From Malls to Markets: What Makes Shopping Irresistible for Chinese Tourists?

Abstract

This study investigates how multidimensional value and experience quality shape satisfaction and loyalty in shopping tourism. We extend the QVSL tradition by (i) specifying three hedonic value dimensions (entertainment, exploration, escapism), (ii) differentiating functional value into performance-oriented and money-saving facets, and (iii) incorporating epistemic value and experience quality as additional antecedents. We also model immediate behavioral outcomes (i.e., money spent and time spent) and test involvement as a moderating condition. Using path analysis on data from 413 mainland Chinese tourists in Japan, findings confirm that entertainment, functional value (for performance and money), epistemic value, and experience quality enhance shopping satisfaction. Functional values, epistemic value, and satisfaction drive destination loyalty. Money and time spent are additional outcomes of satisfaction. Involvement moderates the link between satisfaction and money spent. These insights offer strategic implications for Destination Marketing Organizations (DMOs) and retailers to optimize shopping environments and employee services, increasing tourist satisfaction, loyalty, and both time and money spent in the competitive shopping tourism market. Limitations include the cross-sectional design and the use of composite-indicator path analysis; future research could apply longitudinal or full SEM approaches, broaden contexts, and test additional constructs.

1. Introduction

In recent years, shopping has become a prominent and significant form of niche tourism, significantly enhancing the tourist experience (Badu-Baiden et al., 2024; Lee & Choi, 2020; Murphy et al., 2011; Pang & Sanders, 2025). The trend is particularly evident among Chinese tourists, whose shopping–focused travels have bolstered Japan (Correia et al., 2018; Hung et al., 2021). Recent data show a 228.4% surge in visitor arrivals from January to September 2024 (Nippon, 2020). This surge, fueled by increased flight connectivity, highlights the economic significance of shopping tourism, particularly amid favorable currency conditions such as the depreciation of the Japanese yen during peak travel seasons like China’s Golden Week (The Asahi Shimbun, 2024). Recent industry data also show that Korea and Japan rose to first and second place among outbound Chinese destinations in 2024, with Japan listed among the fastest-growing routes, underscoring this market’s salience for shopping-motivated travel (Sabre, 2024). Given this growth, it is important to clarify how shopping experiences translate into satisfaction and destination loyalty among international tourists, especially outbound Chinese visitors to Japan, in order to inform destination strategy. These shifts highlight the need to reassess established value–satisfaction–loyalty models such as QVSL in light of post-COVID, digitally mediated, and sustainability-salient shopping tourism.

Beyond traditional brick-and-mortar shopping, several recent shifts are reshaping tourist purchasing. Tourists increasingly engage in in-destination online shopping (DOS) (i.e., placing e-commerce orders while traveling), which complements store visits and reflects changing retail formats and behaviors (Xu et al., 2024). Sustainability has become a salient evaluative lens: tourists exhibit segment-specific preferences for sustainability features and varying willingness-to-pay, with five distinct market segments identified (Cai et al., 2024). Additionally, post-pandemic evidence indicates a rebalancing toward utilitarian/functional value in driving satisfaction and revisit intentions, while the influence of hedonic and social value has attenuated and varies with shoppers’ COVID-responsible behaviors and visit frequency (Moharana & Pattanaik, 2023). Taken together, these developments heighten the need to clarify which value dimensions and experience-quality cues matter most for cross-border shoppers—particularly mainland Chinese visitors to Japan. Accordingly, our study foregrounds which value dimensions and experience-quality cues matter most now, and it links attitudinal evaluations to immediate on-site behaviors (time and spending) while testing involvement as a moderator.

Despite these shifts, existing literature reveals important research gaps. First, limited research has specifically investigated Chinese tourists’ shopping behaviors within the context of Japan, focusing predominantly on general expenditure patterns rather than an in-depth analysis of shopping values and experiences (Jin et al., 2017). Additionally, while previous studies acknowledge the multidimensional nature of shopping value (Choi et al., 2018; El-Adly & Eid, 2017; Sheth et al., 1991), there remains insufficient empirical investigation of how distinct dimensions of shopping value (e.g., functional, hedonic, epistemic) collectively and independently influence both satisfaction and loyalty specifically among international tourists. In shopping-led trips, this matters for destination competitiveness: tourist shopping is a major contributor to destination revenues (Albayrak et al., 2016), and satisfying shopping experiences elevate overall trip satisfaction and stimulate positive word-of-mouth about the destination (Vega-Vázquez et al., 2017). Moreover, destination loyalty (i.e., repeat visitation and recommendation) supports sustained demand and helps destinations remain competitive (Chang et al., 2025; J. S. Chen & Gursoy, 2001). Understanding its antecedents is therefore essential for developing an attractive shopping destination (Suhartanto et al., 2016). Furthermore, while tourist loyalty is well-explored as an outcome in traditional quality-value-satisfaction (QVS) frameworks, the immediate behavioral consequences of satisfaction, particularly money and time spent during the visit, remain understudied outcomes (Vena-Oya et al., 2021; Zhang et al., 2012). This study addresses these gaps by empirically examining how multidimensional values influence shopping satisfaction and loyalty and identifying immediate behavioral outcomes, such as tourists’ monetary and temporal expenditures.

Shopping tourism research often conceptualizes “value” as multidimensional, encompassing both hedonic (entertainment, exploration, escapism) and functional aspects (performance, monetary value), as well as epistemic value related to novelty and learning experiences (Kim et al., 2014; Rintamäki et al., 2006; Sheth et al., 1991). However, prior studies predominantly focused on local or domestic retail environments (Arnold & Reynolds, 2003; El-Adly & Eid, 2015), providing limited insights into how international tourists evaluate and prioritize these value dimensions differently, thus limiting generalizability. Our selection of mainland Chinese tourists shopping in Japan was deliberate because this population represents a prominent and economically significant segment of the global shopping tourism market (Hung et al., 2021; Jin et al., 2017), yet remains understudied regarding their multifaceted consumption behaviors abroad. Investigating this specific tourist population thus provides a clearer understanding of distinct international shopping behaviors. It offers comparative insights applicable to similar contexts involving tourists from emerging economies visiting developed countries characterized by strong retail sectors.

Moreover, this study uniquely integrates the moderating effect of tourist involvement, an essential yet under-explored psychological construct that influences consumer behavior differently across contexts (C. F. Chen & Tsai, 2008; Sohn & Lee, 2017). Prior research indicates involvement significantly shapes shopping behaviors and spending patterns. Still, its role as a moderator in international shopping contexts remains unclear, particularly between satisfaction and immediate outcomes (money and time spent). Therefore, this study addresses these research gaps by testing a comprehensive conceptual model among a selected sample, offering theoretical clarity and practical strategies for optimizing shopping tourism outcomes that can extend to broader international tourism contexts.

