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Article

The Mediating Role of Travel Destination Engagement in the Effects of Country Images on Consumer-Based Brand Equity of Dairy Products: Evidence from China

by
Rongbin Yang
1,*,
Roshnee Ramsaran
1 and
Santoso Wibowo
2
1
School of Business & Law, Central Queensland University, 120 Spencer St, Melbourne VIC 3000, Australia
2
School of Engineering & Technology, Central Queensland University, 120 Spencer St, Melbourne VIC 3000, Australia
*
Author to whom correspondence should be addressed.
Tour. Hosp. 2025, 6(5), 225; https://doi.org/10.3390/tourhosp6050225
Submission received: 30 August 2025 / Revised: 21 October 2025 / Accepted: 23 October 2025 / Published: 27 October 2025
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Abstract

Food and agricultural products shape tourism by linking communities and regions to leisure travel. Consumers’ perceptions of a country and its food products can shape their attitudes and behaviors toward it as a travel destination. This study compares the effects of general country image (GCI), product–country image (PCI), and product image (PI) on Chinese dairy consumers’ engagement with the country of origin as a travel destination (TDE). It also tests whether TDE mediates the effects of country images on consumer-based brand equity (BEQ) for dairy products. We analyzed 573 valid online responses from mainland China, a major market for dairy products and outbound tourism, using covariance-based structural equation modeling (CB-SEM) in AMOS 31. The results identify TDE as a key factor that fully mediates the effect of GCI on BEQ. PCI and PI show both direct effects on BEQ and indirect effects through TDE. The proposed framework links country evaluations to destination engagement and brand outcomes, highlighting opportunities for integrated cross-sector promotion. This research is among the first to examine co-marketing between the tourism sector and the dairy industry through a country-image perspective. It provides practical guidance for cross-sector strategy and contributes to ongoing debates in both fields.

1. Introduction

Food and agricultural products play a pivotal role in tourism by linking communities and regions to leisure travel (Ellis et al., 2018). Evidence indicates that consumers’ perceptions of a country’s food products can shape their engagement with that country as a travel destination (Choe & Kim, 2018). Coordinating the tourism and agri-food sectors can therefore diversify regional economies (Lane & Kastenholz, 2015). For example, the UK government’s Food 2030 strategy emphasizes cross-sector synergies that support rural sustainability and brand building. Yet, despite the well-recognized role of food culture in sustaining tourism, discussion of mutually beneficial interactions between these domains remains limited (Everett & Slocum, 2013). In addition, collaboration has been examined mainly in the context of wine and wineries (Carvalho et al., 2023), leaving other important agri-food products understudied. Dairy is a high-frequency staple in which safety and quality matter to shoppers, so country cues become central to brand judgments in ways that differ from hedonic categories such as wine (FAO, 2022; R. Yang et al., 2018). As one of the most widely consumed agricultural products worldwide, dairy provides a strong test of how country images translate into travel-destination engagement and brand outcomes (FAO, 2022; Elliot et al., 2011; Sio et al., 2024). Examining a staple category also allows us to assess whether effects documented in wine generalize to everyday purchase contexts (Mitchell & Hall, 2004; Brown & Getz, 2005).
Country images influence consumer preferences across products and services. In tourism, perceptions of destination countries affect subsequent behaviors (Avloniti et al., 2025; Fonseca et al., 2025; H. Zhang et al., 2016). In international marketing, country images shape attitudes toward imported products (Roth & Diamantopoulos, 2009) and can enhance food branding by strengthening consumer-based brand equity (BEQ), defined as consumer-perceived value in terms of awareness, associations, perceived quality, and loyalty (R. Yang et al., 2018). Interdisciplinary studies that connect country images to both tourism and food have only recently emerged (Elliot et al., 2011; Lee & Lockshin, 2011, 2012; Sio et al., 2024). They suggest that the image associated with a country’s food products can improve attitudes toward that country as an international travel destination and that country image has three facets: general country image (GCI, overall beliefs about the nation), product–country image (PCI, category-specific beliefs linked to the country), and product image (PI, perceived quality of products made in that country). What is missing is a direct, within-model comparison of these three facets together with an explicit test of whether destination engagement transmits their effects to brand outcomes in food contexts beyond wine.
Some studies also indicate that travel-destination engagement (TDE), defined as connectedness to the place, can mediate the influence of country images on future behaviors (Chen et al., 2020; Palau-Saumell et al., 2016; Sio et al., 2024). Whether a similar mediating mechanism extends to consumer products originating from the destination country remains unclear. Building on research in tourism and international marketing, this study addresses two questions:
RQ1: Do general country image, product–country image, and product image differentially influence consumers’ engagement with international travel destinations and the BEQ of dairy products?
RQ2: Does travel-destination engagement mediate the effects of these country-image facets on the BEQ of dairy products?
This study makes three contributions. First, it simultaneously tests the effects of the three country-image facets on consumers’ engagement with international travel destinations and their brand preferences for food products. Second, it develops and examines a model in which travel-destination engagement mediates the relationship between country images and food consumers’ brand preferences. Third, it offers a cross-sector perspective that informs strategic alliances between the tourism and dairy sectors and aligns destination marketing, food promotion, and public policy in agribusiness practice.

2. Theoretical Background

2.1. Definitions of Country Image

Country image (CI) refers to the collective beliefs and perceptions individuals hold about specific places (Kotler & Gertner, 2002, p. 251). CI has been extensively examined in international business since the 1960s and plays an important role in consumers’ decision-making (H. Zhang et al., 2016). The country-of-origin effect suggests that consumers use CI as an indicator of product quality. A positive CI is therefore associated with higher perceived quality and stronger brand presence (Han, 1989; Papadopoulos & Heslop, 2014; R. Yang et al., 2018; R. Yang et al., 2021).
In marketing research, CI is often studied through three categories: general country image (GCI), product–country image (PCI), and product image (PI) (Roth & Diamantopoulos, 2009). GCI captures consumers’ overall perceptions of a country’s macro-level attributes, such as political and economic factors (Pappu et al., 2007; Magnusson et al., 2014; Garcia-De los Salmones et al., 2022). In this sense, GCI concerns the country itself rather than specific products or services (Mossberg & Kleppe, 2005; J. Zhang et al., 2018; K. Henderson et al., 2025). GCI reflects both cognitive beliefs (for example, “This is a safe country”) and affective beliefs (for example, “I admire this country”) (Maher & Carter, 2011; Roth & Diamantopoulos, 2009). GCI influences product choices; for instance, consumers in less-developed countries often prefer brands from highly developed economies (Johansson et al., 2018).
PCI is “the place-related images with which buyers or sellers may associate a product” (Roth & Diamantopoulos, 2009, p. 727). It focuses on perceptions of product-related attributes linked to a specific country (Serrano-Arcos et al., 2020; K. Henderson et al., 2025). For example, many consumers associate Germany with advanced automobile technologies, which strengthens the competitive position of German car brands (Lee & Lockshin, 2012; Papadopoulos & Heslop, 2014).
PI refers to “consumers’ general perceptions of quality for products made in a given country” (Han, 1989, p. 222). It centers on beliefs about the excellence of products from a specific country. For example, consumers may perceive different levels of safety in dairy products from different countries of origin and prefer products from countries with a stronger PI (R. Yang et al., 2018).

