Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic

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Integrating the Theory of Planned Behavior (TPB) with brand-related constructs—perceived scarcity, perceived quality, and self-congruity—this research examines how these factors shape consumer attitudes, subjective norms, perceived behavioral control, consumption intentions, brand loyalty, and word-of-mouth. Using studies published between 2004 and 2024, a random-effects meta-analysis reveals that brand attitude is the strongest predictor of purchase intention, while self-congruity with fashion brands significantly enhances all TPB components. Perceived quality exerts a cross-cutting influence on both cognitive and social evaluations, reinforcing the multidimensional nature of consumer judgments. The findings extend the TPB framework by embedding symbolic and perceptual brand dimensions, offering a more comprehensive explanatory model of fashion consumption. From a managerial perspective, the results suggest that marketing strategies emphasizing authentic scarcity cues and alignment with consumers’ self-identity can strengthen emotional attachment, perceived control, and loyalty. The study concludes with theoretical and practical implications for designing culturally sensitive and identity-driven branding strategies in the fast fashion sector." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/14-1256/v2", "name": "Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption:..." } } ] } Home Browse Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption:... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Hsu SC, Liao YK, Huang KC et al. Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.12688/f1000research.170388.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Systematic Review Revised Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] Shu-Chuan Hsu https://orcid.org/0009-0001-7824-0018 1 , Ying-Kai Liao 2 , Kuo-Chung Huang 1 , [...] Lun-Chuan Lin 2 , Vo Thi Thinh 1 , Wann-Yih Wu 1 , Khemraj Sharma https://orcid.org/0009-0004-3035-1335 3 Shu-Chuan Hsu https://orcid.org/0009-0001-7824-0018 1 , Ying-Kai Liao 2 , [...] Kuo-Chung Huang 1 , Lun-Chuan Lin 2 , Vo Thi Thinh 1 , Wann-Yih Wu 1 , Khemraj Sharma https://orcid.org/0009-0004-3035-1335 3 PUBLISHED 10 Feb 2026 Author details Author details 1 Department of Business Administration, Nanhua University, Dalin, Taiwan Province, 62249, Taiwan 2 Department of International Business Administration, Nanhua University, Dalin, Taiwan Province, 62249, Taiwan 3 International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, 751024, India Shu-Chuan Hsu Roles: Formal Analysis Ying-Kai Liao Roles: Methodology, Writing – Review & Editing Kuo-Chung Huang Roles: Writing – Review & Editing Lun-Chuan Lin Roles: Writing – Review & Editing Vo Thi Thinh Roles: Software, Writing – Review & Editing Wann-Yih Wu Roles: Supervision Khemraj Sharma Roles: Supervision, Writing – Original Draft Preparation OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Social Psychology gateway. Abstract This study employs a meta-analytic approach to synthesize empirical evidence on the psychological and behavioral determinants of fast fashion consumption. Integrating the Theory of Planned Behavior (TPB) with brand-related constructs—perceived scarcity, perceived quality, and self-congruity—this research examines how these factors shape consumer attitudes, subjective norms, perceived behavioral control, consumption intentions, brand loyalty, and word-of-mouth. Using studies published between 2004 and 2024, a random-effects meta-analysis reveals that brand attitude is the strongest predictor of purchase intention, while self-congruity with fashion brands significantly enhances all TPB components. Perceived quality exerts a cross-cutting influence on both cognitive and social evaluations, reinforcing the multidimensional nature of consumer judgments. The findings extend the TPB framework by embedding symbolic and perceptual brand dimensions, offering a more comprehensive explanatory model of fashion consumption. From a managerial perspective, the results suggest that marketing strategies emphasizing authentic scarcity cues and alignment with consumers’ self-identity can strengthen emotional attachment, perceived control, and loyalty. The study concludes with theoretical and practical implications for designing culturally sensitive and identity-driven branding strategies in the fast fashion sector. READ ALL READ LESS Keywords Perceived scarcity, perceived quality, self-congruity, brand attitude, subjective norm, perceived behavioral control, consumption intention, brand loyalty, word-of-mouth, meta-analysis Corresponding Author(s) Khemraj Sharma ( [email protected] ) Close Corresponding author: Khemraj Sharma Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2026 Hsu SC et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Hsu SC, Liao YK, Huang KC et al. Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.12688/f1000research.170388.2 ) First published: 14 Nov 2025, 14 :1256 ( https://doi.org/10.12688/f1000research.170388.1 ) Latest published: 10 Feb 2026, 14 :1256 ( https://doi.org/10.12688/f1000research.170388.2 ) Revised Amendments from Version 1 Based on the reviewer's comment, we have revised the content of Publication Bias Assessment to confirm the robustness of the findings. Following the revised addition: Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. Based on the reviewer's comment, we have revised the content of Publication Bias Assessment to confirm the robustness of the findings. Following the revised addition: Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. See the authors' detailed response to the review by Pablo Gutiérrez Rodríguez See the authors' detailed response to the review by Tiara Nur Anisah READ REVIEWER RESPONSES 1. Introduction The rapid proliferation of fast fashion has significantly reshaped the landscape of global consumer culture. Driven by the principles of affordability, trend responsiveness, and accelerated product turnover, fast fashion brands have disrupted traditional apparel markets and deeply influenced consumption patterns, particularly among younger demographics. This evolving industry model satisfies consumers’ pursuit of immediacy and novelty, yet it simultaneously raises alarming concerns related to environmental degradation, ethical production, and the overextension of natural resources. Moreover, the psychological mechanisms underlying fast fashion consumption—characterized by emotional impulses, brand identification, and peer influence—are far more complex than traditional rational decision-making models can fully explain. Although the TPB has been widely employed to interpret behavioral intentions in consumption studies, its core framework, which focuses on attitude, subjective norms (SN), and perceived behavioral control (PBC), may insufficiently capture the symbolic and affect-driven aspects of consumer-brand interaction in fast fashion contexts. In particular, variables such as perceived scarcity (PS), perceived quality (PQ), and self-congruity with fast fashion brands—elements often shaped through marketing practices like limited-edition releases, celebrity collaborations, and influencer endorsement—remain underexplored and inconsistently measured across empirical studies. The motivation for this study arises from several critical research gaps and practical needs. First, past investigations into fast fashion consumption have been largely siloed by region or culture, relying heavily on single studies that are limited by methodological constraints such as small sample sizes, cross-sectional designs, and narrow cultural representation. These limitations hinder the generalizability and cumulative understanding of how key psychological constructs operate across broader consumer contexts. Second, the mediating role of TPB constructs—attitude, subjective norm, and PBC—in linking brand-related perceptions to behavioral outcomes remains theoretically promising but empirically fragmented. Despite the intuitive importance of symbolic variables such as brand congruity or scarcity, few studies have systematically evaluated how these variables influence downstream consequences like brand loyalty or word-of-mouth (WoM) behavior. Third, the absence of comprehensive synthesis efforts leaves unresolved questions regarding the robustness, consistency, and boundary conditions of these effects across different market and demographic settings. In response, this study adopts a meta-analytic methodology to systematically integrate and evaluate findings from a large body of empirical literature. By focusing on three theoretical blocks—antecedents (PS, brand congruity, and PQ), mediating TPB constructs (attitude, SN, PBC, and purchase intention), and behavioral outcomes (brand loyalty and WoM)— this research seeks to quantify the strength and nature of the connections between psychological factors and fast fashion consumption results. By linking consumer psychology with rational behavioral theory, it seeks to establish a comprehensive, theory-grounded framework that not only enriches scholarly discussion but also offers useful advice for brand managers, marketers, and policymakers who are working to connect business success with social and environmental responsibility. Accordingly, the research pursues three main objectives. First, it evaluates the direct and indirect effects of perceived scarcity, brand congruity, and perceived quality on consumer outcomes through a meta-analytic approach. Second, it examines the mediating roles of the TPB components—attitude, subjective norms, and perceived behavioral control—in explaining how these antecedents influence purchase intention. Finally, it strives to generate a broader and more generalizable understanding of fast fashion consumption patterns while offering implications for both theoretical advancement and practical applications. 2. Literature review 2.1 Theoretical foundations This study is grounded in five interrelated theoretical foundations: PS Theory, Self-Congruity Theory, PQ Theory, the TPB, and the Expectation-Confirmation-Loyalty (ECL) Model. Each theory, developed from distinct disciplinary roots—ranging from consumer psychology and marketing to behavioral economics—collectively forms a robust conceptual framework for understanding not only the formation of fast fashion consumption intentions, but also the resulting post-purchase behaviors. This study integrates these theories to examine the consumer decision-making process across both pre-intention and post-intention phases. The PS theory, initially advanced by Worchel, Lee, and Adewole (1975) , argues that when products are perceived to be in limited supply, their desirability increases due to a psychological scarcity effect. This phenomenon has been widely validated across various consumer contexts, from luxury retail to online flash sales. Scarcity can take many forms—such as limited-time availability, exclusive collaborations, or artificial supply constraints—and often evokes emotions such as urgency, anxiety, and Fear of Missing Out (FOMO). In our model, PS functions as a core antecedent variable influencing consumers’ attitudes toward fast fashion brands, their perception of social expectations (SN), and their sense of behavioral control. These, in turn, determine their intention to engage in fast fashion consumption. Self-Congruity Theory, introduced by Sirgy (1986) , is rooted in Rogerian psychology and symbolic interactionism. It emphasizes that consumers prefer brands and products that reflect or reinforce their self-image, including actual, ideal, and social identities. In this framework, brand congruity (CFFB) is a psychological alignment between the consumer’s self-concept and the symbolic meaning of the brand. This alignment deepens emotional involvement and fosters stronger brand attitudes and purchase intentions. Particularly in high-symbolism product categories like fashion, symbolic congruity plays a pivotal role. In this study, CFFB is positioned as a critical antecedent influencing all three TPB constructs and indirectly shaping consumption intention. The PQ theory, articulated by Zeithaml (1988) and extended by Dodds et al. (1991) , frames quality as a subjective perception shaped by product expectations, brand cues, and actual experience. Unlike objective quality metrics, PQ reflects how consumers interpret quality signals—especially in environments like fast fashion where purchases are often impulse-driven and heavily influenced by aesthetics, branding, and digital presentation. In our research model, PQ informs attitudes, SN, and PBC, thereby playing a central role in how consumers form purchase intentions. Digital platforms, influencer marketing, and social proof amplify the influence of PQ, especially among younger, digitally native consumer segments. The TPB, introduced by Ajzen (1991) , continues to be a framework that is very frequently used to explain and forecast how people make decision in a variety of fields. The TPB suggests that behavioral intention is determined by three key factors: a person’s attitude toward the behavior (attitude), the subjective norms they perceive, and their sense of perceived behavioral control. This theory serves as the central mediating framework in our model, linking the psychological and contextual antecedents (PS, CFFB, PQ) to intention (IFFC). In this study, inclusion of TPB allows for a structured understanding of how both rational evaluations and affective responses influence behavioral intentions in fast fashion consumption. The ECL Model extends the analysis beyond intention to behavioral outcomes. Initially proposed by Oliver (1980) and later refined by Bhattacherjee (2001) , the model explains how post-purchase satisfaction and brand loyalty emerge when consumers’ expectations are met or exceeded by actual experience. Our study uses the ECL model to examine how behavioral intention (IFFC) influences downstream loyalty (BL) and WoM. The integration of this model emphasizes that building long-term consumer relationships in fast fashion requires more than stimulating desire—it necessitates consistent delivery on perceived promises. In conclusion, each of the five theories contributes a distinct lens: PS, SC, and PQ address different aspects of consumer psychology; TPB provides the behavioral intention mechanism; and the ECL model explains loyalty formation. This multi-theoretical integration offers a comprehensive and layered understanding of fast fashion consumption behavior, combining cognitive, emotional, and contextual dimensions in a single empirical framework (see Figure 1 ). Figure 1. Research model. 2.2 Hypotheses development 2.2.1 The influence of perceived scarcity on attitude, subjective norm, perceived behavioral control, and intention to purchase fast fashion PS refers to consumers’ subjective sense that a product is limited in quantity, availability, or subject to purchase constraints ( Chen & Yao, 2018 ). Brands often deploy scarcity-based marketing tactics—such as limiting the availability or duration of product access—to create a sense of urgency and exclusivity ( Cremer & Loebbecke, 2021 ; Gupta & Gentry, 2016 ). These tactics appeal to consumers’ psychological need for ownership, status, and FOMO, all of which have been linked to enhanced consumer engagement and decision-making speed. Attitude ( Ajzen & Fishbein, 2000 ), a key variable in the TPB, is shaped by both emotional and cognitive factors. When consumers perceive a product as scarce, it often signals desirability and value, leading to more favorable attitudes toward the brand. Table 1 presents empirical evidence supporting the relationship between PS and consumer attitudes toward fast fashion brands. Across studies conducted in Taiwan, the U.S., China, Turkey, and Indonesia, positive correlations ( r ranging from 0.232 to 0.49) were observed between perceived scarcity and favorable brand attitudes. These findings suggest a robust cross-cultural effect. The psychological mechanism behind this relationship can be explained through the Stimulus-Organism-Response (S-O-R) model and TPB, where PS (stimulus) influences internal evaluations (attitude) and results in behavioral intentions. Hence, the following hypothesis is proposed: H1: PS of products positively influences consumers’ attitudes toward fast fashion brands. Table 1. Summary of Empirical studies on the relationship between PS and attitude toward fast fashion brands. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) PS AT 201 0.232 Survey/Taiwan Cook and Yurchisin (2017) PS AT 246 0.49 Survey/USA Lee et al. (2023) PS AT 385 0.252 Survey/China Köse and Özer Çizer (2021) PS AT 399 0.281 Survey/Turkey Yusuf (2021) PS AT 200 0.41 Survey/Indonesia PS may also affect consumers’ SN, a core component of the TPB that captures an individual’s perception of social expectations to either engage in or abstain from a certain action ( Ajzen, 1991 ). A consumer who perceives a product to be scarce may experience increased pressure from significant others (family, friends, and influencers) who also value the scarce product. This occurrence can be understood by applying Social Influence Theory ( Cialdini & Goldstein, 2004 ), which posits that individuals have a greater tendency to adopt the group’s behavior when they perceive group consensus or peer endorsement. Table 2 supports this notion, indicating that PS and SN are moderately and positively correlated when considering the consumption of fast fashion. Based on this evidence, the following hypothesis is proposed: H2: PS of products positively influences consumers’ subjective norms toward fast fashion brands. Table 2. Summary of Empirical study on the relationship between PS and subjective norm toward fast fashion brands. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) PS SN 201 0.35 Survey/Taiwan The third dimension of TPB, PBC, relates to a person’s judgment on the level of control they have over performing a certain behavior. Interestingly, Meuthia et al. (2023) found an inverse link between PS and PBC; this finding suggests that scarcity may create psychological barriers and feelings of helplessness when consumers believe they lack the ability to access scarce products. This aligns with the principles of the Cognitive Appraisal Theory, where individuals evaluate stressful stimuli based on perceived controllability. As shown in Table 3 , if consumers feel that products are overly difficult to obtain, their PBC—and consequently, their purchase intention—may decrease. Accordingly, we propose: H3: PS of products negatively influences consumers’ perceived behavioral control toward fast fashion brands. Table 3. Summary of Empirical study on the relationship between PS and perceived behavioral control toward fast fashion brands. Author(s) name Independent variable Dependent variable n r Method/Country Meuthia et al. (2023) PS PBC 289 -0.295 Survey/Indonesia PS has been widely studied as a psychological trigger that influences consumer behavior, particularly in contexts involving limited availability or exclusivity. As shown in Table 4 , Chang, Lai, and Yen (2024) found that PS can increase consumers’ willingness to buy by fostering feelings of uniqueness and time-sensitivity for products with restricted availability, which encourages customers to expedite their purchase due to the fear of the item becoming unavailable. Similarly, Cengiz and Şenel (2024) argued that PS increases consumers’ FOMO and impulse-buying tendencies. However, they also emphasized that the effectiveness of scarcity appeals can be highly context-dependent, varying with product category and cultural background. Despite these findings, the connection between PS and the desire to purchase is inconsistent throughout the existing literature. Broeder and Wentink (2022) reported that PS did not significantly induce purchase intentions in their sample, suggesting that the effect may be contingent on additional factors such as consumer characteristics or market conditions. Furthermore, Meuthia et al. (2023) found that PS did not directly or significantly influence panic-driven purchasing habits, which may parallel the dynamics of intention formation in fast fashion consumption. Given these mixed empirical results, the present meta-analysis posits that an overall positive relationship exists between PS and the intent of consumers to engage in greater fast fashion consumption. Accordingly, we propose the following hypothesis: H4: PS is positively associated with consumers’ intention to increase fast fashion consumption. Table 4. Summary of Empirical study on the relationship between PS and intention to increase fast fashion consumption. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) PS IFFC 201 0.195 Survey/Taiwan Cengiz and Şenel (2024) PS IFFC 271 0.663 Survey/Turkey Yuen et al. (2022) PS IFFC 507 0.263 Survey/Singapore Zhang et al. (2021) PS IFFC 509 0.274 Survey/Malaysia Zhang et al. (2022) PS IFFC 488 0.238 Survey/Malaysia Chen et al. (2022) PS IFFC 437 0.155 Survey/China Omar et al. (2021) PS IFFC 157 0.026 Survey/Malaysia Köse and Özer Çizer (2021) PS IFFC 399 0.141 Survey/Turkish Sung et al. (2021) PS IFFC 134 0.1628 Survey/Australia Broeder and Wentink (2022) PS IFFC 208 -0.061 Survey/Netherlands Meuthia et al. (2023) PS IFFC 289 -0.217 Survey/Indonesia 2.2.2 The effect of congruity on attitude toward fast fashion brands, subjective norm, and perceived behavioral control Within branding research, Self-Congruity Theory ( Sirgy, 1982 ) suggests that individuals tend to prefer brands that reflect or correspond to their self-identity. This alignment—often referred to as brand-self congruity or simply congruity—enhances emotional connection, brand preference, and favorable evaluations. In the fast fashion context, this theory is especially relevant, as consumers are not merely purchasing clothing for functional purposes but are also seeking to express identity, lifestyle, and social affiliation. Empirical evidence has consistently shown that when a consumer perceives a fast fashion brand to be congruent with their self-image, their attitude toward that brand becomes more favorable. As shown in Table 5 , multiple studies across various countries—ranging from the United States to Indonesia, China, and Vietnam—report significant positive correlations between brand congruity and consumer attitudes toward fast fashion brands. For example, Fu et al. (2017) report a strong correlation (r = 0.81) in the U.S., while Setyaningsih & Asnawi (2022) find a similarly high correlation (r = 0.532) in Indonesia. Table 5. Summary of Empirical evidence on the relationship between brand congruity and attitude toward fast fashion brands. Author(s) name Independent variable Dependent variable n r Method/Country Fu et al. (2017) CFFB AT 365 0.81 Survey/USA Badrinarayanan et al. (2014) CFFB AT 316 0.35 Survey/USA Setyaningsih and Asnawi (2022) CFFB AT 204 0.532 Survey/Indonesia Abimbola et al. (2012) CFFB AT 264 0.46 Survey/Australia Chetioui et al. (2020) CFFB AT 610 0.199 Survey/Morocco Su and Reynolds (2017) CFFB AT 420 0.34 Survey/China Chau and Thanh (2022) CFFB AT 510 0.414 Survey/Vietnam Foroudi et al. (2021) CFFB AT 448 0.196 Survey/UK Lee et al. (2023) CFFB AT 385 0.224 Survey/China Koh et al. (2022) CFFB AT 458 0.275 Survey/Korea Chen et al. (2022) CFFB AT 225 0.152 Survey/Taiwan Shin et al. (2016) CFFB AT 854 0.46 Survey/USA Kang et al. (2012) CFFB AT 389 0.455 Survey/USA Han & Chen (2024) CFFB AT 304 0.705 Survey/Thailand Yen and Mai (2020) CFFB AT 539 0.344 Survey/Vietnam The theoretical underpinning for this relationship is that congruity enhances cognitive consistency, leading to positive affect and reinforcement of self-identity ( Sirgy et al., 2000 ). Consumers perceive congruent brands as extensions of themselves, which fosters brand loyalty and deepens affective evaluations. Thus, brand managers in the fast fashion industry often focus on tailoring their brand identity to reflect aspirational or socially desirable traits of their target audiences. H5: Congruity between consumer self-image and fast fashion brand identity positively influences consumer attitudes toward the brand. Building upon self-congruity theory ( Sirgy, 1982 ), researchers have explored how congruity between consumer self-image and brand identity extends beyond individual attitudes to influence social perceptions and expectations. As a concept within the TPB ( Ajzen, 1991 ), subjective norm is defined as the social pressure an individual feels from influential people to either engage in or refrain from a specific behavior. In the context of fast fashion, if a consumer perceives a brand to align closely with their identity and values, this congruity may enhance their sensitivity to others’ opinions about the brand and increase their conformity to perceived social expectations. The empirical evidence summarized in Table 6 shows a significant and consistent link between the alignment of a brand with a brand congruity and SN. The findings show that when consumers feel a fashion brand is aligned with their sense of self-image, they have a greater tendency to expect that significant others, like friends and influencers, would endorse their choice of the brand. This alignment fosters a normative belief that strengthens behavioral intentions to engage in consumption aligned with group expectations. Table 6. Summary of Empirical evidence on the relationship between brand congruity and subjective norms toward fast fashion brands. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) CFFB SN 201 0.295 Survey/Taiwan Setyaningsih and Asnawi (2022) CFFB SN 204 0.337 Survey/Indonesia Lee et al. (2023) CFFB SN 385 0.251 Survey/China Chau and Thanh (2022) CFFB SN 510 0.332 Survey/Vietnam Chen et al. (2022) CFFB SN 225 0.212 Survey/Taiwan Additionally, this relationship is framed by social identity theory ( Tajfel & Turner, 1981 ), which states that people’s identity is partly a result of their connection to social groups. As such, fast fashion brands that reflect collective or group-based identities (e.g., youth culture, sustainability-conscious groups) may reinforce both individual and normative motivations to engage with the brand. H6: Congruity between consumer self-image and fast fashion brand identity positively influences subjective norms toward the brand. According to Ajzen’s (1991) TPB, PBC is the degree to which an individual feels that performing a certain action would be either easy or difficult. It shares conceptual overlap with Bandura’s notion of self-efficacy and reflects one’s belief in their capacity to act despite potential barriers or facilitators. Recent research has increasingly integrated self-congruity theory ( Sirgy, 1982 ) into the TPB framework, emphasizing that when a brand’s image aligns with a consumer’s self-concept, it can impact not only their attitudes and subjective norms but also their sense of control. Empirical findings, as summarized in Table 7 , provide strong support for this proposition. Studies across diverse contexts—including Vietnam ( Chau & Thanh, 2022 ), the U.S. ( Shin et al., 2016 ), and Thailand ( Han & Chen, 2024 )—have reported positive and significant correlations between brand congruity and PBC. These results suggest that when fast fashion brands resonate with a consumer’s self-identity, they foster a sense of agency, making the act of purchasing feel more feasible, appropriate, and achievable. Table 7. Summary of Empirical evidence on the relationship between brand congruity and perceived behavioral control toward fast fashion brands. Author(s) name Independent variable Dependent variable n r Method/Country Chau and Thanh (2022) CFFB PBC 510 0.372 Survey/Vietnam Shin et al. (2016) CFFB PBC 854 0.43 Survey/USA Han and Chen (2024) CFFB PBC 304 0.402 Survey/Thailand Yen and Mai (2020) CFFB PBC 539 0.55 Survey/Vietnam This theoretical integration is especially relevant in fast fashion, where brand symbolism plays a critical role. Products are not merely functional; they serve as social markers of identity and status. Thus, when a consumer sees a brand as an extension of themselves, the psychological barriers to purchase are lowered. The increased confidence and fluency in decision-making fostered by congruity reinforce one’s perception of behavioral control, enhancing overall purchase intention and consumer empowerment. H7: Congruity between consumer self-image and fast fashion brand identity positively influences perceived behavioral control. 2.2.3 Perceived quality positively influences consumers’ attitude toward fast fashion brands, subjective norm, perceived behavioral control, and intention to purchase fast fashion Perceived Quality is a central concept in consumer behavior research. According to Zeithaml (1988) , it reflects a consumer’s assessment of a product’s overall excellence. These perceptions are critical in attitude-behavior and expectancy-value frameworks, as they affect both emotional responses and evaluations of the brand, ultimately influencing consumer attitudes. Attitude, in turn, is conceptualized as a consumer’s overall evaluative disposition—favorable or unfavorable—toward engaging with a particular brand or product category ( Ajzen, 1991 ). When consumers perceive a brand’s offerings as being of high quality—whether in terms of aesthetics, material durability, functionality, or value— it becomes more probable that they will have a positive view of the brand. Empirical studies as shown in Table 8 have consistently demonstrated that PQ positively influences brand attitude. Gelaidan et al. (2023) demonstrated that perceived service quality plays a significant role in shaping consumer attitudes toward sustainable metro services in the transportation sector. Likewise, in the context of organic foods, factors such as taste and safety have been found to enhance consumer assessments and intentions to buy ( Teixeira et al., 2021 ). Within the beauty and personal care industry, Echchad and Ghaith (2022) found that product quality and environmental values jointly contributed to a favorable attitude toward green cosmetics. In service-oriented contexts, Foroudi et al. (2021) highlighted the effect of high-quality perception on consumers’ attitude toward restaurant brands, and similar effects were documented in ESG-related brand perception studies ( Koh et al., 2022 ). Notably, Wang et al. (2020) identified that PQ was a key determinant of Chinese consumers’ attitudes toward certified pork, suggesting that this construct may hold cross-industry and cross-cultural relevance. Table 8. Summary of Empirical evidence on the relationship between perceived quality and attitude toward fast fashion brand. Author(s) name Independent variable Dependent variable n r Method/Country Koh et al. (2022) PQ AT 458 0.378 Survey/Korean Foroudi et al. (2021) PQ AT 448 0.323 Survey/UK Gelaidan et al. (2023) PQ AT 1334 0.207 Survey/Qatar Hou et al. (2021) PQ AT 503 0.71 Survey/China AlHadid et al. (2022) PQ AT 442 0.299 Survey/Jordan Wang et al. (2020) PQ AT 844 0.545 Survey/Hong Kong Teixeira et al. (2021) PQ AT 206 0.85 Survey/Portugal Echchad and Ghaith (2022) PQ AT 204 0.31 Survey/Hungary Jalil and Shaharuddin (2020) PQ AT 98 0.64 Survey/Malaysia In the fast fashion context, although relatively underexplored, the positive link between PQ and consumer attitude is theoretically transferable. Fast fashion brands typically compete by offering trend-responsive, affordable clothing at scale. If consumers perceive these products as being well-designed, comfortable, or offering good value for money, such perceptions are likely to translate into favorable brand evaluations. As evidenced by studies from Koh et al. (2022) , Hou et al. (2021) , and Teixeira et al. (2021) , fast fashion consumers in various markets tend to report positive attitudes when they associate the brand with reliability, style, and price-quality alignment. Therefore, grounded in both theoretical expectations and cross-sector empirical findings, this study proposes the following hypothesis: H8: PQ positively influences consumers’ attitude toward fast fashion brands and perceived behavioral control toward fast fashion brands. While the role of PQ in shaping attitudes and purchase intentions is well-documented, its impact on subjective norm—a key construct in the TPB—has received limited attention, particularly in fast fashion. Subjective norm captures the perceived expectations of important others, including friends, family, or peers, about engaging in specific behaviors ( Ajzen, 1991 ). Emerging studies suggest that perceptions of brand quality can influence consumers’ own evaluations as well as their beliefs regarding what behaviors are socially endorsed among peers. Empirical studies as shown in Table 9 provide emerging support for this association. For instance, Nurhidayat et al. (2023) showed a strong correlation between PQ and subjective norms in the Indonesian fashion context (r = 0.645), which suggests that when consumers view a fashion brand as high-quality, it becomes more probable that they will feel others approve of using the brand as