This study advances shopping-tourism research by modeling how multidimensional value and experience quality shape tourist outcomes in shopping contexts. Building on the quality–value–satisfaction–loyalty (QVSL) tradition, we extend this framework to shopping tourism by (i) disentangling hedonic value into three conceptually distinct dimensions, i.e., entertainment, exploration, and escapism; (ii) differentiating functional value into performance-oriented and money-saving facets; and (iii) examining epistemic value and experience quality (the perceived excellence of the shopping encounter) as additional antecedents of shopping satisfaction and destination loyalty. We also incorporate immediate behavioral outcomes (i.e., money spent and time spent) and test tourist involvement as a moderator of these relationships. Accordingly, we ask: (RQ1) do these value dimensions and experience quality explain shopping satisfaction; (RQ2) do values and satisfaction extend to destination loyalty; (RQ3) does satisfaction translate into time and money spent; and (RQ4) does involvement condition these links? The paper is organized as follows. Section 2 reviews the literature and develops hypotheses linking multidimensional values (hedonic subdimensions, functional and epistemic values) and experience quality to shopping satisfaction, destination loyalty, and the immediate outcomes of time and money spent, while positioning shopping involvement as a moderator. Section 3 describes the research design and study context (i.e., mainland Chinese tourists visiting Japan) and details the analytic procedures. Section 4 presents the results, covering construct dimensionality, path estimates, and moderation tests and Section 5 offers the discussion and conclusions. By situating our model in this evolving context, we make the study’s novelty explicit as both an extension of QVSL to shopping tourism and a set of new insights on behavioral outcomes and involvement.

2. Literature Review

2.1. Shopping Tourism

Shopping tourism refers to travel in which shopping serves as a primary motivation and a central experiential component (Choi et al., 2018; Lee & Choi, 2020; Pang & Sanders, 2025; Timothy, 2005). This niche tourism category not only emphasizes cross-border shopping, driven by currency fluctuations, enhanced product quality, and competitive price advantages but also captures the multidimensional experiential values associated with shopping (Baruca & Zolfagharian, 2013; Said et al., 2024). Although often used interchangeably, “tourist shopping” and “shopping tourism” differ based on contextual emphasis. Studies on “tourist shopping” have traditionally focused on souvenir purchases and designated shopping districts, such as tourist shopping villages (Murphy et al., 2011; Vega-Vázquez et al., 2017). Timothy (2005) characterizes tourist shopping as a supplementary activity that complements the primary travel purpose.

Notably, studies that primarily adopt a purchase-focused perspective emphasize expenditure (Alegre & Cladera, 2012; Bojanic, 2011). Research has shown that expenditure is shaped by various factors, including demographics, individual tourist characteristics, attitudes towards shopping experiences, and overall satisfaction (Alegre & Cladera, 2012; Bojanic, 2011; Chebat et al., 2014; Yu & Littrell, 2003). Given this complexity, our study emphasizes shopping as a primary driver and integral component of the overall travel experience.

2.2. Value and Value Dimensionality

Customer value, a cornerstone of competitive advantage, has been extensively studied as a key predictor of satisfaction and loyalty (Atulkar & Kesari, 2017; Gallarza et al., 2013; Huang et al., 2021). Despite this consensus, researchers define “value” in various ways. While traditionally viewed through an economic lens (Bolton & Lemon, 1999), value also captures non-monetary costs such as time, effort, and opportunity costs, thereby reflecting the holistic nature of consumer decision-making (Rintamäki et al., 2006; Zeithaml, 1988). Zeithaml (1988) defines value as a customer’s overall assessment of the utility of a product or service based on perceptions of what is received and what is given, including non-monetary costs (e.g., time, search efforts, and convenience) as well as tangible benefits. This definition has gained widespread acceptance in marketing and consumer behavior research (Albayrak et al., 2016; Choi et al., 2018; Cronin et al., 2000).

One of the most widely used lenses is the quality–value–satisfaction–loyalty (QVSL) chain, which posits that perceived quality shapes value, which in turn drives satisfaction and ultimately loyalty (Cronin et al., 2000). This logic has guided tourism and retail research and practice by offering a step-wise pathway for improving performance (Gallarza et al., 2013; Suhartanto et al., 2025). Numerous extensions examine parts of the chain, for example, refining the value → satisfaction → loyalty links by introducing mediators between satisfaction and loyalty (e.g., Granados et al., 2021), or enriching the antecedents of value with constructs such as motivation (Huang et al., 2021) and self-image congruity (Han et al., 2019).

In parallel, scholars emphasize that value is multidimensional rather than singular. Sheth et al. (1991) conceptualize distinct consumption values (e.g., functional, conditional, social, emotional, epistemic) that contribute independently to consumer choice. Empirically, mall-shopping studies likewise report multifaceted value structures (e.g., El-Adly & Eid, 2015). More recent perspectives go beyond static typologies: value co-creation within service systems (Vargo & Lusch, 2004), experiential value in interactive contexts (Yuan & Wu, 2008), and value-in-the-experience (VALEX), which situates value in the broader service environment where shopping occurs (Wong et al., 2024). Together, these streams motivate modeling value with finer granularity while acknowledging the role of the service context. Consistent with these emerging perspectives, we treat value as co-created within the destination retail ecosystem and measured at the experience level, which justifies our decomposition of hedonic and functional value and our inclusion of epistemic value as learning/novelty accruing in situ.

In this study, shopping value refers to tourists’ overall evaluation of shopping experiences at destinations based on their perceptions of what is received and what is given. Research highlights the multidimensional nature of shopping value, with hedonic and functional dimensions dominating discussions (Atulkar & Kesari, 2017; Badu-Baiden et al., 2024; Overby & Lee, 2006). Scholars argue that a two-dimensional framework—functional and hedonic values—effectively evaluates the shopping experience (Babin et al., 1994; Yüksel, 2007). However, emerging perspectives suggest that such a binary classification may overlook other critical dimensions. Recent studies emphasize a multidimensional approach to capturing the complexity of shopping experiences, incorporating epistemic, social, and self-gratification values (El-Adly & Eid, 2017; Rintamäki et al., 2006). For instance, Rintamäki et al. (2006) suggest that focusing exclusively on functional and hedonic values restricts exploring additional dimensions that contribute to a comprehensive understanding of the shopping experience—indeed, in the context of shopping malls, El-Adly and Eid (2015) identified eight customer-perceived value dimensions, including hedonic, self-gratification, utilitarian, epistemic, social interaction, spatial convenience, transaction, and time convenience. While these dimensions enrich our understanding of consumer behavior, further research is necessary to empirically validate how each dimension relates to tourist shopping constructs, such as satisfaction and loyalty. Moreover, in digitally mediated, cross-border shopping (e.g., in-destination online shopping, omnichannel search–purchase journeys), value formation depends on the interplay of physical and digital touchpoints, reinforcing the need to model experience quality as a proximal driver of value and outcomes.

Guided by the QVSL tradition, our conceptual model (Figure 1) posits that multidimensional shopping values, including hedonic (entertainment, exploration, escapism), functional, social, and epistemic values, and experience quality act as antecedents of shopping satisfaction (H1–H7). Satisfaction then predicts destination loyalty (H14) and the immediate behavioral outcomes of money spent and time spent at the destination (H15–H16). To capture value-driven attachment beyond satisfaction, we also include direct paths from value dimensions to loyalty (H8–H13). Finally, we propose shopping involvement as a moderator, conditioning (i) value/experience-quality → satisfaction and (ii) satisfaction → loyalty/(money and time) spending links (H17). Section 2.3, Section 2.4, Section 2.5, Section 2.6, Section 2.7, Section 2.8, Section 2.9, Section 2.10 and Section 2.11 develop these links into testable hypotheses (H1–H17). In sum, our integration of service-dominant logic, experiential value, and value-in-the-experience perspectives with QVSL clarifies why experience quality is modeled proximally and why immediate behavioral outcomes are theorized alongside attitudinal loyalty.

