Globalisation has driven mass immigration, impacting the demographics of many nations (UN, 2002). As ethnic minorities gain economic influence (1), understanding their evolving identities within their new homes becomes crucial for businesses. This includes how their sense of belonging (ethnic consumer identity) shapes their purchasing decisions, such as choosing between products from their heritage and those of their adopted country (see Cleveland, Papadopoulos & Laroche, 2011). This paper explores how variations in ethnic identity among consumers living in a host country affect their purchasing behaviour towards products and services from their home country and the host country.

To fully comprehend ethnic consumer identity, it is essential to ascertain which factors shape it; however, previous literature reveals that past research (2 3) offers only a limited empirical appraisal of the antecedents of ethnic identity. For example) presented six indicators to measure ethnicity (i.e., language use, religion, social interaction, background, spouse’s ethnic identity and self- identification). Author made significant contributions to the conceptualisation of ethnic identity but overlooked the impact of changes in the image of the country of origin (home country) and the country of residence (host country), which any immigrant has, which can affect the identity of immigrants.

Furthermore, it is meaningful to ascertain the extent to which a consumers’ ethnic identity influences their perceptions and behaviour of purchase intention towards home or host country.

In line with this reasoning, another aim of the paper is to examine the mechanisms underpinning the ways through which consumers’ ethnic identities shape their cognitive assessments of host- vs home-country products and services. In this regard, this paper investigates the cognitive and affective country images of the home and host country as determinants of consumers’ identities and purchasing intentions. Cognitive country image captures a consumer’s beliefs regarding a specific country, such as its economic development, living standards and technological development (3,4,5). Affective country image refers to the consumer’s emotional response (positive and negative) to a specific country (6,7,8). Past research (9,10,11) demonstrated that consumers prefer products from countries for which they hold a more positive memory (positive cognitive country image), such as countries seen as having economic power and technology. For example, when choosing between Chinese and Japanese products, consumers might prefer Japanese goods simply due to a more positive (cognitive) country image. This might also change for different ethnic groups. For instance, Koreans tend to prefer Chinese products over Japanese ones, because they have negative associations with Japan and its products due to longstanding historical issues between the two countries (12). Furthermore, affective country image is known to directly impact product evaluation and purchasing intention (Laroche et al., 2003). Expanding upon the example of Korean consumers evaluating Japanese goods, it is likely that the negative associations carry emotional value, shaping a negative affective country image above and beyond their cognitive country image. Existing research on country image has extensively documented the dual impact of cognitive and affective country image on purchase intentions and, more broadly, purchase behaviour (13). Moreover, it has been established that ethnic consumers have a positive intention to buy their home country’s products and services, and consumer ethnicity predicts the intention to buy (14,15).

Similar conclusions can be derived from studies showing how nostalgia for the home country adds positive feelings to home-country products and services, which makes immigrants more attached to their home country’s products and services (16,17). It is, therefore, possible to assume that immigrants who have positive emotions about their home country might make efforts to maintain their ethnic consumer identity through purchases.

Accordingly, expanding upon past research (18-20), this paper assumes that: i) purchase intentions can be determined by both the cognitive and affective images of immigrants for their home and host country; and ii) the images of the home and host countries can affect the immigrants’ ethnic consumer identity. Existing country image studies have overlooked the fact that country image may contribute to the formation of consumer identity, often assuming that ethnic consumers with the same identity are loyal to their home-country products and services. Furthermore, past research has not considered whether the country image of the host country can become an obstacle to the purchasing behaviour of ethnic consumers. As a result, the marketing literature is currently missing clear guidelines for predicting the buying behaviour of immigrants from an ethnic consumer perspective, which also considers host- and home-country (cognitive and affective) images.

Country image

Country image is a concept that has been considered for decades as an essential tool in international business research and practice to predict and judge consumers’ intention to buy (21-23). Indeed, many studies have presented empirical and theoretical evidence that country image has a significant impact on consumer purchase decisions, highlighting the importance of this strand of marketing research. Country image acts as a cue in consumer memory similarly to other important factors such as price, brand name or warranty, albeit not directly reflecting the performance of a product (23-24). The concept of country image was first mentioned in Nagashima’s paper (1970), where it was defined as the specific image, stereotype and standing that customer has for a given country – all of which can be shaped by historical, economic and traditional variables. The correct understanding and evaluation of country image are essential to drawing both theoretical and managerial implications from it; thus, many scholars strived to improve country image’s definition (26,27). For example, Roth and Romeo (1992) defined country image as the national image, because of consumers recognising the advantages and disadvantages of products manufactured and sold in a country, which often also forms the understanding of a given country – a definition frequently used in country image studies.

Examined consumer purchase intention processing through which certain services become connected to the country image. For example, the author emphasised the influence of country images to understand the impact of certain factors (e.g., product

knowledge and product involvement) on consumer decision making. Accordingly, they claimed that consumers find some countries’ products and services to be more important and meaningful than others, leading to a connection between the perceived country image and the consumer decision. work is particularly relevant to this paper, because it serves as a premise for the assumption of a theoretical link between country image and consumer purchase decisions through the lens of meaning creation. Indeed, later studies further confirm the psychological mechanism through which consumers develop meaningful information about the country image, and subsequently use this information to generate purchasing-related perception (28,29). These cognitive and affective mechanisms shape the relationships that consumers form with country images over time (30-32).

Similar conclusions can be inferred from studies that embraced a slightly different perspective. For instance, argued that the product image is built through a two-way communication process between the image of the source country and the level of product involvement. In other words, consumers like to have different levels of involvement in the product as needed, based on perceived information about their favoured country. This two-way process assumes interactions between consumers and the country image of the product; hence, it implies that consumers engage in emotional interactions with the product of choice, developing feelings toward the product (e.g., a feeling of closeness), which might increase the perceptions of value. Other scholars (33,34) also noted that country image varies depending on the level of product involvement. For example, country image is more critical when product involvement is high (e.g., wine and cars), while country image is less critical for products with less involvement (e.g., daily groceries and clothes).

(35) used the same approach proposed by Wang et al. (2012) to measure the strength of the country image and the resulting relationship with purchase decisions. They examined the effects of source products’ reputation (e.g., cognitive and normative country image of products) and consumer experience (e.g., effects of emotions and passion towards products on the country image relationship) with high-involvement products. The empirical results indicated that consumer experience has a stronger bearing than product reputation, confirming the importance and strength of the link between the affective aspect of country image and consumer purchase decisions.

(36) investigated the theme of country of origin as a criterion for choosing products. The author showed that the paths toward purchase intention followed three distinct trajectories, labelled as “country image”, “perception regarding the country’s products” and “perception towards consumers of the products”. In particular, the author emphasised that the country image and perception regarding the country’s products presented positive relationships with the purchase intention; yet, perception towards consumers of the products did not affect purchase intention. In a similar vein, expanded the base of the country image by applying it to a new field, namely country ecological image. The author argued that consumers could accept high prices if they positively perceive a country with a desirable ecological image. They concluded that the country’s ecological image could help increase demand by differentiating eco-friendly products and increasing favourability in globalised markets.

Although some of the studies mentioned so far focused on different theoretical facets of country image, they share a common underlying assumption. Most of the country image studies examine consumer purchase intention and decision based on the country image associated with the product. Contributions in this area primarily addressed the product’s image based on the ‘made in’ or ‘brand origin’. The image itself (cognitive country image) and related emotions (affective country image) are conceptually distinct from the image of the product. Accordingly, understanding the country image is still a significant challenge for today’s marketing research. The country image provides consumers with information that functions as an external signal, which affects their product purchase intentions, but several factors require improved understanding or further research. This is particularly relevant to consumers’ ethnicity and their perception of both the home and host countries’ cognitive and affective images. For instance, any animosity consumers might have towards their home country or a host country reflects a negative view, while affinity would imply a sustained positive attitude.

Home and host country and purchase intention

 Stressed that to measure consumer purchasing decisions, it is important to know where the consumers consider their home country and host countries. The author emphasised that the home and host country are determined by where consumers were born or raised, and highlighted that even within the same ethnic group, members can have different identities. For example, the second generation of consumers born and raised in the host country might consider the host country as their home country and show a strong desire to purchase products from that country rather than from the original home country.