2.2. Country Image and Tourism

In tourism research, CI is sometimes framed as travel destination image (TDI) when the destination is a country. TDI refers to tourists’ perceptions and beliefs about specific countries as travel destinations (Chaulagain et al., 2019; S. Yang et al., 2021; H. Zhang et al., 2016). Although both CI and TDI concern perceptions of countries, they are distinct. CI, used more often in international marketing, examines how perceptions of a country influence choices of tangible products. TDI focuses on tangible elements, such as facilities, and intangible elements, such as culture, that shape tourists’ behaviors at a destination. Accordingly, when the destination is a country, we treat GCI as a proxy for the macro components of TDI (for example, broad perceptions of governance, economy, safety, and national culture), while recognizing that TDI also includes destination-specific features not captured by product-agnostic country beliefs.
The scales used to measure TDI vary across studies and range from villages to entire countries (Chaulagain et al., 2019; Elliot et al., 2011; H. Zhang et al., 2016). Many studies show that TDI significantly influences tourist preferences. A positive TDI can encourage first visits and repeat visits (Cahyanti et al., 2014; López-Guzmán et al., 2017; Loureiro & Jesus, 2019; Scherrer et al., 2009). At the same time, a growing body of work examines how CI influences tourists’ perceptions in ways that are distinct from TDI (Chaulagain et al., 2019; Elliot et al., 2011; Everett & Slocum, 2013; Sio et al., 2024).

2.3. Consumer-Based Brand Equity

Brand equity (BEQ) is commonly defined from two perspectives. The financial perspective emphasizes the brand’s economic value to the firm. The consumer-based perspective emphasizes the brand’s value to consumers (Pina & Dias, 2021). The consumer-based perspective is more common in marketing because it centers on consumers’ perceptions, emotions, and behaviors toward brands (Aaker, 1991; Keller, 1993; Pappu et al., 2007; Shaikh et al., 2024). In this study, BEQ denotes consumer-based brand equity. BEQ exists when consumers perceive a brand’s product as superior to competing products (Pina & Dias, 2021; Shaikh et al., 2024). BEQ is often modeled as the positive outcome of perceived quality, brand awareness, brand associations, and brand loyalty (Pina & Dias, 2021; R. Yang et al., 2018).
Perceived quality is a consumer’s assessment of a product’s overall excellence or superiority (Pina & Dias, 2021; R. Yang et al., 2018; Shaikh et al., 2024). Brand awareness is the extent to which a brand is present in memory, from recognition to recall, ideally reaching top-of-mind status (Pina & Dias, 2021; R. Yang et al., 2018; C. Zhang et al., 2023). Brand associations are the mental links to a brand in memory (Pina & Dias, 2021; R. Yang et al., 2018; C. Zhang et al., 2023). Brand loyalty is a strong and persistent commitment to repurchase a preferred product or service despite external influences that might prompt change (Pina & Dias, 2021; R. Yang et al., 2018). Together, these factors indicate that BEQ depends on consumers’ perceptions, interactions, and attachments to a brand, and that BEQ can be influenced by the brand’s country of origin. Prior research shows that a positive CI can enhance BEQ (R. Yang et al., 2018). However, most studies examine BEQ in the context of direct experience with the product category. It remains unclear whether BEQ is also affected when consumers engage with the brand’s country of origin as a tourist destination.

3. Hypothesis Development

The preceding review indicates that GCI, PCI, and PI shape evaluations of both consumer products and travel destinations, and that TDE can transmit country-related perceptions to downstream outcomes. Prior work typically tests parts of this chain in isolation or focuses on wine. Building on this evidence, we develop an integrated set of hypotheses that: (i) compare the direct effects of GCI, PCI, and PI on brand equity (BEQ), (ii) test their effects on TDE, and (iii) examine whether TDE mediates the influence of GCI, PCI, and PI on BEQ in the dairy context.
Marketing studies increasingly examine how country evaluations shape brand outcomes, yet GCI, PCI, and PI operate at different distances from product beliefs and may therefore relate to BEQ in distinct ways. Prior research links favorable country evaluations to stronger BEQ for imported products (Pappu et al., 2007; Yasin et al., 2007). Halo effect theory explains how positive stereotypes about a country spill over to evaluations of its products and brands (Han, 1989; Abdelwahab et al., 2022). Treating country evaluations as a single construct can therefore obscure important differences across GCI, PCI, and PI.
In markets where buyers lack full information, signaling theory holds that brands and country of origin act as signals that reduce perceived risk and decision effort (Erdem & Swait, 1998). The stereotype content model suggests that beliefs about a country’s competence and standards can transfer to product beliefs in a given category (Fiske et al., 2002). Experiential marketing shows that direct contact with a place through sensory, emotional, cognitive, and behavioral encounters builds brand knowledge (Schmitt, 1999; Brakus et al., 2009). These ideas align with the accessibility–diagnosticity view: country cues shape judgments when they are easy to recall and clearly relevant to the decision (Feldman & Lynch, 1988). Together, these perspectives support the hypotheses below.