2.3. Hedonic Value and Shopping Satisfaction

The shift toward experiential retail settings characterized by immersive lighting, music, and interactive gaming zone has led scholars to explore hedonic shopping motivations more deeply (Arnold & Reynolds, 2003; El-Adly & Eid, 2015). Hedonic value reflects enjoyment and emotional fulfillment derived from shopping, encompassing sensory, imaginative, and emotional experiences (Babin et al., 1994; Jones et al., 2006). Studies suggest that hedonic value strongly influences shopping satisfaction and loyalty, as customers who seek enjoyment and fun are more likely to be satisfied and remain loyal to products, stores, and services (Rintamäki et al., 2006). Rather than a single factor, recent work treats hedonic value as multidimensional, with distinct dimensions that drive positive tourist behaviors (Arnold & Reynolds, 2003; Atulkar & Kesari, 2017; Kesari & Atulkar, 2016).

Our study focuses on three primary hedonic dimensions—entertainment, exploration, and escapism—as the key drivers of shopping satisfaction (Atulkar & Kesari, 2017; Çavuşoğlu et al., 2021). The shopping experience offers tourists fun, discovery, and a temporary escape from daily life. Entertainment is particularly influential, as retailers incorporate lighting, music, scents, and color schemes to create an engaging shopping environment (Arnold & Reynolds, 2003; Atulkar & Kesari, 2017). Exploration enhances the sense of adventure as tourists discover diverse products and engage in cultural learning activities (Kesari & Atulkar, 2016). Escapism allows tourists to step outside their daily routines and alleviate stress through immersive shopping experiences (Çavuşoğlu et al., 2021). Therefore, this study examines these three factors, including entertainment, exploration, and escapism as predictors of tourist shopping satisfaction and proposes the following hypotheses:

H1: 

Entertainment has a positive impact on shopping satisfaction.

H2: 

Exploration has a positive impact on shopping satisfaction.

H3: 

Escapism has a positive impact on shopping satisfaction.

2.4. Functional Value and Shopping Satisfaction

Functional value refers to the practical benefits of efficient shopping, such as task completion and time savings (Jones et al., 2006; Kim et al., 2014). Shopping is considered functionally valuable when viewed as a process that allows customers to quickly locate desired items or services and easily obtain relevant information (Babin et al., 1994). Efficiency in shopping enhances customer satisfaction by freeing time for leisure or other productive activities (Chung, 2015). Extensive research in shopping and tourism contexts has established that functional value is positively associated with customer satisfaction (Kesari & Atulkar, 2016; Sirakaya-Turk et al., 2015).

However, when hedonic and functional values are examined together, results vary across shopping environments. For example, Bakırtaş et al. (2015) reported that both utilitarian and hedonic values positively affect satisfaction and behavioral intentions, but the hedonic effect was stronger, likely reflecting their context (apparel shoppers in a single Turkish mall) where experiential cues are salient. In other studies, shopping value is modeled as an aggregate multidimensional construct, which confirms a positive overall effect on satisfaction but obscures the separate contributions of hedonic and utilitarian dimensions (e.g., Vega-Vázquez et al., 2017). In contrast, our study estimates hedonic and functional values separately within one model and further specifies three hedonic facets (entertainment, exploration, escapism), allowing a clearer test of their distinct links to satisfaction in a cross-border shopping context. These mixed results constitute an unresolved theoretical tension about whether functional value or specific hedonic facets more strongly predict satisfaction once experience quality and involvement are accounted for, particularly in cross-border, digitally mediated, post-COVID shopping contexts. To address this tension, we test hedonic subdimensions and functional value side-by-side within one model (with experience quality modeled proximally), expecting functional–performance to be at least as strong as any single hedonic facet in predicting shopping satisfaction among international tourists. Accordingly, we propose:

H4: 

Functional value has a positive impact on shopping satisfaction.

2.5. Social Value and Shopping Satisfaction

Social value refers to the utility customers perceive through their associations with social groups (Sheth et al., 1991). Shopping fosters social connections and interactions with friends, family, and like-minded individuals (Arnold & Reynolds, 2003). These social interactions not only facilitate the exchange of information but also contribute to a sense of belonging and shared experience. By engaging in social exchanges, shoppers gain exposure to new trends and benefit from shared experiences, enhancing overall satisfaction (Kesari & Atulkar, 2016). Therefore, hypothesis 5 is proposed as follows:

H5: 

Social value has a positive impact on shopping satisfaction.

2.6. Epistemic Value and Shopping Satisfaction

Epistemic value captures the utility derived from novelty and curiosity, enriching the shopping experience through knowledge and discovery (Albayrak et al., 2016; Atulkar & Kesari, 2017; El-Adly & Eid, 2015). This dimension is particularly relevant in tourism, where shopping extends beyond acquiring goods to learning about local culture and traditions. For instance, destination-specific experiences offer insights into local craftsmanship and traditions, thereby creating engaging and memorable shopping moment (El-Adly & Eid, 2015). Retail storytelling enhances epistemic value by linking products to their history and significance, which satisfies tourists’ curiosity and desire for discovery and, in turn, generates positive emotions and memorable experiences (Choi et al., 2018; Kesari & Atulkar, 2016). To evaluate the influence of epistemic value on shopping satisfaction, hypothesis 6 is proposed as follows:

H6: 

Epistemic value has a positive impact on shopping satisfaction.

2.7. Experience Quality and Shopping Satisfaction

Tourists seek more than just products and services; they desire engaging and memorable experiences (Sangpikul, 2018). Unlike service quality, experience quality provides a subjective, holistic assessment encompassing provider attributes and visitor perceptions (Fernandes & Cruz, 2016). It considers the attributes offered by the service provider and those brought by the visitor, focusing on an internal evaluation of the entire experience (C. F. Chen & Chen, 2010). Experience quality is “the psychological outcome resulting from customer participation in tourism activities” (C. F. Chen & Chen, 2010, p. 30). In the context of this study, experience quality refers to the psychological outcome derived from tourists’ participation in shopping for products or services.

Research shows that experience quality positively impacts tourist satisfaction and, in some cases, loyalty, directly (Fernandes & Cruz, 2016) or indirectly through mediating factors (C. F. Chen & Chen, 2010). For instance, Fernandes and Cruz (2016) demonstrated that experience quality enhances tourist satisfaction and loyalty, even in niche contexts like wine tourism. While the direct impact on satisfaction is well established, some studies suggest that experience quality’s influence on loyalty may be mediated by other factors, such as perceived value and satisfaction (Cronin et al., 2000). Therefore, this study examines the relationship between shopping experience quality and satisfaction, proposing the following hypothesis:

H7: 

Shopping experience quality is positively related to shopping satisfaction.

2.8. Shopping Values and Destination Loyalty

Destination loyalty refers to tourists’ repeated visits to the same destination and their intention to recommend it to family and friends (Oppermann, 2000; Sangpikul, 2018). Previous shopping studies have identified a direct relationship between value and loyalty, including revisit intention and word-of-mouth (WOM) (Albayrak et al., 2016; Chung, 2015). While some studies, such as Chung (2015), demonstrate that hedonic and functional values influence revisit intentions positively, others, like Sirakaya-Turk et al. (2015), suggest that value may not directly translate into loyalty without considering mediating factors, featuring the complexity of the relationship. This inconsistency highlights the need to further explore how multidimensional shopping values influence loyalty in tourism contexts.

