This study aims to explore the impact of various factors on consumer responses to apparel resale programs in the USA, using the stimulus-organism-response model. It investigates how product quality (PQ), information quality (IQ), brand image (BI) and promotional efforts (PE) influence consumer behavior, and examines the moderating role of consumer environmental knowledge (CEK).
A survey was conducted among US consumers familiar with apparel resale programs. The research model integrated constructs like product satisfaction (PS), brand trust (BT), perceived utilitarian and hedonic values as responses to external stimuli and purchase intention, brand loyalty (BL) and word-of-mouth (WOM) as subsequent behaviors. Multiple regression analysis was used to test the hypothesized relationships.
The study reveals that PQ significantly influences consumer satisfaction and utilitarian value, but not BT or hedonic value, while IQ enhances consumer satisfaction, trust and perceived values. BI and PE improve all consumer responses, with CEK moderating these effects. Notably, consumer PS strongly drives purchase intentions but not BL; BT enhances loyalty and WOM without directly affecting purchase intentions. Both perceived utilitarian and hedonic values positively impact purchase intentions and BL, highlighting their importance in motivating consumer behaviors within apparel resale programs.
The findings can assist retailers and marketers in effectively designing and promoting apparel resale programs. Emphasizing high-quality products and trustworthy information can significantly enhance consumer trust and satisfaction. Moreover, understanding the role of environmental knowledge can help tailor marketing strategies to better meet consumer expectations and enhance engagement.
This study advances the literature on sustainable consumer behavior and circular fashion by identifying how distinct marketing stimuli – PQ, IQ, BI and PE shape consumer cognition, emotions and behavioral responses in apparel resale contexts, and by revealing the moderating role of environmental knowledge in these relationships.
1. Introduction
The fashion industry is typified by swiftly shifting trends, the mass production of low-cost items and brief product life cycles. Such practices promote unsustainable consumption habits and encourage the frequent disposal of clothing that remains in good condition (Garcia-Ortega et al., 2023; Teixeira et al., 2023). Despite advancements in technology and science enhancing product reliability and durability, the prevailing business model in fashion significantly shortens these products’ lifespans, thus undermining the potential benefits of technological improvements (Lv et al., 2021). This paradox underscores the urgent need for a business model that minimizes waste and alters consumer disposal behaviors.
In response, numerous prominent US brands have introduced resale programs, wherein returned, exchanged or donated apparel is resold at a discount. For example, Patagonia’s “Worn Wear” program offers customers gift cards in exchange for their used items, which are then assessed and resold on its Worn Wear website at reduced prices (Hirsh, 2022). Similar initiatives have been adopted by brands such as Lululemon, Nordstrom, The North Face, REI, Eileen Fisher, Athleta and Outerknown. A thorough understanding of consumer behavior toward these resale programs is vital for the success of this nascent business model (Lou et al., 2022).
In addition, the concept of circular business models (CBMs), which promote sustainable approaches like refurbishment, repair, remanufacturing and restoration to extend product life cycles, has been increasingly discussed (Gomes et al., 2022). Soyer and Dittrich (2021) introduced the “R’s” – refuse, reduce, resell, reuse, repair, refurbish, remanufacture, repurpose, recycle, recover and remain – as principles of sustainable consumption. While the importance of these practices in fostering a circular economy is recognized, their impact on consumer purchase intentions remains underexplored. Furthermore, many studies have applied the value-belief-norm theory, focusing predominantly on internal consumer values and overlooking significant external factors like cost, which are crucial to sustainability (Batool et al., 2024; Fornara et al., 2016; Ganak et al., 2020; Gomes et al., 2022).
This study aims to bridge these gaps by using the stimulus-organism-response (S-O-R) model to develop a conceptual framework that investigates factors influencing purchase intentions toward refurbished, reconditioned, repaired and resold apparel. The S-O-R model, with its focus on external stimuli and their impact on consumer internal states and subsequent behaviors, is well-suited for this analysis (Sultan et al., 2021; Tymoshchuk et al., 2024). This research seeks to delve into consumer cognition and emotions such as product satisfaction (PS), brand trust (BT), perceived utilitarian value (PUV) and perceived hedonic value (PHV) in response to apparel resale programs, taking into account product quality (PQ), information quality (IQ), brand image (BI) and promotional efforts (PE) as stimuli. In addition, this study examines the moderating role of consumer environmental knowledge (CEK) in these relationships. The objectives of this study are fourfold:
to analyze the emerging business model of reselling reconditioned apparel;
to elucidate how various stimuli affect consumer responses and subsequent behaviors like purchase intention, brand loyalty (BL) and word-of-mouth (WOM);
to explore the moderating effect of CEK; and
to offer actionable insights for apparel brands and retailers on effectively marketing apparel resale programs.
This study makes several key contributions to the literature on sustainable consumption and circular fashion. First, it extends the application of the S-O-R framework to the underexplored domain of branded apparel resale programs, offering a nuanced understanding of how specific external stimuli such as PQ, IQ, BI and promotional strategies influence consumers’ internal evaluations and purchase intentions. Second, it distinguishes between cognitive and affective responses as mediators, providing empirical support for their differential roles in shaping behavioral outcomes within resale contexts. Third, the study identifies environmental knowledge as a significant moderating variable, offering insights into how individual differences in sustainability awareness condition consumer responses to resale program attributes. Collectively, these contributions deepen our understanding of the psychological mechanisms driving participation in apparel resale and inform strategies for retailers seeking to design more effective and consumer-responsive resale initiatives.
2. Literature review
2.1 Stimulus organism response (S-O-R) model
The theoretical foundation of this study is based on the S-O-R framework. Originally conceptualized by Mehrabian and Russell (1974) in an environmental psychology study, the S-O-R model has been extensively applied in various contexts, including retail and consumer behavior (Chang et al., 2011; Chebat and Michon, 2003). It has also been widely used in sustainable fashion research to explain topics such as social sustainability, brand attachment, perceived social responsibility, green adoption behavior, green BI and transparency (Amaya Rivas et al., 2022; Grădinaru et al., 2022; Rahman and Nguyen-Viet, 2022). Given its successful application in previous studies, the S-O-R model is well-suited for the current research.
In the S-O-R model, the Stimulus refers to external factors that elicit responses from the study group. The organism represents the individual’s cognitive and affective reactions, which then lead to their response (Donovan and Rossiter, 1982). Building on the S-O-R framework, this study proposes 12 constructs, including one moderator, to identify the determinants of US consumers’ behavioral responses toward apparel resale programs. The stimulus constructs include PQ, IQ, BI and PE, which are external to the consumer and influence the organism’s role in the model (Bagozzi, 1986). The moderator in this study is CEK, which could affect the relationships between the stimulus constructs and organism constructs (Bhandari, 2022). The organism constructs consist of PS, BT, PUV and PHV. These variables then elicit a response, measured in terms of purchase intention, BL and WOM.
Previous studies have used the S-O-R model to investigate brands and their sustainable positioning, influencing purchase intention, technology adoption and WOM within the retail context (Chang and Jai, 2015; Loureiro et al., 2019; Mehrabian and Russell, 1974). Given its effectiveness in past retail studies and its relevance to similar elements, the S-O-R model is used in the present study to investigate apparel resale programs, a focus that has not been extensively explored in prior literature.
2.2 Stimulus: product quality
PQ is a crucial factor for consumers during the decision-making process (Chen and Chi, 2024). Zeithaml (1998) defines PQ as a consumer’s judgment about the superiority or excellence of a product. High PQ meets or exceeds consumer expectations, leading to greater satisfaction (Konuk, 2018). Intrinsic cues such as durability and fabric type, and extrinsic cues such as brand reputation and price, are critical in forming consumers’ quality perceptions (Zanjirani Farahani et al., 2022). Remanufactured apparel refers to items that have been previously owned or used and then restored to a like-new condition by the original brand or an authorized third party through processes such as cleaning, repairing or reconditioning before being reintroduced to the market for resale (Abbey et al., 2015). In apparel resale programs, the perceived quality of these remanufactured products plays a crucial role in shaping consumer responses, which can either reassure or deter potential buyers. As Abbey et al. (2015) pointed out, when the quality of remanufactured apparel aligns with consumer expectations, it enhances satisfaction and fosters repeat purchases. Similarly, Vedantam et al. (2021) emphasize that PQ and durability are essential components of a successful resale model in the fashion industry.
BT is another essential outcome of perceived PQ. Consumers tend to trust brands that consistently deliver high-quality products (Tian et al., 2022). In the apparel resale market, maintaining high PQ is crucial for building and sustaining BT. When consumers believe that a resale brand offers reliable and excellent products, their trust in the brand increases (He et al., 2016). This trust is pivotal for the long-term success of resale programs, as it fosters customer loyalty and positive WOM (Loureiro et al., 2019). Therefore, ensuring PQ in resale items can significantly enhance BT.
PUV refers to the practical benefits and functionality that consumers derive from a product (Chang et al., 2011). High-quality products often exhibit superior performance, durability and functionality, contributing to higher utilitarian value (Bagozzi, 1986). In the resale apparel context, consumers are likely to value products that offer substantial utility, such as lasting wear and versatility. Konuk (2018) posits that consumers are more inclined to purchase and value resale products if they perceive them to be of high quality and functional utility. This PUV is a strong determinant of purchase intention in the resale market.
PHV pertains to the experiential and emotional benefits that consumers gain from a product (Chi and Kilduff, 2011). High-quality apparel can provide aesthetic pleasure, comfort and a sense of pride in ownership, thereby enhancing the hedonic value (Rahman and Nguyen-Viet, 2022). In the context of apparel resale programs, consumers may derive joy from finding high-quality, unique or vintage items that stand out from mass-produced fast fashion (Grădinaru et al., 2022). The emotional satisfaction associated with high-quality resale items can drive consumer preference and loyalty (Amaya Rivas et al., 2022).