3.1. Effects of Country Images on Consumer-Based Brand Equity

GCI summarizes broad national attributes that are conceptually distant from concrete product cues in food categories, which can attenuate any direct effect of GCI on BEQ (Roth & Diamantopoulos, 2009; Garcia-De los Salmones et al., 2022). By contrast, PCI ties country associations to category-relevant cues such as craftsmanship, safety, and production capability, and PI reflects perceived quality for products made in that country. Because PCI and PI are closer to the information consumers use when judging brands, they should exhibit stronger direct relationships with BEQ than GCI, especially in dairy where quality and safety are salient (Pappu et al., 2007; Yasin et al., 2007; R. Yang et al., 2018).
Empirically, many studies investigate only subsets of these facets, which limit cumulative inference. For example, Maher and Carter (2011) consider GCI with PCI, whereas Wang et al. (2012) study GCI with PI. This piecemeal approach leaves open the comparative strength of all three facets when modeled together. We therefore position GCI, PCI, and PI within a single framework and test their direct effects on BEQ in the dairy context, where proximal category signals should matter most. Following signaling theory, PCI and PI are more diagnostic and proximate than GCI for judging product quality, so we expect stronger direct effects on BEQ for PCI and PI (Erdem & Swait, 1998):
H1. 
Consumer-based brand equity for dairy brands from a preferred foreign country is directly influenced by the general country image (a), product–country image (b), and product image (c).

3.2. Effects of Country Images on Travel Destination Engagement

Food products are often a distinctive aspect of a country as a travel destination (J. C. Henderson, 2009). Local foods play a central role in destination branding, which makes GCI, PCI, and PI especially relevant in studies of food and rural tourism, particularly for international destinations sought for specific foods or agricultural products (Ellis et al., 2018; J. C. Henderson, 2009; Sio et al., 2024). These food experiences are both consumer products and core elements of a destination’s experiential offerings (Mossberg & Kleppe, 2005). For example, the prestigious image of wine-producing countries can increase interest in those countries as international travel destinations (Scherrer et al., 2009). Recent studies therefore examine how consumer products shape tourists’ destination choices and preferences for international travel (Elliot et al., 2011; Lee & Lockshin, 2012; S. B. Kim & Kwon, 2018; Sio et al., 2024). This pattern is consistent with the country-of-origin halo, in which a favorable perception of a country extends to its products and brands (Han, 1989).
Engagement varies by context (Taheri et al., 2014). Travel destination engagement (TDE) is the attitude, behavior, and level of connectedness between tourists and the attraction itself (Loureiro & Sarmento, 2019, p. 370). Customer engagement contributes to business performance (Dessart et al., 2015; Huang & Choi, 2019; J. E. Kim et al., 2016). A product’s country of origin can shape consumer engagement through cultural and social meanings (J. E. Kim et al., 2016; R. Yang et al., 2018; R. Yang et al., 2021). Thus, following accessibility–diagnosticity and signaling, salient and relevant country cues should encourage stronger TDE (Feldman & Lynch, 1988; Erdem & Swait, 1998). In tourism, favorable GCI, PCI, and PI can enhance TDE (Chen et al., 2020; Tham et al., 2013). A positive GCI is linked to higher TDE and stronger visit intentions (Huerta-Álvarez et al., 2020; Villamediana-Pedrosa et al., 2020; S. B. Kim & Kwon, 2018). A prestigious PCI can increase behavioral engagement with the destination country (Qiu et al., 2016; Sio et al., 2024). Attitudes toward a country’s products, captured by PI, also influence receptivity to the country as a destination (Elliot et al., 2011). Although GCI, PCI, and PI have each been examined, their effects have not been integrated within a single framework. We therefore test their effects on TDE and compare their strengths empirically:
H2. 
The positive general country image (a), product–country image (b), and product image (c) directly enhance consumers’ engagement with the associated international travel destination.

3.3. The Role of Travel Destination Engagement in Consumer-Based Brand Equity

Engagement objects can include brands, offerings, organizations, and organizational activities beyond purchases (Hollebeek et al., 2014, p. 6). Customer engagement primarily refers to individuals’ behavioral expressions toward a brand or business (Prentice & Loureiro, 2018), but the construct extends beyond commitment to a single company. Recent studies indicate that TDE can shape consumers’ perceptions of a visited country when they evaluate its products and brands (Wu, 2025; Xu et al., 2018). For example, winery visits can substantially increase tourists’ brand awareness of wines from the destination country, an effect attributed to direct and immersive exposure to products and brands in situ (Mitchell & Hall, 2004; Wu, 2025; Xu et al., 2018). Although TDE is well established in wine contexts, applications to other categories, such as dairy, remain limited.
BEQ is built on consumers’ sensory, emotional, intellectual, and behavioral experiences with a brand (Pina & Dias, 2021; Wu, 2025). Halo effect theory holds that positive perceptions of a country can extend to its products and brands (Han, 1989). Accordingly, BEQ may be influenced by experiences with other products or services from the same country. Tourism provides sensory encounters such as tasting local foods, emotional experiences such as excitement, intellectual stimulation such as curiosity, and behavioral opportunities such as shopping. TDE is therefore likely to shape the BEQ of related consumer products. As noted earlier, TDE can be driven by GCI, PCI, and PI, which implies a mediating role for TDE between these facets and BEQ. In other words, favorable GCI, PCI, and PI should elevate TDE, which in turn should raise BEQ. Prior work shows that TDE mediates country-related influences on post-travel behaviors, such as recommending destinations (Chen et al., 2020; Palau-Saumell et al., 2016). However, the mediating role of TDE between GCI, PCI, or PI and BEQ for consumer products remains underexplored.
In food categories, consumers often rely on external cues to judge safety and quality that cannot be verified at purchase, so these cues matter greatly (Grunert, 2005; Erdem & Swait, 1998; R. Yang et al., 2022). Dairy is a frequently purchased staple where safety and quality are difficult to verify at the point of sale. Consumers therefore rely on origin signals and category-relevant beliefs about handling, hygiene, and standards (Grunert, 2005; Erdem & Swait, 1998). GCI reflects broad national perceptions that are less tied to specific products, whereas PCI and PI capture beliefs that are closer to the product itself (Han, 1989; Roth & Diamantopoulos, 2009; R. Yang et al., 2018). TDE can translate these country beliefs into brand knowledge by providing sensory, emotional, cognitive, and behavioral experiences with the producer country, which makes country cues more relevant for brand evaluations (Feldman & Lynch, 1988; Brakus et al., 2009; Loureiro & Sarmento, 2019). In practice, tasting, observing production or hygiene standards, and learning origin stories at retail or on site help consumers link country signals to perceived quality, awareness, and associations, which strengthens BEQ (Mitchell & Hall, 2004; Aaker, 1991; Keller, 1993; R. Yang et al., 2022). This logic leads to the following hypotheses:
H3. 
Travel destination engagement mediates the effects of country images on consumer-based brand equity. The positive general country image (a), product–country image (b), and product image (c) can enhance consumers’ engagement with the travel destination, subsequently boosting the consumer-based brand equity of products from the related country.
The existing literature highlights the significant effects of GCI, PCI, and PI on consumers’ attitudes toward both products and travel destinations. This study proposes that a country’s GCI, PCI, and PI influence consumers’ travel destination engagement (TDE) and their brand preferences, reflected in the consumer-based brand equity (BEQ) of local products. We further hypothesize that TDE mediates the effects of GCI, PCI, and PI on BEQ. Based on these relationships, a theoretical framework is proposed to illustrate the hypothesized paths among the constructs (see Figure 1).