Loyalty can be increased when driven by hedonic experiences like entertainment, exploration, and escapism, which foster enjoyable moments and strengthen emotional bonds with the destination (Atulkar & Kesari, 2017; Arnold & Reynolds, 2003). Meanwhile, functional value strengthens loyalty via time and goal achievement effectiveness under shopping activities; social value encourages loyalty via the experience shared and narrated by group members. El-Adly & Eid (2015) further contend that epistemic value drives loyalty by cultivating curiosity and facilitating intercultural stimulation. Therefore, this study proposes hypotheses 8 to 13 as follows:

H8: 

Entertainment positively impacts destination loyalty, including revisit intention and WOM.

H9: 

Exploration positively impacts destination loyalty, including revisit intention and WOM.

H10: 

Escapism positively impacts destination loyalty, including revisit intention and WOM.

H11: 

Functional value positively impacts destination loyalty, including revisit intention and WOM.

H12: 

Social value positively impacts destination loyalty, including revisit intention and WOM.

H13: 

Epistemic value positively impacts destination loyalty, including revisit intention and WOM.

2.9. Shopping Satisfaction and Destination Loyalty

Extensive research has established that satisfaction is a significant predictor of loyalty in retail shopping (Atulkar & Kesari, 2017), the service industry (Cronin et al., 2000), and tourism (Vega-Vázquez et al., 2017). Given the diversity of tourist motivations, especially among international travelers, loyalty is better captured through behaviors that reflect overall destination attachment rather than sustained engagement with the destination (McKercher & Guillet, 2011; Oppermann, 2000; Sangpikul, 2018). Instead, satisfaction often drives loyalty through broader behaviors, such as word-of-mouth (WOM) and intention to recommend, providing stronger indicators of long-term destination engagement (Chang et al., 2025; C. F. Chen & Tsai, 2008; Smolčić Jurdana & Soldić Frleta, 2017).

Some studies have used tourist expenditure as an outcome variable of tourist satisfaction (Smolčić Jurdana & Soldić Frleta, 2017), reinforcing that shopping can be a motivator for tourists to revisit due to its leisure and experiential elements (Murphy et al., 2011; Tsang et al., 2014). Sirakaya-Turk et al. (2015) found that shopping satisfaction contributes to destination loyalty, including destination patronage intention and word-of-mouth. In essence, satisfied tourists demonstrate stronger attachment to the destination by both returning and actively promoting it to others. Accordingly, hypothesis 14 is proposed as follows:

H14: 

Shopping satisfaction positively impacts destination loyalty, including revisiting intention and word-of-mouth (WOM).

2.10. Shopping Satisfaction and Money and Time Spent

While loyalty is often regarded as a primary outcome of satisfaction, more immediate behavioral outcomes offer actionable insights for destination marketers by directly linking satisfaction to observable consumer actions. Yeung et al. (2013) found that aggregate customer satisfaction significantly influences consumer expenditure at the national level in Europe, demonstrating that heightened satisfaction can drive increased spending on a wide range of products and services. In the tourism context, Gogoi (2013) found that satisfaction increases monetary expenditure and encourages tourists to devote more time to exploring shopping environments, thereby enhancing their overall experience. Consequently, this study posits that satisfaction exerts direct, measurable effects on immediate consumer behaviors—specifically, the amounts of money and time spent at the destination—leading to the following hypotheses:

H15: 

Shopping satisfaction positively impacts money spent at the destination.

H16: 

Shopping satisfaction positively impacts time spent at the destination.

2.11. Moderating Effect of Shopping Involvement

Customer involvement significantly influences decision-making and purchasing behavior (C. F. Chen & Tsai, 2008; Sohn & Lee, 2017). Different levels of involvement lead to distinct shopping behaviors: highly involved shoppers actively seek opinions from others, rely on non-personal sources, shop more frequently, spend more, and demonstrate unique shopping behaviors (Kinley et al., 2010). Conversely, low-involvement customers make quick decisions with minimal information processing and effort and are less likely to be satisfied or make recommendations (Josiam et al., 2005). Although previous studies report mixed findings regarding the moderating role of involvement, shopping involvement will likely moderate the relationship between values, satisfaction, and loyalty. For instance, highly involved customers prioritize functional and epistemic values, while less involved customers may focus on hedonic aspects (C. F. Chen & Tsai, 2008; Sohn & Lee, 2017).

This study acknowledges that consumer behavior varies with involvement levels and explores involvement’s moderating role in the proposed relationships. Rather than assuming a definitive moderating effect, the study tests whether involvement alters the strength or direction of the relationships among shopping values (i.e., entertainment, exploration, escapism, functional, epistemic, and social values), experience quality, satisfaction, loyalty, and immediate spending behaviors (money and time spent). Although involvement is hypothesized to moderate these relationships, this moderation is not presumed across all linkages. The examined relationships include shopping values (i.e., entertainment, exploration, escapism, functional, epistemic, and social values) and satisfaction (H1 to H6), experience quality and satisfaction (H7), shopping values and loyalty (H8 to H13), satisfaction and loyalty (H14), as well as satisfaction and money spent (H15) and satisfaction and time spent (H16). Therefore, we propose the following hypothesis:

H17: 

Shopping involvement moderates the relationships within the proposed model.

Figure 1. Initial conceptual model.

Figure 1. Initial conceptual model.

3. Methodology

3.1. Research Design

We designed a structured survey containing two main sections: measurement items for constructs and participants’ demographics. Entertainment (4 items), exploration (5 items), escapism (5 items), social value (4 items), and epistemic value (4 items) were sourced from previous studies (Arnold & Reynolds, 2003; Atulkar & Kesari, 2017; El-Adly & Eid, 2015). Similarly, functional value (9 items) (Choi et al., 2018), experience quality (5 items) (Fernandes & Cruz, 2016), involvement (4 items) (Olsen, 2007), and shopping satisfaction (5 items) and destination loyalty (7 items) (Sirakaya-Turk et al., 2015) were adapted from prior research. We minimally modified item wording to fit the Japan trip-shopping context. To balance content coverage with respondent burden, we selected 4–5 items for most constructs, with two planned exceptions: functional value (anticipating subfacets) and destination loyalty (initially modeled with revisit intention and WOM items). The final survey included 52 items for the constructs, measured on a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree).

Fully independent travelers (FITs) were chosen for their flexibility to engage in diverse shopping and leisure activities (Hsiao & Chuang, 2015). Screening targeted mainland Chinese tourists aged 18+ who had visited Japan within the past 12 months and ensured: (i) a minimum two-night stay in paid accommodations, (ii) leisure as the primary trip purpose, and (iii) documented shopping (reported spend and at least one purchase such as clothing, cosmetics, jewelry, or souvenirs).

3.2. Data Collection and Analysis

The questionnaire was pre-tested to ensure clarity. Data were collected through self-administered online questionnaires managed by Rakuten Insight, a leading market research platform that facilitates access to a large panel of qualified respondents from mainland China. Sample size requirements were determined using Cochran’s (1977) formula and a path analysis guideline recommending 20 participants per parameter, targeting 260 to 386 respondents for adequate statistical power. A multi-group analysis was performed to evaluate the moderating effect of involvement.