Integrating PQ into apparel resale programs is vital for meeting consumer expectations, building BT and enhancing both utilitarian and hedonic values. This comprehensive approach can drive consumer engagement and support the sustainability goals of the fashion industry. Thus, the following hypotheses are proposed:
Product quality in the apparel resale program positively affects (a) consumer product satisfaction, (b) brand trust, (c) perceived utilitarian value and (d) perceived hedonic value.
2.3 Stimulus: information quality
IQ measures the usefulness, accuracy and timeliness of information (Tian et al., 2022). High-quality information helps consumers make informed decisions, reducing uncertainty and increasing satisfaction with their purchases. In apparel resale programs, detailed and accurate product descriptions are crucial for setting realistic consumer expectations. When consumers receive items in the condition described, their satisfaction levels increase, enhancing their overall shopping experience (Park et al., 2012). Kim and Niehm (2009) found that perceived IQ significantly impacts consumers’ perceived value of retailers, directly applying to online apparel resale programs. Reliable and comprehensive information about resale items reassures consumers about their purchase decisions, thereby increasing satisfaction.
BT is heavily influenced by the quality of information provided by retailers. Consumers are more likely to trust a retailer that consistently provides accurate and detailed product information (Zhou, 2011). In the apparel resale market, accurate descriptions and images reflecting the condition and features of the items strengthen consumers’ trust in the brand. Zhang and Zhao (2021) noted that resale programs benefit significantly from reliable and high-quality information sharing, reducing the risk of dissatisfaction and returns. Pretner et al. (2021) further support this by demonstrating that information about the environmental benefits of second-hand products can enhance consumer trust and willingness to purchase.
High-quality information helps consumers assess the practical benefits of a product more accurately (Chang et al., 2011). In apparel resale programs, detailed descriptions of fabric type, size and wear and tear allow consumers to judge the utility of the products effectively (Kim and Niehm, 2009). When consumers rely on the provided information to make practical purchase decisions, the PUV of the products increases. This reliability in information helps consumers find items that meet their functional needs, making them more likely to engage in resale shopping.
High-quality information enhances the shopping experience by providing engaging and appealing product narratives and visuals. Detailed stories about the uniqueness or history of a resale item add to its emotional appeal, making the shopping experience more enjoyable (Rahman and Nguyen-Viet, 2022). Accurate and appealing product information creates a sense of excitement and satisfaction, contributing to higher PHV. Pretner et al. (2021) found that when consumers are informed about the positive environmental impact of their purchases, their emotional satisfaction and perceived value increase. Therefore, the following hypotheses are proposed:
Information quality in the apparel resale program positively affects (a) consumer product satisfaction, (b) brand trust, (c) perceived utilitarian value and (d) perceived hedonic value.
2.4 Stimulus: brand image
BI significantly influences consumers’ perceptions and behaviors toward a brand, encompassing the overall impression formed by consumer experiences, associations and beliefs (Veloutsou, 2015). A positive BI helps consumers distinguish a brand from its competitors, facilitating purchase decisions (Lien et al., 2015). When consumers associate a brand with positive attributes such as quality, reliability and sustainability, their satisfaction with purchases increases (Munir, 2020). This satisfaction arises from the assurance that resale products will meet expectations and align with the brand’s reputation.
Trust is built through consistent positive interactions with a brand, reinforcing consumers’ belief in the brand’s reliability and integrity (Tian et al., 2022). In apparel resale programs, a strong BI enhances trust by assuring consumers of the quality and authenticity of resale items (Abbey et al., 2015). Consumers purchasing used products from well-known brands often rely on the brand’s reputation for quality and reliability. Previous research shows a strong correlation between BI and trust in various contexts, including online hotel bookings (Lien et al., 2015; Lou et al., 2022).
A strong BI enhances PUV by assuring consumers of the product’s quality and functionality (Jin et al., 2012). In apparel resale programs, brands known for their durable and high-quality products instill confidence that resale items offer similar practical benefits. This assurance leads to a higher PUV, making consumers more likely to purchase resale apparel. A strong BI elevates PHV by fostering a sense of pleasure and satisfaction in owning and using the product (Chebat and Michon, 2003). Consumers may gain emotional fulfillment from buying resale items from a brand they respect and trust, knowing their purchase promotes sustainability and aligns with their personal values. This emotional bond substantially increases the PHV of resale products (Rahman and Nguyen-Viet, 2022). Thus, the following hypotheses are proposed:
Brand image in the apparel resale program positively affects (a) consumer product satisfaction, (b) brand trust, (c) perceived utilitarian value and (d) perceived hedonic value.
2.5 Stimulus: promotional efforts
PE, defined as marketing activities to boost sales and brand recognition, are crucial for the success of apparel resale programs (Musfar, 2019). These efforts facilitate communication with customers, provide information and establish a connection between consumers and the company (Rindi et al., 2021). Promotion uses various strategies to inform and persuade consumers about products and services, encouraging purchases (Rinnanik et al., 2021). By aligning offerings with consumer needs, promotional activities can significantly enhance consumer purchase behavior and product knowledge (Faizani and Prihatini, 2020).
Many companies now use green narratives in their promotions to attract younger, environmentally-conscious consumers who prefer sustainable products (Cloud, 2014). Fashion brands increasingly highlight the sustainability of their apparel and its role in a circular economy (Fletcher, 2008). Terms like green, natural, organic, eco and sustainable are common in brand names, advertisements, product labels and websites (Fairclough, 2001). By promoting a circular economy, companies can shift consumer preference toward sustainable fashion over fast fashion (Peleg Mizrachi and Tal, 2022). Campaigns like “Loved Clothes Last” by Fashion Revolution, LoveNotLandfill by London Waste and the 6 Item Challenge by Labor Behind the Label encourage sustainable shopping habits and educate consumers on extending the life of garments and choosing resale items (Brydges et al., 2020).
Research shows that PE can have varying psychological effects on consumers, depending on whether they are monetary or non-monetary (Chandon et al., 2000). Monetary promotions offer utilitarian benefits like cost savings and value enhancement, while non-monetary promotions provide hedonic benefits such as entertainment and the excitement of exploring resale garments (Büttner et al., 2015). Consumer satisfaction can result from goal-oriented and monetary promotions, as they perceive the brand as helping achieve their shopping goals (Mathwick et al., 2001).
In apparel resale programs, PE are expected to positively influence consumer satisfaction, BT and perceived value. By effectively communicating the benefits of resale items and aligning them with consumer values, promotional strategies can enhance the overall consumer experience and drive positive behavioral outcomes. Thus, the following hypotheses are proposed:
Promotional efforts in the apparel resale program positively affect (a) consumer product satisfaction, (b) brand trust, (c) perceived utilitarian value and (d) perceived hedonic value.
2.6 Moderating effect: consumer environmental knowledge
CEK is defined as an individual’s ability to understand the impact of their actions on both society and the ecosystem (Kaplan, 1991). This knowledge can foster environmentally conscious behaviors, influencing how consumers use, acquire and dispose of apparel (Haron et al., 2005). When consumers lack this knowledge, they may be confused about the environmental benefits of resale garments, reducing their likelihood to participate in resale programs (Kaplan, 1991). Conversely, increased knowledge of environmental elements can lead to positive attitudes toward sustainable living and enhance sustainable purchase intentions (Moisander, 2000).
Environmental knowledge can act as a moderating variable that influences the relationship between various stimuli and consumer outcomes. This moderation occurs because knowledgeable consumers are better equipped to understand and appreciate the environmental benefits of high-quality products, reliable information, positive BI s and targeted PE. They are more likely to respond positively to these stimuli, enhancing their satisfaction, trust and perceived value of the products and brands they engage with.
The impact of PQ on consumer outcomes can be amplified when consumers have high environmental knowledge. These consumers are more likely to recognize and appreciate the sustainability aspects of high-quality products, further enhancing their satisfaction and trust (Abbey et al., 2015; Zanjirani Farahani et al., 2022). For consumers with high environmental knowledge, a positive BI associated with sustainability can significantly enhance their satisfaction and trust in the brand. These consumers are more likely to support brands that align with their environmental values, leading to stronger perceived utilitarian and hedonic values (Munir, 2020; Abbey et al., 2015). The consumers with better environmental knowledge are more likely to respond positively to green marketing efforts, resulting in higher satisfaction, trust and perceived value (Cloud, 2014; Peleg Mizrachi and Tal, 2022). Thus, the following hypotheses are proposed:
Consumer environmental knowledge moderates the effects of stimuli (product quality, information quality, brand image and promotional efforts) on organisms (consumer product satisfaction, brand trust, perceived utilitarian value and perceived hedonic value).
2.7 Responses: purchase intention, brand loyalty and word-of-mouth (WOM)
Purchase intention is a behavior that drives individuals to buy a product (Rezvani et al., 2012) and can be understood as the psychological inclination to make a purchase (Lin and Lu, 2010). It reflects the perceived likelihood of purchasing a repurposed product, indicating loyalty to a specific brand or group of brands (Rezvani et al., 2012). Some studies define purchase intention simply as consumers’ interest and attitude toward buying a product (Lv et al., 2021). Various internal and external factors influence purchase intention. External factors include PQ, PS and product value. Internal factors encompass perceived values such as utilitarian and hedonic value, as well as BT. Research has shown that PS, BT and perceived value are crucial in shaping consumers’ purchase intentions (Tsiotsou, 2006; Wang et al., 2014; Tian et al., 2022).
