Why Chinese Consumers Buy Pre-Loved Luxury Fashion: The Mediating Role of Channel Engagement

Abstract

The rapid rise of the pre-loved luxury fashion market in China reflects a unique shift in consumer behaviour, shaped by growing concerns for sustainability, affordability, and personal expression. While global scholarship on circular fashion has expanded, studies remain predominantly focused on Western consumers, leaving Chinese market dynamics underexplored. This study addresses this gap by examining the motivations and channel engagement of Chinese consumers purchasing pre-loved luxury fashion, including pre-owned, vintage, and collectors’ items. A sequential mixed-methods design was employed, integrating quantitative data from a survey of 438 Chinese consumers with qualitative insights from 21 semi-structured interviews. Structural equation modelling revealed that economic, individual, and social motivations significantly influenced perceived value, which in turn enhanced engagement with resale channels. Functional motivations, though present, played a less prominent role. Furthermore, engagement with online and offline channels, including social media platforms, livestream commerce, and luxury consignment boutiques, was found to mediate the relationship between perceived value and purchase intention. The study contributes to theory by adapting established luxury value frameworks to the pre-loved context and by introducing channel engagement as a mediating construct in the consumption of second-hand luxury fashion. The main theoretical frameworks that underpin the study, such as the Brand Luxury Index and the Four Value Dimensions, are used to provide a clearer understanding of its conceptual foundation. In particular, some key quantitative indicators, such as β-values or R², would make the summary more specific and informative. Practically, the findings provide actionable insights for platform operators and luxury brands seeking to build consumer trust and enhance experiential value in China’s rapidly evolving resale market. By situating the research within a culturally specific and digitally advanced retail environment, the study broadens understanding of circular luxury fashion consumption in non-Western contexts.

1. Introduction

Fuelled by growing consumer awareness of sustainability and circular economic values, and by shifting attitudes toward ownership, this segment now constitutes a major force within both mainstream and luxury fashion. Notably, the Chinese market is emerging as a key growth driver, with reports indicating that the second-hand luxury sector is expanding at nearly 4 times the pace of the new luxury market [1].

Previous studies have explored motivations such as value-seeking, uniqueness, and sustainability in second-hand consumption [2,3], and frameworks such as the Brand Luxury Index [4] and Four Luxury Value Dimensions [5] have been used to interpret luxury purchase intentions. However, few studies have applied these theories to the pre-loved context in emerging economies, such as China. Moreover, a significant research gap remains in understanding the mediating role of channel engagement in how consumers interact with, evaluate, and trust resale platforms and intermediaries. In contrast, retail channel dynamics are widely discussed in the current literature [6,7,8]. The intersection between channel engagement and second-hand luxury behaviour, especially on culturally specific hybrid platforms, has not been adequately addressed.

This study addresses these gaps by examining how Chinese consumers’ economic, functional, individual, and social motivations influence their perceptions of the value of pre-loved luxury fashion, and how these perceptions, in turn, shape their engagement with retail channels and their ultimate purchasing intentions. By integrating three theoretical lenses, the Brand Luxury Index [4], four-dimensional value framework [5], and a model of second-hand shopping motivations [2]. The study develops a conceptual framework tailored to the Chinese context. A mixed-methods sequential explanatory design is adopted, beginning with a large-scale quantitative survey followed by in-depth interviews to enrich and contextualise findings.

The objective of this paper is twofold: first, to enhance theoretical understanding of the perceived value and behavioural processes underpinning pre-loved luxury fashion consumption in China. The conceptual framework integrates motivational antecedents, perceived value, and channel engagement to explain consumer behaviour in China’s pre-loved luxury fashion market. By addressing economic, functional, individual, and social drivers, the study provides a comprehensive understanding of the factors shaping value perceptions and their impact on purchase intentions through retail channel engagement. In addition, the study employs channel engagement as a mediating variable, which is supported by stronger theoretical reasoning linking consumer value perception and behavioural intention through digital interaction pathways. Second, to offer practical recommendations for resale platforms, luxury brands, and policymakers aiming to foster more inclusive and trustworthy circular retail ecosystems. By focusing on China’s distinctive digital infrastructure and socio-cultural context, this study offers timely insights into both academic and commercial discussions on sustainable luxury consumption.

However, the unique dynamics of this sector in China warrant closer academic scrutiny. Cultural factors, including the historical stigma associated with used goods, the concept of ‘face’ (mianzi), and the growing sustainability consciousness among younger consumers, collectively shape evolving attitudes toward pre-loved luxury fashion. Social stigma is defined as a prejudicial attitude held by a particular group of people, characterised by labelling, exclusion, discrimination, isolation, and stereotyping [9,10]. At the same time, digital innovation in China, spanning livestreaming e-commerce, social media marketplaces, and hybrid online–offline consignment platforms, has created a retail environment distinct from that of Western markets [11].

The remainder of this paper is organised as follows. Section 2 reviews the relevant literature on pre-loved luxury fashion consumption and introduces the study’s conceptual framework and hypotheses. Section 3 outlines the research methodology. Section 4 presents the results of both the quantitative and qualitative analyses. Section 5 discusses the theoretical and managerial implications of the findings. Finally, Section 6 concludes the paper by highlighting contributions, limitations, and directions for future research.

2. Literature Review and Hypotheses Development

2.1. Conceptualising Pre-Loved Luxury Fashion

Pre-loved luxury fashion encompasses previously owned luxury goods that retain significant symbolic, functional, and aesthetic value even though they are no longer new. These items, typically from prestigious brands, maintain strong brand equity and desirability in secondary markets. Unlike generic second-hand clothing, pre-loved luxury is distinguished not merely by prior ownership but by enduring luxury attributes such as superior craftsmanship, exclusivity, and cultural significance [12]. Regarding luxury and sustainability, consumers in Hong Kong are now interested in sustainable consumption, green manufacturing, natural environment, green ethics, and eco-friendliness [13,14]. In response to changing consumer attitudes and behaviours, fashion designers and manufacturers may need to integrate the notions of fashion consumption with environmental proactivity and concern (e.g., upcycling) [15]. Sustainable fashion strives to minimise negative and maximise positive social, economic, and ecological impacts across the value chain [16]. As such, the R&D funding for eco-textiles and a closed-loop economy is articulated to industrial practitioners in the luxury fashion sector [17].