Both procedural and statistical remedies were employed to address potential common method bias (CMB). Procedurally, predictor and outcome variables were measured separately using distinct scales, and respondents were assured of the anonymity and confidentiality of their responses. Reverse-worded items were included to reduce response bias, and a pilot test was conducted to refine the survey design. Statistically, Harman’s Single Factor Test was performed, revealing that a single factor accounted for 41.9% of the variance, below the 50% threshold, indicating that common method bias is not a significant concern. Although Harman’s test is a coarse diagnostic, taken together with our procedural remedies and the EFA-supported multi-factor measurement structure, it suggests CMB is unlikely to drive the results.

4. Results

4.1. Descriptive Analysis

Appendix A summarizes respondent demographics and trip profiles. The sample was roughly gender-balanced (53% female), predominantly aged 21–40 (72%), highly educated (75% bachelor’s), and mostly full-time employed (95%). Most were married/partnered (83%). Incomes clustered between ¥100,000–¥399,999 (73%), with 23% above ¥400,000. Travel-wise, 84% had visited Japan 1–3 times, 51% stayed ≥ 5 nights, and 60% reported shopping from a prepared list.

4.2. Exploratory Factor Analysis (EFA)

Separate EFAs were conducted for each core construct—shopping values, experience quality, satisfaction, and destination loyalty. Appendix B summarizes the factor loadings, eigenvalues, percentage of variance explained, and Cronbach’s alpha reliability. Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) test confirm sample adequacy for principal component analysis (PCA).

EFA on 31 shopping-value items retained 22, explaining 69.08% of the variance; nine were removed, including two exploration items, two escapism items, all four social-value items, and one functional-value item (see Appendix B). PCA with varimax rotation excluded social value items due to low factor loadings (<0.5), and functional value split into two factors: performance (quality and reliability) and money (economic benefit). Entertainment emphasizes enjoyment and pleasure, while epistemic value reflects knowledge and novelty. Escapism captures psychological relief and escape, and exploration focuses on adventure.

EFAs for experience quality (4 of 5 items retained), shopping satisfaction (all 5 items retained), and destination loyalty (all 7 items retained) revealed single-factor solutions. Experience quality emphasizes employee expertise and a positive environment. Shopping satisfaction captures positive attitudes and expectations, while destination loyalty indicates revisit intention and word-of-mouth recommendations. For all listed constructs, Cronbach’s alpha reliability coefficients ranged from 0.739 to 0.903, exceeding the threshold of 0.70 (Hair et al., 2014), indicating good internal consistency. Accordingly, we refined the hypothesized relationships to reflect these empirical adjustments. In the revised framework (Figure 2), functional value is conceptualized as two distinct yet complementary dimensions (performance and money), each expected to enhance both shopping satisfaction (revised H4 and H5) and destination loyalty (revised H11 and H12). Specifically, tourists who perceive high product quality and reliability (performance) or favorable price–value ratios (money) are anticipated to report stronger satisfaction with their shopping experiences and a greater tendency to revisit or recommend the destination. This adjustment maintains the theoretical integrity of the value–satisfaction–loyalty chain.

H4: 

Functional value for performance has a positive impact on shopping satisfaction.

H5: 

Functional value for money has a positive impact on shopping satisfaction.

H11: 

Functional value for performance has a positive impact on destination loyalty.

H12: 

Functional value for money has a positive impact on destination loyalty.

In sum, the retained structure shows tourists evaluate shopping value across five facets (ENT, EXP, ESC, FVP, FVM) plus EPV and EQ. Functional value empirically splits into performance and money facets, whereas social value lacks coherence in this context.

4.3. Path Analysis and Hypothesis Testing

To examine the causal relationships between variables, path analysis was performed using Amos 25.0, enabling simultaneous estimation of parameters (Mishra & Min, 2010). Composite means for each variable were created in SPSS 26 based on the EFA results to reduce multicollinearity and manage error variance among indicators. This approach is commonly used in path analysis involving reflective constructs, particularly when the sample-to-parameter ratio is tight or when aiming for parsimony to simplify the model structure, consistent with prior procedures (e.g., Cole & Chancellor, 2009). Given our focus on predictive relationships among validated composite constructs, and with reliability and validity confirmed through EFA and CFA, path analysis was deemed statistically robust and appropriate. While SEM or PLS-SEM could also be applied, path analysis aligns with our theoretical goals and sample size, and robustness checks supported the stability of the results.

We assessed univariate normality for all composite indicators (ENT, EXP, ESC, FVP, FVM, EPV, EQ, SAT, LOY). Skewness ranged from −1.19 to −0.50 and kurtosis from 0.09 to 2.55, consistent with approximate normality. Shapiro–Wilk tests were significant due to the large sample (N = 413), histograms and P–P plots showed approximately normal, unimodal distributions. Boxplots indicated no values outside the 1–7 Likert range and no extreme outliers; all cases were retained. For the path analysis, model fit indices indicated a satisfactory fit: chi-square/df ratio = 1.781 (X² = 32.055, df = 18), RMSEA = 0.044, NFI = 0.956, CFI = 0.995, GFI = 0.986, and AGFI = 0.950 (Hair et al., 2014; Hu & Bentler, 1999).

The path analysis results (see

Table 1. Path analysis results.

Path	Standardized Estimate	Results
H1: ENT → SAT	0.082 **	Supported (+)
H2: EXP → SAT	−0.003	Not Supported
H3: ESC → SAT	0.028	Not Supported
H4: FVP → SAT	0.278 ***	Supported (+)
H5: FVM → SAT	0.144 ***	Supported (+)
H6: EPV → SAT	0.209 ***	Supported (+)
H7: EQ → SAT	0.259 ***	Supported (+)
H8: ENT → LOY	0.059	Not Supported
H9: EXP → LOY	0.034	Not Supported
H10: ESC → LOY	0.014	Not Supported
H11: FVP → LOY	0.202 ***	Supported (+)
H12: FVM → LOY	0.194 ***	Supported (+)
H13: EPV → LOY	0.140 **	Supported (+)
H14: SAT → LOY	0.333 ***	Supported (+)
H15: SAT → MON	0.158 **	Supported (+)
H16: SAT → TIM	0.132 **	Supported (+)

Notes: *** p < 0.001, ** p < 0.05. ENT = entertainment; EXP = exploration; ESC = escapism; FVP = functional value for performance; FVM = functional value for money; EPV = epistemic value; EQ = experience quality; SAT = satisfaction; LOY = loyalty; MON = money spent; TIM = time spent.

and Figure 3) show the path coefficients (β) and squared multiple correlations (R²). The R² values represent the variance explained by independent variables for each dependent variable, while the path coefficients indicate the relative contribution of each independent variable to a dependent variable. Of the 16 hypotheses, eleven showed significant positive effects (p < 0.05 and p < 0.001). The significant paths include:

• Shopping satisfaction predictors: entertainment (H1), functional value for performance (H4), functional value for money (H5), epistemic value (H6), and experience quality (H7).
• Destination loyalty predictors: functional value for performance (H11), functional value for money (H12), epistemic value (H13), and satisfaction (H14).
• Shopping impact: satisfaction significantly influenced money spent (H15) and time spent (H16).

