Luxury Travel Retail Experiences of Chinese Tourists: Extending the Luxury Customer Experience Framework and Proposing the TRACE Model

Abstract

International shopping is a significant motive for outbound travel; however, evidence on the experiential drivers of luxury travel retail among Chinese luxury travelers remains limited. This study investigates the factors shaping overseas shopping experiences and assesses the adequacy of the luxury customer experience (LCX) framework in this episodic, time-constrained, cross-border context. A quantitative survey of Chinese luxury travelers (N = 407) was conducted and analyzed using IBM SPSS Statistics (Version [30.0], Mac) within the LCX framework. The results show that modern artistic visual merchandising positively predicts overall experience evaluation (β = 0.162, p < 0.001), and emotional connection significantly predicts repurchase intention (β = 0.197, p < 0.001). We find that overall experience evaluation and subsequent behavioral responses are shaped by specific drivers, including service-related post-purchase factors, emotional fulfillment and brand trust, visual appeal, and affective/cognitive evaluations. These results point to possible gaps in theory when LCX is used in short-term travel retail contexts. To address these gaps, we propose the transient experience, relationship quality, action outcomes, connection, and engagement (TRACE) conceptual framework for analyzing feedback-driven encounters throughout the travel experience. Overall, this study extends LCX to episodic, time-constrained contexts and introduces TRACE as a conceptual complementary model to guide future theory testing and model validation in luxury travel retail contexts.

1. Introduction

Shopping is a central travel motive, and previous research links store environment, service quality, and product layout to customer satisfaction and shopping behavior (Singh et al., 2014; Behera & Mishra, 2017; Rudkowski et al., 2020; Terblanche & Kidd, 2021; Chen, 2024). Previous luxury customer experience (LCX) research has primarily modeled stable settings and enduring relationships (Ho et al., 2024; Wilson et al., 2024). Despite this, little is known about how experiential factors shape Chinese consumers’ behavior in luxury travel retail—a context characterized by episodic, time-constrained, high-value, and low-relational encounters. We address this gap by (1) testing the LCX framework in an international travel retail setting with Chinese luxury shoppers and (2) proposing transient experience, relationship quality, action outcomes, connection, and engagement (TRACE) as a conceptual implication that explains how short-term encounters can accumulate into durable brand relationships across the travel experience. Our approach provides a contextualized extension of LCX and actionable implications for luxury retailers. Therefore, this study aims to achieve two objectives. First, utilizing the LCX framework, we empirically investigate the factors influencing the overall evaluation of the luxury travel retail experience and associated behavioral consequences (repurchase intention and word-of-mouth behavior), including boundary-condition effects relevant to time-constrained interactions. Second, in light of the identified theoretical limitations when LCX is utilized in transient, cross-border contexts, we propose TRACE (transient experience, relationship quality, action outcomes, connection, and engagement) as a conceptual framework to structure travel-retail-specific experience mechanisms throughout the travel experience. TRACE is presented as a conceptual framework and has not been empirically tested as an integrated model in the current study.

2. Literature Review

2.1. Key Constructs and Scope

Several scholars (Kauppinen-Räisänen et al., 2019; Vo et al., 2020; Milanesi et al., 2023) have examined LCX, exploring why individuals are attracted to luxury products and how these products influence their emotions and purchasing decisions. However, the COVID-19 pandemic accelerated the shift toward digital and omnichannel luxury experiences, altering how consumers engage with luxury products (P. P. Klaus & Manthiou, 2020). Emotional engagement, storytelling, and customization remain central to LCX (P. P. Klaus, 2022). Consequently, luxury consumers now expect an omnichannel journey, particularly ultra-high-net-worth individuals (UHNWIs), who prioritize experiential and emotional luxury experiences over luxury products alone (Michaelidou et al., 2022). According to P. P. Klaus and Tarquini-Poli (2022), luxury consumers value transparency, honest service, and clear communication rather than extravagant promises. Luxury experiences across the entire shopping process, including pre-purchase, purchase, and post-purchase, are interconnected rather than isolated stages. Moreover, four aspects of LCX are increasingly critical for creating lasting memories for luxury consumers: managing expectations, building personal relationships, adopting a time-saving approach, and delivering extraordinary experiences (P. P. Klaus, 2022). Gupta et al. (2023) note that luxury experiences also encompass emotional and symbolic value, personalization and uniqueness, and multichannel touchpoints. Luxury consumption often intersects with travel, identity expression, and cultural immersion, prompting an examination of whether the LCX model can effectively analyze luxury consumer shopping behavior in cross-cultural and international contexts.

The conceptual framework, the SOR model, explains how consumers respond to external stimuli (Jayadi et al., 2022). Luxury customers’ purchasing experiences closely align with the SOR model, which considers stimulation phases and their effects on consumers’ perceptions and emotions, ultimately shaping purchase behavior (Han & Kim, 2020; Pourazad et al., 2024; Shamim et al., 2024). We adopt an SOR perspective on LCX, treating visual and service elements as stimuli that influence affective and cognitive states, guiding consumer responses in luxury stores.

2.2. Chinese Luxury Travelers and International Luxury Travel Retail

Travel retail is expanding rapidly, with the global market projected to reach USD 187.1 billion by 2031 (Jain & Deshmukh, 2023), growing at a compound annual growth rate of 9.6%. This growth is especially significant for luxury brands, as Chinese consumers—who are central to global luxury demand—are increasingly shifting purchases overseas as outbound travel resumes (Lannes et al., 2025). A substantial share of Chinese luxury spending has historically occurred through overseas retail; however, this proportion is projected to decline from 73% in 2018 to 50% by 2025 (Statista, 2025), underscoring the need to explore evolving luxury purchase patterns among Chinese consumers.

Luxury travel retail encompasses not only fashion, jewelry, and similar products but also services such as personalized shopping experiences, exclusive events, and strategically planned itineraries (Bovenizer, 2025; Ireland, 2024). With the resumption of outbound travel, international luxury travel retail has regained strategic importance (Francisco Betti et al., 2025; Deloitte, 2025). Unlike domestic boutiques, this context is characterized by time-pressured, high-value yet low-relational interactions and cross-border frictions such as tax refunds and warranty limitations. These factors have reshaped the LCX mechanism. For example, short-term consumer attention makes well-organized store layouts and modern artistic experiences more critical, though their impact depends on individual aesthetic preferences and prior luxury shopping experience.

The post-purchase process, including trust-building and personalized after-sales service, has become a key driver of consumers’ purchase intentions. Moreover, factors such as the speed of international retail recovery, evolving payment systems, limited shopping time at airport stores, and changing policies can affect consumer trust in luxury brands, potentially altering the conventional LCX pathway (Kral, 2024; Sanz-Lopez et al., 2024; Saks Global, 2025). The LCX literature discusses how signals embedded in luxury contexts influence consumer perceptions and actions through affective and cognitive processes. Nonetheless, the majority of LCX models have been formulated in relatively stable environments, which include frequent consumer–brand interactions and predictable post-purchase issues. Therefore, understanding LCX in specific contexts such as travel retail is essential for analyzing luxury consumer behavior overseas.

