Culturally Mixed Co-branding Product Framing in China: The Role of Cultural Sensitivity, Product Quality, and Purchase Probability

Over the past few years, the Chinese government has continuously promoted national pride and encouraged consumers to purchase domestic brands. It has enacted preferential policies that encourage local brands to compete with foreign brand (FB) rivals. The Made in China 2025 policy targets a shift from China’s products to China’s brands, from speed to quality, and from made in China to designed in China. Local brands have created Guochao (patriotic brands, PBs) that embed Chinese cultural elements (arts, crafts, calligraphy, traditional patterns), reflecting younger generations’ interest in national culture and signaling a shift toward domestic products. PBs are tapping co-branding collaborations, blending local and foreign cultural symbols to create glocal or hybrid products. While prior research often studies global brands incorporating local identity to create culturally mixed products (CMPs), mechanisms influencing consumer preferences toward culturally mixed co-branded products (CMCPs) remain unclear. This study addresses gaps by examining cultural mixing framing via a co-branding model of an FB and a PB: FB × PB (foreign × host) and PB × FB (host × foreign), and how these framing strategies affect consumer responses. It also evaluates whether combining appropriate cultural elements yields positive consumer responses. Drawing on brand association theory, perceived fit (product fit and brand fit) is central to consumer evaluation in co-branding. Poor perceived fit can yield negative outcomes. The study also investigates cultural congruence as part of perceived fit, given acceptance of FB products is higher when cultural elements match consumers’ cultural dispositions. Beyond exclusionary reactions reported in prior studies (cultural intrusion or contamination), few have examined positive reactions (perceived creativity, cultural compatibility, cultural respect). This study introduces cultural sensitivity as an integrative response, proposing PB × FB may evoke higher cultural sensitivity because PBs are more iconic locally. It also examines whether co-branding changes product quality perceptions: do PB × FB collaborations elevate perceived PB quality, or are FB × PB still perceived as higher quality due to FBs’ reputations? The study’s contributions inform glocalization strategies for global companies in emerging markets, using congruity theory to test integrative responses (cultural sensitivity and product quality) toward CMCPs. The paper proceeds with a theoretical foundation and hypotheses, testing in China, followed by discussion, contributions, managerial implications, and future research.

Theoretical approach and hypothesis development: Patriotic brands (PBs) are iconic local brands that embody national identity and pride. In China, Guochao captures the rise of PBs that integrate traditional cultural elements, supported by policy and market initiatives (e.g., Tmall’s National Tide Action). Cultural mixing in co-branding: Cultural mixing presents globalness and localness symbols simultaneously. FBs increasingly localize designs (e.g., Dior’s Chinese floral patterns; Gucci’s Shanghai Dragon Bag), though missteps (e.g., Victoria’s Secret dragon-themed swimsuit) can trigger backlash. Polycultural psychology views culture as hybrid and evolving. Framing strategies for CMPs (Cui et al., 2016), based on psycholinguistic noun-noun combinations: (1) foreign × host culture (modifier = foreign element; head = host element; e.g., Frappuccino dumpling) and (2) host × foreign culture (modifier = host element; head = foreign element; e.g., Peking duck pizza). Co-branding of FBs and PBs can reduce concerns about Western/Eastern stereotypes and increase congruity. Congruity theory and perceived fit: Perceived fit (product fit and brand fit) drives co-branding success. Product fit is the relatedness between product categories; brand fit is image consistency. Poor fit can harm evaluations (e.g., HEYTEA × Durex). Strong fit can create synergy. Cultural congruence (fit of cultural identity) also shapes outcomes; congruent appeals align with norms and values and can foster emotional attachment. Hypotheses: H1 product fit effect on attitude stronger for FB × PB than PB × FB; H2 brand fit effect on attitude stronger for FB × PB than PB × FB; H3 cultural congruence effect on attitude stronger for FB × PB than PB × FB. Cultural sensitivity: Defined as awareness and respect for host cultural practices; cultural respect is an attribute. Missteps (e.g., D&G’s chopsticks ad) show risks of insensitivity. The PB × FB framing may signal FBs’ respect and sensitivity, encouraging positive evaluations. Hypothesis: H4 attitude → cultural sensitivity stronger for PB × FB than FB × PB. Product quality perception: From signaling theory, country/brand cues shape perceived quality. FBs often signal higher quality in developing markets; co-branding can enhance perceived quality of local partners. Hypothesis: H5 attitude → product quality stronger for FB × PB than PB × FB. Attitude and purchase probability: Based on theory of reasoned action, attitudes drive intentions. PBs’ patriotic images can enhance purchase intentions. Hypothesis: H6 attitude → purchase probability stronger for PB × FB than FB × PB.