The literature identifies three overlapping subtypes of pre-loved luxury fashion:

• Pre-owned luxury: Recently released items that have changed ownership with minimal wear, often still aligned with current designs or seasons [18];
• Vintage luxury: Older items, typically over 20 years old, are valued for their scarcity, historical significance, or stylistic appeal [19];
• Collector’s luxury: Items sought for their rarity, cultural importance, or investment potential, often prioritising symbolic over functional value [20,21].

These categories frequently intersect. For instance, a vintage Chanel handbag may serve as both a collector’s item and a celebrity association. Despite distinctions in luxury attributes, pre-loved goods share the fundamental characteristics of second-hand goods: they involve the transfer of ownership and extend a product’s usable lifespan through reuse [22]. In China, the pre-loved luxury market is expanding rapidly, driven by evolving consumer preferences, particularly among younger, sustainability-conscious, and brand-savvy demographics. This study adopts a broad definition of pre-loved luxury fashion, encompassing all three subtypes and focusing on items such as handbags, clothing, and accessories.

2.2. Perceived Value in Pre-Loved Luxury Fashion

Perceived value represents a consumer’s overall evaluation of a product, balancing perceived benefits against the sacrifices required to acquire it [23]. In the context of pre-loved luxury fashion, perceived value is multidimensional, incorporating financial affordability, uniqueness, sustainability, and emotional resonance. Previous research highlights that consumers derive value from exclusive access to discontinued or rare items and from engaging in ethical consumption practices [3].

Unlike traditional luxury markets, where value is often tied to newness and exclusivity, pre-loved luxury redefines value through narratives of heritage, rarity, and circularity [2]. In China, perceived value is particularly influenced by concerns about authenticity and resale assurance, given the prevalence of counterfeit goods [24]. Consequently, understanding the motivational drivers that shape perceived value is critical to explaining consumer engagement with pre-loved luxury fashion.

2.3. Motivational Antecedents

Drawing on frameworks by Guiot and Roux [2] and Wiedmann et al. [5]. This study categorises motivations into economic, functional, individual, and social drivers.

2.3.1. Economic Motivation

Economic motivation is particularly relevant in transitional luxury markets, such as China, where price sensitivity significantly influences consumer behaviour [25]. Additionally, the perception of pre-loved goods as financial assets capable of retaining or appreciating value introduces an investment logic into purchasing decisions. Accordingly, the following is proposed:

H1: 

Economic motivation positively influences perceived value in pre-loved luxury fashion.

2.3.2. Functional Motivation

Functional motivation pertains to tangible product attributes, including quality, condition, and durability. Luxury goods are renowned for their superior craftsmanship and high-quality materials, which enable them to maintain their performance over time [12]. In digital marketplaces, functional trust is often mediated by platform reputation and third-party verification. Given the prevalence of counterfeit goods in China, platforms that ensure product quality and authenticity enhance the perceived value of their offerings. Thus, the following is hypothesised:

H2: 

Functional motivation positively influences perceived value in pre-loved luxury fashion.

2.3.3. Individual Motivation

Individual motivation encompasses personal gratification, aesthetic appreciation, and the pleasure of acquiring unique items. In pre-loved luxury fashion, this manifests as the thrill of “treasure hunting” or nostalgia for vintage aesthetics [26]. Among Chinese Gen Z and millennial consumers, pre-loved luxury is increasingly associated with personal style and authenticity, enabling differentiation in brand-saturated markets [27]. Therefore, the following is proposed:

H3: 

Individual motivation positively influences perceived value in pre-loved luxury fashion.

2.3.4. Social Motivation

Social motivation reflects the desire for social approval, status signalling, or alignment with peer groups. In pre-loved luxury fashion, this involves displaying status through ownership of luxury brands and signalling ethical values by supporting circular fashion [28]. In China, social media platforms such as Xiaohongshu (RedNote) and Weibo play a pivotal role in normalising pre-loved luxury consumption, often through key opinion leader (KOL)-driven content that blends prestige with sustainability [29]. These platforms align individual behaviour with broader social narratives. Consequently, the following is hypothesised:

H4: 

Social motivation positively influences perceived value in pre-loved luxury fashion.

2.4. Channel Engagement as a Mediator

Channel engagement refers to the consumer’s psychological investment and behavioural participation in a retail environment [30]. In China, hybrid retail models that integrate social commerce, livestreaming, consignment boutiques, and international resale platforms dominate the market [31].

Channel engagement mediates the relationship between perceived value and purchase behaviour. High-quality engagement, characterised by seamless navigation, transparent authentication, and responsive customer service, strengthens the link between value perceptions and purchase intentions. Thus, the following hypotheses are proposed:

H5: 

Perceived value positively influences consumer engagement with retail channels.

H6: 

Channel engagement positively influences purchase intention for pre-loved luxury fashion.

A summary of each construct are shown in

Table 1. Summary table of each construct.

Construct	Description	Source
Economic motivation	Consumers’ pursuit of cost savings, value for money, and potential resale returns. Pre-loved luxury fashion enables access to aspirational brands at reduced prices, preserving social status while enhancing affordability.	Turunen et al. [32]
Functional motivation	Tangible product attributes, including quality, condition, and durability.	Turunen and Leipämaa-Leskinen [12]
Individual motivation	Individual motivation encompasses personal gratification, aesthetic appreciation, and the pleasure of acquiring unique items. Consumers often seek rare or discontinued items to express their identity or as a form of self-reward.	Silva et al. [26]
Social motivation	The desire for social approval, status signalling, or alignment with peer groups. In pre-loved luxury fashion, this involves displaying status through ownership of luxury brands and signalling ethical values through support for circular fashion	Aycock et al. [28]
Perceived value	Perceived value represents a consumer’s overall evaluation of a product, balancing perceived benefits against the sacrifices required to acquire it.	Zeithaml [23]
Channel engagement	Channel engagement refers to the consumer’s psychological investment and behavioural participation in a retail environment. In the context of pre-loved luxury fashion, engagement extends beyond transactions to include exploration, authentication verification, and platform loyalty.	Hollebeek et al. [30]
Purchase intention	Purchase intention is identified as one of the purchase behaviour studies. It is used to examine the implementation of a new distribution channel, encouraging decision makers to consider whether the idea can be further developed and to determine which consumer segments and geographic markets to target through the channel.	Peña-García et al. [33]

.

2.5. Research Questions and Contributions

Based on the gaps identified in the literature, this study examines how Chinese consumers form value perceptions and make purchase decisions in the pre-loved luxury fashion market. Specifically, the research investigates (1) how different types of consumer motivations—economic, functional, individual, and social—influence perceived value; (2) how perceived value affects consumer engagement with online and offline resale channels; and (3) whether channel engagement mediates the relationship between perceived value and purchase intention. The qualitative phase further explores how Chinese consumers articulate their trust, concerns about authenticity, and experiential factors when interacting with resale platforms.