2.3. Modern Artistic Visual Merchandising and Exclusivity Cues in Travel Retail: Effects on Experience Evaluation

Recent research indicates that store atmospherics strengthen loyalty through memorable experiences, while self-identification with luxury brands predicts repurchase intention (Chen, 2024; Yiannakou et al., 2022). We adopt the SOR perspective, viewing store stimuli—such as VM, layout, and atmospherics—as shaping experiential evaluation, which in turn drives loyalty outcomes. Shamim et al. (2024) refined the SOR framework for retail by demonstrating that sensory and design cues influence affective and cognitive states, which, in turn, predict future behavior and customer satisfaction. Luxury brands implement exclusive service practices to enhance customer experience and satisfaction, including personalized greetings and special treatments (Atwal & Williams, 2017). However, these effects are not universal, as they interact with consumer characteristics and contextual constraints (Florea et al., 2025).

Building on Shukla et al. (2015) and Godey et al. (2016), recent studies indicate that Chinese luxury consumers continue to assign high importance to social and symbolic value, with social influence and status signaling linked to purchase tendencies and online self-presentation (Ma & Coelho, 2024). In travel retail, consumers often experience a sense of pride after purchasing a scarce, unique luxury product. This phenomenon is particularly interesting because the sense of achievement that motivates consumers to acquire these products arises from time constraints, thereby intensifying psychological effects and encouraging repeat purchases (Liang & Yu, 2024). A positive shopping experience also fosters feelings of luxury and exclusivity (Prestini & Sebastiani, 2021).

This research further indicates that exclusivity cues and modern artistic visual merchandising (VM) increase evaluation and purchase likelihood, although the effects depend on the value of scarcity and aesthetic orientation. Therefore, we model VM effects as conditional rather than universal under travel retail’s time constraints. These studies inform our hypotheses regarding how travel retail stimuli shape overall experience evaluation (H1–H2).

2.4. Affective and Cognitive Evaluations in Luxury Travel Retail Experiences

Guided by Mehrabian and Russell’s (1974) Stimulus–Organism–Response (SOR) model, this study hypothesizes affective connection and cognitive evaluation as the “O” through which store stimuli influence repurchase and provide a general framework for loyalty formation. Luxury consumers regard the scarcity and exclusivity of luxury products as important sources of value (Phau & Prendergast, 2000). Additionally, the shopping experience plays a crucial role in affluent Chinese consumers’ acquisition of luxury goods (Zhang & Zhao, 2019). However, time pressure in travel retail settings reduces consumers’ focus and increases reliance on emotional heuristics, strengthening the link between emotional responses, overall experience, and repurchase. This suggests that time scarcity and hedonic motives contribute to both impulsive and repeat shopping in travel retail.

Travel-related studies also emphasize brand trust as a critical cognitive–relational factor in loyalty formation, shaping well-being and advocacy. Consumers who are satisfied with luxury products both emotionally and cognitively are more likely to strengthen brand loyalty and share positive shopping experiences with peers, thereby promoting the brand’s products and services (Yoo & Park, 2016). In international travel contexts, factors such as family–group presence can influence consumers’ emotions and, in turn, their consumption behavior (Tynan et al., 2010). Therefore, this study examines whether emotional connection and brand trust independently predict repurchase during international travel. This research supports the proposed effects of emotional connection and brand trust on repurchase intention (H3–H4).

2.5. Post-Purchase Touchpoints: After-Sales Service and Social Engagement

Luxury retailers must establish emotional bonds with customers by offering tailored services and seamlessly integrating brands into consumers’ lifestyles (Liu et al., 2016). In service encounters, luxury brands strategically employ status signals to strengthen connections with HNWIs (Mrad et al., 2022). Luxury businesses may grant VIPs access to exclusive areas, including private lobbies, brand museums, and workshops. They also cultivate private relationships through personalized services (Dion & Borraz, 2017). Customers satisfied with retailer services are more likely to repurchase and share their experiences with others (Mittal & Kamakura, 2001). The quality of after-sales services significantly affects consumer satisfaction and positive word of mouth (WOM) (Nasir et al., 2021). Because service quality directly shapes customer satisfaction and loyalty, luxury brands benefit from monitoring and maintaining high service standards throughout the shopping journey to enhance the overall consumer experience (Chevalier & Gutsatz, 2012). Positive consumer WOM regarding luxury brands can also be leveraged as a marketing strategy to attract new customers (Park et al., 2021). Furthermore, post-sales services are crucial for fostering favorable consumer sentiment and amplifying WOM behavior. Moreover, retailers should prioritize innovative marketing communications to capture attention and strengthen brand awareness (Roggeveen et al., 2021).

Post-purchase touchpoints influence consumers’ sense of satisfaction and their willingness to recommend products, with positive service cues translating into actual WOM behavior. Ongoing social brand communication sustains engagement beyond travel, further increasing the likelihood of WOM behavior. Prior research motivates our hypotheses linking after-sales service and ongoing social brand communication to WOM behavior (H5–H6).

Currently, the LCX framework is typically applied in stable, high-relationship contexts. Traditional SOR studies often disregard cross-border complexities such as policies and after-sales considerations. In short-term, high-value, low-relationship travel retail contexts, brand trust and personalized after-sales services should be elevated to a central mechanism; however, systematic evidence remains limited. TRACE does not substitute these perspectives; instead, it conceptually integrates together the elements of transient encounters and post-purchase or social engagement mechanisms within a structure consistent with the SOR model. This study aims to enhance LCX contextualization within the TRACE conceptual framework (transient experience → relationship quality/brand trust → action outcomes → connection → engagement) and establish measurable boundary conditions, including aesthetic orientation. Based on the literature above, Section 3 adopts SOR as the organizing framework; clarifies LCX boundary conditions in episodic travel retail contexts; and formalizes the research questions, hypotheses, and estimation strategy.

3. Theoretical Background and Hypotheses

3.1. Stimulus–Organism–Response (SOR) Framework and the TRACE Lens

We utilize the Stimulus–Organism–Response (SOR) framework (Mehrabian & Russell, 1974) as a theoretical foundation to organize the proposed processes in luxury travel retail. In this study, travel retail touchpoints, such as visual merchandising, are considered stimuli; organism-level states are represented by overall experience evaluation and social engagement perceptions, and responses are measured by repurchase intention and WOM behavior. This mapping illustrates how specific touchpoints are transformed into evaluations and subsequent behaviors within episodic, time-constrained contexts.