4. Methodology

4.1. The Context of the Present Study

According to the Food and Agriculture Organization of the United Nations (FAO, 2022), dairy is “one of the most widely produced and valuable agricultural commodities.” More than six billion people consume dairy products worldwide, many of whom live in densely populated developing countries in Asia, including China, Indonesia, and Vietnam (FAO, 2022). Chinese consumers therefore represent a critical segment of the global dairy market (R. Yang et al., 2018; R. Yang et al., 2021). China is also one of the world’s largest sources of international tourists (Su et al., 2022), which makes it a key player in global tourism. As a result, tourism organizations actively target Chinese travelers (Su et al., 2022). We focus on China because it pairs a large and dynamic dairy market with substantial outbound travel, creating a setting in which country-of-origin perceptions and destination engagement are both salient for testing links among GCI, PCI, PI, TDE, and BEQ.
Existing research on the convergence of tourism and food or agricultural products concentrates primarily on alcoholic beverages, especially wine, and highlights mutual reinforcement between visits to wine-producing regions or wineries and wine exports (Brown & Getz, 2005; Bowe et al., 2015; Mitchell & Hall, 2004). These studies show that favorable evaluations of wine products can stimulate interest in the producer country as a travel destination and that consumers often prefer wines from countries they have visited. Despite this extensive work on wine and wineries, relatively few studies examine collaborations between tourism and other agricultural products, such as dairy.
Dairy provides a relevant test case for three reasons. First, it is a utilitarian, high-frequency staple rather than a hedonic product like wine, so country-linked cues of quality and safety play a central role in shaping brand evaluations and align closely with PCI and PI (R. Yang et al., 2018). Second, because perceptions of safety and quality vary markedly across countries, dairy offers a clear context for examining how GCI, PCI, and PI translate into TDE and BEQ. Third, the global reach of dairy consumption and its importance among Chinese consumers create a meaningful setting where destination engagement and brand perceptions interact at a scale relevant to both tourism and international marketing (Su et al., 2022).
Given these factors, this study investigates how GCI, PCI, and PI, together with TDE, shape dairy brand preferences among Chinese consumers, as reflected in BEQ. In doing so, it complements the wine-focused literature by testing whether country-related evaluations and destination engagement generalize from a hedonic experience to a staple food category.

4.2. Questionnaire Design and Measurement

This study used an online questionnaire to reach a large sample, obtain timely responses, and reduce costs (Evans & Mathur, 2005). Online surveys are widely adopted in research on consumer beliefs, perceptions, and attitudes (including GCI, PCI, and PI) as well as on tourists’ decision-making processes (Andersson et al., 2021; Balabanis & Lopez, 2022).
The questionnaire included multi-item measures for all attitudinal constructs to enhance reliability. Responses were recorded on a seven-point Likert scale (1 = “strongly disagree,” 7 = “strongly agree”) to assess GCI, PCI, PI, TDE, and BEQ. GCI was measured using three items adapted from Han (1989) and Amine (2008). PCI was assessed with three items from Hsieh et al. (2004) and Martin and Eroglu (1993). PI was evaluated with three items from Hsieh et al. (2004) and R. Yang et al. (2018). TDE was measured using three items based on Demangeot and Broderick (2016), Gopalakrishna et al. (2019), and Harrigan et al. (2018). BEQ was assessed using four items adapted from Yasin et al. (2007). Detailed item wordings are provided in Table 1.
The questionnaire also collected information on participants’ purchase history, preferred country of origin for dairy products, and demographic characteristics. The instrument was drafted in English, translated into simplified Chinese, and validated using Brislin’s (1980) back-translation procedure. Two bilingual experts independently translated the items into Chinese and then back into English. Any discrepancies between the original and back-translated versions were discussed by the translators and a consumer research scholar fluent in both languages. Wording was revised until all parties agreed that the meaning was equivalent across versions and appropriate for the Chinese context. A pilot test with 20 respondents confirmed that the final Chinese version was clear and easy to understand.

4.3. Sampling

Participants were recruited in mainland China through Wenjuanxing (www.wjx.cn), an online panel widely used in tourism and consumer research (Liu et al., 2019). All respondents resided in China at the time of the survey. The panel’s sampling quota was structured to reflect the demographic distributions of gender, age, education, income, and residential location based on the most recent Chinese census data (Duan et al., 2020).
Invitations to the online questionnaire were distributed via email and included a hyperlink to the survey. Each response was screened for completeness, and incomplete questionnaires were excluded. A total of 573 valid responses were obtained. As shown in Table 2, 430 participants (75.04%) indicated a preference for foreign countries as the country of origin for dairy products. This subsample was used for subsequent analysis, as the study focused on the relationships among country images, international travel destinations, and preferences for foreign dairy brands.
The final sample size of n = 430 produced a cases-to-parameters ratio of approximately 10.2:1 (about 42 freely estimated parameters, considering both measurement and structural paths). This ratio exceeds widely accepted adequacy thresholds for covariance-based structural equation modeling (CB-SEM), including n ≥ 200 and at least 10 observations per estimated parameter (Byrne, 2016; Kline, 2015).

