- 1Department of Psychology, Manipal University Jaipur, Jaipur, India
- 2Department of Physical Education, Sports and Yoga, Manipal University Jaipur, Jaipur, India
- 3Amity Institute of Behavioural & Allied Sciences, Amity University Rajasthan, Jaipur, India
Fashion production, largely driven by the demand for fashion, is a major contributor to environmental degradation. With the rising awareness of the consequences of fashion consumption, consuming second-hand fashion is a fast-emerging strategy. The current study utilises Theory of Planned Behavior (TPB) framework to investigate the intentions to purchase second-hand clothes in young Indian consumers. TPB is extended by adding mindful consumption and environmental concern as predictors of attitude towards second-hand clothes. 222 Indian young adults (18–30 years) participated in the research and data were analysed using Structural Equation Modelling (SEM). Environmental concern emerged as the most significant predictor of a positive attitude towards second-hand clothing, followed by mindful consumption. Attitude, in turn, had the strongest influence on purchase intention, while subjective norms and perceived behavioral control also showed significant positive effects. The tested model was significant and explained 46.5% variance in purchase intentions. This research contributes to sustainability literature by validating the extended TPB model in the context of second-hand fashion in India.
1 Introduction
The global fashion industry, particularly the fast fashion sector, has emerged as a significant contributor to environmental degradation, producing approximately 92 million tonnes of textile waste annually-a figure projected to reach 134 million tonnes by 2030 if current practices continue (Tang, 2023). Fashion production, largely driven by the demand for fashion, is responsible for an estimated 2–8% of global carbon emissions and is the second-largest consumer of water, utilizing about 215 trillion litres each year (The UN Alliance for Sustainable Fashion, 2025). The global proliferation of fast fashion has normalized the use of inexpensive, short-lived clothing, thereby accelerating the consumption of resources and intensifying ecological damage. Additionally, approximately 85% of all textiles produced annually are discarded in landfills, and the laundering of synthetic garments contributes significantly to marine microplastic pollution [United Nations Economic Commission for Europe (UNECE), 2018].
As environmental consequences become more visible, consumer awareness of sustainability in fashion has grown (Lee et al., 2015). There is a noticeable shift in consumer attitudes, as more people have started considering the long-term environmental consequences of their fashion choices, and there is an increase in the adoption of sustainable fashion (Wang et al., 2015). The growing consciousness about environmental degradation has given way to practices that demand systemic modifications in the ways individuals consume fashion (Bhardwaj and Fairhurst, 2010). Among the various alternatives, second-hand clothing represents a core element of the sustainable fashion movement, which emphasizes durability, reuse, and a reduced environmental burden (Chen and Deng, 2016).
Consuming second-hand fashion aligns with the broader objectives of ecological sustainability by extending the lifecycle of garments and reducing demand for new, resource-intensive production. Purchasing second-hand clothing reduces the volume of textile waste sent to landfills and curtails the demand for new clothing production, thereby conserving water, energy, and raw materials (Xie et al., 2021). Research indicates that buying second-hand clothes can reduce carbon emissions by an average of 25% compared to purchasing new items. Despite increasing concern for sustainability among consumers, actual adoption rates of second-hand fashion remain relatively low (Connell, 2010). This gap between environmental concern and behavioral adoption highlights the need for further research into the psychological, social, and contextual factors influencing consumers’ engagement with second-hand fashion.
A recent report by Down to Earth (2024) revealed that India generates approximately 7,900 kilotons of textile waste annually-accounting for 8.5% of global textile waste-much of which is disposed of in landfills or downcycled rather than recycled into new garments. A huge contributor to this textile waste is the country’s fast fashion market, valued at approximately $10 billion in 2024, and expected to grow 5X to reach $50 billion by FY31. Within the Indian context, promoting second-hand fashion and circular fashion practices can play a pivotal role in addressing the mounting textile waste crisis, fostering sustainable consumption patterns, and supporting the transition toward a more regenerative and less wasteful fashion ecosystem (Down to Earth, 2024).
Although India has a rich history of pre-owned clothing consumption within families that is deeply rooted in the cultural fabric of the society and creates an environment in favour of consuming second-hand clothes, there is a social stigma around wearing pre-owned clothes, associating them with economic necessity rather than sustainability. Despite being one of the largest importer of second-hand clothing items, the Indian market of second-hand clothes is not formalized due to many concerns like hygiene, quality and wearability. Indian consumers still hesitate to adopt second-hand clothing, pointing to a gap between what they know and how they act (Bhardwaj and Fairhurst, 2010; Hristova, 2019). There is a noticeable lack of studies that explore the psychological and emotional processes behind second-hand clothing decisions in India. Therefore, the current study aims to examine the factors responsible for intentions to purchase second-hand clothes.