This study makes three main contributions. First, it extends luxury consumption research by applying established luxury value frameworks to the circular fashion context in China, a market where cultural and digital factors differ from Western settings. Second, it introduces channel engagement as a mediating mechanism, providing a clearer understanding of how perceived value translates into purchase intention. Third, by combining a large-scale quantitative survey with in-depth interviews, the study offers both empirical validation and contextual insights, contributing to a more comprehensive understanding of pre-loved luxury fashion consumption in a rapidly evolving digital environment.

3. Methodology

Before presenting the empirical analyses, this section outlines the methodological framework guiding the study. Given the multifaceted and culturally embedded nature of pre-loved luxury fashion consumption in China, a mixed-methods approach was adopted to capture both breadth and depth of consumer behaviour. The methodology integrates quantitative and qualitative components in a sequential design, beginning with large-scale survey modelling and followed by semi-structured interviews. This structure allows for rigorous testing of hypothesised relationships while also uncovering contextual nuances that enrich interpretation. The following subsections detail the research design, sampling procedures, measurement development, data analysis techniques, and qualitative protocols that collectively underpin the study’s robustness and validity.

3.1. Research Design

This study adopts a mixed-methods research design consisting of an integrated sequence of qualitative exploration, quantitative modelling, and cross-phase interpretation. The overall flow begins with qualitative insights to refine constructs, followed by a large-scale quantitative survey to validate the proposed relationships. It concludes with a triangulation stage that synthesises findings to enhance explanatory depth using IBM SPSS Statistics v29. This multi-phase approach is particularly suitable given the complex, value-laden, and culturally embedded nature of pre-loved luxury fashion consumption in China.

The qualitative component provides an exploratory understanding of motivations, perceived value, and channel engagement, thereby refining measurement items and ensuring that constructs accurately reflect the sociocultural context. The quantitative phase then empirically tests the hypothesised model, in which Confirmatory Factor Analysis (CFA) [34] and Structural Equation Modelling (SEM) [35] are conducted using AMOS 27 Graphics, employing maximum likelihood estimation, widely recognised for its robustness in model estimation and assessment. This enables rigorous evaluation of the measurement structure and its structural relationships.

By combining qualitative insights with quantitative validation, the mixed-methods design strengthens construct validity, mitigates method bias, and allows the study to capture both statistical patterns and interpretive nuances. Such triangulation is essential for examining consumer behaviour in China’s pre-loved luxury fashion market, where concerns about authenticity, brand symbolism, and face consciousness interact in multifaceted ways. The full methodology can be found in Liu [36].

3.2. Quantitative Study

3.2.1. Sample and Procedure

The quantitative phase employed a cross-sectional online survey targeting Chinese consumers who have purchased pre-loved luxury fashion items. A total of 438 valid responses (out of a total of 585, as 147 participants indicated they have no interest in purchasing pre-loved luxury fashion goods in the future) were collected from participants aged over 18 via purposive sampling on platforms such as Xiaohongshu (RedNote), WeChat groups, LinkedIn, and second-hand fashion forums etc. As such, we have received a reasonable survey response rate of 74.9%. Screening questions ensured respondents had prior experience with pre-loved luxury products (e.g., handbags, apparel, accessories, watches, etc.) from recognised global brands.

Demographic diversity across gender, income, education, and geographic location enabled the sample to reflect a range of consumption profiles in China’s luxury resale market.

Table 2. Demographic profile of participants.

Profile of the Participants	Totals		Profile of the Participants	Totals
Gender	n = 438	%	City currently lives	n = 438	%
Male	169	38.6	Tier 1	67	15.3
Female	256	58.4	New Tier 1	170	38.8
Other	13	3.0	Tier 2	68	15.5
Age	n = 438	%	Tier 3	57	13.0
18–25	107	24.4	Tier 4 and below	76	17.4
26–35	128	29.2	Income	n = 438	%
≥36	203	46.3	No income	55	12.6
Occupation	n = 438	%	¥1–3999 (≈$0.14–$552)	80	18.3
Student	114	26.0	¥4000–5999 (≈$552–827)	79	18.0
Employment	296	67.6	¥6000–7999 (≈$827–1103)	92	21.0
Other	28	6.4	¥8000–9999 (≈$1103–1379)	56	12.8
Education	n = 438	%	¥10,000–19,999 (≈$1379–2758)	48	11.0
Degrees include/under tertiary or no degree	54	12.3	¥20,000 or more (≈$2758 or more)	28	6.4
Undergraduate (BSc)	263	60.0
Postgraduate (MSc) and above	121	27.6

presents the demographic profile of the participants. Predominantly, the participants were female (58.4%), with a significant proportion falling within the 36 years and above age group (46.3%). The majority were employed (67.6%), indicating active participation in the workforce. Moreover, a substantial number of respondents possessed an undergraduate degree (60%), indicating a high level of education within the sample. Regarding residential locations, the highest number of participants resided in New Tier 1 cities (38.8%), which typically denotes major urban centres. The Chinese city tier system categorises mainland cities into five levels based on population size, gross domestic product (GDP), infrastructure, administrative rank, and availability of commercial resources [37]. In terms of income distribution, the majority fell within the income brackets ranging from ¥1000 to ¥7999, with the most common being in the range of ¥6000 to ¥7999 (21%), followed by ¥1000 to ¥3999 (18.3%) and ¥4000 to ¥5999 (18%). This distribution reflects diverse economic backgrounds among participants, enriching the data for analysis. Considering that the most recent national statistics report an annual urban per capita disposable income of approximately ¥41,314 in China [38], the income distribution of the sample appears broadly consistent with the economic profile of typical urban consumers, providing further reassurance that the respondents represent a realistic segment of China’s pre-loved luxury fashion market [39].

3.2.2. Measures and Constructs

All measurement items were adapted from validated scales used in previous studies, with wording adjusted to suit the context of pre-loved luxury. A 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) was applied throughout. All scales were translated into Chinese using the back-translation method to ensure linguistic equivalence [40].

Hypotheses are derived from the literature review and integrated into the conceptual model for analysis. The final variables extracted in the CFA are displayed in

Table 3. Conceptual measurement model.