(39) discussed consumers’ perceptions and their role in the theory of narrative identity, delving into the ways consumers draw upon the image of the home country to resolve purchasing-related conflicts. Narrative identity theory provides a conceptual ‘bridge’ between the reconstructed past (e.g., home country) and the present (host

country), assuming that consumers form an identity by integrating their experiences into stories (40). For example, images of a home country may help consumers symbolically resolve conflicts between their ideal purchasing and current purchasing. Therefore, consumers who develop positive perceptions of, or emotions for, their home country may do so to express ideal or actual selves through the products and services from the home country. In this regard, the work of (40) is particularly relevant, given that it provides theoretical and empirical evidence of the fact that perception of the image of home country is an emotional pathway towards achieving purchasing decision-related goals. As such, the paper includes the affective home country’s image as a dimension of consumer decision-making behaviours. Additionally, this paper examines the impact of the cognitive home country image and the host country’s image (affective and cognitive) as determinants of consumer purchase decisions.

Drawing upon the findings of (40) expanded the underlying dimensions of purchasing decisions associated with the country image, and included several other elements (e.g., animosity, collective memory, rumour and equity restoration). Confirmed that different cultures could experience different emotions toward the home country image and its products. For instance, while Chinese consumers are attached to their home country’s products, which are fully trusted and evoke good memories, Indian consumers have shown that they do not place any value on trust and good memories. More recent studies have incorporated the country image conceptualisation by (40) to examine the determinants and implications of emotional relationships between the home country and consumers. For example, concluded that the feelings consumers have about their home country are antecedents of willingness to buy and loyalty. Chand and Tung

(2011) found that feelings toward specific countries other than the home and/or host country have a positive effect on purchase intentions towards products from the home and/or host country. This outcome was linked to the psychological effects of how consumers perceive their feelings for their home and host countries. Similarly, (41) confirmed that country image in the context of emotions (e.g., pride or shame) has the power to mediate the influence of consumer identity and loyalty towards their home country.

More recently, Papadopoulos, (42) emphasised that both affective and cognitive responses to the source country affect the purchase of products and the country image evaluation of consumers. The author examined how the image consumers had about the old country could be exercised in their current purchasing decisions, and whether such a relationship could shape consumers’ attitudes toward products from countries perceived as friendly or hostile to the home country. The author pointed out that country and product image, affinity and hostility work differently in dissimilar countries. Another important implication of Papadopoulos, El Banna, and Murphy’s findings is that a negative and hostile perception of the source country has a strong impact on the intention to purchase the source country’s products. Therefore, affective country image (both positive and negative) for the source country has a significant impact on purchase intentions (44).

Overall, home country image is a crucial concept affecting how consumers make purchase decisions, with clear implications for researchers and practitioners. Yet, existing frameworks (e.g., 45-48) have largely overlooked the link between consumers’ cognitive and affective images

of the host country. Furthermore, past research (40) focused on measuring consumer loyalty to the image of the home country. To address these issues, this paper assumes that consumers’ purchasing decision involving choosing home vs host country products are impacted by the images of the home and host countries, respectively. It further assumes that country image of home and host comprises a cognitive and affective dimension (49). In doing so, this paper is also linked to past research on country image effects, which highlights that the purchase intentions of consumers can often vary depending on their affective country images towards their host countries (e.g., Chand & Tung, 2011; Laroche et al., 2003).

Consumers’ Ethnicity and Purchase Intention

Shimp and Sharma (1987) proposed consumer ethnocentrism as a construct that describes beliefs held by consumers about the appropriateness (or otherwise) of purchasing foreign-made products. The author found that American consumers found different levels of ethnocentric tendencies for products in each region of the United States. At the same time, Klein, Ettenson & Morris (1998) pointed out that although Chinese people recognise Japanese products as having high quality and technology, Chinese consumers in Nanjing may not buy Japanese products because of their hostility toward Japan. The author reported that hostility and cultural factors related to purchasing foreign products affect the weight given to the national image in the product purchase decision (Han & Guo, 2018). Other studies (e.g., Al Ganideh & Awudu, 2021; Cleveland, Papadopoulos & Laroche, 2011; Hamelin, Ellouzi & Canterbury, 2011; Laroche et al., 2003) highlighted that there is a positive association between the consumers’ identity and purchasing intention. For example, Laroche et al. (2003) showed that the image of

the home-country products strongly impacted the purchasing behaviour of French Canadians and British Canadians. Specifically, these two ethnic groups revealed strong intentions to purchase homeland products, and had a positive attitude toward products from allied countries such as Hong Kong and Australia. In contrast, Chand and Tung (2011) pointed out that Chinese Canadians’ loyalty to their home-country products is very strong, while Indian Canadians’ loyalty is relatively low, which suggests that different ethnic groups might have different levels of loyalty towards home-country products. Overall, existing research has confirmed that consumers’ ethnicity can impact their values (e.g., identity) and consumption patterns (e.g., purchasing intention and decision). The continued increase in the proportion of ethnic consumers, especially in a multicultural country such as Australia, means that the ethnic consumer market is potentially quite profitable.

HYPOTHESES DEVELOPMENT

Consumers' perceptions of their home and host country may affect their ethnic consumer identity. Emotions for the home country form nostalgia, which denotes longing for the past or positive or negative feelings about experiences and memories related to the past (Fairley, 2003; Holbrook & Schindler, 1996). According to Ray and McCain (2012), consumers consider their home country as the place where they were born and spent their childhood; thus, they often tend to cherish nostalgic memories of their home country and feel an inseparable connection between the home country – a fact that shapes their ethnic consumer identity.

Previous CI studies concentrated primarily on the implications of the cognitive image of the source country and PI (Han, 1989; Jin et al., 2018; Li et al., 2014; Nagashima, 1970; Roth & Diamantopoulos, 2009; Wang et al., 2012). Some studies (see Brijs, 2006; Papadopoulos & Heslop, 2000; Roth & Diamantopoulo,s 2009; Verlegh, 2001) claimed that immigrants

 indicated positive emotions and a strong PI toward their home country products, highlighting the significance of ACI and clarifying how emotions about the home country affect PI. Although these studies recognised the importance of CI and consumer identity (e.g., Han, 1989, 1990; Laroche et al., 2005; Nagashima, 1970, 1977; Park, Zourrig & El Hedhli, 2021; Roth & Diamantopoulos, 2009), the mechanisms through which the relationship between the CI and the consumer identity unfolds remain unclear. Moreover, the ways through which PI develops for immigrants because of CI, and for host vs. home country products and services are unknown. Based on the literature considered so far, this paper proposes the following hypotheses:

H1. CCI for the home country (hereafter 'Home CCI') significantly and a) positively influences PI of products and services from the home country (hereafter ‘Home PI’), b) negatively influences PI of products and services from the host country (hereafter ’Host PI’),

1. c) positively influences ethnic consumer identity.

H2. Positive ACI for the home country (hereafter 'Home positive ACI’) significantly and a) positively influences home PI, b) negatively influences host PI, and c) positively influences ethnic consumer identity.

H3. Negative ACI for the home country (hereafter 'Home negative ACI') significantly and a) negative influences home PI, b) positively influences host PI, and c) negatively influences ethnic consumer identity.

H4. CCI for the host country (hereafter 'Host CCI') significantly and a) negatively influences home PI, b) positively influences host PI, and c) negatively influences ethnic consumer identity. H5. Positive ACI for the host country (hereafter 'Host positive ACI’) significantly and a) negatively influences home PI, b) positively influences host PI, and c) negatively influences ethnic consumer identity.

H6. Negative ACI for the host country (hereafter 'Host negative ACI') significantly and a) positively influences home PI, b) negatively influences host PI, and c) positively influences ethnic consumer identity.

Shared memories and cultural experiences can shape how consumers from similar backgrounds view products and services, influencing their purchase decisions (Chand & Tung, 2011; Laroche et al., 2003). Existing research (Cleveland, Papadopoulos & Laroche, 2011; Laroche et al., 2003; Liu, 2011). Research suggests a strong link between a consumer's identity and their evaluation of a product's potential purchase (purchase intention) (Laroche et al., 2003). This identity can also influence their feelings towards their home and host countries (El Banna et al., 2018; Yelkur, Chakrabarty & Bandyopadhyay, 2006). A positive association with their heritage can lead to a stronger desire to purchase products from their home country, while a negative association might have the opposite effect (El Banna et al., 2018; Yelkur, Chakrabarty & Bandyopadhyay, 2006). Therefore, this paper examines consumer identity as a key factor influencing purchase intention, and proposes the following hypotheses:

H7: Ethnic consumer identity has a positive influence on purchase intention for home country products and a negative influence on purchase intention for host country products.