1.1 Theoretical framework
1.1.1 Theory of planned behavior
The consumer decision-making is a complex process, and multiple theories in the existing literature attempt to explain such behavior (Koay et al., 2024). One such theory is the Theory of Planned Behavior (TPB) proposed by Ajzen (1985). TPB is the most widely used social-cognition theory to explain volitional behavior (Armitage and Conner, 2001). Based on the assumption that humans are rational, purposeful actors, TPB suggests that intention has the most proximal and direct influence on behavior and therefore, a strong intention to achieve a particular goal should lead to its attainment even if this requires changing current behaviors (Ajzen, 1991). As a rule, the stronger the intention to engage in a behavior, the more likely it is to be performed (Fishbein and Ajzen, 2010). TPB identifies three important determinants of intention: attitude, subjective norm and perceived behavioral control (PBC) (Ajzen, 1991).
Attitude refers to the expectations and overall positive and negative evaluation of performing a particular behavior. These attitudes are fundamentally rooted in behavioral beliefs about the consequences of the behavior and evaluations of those consequences. Attitudes refer to an individual’s positive or negative evaluation of performing a particular behavior (Ajzen, 1991). Attitudes influence intentions and consequently behavior (Ajzen, 1985; Zhao et al., 2013). In the context of sustainability, an environmental attitude can be understood as a cognitive and affective representation of the evaluation process toward an object of environmental protection and sustainability (Bamberg, 2003). Studies reveal that there is a higher possibility that people with strong positive attitudes towards sustainability will involve in ecologically accountable behaviors like responsible consumption, recycling, waste management, choosing sustainable/eco brands, local or seasonal food products, paying higher prices, and recommending these products (Coelho et al., 2017; Dascher et al., 2014; Lee et al., 2015; Miniero et al., 2014; Oliver, 1999; Uncles et al., 2003; Verain et al., 2021; Woo and Kim, 2019).
Subjective norms capture the social dimension of decision-making and refers to the perceived social pressure from significant others to perform or refrain from a particular behavior. Social norms are perceived expectations or behaviors within a social group that influence individual decision-making (Ajzen, 1991). They are the shared expectations and rules shaping the individual decisions of acceptable or typical behavior in a given context (Cialdini et al., 1990). When others have strong expectations and beliefs about a user’s behavior, the user will behave in a certain way according to the expectations and beliefs of others (Wang et al., 2015). There is ample evidence in the existing literature to confirm that social norms positively affect consumers’ attitude towards a variety of behaviors like online clothing shopping (Srinivasan, 2015) and online shopping intentions (Theodorou et al., 2023). Peer approval and societal acceptance is likely to play an important role in the context of second-hand fashion also. Observing important people endorsing thrift culture might be a great source of motivation to adopt it (Boyer et al., 2024; Yang et al., 2024).
In the Indian context, although generational clothing transfer is well accepted (Moitra et al., 2025), public consumption of used apparel is often met with hesitation due to perceived lower status. However, this perception is gradually changing among Indian youth, who are increasingly influenced by global trends and peer behavior. These findings suggest that in India’s evolving consumer landscape, particularly among urban youth, peer approval and shifting norms may serve as powerful stimuli in encouraging second-hand purchases.
Kapoor and Khare (2019) confirmed that social influence positively affects sustainable apparel consumption. Due to existing conflict in perceptions about second hand clothing and considering that young adults in India are concerned about the environmental impact of fast fashion, social norms is a potentially important factor in this context. Therefore, we defined social norms as the extent to which significant others believe that young adults should use second hand clothing items (Fishbein and Ajzen, 1975). Based on the existing literature, it is assumed as follows.
PBC refers to the extent of personal volitional control perceived by an individual in performing a particular behavior. The variable was included to the TPB model developed from the theory of deductive action to improve the prediction of consumer behavior in the context of self-efficacy (Ajzen, 1991). Individual’s perception of control over the behavior has been positively associated with the intention to carry out the target behavior (Ajzen, 2011). Perceived behavior control in the current study is conceptualised as the extent to which consumers perceived sense of control over their behavior of purchasing second-hand fashion.
TPB has been widely used to understand and explain a variety of voluntary behaviors (e.g., Ajzen, 2011; Conner and Armitage, 1998; Cook et al., 2002), e.g., to buy green products (Chen and Deng, 2016), to use public transport (Chiou et al., 2010), to avoid food waste (Mak et al., 2018) and to examine consumer behavior towards sustainable plastic clothing and luxury (Kumagai, 2020), recycling behaviors and sustainable fashion choices (Fauzi et al., 2025; Jahari et al., 2022). TPB has been successfully applied to understand the complex decision-making behavior and hence it was found appropriate to be used in the current study.
In line with the existing literature on TPB, this study posits that attitude, existing social norms and the individual’s confidence in their ability to purchase used clothing items will result in positive intentions to purchase second-hand clothes. As a result, the following hypotheses were formulated:
H1: Positive attitude has a positive influence on the intention to purchase second-hand clothing items.
H2: Subjective norms favouring second-hand clothing items have a positive influence on the intention to purchase second-hand clothing items.