The hypothesized model explained 75.6% shopping satisfaction (R² = 0.756). Functional value for performance emerged as the strongest predictor (β = 0.278), suggesting that consistent quality and performance significantly enhance shopping satisfaction. This was followed by experience quality (β = 0.259), epistemic value (β = 0.209), functional value for money (β = 0.144), and entertainment (β = 0.082). Escapism and exploration were not significant predictors. Thus, H1, H4, H5, H6, and H7 were supported, while H2 and H3 were not.

The model explains 71.9% of the variance (R² = 0.719) for destination loyalty, reflecting strong predictive power. Shopping satisfaction was the most influential predictor (β = 0.333), indicating that higher satisfaction promotes revisit intentions and positive recommendations. This was followed by functional value for performance (β = 0.202), functional value for money (β = 0.194), and epistemic value (β = 0.140). Entertainment, exploration, and escapism had no significant effect on destination loyalty. Therefore, H11, H12, H13, and H14 were supported, while H8, H9, and H10 were not. Additionally, the path coefficients (β) revealed that shopping satisfaction had a significant impact on both money spent (β = 0.158) and time spent (β = 0.132), confirming H15 and H16. This suggests that higher satisfaction correlates with increased spending and more time allocated to shopping at the destination.

Overall, satisfaction is driven mainly by functional value (performance, money), experience quality, epistemic value, and entertainment; in turn, satisfaction predicts destination loyalty and money/time spent, while exploration and escapism are negligible in this setting. Loyalty is also directly predicted by both functional facets and epistemic value.

4.4. Moderation Effect of Involvement

The moderating effects of involvement (H17) were tested using multi-group analysis. The sample was divided into high-involvement (N = 236) and low-involvement (N = 177) groups using a median split 5.80. Separate models were developed for each group: a constrained model, where the path estimate was fixed to 1, and an unconstrained model, where the path was freely estimated (Afthanorhan et al., 2014). Chi-square differences (ΔX²) exceeding 3.84 (p < 0.05) between constrained and unconstrained models indicated significant moderating effect of involvement (Hair et al., 2014).

As shown in

Table 2. Moderating effect of involvement (N = 413).

Model	Path Coefficients		X2	d.f.	ΔX2	Δd.f.
Unconstrained model			69.431	36		1
ENT → SAT	High INV	0.094 **	70.381	37	0.95	1
	Low INV	0.058 **
EXP → SAT	High INV	0.046	71.488	37	2.056	1
	Low INV	−0.054
ESC → SAT	High INV	0.013	70.377	37	0.331	1
	Low INV	0.092
FVP → SAT	High INV	0.206 ***	72.75	37	3.318	1
	Low INV	0.326 ***
FVM → SAT	High INV	0.103	70.095	37	0.663	1
	Low INV	0.150 **
EPV → SAT	High INV	0.196 ***	69.434	37	0.003	1
	Low INV	0.169 **
EQ → SAT	High INV	0.339 ***	69.461	37	0.029	1
	Low INV	0.250 ***
ENT → LOY	High INV	0.036	70.323	37	0.891	1
	Low INV	0.091
EXP → LOY	High INV	−0.009	70.392	37	0.961	1
	Low INV	0.054
ESC → LOY	High INV	0.027	69.46	37	0.029	1
	Low INV	0.002
FVP → LOY	High INV	0.145 **	71.102	37	1.671	1
	Low INV	0.236 ***
FVM → LOY	High INV	0.178 **	70.323	37	0.853	1
	Low INV	0.210 **
EPV → LOY	High INV	0.168 **	69.98	37	0.549	1
	Low INV	0.069
SAT → LOY	High INV	0.325 ***	69.461	37	0.03	1
	Low INV	0.294 ***
SAT → MON	High INV	0.159 **	74.699	37	5.268	1
	Low INV	−0.029
SAT → TIM	High INV	−0.020	70.208	37	0.777	1
	Low INV	0.105

Notes: *** p < 0.001, ** p < 0.05, X² = Chi-square, d.f. = degree of freedom. INV = involvement; ENT = entertainment; EXP = exploration; ESC = escapism; FVP = functional value for performance; FVM = functional value for money; EPV = epistemic value; EQ = experience quality; SAT = satisfaction; LOY = loyalty; MON = money spent; TIM = time spent. Highlighted rows indicate paths where the moderating effect of involvement is significant.

, the chi-square difference between the constrained and unconstrained models was significant only for the path between satisfaction and money spent (X² = 74.699, ΔX² = 5.268, p < 0.05). For high-involvement tourists, satisfaction positively and significantly influenced money spent (β = 0.159, p < 0.05), while low-involvement tourists showed no significant relationship (β = −0.029, p > 0.05). These findings suggest that satisfaction influences money spent more strongly for high-involvement tourists, suggesting they are more likely to increase spending based on their satisfaction levels. No significant moderating effects were observed for other paths, as detailed in Table 2, highlighting the limited role of involvement as a moderator. These results suggest that H17 is only partially supported, as shopping involvement moderates the relationship between satisfaction and money spent but does not affect other paths in the proposed model.

5. Discussion and Conclusions

5.1. Discussion

This study demonstrates that multidimensional shopping values and experience quality are key drivers of shopping satisfaction and destination loyalty, with satisfaction also predicting money and time spent. Exploratory factor analysis refined the model by splitting functional value into performance (FVP) and money (FVM). Among the six remaining shopping values, entertainment, epistemic value, and both functional values significantly influenced satisfaction, partially aligning with past research (Atulkar & Kesari, 2017; Sirakaya-Turk et al., 2015). For loyalty, functional and epistemic values emerged as significant drivers, while satisfaction remained the strongest predictor. Additionally, involvement moderated the link between satisfaction and money spent, emphasizing its role in high-involvement tourists’ spending behavior. Although social value often predicts satisfaction and loyalty in domestic retail settings with co-shopping (e.g., hypermarkets, malls) (Atulkar & Kesari, 2017; Moharana & Pradhan, 2020), our cross-border context likely attenuates its salience. In international trips, shopping activities are more individual and task-focused, with language/payment frictions and fewer opportunities for shared interaction; consistent with Arnold and Reynolds’ (2003) view of social shopping as enjoying time with family/friends and bonding with others while shopping, such sociality may be less prevalent abroad, helping explain why a distinct social-value factor did not emerge.

Prior studies suggest hedonic value often predicts satisfaction (Kesari & Atulkar, 2016). However, our analysis diverged from Atulkar and Kesari (2017), likely because international shopping tourism emphasizes goal-directed behavior over leisure shopping. Their study focused on Indian hypermarkets, where shopping provides adventure and an escape from daily life. In contrast, our findings highlight tourists’ prioritization of excitement, enjoyment, and curated shopping environments to meet practical travel goals. In our study of mainland Chinese tourists shopping in Japan, trips are typically instrumental and planned, targeting specific brands and price/tax advantages, navigating refund procedures, and operating under tight itineraries with language/payment frictions. These conditions privilege diagnostic cues (quality, price) and discourage open-ended browsing or risk-taking, so the exploration facet (novelty seeking, adventurous wandering) contributes little to satisfaction. Likewise, escapism, using shopping to forget problems or seek emotional release, matters less when purchases are purposeful and bounded by budgets, luggage/customs limits, and time. Consistent with Kesari and Atulkar (2016), functional value remained a strong predictor of satisfaction, reinforcing tourists’ purposeful, goal-driven shopping, such as arriving in Japan with specific shopping lists.