5. Results

The data were analyzed using structural equation modeling (SEM). SEM is widely applied in business and social science research to evaluate causal relationships among variables in hypothesized models (Byrne, 2016; Kline, 2015) and is common in studies of consumer and tourist perceptions and behaviors (Cham et al., 2021). Two main SEM approaches exist: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). CB-SEM is typically preferred for confirming causal-predictive relationships when sample sizes are large and data approximate normality, whereas PLS-SEM is more suitable for smaller samples (for example, fewer than 250) or non-normally distributed data (Hair et al., 2021).
All items in this study were measured on seven-point Likert scales. Consistent with guidance that Likert variables with five or more categories and limited skew can be treated as approximately continuous for SEM (Rhemtulla et al., 2012; Finney & DiStefano, 2006; Flora & Curran, 2004), we proceeded with CB-SEM. Univariate normality was assessed using skewness and kurtosis. Analyses conducted in SPSS 30 showed skewness values between −1 and +1 (lowest −0.823; highest 0.310) and kurtosis values between −2 and +2 (lowest −0.996; highest 0.737), indicating acceptable normality (Hair et al., 2010).
Accordingly, the structural model was estimated in AMOS 31 using maximum likelihood estimation with bias-corrected bootstrapping (5000 resamples) to generate robust standard errors and confidence intervals. For future robustness checks involving ordinal indicators, alternative estimators based on polychoric correlations, such as diagonally weighted least squares (DWLS) or weighted least squares mean and variance adjusted (WLSMV), could also be considered.

5.1. The Measurement Model

Table 1 reports composite reliability (CR). All constructs have CR values above 0.80, indicating strong internal consistency (Fornell & Larcker, 1981). Convergent validity was assessed using average variance extracted (AVE). The AVE values for GCI, PCI, PI, TDE, and BEQ all exceed 0.50, supporting convergent validity (Fornell & Larcker, 1981). For discriminant validity, the largest inter-construct correlation was 0.554 (Table 3), which is lower than the smallest square root of AVE (0.782). This satisfies the Fornell–Larcker criterion (Fornell & Larcker, 1981). We also conducted a confirmatory factor analysis (CFA) to evaluate the measurement model. As shown in Table 4, the fit indices meet recommended thresholds (Hair et al., 2010): χ2(94) = 194.38, p < 0.001, χ2/df = 2.068 (<3), CFI = 0.974 (>0.90), RMSEA = 0.050 (<0.08), and SRMR = 0.043 (<0.08). It worths to note that items, such as GCI3, showed a relatively higher loading, sensitivity analyses indicated that removing it did not materially affect reliability, validity, or structural results. We retain GCI3 for polarity balance but acknowledge its potential wording-related method effect and recommend using balanced polarity or milder negative wording in future work.
To assess common method bias, we conducted Harman’s one-factor test (Podsakoff et al., 2003). Common method bias is indicated if a single factor accounts for more than 50 percent of the variance across the constructs. In our data, the first factor explained 33.29 percent of the total variance, which is below this threshold. This finding is consistent with the poor fit of a single-factor CFA model, χ2/df = 15.073, CFI = 0.496, SRMR = 0.129, and RMSEA = 0.181. We also applied the common latent factor approach, and the absolute differences between standardized regression weights with and without the latent factor were all below 0.20. Taken together, these results suggest that substantial common method bias is unlikely in this study (Podsakoff et al., 2003).

5.2. The Structural Model

Having established strong measurement properties in the previous section, we proceed to test the hypothesized relationships. The CFA results indicate good fit for the measurement model. On this basis, this section estimates the structural paths among GCI, PCI, PI, TDE, and BEQ, evaluates H1 to H3, and tests mediation with bias-corrected bootstrapping.
The overall goodness-of-fit statistics indicated acceptable fit, χ2(95) = 264.41, p < 0.001, χ2/df = 2.783, CFI = 0.956, RMSEA = 0.064, and SRMR = 0.069, which are consistent with commonly used criteria (see Table 4). As shown in Figure 2, GCI (β = −0.025, p = 0.191) did not have a direct effect on BEQ, whereas PCI (β = 0.136, p < 0.05) and PI (β = 0.405, p < 0.001) had significant positive effects. Accordingly, H1a was rejected, and H1b and H1c were supported. These results highlight differential effects across the three country image facets: BEQ is directly influenced by PCI and PI, but not by GCI.
In addition, GCI (β = 0.222, p < 0.01), PCI (β = 0.234, p < 0.001), and PI (β = 0.238, p < 0.01) all had significant positive effects on TDE, supporting H2a, H2b, and H2c. These findings are consistent with prior work showing that country image facets can shape tourists’ travel choices (for example, Chaulagain et al., 2019; De Nisco et al., 2015) and indicate that TDE is sensitive to a country’s image as it relates to a specific product category.
The analysis also showed that TDE positively affects BEQ (β = 0.308, p < 0.001). This result aligns with evidence that tourism experiences increase receptivity to related products (Mainolfi & Marino, 2020). To assess mediation, we tested indirect effects using bias-corrected bootstrapping with 5000 resamples, following Moulard et al. (2016). We compared models with and without the mediator to evaluate direct and indirect paths. When both the direct and indirect paths are significant, mediation is partial; when only the indirect path is significant, mediation is full.
As reported in Table 5, TDE mediated the following paths: GCI→TDE→BEQ (β = 0.222, p < 0.01), PCI→TDE→BEQ (β = 0.231, p < 0.001), and PI→TDE→BEQ (β = 0.041, p < 0.05). Therefore, H3a, H3b, and H3c were supported. Notably, GCI→TDE→BEQ exhibited full mediation because the direct effect of GCI on BEQ was not significant (β = −0.025, p = 0.191). These findings confirm the mediating role of TDE and underscore that the three facets (GCI, PCI, PI) influence BEQ through both direct and indirect pathways, with GCI operating only indirectly via TDE.
In addition, the structural model explains 22% of the variance in TDE (R2 = 0.22) and 38% of the variance in BEQ (R2 = 0.38). These values suggest modest explanatory power for TDE and moderate explanatory power for BEQ.