well. Similarly, research in China and Hong Kong ( Hou et al., 2021 ; Wang et al., 2020 ) confirmed that PQ exerts a substantial effect on subjective norm, indicating a shared valuation process where quality signals influence collective norms of acceptability and desirability. Table 9. Summary of Empirical evidence on the relationship between perceived quality and subjective norm toward fashion brand. Author(s) name Independent variable Dependent variable n r Method/Country Nurhidayat et al. (2023) PQ SN 100 0.645 Survey/Indonesia Hou et al. (2021) PQ SN 503 0.57 Survey/China Wang et al. (2020) PQ SN 844 0.306 Survey/Hong Kong The mechanism underlying this relationship may stem from social validation: consumers tend to internalize quality cues not only as personal assessments but also as indicators of how others might evaluate the brand. In fast fashion, where peer identity and trend alignment are salient, a high PQ can serve as a normative anchor that guides social behavior. That is, consumers may perceive that others expect them to use or recommend brands that are perceived as reliable, stylish, or environmentally responsible—attributes commonly associated with quality. Furthermore, the symbolic value attached to quality in fashion contexts—especially in cultures with strong collectivist orientations—amplifies the likelihood that quality perceptions translate into social conformity pressures. Accordingly, it is proposed that when consumers view a fast fashion brand as high-quality, they are more inclined to think that important referents would approve of their purchasing decisions. Based on this reasoning, the following hypothesis is proposed: H9: PQ positively influences consumers’ subjective norm toward fast fashion brands. PBC, a central construct in the TPB, reflects an individual’s perception of the ease or difficulty of performing a given behavior, often influenced by both internal factors (e.g., skills, knowledge) and external resources (e.g., time, money, support) ( Ajzen, 1991 ). While PBC is traditionally conceptualized as distinct from attitudinal or normative beliefs, emerging research has suggested that external cues—such as perceived product quality—may indirectly shape individuals’ sense of behavioral control, especially in consumption contexts where quality is linked to trust, predictability, and satisfaction. Although the relationship between PQ and PBC has not been widely examined in fast fashion specifically, studies as shown in Table 10 offer theoretical support for a positive link. Wang et al. (2020) found that in the context of certified pork consumption in China, perceived product quality significantly enhanced subjective norm and interacted positively with PBC, indicating that higher quality perception may enhance consumers’ confidence in engaging in the intended behavior. Similarly, Hou et al. (2021) demonstrated that perceived train service quality significantly strengthened PBC in a high-speed rail setting, as better service experiences led passengers to feel more capable of using the service reliably and regularly. Table 10. Summary of Empirical Evidence on the Relationship between Perceived Quality and Subjective Norm toward Fashion Brand. Author(s) name Independent variable Dependent variable n r Method/Country Gelaidan et al. (2023) PQ PBC 1334 0.417 Survey/Qatar Hou et al. (2021) PQ PBC 503 0.54 Survey/China Abu-Taieh et al. (2022) PQ PBC 403 0.154 Survey/Jordan Wang (2020) PQ PBC 844 0.442 Survey/Hong Kong Yu et al. (2024) PQ PBC 1109 -0.07 Survey/China Further evidence from Gelaidan et al. (2023) , Abu-Taieh et al. (2022) , and Yu et al. (2024) shows mixed but generally positive correlations between PQ and PBC in the context of fashion and services. These findings support the idea that when consumers believe a product or service is of high quality, they are more likely to feel in control of their decision to use or purchase it—due to expectations of reliability, ease of use, and lower risk of dissatisfaction. Applying these insights to the fast fashion domain, we can infer that consumers who perceive fast fashion brands as high-quality may also feel more confident in their ability to make satisfying and socially supported purchase decisions. High PQ may reduce perceived risks, increase perceived access, and foster a sense of empowerment in the purchase process—thereby strengthening perceived behavioral control. Therefore, the following hypothesis is proposed: H10: PQ positively influences consumers’ perceived behavioral control toward fast fashion brands. For a long time, PQ has been considered a fundamental influence on consumer choices, playing a significant role in forming behavioral intentions in various consumption contexts. In the framework of the TPB, PQ is often incorporated as an external belief-based factor that indirectly or directly influences key outcome variables, such as purchase intention or behavioral control. Although the influence of perceived quality (PQ) on fast fashion consumption intention has received limited scholarly attention, emerging empirical findings indicate a strong positive association between the two variables (see Table 11 ). Table 11. Summary of Empirical evidence on the relationship between perceived quality and intention to increase fast fashion consumption. Author(s) name Independent variable Dependent variable n r Method/Country Aquinia et al. (2021) PQ IFFC 100 0.202 Survey/Indonesia Islam et al. (2022) PQ IFFC 236 0.207 Survey/Bangladesh Akem and Cheumar (2024) PQ IFFC 381 0.164 Survey/Malaysia Filieri and Lin (2017) PQ IFFC 321 0.38 Survey/UK Nurhidayat et al. (2023) PQ IFFC 100 0.22 Survey/Indonesia Das (2014) PQ IFFC 365 0.496 Survey/Malaysia Wang et al. (2020) PQ IFFC 844 0.318 Survey/Hong Kong Kanwar and Huang (2022) PQ IFFC 400 0.71 Survey/Taiwan Hardiyanto et al. (2020) PQ IFFC 210 0.731 Survey/Indonesia Cayaban et al. (2023) PQ IFFC 407 0.109 Survey/Philippines Hou et al. (2021) PQ IFFC 503 0.28 Survey/China Abu-Taieh et al. (2022) PQ IFFC 403 0.164 Survey/Jordan As an example, Wang et al. (2020) showed that Chinese consumers who perceived higher product quality in certified pork exhibited stronger intentions to purchase, mediated by enhanced confidence and PBC. Similarly, in the high-speed rail context, Hou et al. (2021) found that a high standard of service quality significantly influenced both a person’s sense of behavioral control and their intentions. In the public transportation domain, Gelaidan et al. (2023) confirmed that service quality enhances users’ perceived ability and motivation to engage in the intended behavior. Although these studies are drawn from non-fashion contexts, they consistently support the view that high PQ contributes to increased confidence, perceived control, and ultimately stronger behavioral intentions. Drawing from these findings, recent research in the fast fashion industry has increasingly confirmed a direct effect of Perceived Quality (PQ) on consumers’ purchase intentions. Studies from diverse countries—including Indonesia ( Aquinia et al., 2021 ; Hardiyanto et al., 2020 ), Malaysia ( Akem & Cheumar, 2024 ), China ( Hou et al., 2021 ), and the UK ( Filieri & Lin, 2017 )—report moderate to strong positive correlations (ranging from r = 0.164 to r = 0.731) between consumers’ perception of product quality and their intention to increase consumption. These results suggest that consumers who perceive fast fashion products as stylish, well-made, and reasonably priced are more likely to express intentions to purchase more frequently or in larger quantities. In fast fashion, where purchase decisions are often spontaneous and influenced by aesthetic appeal, PQ may serve not only as a signal of product value but also as a justification for repeat or increased purchases. Higher quality perception reduces cognitive dissonance, elevates satisfaction, and enhances consumers’ willingness to re-engage with the brand. Thus, when consumers believe that fast fashion products meet their expectations in terms of design, durability, and affordability, their intention to increase consumption is likely to be strengthened. Based on these insights, the following hypothesis is proposed: H11: PQ positively influences consumers’ intention to increase fast fashion consumption. 2.2.4 The effect of subjective norms and perceived behavioral control on intentions to increase fast fashion consumption In the TPB model, PBC is a critical determinant of behavioral intention. It is defined as an individual’s sense of their capacity to perform a specific behavior, influenced by both internal elements (e.g., confidence, skills) and external factors (e.g., time, money, social support) as described by Ajzen (1991) . In consumer research, PBC has been consistently linked to purchase intentions, particularly in contexts where decision-making involves autonomy, convenience, or perceived accessibility. In the fast fashion sector, where product availability is high and purchasing decisions are often impulsive yet frequent, PBC plays a particularly salient role. When consumers feel they have sufficient control—such as financial affordability, access to retail channels, and confidence in personal style or product selection—they are more likely to act on their consumption impulses. Prior empirical studies have confirmed this relationship in adjacent domains. As shown in Table 12 , Gelaidan et al. (2023) and Hou et al. (2021) reported that higher PBC significantly enhanced behavioral intentions in public transportation and service settings. Similarly, Wang et al. (2020) found that Chinese consumers’ PBC was positively correlated with their intention to purchase certified pork, especially when quality and availability were perceived as favorable. Table 12. Summary of Empirical evidence on the relationship between attitude toward fast fashion brand and intention to increase fast fashion consumption. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) AT IFFC 201 0.434 Survey/Taiwan Zhu et al. (2024) AT IFFC 913 0.353 Survey/China Nguyen et al. (2022) AT IFFC 638 0.405 Survey/Vietnam Chaudhary and Bisai (2018) AT IFFC 202 0.4 Survey/India Cayaban et al. (2023) AT IFFC 407 0.656 Survey/Indonesia Koh et al. (2022) AT IFFC 458 0.854 Survey/Korean Rostiani and Kuron (2019) AT IFFC 336 0.41 Survey/Indonesia Hageman et al. (2024) AT IFFC 155 0.606 Survey/UK Kashif et al. (2018) AT IFFC 484 0.31 Survey/Pakistan Chen et al. (2022) AT IFFC 225 0.662 Survey/Taiwan Badrinarayanan et al. (2014) AT IFFC 316 0.57 Survey/USA Yusuf (2021) AT IFFC 200 0.511 Survey/Indonesia Harjadi and Gunardi (2022) AT IFFC 419 0.314 Survey/Indonesia Aziz (2019) AT IFFC 319 0.308 Survey/Pakistan Phang and Ilham (2023) AT IFFC 394 0.449 Survey/Malaya Rao et al. (2022) AT IFFC 345 0.245 Survey/USA Chetioui et al. (2020) AT IFFC 610 0.462 Survey/Morocco Stolz (2022) AT IFFC 469 0.172 Survey/Germany Roh et al. (2022) AT IFFC 251 0.486 Survey/Korea Li et al. (2022) AT IFFC 389 0.646 Survey/Malaysia Hao and Jusoh (2024) AT IFFC 211 0.872 Survey/Malaysia Nam et al. (2017) AT IFFC 542 0.4 Survey/USA Suha and Chaichi (2018) AT IFFC 240 0.512 Survey/Malaysia Chetioui et al. (2021) AT IFFC 298 0.55 Survey/Moroccan Rafiq et al. (2020) AT IFFC 452 0.731 Survey/ Lili et al. (2022) AT IFFC 301 0.393 Survey/Malaysia Ma et al. (2023) AT IFFC 471 0.213 Survey/Vietnam Gelaidan et al. (2023) AT IFFC 1334 0.783 Survey/Qatar Islam et al. (2022) AT IFFC 236 0.578 Survey/Bangladesh Teixeira et al. (2021) AT IFFC 206 0.92 Survey/Portugal Echchad and Ghaith (2022) AT IFFC 204 0.786 Survey/Hungary Köse and Özer Çizer (2021) AT IFFC 399 0.687 Survey/Turkish Jain (2020) AT IFFC 215 0.143 Survey/India Yang and Ahn (2020) AT IFFC 456 0.733 Survey/South korea Hasan and Suciarto (2020) AT IFFC 100 0.527 Survey/Indonesia Liu et al. (2020) AT IFFC 485 0.21 Survey/China Bhati et al. (2022) AT IFFC 449 0.359 Survey/India Lee et al. (2023) AT IFFC 385 0.489 Survey/China Setyaningsih and Asnawi (2022) AT IFFC 204 0.718 Survey/Indonesia Hou et al. (2021) AT IFFC 503 0.67 Survey/China AlHadid et al. (2022) AT IFFC 442 0.998 Survey/Jordan Wang et al. (2020) AT IFFC 844 0.731 Survey/Hong Kong Jalil and Shaharuddin (2020) AT IFFC 98 0.83 Survey/Malaysia Shin et al. (2016) AT IFFC 854 0.44 Survey/USA Translating this to fast fashion, consumers who believe they can easily afford, access, and choose fashion products that match their preferences are more inclined to increase consumption frequency or quantity. PBC may be shaped by factors such as the affordability of fast fashion items, the ubiquity of both physical and online retail platforms, and consumers’ confidence in assembling fashionable outfits. This sense of control reduces psychological barriers and heightens the likelihood of engaging in repeat consumption behavior. Thus, consistent with TPB and empirical evidence across multiple consumption contexts, this study proposes the following hypothesis: H12: Perceived behavioral control positively influences consumers’ intention to increase fast fashion consumption. In the original TPB, PBC is considered to directly influence behavioral intention, alongside the effects of attitude and subjective norms. However, recent extensions of TPB and related consumer behavior models suggest that PBC may also indirectly shape other cognitive-affective antecedents, particularly consumer attitude. Attitude is a consumer’s total evaluation, either positive or negative, regarding their participation in a certain behavior or their support for a brand ( Ajzen, 1991 ). When consumers feel they have control over their actions, including the ease, competence, and resources needed to make decisions, this increases the likelihood of generating positive judgments toward the brand or behavior. Empirical studies as shown in Table 13 support this expanded conceptual pathway. For example, in the context of green consumption, consumers who perceive fewer barriers to purchasing eco-friendly products tend to develop more favorable attitudes toward those products ( Yadav & Pathak, 2017 ). In online shopping environments, users with greater perceived control over navigation, purchase steps, or platform familiarity report more positive evaluations of the shopping experience ( Pappas, 2016 ). These findings indicate that a sense of behavioral control can reduce anxiety, increase self-efficacy, and enhance trust—factors that are foundational to favorable attitude formation. Table 13. Summary of Empirical evidence on the relationship between subjective norm toward fashion brand and intention to increase fast fashion consumption. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) SN IFFC 201 0.18 Survey/Taiwan Zhu et al. (2024) SN IFFC 913 0.152 Survey/China Nguyen et al. (2022) SN IFFC 638 0.208 Survey/Vietnam Chaudhary and Bisai (2018) SN IFFC 202 -0.02 Survey/India Nurhidayat et al. (2023) SN IFFC 100 0.258 Survey/Indonesia Cayaban et al. (2023) SN IFFC 407 0.074 Survey/Indonesia Rostiani and Kuron (2019) SN IFFC 336 0.18 Survey/Indonesia Kashif et al. (2018) SN IFFC 484 0.092 Survey/Pakistan Yusuf (2021) SN IFFC 200 0.266 Survey/Indonesia Harjadi and Gunardi (2022) SN IFFC 419 0.810 Survey/Indonesia Aziz (2019) SN IFFC 319 0.238 Survey/Pakistan Phang and Ilham (2023) SN IFFC 394 0.428 Survey/Malaya Rao et al. (2022) SN IFFC 345 0.293 Survey/USA Stolz (2022) SN IFFC 469 0.228 Survey/Germany Roh et al. (2022) SN IFFC 251 0.332 Survey/Korea Li et al. (2022) SN IFFC 389 0.52 Survey/Malaysia Hao and Jusoh (2024) SN IFFC 211 0.771 Survey/ Nam et al. (2017) SN IFFC 542 0.32 Survey/USA Suha and Chaichi (2018) SN IFFC 240 0.442 Survey/Malaysia Islam et al. (2022) SN IFFC 236 0.12 Survey/Bangladesh Echchad and Ghaith (2022) SN IFFC 204 -0.081 Survey/Hungary Akem and Cheumar (2024) SN IFFC 381 -0.037 Survey/Malaysia Filieri and Lin (2017) SN IFFC 321 0.169 Survey/UK Teixeira et al. (2021) SN IFFC 206 0.13 Survey/Portugal Jain (2020) SN IFFC 215 0.257 Survey/India Yang and Ahn (2020) SN IFFC 456 0.329 Survey/South korea Hasan and Suciarto (2020) SN IFFC 100 -0.28 Survey/Indonesia Liu et al. (2020) SN IFFC 485 0.13 Survey/China Bhati et al. (2022) SN IFFC 449 0.337 Survey/India Hou et al. (2021) SN IFFC 503 0.42 Survey/China Wang et al. (2020) SN IFFC 844 0.317 Survey/Hong Kong Jalil and Shaharuddin (2020) SN IFFC 98 0.11 Survey/Malaysia Chetioui et al. (2020) SN IFFC 610 0.141 Survey/Morocco Shin et al. (2016) SN IFFC 854 0.05 Survey/USA Applied to fast fashion, this relationship is particularly relevant. When consumers believe they have the autonomy to choose affordable, trendy items and can easily access and evaluate product information, their perceived control reinforces confidence and satisfaction. This positive user experience, in turn, fosters a favorable affective evaluation of the brand. In contrast, if consumers feel constrained—by price, sizing availability, or ethical concerns—their attitude may be tempered regardless of the product offering. Therefore, in line with the extended TPB and supporting empirical evidence, we propose the following hypothesis: H13: Perceived behavioral control positively influences consumers’ attitude toward fast fashion brands. In the TPB, Ajzen (1991) defines PBC as one’s assessment of their ability to perform a given action, shaped by resources, opportunities, and constraints. While PBC is generally considered a robust predictor of behavioral intention, its influence on fast fashion consumption remains empirically inconsistent across contexts and cultures. The empirical studies as shown in Table 14 report a significant and positive relationship between PBC and the intention to increase consumption. For example, Cayaban et al. (2023) discovered that Filipino consumers with confidence in their ability to find and afford a wide range of fashion items were more prone to have a stronger intent to consume. The availability of product choices and the convenience of access were highlighted as core dimensions enhancing PBC. Likewise, Liu et al. (2023) and Zhu et al. (2024) in Korea and China, respectively, observed strong correlations (r = 0.58 to 0.787) between PBC and fast fashion consumption intention, indicating that perceived ease in navigating retail environments plays a crucial role in fostering behavioral intention. Table 14. Summary of Empirical evidence on the relationship between perceived behavioral control toward fashion brand and intention to increase fast fashion consumption. Author(s) name Independent variable Dependent variable n r Method/Country Chang et al. (2024) PBC IFFC 201 0.207 Survey/Taiwan Zhu et al. (2024) PBC IFFC 913 0.58 Survey/China Liu et al. (2023) PBC IFFC 400 0.787 Survey/Korea Chaudhary and Bisai (2018) PBC IFFC 202 0.74 Survey/India Cayaban et al. (2023) PBC IFFC 407 0.214 Survey/Indonesia Rostiani and Kuron (2019) PBC IFFC 336 0.099 Survey/Indonesia Kashif et al. (2018) PBC IFFC 484 0.766 Survey/Pakistan Aziz (2019) PBC IFFC 319 0.942 Survey/Pakistan Phang and Ilham (2023) PBC IFFC 394 0.236 Survey/Malaya Rao et al. (2022) PBC IFFC 345 0.249 Survey/USA Stolz (2022) PBC IFFC 469 0.247 Survey/Germany Li et al. (2022) PBC IFFC 389 0.423 Survey/Malaysia Giantari et al. (2013) PBC IFFC 150 0.602 Survey/Indonesia Hao and Jusoh (2024) PBC IFFC 211 0.766 Survey/Malaysia Nam et al. (2017) PBC IFFC 542 0.06 Survey/USA Gelaidan et al. (2023) PBC IFFC 1334 0.175 Survey/Qatar Islam et al. (2022) PBC IFFC 236 0.184 Survey/Bangladesh Nurhidayat et al. (2023) PBC IFFC 100 0.049 Survey/Indonesia Teixeira et al. (2021) PBC IFFC 206 0.08 Survey/Portugal Jain (2020) PBC IFFC 215 0.272 Survey/India Hasan and Suciarto (2020) PBC IFFC 100 0.572 Survey/Indonesia Liu et al. (2020) PBC IFFC 485 0.1 Survey/China Bhati et al. (2022) PBC IFFC 449 0.316 Survey/India Hou et al. (2021) PBC IFFC 503 0.22 Survey/China Wang et al. (2020) PBC IFFC 844 0.57 Survey/Hong Kong Yusuf (2021) PBC IFFC 200 -0.003 Survey/Indonesia Harjadi and Gunardi (2022) PBC IFFC 419 -0.09 Survey/Indonesia Chetioui et al. (2020) PBC IFFC 610 0.193 Survey/Morocco Ma et al. (2023) PBC IFFC 471 0.088 Survey/Vietnam Shin et al. (2016) PBC IFFC 854 0.34 Survey/USA Some studies have produced conflicting results. Yusuf (2021) reported that PBC did not significantly influence behavioral intention in online fashion shopping, which he explained by consumers’ sense of limited control in digital purchase settings. Similarly, Nurhidayat et al. (2023) observed weak or insignificant effects of PBC in housing contexts, potentially due to respondents’ limited decision-making experience. Looking beyond fashion, PBC has been found to influence behavioral intentions in domains such as tourism real estate ( Ma et al., 2023 ), organic food ( Boobalan & Nachimuthu, 2020 ), and post-pandemic retail consumption ( Liu et al., 2023 ). These findings emphasize the contextual sensitivity of PBC, suggesting that its predictive power may depend on product familiarity, cost structure, and perceived risk. For instance, in high-involvement product categories such as real estate or housing, the effect of PBC may be muted by structural barriers like affordability or bureaucratic constraints. In contrast, low-involvement categories like fast fashion may provide more opportunity for PBC to shape consumer intention. Given this variation, it is premature to generalize PBC’s effectiveness across all consumption settings. Yet, the cumulative evidence indicates that in fast fashion—characterized by low entry barriers, trend responsiveness, and wide accessibility—consumers who feel empowered in their decision-making processes are more inclined to increase their purchase behavior. Accordingly, this study proposes the following hypothesis: H14: Perceived behavioral control positively influences consumers’ intention to increase fast fashion consumption. 2.2.5 The effect of intentions to increase on brand loyalty toward fast fashion brand Brand loyalty refers to a consumer’s ongoing preference for and commitment to a particular brand over time. This loyalty is often demonstrated through repeated purchases, emotional attachment, and a readiness to tolerate minor product flaws or price differences in favor of the favored brand. In marketing theory, loyalty is not only a key indicator of long-term brand performance but also a crucial mediator between consumer satisfaction and firm profitability. While existing empirical studies have seldom focused specifically on the fast fashion sector, considerable evidence from related fields suggests that purchase intention plays a pivotal role in cultivating brand loyalty. Purchase intention, often described as the consumer’s expressed probability or will to buy a product in the next time, is typically regarded as an antecedent of both actual purchasing behavior and attitudinal commitment ( Yasin & Shamim, 2013 ; Das, 2014 ). Consumers who report a high intention to increase their consumption of a brand’s offerings typically exhibit underlying positive evaluations of that brand—whether based on PQ, emotional resonance, brand symbolism, or utility value. These evaluations, when reinforced over time, foster the emergence of brand loyalty. Numerous studies as shown in Table 15 support this causal chain. Das (2014) , in the Indian non-food retail context, demonstrated that purchase intention was significantly associated with loyalty, particularly when driven by utilitarian and hedonic value. Similarly, Laksamana (2018) examined Indonesian banking consumers and found that purchase intention strongly predicted brand loyalty, suggesting the robustness of this relationship across diverse service industries. In the green marketing domain, Panda et al. (2020) highlighted that purchase intention driven by environmental concern translated into repeat purchases and brand advocacy. Pangaribuan et al. (2020) , examining Indonesia’s Luwak White Coffee, confirmed that repeated behavioral intention was one of the most effective predictors of long-term loyalty. Table 15. Summary of Empirical evidence on the relationship between intention to increase fast fashion consumption and brand loyalty toward fast fashion brand. Author(s) name Independent variable Dependent variable n r Method/Country Laksamana (2018) IFFC BL 286 0.565 Survey/Indonesia Panda et al. (2020) IFFC BL 331 0.475 Survey/India Pangaribuan et al. (2020) IFFC BL 100 0.425 Survey/Indonesia Mookda et al. (2020) IFFC BL 351 0.47 Survey/Malaysia Panda et al. (2020) IFFC BL 331 0.475 Survey/UK Das (2014) IFFC BL 365 0.367 Survey/India Although fast fashion is often associated with low involvement and impulsivity, these traits do not necessarily preclude brand loyalty formation. Fast fashion brands like Zara, H&M, or Uniqlo can evoke strong consumer attachment through brand image consistency, product availability, and lifestyle alignment. A consumer who repeatedly intends to shop from the same fast fashion brand—driven by satisfaction, habit, or convenience—may develop both behavioral and attitudinal loyalty over time. Moreover, the psychological mechanisms linking intention and loyalty are reinforced through positive reinforcement cycles. The more frequently a consumer acts on their purchase intention and experiences satisfaction, the more likely they are to internalize a loyal mindset toward the brand. This loyalty is expressed through increased retention, greater tolerance for product shortcomings, and stronger emotional endorsement. Drawing upon theoretical principles and research findings from similar domains, this study proposes the following hypothesis: H15: Intention to increase fast fashion consumption positively influences consumers’ loyalty toward fast fashion brands. 2.2.6 The effect of intention to increase fast fashion consumption on WoM behavior WoM behavior, both offline and online, is a crucial manifestation of post-consumption engagement that shapes brand perception and market diffusion. In the age of digital consumerism and social sharing, particularly in visually-driven industries like fashion, WoM serves as a vital conduit for brand influence, social validation, and peer persuasion. While few empirical studies currently explore this relationship in the fast fashion context, a substantial body of literature from various industries consistently supports a positive relationship between purchase intention and WoM behavior. Purchase intention reflects a consumer’s motivational state to engage in buying behavior and is frequently cited as a predictor of not only actual purchase but also related behaviors such as recommending, reviewing, and advocating for a brand ( Yasin & Shamim, 2013 ; Abu-Taieh et al., 2022 ). When a consumer develops a strong intention to purchase, this mental commitment often spills over into interpersonal communication, particularly when the brand aligns with their identity or delivers a satisfying experience. In empirical research as shown in Table 16 , Yasin and Shamim (2013) observed that mobile phone users with high purchase intentions were significantly more likely to engage in WoM activities. This behavior was reinforced by emotional involvement and social influence. In a service context, Abu-Taieh et al. (2022) reported similar findings among mobile banking consumers in Jordan, where behavioral intention translated into active advocacy and brand promotion. Most notably, Farzin et al. (2023) showed that in the eco-fashion space, consumers’ purchase intentions had a direct and significant effect on electronic WoM suggesting that intention-driven communication behavior is not confined to functional or utilitarian products but extends to fashion as well. Table 16. Summary of Empirical evidence on the relationship between intention to increase fast fashion consumption and word-of- mouth toward fashion brand. Author(s) name Independent variable Dependent variable n r Method/Country Yasin and Shamim (2013) IFFC WoM 265 0.318 Survey/Pakistan Abu-Taieh et al. (2022) IFFC WoM 403 0.746 Survey/Jordan Farzin et al. (2023) IFFC WoM 389 0.917 Survey/Iran Shah et al. (2020) IFFC WoM 307 0.236 Survey/China Jo (2023) IFFC WoM 645 0.525 Survey/Korea Fast fashion’s dynamic and trend-sensitive ecosystem further amplifies the potential for intention to drive WoM. Consumers are often highly engaged with their fashion choices and motivated to share outfit inspirations, product hauls, and brand experiences across social media platforms. A strong intention to consume not only increases the likelihood of purchase but also enhances the consumer’s willingness to share their enthusiasm with peers—especially in youth-driven or style-conscious segments. In this way, WoM becomes a behavioral extension of consumption intention. Furthermore, WoM is shaped by motivational factors such as self-enhancement, social affiliation, and informational utility. When a consumer intends to make a purchase, they are often gathering or disseminating information, which naturally involves discussing the brand with others. This process is especially relevant in fast fashion, where new styles, limited-time collections, and social comparison cues heighten the likelihood of shared conversations. In sum, although fast fashion-specific research is limited, the consistent empirical pattern across retail, service, and fashion-related studies provides strong justification for the following hypothesis: H16: Intention to increase fast fashion consumption positively influences consumers’ WoM behavior toward fast fashion brands. 3. Methodology 3.1 Meta-analysis Meta-analysis is a robust quantitative research technique designed to synthesize the statistical results of multiple empirical studies that investigate similar theoretical relationships. By aggregating effect sizes across studies, meta-analysis gives a thorough look at the strength, nature, and consistency of variable relationships, while also correcting for potential sampling error and publication bias. This method is particularly useful in fields with mixed results or fragmented theories, because it helps to identify overall patterns, spot inconsistencies, and find missing areas in the existing research. To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979) , and Egger’s regression test, introduced by Egger et al. (1997) . These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12 = 88.60; H14 = 42.85; H5 = 33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value = −0.06, p = 0.99; H13’a intercept = 0.18, p = 0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. Within this research, meta-analysis functions as a robust tool for synthesizing the empirical findings about the factors that precede and result from fast fashion consumption, including PQ, behavioral control, SN, and their impacts on brand loyalty and WoM behavior. Following the protocols of Borenstein et al. (2010) and Wilson and Lipsey (2001) , this meta-analytic investigation adheres to established guidelines to calculate pooled effect sizes, assess heterogeneity, and identify potential moderating influences. A random-effects model was employed throughout the study to account for differences between the research included, such as studied year, sample demographics, methodologies used, and cultural contexts ( Field & Gillett, 2010 ). The procedure ensures transparency, replicability, and theoretical advancement through the integration of dispersed findings. 3.2 Literature search To compile a comprehensive dataset, the authors employed multiple search strategies across a variety of academic databases, including Scopus, Web of Science, ScienceDirect, JSTOR, SpringerLink, Emerald, and Google Scholar. The keywords used included combinations of terms such as ‘fast fashion,’ ‘purchase intention,’ ‘perceived quality,’ ‘brand loyalty,’ ‘behavioral control,’ ‘subjective norm,’ and ‘word of mouth.’ Additionally, the authors screened peer-reviewed journals focusing on marketing, consumer behavior, retail management, and fashion studies, such as the Journal of Retailing and Consumer Services, Journal of Fashion Marketing and Management, and Psychology & Marketing. The search covered studies published between 2004 and 2024. Articles were excluded if they (a) were conceptual or purely theoretical, (b) lacked empirical data, (c) did not report the necessary statistical information (e.g., correlation coefficients, t-values, or standardized betas), or (d) focused on unrelated constructs. The research aimed to mitigate publication bias and the “file drawer problem” by including a variety of unpublished materials like conference papers, dissertations, and working papers ( Guzzo et al., 1987 ). 