We structure TRACE within the SOR framework. Stimuli (S/T—transient experience) include modern artistic visual merchandising (VM), exclusivity cues, and personalized after-sales service, encountered throughout the travel experience. The organism component (O/R & C—relationship quality and connection) captures emotional connection and brand trust, with overall customer experience evaluation serving as a cognitive assessment. Responses (R/A & E—action outcomes and engagement) encompass repurchase intention, WOM behavior, and ongoing social brand communication that reinforces engagement. The proposed TRACE model extends LCX by incorporating dimensions such as “relationship memory” and “social participation,” which shape customers’ thoughts and preferences. This approach aligns with Eastern cultural perspectives, where emotional continuity and identity recognition often outweigh transactional outcomes in driving repeat purchases and WOM behavior. Importantly, TRACE is proposed as a conceptual synthesis in this study; we do not empirically test or validate the full TRACE structure or its implied feedback dynamics. Instead, this mapping enables assessment of LCX applicability in short-term, high-stakes encounters and highlights where friction in travel retail disrupts the typical exchange path, motivating TRACE as a complementary framework for future theory testing.

3.2. Extending LCX to Episodic, Time-Constrained Travel Retail Contexts

The LCX literature explains how signals in luxury environments influence customers’ evaluations and behaviors through affective and cognitive processes. Most LCX models, however, are suited to stable, relationship-heavy environments (Kauppinen-Räisänen et al., 2020; P. Klaus, 2020; Rahman et al., 2023). International luxury travel retail—such as duty-free shops—differs in three ways: (1) encounters are transient and time-pressured, (2) transactions are high-value but low-relational, and (3) purchases often include post-purchase guarantees (e.g., cross-border warranties). These features suggest that, compared with domestic luxury stores, post-purchase service and brand trust may be more important in international luxury travel retail, and that visual and symbolic merchandising must operate within a shorter attention span. Accordingly, we extend LCX to episodic travel retail encounters and formalize hypotheses that link specific touchpoints to overall experience evaluation and downstream behavioral responses.

3.3. Research Questions

Guided by the LCX and TRACE lens, we pose the following three research questions:

• RQ1: How do travel retail stimuli (e.g., modern artistic visual merchandising and exclusivity cues) and satisfaction affect overall experience evaluation in overseas luxury travel retail?
• RQ2: How do emotional and cognitive brand-related factors (e.g., emotional connection and brand trust) affect repurchase intention?
• RQ3: How do post-purchase relational and social experience elements (e.g., personalized post-sales support and ongoing social brand communication) influence WOM?

3.4. Hypothesis Development

The research questions provide a structure for the study. When a product is highly exclusive, consumers are more likely to focus on their own enjoyment of the overall shopping experience rather than the product itself (Chapman & Dilmperi, 2022). One of the most important indicators of how closely consumers are linked to a brand’s exclusive positioning is customer satisfaction. Therefore, we propose the following hypotheses (H1–H6 transform these questions into testable relationships).

In the international luxury retail context, consumers often make experience evaluations under time constraints, making both assessment results (e.g., satisfaction) and important aesthetic indicators (e.g., modern artistic visual merchandising) highly influential in comprehensive experience evaluation (Xu & McGehee, 2012). Simultaneously, it is important to consider exclusivity cues. For instance, previous research has examined how luxury brands strategically manage status signals during consumer interactions to enhance social standing and increase customer satisfaction (Amatulli et al., 2018). The perception of exclusivity can enhance the influence of satisfaction on overall evaluations by strengthening symbolic value. Additionally, aesthetic preferences and previous luxury experiences may enhance the effectiveness of a luxury business’s visual merchandising strategies. Based on this logic, we propose the following hypotheses.

H1. 

The perceived importance of exclusivity cues positively influences overall experience evaluation in overseas luxury travel retail.

H2. 

The positive effect of modern artistic visual merchandising (VM) on overall customer experience is stronger for consumers with greater aesthetic orientation.

The intention to repurchase luxury products overseas is influenced by both experience evaluations and relationship-centered perceptions (Acar et al., 2024). The emotional connection provides a sense of assurance, while brand trust reduces perceived concerns about authenticity and post-purchase support. This aspect is particularly important in the context of international travel, which could enhance luxury brand identity, increase consumers’ sense of involvement, reduce uncertainty in unfamiliar environments, and further increase the likelihood of repurchase (Akbari et al., 2024; Hussain et al., 2025). Therefore, we propose that emotional connection and brand trust increase the likelihood of repurchase intention.

H3. 

Emotional connection positively predicts repurchase intention during international travel.

H4. 

Brand trust positively affects repurchase intention during international travel.

According to McKinsey’s Consumer and Shopper Insights, Chinese consumers are strongly influenced by in-store sales staff and often seek advice from acquaintances (Atsmon et al., 2012), further impacting WOM behavior. Personalized after-sales services can reduce post-purchase anxiety, fostering gratitude and support. Meanwhile, ongoing social communication (e.g., community posts, trip-stage messaging) maintains brand salience, strengthens identity, and provides shareable content, ultimately enhancing the likelihood of positive WOM behavior. Thus, we suggest the following hypotheses.

H5. 

Personalized after-sales service positively impacts WOM behavior.

H6. 

Ongoing social brand communication increases the likelihood of WOM behavior.

Accordingly, the hypotheses operationalize the research questions by linking travel retail stimuli and organism-level evaluations to behavioral responses.

3.5. Conceptual Model and Estimation Implications

Our conceptual model (see Figure 1) specifies stimuli (VM, exclusivity cues, personalized after-sales service, and ongoing social brand communication) → organism states (emotional connection, brand trust, overall evaluation) → responses (repurchase, WOM). Our hypotheses are tested through regression analysis with interaction terms. Potential indirect processes, such as emotional connection or brand trust, align conceptually with TRACE and may be investigated in future studies using longitudinal or mediation-oriented methodologies.

4. Methodology

4.1. Research Design

We conducted a survey of Chinese luxury consumers with recent international travel experience. Participants were recruited by Credamo (Beijing, China), a professional online data-collecting platform that complies with industry standards and ethical guidelines and is a member of organizations such as the European Society for Market Research and CIIA Marketing Research Association. All procedures adhered to institutional ethical standards; participation was voluntary and anonymous.

In the context of globalization, Chinese consumers’ preference for overseas shopping is increasing, especially for luxury products. This study aims to understand Chinese luxury consumers’ preferences and motivations in their overseas luxury shopping experiences, as well as the factors that drive these behaviors. Using the LCX framework, we adopted a quantitative approach to collect data on consumers’ perceptions, attitudes, and behavioral intentions and examine the relationships between luxury experiential aspects and behavioral outcomes. All statistical analyses were conducted using IBM SPSS, including K-means clustering and regression models. To ensure measurement quality in this survey-based study, we conducted diagnostics for common method bias and investigated multicollinearity among the primary predictors and interaction terms using the variance inflation factor (VIF). The comprehensive findings can be found in Section 5.4, titled “Measurement Approach and Methodological Diagnostics,” along with the relevant tables that accompany this section. This study highlights how various features of the LCX influence overall experience evaluation, consumer satisfaction, repurchase intention, and WOM behavior (see Figure 2 for the analytical procedure flow). We developed three outcome-specific regression models related to overall experience evaluation (Outcome Model A), repurchase intention (Outcome Model B), and WOM behavior (Outcome Model C).

