buy coffee made in the Czech Republic. 0.025 20.224 0.862 20.170 20.059 0.059 I always prefer to buy tea that is made in the Czech Republic. 20.068 20.174 0.830 20.160 20.108 20.007 I always prefer to buy wine that is made in the Czech Republic. 20.091 20.125 0.707 0.130 20.021 20.028 I always prefer to buy beer that is made in the Czech Republic. 20.041 20.272 0.456 0.256 20.245 20.166 I consistently consider the country of origin when purchasing tea. 20.084 0.116 0.070 0.776 0.122 0.291 I consistently consider the country of origin when purchasing coffee. 0.009 0.002 20.207 0.773 0.169 0.078 I consistently consider the country of origin when purchasing beer. 0.004 20.133 0.134 0.692 20.213 0.013 I consistently consider the country of origin when purchasing wine. 20.093 0.105 20.272 0.688 20.191 20.087 I will purchase coffee produced outside the EU with confidence. 20.069 0.064 20.306 20.072 0.834 20.013 I will purchase tea produced outside the EU with confidence. 20.054 0.018 20.008 20.057 0.800 20.018 The country from which the beverage originates is a quality indication. 20.147 20.261 0.015 0.056 20.104 0.778 I would rather buy a beverage with a certification of origin. 0.167 0.153 20.005 0.110 20.030 0.727 Source. Own research. Note. F = factor. Velc ˇovska ´and Waliszewska ´9 country of origin effect that make Australians buy Champagne [Conference session]. ANZIBA Conference Proceedings 2004: Dynamism and Challenges in Internationalisation. Oberecker, E. M., Riefler, P., & Diamantopoulos, A. (2008). The consumer affinity construct: Conceptualization, qualitative investigation, and research agenda. Journal of International Marketing,16(3), 23–56. https://doi.org/10.1509/jimk. 16.3.23 Papadopoulos, N., Heslop, L. A., & Bamossy, G. (1990). A comparative image analysis of domestic versus imported products. International Journal of Research in Marketing, 7(4), 283–294. https://doi.org/10.1016/0167-8116(90)90005-8 Pes ˇtek, A., Agic, E., & Cinjarevic, M. (2018). Segmentation of organic food buyers: An emergent market perspective. British Food Journal,120(2), 269–289. https://doi.org/10.1108/ bfj-04-2017-0215 Pharr, J. M. (2005). Synthesizing country-of-origin research from the last decade: Is the concept still salient in an era of global brands? Journal of Marketing,13(4), 34–45. https:// doi.org/10.1080/10696679.2005.11658557 Rezvani, S., Javadian Dehkordi, G., Sabbir Rahman, M., Fouladivanda, F., Habibi, M., & Eghtebasi, S. (2012). A conceptual study on the country of origin effect on consumer purchase intention. Asian Social Science,8(12), 205–205. https://doi.org/10.5539/ass.v8n12p205 Roth, K. P., & Diamantopoulos, A. (2009). Advancing the country image construct. Journal of Business Research, 62(7), 726–740. https://doi.org/10.1016/j.jbusres.2008.05.014 Sadı´lek, T. (2019). Consumer preferences regarding food quality labels: The case of Czechia. British Food Journal,121(10), 2508–2523. https://doi.org/10.1108/bfj-03-2019-0150 Shimp, T. A., & Sharma, S. (1987). Consumer ethnocentrism: Construction and validation of the CETSCALE. JMR, Journal of Marketing Research,24, 280–289. https://doi.org/ 10.1177/002224378702400304 Spa ´c ˇil, V., Hora ´kova ´, J., & Grendysa, D. (2022). The impact of consumer profile on the attitudes on the European wine markets [Conference session]. Proceedings of the 6th International Conference on European Integration 2022. S ˇtrach, P. (2009). Mezina ´rodnı´management. Grada. S€ ur€ uc€ u, L., Yikilmaz, I., & Maslakcxi, A. (2022). Exploratory factor analysis (EFA) in quantitative researches and practical considerations. Center for Open Science. https://doi.org/10. 31219/osf.io/fgd4e Tamasx, A. (2016). Is the country of origin an important cue when buying wine? Journal of Eastern Europe Research in Business & Economics, 2016, 1–14. https://doi.org/10.5171/ 2016.385656 The Food Industry Association. (2015). U.S. grocery shopper trends 2015 – Full Report. https://www.fmi.org/forms/store/ ProductFormPublic/u-s-grocery-shopper-trends-2015-fullreport The Nielsen Company (US). (2017). ‘‘Made in’’ matters.or does it? How consumer perceptions about country of origin are translating to purchasing behaviors around the world. http:// files.r-trends.ru/reports/global_vs_local_brands_report_nov_ 2017.pdf Tokinomo. (2022, April 13). Top 5 shopper profiles for grocery stores. https://www.tokinomo.com/blog/shopper-profilesgrocery-stores Velc ˇovska ´,S ˇ. (2018). Zhodnocenı´mezigenerac ˇnı´ch postoju ˚c ˇesky ´ch spotr ˇebitelu ˚ke znac ˇka ´m kvality potravin. SAEI, vol. 50. VSB-TU. Velc ˇovska ´,S ˇ., & Valec ˇkova ´, J. (2018). Food quality perception in the context of product origin in European Union countries: A study of generation Baby Boomers [Conference session]. Proceedings of the 4th International Conference on European Integration 2018. Velc ˇovska ´,S ˇ., & S ˇvajdova ´, L. (2022). A consumer behaviour study: Is the country of origin important factor in the European Union beverage market? [Conference session]. Proceedings of the 6th International Conference on European Integration 2022. Vesela ´, J., & Zich, R. (2015). The country-of-origin effect and its influence on consumer’s purchasing decision. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis,63(2), 667–673. https://doi.org/10.11118/actaun20156 3020667 Vrontis, D., & Basile, G. (2022). New media marketing as a driver of enterprise country of origin (COO) offer in international markets. International Journal of Entrepreneurial Behaviour & Research,28(5), 1222–1244. https://doi.org/10. 1108/ijebr-01-2021-0085 Wanninayake, W. M. C. B., & Chovancova, M. (2012). Consumer ethnocentrism and attitudes towards foreign beer brands: With evidence from Zlin region in the Czech Republic. Journal of Competitiveness,4(2), 3–19. https://doi.org/ 10.7441/joc.2012.02.01 Yang, R., Ramsaran, R., & Wibowo, S. (2016). A conceptual model for country-of-origin effects. Asia Pacific Journal of Advanced Business and Social Studies,2(1), 96–116. Yang, R., Ramsaran, R., & Wibowo, S. (2022). Do consumer ethnocentrism and animosity affect the importance of country-of-origin in dairy products evaluation? The moderating effect of purchase frequency. British Food Journal, 124(1), 159–178. https://doi.org/10.1108/bfj-12-2020-1126 Zamazalova ´, M. (Ed.). (2010). Marketing (2nd ed.). C. H. Beck. Zhang, Y., Jin, S., Zhang, Y. Y., & Yu, X. (2020). How country of origin influences Chinese consumers’ evaluation of imported milk? China Agricultural Economic Review,13(1), 150–172. https://doi.org/10.1108/caer-06-2019-0103 16 SAGE Open