4. Results The objective of this meta-analysis was to thoroughly examine sixteen theoretically valid hypotheses using frameworks such as the TPB, PS Theory, Self-Congruity Theory, PQ Theory, and the ECL Model (see Table 17 ). Table 17. The meta-analysis results. Effective size and 95% Confidence Heterogeneity Variable Interval Hyp Ind. Dep. k n r LCI UCI p-value Q χ 2 I 2 H1 PS AT 5 1431 0.334 0.234 0.427 0.000 16.883 9.488 76.308 H2 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a H3 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a H4 PS IFFC 11 3600 0.181 0.044 0.311 0.010 174.041 18.31 94.254 H5 CFFB AT 16 6328 0.420 0.314 0.515 0.000 95.747 25.00 95.747 H6 CFFB SN 5 2934 0.544 0.408 0.656 0.000 91.841 9.49 95.645 H7 CFFB PBC 4 2207 0.442 0.360 0.518 0.000 15.515 7.81 80.664 H8 PQ AT 9 4537 0.509 0.345 0.643 0.000 353.394 15.51 97.736 H9 PQ SN 3 1447 0.513 0.284 0.687 0.000 44.110 5.99 95.466 H10 PQ PBC 5 4193 0.311 0.071 0.516 0.000 259.303 9.49 98.457 H11 PQ IFFC 12 4270 0.351 0.221 0.468 0.000 258.706 19.68 95.362 H12 AT IFFC 44 17760 0.605 0.491 0.698 0.000 5145.628 59.30 99.164 H13 SN IFFC 34 13022 0.253 0.174 0.328 0.000 753.045 47.40 95.559 H14 PBC IFFC 30 12788 0.385 0.264 0.494 0.000 1724.060 42.56 98.318 H15 IFFC BL 6 1764 0.465 0.393 0.531 0.000 10.678 11.07 62.539 H16 IFFC WOM 5 2009 0.560 0.240 0.770 0.000 304.288 9.49 98.685 The first set of hypotheses looked into the idea of PS, which comes from scarcity theory. H1 proposed a positive correlation between PS and consumer attitudes towards fast fashion. The meta-analytic estimate revealed a moderate effect size (r = 0.334, 95% CI [0.234, 0.427], p < 0.001), suggesting that limited availability likely augments consumers’ evaluative responses. Notable heterogeneity (Q = 16.883, df = 4, p = 0.002; I 2 = 76.31%) implies that this effect may be dependent on contextual variables, such as the manner in which scarcity cues are framed or perceived. These findings are congruent with both the S-O-R paradigm and the TPB, which posit that environmental stimuli can elicit urgency-driven attitudes. H2 and H3, on the other hand, looked at how scarcity affects SN and PBC, but they couldn’t be evaluated because there weren’t enough qualifying primary research. Although the theoretical justification for these pathways remains plausible, particularly within digitally mediated contexts where social proof and peer validation amplify scarcity cues, their empirical validation is an endeavor for future research. This gap represents a significant blind spot in the extant literature. H4 examined at how PS directly affects behavioral intention. The findings indicate a modest yet statistically significant effect (r = 0.181, 95% CI [0.044, 0.311], p 0.010), although substantial heterogeneity (Q = 174.041, df = 10, p < 0.001; I 2 = 94.25%) once more highlights the significance of moderating factors such as brand type, consumer characteristics, or the format of scarcity (e.g., time-limited versus quantity-limited). While scarcity seems to motivate purchase intention, its effects are notably heterogeneous. H5 through H7 looked examined how the congruence between self-image and brand identity (CFFB) affects the main TPB constructs in the SC dimension. H5 revealed a robust correlation with consumer attitudes (r = 0.420, 95% CI [0.314, 0.515], p < 0.001), albeit accompanied by high heterogeneity (I 2 = 95.75%). Hypothesis 6 identified an even stronger relationship with SN (r = 0.544), underscoring the symbolic and social dimensions of brand identification. Similarly, H7 confirmed that SC significantly enhances PBC (r = 0.442, p < 0.001), indicating that alignment with brand identity strengthens consumers’ sense of agency. Across all three constructs, the variation among studies suggests that congruity is interpreted through culturally and psychologically situated identity frameworks. H8 through H10 looked at the effect of the construct on the mediators of the TPB and focused on Perceived Quality Theory. H8 established a substantial and statistically significant positive correlation between PQ and attitudes (r = 0.509, 95% CI [0.345, 0.643], p < 0.001), although the heterogeneity was markedly pronounced (Q = 353.394, df = 8, p < 0.001; I 2 = 97.74%). H9 exhibited a comparable trend regarding SN (r = 0.513, 95% CI [0.284, 0.687], p < 0.001; Q = 44.110, df = 2, p < 0.001; I 2 = 95.47%), implying that product quality perceptions are not solely individualistic but may be shaped by social feedback and collective assessments. H10 found a statistically significant association with PBC (r = 0.311, 95% CI [0.071, 0.516], p < 0.001; Q = 259.303, df = 4, p < 0.001; I 2 = 98.46%). Overall, our data support the hypothesis that PQ has a major impact on cognitive evaluations that precede consumption intentions, albeit with considerable heterogeneity depending on contextual circumstances. H11 expanded the area of PQ by exploring its direct impact on behavioral intentions. The study found a moderate, positive association (r = 0.351, 95% CI [0.221, 0.468], p < 0.001; Q = 258.706, df = 11, p < 0.001; I 2 = 95.36%), highlighting the importance of perceived product qualities in consumer decision-making. These findings are especially noteworthy in light of fast fashion’s aesthetic and trend-driven dynamics, in which quality is usually determined by surface indications such as style and digital display rather than actual endurance. In the TPB framework, H12 found that attitude was the most important predictor of intention (r = 0.605, 95% CI [0.491, 0.698], p < 0.001), with significant heterogeneity (Q = 5145.628, df = 43, p < 0.001; I 2 = 99.16%). In H13, subjective norm had a substantial, albeit smaller, influence (r = 0.253, 95% CI [0.174, 0.328], p < 0.001; Q = 753.045, df = 33, p < 0.001; I 2 = 95.56%). H14 found a moderate impact of PBC on intention (r = 0.385, 95% CI [0.264, 0.494], p < 0.001), although heterogeneity remained high (Q = 1724.060, df = 29, p < 0.001; I 2 = 98.32%). These results validate the TPB’s structural integrity while highlighting varying degrees of influence, with evaluative attitudes having the greatest impact, followed by volitional control and social influences. Finally, H15 and H16, which are based on the Expectation-Confirmation-Loyalty Model, studied the behavioral consequences of intention. H15 found a moderate and statistically significant relationship between intention and brand loyalty (r = 0.465, 95% CI [0.393, 0.531], p < 0.001), with a reduced level of heterogeneity (Q = 10.678, df = 5, p = 0.058; I 2 = 62.54%). This suggests a more consistent and generalizable relationship between intention and loyalty in different circumstances. H16 showed a stronger connection between intention and WoM behavior (r = 0.560, 95% CI [0.240, 0.770], p < 0.001), although heterogeneity was still significant (Q = 304.288, df = 4, p < 0.001; I 2 = 98.69%). These findings support the notion that behavioral intention serves not only as a cognitive predictor of action, but also as a precursor to relational and communicative consequences, such as brand advocacy and loyalty. Fourteen out of sixteen hypotheses were empirically supported, with significant correlations (p < 0.001) and impact sizes ranging from small (r = 0.135) to large (r = 0.605). Attitude was identified as the most influential predictor of intention, whereas PQ and brand congruity had a significant impact across multiple dimensions of the TPB. The presence of heterogeneity in most relationships, as evidenced by significant Q-statistics and elevated I 2 values, suggests that future research should use moderator analyses (e.g., meta-regression, subgroup analysis) to better understand the discrepancies. 5. Discussion Based on the Theory of TPB, Self-Congruity Theory, PQ Theory, and ECL Model, the present meta-analysis sheds light on a comprehensive view of the psychological and social determinants of consumer behavior in the fast fashion industry. Fourteen of the sixteen initially proposed hypotheses were supported by empirical evidence, revealing a wide range of effects and significant heterogeneity, thus emphasizing the robustness and contextual variability of the important predictors. The results indicate that attitude is the strongest predictor of fast fashion consumption intention, corroborating the foundational premise of the original TPB that a consumer’s positive outlook is a major driver of their purchasing intentions. This study shows that attitude – a consumer’s overall positive or negative assessment of fast fashion – is an important internal factor that explains and guides how people behave as consumers in the fast fashion market where trends evolve quickly and buying choices are frequently based on emotion, impulse, or a product’s aesthetic charm. Similarly, perceived quality is also an important factor influencing AT, SN, PBC, and IFFC, which affects multiple psychological and social dimensions simultaneously. These findings imply that consumers’ perceptions of product quality, whether symbolic (design or aesthetics) or practical (durability or material), are important in promoting social trust, behavioral control, and positive attitudes. This result confirms and extends Zeithaml’s theory (1988) in the context of perceived quality and value playing a key role in persuading consumers to shop frequently at low prices. There was also a notable effect of CFFB on TPB’s key elements. The results show that when a brand aligns with a consumer’s self-image, they develop more favorable attitudes, a stronger sense of consumption control, and better social validation. These results confirm the extent to which product consumption is driven by identity, especially when the brand serves as a social display mechanism, and they support Self-Congruity Theory ( Sirgy, 1982 ). Furthermore, PS had a moderate impact on AT and a small impact on IFFC, but the high heterogeneity of this factor suggests that it affects both contexts. Cultural differences may explain these contrasting results; while scarcity increases appeal in some markets, it may also be a factor that causes resistance or skepticism in others. Given these results, it is possible that cultural norms, consumer skepticism, or brand trust moderate the effect of scarcity on purchase behavior. Although SN and PBC influence consumers’ intentions to participate in the fast fashion market to different degrees, the fact that both effects are supported further supports the TPB theory. Social pressure is also important yet, in the case of fast fashion, it is less influential than personal attitudes or perceptions of control, as evidenced by the smaller effect size associated with SN. On the other hand, PBC’s relative influence indicates that accessibility, affordability, and decision-making power are important considerations. The final part of the research model, behavioral intention to effect, is also supported. Significant effects of IFFC are observed on both brand loyalty and WoM, supporting the post-consumption phase of the ECL model. Particularly for digital consumers, who share their choices with a significant portion of WoM influence, WOM becomes a tool of notable spillover potential in influencing purchase behavior. In summary, the results support the important role of attitudes, perceived quality, and brand consistency in shaping fast fashion consumption, thereby reinforcing the TPB and related frameworks. However, the context-sensitive nature of the gap and the significant differences between studies highlight the need for market-specific approaches and additional empirical research. 5.1 Theoretical implications By integrating these theoretical models, this study provides important findings theorized in key areas: existential formulation, personal identity, perceived quality, and the extension of the TPB to post-consumption behaviors. First, this integration extends TPB theory by identifying external dimensions as antecedents to internal cognitive-affective states, particularly attitudes. Drawing on the S-O-R model ( Russell & Mehrabian, 1974 ), the analysis reveals that scarcity cues serve as theorized salient triggers that determine price evaluations and indirectly influence action intentions. This formulation is beyond the rational assumptions in the TPB that consumers are often experiential and emotionally arousing in high-speed consumer environments such as fast fashion. Second, self-congruity helps to expand the psychological scope of the TPB model. The association between consumers’ self-concept and brand image significantly predicts not only attitudes but also SN and PBC, reinforcing the centrality of symbolic consumption in identity construction ( Sirgy, 1982 ; Gollwitzer et al., 1982 ). Combining this theory with social identity theory ( Tajfel & Turner, 1981 ) suggests that when consumers perceive a brand as reflecting their intrinsic values, normative pressure - and the perceived ease of performing those behaviors - increases. Thus, self-congruity suggests that personal identity is an important determinant of consumer intention. Third, the findings challenge the traditional TPB construct by the cross-cutting influence of PQ ( Zeithaml, 1988 ) in the model. PQ significantly influences attitudes, SN, and PBC. This suggests that these factors are not limited to shaping outcome evaluations but also influence group identity or social status. PQ includes not only physical indicators such as durability and design but also ethical aspects such as sustainability, further complicating its evaluative role. Therefore, the results provide evidence in favor of a reconceptualization and multidimensionality of PQ, including cognitive, affective, and normative aspects. Finally, the study extends the boundaries of the TPB by linking intentions to post-consumption outcomes—specifically, loyalty to cues and WoM. While TPB theory and its extensions typically rest on intentions or behavioral actions, loyalty and WoM in this study argue that intentions act as an antecedent to effective engagement and long-term social performance. These findings need to be viewed as a pivotal point in a chain of actions rather than an end point. Overall, these contributions underscore the importance of integrating identity, emotion, environmental stimuli, and post-consumption motivation into action models. Future refinements of the TPB need to take into account the complexities of symbolism and context, especially in markets where consumption serves both objective and expressive purposes. 5.2 Practical implications This research provides a series of practical insights that can help brands more quickly and effectively craft their next strategy. At the heart of these recommendations is a complex set of consumer perceptions—scarcity, identity congruence, perceived quality, and sense of behavioral control—that together shape how consumers interact with brands, make purchase decisions, and share their experiences with others. First, perceived scarcity is a powerful marketing tool when used skillfully. Customers feel a sense of urgency and are motivated to make a purchase—a feeling similar to FOMO—when brands communicate scarcity by limiting the time of a promotion or the number or variety of products on shelves. However, this technique also has an impact on the brand if the customer does not feel the authenticity but feels psychologically manipulated, then the brand’s reputation will be affected. In markets where social factors have a strong impact, emphasizing the popularity of the product becomes a stimulus for purchase; conversely, in consumer markets where individuality or personal identity is promoted, being different or exclusive becomes an advantage to attract consumers. Second, an important and valuable concept is the concept of self-congruity - a brand’s image is consistent with how consumers see themselves or want to be seen. This connection can have a profound effect on attitudes and behavior, especially in the world of fashion, where clothing often serves as an expression of self-expression. Brands that reflect consumers’ personal values and identities – through intimate stories, influencer partnerships, or customization opportunities – are more likely to build lasting emotional relationships. Younger, more marginalized consumers like Generation Z, in particular, respond strongly to campaigns that reflect their evolving sense of self and digital maturity. However, a one-size-fits-all message is not enough; cultural and generational differences need to be considered when defining identity-driven content. Perceived quality also plays a key role in building consumer trust in all products and commodities, including fast fashion. This perception of quality goes beyond the fabric, fit, and stitching—it also includes how the product meets consumer expectations, such as how it makes the wearer feel, or even the social or environmental value associated with the brand. Quality signals can be both self-image-consistent and symbolic. Feedback from the community—in the form of reviews or endorsements from influencers—is important in enhancing perceptions of quality and trustworthiness, especially among highly socially connected consumers. It is a form of social validation that shapes purchase decisions in digitally-driven, community-driven marketplaces. Ultimately, when consumers feel confident in their ability to make choices, navigate through options, and return items if necessary, they are more likely to make repeat purchases. This is achieved by giving consumers a greater sense of control over the buying process. Streamlining the customer experience – through user-friendly shopping interfaces, product personalization, and clear purchase, warranty, or return policies – can reduce the psychological barriers to purchase. For example, through digital platforms, using AI, businesses can help customers enhance their shopping experience with virtual fitting rooms, data-driven advice based on analysis of past customer shopping habits. This in turn, increases customers’ sense of control over their behavior in a powerful way. Overall, the findings of this study demonstrate the value of integrating marketing approaches from making appeals to increase the perception of genuine scarcity, to building a brand based on identity, communicating a consistent quality message, and empowering consumers to make decisions. When tailored to each cultural context and customer segment, these strategies can help brands create unique consumer experiences, increase loyalty, and build effective brands. In a market with rapid, constant change and short consumption cycles, brands need to demonstrate flexibility and a continuous response strategy. Rapid adjustment to consumer behavior and cultural cues is key to maintaining competitive advantage and brand presence in the marketplace. 