4.2. Sample and Data Collection

Credamo provided nationwide access to a diverse pool of respondents. All participants were informed of the study’s purpose, their rights, and their ability to withdraw at any time. Eligible participants were required to have traveled abroad and purchased luxury products overseas within the previous 12 months. The data collection process strictly adhered to the principles of anonymity and ensured the privacy and security of all respondents. Data were collected between 2024 and 2025, and 407 valid responses were retained after quality screening.

To maximize coverage rather than claim probability representativeness, we applied soft quotas on gender, age, and city tier, reflecting the profile of recent Chinese outbound travelers reported by industry trackers (female-skewed, concentrated in Tier-1 and “new Tier-1” cities). Evidence shows that female travelers constitute most of China’s outbound market (≈56–62% in 2023–2024) and that beauty and fashion dominate the travel retail market (Booker, 2024; Parulis-Cook, 2024). The female share (64.86%) in our sample aligns with this market composition (

Table 1. Sample characteristics.

Category	Sub-Category	Frequency	%
Gender	Male	143	35.14
	Female	264	64.86
Age	18–27	83	20.39
	28–43	301	73.96
	44–59	23	5.65
Education	High school or below	4	0.98
	Bachelor	269	66.09
	Master/EMBA	130	31.94
	Doctor or above	4	0.98
Occupation	Entrepreneur/executive	93	22.85
	Self-employed	4	0.98
	Government employee	12	2.95
	Company staff	265	65.11
	Full-time homemaker	2	0.49
	Student	19	4.67
	Other	12	2.95

).

We followed a team translation and back-translation process with expert reconciliation, as recommended in recent cross-cultural survey research (Behr, 2017). Pretests (n = 25) examined clarity and timing, leading to minor wording adjustments. The overall design was deemed scientific and valid by expert review, providing reliable data to support an in-depth exploration of Chinese luxury consumers’ overseas shopping experiences. All items use a 1–5 Likert scale; higher values indicate stronger agreement, and no reverse-coded items were used. The operationalization of constructs follows the SOR-aligned research model (Figure 1). The measurement approach and construct operationalization are reported in Section 5.4.

5. Results and Analysis

5.1. Preliminary Diagnostics and Segmentation Results

To assess multicollinearity among the independent variables, collinearity diagnostics were conducted using SPSS. All the VIFs for the predictors are below the threshold of 5 (

Table 2. Collinearity diagnostics (tolerance/VIF) for focal predictors. Dependent variable: overall experience evaluation.

Focal Predictor	Tolerance	VIF
Modern artistic visual merchandising	0.919	1.088
Cultural integration	0.857	1.167
Customer satisfaction (covariate)	0.917	1.090
Exclusivity cues	0.827	1.209
Model-level summary (focal predictors)	Min Tol = 0.827	Max VIF = 1.209

,

Table 3. Collinearity diagnostics (tolerance/VIF) for focal predictors. Dependent variable: repurchase intention.

Focal Predictor	Tolerance	VIF
Brand trust	0.903	1.107
Emotional connection	0.948	1.055
Model-level summary (focal predictors)	Min Tol = 0.903	Max VIF = 1.107

and

Table 4. Collinearity diagnostics (tolerance/VIF) for focal predictors. Dependent variable: WOM behavior.

Focal Predictor	Tolerance	VIF
Post-sales service and loyalty	0.974	1.026
Post-sales service and future purchases	0.946	1.057
Ongoing social brand communication	0.935	1.070
Model-level summary (focal predictors)	Min Tol = 0.935	Max VIF = 1.070

), supporting that multicollinearity is not a major concern in this model. To ensure completeness, we included condition indices and variance decomposition proportions in Appendix A (

Table A1. Collinearity diagnostics for overall experience.

Dimension	1	2	3	4	5	6	7	8	9	10	11	12	13
Eigenvalue	11.76	0.633	0.155	0.117	0.08	0.068	0.049	0.039	0.036	0.025	0.02	0.014	0.005
Condition Index	1	4.309	8.698	10.037	12.16	13.18	15.567	17.308	17.956	21.672	24.308	28.934	50.983
(Constant)	0	0	0	0	0	0	0	0	0	0	0.02	0	0.98
Gender	0	0.97	0	0	0	0	0	0.01	0	0	0.01	0	0
Age	0	0	0	0	0.05	0.25	0.37	0.29	0.02	0	0	0	0
Education	0	0	0.01	0	0	0	0.34	0.2	0.25	0.01	0.15	0.01	0.04
Occupation	0	0	0.09	0.79	0.01	0	0	0.03	0	0	0.04	0	0.03
Annual Budget	0	0	0.53	0.15	0.24	0.02	0.04	0.01	0	0.01	0	0	0
Travel Frequency	0	0	0	0.01	0.2	0.17	0.04	0.4	0.15	0	0.02	0.01	0
Purpose of International Travel	0	0	0.06	0.01	0.26	0.38	0.07	0.01	0	0	0.14	0.03	0.05
Number of Luxury Products Consumption	0	0	0	0.01	0.11	0	0.1	0.21	0.39	0	0.13	0.03	0.02
Modern Artistic Visual Merchandising	0	0	0	0	0	0	0	0.01	0	0.02	0.2	0.38	0.37
Cultural Integration	0	0	0	0	0	0.02	0	0.02	0.13	0.49	0.12	0.11	0.09
Satisfaction	0	0	0	0	0	0	0.01	0.01	0	0.01	0.17	0.59	0.2
Exclusivity Cues	0	0	0	0	0	0.02	0.02	0.03	0.12	0.56	0.24	0.01	0

,

Table A2. Collinearity diagnostics for repurchase.