H3: Perceived behavioral control has a positive influence on the intention to purchase second-hand clothing items.
1.1.2 Extending theory of planned behavior
Ajzen (2005) pointed out that addition of more variables can enhance the explanatory power of TPB. Therefore, many researchers have extended the original TPB model by adding relevant variables (Hassan et al., 2015; Yadav and Pathak, 2016; Savari and Khaleghi, 2023) and these extensions have helped to enhance the theory’s explanatory power while maintaining its fundamental theoretical coherence. TPB has been integrated with personal variables like habits, personality, self-identity and values (Obschonka et al., 2014; Gkargkavouzi et al., 2019; Smith et al., 2007) to increase its predictive power in various domains.
Considering the use of TPB in studying environmentally conscious behaviors, scholars have extended the TPB by integrating factors that impact environmental behavior (Chen and Tung, 2013; Jaiswal and Kant, 2017). Since attitude is a key determinant of purchase intentions for circular products (Paul et al., 2016) and second-hand items (Stolz, 2022) the current study aims to contribute by investigating the factors which shape the attitude towards consumption of second-hand fashion. For the current research, TPB has been extended by adding mindful consumption and environmental concern as predictors of attitude.
Mindful consumption refers to the extent to which individuals consciously reflect on the environmental and social consequences of their buying decisions (Sheth et al., 2010). The construct rooted in the theory of mindful-consumption (Sheth et al., 2010), which is an important theoretical framework explaining consumer behavior and emphasizes the role of mindfulness in consumption decisions. According to Dhandra (2019), consumption has two facets- tangible and intangible. Tangible consumption refers to the behavioral patterns of consumption, whereas intangible consumption refers to the expectations, values and attitudes that affect consumption (Balderjahn et al., 2013). Hence, mindful consumption is also a mindset that has the potential to shape attitude towards consuming second-hand fashion. The inclusion of mindful consumption as a predictor of attitude is particularly relevant in the current study as consumption of second-hand fashion manifests as a deliberate, value-driven behavior rooted in ecological responsibility and ethical awareness. Mindful consumers are more likely to engage in purchasing second-hand clothing (Pivato et al., 2007; Balderjahn et al., 2013) as they have a positive attitude towards waste reduction and sustainable lifestyle choices, but contradictory evidence also exists which does not support the link between mindful consumption and attitude towards sustainability behaviors (Mohammad et al., 2020) creating room for further confirmatory evidence.
In the Indian context also, mindful consumption is emerging as a significant behavioral trait among environmentally aware youth. Young consumers with higher mindful consumption patterns are more likely to align their values with sustainable purchasing (Djafarova and Foots, 2022). Given that mindfulness in consumption reflects internalized concern and attention to sustainability, and mindful consumers are more likely to make deliberate and sustainable choices, such as buying second-hand clothes, the following hypothesis was formulated:
H4: Mindful consumption will positively influence the attitude towards consuming second-hand clothing items.
Environmental concern is the awareness, attitudes, and behaviors individuals exhibit regarding environmental issues, reflecting their level of care and willingness to engage in actions that promote environmental sustainability (Dunlap and Jones, 2002). It encompasses personal responsibility, perceived threat of ecological degradation, and commitment to sustainable practices (Bamberg and Möser, 2007). Individuals with high environmental concern are more inclined toward sustainable consumption, including second-hand shopping (Wang et al., 2015).
Recent investigation in the field of circular fashion confirm that environmental concern acts as an affective and cognitive factor that deepens the internal processing of external sustainability-related stimuli, thereby shaping the attitude towards consuming second-hand clothing (Yang et al., 2024). Research also confirms that beliefs about the environment have a strong formative role in shaping the attitude and setting intentions for sustainable behaviors (Zhou et al., 2025).
Thus, the following hypothesis was formulated:
H5: Environmental concern will positively influence the attitude towards consuming second hand clothing items.
Mindful consumption and environmental concern were integrated into the existing TPB model as factors influencing attitude (Supplementary Figure 1). The inclusion of mindful consumption and environmental concern as predictors of attitude toward second-hand clothing in an extended TPB framework will help to address critical gaps in the traditional TPB model when applied to sustainable fashion consumption, capturing nuanced psychological processes that directly shape consumer evaluations of second-hand fashion.
2 Materials and methods
The current study is based on positivism approach and quantitative methods are used to test the proposed hypotheses and validate causal explanatory paths.
2.1 Measurement scale
Based on the recommendations by Ajzen and Fishbein (1980), items to measure TPB constructs were adapted from the existing literature to suit the purpose of current research (Ajzen, 1988). Items for mindful consumption and environmental concern were also adapted from the existing relevant literature (Djafarova and Foots, 2022; McNeill and Moore, 2015). Two subject experts reviewed and provided feedback on the adapted items and items were modified as per the feedback. All items were answered on 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree).