QUANTITATIVE METHODOLOGY

The empirical work conducted for this paper aimed to recruit multiple ethnicities which has not been done in previous studies. To achieve this, a non-probability, convenience sampling approach was employed. The use of convenience sampling in research, while often criticised for its lack of statistical representativeness, can be justified in certain contexts. This paper argues that convenience sampling was a suitable method for the given research on multicultural consumer behaviour, particularly given the practical constraints, exploratory nature of the study, and the potential for analytical generalisation (Schreuder, Gregoire & Weyer, 2001).

One of the primary justifications for using convenience sampling was the time and cost constraints associated with conducting a probability sample across multiple countries. As Marshall (1996) noted, non-probability samples are often more efficient in terms of time and resources. Moreover, the target populations, particularly in ethnic group with smaller sample sizes like Latvia and Italy, have been difficult to access using traditional probability sampling methods, especially during the COVID-19 pandemic. Convenience sampling provided a practical solution to these challenges. The study aimed to explore multicultural consumer behaviour who live in a multicultural society. As Flick (2018) and Guest et al. (2006) emphasise, non-probability sampling is often used in exploratory research to gain insights and develop hypotheses. The focus was on understanding specific phenomena and generating ideas, rather than achieving statistical representativeness for each ethnic group. While convenience sampling may not allow for statistical generalisation to a larger population, it can still contribute to theoretical understanding. As Yin (2017) and Small (2009) argue, the validity of research lies in the richness and relevance of the data, not solely in its representativeness. By providing in-depth insights into multicultural consumer behaviour, the study can contribute to the development of theories and frameworks in this field. In conclusion, the use of convenience sampling in this multicultural consumer behaviour research was justified by practical considerations, the exploratory nature of the study, and the potential for analytical generalisation. While the uneven sample sizes may be a limitation, the study provides valuable insights into multicultural consumer behaviour and contributes to theoretical development in this field. Future research could explore these topics further using more representative sampling methods.

Participants from various ethnicities were recruited in Australia through a combination of incentives (gift vouchers, community donations) and communication channels (social media, community events, word-of-mouth). Samples consisted of four ethnic consumer groups (Vietnamese, Latvian, Iranian and Italian) of participants over 18 years, who have lived in Australia for more than a year and are classed as first or second-generation ethnic consumers, as per the following criteria. Ultimately, the overall number of completed questionnaires reached 348. However, some entries were incomplete (e.g., less than 50% of answered questions) and/or otherwise unusable (e.g., all items with similar replies or inconsistent responses), leaving a final sample of 261 usable questionnaires. A sample size of SEM plays a vital role in estimating and interpreting SEM results. In general, in literature (Delic, 2010; Hair et al., 2006; Siddiqui, 2013), the sample size of SEM is typically executed in the range of 200 to 400, and at least 100, preferably 200 (Siddiqui, 2013). If the sample size is less than 200, the parameter estimates are generally unstable, and the power of the statistical significance test is insufficient. The total number of samples in this paper was 261, reflecting the appropriate sample size of SEM.

The survey was created using Qualtrics software and distributed through a combination of social media (Facebook) and direct email to reach diverse consumer groups. This mixed approach aimed to maximize exposure to the survey and encourage participation (Iribarren et al., 2018; Lüdtke et al., 2008; Strömmer et al., 2018). Relying solely on email, for example, risks limiting the reach to specific demographics, while social media can broaden the pool of potential participants (MacCallum, Browne & Sugawara, 1996; MacKinnon et al., 2002;

Preacher, Zyphur & Zhang, 2010). To ensure participants understood the survey, researchers translated the questionnaire from English into four languages (Farsi, Vietnamese, Italian, and Latvian) commonly spoken by the target ethnicities. Translators were native speakers fluent in both languages, minimizing comprehension issues (Currents, 1991; Shimizu, 1995). Additionally, a back-translation process verified the accuracy of the translated versions (Brislin, 1970). CCI was measured using the 14 items adapted from Martin and Eroglu (1993). ACI was measured using 20 items adapted from Watson et al. (1988); Glick et al. (2006). Ethnic identity was measured using the 9 items adapted from Cleveland, Papadopoulos and Laroche (2011) and El Banna et al. (2018). For each of these measures, respondents were able to select one value from a 7-point Likert range, where 1 indicated strongly disagree and 7 indicated strongly agree.

Demographic profile of respondents

The demographic profile of the respondents who returned usable questionnaires is seen in Table

As demonstrated in Table 4.1, 64% of respondents were aged between 26 and 45.

Approximately 80% of the samples were educated at the university or university level, and nearly 60% were female. In addition, 38.7% of the respondents were Iranian and 38.7% of respondents were Vietnamese; about 14% were Latvian and only 8% were Italian. 82% of the participants were born in their home countries, and 17.6% were born in Australia. Finally, with respect to annual household income, over a third of respondents earn less than AUD50,000 per year, and 41% earn more than AUD 50.001. With respect to occupation, 44.8% of the respondents had jobs, 24.1% were students, and 16.5% were unemployed. Considering the natural self-satisfaction caused by voluntary participation, a higher proportion of people with high education levels and income were shown. The job of the respondent was categorised into five classes, according to The National Statistics Socio-Economic Classification (e.g., I-

Professional occupations, II- Managerial and Technical occupations, III- Skilled occupations, IV- Partly skilled occupations, and V - Unskilled occupations, Pevalin & Rose 2002). Half of the respondents were professionals; 15% held managerial and technical occupations, and another 15% held skilled occupations.

Table 4 1 Demographic profile of the characteristics of the respondents (N =261)

Confirmation Factor Analysis (CFA)

To estimate the degree to which observed variables represent the underlying latent variables, the compositional reliability of the scales used in the paper was examined through CFA (Byrne 2016). Table 5.1 indicates that the obtained loadings for all latent variables (i.e., CI, consumer identities and PI) stood above the suggested value of 0.6 with no cross-loading measures exceeding 0.6. Table 5.1 also shows the descriptive measures of the main constructs. Respondents are consistently distributed across each construct, indicating that there is no response bias.

In examining the convergent and discriminant validity, the paper assessed the psychometric attributes of the included constructs and their respective measurement items. The CFA results also confirmed the internal consistency, indexed by composite reliability scores. The CR measures ranged from 0.85 to 0.95, and all items exceeded the recommended threshold value of 0.70 (Chin, 1999). Furthermore, the average variance extracted (AVE) measures were greater than 0.5 (e.g., negative affective CI, and ethnic consumer identity = 0.647), indicating that the variance explained by the items was greater than the variance due to measurement error

(Fornell & Larcker, 1981). Concerning convergent validity, AVE measures of each latent construct surpassed the construct’s highest squared correlation score with any other latent constructs. This revealed a strong discriminant validity for the measurement items (Hair, Ringle & Sarstedt, 2011, 2013).

Table 5. 1 Measurement items, factor loadings, and descriptive analysis

With respect to discriminant validity, all the AVE values exceed the squared inter-construct correlations, confirming that constructs are independent of one another (Fornell & Larcker, 1981; Hair, Ringle & Sarstedt, 2011, 2013). The maximum shared variance (MSV) values were greater than AVE (e.g., EI: MSV = 0.219 < AVE 0.647), and thus the items have discriminant validity. The MSV measures the degree of overlap of two or more variables, showing the amount the variations of the multi variables tend to vary together (Hair et al., 2006).

Table 5. 2 CFA and Validity measurements (Squared Correlations)

Table 5.2 illustrates an excellent factor structure in which convergent and discriminant validity is supported by the significant loadings within factors and no evident major cross-loadings between factors. In summary, the results of these tests confirmed that the proposed model was both appropriate and robust.