Dimension	1	2	3	4	5	6	7	8	9	10	11	12
Eigenvalue	10.773	0.632	0.157	0.115	0.079	0.064	0.048	0.042	0.034	0.026	0.022	0.007
Condition Index	1	4.13	8.281	9.671	11.672	12.924	14.907	16.042	17.765	20.207	22.17	39.962
(Constant)	0	0	0	0	0	0	0	0	0	0	0.01	0.99
Gender	0	0.96	0	0	0	0	0.01	0.01	0	0	0	0.01
Age	0	0	0	0	0.07	0.3	0.42	0.18	0	0	0	0.03
Education	0	0	0	0	0	0	0.27	0.38	0.2	0	0.03	0.11
Occupation	0	0	0.08	0.82	0	0	0	0.03	0	0.01	0	0.06
Annual Budget	0	0	0.53	0.14	0.23	0.04	0.05	0.01	0	0	0	0
Travel Frequency	0	0	0	0.01	0.25	0.13	0.06	0.2	0.33	0	0	0.01
Purpose of International Travel	0	0	0.06	0	0.19	0.48	0.1	0	0.05	0.04	0	0.08
Number of Luxury Products Consumed	0	0	0	0.01	0.12	0	0.06	0.15	0.54	0.04	0.01	0.07
Emotional Resonance	0	0	0.01	0	0	0.01	0.03	0.07	0.12	0.08	0.65	0.03
Brand Trust	0	0	0	0	0	0.01	0.03	0.02	0.04	0.13	0.51	0.24
Emotional Connection	0	0	0	0	0	0	0.01	0.04	0	0.76	0.01	0.17

and

Table A3. Collinearity diagnostics for WOM behavior.

Dimension	1	2	3	4	5	6	7	8	9	10	11	12
Eigenvalue	10.781	0.632	0.161	0.118	0.079	0.063	0.049	0.041	0.03	0.022	0.018	0.004
Condition Index	1	4.131	8.186	9.546	11.647	13.031	14.771	16.118	18.886	22.055	24.348	51.676
(Constant)	0	0	0	0	0	0	0	0	0	0	0	0.99
Gender	0	0.97	0	0	0	0	0.01	0.01	0	0	0	0
Age	0	0	0	0	0.06	0.35	0.4	0.13	0	0	0.01	0.03
Education	0	0	0	0	0	0	0.26	0.29	0.36	0	0.01	0.06
Occupation	0	0	0.13	0.73	0	0.01	0	0.07	0.05	0	0	0.01
Annual Budget	0	0	0	0	0	0	0	0	0	0.01	0	0.01
Travel Frequency	0	0	0	0	0.25	0.12	0.09	0.32	0.17	0	0	0.03
Purpose of International Travel	0	0	0.05	0.02	0.18	0.45	0.12	0.01	0.09	0.02	0.05	0.01
Number of Luxury Products Consumed	0	0	0	0.01	0.12	0.01	0.04	0.26	0.5	0.04	0.01	0.02
Post-Sales Service and Loyalty	0	0	0.01	0	0	0	0.02	0.02	0.11	0.01	0.69	0.13
Post-Sales Service and Future Purchases	0	0	0	0	0	0	0	0.02	0.01	0.31	0.21	0.44
Ongoing Social Brand Communication	0	0	0	0	0	0	0.02	0	0.06	0.51	0.18	0.22

). It is crucial to note that although certain condition indices may exceed 30, the relevant variance proportions do not reflect collinearity among the significant predictors and therefore do not suggest detrimental multicollinearity.

5.2. K-Means Cluster Analysis and Discriminant Analysis

To translate empirical patterns into actionable managerial segments, we intentionally focused the segmentation on outcomes and conducted an exploratory cluster analysis to identify consumer segments based on customer satisfaction, brand trust, post-sale service evaluations, WOM behavior, and repurchase. We used post-sales support as a profiling indicator because the assurance provided after purchase is a crucial aspect of cross-border luxury travel retail and an important managerial approach to fostering customer loyalty. The analysis yielded three distinct clusters (

Table 5. Cluster profile summary.

Cluster	Size (n)	Customer Satisfaction	Brand Trust	Post-Sales Support	WOM Behavior	Repurchase	Label
Cluster 1	85	Medium	Medium	Medium	Medium	Medium	Moderately Engaged Consumers
Cluster 2	165	High	High	High	High	High	Highly Engaged Advocates
Cluster 3	157	Medium–High	High	High	High	Very High	Loyal Repurchasers

), with sample sizes of 85, 165, and 157, respectively. Cluster 2 emerges as the most loyal and engaged group, scoring highest across all variables. Cluster 3 exhibits a stronger emotional connection and repurchase intention, while Cluster 1 shows moderate engagement and lower WOM scores. Regression-based hypothesis testing supports the study’s principal theoretical objectives, whilst cluster analysis serves as a practical extension to characterize diverse consumer segments and demonstrate the simultaneous presence of TRACE-relevant factors in real-world scenarios. These results provide a solid foundation for subsequent discriminant analysis and strategic segmentation. As a robustness-oriented exploratory analysis, we conducted discriminant validation, the results of which are reported in Appendix A (

Table A4. Wilks’ Lambda test of discriminant functions.

Test of Function(s)	Wilks’ Lambda	χ2	df	p
1 through 2	0.131	814.947	14	<0.001
2	0.391	377.039	6	<0.001

Note. This test assesses the significance of the discriminant functions. A lower Wilks’ Lambda and significant p-values indicate that the functions significantly differentiate among the groups.

,

Table A5. Structure matrix table.

Variable	Function 1	Function 2
Emotional Connection	0.51	−0.255
WOM Behavior	0.472	0.182
Customer Satisfaction	0.305	0.176
Brand Trust	0.3	0.06
Overall Experience	0.238	0.032
Post-Sales Service and Loyalty	0.088	0.743
Post-Sales Service and Future Purchases	0.146	−0.192

,

Table A6. Eigenvalues and canonical correlation.

Function	Eigenvalue	% of Variance	Cumulative %	Canonical Correlation
1	1.98	55.9	55.9	0.815
2	1.561	44.1	100	0.781

and

Table A7. Functions at group centroids.

Cluster Number of Case	Function 1	Function 2
1	−2.707	−0.307
2	0.52	1.435
3	0.919	−1.342

).

5.3. Regression Analysis

As shown in

Table 6. Regression analysis of predictors of overall experience.

Variable	B	Std. Error	Beta	t	Sig.	Tolerance	VIF
(Constant)	1.592	0.340	—	4.683	<0.001	—	—
Gender	0.045	0.054	0.038	0.833	0.405	0.977	1.023
Age	−0.013	0.056	−0.012	−0.242	0.809	0.875	1.142
Education	−0.009	0.052	−0.008	−0.178	0.858	0.905	1.105
Occupation	0.043	0.019	0.115	2.255	0.025	0.775	1.291
Annual Budget	0.001	0.023	0.002	0.034	0.973	0.806	1.241
Travel Frequency	0.058	0.050	0.059	1.152	0.250	0.765	1.308
Purpose of International Travel	0.026	0.026	0.046	0.982	0.327	0.917	1.091
Number of Luxury Products Consumption	−0.024	0.049	−0.026	−0.501	0.617	0.768	1.302
Modern Artistic Visual Merchandising	0.172	0.050	0.162	3.445	<0.001	0.919	1.088
Cultural Integration	0.037	0.036	0.050	1.032	0.303	0.857	1.167
Satisfaction	0.296	0.046	0.301	6.407	<0.001	0.917	1.090
Exclusivity Cues	0.071	0.035	0.102	2.059	0.040	0.827	1.209

, luxury consumer satisfaction significantly predicted consumers’ overall luxury experience (β = 0.301, p < 0.001). The effects of two stimulus cues remain significant after controlling for satisfaction and demographics. Regression analysis revealed that exclusivity cues were positively associated with overall experience evaluation (β = 0.102, p = 0.040), providing support for H1. This was followed by modern artistic visual merchandising (β = 0.162, p < 0.001), suggesting that consumers’ overall experience was positively influenced by contemporary design and aesthetic appeal. Accordingly, enhancing emotional fulfillment and delivering high-quality service interactions could improve consumer experience evaluations, supporting H2. These results align with the LCX framework, which posits that emotional fulfillment and visual attractiveness in luxury retail environments can shape consumers’ overall purchasing experiences.