Construct	Scale	Label	References
Economic Motivations	I don’t want to pay more for a product just because it’s new.	EM1	Adapted from Guiot and Roux [2]
	By buying pre-loved luxury fashion goods, I feel I’m paying a fair price.	EM2
	I enjoy buying pre-loved luxury fashion goods because when I resell it, there is still a good market for some of the more valuable brands of pre-loved luxury fashion goods.	EM3	Adapted from Boardman et al. [41] and Turunen and Pöyry [3]
	I buy pre-loved luxury fashion goods because there is an investment opportunity for some rarer items or limited editions are even greater than the first released in the secondary market.	EM4
	I have explicit intent to sell the product at a later point of time.	EM5
Functional Motivations	A luxury product cannot be sold in supermarkets.	FM1	Adapted from Wiedmann et al. [5]
	Authentic luxury products cannot be mass-produced.	FM2
	Few people own an authentic luxury product.	FM3
	People who buy luxury products try to differentiate themselves from the others.	FM4
	I hope to come across items that nobody else has.	FM5	Adapted from Guiot and Roux [2]
	I hope to come across original items that are not found in mainstream stores.	FM6
	I’m inclined to evaluate the substantive attributes and performance of a luxury brand myself rather than listen to others’ opinions.	FM7	Adapted from Wiedmann et al. [5]
	The luxury brand preferred by many people but that does not meet my quality standards will never enter into my purchase consideration.	FM8
	I buy a luxury brand for satisfying my personal needs without any attempt to make an impression on other people.	FM9
Individual Motivations	Luxury fashion goods make life more beautiful.	IM1	Adapted from Dubois et al. [42] and Faschan et al. [43]
	Luxury fashion goods bring excitement.	IM2
	One buys luxury fashion goods primarily for one’s pleasure.	IM3
	I feel happy when I have luxury fashion goods.	IM4
	I like wandering around pre-loved outlets because I always hope I’ll come across a real find.	IM5	Adapted from Guiot and Roux [2]
	I go to certain pre-loved outlets to rummage around and try to find something.	IM6
	I’m often on the lookout for a find when I go to certain pre-loved outlets.	IM7
	In certain pre-loved outlets, I feel rather like a treasure hunter.	IM8
	I am attracted more to old things than new ones.	IM9	Adapted from Guiot and Roux [2]
	Above all, I buy luxury fashion goods pre-loved, because they are old and have a history.	IM10
	I like buying pre-loved luxury fashion goods because they evoke the past.	IM11
	I like buying pre-loved luxury fashion goods because I find them authentic.	IM12
	I like to buy pre-loved luxury fashion goods because I am a collector.	IM13	Adapted from Turunen and Leipämaa-Leskinen [12]
	I am interested in specific types of pre-loved luxury fashion goods.	IM14
	Collecting pre-loved luxury fashion goods can bring me joy and satisfaction.	IM15
	In relation to collectable items, I feel strong emotional connections.	IM16
Social Motivations	Even though they are pre-loved, luxury items and brands are an indicator of my wealth.	SM1	Adapted from Boardman et al. [41], Vigneron and Johnson [4] and Wiedmann et al. [5]
	Luxury brands can represent my social status.	SM2
	I enjoy buying pre-loved luxury fashion goods because I don’t like objects being thrown away that can still be of use.	SM3	Adapted from Boardman et al. [41] and Guiot and Roux [2]
	By buying pre-loved luxury fashion goods, I feel I’m helping to fight against waste.	SM4
	Buying pre-loved luxury fashion goods are more environmentally friendly.	SM5
Perceived Value	Considering the risks I take in buying luxury fashion products, shopping at pre-loved luxury fashion retailers has value.	PV1	Adapted from Aycock et al. [28]
	Considering the money, I pay for buying luxury fashion products, shopping at pre-loved luxury fashion retailers is a good deal.	PV2
	Considering all the monetary and non-monetary costs I incur in buying luxury fashion products, shopping at pre-loved luxury fashion retailers is of good value.	PV3
Engagement with Channels	I enjoy buying pre-loved luxury fashion goods at brick-and-mortar (in store).	EWC1	Adapted from Aycock et al. [28], Bai et al. [44], and Wang et al. [10]
	I enjoy buying pre-loved luxury fashion goods at official online pre-loved luxury consignment stores (e.g., International—https://www.therealreal.com, https://www.vestiairecollective.com, https://www.fashionphile.com, https://www.luxurygaragesale.com, etc; China—Fei Yu, Zhi Er, Hong Bu Lin, Pang Hu, Si Ku, etc.).	EWC2
	I enjoy buying pre-loved luxury fashion goods at online e-commerce platforms (e.g., Alibaba’s Taobao and Tmall, JD.com, Pinduoduo, etc.)	EWC3
	I enjoy buying pre-loved luxury fashion goods at online social networking sites (e.g., WeChat, Little Red Book, Douyin, etc.).	EWC4
	I enjoy buying pre-loved luxury fashion goods online after I watch an online live stream (e.g., Taobao Live, Douyin Live, Little Red Book Live, WeChat Live, etc.).	EWC5
	I enjoy buying pre-loved luxury fashion goods at multiple channels (including any channels online and offline channels).	EWC6
Purchase Intention	I intend to buy pre-loved luxury fashion products in the near future.	PI	Adapted from Bian and Forsythe [45] and Faschan et al. [43]

below.

3.2.3. Data Analysis

The analysis includes descriptive statistics to summarise the data, factor analysis to identify key constructs, and hypothesis testing using SEM to explore the relationships between variables. Data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) via SmartPLS 4.0. PLS-SEM is particularly suited for theory testing in exploratory models with complex causal paths and formative-reflective constructs [46]. Reliability, convergent validity, discriminant validity, and path significance were assessed. Additionally, mediation effects of perceived value and channel engagement were tested using bootstrapping (5000 subsamples). Furthermore, CFA is employed to validate the measurement models and ensure the scales’ reliability and validity. This comprehensive approach allows for a detailed understanding of the factors driving consumer behaviour in the pre-loved luxury fashion market.

3.3. Qualitative Study

3.3.1. Interview Sample

To complement the quantitative findings, semi-structured interviews were conducted with 21 Chinese consumers (15 females and 6 males, aged over 18) who had purchased pre-loved luxury fashion within the past 12 months. Participants were mainly recruited from first-stage questionnaire respondents who expressed interest in the stage 2 interview, with inclusion criteria focused on experience across multiple platforms (e.g., Taobao/live streaming, Jingdong, Douyin, WeChat resale groups, offline consignment boutiques, Vestiaire Collective, etc.). Interviews were conducted online in Mandarin (30–45 min each). All interviews were recorded, transcribed, and translated for coding.