BL represents a deeply held commitment to a product or service (Oliver, 1999). It comprises both attitudinal and behavioral dimensions. The attitudinal dimension encompasses overall satisfaction with the sustainable apparel product, while the behavioral dimension involves the consumer’s willingness to repeatedly purchase from the same brand (Dick and Basu, 1994; Neal and Strauss, 2008). In essence, the attitudinal dimension reflects how consumers feel about the product, whereas the behavioral dimension is measured by the frequency of past purchases and potential future buying behavior based on these experiences (Alhaddad, 2015). Understanding the determinants of BL is crucial for businesses, particularly in the sustainable apparel sector, as fostering strong BL can lead to increased consumer retention and advocacy (Tanveer et al., 2021).
Information exchange encompasses several approaches, with personal conversations being one of the primary methods. This personal approach, known as WOM, significantly influences consumers’ thoughts, choices and decision-making processes. WOM is a critical factor in shaping consumer behavior, as this form of oral communication can sway consumers in both positive and negative directions (Sweeney et al., 2012; Pereira et al., 2017). Positive WOM can enhance consumer loyalty, stimulate purchase intentions and increase consumer awareness. Conversely, negative WOM can deter potential buyers and damage brand reputation (Salem and Alanadoly, 2021). The impact of WOM is particularly crucial because it can influence consumers’ decisions before the actual purchase takes place. Post-purchase satisfaction also plays a role in WOM, as satisfied consumers are likely to share their positive experiences, thereby influencing the opinions and behaviors of others (Tymoshchuk et al., 2024). In addition, the feedback received through WOM can further shape overall consumer satisfaction and future WOM responses (Huete-Alcocer, 2017). In the context of sustainable products, WOM allows for the dissemination of information in various settings and for diverse reasons. For instance, WOM can enhance consumers’ awareness of sustainability issues, as highlighted by Salem and Alanadoly (2021). This type of information exchange is essential for promoting sustainable practices and products:
2.8 Organism: consumer product satisfaction
Consumer PS, defined as the cognitive evaluation of the level of function or performance and quality of the fashion products purchased (Oliver, 1999), is a pivotal element in consumer behavior. Achieving satisfaction is a primary goal for consumers, motivating them to spend their monetary resources (Lou et al., 2022). Properly marketed products can significantly enhance BL, store loyalty and the frequency of purchases (Kincade et al., 1992). When consumers are satisfied with the resale products they buy, they are likely to share their positive experiences with friends and family through WOM, leading to increased sales and a stronger brand reputation (Lou et al., 2022). In addition, satisfied consumers tend to use products longer, which aligns with sustainable practices and offers a significant opportunity for sustainable resale brands to thrive (Niinimäki, 2014).
For consumers to find satisfaction in resale products, these items need to be durable and long-lasting, especially since they have already been used. An example of this is Patagonia’s Worn Wear program, which repairs, resells or recycles used apparel to promote environmental consciousness. By extending the useful life of these products, Patagonia enables consumers to continue benefiting from their utility, thereby reducing the negative impact of fast fashion and enhancing satisfaction with resale apparel (Patagonia, 2023). The extended lifetime of products not only provides more utility but also contributes to environmental sustainability, creating a virtuous cycle of satisfaction and responsible consumption (Fletcher, 2008).
Previous research underscores the central role of satisfaction in marketing efforts for resale products, identifying it as a key predictor of purchase intention. Consumers have both pre-purchase and post-purchase expectations, and when a product meets or exceeds these expectations, it positively affects purchase intention, BL and WOM. This connection highlights the importance of delivering high-quality, satisfying products to foster consumer loyalty and advocacy. Thus, this study proposes the following hypotheses:
Consumer product satisfaction positively affects (a) their purchase intention, (b) brand loyalty and (c) word of mouth.
2.9 Organism: brand trust
BT is an essential component in building and maintaining long-term relationships with customers, as it reduces uncertainty by fulfilling promises and providing consistent product performance (Hegner and Jevons, 2016). When consumers perceive safety, honesty and reliability in a brand, their trust in the brand increases (Doney and Cannon, 1997). This trust is often formed through direct experiences with the brand. Research has consistently shown that BT is a crucial predictor of BL. Bilgihan’s (2016) study highlighted BT as the strongest predictor of BL, while other studies recognized it as a key variable in maintaining long-term customer relationships, which in turn positively affect BL (Matzler et al., 2008; Sung et al., 2010). Huang (2017) emphasized that BT is essential for retaining loyal customers, suggesting that trust directly influences BL. High levels of BT also lead to increased purchase intention (Lau and Lee, 1999). Trust in a retail brand, whether from previous experience or other stimuli, reduces perceived risk associated with purchasing reconditioned apparel, thereby increasing the likelihood of purchase intention. Jones and Kim’s (2010) study demonstrated that retail BT significantly influenced shopping intention when purchasing apparel online. These findings underline the importance of BT in driving consumer purchase behaviors.
Moreover, there is evidence to suggest that BT positively affects WOM. When consumers trust a brand or product, they are more likely to speak positively about it and recommend it to friends and family. Although there is a gap in the literature specifically examining the relationship between BT and WOM for reconditioned apparel products, it is reasonable to infer that high levels of BT will positively influence consumer WOM. This is because trust fosters a positive perception and satisfaction with the brand, encouraging consumers to share their positive experiences. Thus, this study proposes the following hypotheses:
Brand trust positively affects (a) consumer purchase intention, (b) brand loyalty and (c) word of mouth.
2.10 Organism: perceived utilitarian value
PUV plays a significant role in shaping consumer behavior and decision-making. It refers to the consumer’s evaluation of the practical and functional benefits of a product, considering factors such as cost, utility and overall effectiveness (Overby and Lee, 2006). When products align with consumers’ utilitarian values, they are perceived as meeting practical needs efficiently and effectively.
Research has shown that utilitarian value is a crucial determinant of purchase intention. Gan and Wang (2017) found that both utilitarian and hedonic values significantly influence purchase intentions. Consumers differentiate between these values and tend to choose products that align with their utilitarian goals, especially when the products meet their practical needs (Lou et al., 2022). Guo and Li’s (2022) study demonstrated that utilitarian value is more likely to influence repurchase intention than hedonic value, highlighting its importance in consumer decision-making.
High levels of PUV also contribute to BL. Jones et al. (2006) argued that greater perceptions of utilitarian shopping value correlate with higher BL. When consumers find that a product consistently meets their practical needs, they are more likely to remain loyal to the brand and less likely to purchase similar products from competitors. This loyalty is driven by the product’s ability to deliver functional benefits reliably.
Furthermore, PUV can positively affect WOM. Although direct studies linking PUV to WOM are limited, related research provides valuable insights. Ryu et al. (2010) found that both utilitarian and hedonic values positively affect recommendation intentions in the fast food industry. Similarly, Bae and Jeon (2022) discovered that utilitarian values significantly enhance customer BL and WOM. These findings suggest that when consumers perceive high utilitarian value in a product, they are more likely to recommend it to others. Therefore, this study proposes the following hypotheses:
Perceived utilitarian value positively affects (a) consumer purchase intention, (b) brand loyalty and (c) word of mouth.
2.11 Organism: perceived hedonic value
Unlike utilitarian value, which focuses on functional benefits, hedonic value emphasizes psychological needs and the emotional satisfaction that consumers gain from their purchases (Roy and Ng, 2012). Consumers motivated by hedonic value seek shopping experiences that provide fun, happiness, joy and excitement (Chi and Kilduff, 2011). When making purchasing decisions, they consider the feelings of pleasure and enjoyment they might gain, as well as the opportunity to escape reality (Jong and Hartmans, 2010). This emotional connection to products enhances their overall shopping experience, making them more likely to develop a strong attachment to the brand.
Research supports the positive impact of hedonic value on purchase intention. Chitturi et al. (2007) introduced the principle of hedonic advantage, explaining that consumers prioritize hedonic benefits when choosing products if their utilitarian needs are already met. Jones et al. (2006) and Wang (2008) confirmed the significant effects of hedonic values on the repeat purchase intention of apparel, highlighting the importance of emotional satisfaction in driving consumer behavior. Studies on virtual try-on and augmented reality (AR) apps have demonstrated that hedonic values positively influence apparel purchase intention (Plotkina and Saurel, 2019; Romano et al., 2020). Meilatinova (2021) further found that consumers require significant hedonic value when forming repurchasing intentions.
Hedonic value also plays a crucial role in BL. When consumers derive pleasure and enjoyment from their shopping experiences, they are more likely to develop a strong emotional attachment to the brand, leading to increased loyalty. This loyalty is not just about repeated purchases but also about the overall positive feelings and satisfaction associated with the brand (Qin et al., 2021).
Furthermore, PHV influences WOM. Consumers who experience high levels of enjoyment and pleasure from their purchases are more likely to share their positive experiences with others. This sharing can take the form of recommendations to friends and family, as well as positive reviews and endorsements on social media. Both hedonic and utilitarian values have been shown to affect WOM and BL, as evidenced by the work of Ryu et al. (2010). Therefore, this study proposes the following hypotheses:
Perceived hedonic value positively affects (a) consumer purchase intention, (b) brand loyalty and (c) word of mouth.
3. Methodology
3.1 Proposed research model
Based on the extensive review of the literature, a research model including all the proposed relationships is illustrated in Figure 1. Consumers’ cognition and emotion (i.e. PS, BT, PUV and PHV) toward apparel resale programs are affected by PQ, IQ, BI and PE as stimuli and consequently, consumers’ internal states affect their behavioral responses in terms of purchase intention, BL and WOM. CEK plays a moderating role between the stimulus constructs (PQ, IQ, BI, PE) and the organism constructs (PS, BT, PUV, PHV). The demographic variables, including age, gender, income level and education level are included as control factors.