When examining the value-loyalty relationship, our findings align with previous studies highlighting mixed effects of hedonic and functional values on loyalty (Albayrak et al., 2016; Chung, 2015; Overby & Lee, 2006; Sirakaya-Turk et al., 2015). For example, while Chung (2015) found a direct positive impact of hedonic value on airport shopping patronage intention, our approach dissected these dimensions to reveal nuanced effects. Similarly, Albayrak et al. (2016) found that enjoyment and escapism positively influenced loyalty, but functional value had the strongest effect, with no mediating factors.

Our findings partially align with Sirakaya-Turk et al. (2015), where satisfaction mediated the effect of hedonic value on loyalty, rendering it insignificant, while functional value remained significant, though weaker than satisfaction. This suggests that international shopping tourists prioritize utilitarian goals over hedonic pleasures. Their focus on efficiency and product quality may explain why hedonic aspects like enjoying the environment or seeking adventure have less impact on loyalty. In contrast to Albayrak et al. (2016), where local retail settings foster loyalty through pleasure and social experiences, international tourists emphasize product quality and reliability over leisure or escapism.

Both functional and epistemic values significantly predict loyalty, emphasizing practical and learning-oriented aspects of shopping tourism. Prior studies (Albayrak et al., 2016; Chung, 2015) identify functional value as a key loyalty driver; our findings show that both functional value for performance and money contribute independently. Tourists in Japan value quality, reliability, and economic benefits, reinforcing their intent to revisit or recommend Japan. Similarly, epistemic value—interest in new trends and cultural insights—strongly impacted loyalty, aligning with research on novelty enhancing destination appeal (Toyama & Yamada, 2012). Tourists seeking trends, innovations, or distinctive Japanese styles, such as fashion or décor ideas, exhibited stronger loyalty.

Unexpectedly, no significant differences emerged between high- and low-involvement tourists in the effects of shopping values and experience quality on satisfaction or loyalty. This contrasts with C. F. Chen and Tsai’s (2008) TV-shopping setting and likely reflects contextual and respondent differences. In our case, involvement seems to act mainly pre-purchase, as a motivation/priority that prompts information search and planning before travel, rather than altering in-store value appraisal. Put differently, even though highly involved consumers are more inclined to seek external information and evaluate alternatives (Kinley et al., 2010), once in the destination they assess what is received versus given in similar ways; both groups convert those value cues into satisfaction to a comparable degree. The lack of moderation on satisfaction to loyalty also fits a level mismatch: our loyalty is destination-level and influenced by broader attributes (e.g., scenery, safety, transport; J. S. Chen & Gursoy, 2001; Hallak et al., 2018), whereas shopping involvement is activity-specific. Two contextual factors may further mute differences: the sample skews young, educated, and affluent, who tend to plan purchases, and tight travel schedules with shared price sensitivity for popular items (e.g., cosmetics, food) limit divergent in-store behavior.

However, involvement did moderate the relationship between satisfaction and money spent, with high-involvement tourists spending more. Satisfied high-involvement tourists, having researched extensively, prioritize quality and are more likely to make impulse purchases or respond to promotions during their trips. In contrast, low-involvement tourists, though satisfied, generally spend less. This finding highlights the need to account for involvement as a contextual variable, particularly when examining spending behavior in tourism.

5.2. Theoretical Contributions

Despite growing attention to shopping tourism (e.g., Jin et al., 2017; Said et al., 2024), the complexity of tourist shopping behavior remains underexplored. By integrating and partially applying the QVSL framework, this study broadens the theoretical lens to the shopping-tourism context (Kim et al., 2014; Murphy et al., 2011) and provides a more nuanced understanding of shopping satisfaction (Kang & Park-Poaps, 2011) and destination loyalty (Sirakaya-Turk et al., 2015). We specify a multidimensional value space, including hedonic subdimensions (entertainment, exploration, escapism), functional value (performance and money), social value, and epistemic value, rather than the unidimensional or two-factor (hedonic/functional) treatments often used in QVSL applications (e.g., Chung, 2015; Granados et al., 2021). We also incorporate experience quality as a proximal driver in the QVSL chain. Although social value was later excluded and exploration/escapism did not predict satisfaction in our setting, functional (performance, money), epistemic, and entertainment emerged as central antecedents, reinforcing the importance of multidimensional value for explaining shopping satisfaction and loyalty. In addition, we extend typical QVSL outcomes by linking satisfaction to immediate behaviors (money and time spent) and examine involvement as a contextual moderator. These elements constitute our “framework extensions,” primarily advancing shopping-tourism theory by adapting QVSL to tourist shopping and by connecting shopping evaluations to on-site economic outcomes.

Our findings highlight that multidimensional approaches provide greater explanatory power, particularly emphasizing functional values, experience quality, epistemic value, and entertainment as key drivers of satisfaction. Additionally, we confirm a direct relationship between these value dimensions (functional values and epistemic value) and destination loyalty, with functional value for performance emerging as a powerful predictor of loyalty among mainland Chinese shopping overseas. However, when developing loyalty programs, note that the salience of functional value for Chinese outbound shoppers can vary by shopping type (e.g., luxury; Hung et al., 2021), and cross-cultural differences mean other visitor segments may prioritize different destination attributes or images (Sun et al., 2023). The differentiated effects of functional value (particularly performance) and the loyalty-relevant role of epistemic value constitute “new insights” that speak to broader consumer-behavior debates about which value components most strongly drive loyalty beyond satisfaction.

While this study’s theoretical framework builds on established models, we extend it by incorporating immediate behavioral outcomes, specifically money and time spent, an area largely overlooked in shopping-tourism research (Lin & Chen, 2013). This modest extension invites a reconsideration of the assumption that loyalty is the sole indicator of shopping success, specifying an attitudinal-to-behavioral mechanism from satisfaction to spending/time. We also examine shopping involvement as a contextual moderator; the only significant moderation occurs on the satisfaction → money-spent link. This limited moderation refines theory by challenging the common presumption of uniformly strong involvement effects across QVSL links, suggesting that, in international shopping contexts, spending is largely goal-directed and product-focused, consistent with utilitarian shopping research (Badu-Baiden et al., 2024; Chung, 2015; Lin & Chen, 2013). High-involvement tourists convert satisfaction into higher expenditures, reflecting pre-trip research and a strong quality focus (Choi et al., 2018); whereas low-involvement tourists spend less even when satisfied. Notably, existing research suggests that other tourist characteristics, such as age, family size, and income, may influence spending behavior (Alegre & Cladera, 2012; Bojanic, 2011). Future research could explore these additional factors to enhance the explanatory power of the existing model and develop a more comprehensive view of spending drivers in shopping tourism contexts.