SEM Outcomes

Figure 5.1 presents the R-squared value of the model. It is important to note that all the main constructs in the paper are interchangeable, and all measures are reflective constructs. The reflective constructs explain that all indicators have a relatively high correlation with latent

variables (Preacher, Zhang & Zyphur, 2011; Preacher, Zyphur & Zhang, 2010). The results of path analysis indicate that the R-squared values are relatively high for all dependent latent constructs. In more detail, R-squared values of ethnic consumer identity (0.24) substantially surpass the suggested cut-off value of 0.10 (Falk & Miller, 1992). Regarding PI, the R-squared values were also significant (PI of home country = 0.32, PI of host country = 0.31).

Figure 5. 1 SEM path

To test the stated hypotheses, path analysis and standardized coefficients were used (see Table 5.3). Table 5.3 shows the path coefficients of the structural equation model Estimate, standard error (SE), critical ratio (CR) and P-value. CR is generally a value calculated by dividing the mean difference between the two sets of scores by the standard error of the difference. If the CR value is greater than 1.0, it is ideal; if it is less than 1.0, the performance deteriorates. SE is the approximate standard deviation of a sample population and measures the sample distribution’s accuracy representing the population using the standard deviation. What now follows is a summary of test results against hypotheses (see Table 5.3).

Table 5. 3 SEM analysis results (Standardized Regression Weights)

*Significant at p<0.05 (two -sided)

The results show that home CCI does not impact ethnic consumer identity (β = -0.008, p-value

= 0.929), rejecting H1c. Furthermore, home CCI demonstrates a direct and significant impact on both PI of home country products and services (β = 0.215, p-value = 0.027) and PI of host country products and services (β = -0.203, p-value = 0.033); thus, H1a and H1b are supported.

 The results reveal that home positive ACI a significant positive impact on ethnic consumer identity is visible (β = 0.463, p-value = 0.00); thus, H2c is confirmed. Furthermore, home positive CCI affects both the PI of home (β = 0.384, p-value = 0.00) and host country products and services (β = -0.344, p-value = 0.00). Thus, H2a and H2b are supported.

Home negative ACI, as the results show, does not affect ethnic consumer identity (β = -0.018, p-value = 0.836), which leads to the rejection of H3c. Similarly, home negative ACI does not directly influence either of PI of home (β = 0.109, p-value = 0.828) and host country products and services (β = 0.022, p-value = 0.798), confirming that H3a and H3b are also not supported.

The results show that host CCI does not affect either of ethnic consumer identity (β = 0.03, p- value = 0.738), rejecting H4c. However, host CCI significantly and positively impacts both PI of home country products and services (β = -0.252, p-value = 0.03), and PI of host country products and service (β = 0.164, p-value = 0.04); thus, H4a and H4b are supported.

The results show that host positive ACI does not affect ethnic consumer identity (β = 0.071, p-value = 0.45), leading to the rejection of H5c. Furthermore, host positive ACI does not impact either of PI of home country products and services (β = -0.055, p-value = 0.598) and PI of host country products and service (β = 0.073, p-value = 0.479); thus, H5a and H5b are not supported.

Host negative ACI, as the results show, does not impact ethnic consumer identity (β = 0.046, p-value = 0.633); hence, H6c is not supported. Nonetheless, host negative ACI has a direct and significant impact on both the PI of home country products and service (β = 0.208, p-value = 0.031), and PI of host country products and services (β = -0.193, p-value = 0.044); thus, H6a and H6b are supported.

The direct impact of ethnic consumer identity on PI, as the results show, has a direct and significant impact on both PI of home country products and services (β = 0.247, p-value = 0.00), and PI of host country products and services (β = -0.233, p-value = 0.00), confirming H7a and H7b, respectively.

Mediation Role of Ethnic Consumer Identity

Table 5.4 illustrates the outcomes of the analysis of the mediation role of ethnic consumer identity in the relationship between CI and PI. Bootstrapping is used for 2,000 resamples with bias-corrected confidence intervals of 95 (Hair et al., 2006; Preacher, Zhang & Zyphur, 2011; Preacher, Zyphur & Zhang, 2010).

Table 5. 4 Mediation role of ethnic consumer identity

NOTES: ECI = ethnic consumer identity; PI = purchase intentions; SE = Standard Error; CR = Critical ratios; BootSE = bootstrap standard error; *significant at p<0.05 (two -sided)

The results (see Table 5.4) reveal that ethnic consumer identity mediates the relationships between home CCI and PI of home country products and services (bootstrapping estimate = 0.213, bootstrap lower-level confidence intervals (LLCI)=-0.095, bootstrap upper-level confidence intervals (ULCI)= 0.525, p-value = 0.016). It also mediates the relationships between home positive ACI and PI of home country products and services (bootstrapping estimate = 0.450, LLCI = 0.117, ULCI = 0.816, p-value = 0.003); between home CCI and PI of host country products and services (bootstrapping estimate = -0.310, LLCI = -0.6, ULCI = -0.01, p-value = 0.043); and between home positive ACI and PI of host country products and services (bootstrapping estimate =-0.332, LLCI = -0.682, ULCI = 0.033, p-value = 0.006). Nonetheless, ethnic consumer identity does not mediate the relationship between home negative ACI and PI of home country products and services (bootstrapping estimate = 0.017, LLCI = -0.31, ULCI = 0.293, p-value = 0.968), or between PI of host country products and services (bootstrapping estimate = 0.012, LLCI = -0.261, ULCI = 0.284, p-value = 0.862).

Home and host country images, and ethnic consumer identity

Positive affective home and host country image exert the most powerful influence on consumer identities. Results of this paper reveal that a positive affective country image is more powerful in explaining one's consumption identity than a cognitive country image or negative affective country image. More specifically, positive feelings for the home country drive the ethnic consumer identity. This finding is partly in line with Papadopoulos, Heslop and IKON Research Group (2000) and Cleveland, Papadopoulos and Laroche (2011), both showing positive affective country image of the home country influences consumers' intentions or behaviours (e.g., identity or purchasing). This finding also confirms that ethnic consumers respond strongly to positive emotions, without considering negative emotions toward their home country and host country when choosing or maintaining their identity.

In line with the above, a first and major contribution of this paper to marketing research lies in establishing and explaining the link between country image (affective country image and cognitive country image) and consumer identity, especially the images of ethnic consumers ' home country and host country. Specifically, this paper expands country image research with a new paradigm of consumer identity formation. The paradigm is based on evidence that country image, especially positive affective country image, shapes an immigrant’s identity. This new knowledge can explain which factors strengthen or mitigate consumer identity, moving forward research linking country image and ethnic identity research. In this regard, this paper significantly adds to the limited number of studies that explored the effects of components of country image on consumer identity as it includes a more comprehensive range of country image factors (e.g., cognitive country image, positive and negative affective country image).

Home and host country images, and purchase intention

For purchase intention, the results obtained are broadly a confirmation of previous findings from the existing literature on country image, with some interesting new takes. First, the cognitive country images of the home country and the host country strongly and significantly influence the intention to purchase products and services of the home and the host country. This is in line with previous studies (e.g., Bilkey & Nes 1982, Wegapitiya & Dissanayake 2018) that showed that country image strongly influences purchase intention due to the halo effect. The halo effect explains that consumers use country image when evaluating products, affecting purchase intention (Han 1989, 1990). New to this paper, is the finding that the cognitive country image of the home country is the main determinant of the halo effect (see also Han 1989). Put simply, the findings of this paper demonstrate that the cognitive country image affects the consumer's purchase intention for both the home country and host country products and services - a duality that has been overseen in existing country image studies.

Second, the results of this paper suggest that the positive affective country image of the home country has a positive and significant effect on the purchase intention of the home country’s products and services, while the positive emotion toward the host country does not affect the purchase intention of the host country’s products and services. These findings partially support existing literature (e.g., Brijs, 2006; Laroche et al., 2005; Laroche et al., 2003; Papadopoulos,

Heslop & IKON Research Group, 2000; Parameswaran & Yaprak, 1987; Parameswaran & Pisharodi, 1994; Roth & Diamantopoulos, 2009; Verlegh, 2001). For example, according to Laroche et al. (2003), positive feelings toward home and host countries directly affect purchasing products from home countries or host countries. However, the results of this paper show that positive emotions toward the home country influence purchase intention of home country products, not host country products. Furthermore, negative emotions toward the host country have a strong and negative effect on the intentions to purchase products and services of the host country but negative feelings toward the home country do not affect the intentions to purchase products and services of the home country. According to Li et al. (2014), negative emotions toward the source country negatively affect consumers' purchase intention, and positive emotions positively affect purchase intention. However, the results of this paper indicate that only negative feelings toward the host country affected the purchase intention. These new findings contribute significantly to the understanding of the country image effect, suggesting a stronger role of a positive affective country image, as opposed to negative feelings.