2.2 Sample recruitment and data collection procedures
Current study has used SEM to test the proposed model. There is no consensus in the existing literature regarding an adequate sample size in SEM. According to some researchers SEM models can be tested with a sample size of 100–150 (Gerbing and Anderson, 1988; Tabachnick and Fidell, 2001) whereas some others consider that 200 is an adequate sample size for SEM (Kline, 2005). Another widely accepted rule of thumb is 10 times of the total number of items used to measure the constructs (Nunnally, 1967). The current study utilizes 6 constructs measured by a total of 20 items. According to recommendations of Kline (2005) the required sample size was 210 participants for the current research.
The target population of the current research were individuals in the age range of 18–30 years and having a basic understanding of the English language, as all the questions were framed in English. The young adults were chosen as the sample population because they are more open to adopting new trends and show more adaptability to change in general (Kim et al., 2021). Also, as many individuals are students or early in their career, they are more likely to opt for more affordable options such as thrifting (Mundel et al., 2021; Shim et al., 2001). Studies also show that young adults have higher environmental awareness; therefore, they prioritize eco-friendly practices (Hill and Lee, 2012). To ensure an adequate sample, the final questionnaire was personally distributed to 400 participants using a purposive and snowball sampling approach. Both the sampling approaches were most suitable as they help to select the respondents who are suitable to fulfil the objectives of the current study (Sharma et al., 2020). Subjects recruited through purposive sampling were then requested to provide links to more respondents. Before participating, the respondents read the cover letter, which informed them about the purpose of the research and provided consent to participate. Participation was voluntary and anonymous. Before the participants answered the questions, they were briefed about the construct of second-hand clothing items. A total of 296 (out of distributed 400) filled questionnaires were received between July and September 2024 by the researchers.
2.3 Data analysis techniques
SEM was utilized to analyze data. SEM is particularly useful for testing hypothesized models as it enables to investigate interrelationships among latent variables (Bentler, 1983). AMOS (version 24) was used to conduct SEM. Measurement model analysis was done to establish the reliability and validity of the constructs. Adequacy of the specified measurement model (Supplementary Figure 2) was confirmed through the recommended criteria of factor loadings>0.5, Cronbach’s alpha >0.7, Composite Reliability (CR) > 0.7 and Average Variance Extracted (AVE) of the constructs >0.5 (Hair et al., 2019). Structural model analysis was used to evaluate the relationship among latent constructs and to test the proposed hypotheses. The adequacy of the specified structural model (Supplementary Figure 1) was evaluated on the basis of path coefficient values (Kline, 2011). Goodness of fit for the measurement and structural models was established using overall fit indices. The indices used were chi-square, GFI (Goodness of fit index), CFI (comparative fit index), TLI (Tucker-Lewis index) and RMSEA (Root-mean square error of approximation) (Hair et al., 2010).
2.4 Ethical statement
This research adheres to the principles of ethical conduct in research involving human subjects as outlined in the Declaration of Helsinki. All participants provided informed consent before participating in the study, and their anonymity and confidentiality were ensured throughout the research process.
3 Results
3.1 Preliminary analysis
400 questionnaires were distributed and 296 filled questionnaires were received by the researchers indicating a response rate of 74%. After eliminating 36 responses due to invalid or missing data, the remaining 260 responses were further screened to check whether the respondents were alert while answering. The questionnaire had an item which read “This item checks whether you are reading the items carefully before answering. Please choose ‘do not agree’ as your answer to this question.” 38 responses could not fulfil the criteria of attentiveness and failed to answer this item as instructed and were excluded from the sample. The demographic details of 222 participants are presented in Table 1.
The final sample (N = 222) comprised 41.44% males and 58.56% males. The sample was dominated by students, with 60.36% of the participants enrolled in some academic program. Descriptive statistics were calculated for the constructs. Mean, standard deviation and correlation between the constructs have been presented in Table 2.
3.2 Common method bias
Common method bias is a common source of error in survey research. To reduce this, participants were encouraged to provide honest responses and hence reduce social desirability. Additionally, Harman’s single-factor test was assessed to be 47.63%, which is less than the acceptable criterion of 50% (Podsakoff et al., 2003), indicating absence of common method bias.
3.3 Measurement model testing
The results of the measurement model are presented in Table 3. Factor loadings of all the items were greater than 0.6. Cronbach’s alpha of all the constructs exceeded the acceptable value of 0.7 (Hair et al., 2010), indicating internal consistency. To examine convergent validity, composite reliability (CR) and Average Variance Extracted (AVE) values were used. All CR values were greater than 0.7, and all AVE values were greater than 0.5, confirming the robustness of the measurement model. Discriminant validity was assessed following the recommendations of Fornell and Larcker (1981). Results in Table 3 show that the square root of AVE for all the variables exceeded the correlation coefficient among the variables indicating good discriminant validity.