The conceptual diagram consists of three main blocks labelled Stimuli, Organism, and Responses, connected with directional arrows. The Stimuli block includes product quality, information quality, brand image, and promotional efforts. These connect to the Organism block, which includes product satisfaction, brand trust, perceived utilitarian value, and perceived hedonic value. Arrows then lead to the Responses block containing purchase intention, brand loyalty, and word of mouth. An additional element, consumer environmental knowledge, is positioned centrally below and linked to both the Stimuli and Organism blocks, suggesting a mediating effect. Hypotheses are indicated using labels such as H1, H2, and H3 between the elements.Proposed research model
Source: Authors’ own work
The conceptual diagram consists of three main blocks labelled Stimuli, Organism, and Responses, connected with directional arrows. The Stimuli block includes product quality, information quality, brand image, and promotional efforts. These connect to the Organism block, which includes product satisfaction, brand trust, perceived utilitarian value, and perceived hedonic value. Arrows then lead to the Responses block containing purchase intention, brand loyalty, and word of mouth. An additional element, consumer environmental knowledge, is positioned centrally below and linked to both the Stimuli and Organism blocks, suggesting a mediating effect. Hypotheses are indicated using labels such as H1, H2, and H3 between the elements.Proposed research model
Source: Authors’ own work
3.2 Data collection and sampling
The initial survey instrument underwent a thorough review by experienced faculty members in the field. Following this, it was pretested with graduate students. Feedback from both the faculty and the graduate students was instrumental in refining the survey, focusing on aspects such as layout, wording precision and relevance. This iterative process enhanced the validity and clarity of the final survey instrument. The main data were collected through an online survey questionnaire using Qualtrics. Using random sampling, this link was uploaded to Amazon Mechanical Turk to receive responses from US consumers familiar with apparel resale programs. An advantage of online survey methods is the ability to receive representative samples in a short response time (Dillman et al., 2014). To ensure the consumers are from the USA and have familiarity with apparel resale programs, screening questions were implemented and those who do not meet these qualifications were disqualified from the survey. A total of 387 eligible responses were received. The profile of survey respondents is presented in Table 1.
Profile of survey respondents
| Category | % |
|---|---|
| Gender | |
| Female | 54 |
| Male | 46 |
| Age | |
| 18–25 | 12 |
| 26–30 | 28 |
| 31–35 | 19 |
| 36–40 | 11 |
| 41–45 | 10 |
| 46–50 | 8 |
| 51–55 | 4 |
| 56 and older | 9 |
| Ethnicity | |
| White/Caucasian | 91 |
| Black/African American | 4 |
| Asian American/Pacific Islander | 1 |
| Latino/Hispanic | 1 |
| Others | 3 |
| Annual resale apparel purchase | |
| $0–199 | 6 |
| $200–499 | 26 |
| $500–999 | 27 |
| $1,000–1,499 | 22 |
| $1,500–1,999 | 9 |
| $2,000 and more | 10 |
| Education level | |
| High school diploma | 4 |
| Associate degree/some college education | 2 |
| Bachelor’s degree | 61 |
| Master’s degree | 31 |
| Doctorate degree | 2 |
| Income level | |
| Under $10,000 | 6 |
| $10,000 to $14,999 | 8 |
| $15,000 to $24,999 | 7 |
| $25,000 to $34,999 | 12 |
| $35,000 to $49,999 | 22 |
| $50,000 to $74,999 | 25 |
| $75,000 to $99,999 | 11 |
| $100,000 to $149,999 | 6 |
| $150,000 and more | 3 |
| Annual apparel purchases | |
| $0–199 | 3 |
| $200–499 | 10 |
| $500–999 | 16 |
| $1,000–1,499 | 28 |
| $1,500–1,999 | 18 |
| $2,000–2,499 | 13 |
| $2,500–2,999 | 6 |
| 3,000 and more | 6 |
| Category | % |
|---|---|
| Gender | |
| Female | 54 |
| Male | 46 |
| Age | |
| 18–25 | 12 |
| 26–30 | 28 |
| 31–35 | 19 |
| 36–40 | 11 |
| 41–45 | 10 |
| 46–50 | 8 |
| 51–55 | 4 |
| 56 and older | 9 |
| Ethnicity | |
| White/Caucasian | 91 |
| Black/African American | 4 |
| Asian American/Pacific Islander | 1 |
| Latino/Hispanic | 1 |
| Others | 3 |
| Annual resale apparel purchase | |
| $0–199 | 6 |
| $200–499 | 26 |
| $500–999 | 27 |
| $1,000–1,499 | 22 |
| $1,500–1,999 | 9 |
| $2,000 and more | 10 |
| Education level | |
| High school diploma | 4 |
| Associate degree/some college education | 2 |
| Bachelor’s degree | 61 |
| Master’s degree | 31 |
| Doctorate degree | 2 |
| Income level | |
| Under $10,000 | 6 |
| $10,000 to $14,999 | 8 |
| $15,000 to $24,999 | 7 |
| $25,000 to $34,999 | 12 |
| $35,000 to $49,999 | 22 |
| $50,000 to $74,999 | 25 |
| $75,000 to $99,999 | 11 |
| $100,000 to $149,999 | 6 |
| $150,000 and more | 3 |
| Annual apparel purchases | |
| $0–199 | 3 |
| $200–499 | 10 |
| $500–999 | 16 |
| $1,000–1,499 | 28 |
| $1,500–1,999 | 18 |
| $2,000–2,499 | 13 |
| $2,500–2,999 | 6 |
| 3,000 and more | 6 |
Note(s): Total 387 eligible responses
Of the 387 respondents, 54% were female and 46% were male. The ages of the respondents ranged from 18 years old to 56 years old, with the highest rate of response (28%) from the 26 to 30-year-old age range. Most of the respondents received a college education with 61% earning a bachelor’s degree, 31% earning a master’s degree, 2% earning a doctorate degree and 2% with an associate degree/some college education. Only 4% of respondents had a high school diploma as the highest level of education. The average annual income level for the respondents ranged from under $10,000 to over $150,000. The reported incomes for under $10,000 was at 6%, 10,000 to $14,99 was at 8%, $15,000 to $24,999 was at 7%, $25,000 to $34,999 was at 12%, $35,000 to $49,999 was at 22%, $50,000 to $74,999 was at 25%, $75,00 to $99,999 was at 11%, $100,000 to $149,000 was at 6% and $150,000 and above was at 3%. In terms of ethnicity, the majority of respondents were White/Caucasian (91%), followed by Black/African American (4%), others (3%), Asian American/Pacific Islander (1%) and Latino/Hispanic (1%). Regarding annual apparel purchases, 3% of respondents reported they spend $0 to $199, 10% spend $200 to $499, 16% spend $500 to $999, 28% spend $1,000 to $1,499, 18% spend $1,500 to $1,999, 13% spend $2,000 to $2,499, 6% spend $2,500 to $2,999 and 6% spend $3,000 or more. When asked about annual resale apparel expenditure, 6% of respondents reported spending $0 to $199, 26% spend $200 to $499, 27% spend $5 to $999, 22% spend $1,000 to $1,499, 9% spend $1,500 to $1,999 and 10% spend $2,000 or more.
3.3 Survey instrument
The study consists of 12 constructs adapted from previous literature. Using the primary data gathered by survey, the relationships between the S-O-R constructs were examined along with CEK as a moderator between the stimulus constructs (PQ, IQ, BI, PE) and the organism constructs (PS, BT, PUV, PHV). PQ is measured with four items adapted from Tian et al. (2022). IQ, BI and PE are each measured with three items adapted from Tian et al. (2022). Four items measure PS adapted from Kang and Park-Poaps (2011). BT is measured with four items adapted from Lau and Lee (1999), while PUV is measured with three items adapted from Yoo et al. (2020). PHV is measured with four items adapted from Voss et al., 2003. Purchase intention is measured with four items adapted from Kumar et al. (2017) and Park and Lin (2018). BL is adapted from Lau and Lee (1999) and Zeithaml et al. (1996) and measured with three items. WOM is measured with three items and adapted from Gremler and Gwinner (2000). CEK was measured with four items adapted from Leclercq-Machhado et al. (2022). Demographics are measured as control factors, including age, gender, education and income. All constructs were measured with a five-point Likert scale ranging from 1 “strongly disagree” to 5 “strongly agree”. Table 2 lists all of the constructs and their corresponding measurement scales.