3.3.2. Coding and Analysis

Thematic analysis was used to identify patterns across the data [47]. The coding process followed a hybrid approach:

• Deductive coding based on the conceptual model (economic, functional, individual, and social motivations; perceived value; channel engagement).
• Inductive coding to capture emergent themes such as “trust in daigou,” “face-saving concerns,” and “nostalgic value of vintage brands.”

NVivo 12 software facilitated the organisation of themes and subthemes. Intercoder reliability was ensured by involving a second researcher for cross-checking 30% of transcripts, achieving over 85% agreement.

Findings from the qualitative phase served two purposes: (1) to contextualise the quantitative relationships in culturally grounded insights, and (2) to explore platform-specific behaviours and value articulation not captured in survey data. Several quotes are integrated into the discussion section to support the interpretation of model results.

4. Findings

Before delving into the quantitative analysis, it is essential to highlight that this study adopted a mixed-methods approach, combining survey-based statistical modelling with qualitative insights from semi-structured interviews. The quantitative phase provides empirical validation of the proposed conceptual framework through PCA, reliability testing, and PLS-SEM structural modelling. These results establish the strength and direction of relationships among consumer motivations, perceived value, channel engagement, and purchase intention. The subsequent qualitative phase complements and contextualises these findings, offering more profound insight into consumer perceptions and behaviours within China’s pre-loved luxury fashion market. Together, these two phases provide a robust foundation for understanding the drivers of value formation and buying intention in this emerging consumption domain.

4.1. Quantitative Results

Principal Component Analysis (PCA) is a statistical technique used to reduce the dimensionality of a dataset by identifying patterns in the data and expressing it in a way that highlights its similarities and differences [48]. The extraction method mentioned is Principal Component Analysis, which confirms this approach. Component loadings (factor loadings) indicate how much of a variable’s variance is explained by a component. Loadings above 0.5 are typically considered significant and indicate that the item strongly relates to the component.

The PCA results across the economic motivation, functional motivation, individual motivation, social motivation, perceived value, and engagement with channels sets indicate that the majority of items have loadings above 0.5, affirming their validity in measuring their intended constructs. This analysis underscores the coherence and appropriateness of the items with respect to their underlying factors, with the vast majority demonstrating a strong contribution to the components they are associated with. The criterion of loadings above 0.5 serves as a confirmation of the items’ effectiveness in capturing the constructs they are designed to measure, with only a few exceptions that marginally miss this benchmark.

The Kaiser–Meyer–Olkin (KMO) Measure of Sampling Adequacy is 0.908, indicating a high level of sampling adequacy for the factor analysis. Bartlett’s Test of Sphericity shows a significant Chi-Square value of 1834.169 with 15 degrees of freedom and a significance level of less than 0.001, confirming that the correlations between items are sufficiently large for PCA. The high KMO value suggests that the sample size is adequate for reliable factor analysis, while the significant Bartlett’s Test indicates that the data is suitable for structure detection. These results validate the use of PCA in this study, ensuring that the factor analysis will yield meaningful and interpretable components.

A Cronbach’s alpha threshold of at least 0.70 was established [49,50]; however, as per Leech et al. [50], values ranging from 0.60 to 0.69 are still deemed acceptable in certain contexts. The reliability of the scales was assessed using Cronbach’s Alpha coefficients, which indicated that all variables exhibit acceptable levels of internal consistency. Overall, all variables have Cronbach’s Alpha coefficients above 0.6, with most showing high reliability (above 0.7). This indicates that the scales used to measure these variables are generally reliable. High reliability (Cronbach’s Alpha > 0.6) is often sought in research to ensure that the measurement scales accurately capture the constructs they intend to measure [51,52]. The data support the conclusion that these variables can be considered reliably measured. This robust level of reliability across variables is important for the validity of any findings or conclusions drawn from this data.

The quantitative results were derived using PLS-SEM to assess the structural model and test the hypothesised relationships. The final sample comprised 438 valid responses, with demographic diversity enhancing the generalisability of the results to young, urban Chinese consumers of pre-loved luxury fashion.

4.1.1. H1–H4: Motivational Antecedents of Perceived Value

All four hypothesised paths from consumer motivations to perceived value were supported, with statistically significant standardised coefficients (β) and p-values below the 0.05 threshold.

• H1 (Economic Motivation→Perceived Value): The path coefficient was β = 0.26 (p < 0.001), indicating that price sensitivity, resale potential, and value-for-money perceptions significantly enhanced perceived value. This aligns with prior studies suggesting that pre-loved luxury consumption is partially driven by financially rational decision-making.
• H2 (Functional Motivation→Perceived Value): Functional motivation had the strongest effect (β = 0.35, p < 0.001), underscoring the importance of quality, authenticity, and durability. Consumers placed a premium value on well-preserved items from reputable brands, mirroring previous findings by Turunen et al. (2019) [3].
• H3 (Individual Motivation→Perceived Value): Individualistic motives such as aesthetic appreciation, nostalgia, and personal enjoyment significantly predicted perceived value (β = 0.21, p = 0.004). This suggests that hedonic and emotional attachments to rare or vintage fashion pieces are central to the formation of value.
• H4 (Social Motivation→Perceived Value): The social dimension (e.g., sustainability signalling and social approval) was also positively linked (β = 0.19, p = 0.011), though the effect size was comparatively smaller. This result highlights the increasing, albeit moderate, social legitimacy of second-hand luxury in Chinese culture.

These findings confirm that perceived value in pre-loved luxury consumption is a multidimensional construct shaped by a combination of economic pragmatism, functional expectations, and symbolic self-expression.

4.1.2. H5–H6: Mediation Through Channel Engagement

The second part of the model tested the mediating role of channel engagement in the relationship between perceived value and purchase intention.

• H5 (Perceived Value→Channel Engagement): A strong positive effect was found (β = 0.44, p < 0.001), suggesting that consumers who recognised value in pre-loved items were more inclined to interact with relevant purchase channels, including both online platforms and physical consignment stores.
• H6 (Channel Engagement→Purchase Intention): Engagement significantly predicted purchase intention (β = 0.47, p < 0.001), supporting the assertion that involvement with the shopping environment—through browsing, interacting, or following sellers—increases the likelihood of eventual purchase.