AMOS (version 24) was used to assess the goodness of fit of the measurement model. The overall chi-square value was significant (χ2 = 145.385; df = 120; CMIN/df = 1.212 p < 0.000). The model achieved a good fit as the values of CFI, GFI, and TLI were above the recommended value of 0.9 (Hair et al., 2010; Gerbing and Anderson, 1988). RMSEA was obtained as 0.031, which is less than the recommended 0.07 and hence suggests a good model fit (Steiger, 2006). Table 4 shows the model fit indices of the measurement model.
3.4 Structural model and hypotheses testing
After establishing the reliability and validity of the scales and appropriateness of the measurement model, SEM was used to assess the proposed model (Supplementary Figure 1) to predict the intentions to purchase secondhand clothes. The final model included 5 paths to test the causal relationship between the 6 constructs of the model. The fit indices of the structural model were within the acceptable limits (Hu and Bentler, 1999), as shown in Table 5. The overall chi-square value was significant (χ2 = 341.416; df = 131; CMIN/df = 2.606 p < 0.000). All the indices suggest a good fit of the structural model to the data. RMSEA was obtained as 0.065, which is less than the recommended 0.7 and hence suggests a good model fit (Steiger, 2006).
3.5 Hypothesis testing
SEM was also used to test hypotheses. The indices used were path coefficient (β) values, critical ratio (CR) and p values. Results are shown in Table 5. The analysis revealed that attitude towards purchasing secondhand clothes is significantly influenced by environmental concern (β = 0.772, p < 0.001) and mindful consumption (β = 0.264, p < 0.01) indicating that individuals who were concerned for the environment and are mindful in consuming clothes are more likely to have a positive attitude towards purchasing second hand clothes. Results also confirmed a significant impact of attitude towards purchasing second hand clothes (β = 0.960, p < 0.001), subjective norms (β = 0.111, p < 0.01) and perceived behavioral control (β = 0.258, p < 0.001), confirming the role of TPB constructs in determining the intentions to purchase second hand clothes. The results supported H1-H5.
4 Discussion
The present study aimed to examine an extended TPB model to investigate the intentions to purchase second-hand clothing among Indian young adults. The findings provide valuable insights into drivers of intentions to purchase second-hand clothes in the Indian context. Results confirm the significant positive impact of the core TPB constructs (attitude, subjective norms, and perceived behavioral control) on purchase intentions indicating that behavioral intentions are shaped by individual evaluations, social influences, and perceived control over the behavior.
Attitude towards second-hand clothing emerged as the strongest predictor of purchase intentions (β = 0.960, p < 0.001). Individuals are more likely to have positive intentions towards second-hand clothes if they evaluate it positively. Obtained results are in line with existing findings that individual attitudes remain the primary driver of behavior (Taylor et al., 2023). Perceived behavioral control also had a significant positive impact on purchase intentions (β = 0.258, p < 0.001), highlighting the importance of structural factors such as the availability of second-hand clothing outlets, online platforms, and convenient shopping experiences are important in facilitating sustainable consumption behaviors. Results obtained are in line with the existing body of research (Kim et al., 2021; Beneke and Zimmerman, 2014; Vehmas et al., 2018), which shows that individuals intend to engage in a behavior if they perceive themselves to be in control of that behavior. The third TPB construct- subjective norms also has a significant positive effect on purchase intentions (β = 0.111, p < 0.01). The positive relationship is suggestive of the fact that social perceptions, particularly among urban youth, may go a long way in facilitating greater acceptance of second-hand clothing consumption (Chaudhary and Dey, 2016). It is also interesting to note that the relative contribution of social norms is modest in comparison to attitude and perceived behavioral control, suggesting that while peer approval and social acceptance influence purchase intentions, subjective evaluation and structural factors are more important in shaping the purchase intentions.
To summarize the findings on TPB constructs it may be inferred that positive evaluation of the behavior of buying second-hand clothes and the perceived ease in buying second-hand clothes play a more decisive role as compared to perceived social acceptability of such behavior. This finding has important implications for various stakeholders like retailers, policy makers, etc. as it is indicated that purchase of second-hand clothes can be increased if individuals have positive perceptions of structural factors like availability, variety and cost effectiveness. Results obtained also support the theoretical robustness of TPB constructs in understanding consumer decision-making processes pertaining to environmental behaviors (Hoang et al., 2022; Wicaksono et al., 2024). Findings of the current study are aligned with established literature using the TPB framework to predict second-hand fashion consumption (Tang Fat Sang and Peng, 2025; Nazarie et al., 2025; Koay et al., 2024).
The study extended the TPB model with environmental concern and mindful consumption as predictors of attitude. The most notable finding was the exceptionally strong influence of environmental concern on attitude toward second-hand clothing (β = 0.772, p < 0.001). Similar findings have been reported in the existing literature (Leclercq-Machado et al., 2022; Okur et al., 2023).