Constructs and corresponding measurement items
| Construct | Measure and scale | Sources |
|---|---|---|
| Product quality (PQ) | PQ1: Products in apparel resale programs offer good quality [0.797] | Tian et al., 2022 |
| PQ2: Quality is not a concern for products offered by apparel resale programs [Dropped due to low factor loading] | ||
| PQ3: Apparel resale programs provide quality products [0.732] PQ4: I trust product quality in apparel resale programs [0.647] | ||
| Information quality (IQ) | IQ1: The product provides me with sufficient information about my needs [0.831] | Tian et al., 2022 |
| IQ2: I receive accurate information from the website about the product [Dropped due to low factor loading] | ||
| IQ3: Labeling on resell items is clearly understandable [0.831] | ||
| Brand image (BI) | BI1: The brand’s resale program has better characteristics than that of the original products [0.733] | Tian et al., 2022 |
| BI2: The brand’s resale program has a reputation for quality [0.714] | ||
| BI3: The brand’s products are familiar to me [0.730] | ||
| Promotional efforts (PE) | PE1: The marketing of resale fashion leaves me with a positive impression [0.815] | Tian et al., 2022 |
| PE2: Promotion of resale clothing makes me happy [Dropped due to low factor loading] PE3: Promotion of resale clothing brings me good memories [0.815] | ||
| Product satisfaction (PS) | PS1: In general, resale products that I purchase suit my personal style [0.817] | Kang and Park-Poaps, 2011 |
| PS2: In general, resale fashion products that I purchase are stylish and or fashionable [Dropped due to low factor loading] | ||
| PS3: In general, resale fashion products that I purchase improve my image [0.650] PS4: In general, resale fashion products I purchase are good deals [0.0750] | ||
| Brand trust (BT) | BT1: I trust this brand [0.764] | Lau and Lee, 1999 |
| BT2: I feel that I can trust this brand completely [0.700] | ||
| BT3: I cannot rely on this brand [Dropped due to low factor loading] BT4: I feel safe when I buy used apparel from this brand [0.784] | ||
| Perceived utilitarian value (PUV) | PUV1: The use of reconditioned apparel platforms is convenient [0.803] | Yoo et al., 2020 |
| PUV2: The use of reconditioned apparel platforms is pragmatic and economical [Dropped due to low factor loading] | ||
| PUV3: While using apparel resale program, I can easily find the apparel products I need and want [0.803] | ||
| Perceived hedonic value (PHV) | PHV1: Shopping apparel resale program would be fun [0.743] | Voss et al., 2003 |
| PHV2: Shopping apparel resale program would be exciting [0.722] | ||
| PHV3: Shopping apparel resale program would be delightful [0.657] | ||
| PHV4: Shopping apparel resale program would be thrilling [0.705] | ||
| Purchase intention (PI) | PI1: I consider purchasing resale apparel products [0.764] | Kumar et al., 2017; Park and Lin, 2018 |
| PI2: I intend to buy resale apparel instead of conventional apparel in the future [0.711] | ||
| PI3: I might possibly buy resale apparel in the future [0.669] | ||
| PI4: I would consider buying resale apparel if I happen to see them in an online store [0.757] | ||
| Brand loyalty (BL) | BL1: I choose the same resale program whenever I seek resale apparel [0.815] | Lau and Lee, 1999; Zeithaml et al., 1996 |
| BL2: I would like to shop resale apparel from certain brands [Dropped due to low factor loading] | ||
| BL3: I would like to come back to this resale program in the future [0.815] | ||
| Word of mouth (WOM) | WOM1: I say positive things about resale apparel to other people [0.834] | Gremler and Gwinner, 2000 |
| WOM2: I would recommend resale apparel programs to someone who seeks my advice [Dropped due to low factor loading] | ||
| WOM3: I encourage friends and relatives to refer the resale apparel platforms [0.834] | ||
| Consumer environmental knowledge (CEK) | CEK1: I know how to behave sustainably when buying resale clothing [0.763] | Leclercq-Machhado et al., 2022 |
| CEK2: I know how I could lower the ecological harm with my resale shopping behavior [0.657] | ||
| CEK3: I understand how I could reduce the negative environmental consequences with shopping resale apparel [Dropped due to low factor loading] | ||
| CEK4: I understand how to protect the environment in the long-term with my resale shopping behavior [0.781] |
| Construct | Measure and scale | Sources |
|---|---|---|
| Product quality ( | PQ1: Products in apparel resale programs offer good quality [0.797] | |
| PQ2: Quality is not a concern for products offered by apparel resale programs [Dropped due to low factor loading] | ||
| PQ3: Apparel resale programs provide quality products [0.732] PQ4: I trust product quality in apparel resale programs [0.647] | ||
| Information quality ( | IQ1: The product provides me with sufficient information about my needs [0.831] | |
| IQ2: I receive accurate information from the website about the product [Dropped due to low factor loading] | ||
| IQ3: Labeling on resell items is clearly understandable [0.831] | ||
| Brand image ( | BI1: The brand’s resale program has better characteristics than that of the original products [0.733] | |
| BI2: The brand’s resale program has a reputation for quality [0.714] | ||
| BI3: The brand’s products are familiar to me [0.730] | ||
| Promotional efforts ( | PE1: The marketing of resale fashion leaves me with a positive impression [0.815] | |
| PE2: Promotion of resale clothing makes me happy [Dropped due to low factor loading] PE3: Promotion of resale clothing brings me good memories [0.815] | ||
| Product satisfaction ( | PS1: In general, resale products that I purchase suit my personal style [0.817] | |
| PS2: In general, resale fashion products that I purchase are stylish and or fashionable [Dropped due to low factor loading] | ||
| PS3: In general, resale fashion products that I purchase improve my image [0.650] PS4: In general, resale fashion products I purchase are good deals [0.0750] | ||
| Brand trust ( | BT1: I trust this brand [0.764] | |
| BT2: I feel that I can trust this brand completely [0.700] | ||
| BT3: I cannot rely on this brand [Dropped due to low factor loading] BT4: I feel safe when I buy used apparel from this brand [0.784] | ||
| Perceived utilitarian value ( | PUV1: The use of reconditioned apparel platforms is convenient [0.803] | |
| PUV2: The use of reconditioned apparel platforms is pragmatic and economical [Dropped due to low factor loading] | ||
| PUV3: While using apparel resale program, I can easily find the apparel products I need and want [0.803] | ||
| Perceived hedonic value ( | PHV1: Shopping apparel resale program would be fun [0.743] | |
| PHV2: Shopping apparel resale program would be exciting [0.722] | ||
| PHV3: Shopping apparel resale program would be delightful [0.657] | ||
| PHV4: Shopping apparel resale program would be thrilling [0.705] | ||
| Purchase intention ( | PI1: I consider purchasing resale apparel products [0.764] | |
| PI2: I intend to buy resale apparel instead of conventional apparel in the future [0.711] | ||
| PI3: I might possibly buy resale apparel in the future [0.669] | ||
| PI4: I would consider buying resale apparel if I happen to see them in an online store [0.757] | ||
| Brand loyalty ( | BL1: I choose the same resale program whenever I seek resale apparel [0.815] | |
| BL2: I would like to shop resale apparel from certain brands [Dropped due to low factor loading] | ||
| BL3: I would like to come back to this resale program in the future [0.815] | ||
| Word of mouth ( | WOM1: I say positive things about resale apparel to other people [0.834] | |
| WOM2: I would recommend resale apparel programs to someone who seeks my advice [Dropped due to low factor loading] | ||
| WOM3: I encourage friends and relatives to refer the resale apparel platforms [0.834] | ||
| Consumer environmental knowledge ( | CEK1: I know how to behave sustainably when buying resale clothing [0.763] | |
| CEK2: I know how I could lower the ecological harm with my resale shopping behavior [0.657] | ||
| CEK3: I understand how I could reduce the negative environmental consequences with shopping resale apparel [Dropped due to low factor loading] | ||
| CEK4: I understand how to protect the environment in the long-term with my resale shopping behavior [0.781] |
3.4 Data analysis methods
Initially, the constructs under investigation were assessed for normality, multicollinearity and correlation. Multivariate normality was evaluated using tests for skewness and kurtosis, with values ranging between −2 and +2 indicating a normal distribution. Constructs were retained if their factor loadings were 0.50 or higher; those below this threshold were excluded (Heene et al., 2011).
The study then used Pearson’s correlation to examine relationships between constructs, identifying potential multicollinearity if the correlation coefficient surpassed 0.8 (Iacobucci et al., 2015). Multicollinearity among the independent variables was further checked using the variance inflation factor (VIF), with values below 5.0 signifying the absence of multicollinearity issues (Du Toit et al., 2001).
Confirmatory factor analysis was used to assess unidimensionality, convergent/discriminant validity and reliability of the constructs (Chi and Chen, 2020). Constructs failing to achieve factor loadings of 0.50 or more were excluded, and an eigenvalue threshold of 1.0 was applied for extraction criteria (Thompson, 2004). Should any measures be dropped, it would necessitate a reevaluation of the item-to-item correlations, factor loadings, coefficient alpha and factor structures.
Following this, the study focused on testing for unidimensionality, convergent/discriminant validity and reliability. Unidimensionality was examined to check variations in participant responses and the adequacy of the model (Gatignon, 2010). The internal consistency of the data were analyzed using Cronbach’s alpha, setting a threshold of 0.70 to ensure reliability (Nunnally and Bernstein, 1994). Convergent validity was confirmed if the average variance extracted exceeded 0.50 (Thompson, 2004), while discriminant validity, indicating sufficient distinction between constructs, was validated by achieving a reliability value of 0.70 or higher (Furr and Bacharach, 2006).
Multiple regression analysis was applied to predict the value of a dependent variable based on two or more independent variables, making it suitable for hypothesis testing within this study (Cohen et al., 2013).
3.5 Psychometric properties of investigated constructs
All skewness and kurtosis scores are between +2.0 and −2.0, which suggest there are no violations of normality assumption. All VIF values are below five, suggesting there are no multicollinearity issues among constructs and variables. After exploratory factor analysis, the measurement variables labeled as PQ2, IQ2, PE2, PS2, BT3, PUV2, BL2, WOM2 and CEK3 were dropped due to low factor loading. All the factor loadings of the remaining measurement items to their respective constructs are high (0.6 and higher) and statistically significant, while their loadings to other constructs are very low (0.3 and lower). This also shows unidimensionality for the constructs. In addition, the Chi-square tests of all constructs were insignificant, which established the evidence of unidimensionality. Cronbach’s alphas of all constructs are greater than 0.70, indicating reliability is rigorously met (Nunnally and Bernstein, 1994). The AVE scores for all constructs are above the desired threshold of 0.50, suggesting convergent validity. All average variance extracted (AVE) scores are greater than the squared corresponding correlations, which demonstrates satisfactory discriminant validity.
3.6 Hypothesis testing results
Following the demonstration of construct adequacies, multiple regression tests were conducted to assess the proposed hypotheses. The results are detailed in Table 3, showing the influence of various constructs on different consumer outcomes.