5.3. Practical Implications

We translate the results into actionable guidance for DMOs and retailers focused on four levers: (1) strengthening value cues that matter most (functional—performance and money, plus epistemic and entertainment values), (2) differentiating messages and merchandising for FVP vs. FVM, (3) elevating experience quality (staff expertise, respect, consistency), and (4) using involvement-sensitive spend strategies (convert satisfied, high-involvement tourists on-site). Tourists find satisfaction not only in high-quality products and competitive pricing but also in engaging and informative shopping environments. Retailers can reinforce functional value by ensuring consistent quality, competitive discounts, and tax-free shopping, as seen in Japan’s Isetan and Takashimaya. For mainland Chinese tourists, performance cues can be strengthened with authenticity guarantees (e.g., anti-counterfeit seals), Mandarin product/return information, and staffed service desks with Mandarin support for warranty/repairs. Money value can be reinforced with RMB-denominated price displays (showing ¥ alongside local currency), tax-free prices shown net of refund, instant Alipay/WeChat Pay rebates or coupons, and QR codes that walk shoppers through tax-refund steps. Use side-by-side comparison cards and ‘best value’ tags to help Chinese visitors quickly weigh performance versus price, and feature limited-time deals prominently. To enhance epistemic value, shops could integrate cultural storytelling through live demonstrations of traditional crafts like kimonos or pottery. Pair products with Mandarin provenance cards and QR codes that open WeChat Mini Programs or RED (Xiaohongshu) content featuring short maker videos, step-by-step usage tips, and/or user reviews (with deeper Q&A on Zhihu/Bilibili as needed), enabling Chinese visitors to access trusted information quickly and feel confident in their purchase. Managers should tailor services across various retail formats, from luxury boutiques to street markets, to meet diverse tourist preferences.

Upscale retailers, such as department stores, should prioritize functional value and experience quality through consistent product quality and superior service. Flagship stores like Isetan and Takashimaya cater to tourists with detailed product information and streamlined tax-free services. Training programs can equip sales teams with bilingual skills or translation tools to engage foreign tourists effectively. Sales associates can enhance epistemic value by offering style advice, color coordination tips, and trend updates, using resources like Vogue and InStyle. Managers should also create a welcoming environment with well-chosen décor, soft lighting, scents, and background music to enrich the shopping experience.

Small-scale retailers (e.g., independent cosmetic stores, local souvenir vendors, and family-owned medicine shops) should implement targeted cost-leadership strategies by offering limited-time bundle deals, loyalty discounts, and digital coupons distributed via localized social media channels (e.g., WeChat). Additionally, they should use localized digital signage and pop-up promotions during peak tourist seasons to drive impulse purchases.

Medium-sized retailers are advised to adopt a hybrid strategy combining cost-efficiency and enhanced customer engagement. This can include developing tailored mobile apps for real-time promotions, deploying personalized digital marketing campaigns, and setting up interactive in-store displays that showcase unique product attributes and local cultural heritage, creating a distinct competitive advantage in the international shopping tourism market.

Value and satisfaction are key contributors to destination loyalty. While attracting new tourists matters, retaining them is often more cost-effective. Retailer-DMO partnerships are crucial for loyalty programs tailored to foreign tourists. Retailers could use WeChat applets for product details and membership registration via QR codes. Memberships could offer points redeemable for cash, coupons, or gifts, enhancing shopping incentives. DMOs could collaborate with Chinese OTAs like Ctrip, Fliggy, and MaFengWo to allow point transfers for future hotel stays, dining, or travel purchases. To position shopping as a core destination feature, DMOs should promote shopping environments, tax return policies, and sales events through TV and social media. Providing brochures with QR codes lets tourists preview products before their trip, integrating shopping into travel planning.

Understanding shopping involvement helps DMOs and retailers tailor marketing strategies and enhance competitive advantages. High-involvement tourists prioritize detailed product information and quality shopping experiences. Retailers can cater to this by developing websites, apps, or WeChat applets showcasing product details, purchasing options, and user reviews. Marketing materials should highlight unique brand qualities, product differentiation, and satisfaction guarantees to appeal to these informed shoppers. In-store staff should address tourist queries, explain product differences, and provide tailored recommendations. Improving product tangibility via samples, demonstrations, and side-by-side comparisons can further align with high-involvement tourists’ expectations. Managers should also ensure robust post-purchase support, such as return policies or follow-up services, to build trust and satisfaction, ultimately driving higher spending and loyalty at the destination.

While interested in purchasing, low-involvement consumers typically avoid seeking detailed product information or multiple opinions, favoring spontaneous or low-relevance purchases (Josiam et al., 2005; Kinley et al., 2010). To effectively engage this segment, sales staff should quickly identify low-involvement tourists and recommend easily recognizable “star” products as bestsellers or limited-edition items that require minimal explanation. Strategic placement of travel-sized goods, like hand creams or lip balms, at checkout counters with appealing discounts or bundle deals can further encourage impulse purchases. Clear and concise signage highlighting “top picks” or “staff favorites” can also guide these tourists toward quick, confident buying decisions.

5.4. Limitations and Future Research

Despite its contributions, this study has limitations. High correlations among variables reduced predictive power, limiting the use of structural equation modeling (SEM). Path analysis was applied but assumes linear, unidirectional relationships with uncorrelated error terms (Jeon, 2015), restricting causal interpretation. Future research could use Partial Least Squares SEM (PLS-SEM), which better handles multicollinearity and maximizes explained variance (Hair et al., 2011). Alternatively, a larger sample size could improve SEM robustness. Additionally, as a single-source survey, residual common method variance cannot be fully ruled out; future studies could incorporate a measured latent marker variable (MLMV) approach to enhance robustness (Chin et al., 2013). This study focuses on Chinese tourists shopping in Japan and does not examine specific retail contexts (e.g., malls, souvenir shops). Future research could extend to other countries and compare retail formats, as these may shape how value influences satisfaction and destination loyalty. For instance, Japan is known for department stores, luxury assortments, and character merchandise; Korea emphasizes beauty and fashion; and Singapore features premium mall clusters. Comparative work across these settings could test whether the functional value (i.e., performance vs. money) distinction and hedonic subdimensions vary in strength, offering context-sensitive guidance for shopping-tourism strategy.

Future research should examine omnichannel shopping in tourism—cross-channel journeys spanning online and in-store (T. Chen et al., 2019), and in-destination online shopping (DOS) (Xu et al., 2024) as emerging modes that may reshape how satisfaction converts into destination loyalty and spending. Future studies can also examine additional variables, such as shopping-destination trust (Chang et al., 2025), visit frequency (Moharana & Pattanaik, 2023), role shopping (Arnold & Reynolds, 2003), status (Atulkar & Kesari, 2017), and praise from others (Çavuşoğlu et al., 2021), to further clarify how these factors shape satisfaction, loyalty, and on-site spending. Since functional value was the strongest predictor, its dimensions (convenience, cost, performance) warrant further study. Refining time and money spent metrics (e.g., per day, per hour) could also provide deeper insights into tourist spending behaviors. Future studies could tailor social-value indicators to international group travel (e.g., interest clubs, social-media sharing) to test when social value re-emerges in destination shopping. Last but not least, involvement was operationalized as a unidimensional scale and applied via a median-split multi-group analysis; dichotomizing a continuous construct can reduce statistical power and weaken interaction effects, which may partly explain the limited moderation observed. Future research could treat involvement as a continuous variable and test moderation without splitting the sample (e.g., by including an interaction term such as SAT × INV), or consider involvement as a mediator between satisfaction and loyalty (Olsen, 2007).