Research design and stimuli selection: Four-step preparatory study among Chinese students to select realistic brands, product category, and cultural symbols.

• Step 1 (n=35): From 8 FBs (Coca-Cola, Pepsi, Starbucks, Red Bull, Sprite, 7-Up, McCafé, Costa) and 5 PBs (HEYTEA, Nayuki’s Tea, Cha Yan Yue Se, Jianlibao, LeLeCha), respondents chose preferred co-branding partners. Starbucks (mean 5.64) and HEYTEA (mean 5.59) were selected, indicating strong congruence.
• Step 2 (n=35): Rated product categories best representing CMCPs (tumblers, mugs, tea sets, key chains, postcards, bags). Tea set had the highest rating (mean 6.10) as a culturally meaningful item.
• Step 3 (n=38): Evaluated American and Chinese cultural symbols from curated lists. Teddy bear (mean 5.26) and Panda bear (mean 5.45) were most representative of American and Chinese culture, respectively.
• Step 4 (n=108): Created two tea set CMCPs using bicultural framing: FB × PB (Starbucks teddy bear in HEYTEA Chinese tea set) and PB × FB (HEYTEA panda bear in Starbucks English tea set). Respondents rated perceived cultural mixing on 7-point scales: Western tea set with Panda (α=0.83, mean 5.519, t=45.371, p<0.001); Chinese tea set with Teddy (α=0.85, mean 5.213, t=36.317, p<0.001). Independent t-test showed no significant difference between the two bicultural stimuli (t(214)=1.62, p=0.106). Sampling and data collection: Online survey via a Shanghai marketing agent over 45 days. Total N=547; after excluding low familiarity and incomplete responses, final N=479: FB × PB group n=231, PB × FB group n=248. Demographics: 53% male; ages 18–24 (32%), 25–35 (44%), 36–50 (21%), 51+ (3%); 63% bachelor’s/graduate degree; 68% monthly income > US $1,000; 52% purchase beverages at least three times a week. Measures: Nine constructs measured on 7-point Likert scales (1=strongly disagree, 7=strongly agree) adapted from prior literature: product fit, brand fit, cultural congruence, co-branding attitude, cultural sensitivity, product quality, purchase probability (multi-item scales; standardized loadings >0.5). Reliability and validity: KMO >0.7; Bartlett’s test p<0.01; CR ≥0.81 across constructs; AVE ≥0.52; Cronbach’s alpha >0.7. Discriminant validity: square roots of AVE exceeded inter-construct correlations (Fornell-Larcker). Common method variance: randomized item order; Harman’s single-factor EFA indicated single factor explained 37% (FB × PB) and 32% (PB × FB), below 50%, suggesting CMV not significant. Analysis: Multi-group structural equation modeling (AMOS) to test the conceptual model across FB × PB and PB × FB groups. Model fit indices: χ²=61.215, df=24, p<0.01; RMSEA=0.057; AGFI=0.916; CFI=0.945; TLI=0.911; SRMR=0.072.