Results of hypothesis testing
| Hyp. | DV | IDV | Std. Coef. (β) | t-value | Sig. at p < 0.05 | Control variable | Std. Coef. (β) | t-value | Sig. at p < 0.05 | Total R2 | Sig. at p < 0.05 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| PS | Constant | 3.029 | 0.003 | 0.570 | <0.001 F= 62.57 (8 / 378) | ||||||
| H1a | Y | PQ | 0.142 | 3.113 | 0.002 | Age | −0.032 | −0.940 | 0.348 | ||
| H2a | Y | IQ | 0.175 | 3.676 | <0.001 | Gender | −0.022 | −0.629 | 0.530 | ||
| H3a | Y | BI | 0.251 | 5.108 | <0.001 | Education | −0.035 | −1.02 | 0.310 | ||
| H4a | Y | PE | 0.319 | 6.447 | <0.001 | Income | 0.017 | 0.484 | 0.628 | ||
| BT | Constant | 2.121 | 0.035 | ||||||||
| H1b | N | PQ | 0.043 | 0.929 | 0.353 | Age | −0.002 | −0.056 | 0.955 | <0.001 F= 59.10 (8 / 378) | |
| H2b | Y | IQ | 0.224 | 4.631 | <0.001 | Gender | 0.049 | 1.421 | 0.156 | 0.556 | |
| H3b | Y | BI | 0.426 | 8.519 | <0.001 | Education | −0.003 | −0.073 | 0.942 | ||
| H4b | Y | PE | 0.163 | 3.233 | 0.001 | Income | 0.011 | 0.327 | 0.744 | ||
| PUV | Constant | 3.972 | <0.001 | −0.002 | −0.056 | 0.955 | |||||
| H1c | Y | PQ | 0.151 | 3.293 | 0.001 | Age | −0.025 | −0.724 | 0.470 | <0.001 F= 61.86 (8 / 378) | |
| H2c | Y | IQ | 0.259 | 5.420 | <0.001 | Gender | −0.016 | −0.463 | 0.644 | 0.567 | |
| H3c | Y | BI | 0.190 | 3.846 | <0.001 | Education | −0.012 | −0.346 | 0.730 | ||
| H4c | Y | PE | 0.297 | 5.986 | <0.001 | Income | −0.051 | −1.46 | 0.144 | ||
| PHV | Constant | 4.645 | <0.001 | ||||||||
| H1d | N | PQ | 0.014 | 0.319 | 0.750 | Age | −0.109 | −3.27 | 0.001 | <0.001 F= 69.38 (8 / 378) | |
| H2d | Y | IQ | 0.290 | 6.274 | <0.001 | Gender | −0.054 | −1.64 | 0.102 | 0.595 | |
| H3d | Y | BI | 0.286 | 5.989 | <0.001 | Education | 0.005 | 0.138 | 0.890 | ||
| H4d | Y | PE | 0.283 | 5.895 | <0.001 | Income | −0.024 | −0.718 | 0.473 | ||
| PI | Constant | 1.578 | 0.115 | ||||||||
| H6a | Y | PS | 0.350 | 6.925 | <0.001 | Age | 0.008 | 0.265 | 0.791 | <0.001 F= 88.01 (8 / 378) | |
| H7a | N | BT | 0.014 | 0.314 | 0.754 | Gender | 0.037 | 1.193 | 0.234 | 0.651 | |
| H8a | Y | PUV | 0.269 | 5.926 | <0.001 | Education | −0.041 | −1.33 | 0.183 | ||
| H9a | Y | PHV | 0.274 | 5.198 | <0.001 | Income | −0.001 | −0.040 | 0.968 | ||
| BL | Constant | 0.954 | 0.341 | ||||||||
| H6b | N | PS | 0.011 | 0.202 | 0.840 | Age | 0.065 | 1.919 | 0.056 | <0.001 F= 66.85 (8 / 378) | |
| H7b | Y | BT | 0.217 | 4.424 | <0.001 | Gender | −0.049 | −1.45 | 0.149 | 0.586 | |
| H8b | Y | PUV | 0.399 | 8.053 | <0.001 | Education | −0.010 | −0.285 | 0.776 | ||
| H9b | Y | PHV | 0.241 | 4.194 | <0.001 | Income | 0.069 | 2.034 | 0.043 | ||
| WOM | Constant | 2.403 | 0.017 | ||||||||
| H6c | Y | PS | 0.265 | 4.559 | <0.001 | Age | −0.010 | −0.275 | 0.783 | <0.001 F= 54.93 (8 / 378) | |
| H7c | Y | BT | 0.139 | 2.682 | 0.008 | Gender | 0.013 | 0.369 | 0.712 | 0.538 | |
| H8c | Y | PUV | 0.177 | 3.375 | <0.001 | Education | 0.001 | 0.015 | 0.988 | ||
| H9c | Y | PHV | 0.259 | 4.264 | <0.001 | Income | −0.045 | −1.25 | 0.212 |
| Hyp. | Std. Coef. (β) | t-value | Sig. at p < 0.05 | Control variable | Std. Coef. (β) | t-value | Sig. at p < 0.05 | Total R2 | Sig. at p < 0.05 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Constant | 3.029 | 0.003 | 0.570 | <0.001 F= 62.57 (8 / 378) | |||||||
| H1a | Y | 0.142 | 3.113 | 0.002 | Age | −0.032 | −0.940 | 0.348 | |||
| H2a | Y | 0.175 | 3.676 | <0.001 | Gender | −0.022 | −0.629 | 0.530 | |||
| H3a | Y | 0.251 | 5.108 | <0.001 | Education | −0.035 | −1.02 | 0.310 | |||
| H4a | Y | 0.319 | 6.447 | <0.001 | Income | 0.017 | 0.484 | 0.628 | |||
| Constant | 2.121 | 0.035 | |||||||||
| H1b | N | 0.043 | 0.929 | 0.353 | Age | −0.002 | −0.056 | 0.955 | <0.001 F= 59.10 (8 / 378) | ||
| H2b | Y | 0.224 | 4.631 | <0.001 | Gender | 0.049 | 1.421 | 0.156 | 0.556 | ||
| H3b | Y | 0.426 | 8.519 | <0.001 | Education | −0.003 | −0.073 | 0.942 | |||
| H4b | Y | 0.163 | 3.233 | 0.001 | Income | 0.011 | 0.327 | 0.744 | |||
| Constant | 3.972 | <0.001 | −0.002 | −0.056 | 0.955 | ||||||
| H1c | Y | 0.151 | 3.293 | 0.001 | Age | −0.025 | −0.724 | 0.470 | <0.001 F= 61.86 (8 / 378) | ||
| H2c | Y | 0.259 | 5.420 | <0.001 | Gender | −0.016 | −0.463 | 0.644 | 0.567 | ||
| H3c | Y | 0.190 | 3.846 | <0.001 | Education | −0.012 | −0.346 | 0.730 | |||
| H4c | Y | 0.297 | 5.986 | <0.001 | Income | −0.051 | −1.46 | 0.144 | |||
| Constant | 4.645 | <0.001 | |||||||||
| H1d | N | 0.014 | 0.319 | 0.750 | Age | −0.109 | −3.27 | 0.001 | <0.001 F= 69.38 (8 / 378) | ||
| H2d | Y | 0.290 | 6.274 | <0.001 | Gender | −0.054 | −1.64 | 0.102 | 0.595 | ||
| H3d | Y | 0.286 | 5.989 | <0.001 | Education | 0.005 | 0.138 | 0.890 | |||
| H4d | Y | 0.283 | 5.895 | <0.001 | Income | −0.024 | −0.718 | 0.473 | |||
| Constant | 1.578 | 0.115 | |||||||||
| H6a | Y | 0.350 | 6.925 | <0.001 | Age | 0.008 | 0.265 | 0.791 | <0.001 F= 88.01 (8 / 378) | ||
| H7a | N | 0.014 | 0.314 | 0.754 | Gender | 0.037 | 1.193 | 0.234 | 0.651 | ||
| H8a | Y | 0.269 | 5.926 | <0.001 | Education | −0.041 | −1.33 | 0.183 | |||
| H9a | Y | 0.274 | 5.198 | <0.001 | Income | −0.001 | −0.040 | 0.968 | |||
| Constant | 0.954 | 0.341 | |||||||||
| H6b | N | 0.011 | 0.202 | 0.840 | Age | 0.065 | 1.919 | 0.056 | <0.001 F= 66.85 (8 / 378) | ||
| H7b | Y | 0.217 | 4.424 | <0.001 | Gender | −0.049 | −1.45 | 0.149 | 0.586 | ||
| H8b | Y | 0.399 | 8.053 | <0.001 | Education | −0.010 | −0.285 | 0.776 | |||
| H9b | Y | 0.241 | 4.194 | <0.001 | Income | 0.069 | 2.034 | 0.043 | |||
| Constant | 2.403 | 0.017 | |||||||||
| H6c | Y | 0.265 | 4.559 | <0.001 | Age | −0.010 | −0.275 | 0.783 | <0.001 F= 54.93 (8 / 378) | ||
| H7c | Y | 0.139 | 2.682 | 0.008 | Gender | 0.013 | 0.369 | 0.712 | 0.538 | ||
| H8c | Y | 0.177 | 3.375 | <0.001 | Education | 0.001 | 0.015 | 0.988 | |||
| H9c | Y | 0.259 | 4.264 | <0.001 | Income | −0.045 | −1.25 | 0.212 |
Note(s): Y – hypothesis supported; N – hypothesis not supported; Std. Coef. = standardized coefficients, DV = dependent variable. IDV = independent variable. Product quality = PQ, information quality = IQ, brand image = BI, promotional efforts = PE, product satisfaction = PS, brand trust = BT, perceived utilitarian value = PUV, perceived hedonic value = PHV, purchase intention = PI, brand loyalty = BL, word of mouth = WOM. Significant at p < 0.05
PQ exhibited a positive effect on consumer PS (β = 0.142, t = 3.113), confirming hypothesis H1a. This suggests that higher PQ leads to greater satisfaction among consumers with resale apparel. IQ also positively influenced consumer satisfaction (β = 0.175, t = 3.676), supporting hypothesis H2a, indicating that quality information about resale programs increases consumer satisfaction with the products. BI further enhanced consumer satisfaction (β = 0.251, t = 5.108), validating hypothesis H3a and showing that a strong BI increases satisfaction with resale products. In addition, PE were found to positively impact consumer satisfaction (β = 0.319, t = 6.447), supporting hypothesis H4a, suggesting that effective promotions enhance consumer satisfaction with resale apparel.