6. Discussion and Conclusions

6.1. Theoretical Implications

This study offers several theoretical contributions. It examines how GCI, PCI, and PI differentially affect the BEQ of food products. Prior research shows that favorable country evaluations can enhance consumers’ brand preferences for imported goods and, in turn, increase BEQ (R. Yang et al., 2018). Building on this work, we analyze country evaluations through three distinct dimensions. The results indicate that GCI does not directly influence BEQ, consistent with Garcia-De los Salmones et al. (2022), who argue that brand preferences are driven primarily by country evaluations tied to specific product categories. A plausible explanation is that GCI aggregates macro-level factors such as politics, the economy, and society that do not map cleanly onto concrete product attributes in dairy. These broad signals are indirect in diagnostic value for evaluating credence attributes like safety, processing standards, and supply chain quality, so consumers are less likely to rely on them when forming brand judgments. The abstract nature of GCI also creates a mismatch with the more concrete information that guides purchase decisions, which reduces its accessibility and perceived applicability in everyday shopping contexts. Consequently, food consumers may not spontaneously connect brand choices to these broad national characteristics unless additional cues make the link explicit. By contrast, positive PCI and PI are more likely to stimulate interest in locally produced goods and brands, motivate information search and retention, and thereby raise BEQ. These findings highlight the value of incorporating GCI, PCI, and PI in future product marketing studies and recognizing their distinct impacts on BEQ.
Having established distinct effects on BEQ, we next investigate whether the same facets of country evaluation also shape destination-related judgments. This study examines the country-of-origin effect on consumers’ attitudes toward international travel destinations. Prior research indicates that favorable evaluations of food products can shape perceptions of the producer country as a travel destination (Elliot et al., 2011; Lee & Lockshin, 2012). Extending the existing literature, we simultaneously test the effects of GCI, PCI, and PI and find that all three significantly influence tourists’ preferences. Tourists’ motivations are diverse and may be driven by macro aspects, such as cultural tourism, and micro aspects, such as food tourism. Our results confirm a halo effect from dairy products to tourism: dairy consumers’ perceptions of a product’s country of origin are associated with their choices of travel destinations. These findings highlight the value of applying all three dimensions, GCI, PCI, and PI, in future tourism studies to obtain more comprehensive insights.
The next question is how these facets translate into brand outcomes through destination engagement. This study advances research on TDE by demonstrating its influence on consumers’ BEQ for products from a visited country. Prior work shows that TDE can mediate country-related influences on tourists’ post-travel behaviors, such as recommending destinations (Chen et al., 2020; Palau-Saumell et al., 2016). Building on this evidence, we identify TDE as a mediator between GCI, PCI, PI, and BEQ for consumer products. In our framework, TDE channels the effects of GCI, PCI, and PI into product marketing outcomes. Without this mediating role, BEQ is not directly affected by general, non-product-related perceptions of a country, that is, by GCI. Earlier research often emphasized translating GCI into product-related images through marketing campaigns to influence brand preferences. Our results introduce TDE as an alternative mechanism. When consumers engage with a country as a travel destination, they gain direct and immersive exposure to its products and brands, which helps them understand how macro-environmental factors such as politics, the economy, the natural environment, and society contribute to product quality. Enhancing TDE is therefore crucial for activating the influence of GCI on consumers’ brand knowledge of local products. Additionally, the strong direct effect of PI on BEQ and the smaller indirect effect via TDE suggest that in a staple such as dairy, core product beliefs tied to safety, purity, taste, and processing standards dominate brand judgments, while destination engagement adds a smaller but meaningful increment. These findings underscore the importance of interdisciplinary research on co-marketing between tourism destinations and consumer products.
Furthermore, the results refine signaling theory by distinguishing the informativeness of country cues: PCI and PI function as category-diagnostic signals that link directly to BEQ, whereas GCI is a weak signal for credence attributes in dairy and becomes decision-useful only via TDE. They clarify the stereotype content pathway by showing that broad competence beliefs in GCI do not automatically transfer to brand judgments; TDE provides the mechanism that carries country-level beliefs to product-level evaluations. They extend experiential marketing/brand experience by demonstrating that place-based engagement builds brand knowledge in a utilitarian, credence-heavy category (i.e., dairy), not just in hedonic beverages. Finally, consistent with accessibility–diagnosticity, TDE raises both the accessibility and the perceived relevance of country cues, explaining why GCI requires mediation while PCI/PI can act both directly and indirectly.
Building on these findings, this study contributes to academic literature by proposing an integrative theoretical framework that guides future research. The framework is designed to examine how GCI, PCI, and PI interact with TDE to shape BEQ in the context of consumer products and travel destinations.

6.2. Managerial Implications

Guided by the proposed framework and empirical results, this study offers several practical insights for aligning destination marketing with food branding.
Consumer products, particularly food, form a crucial bridge between tourism and local communities. However, governments and industries often manage separate international campaigns to promote tourism services and consumer goods. For instance, Australia promotes tourism through the “There’s Nothing Like Australia” brand platform but markets products through the “Australian Made” and “Australian Grown” programs. Similarly, New Zealand operates distinct campaigns for tourism destinations and for consumer products (see Appendix A, Appendix B, Appendix C and Appendix D). This separation often limits the potential for synergy. Product campaigns typically emphasize technological sophistication and national development, while tourism campaigns highlight natural and cultural attractions. Such divergence can dilute each brand’s impact and weaken the opportunity for mutual reinforcement (Elliot et al., 2011).
Dairy presents a distinctive case. Unlike wine or coffee, which relies on hedonic consumption experiences, dairy is an everyday staple where safety, quality, and purity are central to purchase decisions and strongly associated with perceptions of national standards and trust. Because dairy products are perishable, cold-chain dependent, and consumed by all age groups, they are closely linked to government regulation, certification, and assurance of quality. These characteristics make country cues highly consequential and create a form of consumer engagement that differs from the experience-driven imagery typical of hedonic categories. The finding that TDE fully mediates GCI, while PCI and PI maintain both direct and indirect effects on BEQ, extends destination–product linkages to a utilitarian category where credence attributes dominate.
The mediating role of TDE between GCI, PCI, PI, and brand preferences highlights the importance of coordinated strategies between tourism and agri-food sectors. Government-led national branding programs for exported products can reinforce the tourism sector by attracting consumers from key markets, while destination marketing can enhance trust in the country’s products. Effective collaboration requires closer coordination between tourism authorities and exporters. Tourism organizations can leverage favorable perceptions of local foods as distinctive selling propositions by featuring them in promotional materials and visitor experiences. Conversely, exporters can strengthen international competitiveness by incorporating destination narratives into product packaging, websites, and retail displays. For dairy, coordinated campaigns between marketers and tourism bodies, including joint advertisements, origin storytelling, or promotional activities in airports and visitor centers, can enhance both BEQ and destination appeal.
Achieving synergy also depends on the congruence between the country images projected through tourism and those projected through product branding (Holmefjord, 2000). While earlier studies highlighted hedonic products such as wine as natural candidates for tourism co-promotion (Lee & Lockshin, 2012), our results show that utilitarian products like milk (Rubera et al., 2011) can also contribute meaningfully to co-marketing. Aligning tourism and product messages can strengthen a country’s overall image and support sustainable development. When dairy producers from countries with favorable PCI and PI integrate destination cues into their marketing mix, such as packaging, digital storytelling, and sales channels, they can actively contribute to TDE. Governments and tourism agencies can encourage such initiatives by facilitating co-branding strategies, offering grants or subsidies, and developing integrated marketing platforms that link tourism and agri-food sectors.
These findings also suggest a deeper level of collaboration between the tourism and dairy industries. Food tourism research has traditionally focused on travelers who visit destinations for distinctive culinary experiences (López-Guzmán et al., 2017; Smith & Costello, 2009) or on tourists’ food purchases during trips (Skuras et al., 2006). In contrast, our results point to a longer-term effect of destination engagement on food consumers through enhanced BEQ. Food companies can extend this effect by maintaining connections with tourists after their visits, using follow-up marketing, storytelling, and loyalty initiatives that tie destination memories to product experiences. Such initiatives demonstrate how agri-food sectors can act not only as suppliers but also as strategic marketing partners that contribute to sustainable tourism development and national branding.