A bootstrapping analysis (5000 samples) confirmed that channel engagement mediates the relationship between perceived value and purchase intention. The indirect effect was significant (β = 0.21, p < 0.001), reinforcing the model’s conceptual logic.

4.2. Structural Model Summary

The structural equation model is shown in Figure 1. The R² values for perceived value (R² = 0.61), channel engagement (R² = 0.56), and purchase intention (R² = 0.49) indicate moderate to strong explanatory power. Model fit indices (e.g., SRMR = 0.065) fall within acceptable thresholds, confirming robustness.

4.3. Qualitative Themes

To enrich the statistical results with contextual understanding, thematic analysis was applied to interview transcripts from 21 Chinese consumers of pre-loved luxury fashion. Two dominant themes emerged that reinforce and elaborate on the quantitative pathways.

In the second phase of the study, which involved online one-to-one semi-structured interviews, convenience non-probability sampling was employed. The criterion for recruiting interviewees was that they had to have completed the questionnaire survey. Participants were selected from individuals who proactively provided their contact information during phase one. A total of 119 respondents expressed their willingness to participate in phase two, and 21 participants ultimately agreed to take part in this stage of the research. To gather data, three major questions were used in the one-to-one online semi-structured interviews, aimed at contributing to theory development within the research domain. The formulation of these interview questions was primarily based on the findings from phase one and theoretical insights from literature reviews, and they are listed in Appendix A.

As Patton [53] notes, “There are no rules for sample size in qualitative inquiry”. The sample size for qualitative research depends on various factors, including the nature of the research project and its specific objectives Patton [53]. Essentially, the sample size should be large enough for the researcher to determine when data saturation has been achieved. The goals of the interviews primarily influence the sample size, the quality of the data being gathered, and the constraints of time, effort, and financial resources. Therefore, data collection stopped at data saturation, the point at which no additional information emerged (21 interviews) [54]. While 21 participants may represent a small sample of the broader population, this sample size is deemed sufficient given the study’s two-stage design. The richness and diversity of the information collected, rather than the sheer number of participants, are critical to the quality of qualitative research [55]. Furthermore, considering the constraints of a PhD timeline, this sample size is adequate for the study’s purposes.

Table 4. Demographic attributes of the interview respondents.

	Gender	Age	Current City	Personal Monthly Income	Purchase Experience	Intention in Future
P1	Female	18–25	New Tier 1	No income	No	Yes
P2	Female	18–25	New Tier 1	No income	No	Yes
P3	Female	26–35	Tier 1	¥10,000–19,999	Yes
P4	Female	26–35	New Tier 1	No income	No	No
P5	Female	≥36	New Tier 1	¥10,000–19,999	No	No
P6	Female	26–35	Tier 1	No income	No	Yes
P7	Female	26–35	New Tier 1	¥8000–9999	No	No
P8	Male	26–35	New Tier 1	¥6000–7999	Yes
P9	Male	26–35	New Tier 1	¥10,000–19,999	No	No
P10	Male	26–35	New Tier 1	No income	Yes
P11	Male	18–25	New Tier 1	No income	No	Yes
P12	Female	26–35	New Tier 1	¥8000–9999	Yes
P13	Male	26–35	Tier 2	¥8000–9999	No	Yes
P14	Female	18–25	Tier 1	No income	No	Yes
P15	Female	18–25	Tier 2	No income	Yes
P16	Female	18–25	Tier 4 and below	No income	No	Yes
P17	Female	18–25	Tier 2	¥1–3999	Yes
P18	Female	18–25	Tier 2	No income	No	Yes
P19	Female	18–25	Tier 1	¥1–3999	No	No
P20	Male	≥36	Tier 3	¥20,000 or more	No	Yes
P21	Male	≥36	New Tier 1	¥20,000 or more	No	Yes

summarises the demographic attributes of the 21 interview respondents, highlighting diversity in gender, age, occupation, education, city of residence, income, purchasing experience, and future purchase intentions. The majority are female, with young adults (18–35 years old) comprising the respondents. Most are students, with a high proportion holding undergraduate or postgraduate degrees. Respondents are distributed across various city tiers (for reference to the Chinese city tier system, see Chapter 6.2), with the largest group in New Tier 1 cities. Income levels vary: nearly half have no income, while the rest earn across a broad range. Most respondents have no prior purchasing experience, but 10 out of 21 interviewees intend to purchase in the future. This demographic diversity provides a comprehensive view of the motivations and potential market for pre-loved luxury fashion.

4.3.1. Theme 1: Trust Barriers in Online Channels (Supports H5)

A recurring theme was consumer concern about authenticity and platform credibility in online transactions. Although participants valued the convenience and product variety offered by platforms like Vestiaire Collective or WeChat resale groups, many expressed hesitancies about payment safety and product verification:

“I love the idea of buying rare bags online, but unless I get a certificate or real-time authentication, I worry it’s fake.”

(Female, 27, Shanghai)

Paradoxically, the shift towards other digital formats, such as live-stream shopping, also revealed distinct trust dynamics. While platforms like Douyin offer a dynamic, engaging experience that mimics in-store social interaction, participants still rely heavily on trust-building cues to mitigate perceived risks. Live stream shopping, although offering immediacy and interactivity, required consumers to evaluate the seller’s credibility actively, as one respondent articulated:

“I bought from a Douyin live stream after seeing others buy and reading their reviews, considering the shop’s opening duration, considering if the store owner gathered the money and ran away or something like that, and after-sales satisfaction”.

(Female, 33, Hefei)

This trust deficit affected engagement levels; some respondents reported frequent browsing without completing purchases. Others engaged only when a third-party authentication service or a “daigou” intermediary was available. These insights corroborate the importance of perceived value in motivating channel interaction (H5) but also point to barriers that can weaken engagement even after value recognition.

4.3.2. Theme 2: Tactile Advantage in Offline Experiences (Supports H6)

In contrast, physical consignment boutiques and high-end second-hand stores were viewed as more trustworthy and enjoyable. Participants emphasised the value of tactile exploration, human interaction, and real-time validation:

“Trying on the clothes and seeing the texture helps me decide. It feels like shopping for new luxury, but with better prices”.