• Model fit was adequate (χ²=61.215, df=24, RMSEA=0.057, AGFI=0.916, CFI=0.945, TLI=0.911, SRMR=0.072).
• H1 (product fit → attitude stronger for FB × PB than PB × FB): Not supported. Product fit predicted co-branding attitude in both groups but was stronger for PB × FB (β=0.36, p<0.01) than FB × PB (β=0.14, p<0.05).
• H2 (brand fit → attitude stronger for FB × PB than PB × FB): Supported. Brand fit had a stronger effect in FB × PB (β=0.41, p<0.01) than PB × FB (β=0.28, p<0.05).
• H3 (cultural congruence → attitude stronger for FB × PB than PB × FB): Not supported. Cultural congruence effects were significant in both, but stronger for PB × FB (β=0.41, p<0.01) than FB × PB (β=0.35, p<0.01).
• H4 (attitude → cultural sensitivity stronger for PB × FB): Supported. Attitude predicted cultural sensitivity in PB × FB (β=0.23, p<0.01) but not significantly in FB × PB (β=0.09, p=0.17).
• H5 (attitude → product quality stronger for FB × PB): Supported. Attitude predicted product quality in FB × PB (β=0.39, p<0.01) but not significantly in PB × FB (β=0.10, p=0.11).
• H6 (attitude → purchase probability stronger for PB × FB): Supported. Attitude predicted purchase probability in both groups, stronger in PB × FB (β=0.49, p<0.01) than FB × PB (β=0.31, p<0.01). Additional descriptive findings from stimuli checks: Both bicultural tea-set products were perceived as highly culturally mixed (means 5.519 and 5.213 on 7-point scales) with no significant preference difference between the two bicultural framings.

The study demonstrates that Chinese consumers respond differently to two culturally mixed co-branding framings. PB × FB (host × foreign) yields stronger effects of product fit and cultural congruence on co-branding attitude than FB × PB, indicating consumers prefer host-led cultural frames that affirm local identity. Conversely, brand fit matters more for FB × PB, suggesting FBs’ strong reputations act as heuristic quality signals that enhance attitudes when FBs lead co-branding. Cultural sensitivity is more strongly recognized when PB × FB frames are used, implying that FBs embedding Chinese cultural elements signal respect and glocalization, mitigating perceived cultural intrusion. Product quality perceptions are more strongly driven under FB × PB, consistent with foreign product bias and the perception of FBs’ superior quality as co-brand leaders. Attitude positively affects purchase probability for both framings, but the effect is stronger for PB × FB, aligning with rising patriotism and preference for local cultural leadership in collaborations. These findings contribute to cultural mixing and congruity theory by showing that perceived fit dimensions (product, brand, and cultural congruence) and the framing order (who leads: PB or FB) jointly shape attitudes and downstream responses (cultural sensitivity, product quality, and purchase probability). The results nuance prior literature that emphasized exclusionary reactions to culture mixing by identifying conditions under which integrative, positive responses emerge. Managerially, co-branding with culturally sensitive design and appropriate fit assessment can help FBs navigate China’s market, where Guochao and patriotism are salient.

This paper advances understanding of culturally mixed co-branding in China by comparing two framing strategies: FB × PB (foreign × host) and PB × FB (host × foreign). Structural equation modeling on 479 Chinese consumers shows: (1) product fit and cultural congruence influence attitudes more strongly in PB × FB; (2) brand fit influences attitudes more strongly in FB × PB; (3) attitude enhances cultural sensitivity in PB × FB and elevates perceived product quality in FB × PB; and (4) attitude increases purchase probability for both, with a stronger effect in PB × FB. The findings inform glocalization strategies, showing how FBs can leverage PB partnerships to signal cultural respect and enhance acceptance, while FB leadership can bolster perceived quality. Future research should generalize beyond Shanghai and China, examine additional product categories, cultural elements, and incorporate consumer traits (e.g., ethnocentrism, national/global identification) to refine co-branding positioning in diverse markets.

• Context specificity: Focused on Chinese consumers; results may not generalize to other emerging markets. Cross-cultural replications are encouraged.
• Sampling frame: Data collected in Shanghai (a first-tier city), which may limit generalizability across different Chinese city tiers with varying market environments.
• Product scope: Examined a non-food product category (tea sets). Future studies should test broader categories and cultural elements to assess robustness across contexts.
• Model scope: Did not include additional consumer traits and psychosocial moderators (e.g., consumer ethnocentrism, global/national identification). Incorporating these could clarify boundary conditions and segmentation strategies for co-branding glocalization.