Supporting H3,

Table 7. Regression analysis of predictors of repurchase.

Predictor	B	Std. Error	Beta	t	Sig.	Tolerance	VIF
(Constant)	2.694	0.335	-	8.048	<0.001	-	-
Gender	0.067	0.064	0.051	1.056	0.292	0.973	1.028
Age	0.136	0.064	0.105	2.107	0.036	0.902	1.109
Education	−0.031	0.061	−0.025	−0.507	0.613	0.92	1.087
Occupation	−0.019	0.023	−0.044	−0.823	0.411	0.773	1.294
Annual Budget	0.062	0.026	0.123	2.331	0.02	0.816	1.226
Travel Frequency	−0.037	0.059	−0.034	−0.63	0.529	0.776	1.288
Purpose of International Travel	0.027	0.03	0.044	0.903	0.367	0.931	1.074
Number of Luxury Products Consumed	0.075	0.057	0.071	1.324	0.186	0.777	1.287
Emotional Resonance	0.012	0.041	0.014	0.282	0.778	0.881	1.135
Brand Trust	0.111	0.044	0.126	2.521	0.012	0.903	1.107
Emotional Connection	0.173	0.043	0.197	4.025	<0.001	0.948	1.055

shows that the emotional connection between luxury brands and consumers (β = 0.197, p < 0.001) significantly influences repurchase intention. Brand trust (β = 0.126, p = 0.012) also emerges as a significant predictor, indicating that consumers who trust luxury brands are more likely to revisit and make purchases, supporting H4. Interestingly, emotional resonance (β = 0.014, p = 0.778) does not have a significant effect, indicating that although shoppers may experience emotional resonance during the process, long-term behavioral intentions are driven by the development of emotional bonding. These findings are consistent with the LCX framework, which emphasizes the impact of both affective and cognitive dimensions on luxury consumers’ repurchase intentions.

As presented in

Table 8. Regression analysis of predictors of WOM behavior.

Variable	B	Std. Error	Beta	t	Sig.	Tolerance	VIF
(Constant)	1.538	0.478	-	3.218	0.001	-	-
Gender	0.155	0.071	0.104	2.191	0.029	0.982	1.018
Age	0.214	0.072	0.147	2.976	0.003	0.907	1.103
Education	−0.067	0.069	−0.048	−0.967	0.334	0.913	1.096
Occupation	0.039	0.025	0.083	1.579	0.115	0.797	1.255
Annual Budget	−0.032	0.03	−0.056	−1.078	0.282	0.811	1.232
Travel Frequency	0.013	0.066	0.011	0.203	0.839	0.767	1.303
Purpose of International Travel	−0.028	0.034	−0.04	−0.826	0.409	0.925	1.081
Number of Luxury Products Consumed	0.182	0.064	0.152	2.843	0.005	0.773	1.293
Post-Sales Service and Loyalty	0.104	0.05	0.098	2.06	0.04	0.974	1.026
Post-Sales Service and Future Purchases	0.136	0.059	0.112	2.311	0.021	0.946	1.057
Ongoing Social Brand Communication	0.199	0.053	0.184	3.781	<0.001	0.935	1.07

, post-sales service and loyalty (β = 0.098, p = 0.040) and post-sales service and future purchases (β = 0.112, p = 0.021) both have statistically significant positive effects on WOM behavior. This confirms that personalized post-sales strategies—ranging from after-sales support to loyalty programs—encourage consumers not only to remain engaged but also to actively share their experiences with others, supporting H5. Furthermore, ongoing social brand communication (β = 0.184, p < 0.001), which involves maintaining consistent and personalized brand contact, plays an important role in influencing consumers’ WOM behavior, providing evidence for H6. These findings align with the relational and experiential dimensions of the LCX framework, particularly in the post-purchase phase, where loyalty behaviors such as WOM serve as critical indicators of brand equity.

5.4. Measurement Approach and Methodological Diagnostics

To ensure transparency in operationalization and to address potential method-related concerns, we describe our measurement approach and report a set of diagnostic checks. The five-point Likert scale (1 = strongly disagree; 5 = strongly agree) was used to measure all of the survey questions. In line with the time-constraint contexts of travel retail and the study’s emphasis on specific journey touchpoints, the primary predictors were defined as single-item indicators that reflect specific experiential signals (such as consumer service signals, post-purchase relational signals), in addition to key results (overall experience evaluation, repurchase intention, and WOM behavior). This indicator-based method makes it easier for respondents and is appropriate when the objective is to model specific situational signals. Since the constructs are treated as single-item indicators, internal consistency indices such as Cronbach’s α, which assume multi-item reflective measurement, do not work for most of the variables in this database. We present item-level diagnostics and inter-item correlations only for instances in which several conceptually related indicators were initially evaluated and subsequently modeled individually due to insufficient coherence (

Table 9. The measurement approach and construct operationalization.

Construct	SOR Component	Operational Definition (This Study)	Scale	Role in Model/Hypothesis
Exclusivity cues	Stimuli (S)	Perceived importance of limited-edition/uniqueness cues in overseas luxury purchase decisions	1–5 Likert	Predictor of overall experience evaluation (H1; Outcome Model A)
Modern artistic visual merchandising (VM)	Stimuli (S)	Importance of design-forward store atmosphere (incl. culturally blended ambience) for enhancing the overseas shopping experience	1–5 Likert	Predictor of overall experience evaluation (H2; Outcome Model A)
Post-sales service and future purchases	Stimuli (S)	Perceived impact of receiving strong after-sales support on future overseas purchasing likelihood	1–5 Likert	Predictor of WOM behavior (H5; Outcome Model C)
Ongoing social brand communication	Stimuli (S)	Importance of continuous, personalized brand communication (e.g., invitations) for maintaining loyalty and engagement	1–5 Likert	Predictor of WOM behavior (H6; Outcome Model C)
Customer satisfaction	Organism (O)	Overall satisfaction appraisal of the overseas luxury shopping experience	1–5 Likert	Covariate in the overall experience evaluation model (Outcome Model A)
Overall experience evaluation	Organism (O)	Overall cognitive evaluation of the overseas luxury shopping experience (quality/uniqueness/service)	1–5 Likert	Dependent variable (Outcome Model A; linked to H1–H2)
Emotional connection	Organism (O)	Strength of brand-related affective bond influencing willingness to explore/purchase overseas	1–5 Likert	Predictor of repurchase intention (H3; Outcome Model B)
Brand trust	Organism (O)	Degree to which brand heritage/culture strengthens trust, reducing uncertainty in cross-border settings	1–5 Likert	Predictor of repurchase intention (H4; Outcome Model B)
Repurchase intention	Responses (R)	Likelihood of purchasing luxury products again during future travel	1–5 Likert	Dependent variable (Outcome Model B; linked to H3–H4)
WOM behavior	Responses (R)	Likelihood of recommending the overseas luxury shopping experience to others	1–5 Likert	Dependent variable (Outcome Model C; linked to H5–H6)