(Male, 31, Guangzhou)

The value of human interaction was further highlighted by the impact of professional offline customer service on purchase behaviour. Expert and knowledgeable salespersons can significantly enhance the overall shopping experience, thereby increasing consumer satisfaction and loyalty. Excellent customer service not only aids the initial sale but also bolsters trust mechanisms and assurance regarding product authenticity. One respondent detailed their positive experience with a salesperson who demonstrated exceptional professionalism and expertise:

“The shop salesperson is a young man, probably around your age. We call him ‘Big Brother’. I feel he’s very professional. He has various appraisal tools and demonstrated how he appraises items in front of me. For example, he explained the craftsmanship and showed me the lettering on the back of a Ferragamo buckle, explaining how the font is printed. He taught me how to distinguish authentic items from counterfeits. He also wears a long, microscope-like device over his eyes, and his phone has a magnification function similar to that of a tablet. He can use it to show you the craftsmanship details on the back of an item. He can show you clearly whether a part is connected properly or how it has been handcrafted”.

(Male, 29, Xi’an)

Such experiences also deepened psychological engagement in the purchase process, leading to more confident, immediate buying decisions. The immersive and sensory-rich environment supported both hedonic and functional value perceptions. This theme aligns with H6, which is confirmed: higher engagement with retail channels, particularly offline, facilitates purchase intention.

These qualitative themes validate and extend the model’s logic by revealing the nuanced drivers and inhibitors of engagement. In particular, they highlight how trust mechanisms and experiential factors mediate the path from perceived value to final purchase decision.

5. Discussion

The results show that Chinese consumers of pre-loved luxury goods are primarily driven by functional and economic value, rather than hedonic or symbolic factors. This suggests a pragmatic approach in the Chinese second-hand luxury market: shoppers focus on practical benefits (quality, utility) and financial advantages (better prices, investment value) when considering pre-owned luxury. One explanation is that luxury resale in China remains an emerging practice, so consumers emphasise tangible benefits to justify purchasing second-hand. In contrast, more abstract motives, such as the enjoyment of the shopping experience or the status signalled by vintage items, appear secondary. This pattern differs from some Western contexts were sustainability, uniqueness, or experiential “treasure-hunt” thrills can strongly drive second-hand luxury purchases. The comparatively lower influence of hedonic and symbolic motives in our study may reflect cultural nuances: traditionally, Chinese luxury consumers have valued newness and prestige, and second-hand items have carried a stigma as “used.” However, attitudes are changing among younger generations, who increasingly view savvy purchasing, including secondhand bargains or rare vintage finds, as a mark of good taste. Our findings capture this transitional phase: functional and economic motives dominate, but there is potential for growth in hedonic and symbolic appreciation as the culture around resale matures.

Importantly, this study confirms that channel engagement plays a central mediating role between consumers’ perceived value and their purchase intentions in a digital resale context. In other words, simply perceiving value in a pre-loved luxury item is not enough—consumers are more likely to act on those value perceptions when they are actively engaged with the online resale platform or channel. This engagement encompasses how consumers interact with the resale app or website, including browsing, following sellers, reading reviews, and participating in community features. A high level of engagement indicates that consumers feel comfortable and interested in the platform environment, which in turn bridges the gap between their motivations and the decision to purchase. The strong mediation effect observed suggests that engagement is the mechanism by which value perceptions translate into action. Suppose a consumer perceives a pre-owned luxury handbag as high value, for its functionality, price, or perhaps status. In that case, they will only proceed to purchase if they also engage deeply with the platform—exploring listings, trusting the service, and spending time on it. This insight aligns with engagement theories and underscores the importance of the digital experience in the online luxury resale market.

Our discussion also points to the influence of cultural and generational factors on these dynamics. Chinese consumers operate in a highly digitised retail environment, but they bring unique cultural perspectives: for instance, concerns about counterfeit goods and an ingrained emphasis on social prestige. Trust in a platform’s authenticity guarantees is especially crucial in China’s resale market, given a history of counterfeit luxury items. This need for trust can amplify the role of channel engagement: consumers who perceive a platform as trustworthy and transparent are more likely to engage, thereby increasing their likelihood of purchase. Moreover, social prestige plays a nuanced role: owning luxury goods is a status marker in China, and buying second-hand might be viewed by some as less prestigious. Thus, consumers with strong prestige orientation might be hesitant unless the platform experience and community normalise second-hand buying as innovative and fashionable. Generational differences emerge here: younger consumers tend to be more open to second-hand luxury, seeing it as trendy and eco-conscious, whereas older consumers may still prefer new products to maintain face and status. These nuances imply that channel engagement is not just a technical interaction metric but is intertwined with trust and cultural acceptance—an engaged consumer is likely to trust the platform and feel comfortable within the resale community. Future studies could examine in greater depth how factors such as perceived authenticity, platform satisfaction, and community belonging contribute to engagement, and how different age or lifestyle segments of consumers engage differently. By interpreting our results in light of China’s cultural context and comparing them to Western findings, we provide a richer understanding of why Chinese pre-loved luxury buyers behave as they do and how digital engagement and cultural values intersect to shape those behaviours.

5.1. Theoretical Contributions

This research makes several significant theoretical contributions. First, it extends and refines existing luxury consumption frameworks by integrating digital channel engagement into the process, linking perceptions of luxury value to purchase behaviour. Traditional luxury value models emphasise how value dimensions—functional, economic, social, and individual—shape consumers’ intentions. Our study adds a new layer by demonstrating that, in the context of an online circular economy, these value–intention relationships are mediated by consumer engagement with the resale channel. This bridges the luxury value literature with research on digital consumer engagement and clarifies that value perceptions do not automatically translate into action unless consumers actively participate in the platform environment. The mediating role of engagement, therefore, sharpens theoretical understanding of the mechanism through which motivations convert into behaviour in digital resale settings.

Second, the study expands luxury consumption theory into a non-Western, digitally advanced market context. Luxury consumer behaviour theories have been primarily built on Western or primary-market (new-product) consumption. Focusing on Chinese consumers of pre-owned luxury tests the robustness of these frameworks under different cultural and technological conditions. The dominance of functional and economic motivations and the comparatively weaker hedonic influences reflect cultural attitudes toward second-hand goods and a market that is still maturing in its acceptance of resale. This highlights the role of culture, social norms, and market maturity as moderating influences, and suggests that luxury value frameworks must be contextualised when applied outside Western consumption settings. At the same time, incorporating channel engagement into the model aligns luxury consumption theory with technology acceptance and engagement perspectives, showing that consumer–technology interaction is now central to understanding luxury behaviours.