6.3. Limitations and Future Study

This study, while offering valuable contributions, has several limitations. First, it focuses on Chinese dairy consumers. Although China is a major market, results may not necessarily generalize to other markets with different dairy penetration or travel patterns; future work should examine diverse populations across countries and extend the scope to additional food categories.
Second, the use of online data collection may constrain the sample composition, which could limit generalizability. Although the study used demographic quotas to align the sample with national census data, online panels may still overrepresent younger and urban consumers. Future research should consider mixed sampling methods, including offline data collection, to improve representativeness and cross-validate the findings.
Third, we analyzed only respondents who preferred foreign origins, which concentrates on foreign-leaning consumers and limits generalizability to the broader market. Although this choice preserves a consistent country anchor for GCI, PCI, and PI, it may inflate the estimated country-image effects, especially the direct PCI → BEQ and PI → BEQ paths and the indirect GCI → TDE → BEQ pathway, because such consumers attend more to origin cues and are more receptive to international destinations. Future studies should include both foreign- and domestic-preferring consumers and test moderation using multi-group SEM or pooled models with preference as a moderator. Finally, although our framework treats country evaluations through GCI, PCI, and PI, future research should separate affective and cognitive components within these facets to provide a more granular understanding.

7. Conclusions

This paper contributes to marketing and tourism management by comparing the effects of general country image (GCI), product–country image (PCI), and product image (PI) on individuals’ travel destination engagement (TDE) and brand preferences. It also introduces a theoretical framework that explains the mediating role of TDE in the relationship between country image facets and consumers’ brand preferences, reflected in brand equity (BEQ). This framework can serve as a foundation for future research on co-marketing strategies that link travel destinations with food products.

Author Contributions

Conceptualization, R.Y.; Methodology, R.Y.; Formal Analysis, R.Y.; Investigation, R.Y.; Writing—Original Draft Preparation, R.Y.; Writing—Review and Editing, R.R. and S.W.; Visualization, R.Y.; Supervision, R.R. and S.W.; Project Administration, R.R. All authors have read and agreed to the published version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the Human Research Ethics Committee of Central Queensland University (protocol code H16/10-279 and 27 October 2016).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Tourismhosp 06 00225 g0a1
Figure A1. “There’s Nothing Like Australia” campaign by Tourism Australia. Scheme from: https://www.tourism.australia.com/en/about/our-campaigns.html (accessed on 1 December 2024).
Figure A1. “There’s Nothing Like Australia” campaign by Tourism Australia. Scheme from: https://www.tourism.australia.com/en/about/our-campaigns.html (accessed on 1 December 2024).
Tourismhosp 06 00225 g0a1

Appendix B

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Figure A2. The “Australia Made" Campaign. Sourced from: https://www.australianmade.com.au/why-buy-australian-made/about-the-logo/ (accessed on 1 December 2024).
Figure A2. The “Australia Made" Campaign. Sourced from: https://www.australianmade.com.au/why-buy-australian-made/about-the-logo/ (accessed on 1 December 2024).
Tourismhosp 06 00225 g0a2

Appendix C

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Figure A3. The "100% Pure New Zealand" campaign by Tourism New Zealand. Sourced from: https://www.tourismnewzealand.com/about/what-we-do/campaign-and-activity/ (accessed on 1 December 2024).
Figure A3. The "100% Pure New Zealand" campaign by Tourism New Zealand. Sourced from: https://www.tourismnewzealand.com/about/what-we-do/campaign-and-activity/ (accessed on 1 December 2024).
Tourismhosp 06 00225 g0a3

Appendix D

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Figure A4. The “Buy New Zealand Made” campaign. Sourced from: https://www.buynz.org.nz/site_files/35177/upload_files/The%20Kiwi%20trademark%20-%20Black.pdf.pdf?dl=1 (accessed on 1 December 2024).
Figure A4. The “Buy New Zealand Made” campaign. Sourced from: https://www.buynz.org.nz/site_files/35177/upload_files/The%20Kiwi%20trademark%20-%20Black.pdf.pdf?dl=1 (accessed on 1 December 2024).
Tourismhosp 06 00225 g0a4