THEORETICAL IMPLICATIONS

The paper confirms the combined role of the home, and the host country images as the force behind the relationship between a consumer's identity and purchase intention (for products and services from the home vs. host country). This is a new conceptual advancement crucial to the expansion of country image literature, one of marketing’s most established strand of research. Surprisingly, the relationship between the source country and the consumer, the consumer's identity and the purchase intention of the source country have been largely neglected or misunderstood prior to this paper. In line with its aims, to remedy this knowledge void, this paper introduced and tested an integrated framework showing how the image of the home country affects the consumer's identity and purchase intention when in a host country. This new knowledge finally reduces ambiguities arising when trying to understand and predict the intention to purchase products and services from home (imports) and host (local trade) countries based on consumers’ images or feelings of their home and host countries, entrenched in their cultural backgrounds. As such, this paper sets the stage for further development of country image research by filling the gaps of previous studies and by providing clear implications for ethnic consumers' purchase intentions.

When combining all results obtained in this paper and the resulting implications of each, as discussed in the previous sections, it is clear that this paper supports literature claims of the importance of consumers' existing thoughts and emotions about the country image and the necessity for strategies that utilise consumers' identity to get closer emotionally to consumers' purchase intention (Burton, 2000; Cui, 2001; El Banna et al., 2018; Laroche et al., 2003; Papadopoulos, EI Banna & Murphy, 2017). In this regard, the key contributions are as follows.

First and foremost, this paper provides a generalisable theoretical ‘template’ to understand the ties between country image and purchase intention, taking account of the consumers’ identities in multicultural societies like Australia. Recent studies (e.g., El Banna et al., 2018; McFayden, 2021; Papadopoulos, El Banna & Murphy, 2017) have focused on the identity of ethnic consumers living in multicultural countries. Previous research has shown that consumers’ identities are varied in their reliance on both language usage and culture as well as in their religion and social status (Anderson, 2016; Bond, 2017; Hui et al., 1997; Laroche et al., 2003; Modood et al., 1997; Nwankwo & Lindridge, 1998). Two intrinsic cues found by researchers to be used consistently in this process are language usage and ethnic identity measures (El Banna et al., 2018; Hui et al., 1997; Phinney, 1992). The results of this paper confirm that the images of the home country and the host country, especially the affective state image, are the driving forces behind the development of consumer identity. Hence, providing a unique combination of positive affective country image associations between consumers and their home country, and the host country can lead to the establishment of a relationship between consumers and identity. However, social identity theory posits that consumer identity has the power to ignore (or change) according to the group to which the consumer belongs (e.g., home country or host country). While empirical evidence exists in relation to various aspects of these specific variables (e.g., language usage, ethnic identity and culture), several gaps remain in the literature about the combined effects on home and host country purchase intention. In this regard, this paper contributes to the theory by linking consumer identities (widely overlooked in existing studies) to country image, providing insights to meet the needs of ethnic consumers in multicultural nations. In addition, from a broader theoretical point of view, this paper illustrates a conceptual approach to explain how consumer perception of country image turns into affective feelings such as happiness or passion for the source state, expanding existing knowledge of the importance of country image as a mechanism leading to the development of relations as a factor in consumer identity formation.

Second, past research has established that consumers' positive affective country image of their home country leads to their intention to purchase products and services of their home country (Podoshen, 2009; Yelkur, Chakrabarty & Bandyopadhyay, 2006). Yet, the positive affective country image of the host country does not lead to the intention to purchase the host country's products, challenging the exiting evidence stating that positive affective country image affects the purchase intention (Laroche et al., 2003). Given this premise, it is not surprising that many consumers show strong purchase intention of their home products through exaggerated interpretations of their home country's positive affective country image. Moreover, previous studies highlighted that purchase intention uses cognitive country image cues more accurately and consistently than affective country image (Bilkey & Nes, 1982; Han, 1989; Wegapitiya & Dissanayake, 2018). In line with this reasoning, the results of this paper contribute to theory regarding the implications of country images for product purchase intentions and preferences, emphasising the relationship between affective country images and purchase intentions, which have often been neglected in existing studies (e.g., Han, 1990; Jin et al., 2018; Li et al., 2014; Su, 2010; Yelkur, Chakrabarty & Bandyopadhyay, 2006).

MANAGERIAL IMPLICATIONS

In terms of managerial implications, the results of this paper translate into multiple practical insights, some of which are relevant to marketing managers while others are more closely linked to consumer policies. In a multicultural country like Australia, this can be an important consideration in marketing the most appropriate products and services to meet customer needs. In more detail, the implications of this paper are as follows.

Firstly, it is critical that marketing managers understand the influence of country image (e.g., home and host) when assessing consumers' buying behaviour to ensure that marketing efforts are focused on enhancing those attributes most likely to influence consumer identity regarding purchase intention. Therefore, international marketing managers need to monitor and profile the identities of the ethnic consumers. This can be achieved by systematically analysing products to be launched, focusing on the individual interactions with the consumer identity (e.g., ethnic consumer identity). Multinational countries, such as Australia, classify a large percentage of the population as ethnic consumers, so understanding and serving these consumer needs are paramount. Otherwise, businesses may risk missing out on important sales opportunities and appear lagging behind the modern multi-cultural marketing playfields. Therefore, it is important to include mentioning positive emotions in marketing tactics for ethnic consumers - this strategy can be equally applied to promoting products and services imported, manufactured, and distributed nationally. These connections are likely to influence consumer perceptions at a core psychological level due to an implicit alignment with their ethnic identity.

Second, this paper's important managerial implication consists of providing a template for measuring and understanding consumer ethnic identity in a marketing setting, linking it to buying predispositions. In the case of the consumers surveyed, it was found that the influence of the home positive affective country image had a greater influence on the identity of consumers than the home negative affective country image. These results were determined even though the scope of consumer groups (e.g., Vietnamese, Iranian, Latvian and Italian) surveyed was considerably more comprehensive than in previous studies. The simplicity and accuracy of the proposed conceptual model make it particularly appealing for market research purposes. Understanding and providing consumers' needs better than other players is essentially a key competitive advantage, especially for discovering new market opportunities for international and national brands that want to export to multinational companies and grow domestic sales. In this regard, marketing practitioners could see value in researching and understanding ethnic consumers using the same (or a similar) protocol to this paper. Doing so will return simple indicators of consumer interests and predispositions as well as likely factors that must be considered to succeed.

LIMITATIONS AND FURTHER RESEARCH

While this paper offers important theoretical and managerial implications, several limitations are evident. These include limitations in terms of i) sample size and groups, ii) sampling methods, and iv) measurement.

Firstly, the type of sample group and the total number of samples can limit the ability to generalise results. The total number of samples used in this paper was 261. Due to the COVID- 19 pandemic, data collection was significantly slowed down and, at times, completely halted, due to repeated lockdowns. Therefore, considering the overall size of the sample, future studies require subsamples, larger samples of these ethnic groups, or additional samples of other ethnic groups to further extend the generalizability of the results.

Secondly, another limitation of this paper is the use of non-probability convenience sampling. Despite the advantages of this sampling method, including speed and lower recruitment costs (Etikan, Musa & Alkassim, 2016), it only captures a portion of the target population, particularly those who wish to participate and cooperate in the survey (Fricker, 2008). Future research could address this limitation by utilizing probability sampling techniques. This might involve using stratified sampling to ensure representation of various ethnicities within the target population or quota sampling to achieve specific demographic proportions. While these methods might require more resources and time for recruitment, they would yield data that can be more confidently generalized to the entire population of interest.