Environmental concern can be linked to intentions to purchase second-hand clothes through multiple pathways. Firstly, environmental concern is linked to higher levels of awareness about the harmful impacts of consumption (Koay et al., 2024) including fashion (Horvat and Vendramin, 2021) and consuming second-hand fashion might be seen as a mitigation strategy (Yan et al., 2021). Secondly, it is highly likely that environmentally concerned individuals are have a strong environmental identity (Lou and Li, 2021) which predisposes them to indulge in more environmentally friendly behaviors which includes purchasing second-hand clothes. This finding is particularly significant in the Indian context, where environmental consciousness among youth is reportedly growing due to increased climate discourse, education, and social media exposure (Liu, 2022). Consequently, sustainability messaging may be particularly effective in promoting second-hand clothing consumption among this demographic.
Mindful consumption had a moderate but significant positive influence on attitude toward second-hand clothing (β = 0.264, p < 0.01). This finding is particularly important as the existing literature reports mixed results regarding the relationship between mindfulness and sustainable fashion consumption (Riesgo et al., 2022). The positive association indicates that individuals who consciously reflect upon the environmental and social consequences of their consumption decisions are more likely to develop more favourable attitudes toward second-hand clothing (Garnelo-Gomez et al., 2025). The moderate size of the influence indicates that while mindfulness plays a role in shaping attitudes, it may work in conjunction with other factors such as environmental concern to influence sustainable consumption behavior.
The study’s integration of mindful consumption and environmental concern as predictors of attitude within the TPB framework addresses critical gaps in traditional models when applied to sustainable fashion consumption (Garg et al., 2024; Koay et al., 2024). Based on the results obtained it can be said that extended TPB model significantly explains second-hand clothing purchase intentions among Indian youth. The tested model accounted for significant (46.5%) variance in purchase intentions. The findings support the call for extending TPB models to include context-specific variables that enhance explanatory power of TPB (Hien et al., 2024).
Findings from the current research may also prove useful for multiple stakeholders like fashion brands and various agencies which can use the insights to shape consumer expectations and experiences. Campaigns rooted in predictors identified as significant might go a long way in creating positive attitudes towards second-hand clothes.
5 Limitations and future research directions
While the study provides valuable insights into second-hand clothing purchase intentions among Indian youth, several limitations should be acknowledged. The study utilised a cross-sectional design which limits causal inferences. Additionally, the sample comprised majority of females and hence may have some concerns regarding the representation of gender. However, prior research points that more women than men purchase second-hand clothes (Kaur et al., 2023). Additionally, the study examined intentions rather than actual purchase behavior, highlighting the need for longitudinal research to understand the intention-behavior relationship more fully (Kaur et al., 2023). Future research can explore additional factors that may influence second-hand clothing consumption in the Indian context, such as product quality perceptions, hygiene concerns, and fashion consciousness. Moreover, investigating the moderating effects of demographic variables and cultural values could provide deeper insights into the heterogeneity of consumer responses to sustainable fashion alternatives.
6 Conclusion
The study successfully demonstrates that the extended TPB model provides a robust framework for understanding second-hand clothing purchase intentions among Indian young adults. The findings highlight the critical roles of environmental concern and mindful consumption in shaping attitudes toward sustainable fashion consumption, while confirming the continued relevance of traditional TPB constructs in this context. These results offer valuable guidance for developing targeted interventions and marketing strategies to promote sustainable consumption behaviors in the growing Indian fashion market which holds a huge potential owing to the predominantly young population of the nation.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
Ethical approval was not required for the studies involving humans because this research adheres to the principles of ethical conduct in research involving human subjects as outlined in the Declaration of Helsinki. The information solicited was not sensitive in nature and all participants provided informed consent before participating in the study, and their anonymity and confidentiality were ensured throughout the research process. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
HS: Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing. BA: Formal analysis, Methodology, Software, Supervision, Writing – original draft, Writing – review & editing. VB: Resources, Visualization, Writing – original draft, Writing – review & editing. HK: Resources, Visualization, Writing – original draft, Writing – review & editing.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frsus.2025.1695052/full#supplementary-material
References
Ajzen, I. (1985). “From intentions to actions: a theory of planned behavior” in Action control: From cognition to behavior (Berlin, Heidelberg: Springer Berlin Heidelberg), 11–39.