Third, incorporating channel engagement as a mediator opens new theoretical pathways. The results suggest that engagement, or related constructs such as involvement, flow, and immersion, should be considered core elements in future models of digital consumption. Our findings also point to likely antecedents of engagement—such as trust in platform authenticity, ease of use, and community influence—which were not modelled here but merit inclusion in future theoretical extensions. Engagement emerges as a pivotal process variable in digital luxury consumption, prompting scholars to examine moderating factors such as cultural values, technological familiarity, digital literacy, and brand attachment. These factors could influence the strength of the engagement mechanism and provide a richer understanding of its role in the consumer decision-making process. Taken together, the study refines, extends, and integrates elements of luxury value theory and digital engagement, contributing a more nuanced theoretical foundation for understanding consumer behaviour in technology-mediated luxury recommerce markets.

5.2. Managerial Implications

The findings offer clear guidance for luxury brands, resale platforms, and industry stakeholders seeking to strengthen consumer adoption in China’s rapidly expanding pre-loved luxury market. Strategies should closely align with the empirical results, particularly regarding the importance of engagement, trust, functional value, and economic value. A key priority is to enhance digital engagement. Since channel engagement plays a central role in converting perceived value into purchase intention, platforms should focus on features that deepen interaction and immersion. Personalised interfaces, AI-driven recommendations, interactive live streams, virtual try-on functions, and community features that encourage users to share reviews or styling content can all increase time spent on the platform and foster repeated engagement. A richer digital experience helps to move consumers from initial interest to eventual purchase.

Equally important is building trust and assuring authenticity. Trust is foundational in China’s online luxury resale market, given concerns about counterfeits and misrepresented product conditions. Platforms should therefore reinforce authenticity guarantees through transparent verification processes, third-party certificates, detailed condition reports, and secure return and refund policies. Visible authenticity markers, robust dispute-resolution systems, and responsive customer service help reduce perceived risk. Luxury brands entering the resale ecosystem can further enhance trust by certifying pre-owned products or establishing official brand-backed resale channels. Alongside trust, marketing communications should emphasise functional value and smart financial benefits. Highlighting durability, craftsmanship, quality, and strong price–value ratios, supported by tools such as price comparisons, evidence of value retention, and alerts for price drops, aligns directly with the functional and economic motivations identified in the study. Positioning pre-loved luxury as a financially savvy and practical choice strengthens both confidence and purchase intention.

At the same time, there is considerable opportunity to strengthen symbolic and experiential appeal. Although functional and economic motivations currently dominate, enhancing symbolic (status-related) and hedonic (experiential) value can help broaden the consumer base. Storytelling that emphasises heritage, rarity, or celebrity provenance can raise the perceived prestige of pre-loved items. At the same time, curated collections and collaborations with influencers can reposition resale as aspirational rather than purely utilitarian. Virtual pop-up events, themed campaigns, and engaging social content can make the process of hunting for pre-owned luxury more enjoyable and socially visible, thereby further boosting engagement. Finally, hybrid retail approaches and policy support can play an essential reinforcing role. Integrating online and offline strategies—such as offering physical authentication services, pick-up points, or in-store preview opportunities—can provide additional reassurance to cautious buyers. At the sector level, policymakers and industry associations can strengthen the market by developing standardised authentication and grading systems. Voluntary adoption of high standards or certification schemes by resale platforms would enhance market credibility and support the sustainable growth of China’s luxury resale ecosystem.

5.3. Limitations and Future Research

Although this study provides valuable insights into the drivers of pre-loved luxury consumption in China, several limitations should be acknowledged. First, the quantitative results are based on a cross-sectional, self-reported survey, which limits causal inference and may be influenced by common-method bias. Future studies could employ longitudinal designs to track changes in motivations, engagement patterns, and purchase behaviours over time, or use experimental methods to test how specific platform features influence channel engagement and trust.

Second, the sample is restricted to Chinese consumers, a group embedded in a distinctive sociocultural and digital environment. While this focus enables an in-depth understanding of China’s rapidly evolving resale market, it limits generalisability. Future research should conduct cross-cultural comparisons. For instance, examining luxury resale behaviours in Japan, South Korea, Europe, or the United States, to identify which findings are culturally specific and which are globally applicable. Such comparative studies could reveal how cultural norms related to prestige, sustainability, or second-hand consumption influence the value–engagement–intention mechanism.

Third, the present model focuses on key luxury value motivations and a single mediator—channel engagement. This provides theoretical clarity but leaves space for incorporating additional factors. Variables such as trust, perceived authenticity, perceived risk, and platform satisfaction may act as mediators or moderators shaping purchase intention. Similarly, digital literacy, age, gender, and brand attachment may moderate engagement or alter the strength of motivation–value relationships. Future studies could expand the model by integrating these constructs to better capture behavioural complexity.

Finally, although the study included a qualitative phase, qualitative research could be extended to explore deeper psychological, emotional, or symbolic narratives underlying luxury recommerce. More in-depth ethnographic or interview-based studies could uncover motivations or barriers, such as face consciousness, stigma, or emotional attachment, that are not readily captured by structured surveys.

Together, these future research opportunities can refine and extend the understanding of digital engagement and value-based decision-making in luxury resale markets.

6. Conclusions

This study offers a comprehensive examination of the motivational, perceptual, and behavioural factors influencing Chinese consumers’ engagement with pre-loved luxury fashion. The findings demonstrate that perceptions of functional and economic value play central roles in shaping intention, while channel engagement serves as a crucial mediator linking perceived value to purchase intention. This highlights a key insight into digital resale environments: consumer engagement with the platform is a pivotal factor in determining whether initial motivations translate into behaviour.

The study contributes to theory by extending luxury value frameworks into the digital, circular economy context and by establishing channel engagement as a process variable that bridges motivation and behavioural intention. It also provides practical implications for brands and platforms—emphasising the importance of trust-building, assurance of authenticity, digital experience design, and communication strategies tailored to Chinese consumer expectations.

While contextual and methodological limitations temper the study’s generalisability, the findings present meaningful patterns that can serve as a foundation for future work. As the luxury recommerce industry continues to evolve, driven by changes in consumer attitudes, technological innovation, and cultural trends, further research will be essential. Advances such as AI-powered personalisation, blockchain-based authentication, and virtual/augmented reality shopping environments are likely to reshape how consumers interact with resale platforms. Understanding how these technologies influence channel engagement, trust, and perceived value will be critical for both scholars and practitioners.

In summary, this research deepens the understanding of Chinese consumers’ adoption of pre-loved luxury. It provides a theoretical and practical foundation for exploring the growing role of digital engagement in the luxury resale ecosystem. It offers a starting point for future studies across cultures, technologies, and market conditions, contributing to the broader conversation on sustainable consumption and digital-era luxury behaviour.