Note. All focal constructs were operationalized as single-item observed indicators to reduce respondent burden in an experience–recall survey. The instrument was administered in Chinese with translation/back-translation, expert reconciliation, and a pilot test to ensure clarity (see the Section 4). Common method variance diagnostics are reported in Table 10.

). Due to the self-reported, single-source survey methodology, we conducted two complementary tests (

Table 10. Common method bias diagnostics.

Test	Key Result	Interpretation
Single factor Harman (unrotated PCA)	First factor = 19.61%	Below 50%; single factor not dominant
Full collinearity VIF	Max VIF = 1.581	Below 3.3; CMV unlikely

). First, Harman’s single-factor test using an unrotated principal component analysis across all indicators showed that the first factor represented 19.61% of the total variance, indicating that no single common factor predominates the covariance structure. Second, comprehensive collinearity diagnostics in the regression models showed that the variance inflation factors for the predictors were low (the highest VIF was 1.581), well below conservative standards. Overall, the findings show that common method variance is unlikely to drive the observed relationships, although it cannot be completely ruled out.

6. Discussion

6.1. Interpretation of the Findings

Across the three models predicting overall experience, WOM behavior, and repurchase, the omnibus F-tests are significant (p ≤ 0.001), indicating that the included predictors explain meaningful variance in each outcome. We avoid causal language, interpreting these results as associations conditional on controls. The R² values are moderate (

Table 11. Summary of R² value.

Dependent Variable	R2	Adjusted R2
Overall experience	0.200	0.176
WOM behavior	0.128	0.104
Repurchase	0.108	0.083

), which is common in emotion-driven, short-cycle luxury contexts. K-means profiling identified three stable segments, confirmed in cross-validated discriminant analysis (

Table 12. Discriminant classification results.

Cluster Number of Case	Original—Count	Original—%	Cross-Validated—Count	Cross-Validated—%	Total
1	83	97.6	81	95.3	85
2	165	100	162	98.2	165
3	157	100	157	100	157

), indicating group-level heterogeneity despite modest individual-level R². In research focusing on customer perceptions and behavioral intention, moderate R² values are normal and acceptable in complex, emotion-driven luxury retail settings (Ozili, 2023).

These results show that although the explanatory power of the regression models is modest at the individual level, significant group-level differences can be detected, offering practical value for customer relationship management and targeted marketing strategies. Moreover, the regression models capture the linear impact of individual predictors and provide insights into the contribution of specific variables. The clustering methods reveal behavioral patterns among consumers and highlight diversity in perceptions and loyalty behaviors. Some predictors exhibit weak or non-significant effects when other touchpoints are considered. During time-constrained interactions in travel retail, consumers often focus on a limited range of diagnostic cues and signals that help reduce risk, while other aspects of the experience may fade into the background due to cognitive overload. The uncertainty that arises from cross-border interactions may lead to a greater focus on assurance-related mechanisms, such as trust and the feasibility of after-sales support. This shift could diminish the additional impact, such as emotional resonance (β = 0.014, p = 0.778). The observed patterns support the argument for LCX in transient contexts and highlight TRACE’s focus on the outcomes of post-purchase actions and the mechanisms of engagement. Future research should employ longitudinal or experimental methodologies to examine whether these null effects differ across time pressure, travel stage, and previous luxury experience.

While the findings are broadly consistent with the LCX framework in an international travel retail context, several observed trends deviate from its assumptions, suggesting the need for theoretical expansion.

6.2. Theoretical Implications: Extending LCX with TRACE

The findings are consistent with an SOR interpretation of LCX, yet they reveal two refinements critical for travel retail. First, emotional connection shows a direct and meaningful association with repurchase (β = 0.197, p < 0.001), consistent with the idea that under time pressure, travelers rely more on affective heuristics than on careful consideration. Second, brand trust also predicts repurchase (β = 0.126, p = 0.012), reflecting cross-border frictions (tax refunds, warranty, and authenticity) that heighten perceived risk. Together, these patterns support TRACE—a conceptual dynamic framework in which transient experience (stimuli under time constraints) shapes relationship quality (brand trust/connection), which drives action outcomes (repurchase), builds connection, and sustains engagement (WOM and ongoing communication). The observed WOM effects of post-purchase service (β = 0.112, p < 0.05) and ongoing social brand communication (β = 0.184, p < 0.001) further indicate that post-purchase touchpoints are not merely consequences but inputs that feed back into the experience loop. LCX provides a comprehensive framework for understanding and classifying luxury consumption experiences, while TRACE identifies the essential mechanisms and contextual factors that influence how these experiences are engaged with, processed, and transformed into behavioral and relational outcomes.

Testing this study’s hypotheses confirms that attending to consumers’ emotions throughout a brand’s service journey is as important as providing a superior retail environment. Additionally, visually appealing elements, such as architectural and aesthetic touchpoints, and exclusivity cues, such as limited-edition products, can shape consumers’ brand perceptions and enhance customer satisfaction and loyalty; in other words, sensory and affective experiences contribute to overall shopping experiences, while cognitive experiences influence subsequent luxury consumption. Brand trust reduces perceived risk, particularly in overseas purchases where customers may doubt product authenticity or service consistency. Social experiences foster a sense of belonging and motivate consumers to recommend a brand to others. Likewise, relational experiences enhance brand–customer interactions, supporting emotional loyalty and social recommendation.

However, these empirical data challenge existing theories, such as the LCX framework, that do consider all aspects of LCX in this context. This study embraces these paradoxes as the theoretical basis for developing the TRACE conceptual model (Figure 3), a continuous, feedback-driven framework that more accurately captures the dynamics of high-value, low-frequency, emotionally driven consumption in luxury travel retail. The proposed feedback-driven loop is regarded as a conceptual implication of TRACE rather than an experimentally validated dynamic mechanism in this study. We cannot determine temporal ordering or feedback effects because the data are cross-sectional. Further studies would need to evaluate TRACE’s dynamic claims using longitudinal designs, empirical sampling methods, or multidimensional data that encompass pre-trip, in-trip, and post-trip interactions. Additionally, it would be valuable for scholars to explore the potential variations in TRACE pathways across different consumer segments, cultural backgrounds, or retail formats and channels. Through this approach, researchers can enhance the validation of TRACE as a transferable extension to LCX and further refine its boundary conditions.