Contrarily, PQ did not significantly impact BT (β = 0.043, t = 0.929), not supporting hypothesis H1b, indicating that PQ alone does not significantly influence trust in a brand’s resale program. However, IQ significantly enhanced BT (β = 0.224, t = 4.631), supporting hypothesis H2b, showing that reliable information can increase trust in the brand. BI also positively affected BT (β = 0.426, t = 8.519), supporting hypothesis H3b, demonstrating that a strong brand image enhances trust in the resale program. Similarly, PE positively influenced BT (β = 0.163, t = 3.233), supporting hypothesis H4b, indicating that strong marketing efforts can increase consumer trust.
In terms of PUV, PQ had a positive effect (β = 0.151, t = 3.293), supporting hypothesis H1c, suggesting that high-quality products enhance perceived functionality and convenience. IQ also positively influenced utilitarian value (β = 0.259, t = 5.420), supporting hypothesis H2c, indicating that detailed information increases perceptions of usability. BI had a similar effect on utilitarian value (β = 0.190, t = 3.846), supporting hypothesis H3c, showing that strong brand imagery enhances the perceived functionality of resale products. In addition, PE positively affected utilitarian value (β = 0.297, t = 5.986), supporting hypothesis H4c, suggesting that effective promotions enhance perceptions of product functionality and convenience.
However, PQ did not positively affect PHV (β = 0.014, t = 0.319), not supporting hypothesis H1d, indicating that PQ alone does not enhance the excitement or enjoyment of resale products. Conversely, IQ had a positive impact on hedonic value (β = 0.290, t = 6.274), supporting hypothesis H2d, suggesting that detailed information can enhance consumer excitement. BI also positively influenced hedonic value (β = 0.286, t = 5.989), supporting hypothesis H3d, indicating that a strong BI can increase enjoyment and engagement with resale products. Similarly, PE positively impacted hedonic value (β = 0.283, t = 5.895), supporting hypothesis H4d, showing that dynamic promotional activities can create excitement and enjoyment around resale apparel.
In addition, consumer PS significantly influenced their purchase intentions toward apparel resale programs (β = 0.350, t = 6.925), supporting hypothesis H6a, indicating that satisfaction is crucial for motivating purchase decisions. However, BT did not show a significant effect on purchase intentions (β = 0.314, t = 0.754), not supporting hypothesis H7a, revealing that trust in a brand does not directly lead to purchase intentions. PUV positively affected purchase intentions (β = 0.269, t = 5.926), supporting hypothesis H8a, suggesting that the practicality of resale apparel motivates purchases. PHV also had a significant positive effect on purchase intentions (β = 0.274, t = 5.198), supporting hypothesis H9a, showing that the excitement generated by resale platforms encourages consumer purchases.
Furthermore, consumer PS did not positively impact BL (β = 0.011, t = 0.202), not supporting hypothesis H6b, indicating that satisfaction with a product does not necessarily translate into BL. However, BT positively affected BL (β = 0.217, t = 4.424), supporting hypothesis H7b, showing that trust leads to greater BL. PUV had a strong positive effect on BL (β = 0.399, t = 8.053), supporting hypothesis H8b, suggesting that functional aspects of the products enhance consumer loyalty. PHV also positively influenced BL (β = 0.241, t = 4.194), supporting hypothesis H9b, indicating that enjoyment and excitement associated with the products foster loyalty.
Finally, consumer PS had a positive effect on WOM (β = 0.265, t = 4.559), supporting hypothesis H6c, showing that satisfied consumers are likely to recommend the resale program to others. BT also positively influenced WOM (β = 0.139, t = 2.682), supporting hypothesis H7c, indicating that trust in the brand encourages consumers to share their positive experiences. PUV positively affected WOM (β = 0.177, t = 3.375), supporting hypothesis H8c, suggesting that the practical benefits of the products prompt consumers to discuss them with others. Finally, PHV had a positive impact on WOM (β = 0.259, t = 4.264), supporting hypothesis H9c, showing that the fun and enjoyment associated with the resale program drive consumers to spread the word.
Table 4 presents the results of moderating effect testing. For the moderating effects, consumer environmental knowledge (CEK) moderated the relationship between IQ (β = 0.222, t = 2.541) and PE (β = 0.340, t = 4.047) with consumer product satisfaction, supporting H5b-a and H5d-a. CEK did not moderate PQ (β = 0.084, t = 1.051) and BI (β = 0.164, t = 1.911) with consumer product satisfaction, not supporting H5a-a or H5c-a.
Results of hypothesis testing (moderating effects)
| Hyp. | DV | IDV | Std. Coef. (β) | t-value | Sig. at p< 0.05 | |
|---|---|---|---|---|---|---|
| PS | ||||||
| H5a-a | N | PQ*CEK | 0.084 | 1.051 | 0.294 | |
| H5b-a | Y | IQ*CEK | 0.222 | 2.541 | 0.011 | |
| H5c-a | N | BI*CEK | 0.164 | 1.911 | 0.057 | |
| H5d-a | Y | PE*CEK | 0.340 | 4.047 | <0.001 | |
| BT | ||||||
| H5a-b | N | PQ*CEK | −0.132 | −1.477 | 0.140 | |
| H5b-b | Y | IQ*CEK | 0.269 | 2.761 | 0.006 | |
| H5c-b | Y | BI*CEK | 0.478 | 4.981 | <0.001 | |
| H5d-b | N | PE*CEK | 0.110 | 1.179 | 0.239 | |
| PUV | ||||||
| H5a-c | N | PQ*CEK | 0.097 | 1.103 | 0.271 | |
| H5b-c | Y | IQ*CEK | 0.314 | 3.277 | 0.001 | |
| H5c-c | N | BI*CEK | 0.040 | 0.424 | 0.672 | |
| H5d-c | Y | PE*CEK | 0.300 | 3.248 | 0.001 | |
| PHV | ||||||
| H5a-d | Y | PQ*CEK | −0.157 | −2.010 | 0.045 | |
| H5b-d | Y | IQ*CEK | 0.431 | 5.074 | <0.001 | |
| H5c-d | Y | BI*CEK | 0.251 | 2.998 | 0.003 | |
| H5d-d | Y | PE*CEK | 0.284 | 3.476 | <0.001 |
| Hyp. | Std. Coef. (β) | t-value | Sig. at p< 0.05 | |||
|---|---|---|---|---|---|---|
| H5a-a | N | PQ*CEK | 0.084 | 1.051 | 0.294 | |
| H5b-a | Y | IQ*CEK | 0.222 | 2.541 | 0.011 | |
| H5c-a | N | BI*CEK | 0.164 | 1.911 | 0.057 | |
| H5d-a | Y | PE*CEK | 0.340 | 4.047 | <0.001 | |
| H5a-b | N | PQ*CEK | −0.132 | −1.477 | 0.140 | |
| H5b-b | Y | IQ*CEK | 0.269 | 2.761 | 0.006 | |
| H5c-b | Y | BI*CEK | 0.478 | 4.981 | <0.001 | |
| H5d-b | N | PE*CEK | 0.110 | 1.179 | 0.239 | |
| H5a-c | N | PQ*CEK | 0.097 | 1.103 | 0.271 | |
| H5b-c | Y | IQ*CEK | 0.314 | 3.277 | 0.001 | |
| H5c-c | N | BI*CEK | 0.040 | 0.424 | 0.672 | |
| H5d-c | Y | PE*CEK | 0.300 | 3.248 | 0.001 | |
| H5a-d | Y | PQ*CEK | −0.157 | −2.010 | 0.045 | |
| H5b-d | Y | IQ*CEK | 0.431 | 5.074 | <0.001 | |
| H5c-d | Y | BI*CEK | 0.251 | 2.998 | 0.003 | |
| H5d-d | Y | PE*CEK | 0.284 | 3.476 | <0.001 |
Note(s): Y – hypothesis supported; N – hypothesis not supported; Std. Coef.=standardized coefficients, DV = dependent variable. IDV = independent variable. Product quality = PQ, information quality = IQ, brand image = BI, promotional efforts = PE, product satisfaction = PS, brand trust = BT, perceived utilitarian value = PUV, perceived hedonic value = PHV, consumer environmental knowledge = CEK. Significant at p< 0.05
CEK also moderated the relationship between IQ (β = 0.269, t = 2.761) and BI (β = 0.478, t = 4.981) with BT, supporting H5b-b and H5c-b. CEK did not moderate the relationship between PQ (β = −0.132, t = −1.477) and PE(β = 0.110, t = 1.179) with BT, not supporting H5a-b and H5d-b.
CEK also moderated the relationship between IQ (β = 0.314, t = 3.277) and PE (β = 0.300, t = 3.248) with PUV, supporting H5b-c and H5d-c. CEK did not moderate the relationship between PQ (β = 0.097, t = 1.103) and BI (β = 0.040, t = 0.424) with PUV, not supporting H5a-c and H5c-c.
Finally, CEK moderated PQ (β = −0.157, t = −2.010), IQ (β = 0.431, t = 5.074), BI (β = 251, t = 2.998) and PE (β = 0.284, t = 3.476) with PHV, supporting H5b-d, H5c-d and H5d-d. CEK/PQ had a negative moderating effect, and even though it was significant, it was not supported in this study.
4. Discussion
This study explored how consumers respond to branded apparel resale programs by examining the influence of multiple brand-driven stimuli on cognitive and affective reactions, which in turn shape behavioral intentions. The findings deepen our understanding of consumer behavior within circular fashion systems and demonstrate how the interplay between marketing efforts and consumer psychology can facilitate engagement with sustainable business models.