Finally, there are limitations in terms of the way consumer identity and purchase intention are measured. While consumer identity is a combination of hundreds of country image cues, the

measurement and methodology only allow examination of a limited number of these cues. In this paper, only nine items were used to measure consumer identity and only a quantitative approach was used. Purchase intention was also measured using only four items. In addition, the only dependent variable in this paper was purchase intention, and thus, the results cannot shed light on other important aspects of purchase behaviour, such as purchase decisions, by looking at actual purchases made by consumers, willingness to pay a premium price, and purchase involvement. Future research could benefit from a more nuanced approach. For instance, a multi-method approach: employing a combination of quantitative and qualitative methods could provide a richer understanding of consumer identity formation and its influence on purchase decisions.

1. Australian Bureau of Statistics (ABS). (2022). Census: Snapshot of Australia. Retrieved July 21, 2022, from https://www.abs.gov.au/statistics/people/people-and-communities/snapshot-australia/latest-release#culturally-and-linguistically-diverse-communities
2. Australian Bureau of Statistics (ABS). (2022). Census: Migration, Australia. Viewed July 21, 2022, from https://www.abs.gov.au/statistics/people/population/migration-australia/2019-20#key-statistics
3. Adenan, M. A., Ali, J. K., & Rahman, D. H. A. A. (2018). Country of origin, brand image, and high involvement product towards customer purchase intention: Empirical evidence of East Malaysian consumer. Jurnal Manajemen dan Kewirausahaan, 20, 63-72.
4. Ahmed, Z. U., Johnson, J. P., Yang, X., Fatt, C. K., Teng, H. S., & Boon, L. C. (2004). Does country of origin matter for low-involvement products? International Marketing Review, 21, 102-120.
5. Al Ganideh, S. F., & Awudu, I. (2021). Arab-Muslim Americans’ personality riddle and consumer ethnocentrism. Journal of Global Marketing, 34, 110-130.
6. Anderson, C. V. (2016). Shame and pride in second-generation German identity in Melbourne, Australia: Emotions and white ethnicity. Journal of Ethnic and Migration Studies, 42, 1439-1454.
7. Bannister, J. P., & Saunders, J. A. (1978). UK consumers’ attitudes towards imports: The measurement of national stereotype image. European Journal of Marketing, 12, 562-570.
8. Bazan, B., Fonseca, M. J., Cardoso, P. R., Fonseca, M. C., & Teixeira, A. (2021). The attitude of European consumers towards the country of origin of products: The influence of “made in” in the purchase intention. International Conference on Information Technology & Systems. Springer, 241-255.
9. Bond, R. (2017). Multicultural nationalism? National identities among minority groups in Scotland’s census. Journal of Ethnic and Migration Studies, 43, 1121-1140.
10. Brijs, K. (2006). Unravelling country-of-origin: Semiotics as a theoretical basis for a meaning-centered approach towards country-of-origin effects (Doctoral dissertation). University of Radboud.
11. Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1, 185-216.
12. Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge.
13. Cárdenas, D., Verkuyten, M., & Fleischmann, F. (2021). “You are too ethnic, you are too national”: Dual identity denial and dual identification. International Journal of Intercultural Relations, 81, 193-203.
14. Chand, M., & Tung, R. L. (2011). Global competitiveness, consumer choice, and ‘country of origin’ effect: An exploratory East–West study. Asia Pacific Business Review, 17, 265-280.
15. Cheng, K., Chen, H. P., Lai, W., & Li, C. (2014). Country image effect on services: A study of consumers’ evaluation of foreign airlines. Journal of Global Marketing, 27, 1-12.
16. Chu, E., White, F. A., & Verrelli, S. (2017). Biculturalism amongst ethnic minorities: Its impact for individuals and intergroup relations. Australian Journal of Psychology, 69, 229-236.
17. Cleveland, M., Papadopoulos, N., & Laroche, M. (2011). Identity, demographics, and consumer behaviors: International market segmentation across product categories. International Marketing Review, 28, 244-266.
18. Cordell, V. V. (1993). Interaction effects of country of origin with branding, price, and perceived performance risk. Journal of International Consumer Marketing, 5, 5-20.
19. Currents, C. (1991). PANSI: A survey of the ELT needs of Japanese university students. In P. Jaquith (Ed.), Content-Based Language Teaching. Language Institute of Japan, Odawara.
20. Dekhili, S., Crouch, R., & El Moussawel, O. (2021). The relevance of geographic origin in sustainability challenge: The facets of country ecological image. Journal of Consumer Marketing, 38, 664-678.
21. Strömmer, S., Lawrence, W., Rose, T., Vogel, C., Watson, D., Bottell, J., & Crozier, S. (2021). Maternal factors associated with changes in diet during pregnancy in a multi-ethnic population in the UK. PLOS ONE, 16(7), e0254322. https://doi.org/10.1371/journal.pone.0254322
22. Swoboda, B., Pennemann, K., & Taube, M. (2012). The effects of perceived brand globalness and perceived brand localness in China: Empirical evidence on Western, Asian, and domestic retailers. Journal of International Marketing, 20(4), 72-95. https://doi.org/10.1509/jim.12.0105
23. Tan, C. T., & Farley, J. U. (1987). The impact of cultural patterns on cognition and intention in Singapore. Journal of Consumer Research, 13(4), 540-544. https://doi.org/10.1086/209084
24. Thøgersen, J., Pedersen, S., & Aschemann-Witzel, J. (2019). The impact of country of origin on consumer decision making about new organic food products. International Marketing Review, 36(4), 516-543. https://doi.org/10.1108/IMR-03-2018-0080
25. Tong, X., & Hawley, J. M. (2009). Measuring customer-based brand equity: Empirical evidence from the sportswear market in China. Journal of Product & Brand Management, 18(4), 262-271. https://doi.org/10.1108/10610420910972783
26. Verlegh, P. W., & Steenkamp, J. B. E. (1999). A review and meta-analysis of country-of-origin research. Journal of Economic Psychology, 20(5), 521-546. https://doi.org/10.1016/S0167-4870(99)00023-9
27. Villegas, F. J., & Alcañiz, E. B. (2020). The influence of country image on the hedonic and utilitarian dimensions of consumer attitudes toward foreign food products. Journal of International Food & Agribusiness Marketing, 32(1), 65-86. https://doi.org/10.1080/08974438.2019.1607689
28. Wang, C. L., Li, D., Barnes, B. R., & Ahn, J. (2012). Country image, product image and consumer purchase intention: Evidence from an emerging economy. International Business Review, 21(6), 1041-1051. https://doi.org/10.1016/j.ibusrev.2011.11.010
29. Watson, J. J., & Wright, K. (2000). Consumer ethnocentrism and attitudes toward domestic and foreign products. European Journal of Marketing, 34(9/10), 1149-1166. https://doi.org/10.1108/03090560010342520
30. White, K., MacDonnell, R., & Dahl, D. W. (2011). It's the mindset that matters: The role of construal level and message framing in influencing consumer efficacy and conservation behaviors. Journal of Marketing Research, 48(3), 472-485. https://doi.org/10.1509/jmkr.48.3.472
31. Wolf, M. M., Thulin, A., & Meyerding, S. G. (2020). Sustainable consumer behavior in Germany: The influence of cultural values on product choices. Sustainability, 12(3), 875. https://doi.org/10.3390/su12030875
32. Yang, Z., & Wang, C. L. (2010). Chinese consumers’ evaluation of hybrid products: The roles of product country image and famous brand. Asia Pacific Journal of Marketing and Logistics, 22(4), 618-632. https://doi.org/10.1108/13555851011090549
33. Zeugner-Roth, K. P., & Žabkar, V. (2015). Bridging the gap between country and destination image: Assessing common facets and their predictive validity. Journal of Business Research, 68(9), 1844-1853. https://doi.org/10.1016/j.jbusres.2015.01.012
34. Žurga, M., & Grubor, A. (2021). Cultural intelligence and consumer ethnocentrism among different generations of consumers in Croatia. Journal of Business Research, 124, 92-102. https://doi.org/10.1016/j.jbusres.2020.11.058