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Figure 1. The proposed structural model. (Chen et al., 2020; Mitchell & Hall, 2004; Palau-Saumell et al., 2016; Xu et al., 2018; Han, 1989; Kotler & Gertner, 2002; Papadopoulos & Heslop, 2014; R. Yang et al., 2018).
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Figure 2. Estimated results of the model. Note. *** p < 0.001, ** p < 0.01, * p < 0.05.
Figure 2. Estimated results of the model. Note. *** p < 0.001, ** p < 0.01, * p < 0.05.
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Table 1. Results of reliability and validity tests.
Table 1. Results of reliability and validity tests.
Variables/ItemsFactor LoadingMeanStd. DeviationCRAVEα
General Country Image (GCI) 0.8740.7020.839
 GCI1: ‘It is a country that has an image of an advanced country.’0.7925.70 1.081
 GCI2: ‘It is a country that is prestigious.’0.7215.47 1.156
 GCI3: ‘I dislike this country.’ (R)0.9805.51 0.650
Product–Country Image (PCI) 0.8780.7090.828
 PCI1: ‘It is a country that has a nice environment for dairy products.’0.7886.39 0.717
 PCI2: ‘It is a country that has high dairy production standards.’0.7526.33 0.786
 PCI3: ‘It is a country that has good dairy products.’0.9706.16 0.693
Product Image (PI) 0.8680.6860.828
 PI1: ‘The dairy products from this country taste good.’0.8206.05 0.835
 PI2: ‘The dairy products from this country are safe.’0.8646.09 0.810
 PI3: ‘The dairy products from this country are trustable.’0.8006.05 0.876
Travel Destination Engagement (TDE) 0.8250.6120.784
 TDE1: ‘I seek a lot of information about this country.’0.7255.70 1.209
 TDE2: ‘I have many experiences in this country.’ 0.7775.90 1.090
 TDE3: ‘I would like to visit this country in the next 24 months if there is an opportunity.’0.8405.71 1.187
Brand Equity (BEQ) 0.8750.6370.745
 BEQ1: ‘If I have to choose among brands of dairy products, those from this country are definitely my choice.’0.8054.98 1.268
 BEQ2: ‘If I have to buy dairy products, I plan to buy those from this country even though there are other brands from other countries as good.’0.8395.03 1.246
 BEQ3: ‘If there is a dairy brand from other countries as good as those from this country, I prefer to buy the latter.’0.8145.18 1.171
 BEQ4: ‘It makes sense to buy dairy products from this country instead of any brands from other countries, even if they are the same.’0.7295.23 1.192
Note. The Likert Scale ranges from 1 to 7: 1: Strongly Disagree; 2: Disagree; 3: Somewhat Disagree; 4: Neutral; 5: Somewhat Agree; 6: Agree; 7: Strongly Agree. (R): The item was inverted for data analysis.
Table 2. Summary of profiles.
Table 2. Summary of profiles.
VariablesScaleNumberFrequency
Number of informants 573
Gender1. Female32156.00%
2. Male25244.00%
Age1. 18–2925143.80%
2. 30–3928349.40%
3. 40–49315.40%
4. 50 or more81.40%
Education1. Uneducated00.00%
2. Primary00.00%
3. Junior secondary101.70%
4. Senior secondary488.40%
5. Diploma12020.90%
6. Bachelor33458.30%
7. Masters579.90%
8. Doctorates40.70%
Location1. City34159.50%
2. County11620.20%
3. Town7613.30%
4. Village407.00%
The annual household income per capita before tax (CNY)1. 20,000 or less11419.90%
2. 20,001–49,99924242.20%
3. 50,000–99,99911219.50%
4. 100,000–199,9997713.40%
5. 200,000 or more284.90%
Preferred country of origin1. Australia17630.72%
2. New Zealand15927.75%
3. China Mainland14324.96%
4. Netherlands406.98%
5. Germany162.79%
6. USA101.75%
7. UK91.57%
8. Switzerland50.87%
9. Others152.62%
Table 3. Inter-construct correlations.
Table 3. Inter-construct correlations.
Global Country ImageProduct Image Product–Country ImageTravel Destination Engagement
Product Image0.554
Product–Country Image0.5100.380
Travel Destination Engagement0.3910.3750.404
Brand Equity0.2050.4780.3280.412
Table 4. Goodness-of-fit indices.
Table 4. Goodness-of-fit indices.
Modelχ2dfχ2/dfpCFIIFITLISRMRRMSEAAIC
Measurement model194.383942.068<0.0010.9740.9740.9670.0430.05310
Structural model264.407952.783<0.0010.9560.9560.9450.0690.064378
Recommended value <3.00 ≥0.900≥0.900≥0.900<0.080<0.080
Note: insignificant path in initial structural model: GCI->BA (p = 0.135).
Table 5. Tests of mediation.
Table 5. Tests of mediation.
PathEffectStandardized
Estimate		Lower
Interval		Upper
Interval		HypothesisMediation
GCI→BEQDirect−0.025−0.1470.099H3a SupportedFull
GCI→TDE→BEQIndirect0.222 **0.1580.303
PCI→BEQDirect0.136 *0.0200.264H3b SupportedPartial
PCI→TDE→BEQIndirect0.231 **0.1660.308
PI→BEQDirect0.405 ***0.2880.510H3c SupportedPartial
PI→TDE→BEQIndirect0.041 *0.0140.084
Note. The table format was sourced from Moulard et al. (2016); * p < 0.05; ** p < 0.01; *** p < 0.001.
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Yang, R.; Ramsaran, R.; Wibowo, S. The Mediating Role of Travel Destination Engagement in the Effects of Country Images on Consumer-Based Brand Equity of Dairy Products: Evidence from China. Tour. Hosp. 2025, 6, 225. https://doi.org/10.3390/tourhosp6050225

AMA Style

Yang R, Ramsaran R, Wibowo S. The Mediating Role of Travel Destination Engagement in the Effects of Country Images on Consumer-Based Brand Equity of Dairy Products: Evidence from China. Tourism and Hospitality. 2025; 6(5):225. https://doi.org/10.3390/tourhosp6050225

Chicago/Turabian Style

Yang, Rongbin, Roshnee Ramsaran, and Santoso Wibowo. 2025. "The Mediating Role of Travel Destination Engagement in the Effects of Country Images on Consumer-Based Brand Equity of Dairy Products: Evidence from China" Tourism and Hospitality 6, no. 5: 225. https://doi.org/10.3390/tourhosp6050225

APA Style

Yang, R., Ramsaran, R., & Wibowo, S. (2025). The Mediating Role of Travel Destination Engagement in the Effects of Country Images on Consumer-Based Brand Equity of Dairy Products: Evidence from China. Tourism and Hospitality, 6(5), 225. https://doi.org/10.3390/tourhosp6050225

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