The results confirm that PQ and IQ significantly influence consumer cognition, specifically product satisfaction. These findings are consistent with prior literature suggesting that clearly communicated and well-executed product attributes can mitigate concerns about purchasing secondhand items (Abbey et al., 2015). In the resale context, where concerns about wear, damage and hygiene often arise, high perceived quality becomes a critical assurance mechanism. When consumers perceive remanufactured apparel as comparable in quality to new products, they are more likely to form favorable evaluations, thus validating the relevance of quality-related cues in shaping trust and satisfaction.
The role of BI and PE in shaping BT is similarly noteworthy. Previous studies have shown that brand equity plays a central role in influencing consumer decisions in both conventional and sustainable retail environments (Grădinaru et al., 2022; Rahman and Nguyen-Viet, 2022). Our findings further suggest that when brands actively promote their resale initiatives and integrate them into their core identity, they reinforce consumer trust not only in the specific resale program but also in the brand’s broader value proposition. This link between perceived authenticity and sustainability efforts strengthens the theoretical association between brand-led sustainability communication and consumer trust-building mechanisms.
Cognitive evaluations were also found to shape emotional responses, namely, perceived utilitarian and hedonic value. This relationship supports earlier findings that emphasize the integration of rational and emotional components in consumption decisions (Chang et al., 2011; Hirschman and Holbrook, 1982). However, the findings extend this stream of research by demonstrating that even in the context of remanufactured apparel, hedonic value such as enjoyment, satisfaction and personal gratification, plays a pivotal role in shaping behavioral responses. This highlights the growing relevance of affective benefits in sustainable consumption choices, echoing observations by Tymoshchuk et al. (2024) that sustainability-driven experiences must also be emotionally resonant to foster consumer buy-in.
Furthermore, the empirical differentiation between utilitarian and hedonic value enriches our understanding of how consumers evaluate circular consumption. Whereas utilitarian value stems from functionality, affordability or practicality, hedonic value captures the emotional and experiential dimensions of consumption. In resale programs, where motivations may range from environmental concern to the thrill of finding a unique item, both value dimensions co-exist and reinforce one another. Our results affirm that these distinct yet interrelated paths warrant more attention in future theoretical modeling of sustainable consumer behavior.
Finally, the moderating effect of environmental knowledge offers additional insight into the heterogeneity of consumer responses. Consumers with higher environmental awareness appear more responsive to emotionally driven value propositions, particularly hedonic benefits. This supports the proposition that sustainability literacy not only informs ethical judgments but also enhances emotional receptivity to green marketing efforts (Vedantam et al., 2021). As such, environmental knowledge serves not merely as a background trait but as an active variable shaping the translation of internal evaluations into action. This insight contributes to refining the S-O-R framework by introducing a consumer-level cognitive characteristic that influences the strength and direction of response pathways.
In summary, this study enhances theoretical understanding by demonstrating how brand-managed stimuli interact with both cognitive and affective mechanisms in the emerging domain of apparel resale. By integrating insights from consumer psychology, sustainability marketing and circular fashion, the findings offer a multidimensional perspective that advances the theoretical modeling of consumer engagement in branded resale contexts.
5. Conclusion
This study offers an extensive evaluation of the various factors that shape consumer behavior in the context of apparel resale programs. The research has illuminated the significant role played by PQ, IQ, BI, PE and CEK in influencing a range of consumer responses, including satisfaction, BT, PUV, PHV, purchase intention, BL and WOM. These findings not only underscore the multifaceted nature of consumer decision-making within the resale market but also highlight the intricate interplay between these factors.
The study reveals that PQ and IQ are critical in determining the consumer’s satisfaction and trust, which are foundational for fostering repeat business and positive referrals. BI and PE, on the other hand, are shown to significantly enhance both the perceived value of products and the overall attractiveness of the resale programs, influencing consumer’s purchase intentions and their propensity to engage in WOM advocacy. Furthermore, CEK plays a crucial moderating role, suggesting that a deeper understanding of environmental issues can alter the way consumers perceive and respond to various marketing stimuli.
These insights emphasize the need for retailers and marketers to develop more nuanced and targeted strategies that can effectively tap into the changing dynamics of consumer preferences in the resale market. For instance, enhancing PQ and providing comprehensive, transparent information can help build consumer trust and satisfaction. Similarly, leveraging a strong BI and engaging promotional activities can elevate perceived values and encourage purchase behaviors.
Moreover, given the growing consumer interest in sustainability, incorporating environmental considerations into marketing strategies could align brand objectives with consumer expectations, potentially leading to higher consumer engagement and loyalty. Retailers might consider integrating these insights into their operational strategies to not only appeal to environmentally conscious consumers but also to differentiate their offerings in a competitive market.
In conclusion, this study contributes to a deeper understanding of the critical factors that influence consumer behavior in apparel resale programs. By addressing these factors, businesses can enhance the appeal and effectiveness of their resale programs, ultimately leading to improved consumer engagement and success in the sustainable fashion sector. These findings serve as a valuable resource for practitioners in the field, offering actionable strategies that can be used to optimize the performance of resale programs and to better meet the needs of today’s diverse consumer base.
6. Implications
6.1 Theoretical implications
This study offers several theoretical contributions to the literature on sustainable fashion consumption and CBMs. By applying and extending the S-O-R framework, the research identifies how specific external stimuli, namely, PQ, IQ, BI and PE, influence consumer cognitive evaluations (product satisfaction and BT) and affective responses (perceived utilitarian and hedonic value) within the context of apparel resale programs. Unlike prior applications of the S-O-R model, which have primarily focused on linear retail settings, this study uniquely tests its relevance in a branded resale environment, advancing understanding of consumer behavior in circular consumption systems.
The study’s hypotheses explore the mediating role of cognitive (H1–H4) and affective responses (H5–H6), and how these mediate the effects of stimuli on downstream behavioral outcomes, such as purchase intention (H7), BL (H8) and WOM advocacy (H9). Notably, the findings confirm that product satisfaction and BT are critical cognitive pathways through which stimuli operate, while utilitarian and hedonic value significantly shape emotional engagement. Furthermore, the study introduces environmental knowledge as a novel moderator (H10a–H10d), revealing that it significantly strengthens the relationship between emotional responses particularly hedonic value and consumer behavioral outcomes like purchase intention, BL and WOM advocacy.
By empirically validating these relationships, the study enriches the S-O-R literature by clarifying the multi-pathway mechanisms through which stimuli shape consumer responses in a circular fashion context. It also advances sustainable consumption theory by highlighting the role of individual-level knowledge in enhancing or attenuating emotional engagement with CBMs.
6.2 Practical implications
The findings from this study provide valuable, actionable insights for retail managers and sustainable fashion brands aiming to strengthen their competitive positioning in the growing circular fashion market. The demonstrated influence of external stimuli such as PQ, information accuracy, BI and promotional effectiveness on consumer cognition and emotion highlights the need for a strategic, multidimensional approach to customer engagement. These factors play a pivotal role in shaping favorable consumer responses, including heightened purchase intention, BL and positive WOM advocacy.
For retail managers, the results suggest prioritizing the delivery of high-quality, sustainably produced apparel as a means to enhance perceived value and drive conversion. Equally important is the provision of clear, transparent and credible product and brand information, which fosters consumer trust and strengthens emotional engagement. PE should not only emphasize sustainability but also highlight the functional and emotional benefits of resale offerings, appealing to both utilitarian and hedonic motivations.
Sustainable fashion brands can leverage these insights to refine their market positioning and communication strategies. By reinforcing their commitment to environmental and ethical values, brands can build deeper trust with consumers, enhance their reputational capital and stimulate organic brand advocacy through WOM. The broad appeal of resale programs, as evidenced by consistently positive consumer responses across multiple psychological constructs, underscores the market potential of circular models in appealing to diverse consumer segments.
Importantly, the study reinforces the strategic imperative of sustainable brand positioning not as a peripheral value-add, but as a core business strategy. Brands seeking long-term success in the sustainable fashion space should embed sustainability principles into their marketing narratives, customer experiences and operational practices. Doing so will not only optimize consumer engagement and satisfaction but also contribute to sustained competitive advantage and improved business performance in a rapidly evolving retail landscape.
7. Limitations and future studies
Despite offering valuable insights, this study is not without limitations. First, the data were collected using a cross-sectional survey design, which restricts our ability to infer causality between constructs. Future research could adopt longitudinal or experimental methods to validate the directionality of the proposed relationships and to assess changes in consumer perceptions and behaviors over time as resale programs mature.
Second, the sample was limited to US consumers recruited via an online panel, which may limit the generalizability of the findings. Cultural attitudes toward sustainability and secondhand consumption vary significantly across countries; thus, future studies could replicate this model in different cultural or regional contexts to explore potential differences in cognitive and emotional responses to apparel resale programs.
Third, although participants were asked to reflect on a well-known apparel brand with a resale program, no specific brand was assigned. While this approach allowed respondents to consider brands they were personally familiar with, it may have introduced variability in brand-related responses. Future research could control for brand effects by specifying particular brands or conducting comparative studies between national and boutique resale initiatives.
In addition, while this study focused on consumers’ perceptions of brand-controlled stimuli, it did not account for broader platform features or peer-to-peer dynamics often present in multi-brand or consumer-driven resale environments. Expanding the framework to include these dimensions could offer a more comprehensive understanding of resale ecosystems and their influence on consumer decision-making.
Finally, the model incorporated environmental knowledge as a moderator, but future studies could explore additional consumer characteristics such as environmental values, past reuse behaviors or perceived behavioral control to refine segmentation strategies and better understand the psychological drivers of sustainable apparel consumption.
Institutional review board statement
This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Washington State University (IRB#19950-001).