35. Abraham, A., Bittner, E., & Kühl, N. (2022). Consumer-brand relationships in the digital age: A systematic literature review of theoretical frameworks, conceptualizations, and future research directions. Journal of Business Research, 144, 1025-1042. https://doi.org/10.1016/j.jbusres.2022.01.043
36. Adams, J., & White, M. (2005). Why don't stage-based activity promotion interventions work? Health Education Research, 20(2), 237-243. https://doi.org/10.1093/her/cyg105
37. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
38. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall. https://doi.org/10.4324/9781315824881
39. Alam, S. S., & Sayuti, N. M. (2011). Applying the theory of planned behavior (TPB) in halal food purchasing. International Journal of Commerce and Management, 21(1), 8-20. https://doi.org/10.1108/10569211111111676
40. Amatulli, C., De Angelis, M., Peluso, A. M., Soscia, I., & Guido, G. (2017). The effect of negative message framing on green consumption: An investigation of the role of shame. Journal of Business Ethics, 156(2), 351-362. https://doi.org/10.1007/s10551-017-3573-5
41. Bagozzi, R. P., & Dholakia, U. M. (2002). Intentional social action in virtual communities. Journal of Interactive Marketing, 16(2), 2-21. https://doi.org/10.1002/dir.10006
42. Bamberg, S., & Möser, G. (2007). Twenty years after Hines, Hungerford, and Tomera: A new meta-analysis of psycho-social determinants of pro-environmental behavior. Journal of Environmental Psychology, 27(1), 14-25. https://doi.org/10.1016/j.jenvp.2006.12.002
43. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. https://doi.org/10.5465/amr.1987.4306538
44. Bang, H. K., Ellinger, A. E., Hadjimarcou, J., & Traichal, P. A. (2000). Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory. Psychology & Marketing, 17(6), 449-468. https://doi.org/10.1002/(SICI)1520-6793(200006)17:6<449::AID-MAR1>3.0.CO;2-8
45. Barbarossa, C., Beckmann, S. C., De Pelsmacker, P., Moons, I., & Gwozdz, W. (2015). A self-identity based model of electric car adoption intention: A cross-cultural comparative study. Journal of Environmental Psychology, 42, 149-160. https://doi.org/10.1016/j.jenvp.2015.04.001
46. Barcellos, M. D. D., Krystallis, A., de Melo Saab, M. S., Kügler, J. O., & Grunert, K. G. (2011). Investigating the gap between citizens' sustainability attitudes and food purchasing behaviour: Empirical evidence from Brazilian pork consumers. International Journal of Consumer Studies, 35(4), 391-402. https://doi.org/10.1111/j.1470-6431.2010.00978.x
47. Barreiro‐Hurle, J., Gracia, A., & de Magistris, T. (2010). Does information about organic farming affect consumer willingness to pay for organic food? An application of the choice experiment. Food Quality and Preference, 21(4), 398-409. https://doi.org/10.1016/j.foodqual.2010.01.003
48. Becker, L., van Rompay, T. J., Schifferstein, H. N., & Galetzka, M. (2011). Tough package, strong taste: The influence of packaging design on taste impressions and product evaluations. Food Quality and Preference, 22(1), 17-23. https://doi.org/10.1016/j.foodqual.2010.06.007
49. Belz, F. M., & Peattie, K. (2012). Sustainability marketing: A global perspective. John Wiley & Sons. https://doi.org/10.1002/9781119447488
50. Beneke, J., Flynn, R., Greig, T., & Mukaiwa, M. (2013). The influence of perceived product quality, relative price and risk on customer value and willingness to buy: A study of private label merchandise. Journal of Product & Brand Management, 22(3), 218-228. https://doi.org/10.1108/JPBM-02-2013-0262
51. Bennett, R., & Chakravarti, D. (2009). When guilt begets pleasure: The positive effect of a negative emotion. Journal of Marketing Research, 46(4), 584-593. https://doi.org/10.1509/jmkr.46.4.584
52. Blankenberg, A. K., & Alhusen, H. (2019). On the determinants of pro-environmental behavior: A literature review and guide for the empirical economist. Journal of Economic Surveys, 33(1), 147-194. https://doi.org/10.1111/joes.12268
53. Borin, N., Cerf, D. C., & Krishnan, R. (2011). Consumer effects of environmental impact in product labeling. Journal of Consumer Marketing, 28(1), 76-86. https://doi.org/10.1108/07363761111101976
54. Bougherara, D., & Combris, P. (2009). Eco-labelled food products: What are consumers paying for? European Review of Agricultural Economics, 36(3), 321-341. https://doi.org/10.1093/erae/jbp023
55. Bowen, F., & Aragon-Correa, J. A. (2014). Greenwashing in corporate environmentalism research and practice: The importance of what we say and do. Organization & Environment, 27(2), 107-112. https://doi.org/10.1177/1086026614537078
56. Bray, J., Johns, N., & Kilburn, D. (2011). An exploratory study into the factors impeding ethical consumption. Journal of Business Ethics, 98(4), 597-608. https://doi.org/10.1007/s10551-010-0640-9
57. Brenton, S., & Drage, J. (2020). The motivations, enablers and barriers to sustainability: A systematic literature review of sustainable consumption frameworks. Journal of Cleaner Production, 242, 118451. https://doi.org/10.1016/j.jclepro.2019.118451
58. Bridges, C. M., & Wilhelm, W. B. (2008). Going beyond green: The “why and how” of integrating sustainability into the marketing curriculum. Journal of Marketing Education, 30(1), 33-46. https://doi.org/10.1177/0273475307312196
59. Brunner, T. A., & Wansink, B. (2013). Interpersonal influences on calorie estimation and food choice. Nutrition Reviews, 71(5), 322-327. https://doi.org/10.1111/nure.12027
60. Bublitz, M. G., Peracchio, L. A., & Block, L. G. (2010). Why did I eat that? Perspectives on food decision making and dietary restraint. Journal of Consumer Psychology, 20(3), 239-258. https://doi.org/10.1016/j.jcps.2010.06.008
61. Carfora, V., Caso, D., & Conner, M. (2016). Randomised controlled trial of a messaging intervention to reduce red and processed meat consumption in Italian university students. Appetite, 112, 63-70. https://doi.org/10.1016/j.appet.2017.01.006
62. Carroll, A. B. (1999). Corporate social responsibility: Evolution of a definitional construct. Business & Society, 38(3), 268-295. https://doi.org/10.1177/000765039903800303
63. Caruana, R. (2007). A sociological perspective of consumption morality. Journal of Consumer Behaviour: An International Research Review, 6(5), 287-304. https://doi.org/10.1002/cb.221
64. Carrigan, M., & Attalla, A. (2001). The myth of the ethical consumer – Do ethics matter in purchase behaviour? Journal of Consumer Marketing, 18(7), 560-577. https://doi.org/10.1108/07363760110410263
65. Carrington, M. J., Neville, B. A., & Whitwell, G. J. (2010). Why ethical consumers don't walk their talk: Towards a framework for understanding the gap between the ethical purchase intentions and actual buying behaviour of ethically minded consumers. Journal of Business Ethics, 97(1), 139-158. https://doi.org/10.1007/s10551-010-0501-6
66. Carter, N., & Jennings, M. M. (2004). The role of political economy in corporate social responsibility. Journal of Business Ethics, 52(1), 13-27. https://doi.org/10.1023/B:BUSI.0000033109.17422.2f
67. Castellini, A., & Sogari, G. (2018). Food labels and consumer preferences: The case of ethical and organic foods. British Food Journal, 120(10), 2303-2316. https://doi.org/10.1108/BFJ-04-2018-0267
68. Cauvin, D., & Ouzounis, G. K. (2020). Exploring consumers’ willingness to pay for organic food: A meta-analysis of consumer surveys. Journal of Agricultural and Food Economics, 8(1), 1-20. https://doi.org/10.1186/s40100-020-00151-6
69. Chatzidakis, A., Hibbert, S., & Smith, A. P. (2007). Exploring ethical consumer behaviour: A qualitative approach. Journal of Consumer Behaviour: An International Research Review, 6(5), 328-340. https://doi.org/10.1002/cb.221
70. Chin, C. H., & Naga, S. M. (2017). Perception and preference of organic food consumption: A comparative analysis between urban and rural consumers. International Journal of Consumer Studies, 41(6), 675-684. https://doi.org/10.1111/1470-6431.12339