5.3 Limitations and future research directions Despite its positive findings, the study has certain limitations. Grasping these limitations is key for providing future researchers with a roadmap for further investigation and model enhancement. An obvious limitation is shown by the significant heterogeneity among many hypotheses, which suggests that the effect sizes are inconsistent. This limitation suggests the presence of unaccounted-for moderators such as culture, psychology, or context, which affect the generalizability and theoretical precision of the findings. In the future, researchers could use meta-analytic regression or subgroup analysis to identify and quantify such moderators. Second, although recognizing potential moderators (e.g., cultural orientation, materialism, generational identity), the current study did not systematically examine their moderating effects. Addressing this gap would enable deeper insights and support context-specific strategic recommendations. Although the meta-analysis includes data from different national contexts, it lacks explicit modeling of cultural variables (e.g., collectivism, power distance). Future research should integrate established cultural frameworks to further elucidate how culture shapes consumer responses and moderates key relationships. Finally, the model ignores ethical and sustainability constructs, which have received increasing attention in fast fashion. Despite some implications for environmentally conscious behavior, sustainability has not been systematically and explicitly integrated into the research model. Future research should incorporate sustainability-related attitudes and values to enhance relevance in ethically conscious markets and reflect changing consumer expectations. Informed consent statement This research is a meta-analysis and did not involve direct interaction or data collection from human participants. Informed consent was obtained in the primary studies included in this synthesis, as applicable to their research designs and data collection methods. 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Conserv. 2024; 292 : 110544. Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 14 Nov 2025 ADD YOUR COMMENT Comment Author details Author details 1 Department of Business Administration, Nanhua University, Dalin, Taiwan Province, 62249, Taiwan 2 Department of International Business Administration, Nanhua University, Dalin, Taiwan Province, 62249, Taiwan 3 International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, 751024, India Shu-Chuan Hsu Roles: Formal Analysis Ying-Kai Liao Roles: Methodology, Writing – Review & Editing Kuo-Chung Huang Roles: Writing – Review & Editing Lun-Chuan Lin Roles: Writing – Review & Editing Vo Thi Thinh Roles: Software, Writing – Review & Editing Wann-Yih Wu Roles: Supervision Khemraj Sharma Roles: Supervision, Writing – Original Draft Preparation Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (2) version 2 Revised Published: 10 Feb 2026, 14:1256 https://doi.org/10.12688/f1000research.170388.2 version 1 Published: 14 Nov 2025, 14:1256 https://doi.org/10.12688/f1000research.170388.1 Copyright © 2026 Hsu SC et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Hsu SC, Liao YK, Huang KC et al. Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.12688/f1000research.170388.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 10 Feb 2026 Revised Views 0 Cite How to cite this report: Rodríguez PG. Reviewer Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.194662.r457879 ) The direct URL for this report is: https://f1000research.com/articles/14-1256/v2#referee-response-457879 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Mar 2026 Pablo Gutiérrez Rodríguez , Universidad de Léon, León, Spain Approved VIEWS 0 https://doi.org/10.5256/f1000research.194662.r457879 The manuscript addresses a timely and relevant topic and presents an ambitious theoretical integration combining the Theory of Planned Behavior with key brand-related constructs in the fast fashion context. The rationale and objectives are clearly articulated, and the use of ... Continue reading READ ALL The manuscript addresses a timely and relevant topic and presents an ambitious theoretical integration combining the Theory of Planned Behavior with key brand-related constructs in the fast fashion context. The rationale and objectives are clearly articulated, and the use of a random-effects meta-analytic model is, in principle, appropriate given the diversity of cultural settings and empirical designs included in the analysis. However, in order for the manuscript to achieve full scientific robustness, several methodological and interpretative aspects should be strengthened. In particular, the methods section would benefit from greater transparency and detail regarding the search strategy, inclusion and exclusion criteria, study selection process, and the handling of potential dependencies among effect sizes. Although heterogeneity is acknowledged, a deeper exploration of its sources would enhance the credibility of the findings. Additionally, some conclusions adopt a tone that approaches causal interpretation, whereas the underlying evidence is primarily correlational; these implications should be framed more cautiously. Importantly, these observations do not undermine the viability of the manuscript but rather point to areas that are clearly addressable. With improved methodological transparency and a more carefully calibrated interpretation of the results, the manuscript has strong potential to become a rigorous and valuable contribution to the literature on consumer behavior in the fast fashion sector. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Partly Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Marketing I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Rodríguez PG. Reviewer Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.194662.r457879 ) The direct URL for this report is: https://f1000research.com/articles/14-1256/v2#referee-response-457879 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 17 Mar 2026 KHEMRAJ SHARMA , International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India 17 Mar 2026 Author Response We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. Competing Interests: No competing interests were disclosed. We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 17 Mar 2026 KHEMRAJ SHARMA , International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India 17 Mar 2026 Author Response We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. Competing Interests: No competing interests were disclosed. We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Anisah TN. Reviewer Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.194662.r456981 ) The direct URL for this report is: https://f1000research.com/articles/14-1256/v2#referee-response-456981 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 19 Feb 2026 Tiara Nur Anisah , Janabadra University, Yogyakarta, Indonesia Approved VIEWS 0 https://doi.org/10.5256/f1000research.194662.r456981 I have reviewed the revised manuscript (Version 2) and the authors' detailed responses. I appreciate the effort put into addressing the previous comments, particularly the inclusion of the Publication Bias Assessment and the availability of the PRISMA flow diagram ... Continue reading READ ALL I have reviewed the revised manuscript (Version 2) and the authors' detailed responses. I appreciate the effort put into addressing the previous comments, particularly the inclusion of the Publication Bias Assessment and the availability of the PRISMA flow diagram in the repository. These additions have significantly improved the transparency of the study. Regarding the issue of high heterogeneity (I2), I accept the authors' explanation and the decision to acknowledge this in the 'Limitations and Future Research' section. While a subgroup analysis would have been ideal, listing it as a limitation is an acceptable compromise for the current scope of this meta-analysis. One minor technical note for the final version: In the newly added Publication Bias section, you cited a Fail-Safe N of 88.60 for H12. Strictly speaking, with k=44 studies, this value falls slightly below the classic Rosenthal threshold (5k+10, which would be roughly 230). However, since your Egger’s regression test results are non-significant (p > 0.05), the overall conclusion that there is no serious publication bias remains valid. You might want to slightly temper the phrasing "consistently large" to something more moderate in the final proof to be statistically precise, though this does not affect my final decision. Competing Interests: No competing interests were disclosed. Reviewer Expertise: green & sustainability, marketing management, and digital marketing. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Anisah TN. Reviewer Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.194662.r456981 ) The direct URL for this report is: https://f1000research.com/articles/14-1256/v2#referee-response-456981 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 14 Nov 2025 Views 0 Cite How to cite this report: Anisah TN. Reviewer Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.187836.r433498 ) The direct URL for this report is: https://f1000research.com/articles/14-1256/v1#referee-response-433498 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 01 Dec 2025 Tiara Nur Anisah , Janabadra University, Yogyakarta, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.187836.r433498 PEER REVIEW REPORT Manuscript Title: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic Overall Evaluation: This meta-analytic study is a highly relevant and timely contribution to the consumer behavior literature, specifically in the fast ... Continue reading READ ALL PEER REVIEW REPORT Manuscript Title: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic Overall Evaluation: This meta-analytic study is a highly relevant and timely contribution to the consumer behavior literature, specifically in the fast fashion context. The methodology, a random-effects meta-analysis, is appropriate for synthesizing a heterogeneous body of literature and has provided statistically robust effect sizes for the proposed conceptual model. The integration of the Theory of Planned Behavior (TPB) with brand-related antecedents (Self-Congruity, Perceived Quality, and Perceived Scarcity) is a significant theoretical extension. The manuscript is well-structured, and the results clearly support the majority of the hypotheses. However, two critical areas—high statistical heterogeneity and data limitations—require substantial methodological and discussion enhancements before acceptance. Detailed Review and Questions 1. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes The rationale is clearly articulated by identifying significant gaps in the extant literature, including the siloed nature of single studies, the empirical fragmentation of TPB mediators, and the absence of a comprehensive synthesis. The three main objectives—to evaluate effects, examine mediating roles, and generate generalizable understanding—are also clearly presented. 2. Are sufficient details of the methods and analysis provided to allow replication by others? Partly The methodological foundation is sound, citing the random-effects model and adherence to Borenstein et al. (2010) and Wilson and Lipsey (2001) protocols. Details on the search strategy, including databases (Scopus, Web of Science, ScienceDirect, etc.), keyword groupings, and date range (2004–2024), are provided. CRITICISM: To ensure full replicability, the authors must provide the specific search strings used for each database and a formal reporting flow chart, such as a PRISMA diagram. Furthermore, details on the assessment or correction for publication bias (e.g., Egger's test, trim-and-fill procedure), which is a crucial component of robust meta-analysis, were mentioned as part of the protocol but not explicitly reported in the Results section. 3. Is the statistical analysis and its interpretation appropriate? Yes The statistical analysis is technically appropriate. But the authors must conduct and report a meta-regression or subgroup analysis (e.g., by culture, fast fashion brand type, or consumer demographic) to investigate the source of this heterogeneity. Without this step, the aggregated effect sizes ( r values) may mask significant underlying differences and limit the specificity of the theoretical and managerial conclusions. Additionally, the full model test is compromised by the inability to evaluate H2 and H3 due to a lack of data. 4. Are the conclusions drawn adequately supported by the results presented in the review? Yes The core conclusions are well-supported by the quantitative findings. For instance, the conclusion that Attitude is the most influential predictor of intention is directly supported by the largest effect size (r=0.605). Similarly, the robust influence of Self-Congruity (H5-H7, r ranging from 0.420 to 0.544) and the connection between intention and post-behavioral outcomes (H15 and H16, r=0.465 and r=0.560) are all clearly backed by the meta-analytic results. 5. If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? Not Applicable This is a standard systematic review/meta-analysis, not a Living Systematic Review. Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions): Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Yes Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests: No competing interests were disclosed. Reviewer Expertise: green & sustainability, marketing management, and digital marketing. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Anisah TN. Reviewer Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.187836.r433498 ) The direct URL for this report is: https://f1000research.com/articles/14-1256/v1#referee-response-433498 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 10 Feb 2026 KHEMRAJ SHARMA , International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India 10 Feb 2026 Author Response Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most ... Continue reading Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Response: Thank you for this important comment. We recognized that some I 2 is higher than 0.95 which indicate high heterogeneity in some hypotheses. Following McFadzean’s, et al.