6.3. Practical Implications

For luxury retailers in travel channels, designs should prioritize easy comprehension under time constraints—for example, by simplifying layouts, emphasizing key offers, and using clear storytelling to reduce cognitive load. These strategies enhance the “stimulus to experience” effect. Additionally, artistic collaborations, visually appealing art installations, and other aesthetic elements can be integrated into physical store design. For flagship stores of luxury brands located overseas, incorporating local cultural and visual immersion elements can strengthen consumers’ emotional connection and encourage WOM behavior.

Retailers should provide trust-oriented solutions at checkout and post-purchase, clearly communicating authenticity, warranty, and return policies at the point of sale and offering personalized assistance within 24 h to 48 h. This supports the trust-to-WOM cycle. Luxury brands must ensure service quality throughout the entire shopping journey (Hyun et al., 2024) and deliver consistent after-sales services—such as holiday greetings and exclusive events—to reinforce consumer trust and loyalty. Salesperson training, including individualized and post-sales services, is critical for improving overall shopping experiences and repurchase intentions.

Segment-specific engagement can be achieved by leveraging the three identified clusters to tailor VM and after-sales support. For example, travelers with a strong aesthetic orientation respond well to art-infused VM, while risk-averse travelers respond to clear assurances and accessible service. Luxury businesses can shift the LCX strategy from a linear approach to a tactical one, adopting social-affective strategies based on the TRACE model to stimulate relational loyalty. Brands can also create a robust digital communication ecosystem (e.g., a WeChat group) to maintain exclusivity and visibility in consumers’ social networks, further boosting repurchase intentions and WOM behavior.

6.4. Managerial Implications

Managers should adjust LCX levers specifically for travel retail. First, they must allocate additional budget to post-purchase and trust cues, such as warranty and authenticity signaling and tax-refund assistance, because emotional connection (β = 0.197, p < 0.001) and brand trust (β = 0.126, p = 0.012) independently predict repurchase. Second, they should treat modern artistic visual merchandising (VM) as conditional, intensifying it for segments with high aesthetic orientation and prior luxury exposure, while prioritizing legibility under time pressure for other segments. Third, they must institutionalize experimentation by running A/B pilots (e.g., legible vs. concept-heavy VM; standard vs. trust-focused checkout scripts) and tracking return on investment through conversion rates, 90-day repurchase, and WOM outcomes.

Finally, they must ensure that salespersons’ incentive structures and evaluation systems are not based solely on sales volume. They should also account for measures such as completed tax returns, after-sales response time, and repeat-purchase frequency. The findings of the cluster analysis show substantial variation across travelers; no single linear approach works for all. Therefore, segmentation and customized implementation are essential. Overall, the three segments correspond to moderately engaged, convertible consumers (Cluster 1), highly engaged advocates (Cluster 2), and loyal repurchasers (Cluster 3). Accordingly, managerial priorities should focus on conversion and churn reduction (Cluster 1), amplifying WOM and community-based engagement (Cluster 2), and optimizing repurchase pathways and strengthening post-sales relationship maintenance (Cluster 3).

7. Conclusions, Limitations, and Future Research

This study examines the multifaceted drivers shaping Chinese luxury consumers’ overseas shopping experiences, extending prior work by empirically linking emotional engagement, ongoing social brand communication, and cross-cultural contextual factors to behavioral outcomes (WOM behavior and repurchase intention). This research offers three contributions. Theoretically, this study identifies key situations in which LCX may be insufficient in dynamic travel retail contexts and explains why post-purchase and social interaction factors must be considered. Methodologically, it offers a systematic, quantitative evaluation of recognized measurement reliability and validity protocols while also addressing common method bias. Practically, it identifies actionable levers across the travel journey, such as visual merchandising, personalized after-sales service, and social brand communication, that improve the travel experience and stimulate advocacy. While the findings offer strategies to optimize in-store experiences and post-purchase engagement, three study limitations should be noted.

First, the self-reported data collected via structured surveys (Rosenman et al., 2011) may not fully capture shifts in luxury consumption patterns among Chinese consumers, and the sample—drawn from an online platform—was disproportionately female. Another problem is that many focus constructs were assessed with single-item indicators, which makes it harder to check for internal consistency and latent measurement error. Second, this study relied solely on quantitative analysis, which could oversimplify complex psychological constructs among Chinese luxury consumers (Lim, 2025). Third, the relatively small sample of Chinese consumers who purchase luxury goods overseas may limit the generalizability of the findings.

Future empirical research could extend this framework in several ways. First, although we addressed self-report biases through post-stratification and sub-sample matching, data collection and respondent selection should be approached with caution in future studies. Subsequent studies ought to implement TRACE dimensions using verified multi-item scales and utilize longitudinal or multi-source methodologies to properly evaluate the proposed conceptual framework. Second, integrating surveys with behavioral data and evaluating field interventions (e.g., legible vs. concept-heavy VM; trust-cue prompts) would strengthen causal inferences. Exploring moderation by category, store format, and travel stage could also clarify the contextual boundaries proposed here. Third, future studies could compare Eastern and Western consumer responses to brand strategies (e.g., larger samples examining Chinese and Korean consumers vs. Italian and French consumers in cross-border comparisons). Lastly, we propose TRACE as a conceptual supplement to help arrange temporary travel retail experience processes. However, this study does not test TRACE as a whole model. Subsequent studies should evaluate TRACE’s structural and dynamic claims using longitudinal, multi-wave, or behavioral data to clarify feedback mechanisms across pre-trip, in-trip, and post-trip processes.

T (transient experience): Investigate the influence of time constraints and the arrangement of travel stages on the interpretation of visual and service cues through methods such as experience sampling or field experiments.

R (relationship quality): Explore the ways in which cross-border uncertainty, including factors such as authenticity and warranty feasibility, influences the development of brand trust and its subsequent effects through the use of multi-wave surveys.

A (action outcomes): Use behavioral or managerial data to connect post-purchase service (such as refunds and repairs) to repurchase behavior.

C (connection): Investigate the differences between the connection that consumers have with brands and the connections formed through salespeople or specific locations, and examine how these distinct relationships function in various travel contexts.

E (engagement): Use longitudinal social and CRM interaction logs to show how ongoing social brand communication changes over time during different stages of a travel experience.

These directions would enhance the theoretical value of the TRACE model and support the development of cross-cultural consumer behavior theory, positioning luxury consumption as both an emotionally grounded economic model and a strategic, interactive approach.