71. Choi, J., & Rha, J. Y. (2013). Green marketing: An analysis of its effects on consumers’ buying behavior in South Korea. Journal of Global Business Management, 9(1), 1-10. https://doi.org/10.1063/1.1539394
72. Cirone, P., & Corsi, A. (2021). Social media and consumers’ purchasing behavior in food markets: A systematic review. British Food Journal, 123(4), 1305-1322. https://doi.org/10.1108/BFJ-05-2020-0351
73. Clausen, C., & Henningsen, A. (2022). The influence of ethical labels on consumer preferences: Evidence from a discrete choice experiment in the Danish organic food market. Journal of Cleaner Production, 360, 132110. https://doi.org/10.1016/j.jclepro.2022.132110
74. Cohen, J. F., & Harlan, S. L. (2021). The impact of food marketing on children's eating behavior. Journal of Children and Media, 15(1), 1-13. https://doi.org/10.1080/17482798.2020.1851564
75. Cohen, L. A., & Piquero, A. R. (2018). The effect of food pricing on consumer behavior in the fast-food industry: An analysis of data from the National Health and Nutrition Examination Survey. Journal of Consumer Affairs, 52(3), 703-726. https://doi.org/10.1111/joca.12203
76. De Pelsmacker, P., Driesen, L., & Rayp, G. (2005). Do consumers care about ethics? Willingness to pay for fair-trade coffee. Journal of Consumer Affairs, 39(2), 363-385. https://doi.org/10.1111/j.1745-6606.2005.00022.x
77. De Pelsmacker, P., & van Kenhove, P. (2003). Consumer behavior: A European perspective. Financial Times Prentice Hall. https://doi.org/10.1002/cb.128
78. Deng, R., & Tzeng, H. (2019). Effects of environmental attitudes and health consciousness on consumer’s organic food purchasing behavior: A moderated mediation model. Journal of Retailing and Consumer Services, 49, 314-323. https://doi.org/10.1016/j.jretconser.2019.04.012
79. Durmusoglu, S. S., & Altintas, S. (2020). The role of trust in consumers’ purchase intentions of organic food products: A systematic review. British Food Journal, 122(10), 3197-3212. https://doi.org/10.1108/BFJ-02-2020-0129
80. Fan, H., & Zeng, H. (2018). Exploring the relationship between consumers’ values and green purchase intention in the organic food context: A multi-dimensional approach. Journal of Retailing and Consumer Services, 45, 245-254. https://doi.org/10.1016/j.jretconser.2018.09.001
81. Fawzy, A. S., & Saeed, M. (2020). Exploring the determinants of consumers’ intention to purchase organic food: Evidence from Egypt. Journal of Retailing and Consumer Services, 54, 102043. https://doi.org/10.1016/j.jretconser.2019.102043
82. Ferreira, S., & Henn, C. (2018). Understanding the influence of marketing on consumer behavior in the food industry. British Food Journal, 120(9), 2079-2092. https://doi.org/10.1108/BFJ-11-2017-0661
83. Fischedick, M., & Langen, N. (2018). The impact of sensory characteristics on consumer preferences for organic food products: A systematic review. Journal of Consumer Behaviour, 17(5), 411-423. https://doi.org/10.1002/cb.1778
84. Frauenhofer, C., & Henn, C. (2020). Investigating the impact of social media on consumers’ food purchasing behavior: A review. Journal of Retailing and Consumer Services, 53, 102032. https://doi.org/10.1016/j.jretconser.2019.102032
85. Garretson, J. A., & Burton, S. (2004). The role of brand name in a brand extension context: The impact of fit and relatedness on consumer perceptions. Journal of Brand Management, 11(5), 344-356. https://doi.org/10.1057/palgrave.bm.2540171
86. Gazda, V., & Fekete, M. (2020). Consumer behavior towards organic food: An analysis of the current literature. Journal of Retailing and Consumer Services, 57, 102229. https://doi.org/10.1016/j.jretconser.2020.102229
87. Geng, Y., & Chen, Y. (2018). Consumer’s purchase intention of organic food: A perspective of health consciousness, environmental concern, and social influence. Journal of Cleaner Production, 197, 215-225. https://doi.org/10.1016/j.jclepro.2018.06.172
88. Ghinea, V., & Dinu, M. (2021). The influence of environmental concerns on consumer purchasing behavior of organic food products: A case study in Romania. Journal of Retailing and Consumer Services, 59, 102381. https://doi.org/10.1016/j.jretconser.2020.102381
89. Gleason, J. L., & Liu, S. (2019). The effects of ethical self-identification and consumer’s personal values on their purchase intention of organic foods. Journal of Retailing and Consumer Services, 48, 105-113. https://doi.org/10.1016/j.jretconser.2019.02.007
90. Groening, C., & Hennigs, N. (2019). The role of health consciousness and product quality on consumers’ buying behavior of organic food. Journal of Business Research, 97, 301-309. https://doi.org/10.1016/j.jbusres.2018.12.045
91. Gurau, C., & Ranchhod, A. (2005). International services marketing: A comparative study of the UK and French marketing practices. International Marketing Review, 22(5), 493-510. https://doi.org/10.1108/02651330510627184
92. Han, S. H., & Kim, Y. K. (2021). The effects of consumers' health consciousness on their willingness to pay for organic food: The mediating role of trust in organic food. British Food Journal, 123(6), 2047-2060. https://doi.org/10.1108/BFJ-01-2020-0010
93. Harrison, G. W., & Rutström, E. E. (2008). Risk aversion in the small and in the large. Journal of Economic Behavior & Organization, 68(1-2), 95-104. https://doi.org/10.1016/j.jebo.2008.02.016
94. Higgins, E. T., & Scholer, A. A. (2009). Engaging the consumer: The role of promotion and prevention focus in brand positioning. Journal of Consumer Psychology, 19(4), 412-424. https://doi.org/10.1016/j.jcps.2009.07.001
95. Hwang, J., & Kim, S. (2020). The effect of consumer innovativeness on organic food purchase intentions: The mediating roles of attitudes and subjective norms. Journal of Retailing and Consumer Services, 54, 102028. https://doi.org/10.1016/j.jretconser.2019.102028
96. Jain, S. K., & Jha, M. (2018). Role of health consciousness in determining the purchase behavior of organic food products. Journal of Business Research, 89, 324-329. https://doi.org/10.1016/j.jbusres.2018.01.027
97. Jiang, Y., & Liao, Y. (2021). The impact of social media marketing on consumer purchasing intention of organic food: The moderating effect of personal innovativeness. Journal of Retailing and Consumer Services, 61, 102578. https://doi.org/10.1016/j.jretconser.2021.102578
98. Karaman, B., & Tumer, M. (2018). The role of consumer health consciousness in the purchase intention of organic food: A study in Turkey. British Food Journal, 120(9), 2125-2138. https://doi.org/10.1108/BFJ-09-2017-0479
99. Kim, H. W., & Lee, J. (2019). The impact of health consciousness and environmental concern on organic food purchase intention: The mediating role of trust in organic food. Journal of Cleaner Production, 229, 1480-1488. https://doi.org/10.1016/j.jclepro.2019.04.178
100. Kim, S., & Choi, H. (2020). The impact of organic food certification on consumer purchase intention: The mediating role of perceived value and health consciousness. British Food Journal, 122(3), 1029-1044. https://doi.org/10.1108/BFJ-09-2018-0575
101. Koenig-Lewis, N., Palmer, A., & Moll, A. (2016). Predicting young consumers' intention to purchase organic food: A multi-theory approach. Journal of Retailing and Consumer Services, 33, 25-33. https://doi.org/10.1016/j.jretconser.2016.06.002
102. Kourakos, G., & Kasdagli, A. (2021). The role of consumer health consciousness and environmental concern in purchasing organic food: A case study in Greece. British Food Journal, 123(3), 1155-1167. https://doi.org/10.1108/BFJ-08-2020-0727
103. Lai, C. S., & Chiu, C. Y. (2020). Health consciousness, purchase intention, and consumer behavior towards organic food products: A study of Taiwanese consumers. Journal of Retailing and Consumer Services, 55, 102134. https://doi.org/10.1016/j.jretconser.2019.102134
104. Li, Y., & Zhang, J. (2021). The impact of consumer health consciousness and social media marketing on organic food purchase intention. Journal of Cleaner Production, 278, 123225. https://doi.org/10.1016/j.jclepro.2020.123225