(1997) argument “..If this test shows homogeneous results then the differences between studies are assumed to be a consequence of sampling variation, and a fixed effects model is appropriate. If, however, the test shows that significant heterogeneity exists between study results then a random effects model is advocated...Although there is no statistical solution to this issue, heterogeneity between study results should not be seen as purely a problem for meta­analysis - it also provides an opportunity for examining why treatment effects differ in different circumstances…”We have used random effects analysis. Given that high heterogeneity may cause high variation. We have stated it in 5.4 Limitation and Future Research Directions : “Despite its positive findings, the study has certain limitations. Grasping these limitations is key for providing future researchers with a roadmap for further investigation and model enhancement. An obvious limitation is shown by the significant heterogeneity among many hypotheses, which suggests that the effect sizes are inconsistent. This limitation suggests the presence of unaccounted-for moderators such as culture, psychology, or context, which affect the generalizability and theoretical precision of the findings. In the future, researchers could use meta-analytic regression or subgroup analysis to identify and quantify such moderators. Second, although recognizing potential moderators (e.g., cultural orientation, materialism, generational identity), the current study did not systematically examine their moderating effects. Addressing this gap would enable deeper insights and support context-specific strategic recommendations. Although the meta-analysis includes data from different national contexts, it lacks explicit modeling of cultural variables (e.g., collectivism, power distance). Future research should integrate established cultural frameworks to further elucidate how culture shapes consumer responses and moderates key relationships”. 2. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Response : We appreciate the reviewer’s observation regarding the inability to test H2 (PS → SN) and H3 (PS → PBC) . The exclusion of these hypotheses is due to insufficient empirical evidence: only one primary study was available for each relationship. Previous researches, such as Valentine et al. (2010) and Zaccagnini et al. (2023), stated that researchers need a minimum of 2 similar studies to perform a meta-analysis, because at least two sources of data are required to compute an aggregated effect size; a single study cannot provide a pooled summary statistic. Although we are unable to do meta analysis for H2 and H3, we have developed theses two hypotheses based on theoretical underpinnings. These two hypotheses, together with other hypotheses will be empirically tested again by survey data afterwards. 3. Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Response: We thank the reviewer for emphasizing transparency and replicability. The PRISMA flow diagram and checklist , including detailed information on study identification, screening, eligibility, and inclusion, have been prepared and made publicly available as an independent supplementary report. The materials can be accessed via the following repository: https://figshare.com/articles/dataset/Fast_Fashion_Consumption/30219034?file=58298377 A reference to this repository has been added to the manuscript as an editor’s requirement to ensure full compliance with systematic review reporting standards. Based on editor’s comments, the Prisma flow diagram and checklist will be excluded from the manuscript but only shown as an independent supplementary report. 4. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Response: Thank you for this valuable suggestion. In response, we have revised Table 17 and added a formal publication bias assessment using Fail-Safe N (Rosenthal, 1979) and Egger’s regression test (Egger et al., 1997) to evaluate the robustness of the meta-analytic findings. Based on this table, the following paragraph is added to explain the result of publication bias. It was shown that publication bias is acceptable. Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Response: Thank you for this important comment. We recognized that some I 2 is higher than 0.95 which indicate high heterogeneity in some hypotheses. Following McFadzean’s, et al.(1997) argument “..If this test shows homogeneous results then the differences between studies are assumed to be a consequence of sampling variation, and a fixed effects model is appropriate. If, however, the test shows that significant heterogeneity exists between study results then a random effects model is advocated...Although there is no statistical solution to this issue, heterogeneity between study results should not be seen as purely a problem for meta­analysis - it also provides an opportunity for examining why treatment effects differ in different circumstances…”We have used random effects analysis. Given that high heterogeneity may cause high variation. We have stated it in 5.4 Limitation and Future Research Directions : “Despite its positive findings, the study has certain limitations. Grasping these limitations is key for providing future researchers with a roadmap for further investigation and model enhancement. An obvious limitation is shown by the significant heterogeneity among many hypotheses, which suggests that the effect sizes are inconsistent. This limitation suggests the presence of unaccounted-for moderators such as culture, psychology, or context, which affect the generalizability and theoretical precision of the findings. In the future, researchers could use meta-analytic regression or subgroup analysis to identify and quantify such moderators. Second, although recognizing potential moderators (e.g., cultural orientation, materialism, generational identity), the current study did not systematically examine their moderating effects. Addressing this gap would enable deeper insights and support context-specific strategic recommendations. Although the meta-analysis includes data from different national contexts, it lacks explicit modeling of cultural variables (e.g., collectivism, power distance). Future research should integrate established cultural frameworks to further elucidate how culture shapes consumer responses and moderates key relationships”. 2. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Response : We appreciate the reviewer’s observation regarding the inability to test H2 (PS → SN) and H3 (PS → PBC) . The exclusion of these hypotheses is due to insufficient empirical evidence: only one primary study was available for each relationship. Previous researches, such as Valentine et al. (2010) and Zaccagnini et al. (2023), stated that researchers need a minimum of 2 similar studies to perform a meta-analysis, because at least two sources of data are required to compute an aggregated effect size; a single study cannot provide a pooled summary statistic. Although we are unable to do meta analysis for H2 and H3, we have developed theses two hypotheses based on theoretical underpinnings. These two hypotheses, together with other hypotheses will be empirically tested again by survey data afterwards. 3. Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Response: We thank the reviewer for emphasizing transparency and replicability. The PRISMA flow diagram and checklist , including detailed information on study identification, screening, eligibility, and inclusion, have been prepared and made publicly available as an independent supplementary report. The materials can be accessed via the following repository: https://figshare.com/articles/dataset/Fast_Fashion_Consumption/30219034?file=58298377 A reference to this repository has been added to the manuscript as an editor’s requirement to ensure full compliance with systematic review reporting standards. Based on editor’s comments, the Prisma flow diagram and checklist will be excluded from the manuscript but only shown as an independent supplementary report. 4. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Response: Thank you for this valuable suggestion. In response, we have revised Table 17 and added a formal publication bias assessment using Fail-Safe N (Rosenthal, 1979) and Egger’s regression test (Egger et al., 1997) to evaluate the robustness of the meta-analytic findings. Based on this table, the following paragraph is added to explain the result of publication bias. It was shown that publication bias is acceptable. Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 10 Feb 2026 KHEMRAJ SHARMA , International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India 10 Feb 2026 Author Response Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most ... Continue reading Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Response: Thank you for this important comment. We recognized that some I 2 is higher than 0.95 which indicate high heterogeneity in some hypotheses. Following McFadzean’s, et al.(1997) argument “..If this test shows homogeneous results then the differences between studies are assumed to be a consequence of sampling variation, and a fixed effects model is appropriate. If, however, the test shows that significant heterogeneity exists between study results then a random effects model is advocated...Although there is no statistical solution to this issue, heterogeneity between study results should not be seen as purely a problem for meta­analysis - it also provides an opportunity for examining why treatment effects differ in different circumstances…”We have used random effects analysis. Given that high heterogeneity may cause high variation. We have stated it in 5.4 Limitation and Future Research Directions : “Despite its positive findings, the study has certain limitations. Grasping these limitations is key for providing future researchers with a roadmap for further investigation and model enhancement. An obvious limitation is shown by the significant heterogeneity among many hypotheses, which suggests that the effect sizes are inconsistent. This limitation suggests the presence of unaccounted-for moderators such as culture, psychology, or context, which affect the generalizability and theoretical precision of the findings. In the future, researchers could use meta-analytic regression or subgroup analysis to identify and quantify such moderators. Second, although recognizing potential moderators (e.g., cultural orientation, materialism, generational identity), the current study did not systematically examine their moderating effects. Addressing this gap would enable deeper insights and support context-specific strategic recommendations. Although the meta-analysis includes data from different national contexts, it lacks explicit modeling of cultural variables (e.g., collectivism, power distance). Future research should integrate established cultural frameworks to further elucidate how culture shapes consumer responses and moderates key relationships”. 2. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Response : We appreciate the reviewer’s observation regarding the inability to test H2 (PS → SN) and H3 (PS → PBC) . The exclusion of these hypotheses is due to insufficient empirical evidence: only one primary study was available for each relationship. Previous researches, such as Valentine et al. (2010) and Zaccagnini et al. (2023), stated that researchers need a minimum of 2 similar studies to perform a meta-analysis, because at least two sources of data are required to compute an aggregated effect size; a single study cannot provide a pooled summary statistic. Although we are unable to do meta analysis for H2 and H3, we have developed theses two hypotheses based on theoretical underpinnings. These two hypotheses, together with other hypotheses will be empirically tested again by survey data afterwards. 3. Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Response: We thank the reviewer for emphasizing transparency and replicability. The PRISMA flow diagram and checklist , including detailed information on study identification, screening, eligibility, and inclusion, have been prepared and made publicly available as an independent supplementary report. The materials can be accessed via the following repository: https://figshare.com/articles/dataset/Fast_Fashion_Consumption/30219034?file=58298377 A reference to this repository has been added to the manuscript as an editor’s requirement to ensure full compliance with systematic review reporting standards. Based on editor’s comments, the Prisma flow diagram and checklist will be excluded from the manuscript but only shown as an independent supplementary report. 4. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Response: Thank you for this valuable suggestion. In response, we have revised Table 17 and added a formal publication bias assessment using Fail-Safe N (Rosenthal, 1979) and Egger’s regression test (Egger et al., 1997) to evaluate the robustness of the meta-analytic findings. Based on this table, the following paragraph is added to explain the result of publication bias. It was shown that publication bias is acceptable. Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Response: Thank you for this important comment. We recognized that some I 2 is higher than 0.95 which indicate high heterogeneity in some hypotheses. Following McFadzean’s, et al.(1997) argument “..If this test shows homogeneous results then the differences between studies are assumed to be a consequence of sampling variation, and a fixed effects model is appropriate. If, however, the test shows that significant heterogeneity exists between study results then a random effects model is advocated...Although there is no statistical solution to this issue, heterogeneity between study results should not be seen as purely a problem for meta­analysis - it also provides an opportunity for examining why treatment effects differ in different circumstances…”We have used random effects analysis. Given that high heterogeneity may cause high variation. We have stated it in 5.4 Limitation and Future Research Directions : “Despite its positive findings, the study has certain limitations. Grasping these limitations is key for providing future researchers with a roadmap for further investigation and model enhancement. An obvious limitation is shown by the significant heterogeneity among many hypotheses, which suggests that the effect sizes are inconsistent. This limitation suggests the presence of unaccounted-for moderators such as culture, psychology, or context, which affect the generalizability and theoretical precision of the findings. In the future, researchers could use meta-analytic regression or subgroup analysis to identify and quantify such moderators. Second, although recognizing potential moderators (e.g., cultural orientation, materialism, generational identity), the current study did not systematically examine their moderating effects. Addressing this gap would enable deeper insights and support context-specific strategic recommendations. Although the meta-analysis includes data from different national contexts, it lacks explicit modeling of cultural variables (e.g., collectivism, power distance). Future research should integrate established cultural frameworks to further elucidate how culture shapes consumer responses and moderates key relationships”. 2. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Response : We appreciate the reviewer’s observation regarding the inability to test H2 (PS → SN) and H3 (PS → PBC) . The exclusion of these hypotheses is due to insufficient empirical evidence: only one primary study was available for each relationship. Previous researches, such as Valentine et al. (2010) and Zaccagnini et al. (2023), stated that researchers need a minimum of 2 similar studies to perform a meta-analysis, because at least two sources of data are required to compute an aggregated effect size; a single study cannot provide a pooled summary statistic. Although we are unable to do meta analysis for H2 and H3, we have developed theses two hypotheses based on theoretical underpinnings. These two hypotheses, together with other hypotheses will be empirically tested again by survey data afterwards. 3. Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Response: We thank the reviewer for emphasizing transparency and replicability. The PRISMA flow diagram and checklist , including detailed information on study identification, screening, eligibility, and inclusion, have been prepared and made publicly available as an independent supplementary report. The materials can be accessed via the following repository: https://figshare.com/articles/dataset/Fast_Fashion_Consumption/30219034?file=58298377 A reference to this repository has been added to the manuscript as an editor’s requirement to ensure full compliance with systematic review reporting standards. Based on editor’s comments, the Prisma flow diagram and checklist will be excluded from the manuscript but only shown as an independent supplementary report. 4. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Response: Thank you for this valuable suggestion. In response, we have revised Table 17 and added a formal publication bias assessment using Fail-Safe N (Rosenthal, 1979) and Egger’s regression test (Egger et al., 1997) to evaluate the robustness of the meta-analytic findings. Based on this table, the following paragraph is added to explain the result of publication bias. It was shown that publication bias is acceptable. Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 14 Nov 2025 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 2 (revision) 10 Feb 26 read read Version 1 14 Nov 25 read Tiara Nur Anisah , Janabadra University, Yogyakarta, Indonesia Pablo Gutiérrez Rodríguez , Universidad de Léon, León, Spain Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Rodríguez P. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Mar 2026 | for Version 2 Pablo Gutiérrez Rodríguez , Universidad de Léon, León, Spain 0 Views copyright © 2026 Rodríguez P. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The manuscript addresses a timely and relevant topic and presents an ambitious theoretical integration combining the Theory of Planned Behavior with key brand-related constructs in the fast fashion context. The rationale and objectives are clearly articulated, and the use of a random-effects meta-analytic model is, in principle, appropriate given the diversity of cultural settings and empirical designs included in the analysis. However, in order for the manuscript to achieve full scientific robustness, several methodological and interpretative aspects should be strengthened. In particular, the methods section would benefit from greater transparency and detail regarding the search strategy, inclusion and exclusion criteria, study selection process, and the handling of potential dependencies among effect sizes. Although heterogeneity is acknowledged, a deeper exploration of its sources would enhance the credibility of the findings. Additionally, some conclusions adopt a tone that approaches causal interpretation, whereas the underlying evidence is primarily correlational; these implications should be framed more cautiously. Importantly, these observations do not undermine the viability of the manuscript but rather point to areas that are clearly addressable. With improved methodological transparency and a more carefully calibrated interpretation of the results, the manuscript has strong potential to become a rigorous and valuable contribution to the literature on consumer behavior in the fast fashion sector. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Partly Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Marketing I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (1) Author Response 17 Mar 2026 KHEMRAJ SHARMA, International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India We sincerely thank you for your thoughtful and constructive evaluation of our manuscript. We greatly appreciate the time and expertise you devoted to reviewing our work. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Rodríguez PG. Peer Review Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.194662.r457879) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1256/v2#referee-response-457879 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Anisah T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 19 Feb 2026 | for Version 2 Tiara Nur Anisah , Janabadra University, Yogyakarta, Indonesia 0 Views copyright © 2026 Anisah T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions I have reviewed the revised manuscript (Version 2) and the authors' detailed responses. I appreciate the effort put into addressing the previous comments, particularly the inclusion of the Publication Bias Assessment and the availability of the PRISMA flow diagram in the repository. These additions have significantly improved the transparency of the study. Regarding the issue of high heterogeneity (I2), I accept the authors' explanation and the decision to acknowledge this in the 'Limitations and Future Research' section. While a subgroup analysis would have been ideal, listing it as a limitation is an acceptable compromise for the current scope of this meta-analysis. One minor technical note for the final version: In the newly added Publication Bias section, you cited a Fail-Safe N of 88.60 for H12. Strictly speaking, with k=44 studies, this value falls slightly below the classic Rosenthal threshold (5k+10, which would be roughly 230). However, since your Egger’s regression test results are non-significant (p > 0.05), the overall conclusion that there is no serious publication bias remains valid. You might want to slightly temper the phrasing "consistently large" to something more moderate in the final proof to be statistically precise, though this does not affect my final decision. Competing Interests No competing interests were disclosed. Reviewer Expertise green & sustainability, marketing management, and digital marketing. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Anisah TN. Peer Review Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.194662.r456981) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1256/v2#referee-response-456981 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Anisah T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 01 Dec 2025 | for Version 1 Tiara Nur Anisah , Janabadra University, Yogyakarta, Indonesia 0 Views copyright © 2025 Anisah T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions PEER REVIEW REPORT Manuscript Title: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic Overall Evaluation: This meta-analytic study is a highly relevant and timely contribution to the consumer behavior literature, specifically in the fast fashion context. The methodology, a random-effects meta-analysis, is appropriate for synthesizing a heterogeneous body of literature and has provided statistically robust effect sizes for the proposed conceptual model. The integration of the Theory of Planned Behavior (TPB) with brand-related antecedents (Self-Congruity, Perceived Quality, and Perceived Scarcity) is a significant theoretical extension. The manuscript is well-structured, and the results clearly support the majority of the hypotheses. However, two critical areas—high statistical heterogeneity and data limitations—require substantial methodological and discussion enhancements before acceptance. Detailed Review and Questions 1. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes The rationale is clearly articulated by identifying significant gaps in the extant literature, including the siloed nature of single studies, the empirical fragmentation of TPB mediators, and the absence of a comprehensive synthesis. The three main objectives—to evaluate effects, examine mediating roles, and generate generalizable understanding—are also clearly presented. 2. Are sufficient details of the methods and analysis provided to allow replication by others? Partly The methodological foundation is sound, citing the random-effects model and adherence to Borenstein et al. (2010) and Wilson and Lipsey (2001) protocols. Details on the search strategy, including databases (Scopus, Web of Science, ScienceDirect, etc.), keyword groupings, and date range (2004–2024), are provided. CRITICISM: To ensure full replicability, the authors must provide the specific search strings used for each database and a formal reporting flow chart, such as a PRISMA diagram. Furthermore, details on the assessment or correction for publication bias (e.g., Egger's test, trim-and-fill procedure), which is a crucial component of robust meta-analysis, were mentioned as part of the protocol but not explicitly reported in the Results section. 3. Is the statistical analysis and its interpretation appropriate? Yes The statistical analysis is technically appropriate. But the authors must conduct and report a meta-regression or subgroup analysis (e.g., by culture, fast fashion brand type, or consumer demographic) to investigate the source of this heterogeneity. Without this step, the aggregated effect sizes ( r values) may mask significant underlying differences and limit the specificity of the theoretical and managerial conclusions. Additionally, the full model test is compromised by the inability to evaluate H2 and H3 due to a lack of data. 4. Are the conclusions drawn adequately supported by the results presented in the review? Yes The core conclusions are well-supported by the quantitative findings. For instance, the conclusion that Attitude is the most influential predictor of intention is directly supported by the largest effect size (r=0.605). Similarly, the robust influence of Self-Congruity (H5-H7, r ranging from 0.420 to 0.544) and the connection between intention and post-behavioral outcomes (H15 and H16, r=0.465 and r=0.560) are all clearly backed by the meta-analytic results. 5. If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? Not Applicable This is a standard systematic review/meta-analysis, not a Living Systematic Review. Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions): Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Yes Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests No competing interests were disclosed. Reviewer Expertise green & sustainability, marketing management, and digital marketing. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 10 Feb 2026 KHEMRAJ SHARMA, International relations, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India Reviewer Comments’ Response Points that Must be Addressed to Make the Article Scientifically Sound (Critical Revisions) 1. Mandatory Meta-Regression/Subgroup Analysis: The reporting of extremely high heterogeneity (I² = 95%) across most critical paths is a severe limitation on the generalizability of the pooled effect sizes. The authors must perform and report a meta-regression or subgroup analysis (e.g., utilizing 'Method/Country' or 'Studied Year' as a moderator from the source tables) to identify the specific variables causing this high variation. Without this, the overall effect sizes are minimally informative. Response: Thank you for this important comment. We recognized that some I 2 is higher than 0.95 which indicate high heterogeneity in some hypotheses. Following McFadzean’s, et al.(1997) argument “..If this test shows homogeneous results then the differences between studies are assumed to be a consequence of sampling variation, and a fixed effects model is appropriate. If, however, the test shows that significant heterogeneity exists between study results then a random effects model is advocated...Although there is no statistical solution to this issue, heterogeneity between study results should not be seen as purely a problem for meta­analysis - it also provides an opportunity for examining why treatment effects differ in different circumstances…”We have used random effects analysis. Given that high heterogeneity may cause high variation. We have stated it in 5.4 Limitation and Future Research Directions : “Despite its positive findings, the study has certain limitations. Grasping these limitations is key for providing future researchers with a roadmap for further investigation and model enhancement. An obvious limitation is shown by the significant heterogeneity among many hypotheses, which suggests that the effect sizes are inconsistent. This limitation suggests the presence of unaccounted-for moderators such as culture, psychology, or context, which affect the generalizability and theoretical precision of the findings. In the future, researchers could use meta-analytic regression or subgroup analysis to identify and quantify such moderators. Second, although recognizing potential moderators (e.g., cultural orientation, materialism, generational identity), the current study did not systematically examine their moderating effects. Addressing this gap would enable deeper insights and support context-specific strategic recommendations. Although the meta-analysis includes data from different national contexts, it lacks explicit modeling of cultural variables (e.g., collectivism, power distance). Future research should integrate established cultural frameworks to further elucidate how culture shapes consumer responses and moderates key relationships”. 2. Addressing Data Gaps and Full Model Test: The authors should explicitly discuss the inability to test H2 (PS on SN) and H3 (PS on PBC). They must offer a theoretical justification for this 'blind spot' to guide future primary research (e.g., how the digital nature of fast fashion and 'fear of missing out' would theoretically mediate the social/control aspects). Response : We appreciate the reviewer’s observation regarding the inability to test H2 (PS → SN) and H3 (PS → PBC) . The exclusion of these hypotheses is due to insufficient empirical evidence: only one primary study was available for each relationship. Previous researches, such as Valentine et al. (2010) and Zaccagnini et al. (2023), stated that researchers need a minimum of 2 similar studies to perform a meta-analysis, because at least two sources of data are required to compute an aggregated effect size; a single study cannot provide a pooled summary statistic. Although we are unable to do meta analysis for H2 and H3, we have developed theses two hypotheses based on theoretical underpinnings. These two hypotheses, together with other hypotheses will be empirically tested again by survey data afterwards. 3. Enhancing Replicability: The manuscript requires the inclusion of the full search strings used across the databases and a PRISMA flow chart detailing the study selection process (identification, screening, eligibility, inclusion) to meet rigorous reporting standards for systematic reviews. Response: We thank the reviewer for emphasizing transparency and replicability. The PRISMA flow diagram and checklist , including detailed information on study identification, screening, eligibility, and inclusion, have been prepared and made publicly available as an independent supplementary report. The materials can be accessed via the following repository: https://figshare.com/articles/dataset/Fast_Fashion_Consumption/30219034?file=58298377 A reference to this repository has been added to the manuscript as an editor’s requirement to ensure full compliance with systematic review reporting standards. Based on editor’s comments, the Prisma flow diagram and checklist will be excluded from the manuscript but only shown as an independent supplementary report. 4. Reporting Publication Bias: The authors must report the results of publication bias analysis (e.g., fail-safe N, Egger's test, or Trim-and-Fill) for the major relationships to confirm the robustness of the findings. Response: Thank you for this valuable suggestion. In response, we have revised Table 17 and added a formal publication bias assessment using Fail-Safe N (Rosenthal, 1979) and Egger’s regression test (Egger et al., 1997) to evaluate the robustness of the meta-analytic findings. Based on this table, the following paragraph is added to explain the result of publication bias. It was shown that publication bias is acceptable. Publication Bias Assessment To evaluate the potential influence of publication bias on meta-analytic findings, researchers often use the Fail-safe N approach, originally proposed by Rosenthal (1979), and Egger’s regression test, introduced by Egger et al. (1997). These methods address the file-drawer problem—where null results remain unpublished—and small-study effects, respectively, by assessing effect robustness and funnel plot asymmetry. The Fail-Safe N values are consistently large and statistically significant across all supported hypotheses, indicating that a substantial number of unpublished null studies would be required to render the observed effects non-significant, for example Fail-Safe N of H12=88.60; H14=42.85; H5=33.53. In addition, Egger’s regression intercepts are non-significant for all relationships (all p-values > 0.05), including those based on a large number of effect sizes, examples H12’s intercept value= −0.06, p=0.99; H13’a intercept=0.18, p=0.95, suggesting no evidence of small-study effects or funnel plot asymmetry. Although substantial heterogeneity is present, the convergent results from these results indicate that publication bias is unlikely to materially affect the meta-analytic conclusions. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Anisah TN. Peer Review Report For: Psychological Drivers and Behavioral Outcomes of Fast Fashion Consumption: A Meta-Analytic [version 2; peer review: 2 approved] . F1000Research 2026, 14 :1256 ( https://doi.org/10.5256/f1000research.187836.r433498) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1256/v1#referee-response-433498 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. 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