Ajzen, I. (1991). The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211. doi: 10.1016/0749-5978(91)90020-T
Ajzen, I. (2011). The theory of planned behavior: reactions and reflections. Psychol. Health 26, 1113–1127. doi: 10.1080/08870446.2011.613995,
Ajzen, I., and Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
Armitage, C. J., and Conner, M. (2001). Efficacy of the theory of planned behaviour: a meta-analytic review. Br. J. Soc. Psychol. 40, 471–499. doi: 10.1348/014466601164939,
Balderjahn, I., Peyer, M., and Paulssen, M. (2013). Consciousness for fair consumption: conceptualization, scale development and empirical validation. Int. J. Consum. Stud. 37, 546–555. doi: 10.1111/ijcs.12030
Bamberg, S. (2003). How does environmental concern influence specific environmentally related behaviors? A new answer to an old question. J. Environ. Psychol. 23, 21–32. doi: 10.1016/s0272-4944(02)00078-6
Bamberg, S., and Möser, G. (2007). Twenty years after Hines, Hungerford, and Tomera: a new meta-analysis of psycho-social determinants of pro-environmental behavior. J. Environ. Psychol. 27, 14–25. doi: 10.1016/j.jenvp.2006.12.002
Beneke, J., and Zimmerman, N. (2014). Beyond private label panache: the effect of store image and perceived price on brand prestige. J. Consum. Mark. 31, 301–311. doi: 10.1108/jcm-12-2013-0801
Bentler, P. M. (1983). Some contributions to efficient statistics in structural models: specification and estimation of moment structures. Psychometrika 48, 493–517. doi: 10.1007/bf02293875
Bhardwaj, V., and Fairhurst, A. (2010). Fast fashion: response to changes in the fashion industry. Int. Rev. Retail Distrib. Consum. Res. 20, 165–173. doi: 10.1080/09593960903498300
Boyer, S., Jiang, Z., and Lyu, J. (2024). Sustainable style without stigma: can norms and social reassurance influence secondhand fashion recommendation behavior among gen Z? J. Glob. Fashion Mark. 15, 341–356. doi: 10.1080/20932685.2024.2317796
Chaudhary, S., and Dey, A. K. (2016). Influence of socialisation agents on the materialism of Indian teenagers. Int. J. Indian Cult. Bus. Manag. 13, 182–204. doi: 10.1504/IJICBM.2016.078040
Chen, K., and Deng, T. (2016). Research on the green purchase intentions from the perspective of product knowledge. Sustainability 8:943. doi: 10.3390/su8090943
Chen, M., and Tung, P. (2013). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. Int. J. Hosp. Manag. 36, 221–230. doi: 10.1016/j.ijhm.2013.09.006
Chiou, Y., Lan, L. W., and Chang, K. (2010). Sustainable consumption, production and infrastructure construction for operating and planning intercity passenger transport systems. J. Clean. Prod. 40, 13–21. doi: 10.1016/j.jclepro.2010.09.004,
Cialdini, R. B., Reno, R. R., and Kallgren, C. A. (1990). A focus theory of normative conduct: recycling the concept of norms to reduce littering in public places. J. Pers. Soc. Psychol. 58, 1015–1026. doi: 10.1037/0022-3514.58.6.1015
Coelho, F., Pereira, M. C., Cruz, L., Simões, P., and Barata, E. (2017). <article-title update="modified" original="affect and the adoption of pro-environmental behavior: a structural model">affect and the adoption of pro-environmental behaviour: a structural model. J. Environ. Psychol. 54, 127–138. doi: 10.1016/j.jenvp.2017.10.008
Connell, K. Y. H. (2010). Internal and external barriers to eco-conscious apparel acquisition. Int. J. Consum. Stud. 34, 279–286. doi: 10.1111/j.1470-6431.2010.00865.x
Conner, M., and Armitage, C. J. (1998). Extending the theory of planned behavior: a review and avenues for further research. J. Appl. Soc. Psychol. 28, 1429–1464. doi: 10.1111/j.1559-1816.1998.tb01685.x
Cook, A., Kerr, G., and Moore, K. (2002). Attitudes and intentions towards purchasing GM food. J. Econ. Psychol. 23, 557–572. doi: 10.1016/s0167-4870(02)00117-4
Dascher, E. D., Kang, J., and Hustvedt, G. (2014). Water sustainability: environmental attitude, drought attitude and motivation. Int. J. Consum. Stud. 38, 467–474. doi: 10.1111/ijcs.12104
Dhandra, T. K. (2019). Achieving triple dividend through mindfulness: more sustainable consumption, less unsustainable consumption and more life satisfaction. Ecol. Econ. 161, 83–90. doi: 10.1016/j.ecolecon.2019.03.021
Djafarova, E., and Foots, S. (2022). Exploring ethical consumption of generation Z: theory of planned behavior. Young Consum. 23, 413–431. doi: 10.1108/yc-10-2021-1405
Down to Earth. (2024). India generates 8.5% of global textile waste: What it means for sustainability. Retrieved from down to earth website. New Delhi.
Dunlap, R. E., and Jones, R. E. (2002). “Environmental concern: conceptual and measurement issues,” in Handbook of environmental sociology. eds R. E. Dunlap, and W. Michelson (Westport, CT: Greenwood Press), 482–524.
Fauzi, M. A., Hasan, M. N., Zulkepeli, L., and Karuppiah, K. (2025). Organic food consumption and the theory of planned behaviour: science mapping of present and future trends. Br. Food J. 127:2741–2758. doi: 10.1108/bfj-09-2024-0931
Fishbein, M., and Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fishbein, M., and Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach (1st ed.). New York: Psychology Press.
Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50. doi: 10.1177/002224378101800104
Garg, P., Kumar, A., and Mittal, R. K. (2024). Sustainable food consumption behaviour: what really matters! Int. J. Sustain. Soc 16, 125–149. doi: 10.1504/ijssoc.2024.139496
Garnelo-Gomez, I., Saraeva, A., and Hurwood, L. (2025). Dress to impress the planet: how emotions, environmental concern and personal values influence sustainable fashion consumption. J. Sustain. Market. 1–20, 1–20. doi: 10.51300/10.51300/jsm-2025-142,
Gerbing, D. W., and Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. J. Mark. Res. 25, 186–192. doi: 10.1177/002224378802500207
Gkargkavouzi, A., Halkos, G., and Matsiori, S. (2019). Environmental behavior in a private-sphere context: integrating theories of planned behavior and value belief norm, self-identity and habit. Resour. Conserv. Recycl. 148, 145–156. doi: 10.1016/j.resconrec.2019.01.039
Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate Data Analysis. 7rd Edn. New Jersey: Prentice Hall.
Hair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 31, 2–24. doi: 10.1108/EBR-11-2018-0203
Hassan, L. M., Shiu, E., and Parry, S. (2015). Addressing the cross-country applicability of the theory of planned behavior (TPB): a structured review of multi-country TPB studies. J. Consum. Behav. 15, 72–86. doi: 10.1002/cb.1536
Hien, N. V. T., Thong, V. H., and Yen, T. H. (2024). Applying the extended theory of planned behavior model in studying luxury fashion products’ purchase intention of Vietnamese consumers. Rev. Gest. Soc. Ambient. 18:e05471. doi: 10.24857/rgsa.v18n6-095
Hill, J., and Lee, H. (2012). Young generation Y consumers’ perceptions of sustainability in the apparel industry. J. Fashion Mark. Manag. 16, 477–491. doi: 10.1108/13612021211265863
Hoang, D. P., Nguyen, V. D. H., Chu, Q. T., and Hoang, L. B. (2022). Factors affecting behavioral and psychological perspective of young Vietnamese customers in buying second-hand clothes. J. Eco. Finan. Manag. Studies 5, 1325–1345.
Horvat, K. P., and Vendramin, K. Š. (2021). Issues surrounding behavior towards discarded textiles and garments in Ljubljana. Sustainability 13:6491. doi: 10.3390/su13116491
Hristova, Y. (2019). The secondhand goods market: trends and challenges. Izv. J. Union Sci. 8, 62–71. doi: 10.36997/IJUSV-ESS/2019.8.3.62
Hu, L., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. Multidiscip. J. 6, 1–55. doi: 10.1080/10705519909540118
Jahari, S. A., Hass, A., Idris, I. B., and Joseph, M. (2022). An integrated framework examining sustainable green behavior among young consumers. J. Consum. Mark. 39, 333–344. doi: 10.1108/jcm-04-2021-4593
Jaiswal, D., and Kant, R. (2017). Green purchasing behavior: a conceptual framework and empirical investigation of Indian consumers. J. Retail. Consum. Serv. 41, 60–69. doi: 10.1016/j.jretconser.2017.11.008
Kapoor, A., and Khare, A. K. (2019). Understanding purchase intentions of pre owned clothing in India. J. Manag. 6, 9–22. doi: 10.34218/JOM.6.6.2019.002
Kaur, J., Gupta, S., and Singh, L. B. (2023). Role of justification of unethical behavior in sustainable fashion consumption among Indian consumers: a parallel mediation approach. J. Consum. Mark. 40, 842–853. doi: 10.1108/jcm-12-2020-4305
Kim, I., Jung, H. J., and Lee, Y. (2021). Consumers’ value and risk perceptions of circular fashion: comparison between secondhand, upcycled, and recycled clothing. Sustainability 13:1208. doi: 10.3390/su13031208
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: Guilford.
Kline, R. B. (2011). Principles and practice of structural equation modeling 3rd ed American Psychological Association. Available online at: https://psycnet.apa.org/record/2010-18801-000
Koay, K. Y., Lim, W. M., Khoo, K. L., Xavier, J. A., and Poon, W. C. (2024). Consumers’ motivation to purchase second-hand clothing: a multimethod investigation anchored on belief elicitation and theory of planned behavior. J. Prod. Brand. Manag. 33, 502–515. doi: 10.1108/jpbm-05-2023-4512
Kumagai, K. (2020). Sustainable plastic clothing and brand luxury: a discussion of contradictory consumer behaviour. Asia Pac. J. Mark. Logist. 33, 994–1013. doi: 10.1108/apjml-04-2020-0274
Leclercq-Machado, L., Alvarez-Risco, A., Gómez-Prado, R., Cuya-Velásquez, B. B., Esquerre-Botton, S., Morales-Ríos, F., et al. (2022). Sustainable fashion and consumption patterns in Peru: an environmental-attitude-intention-behavior analysis. Sustainability 14:9965. doi: 10.3390/su14169965
Lee, C. K. C., Levy, D. S., and Yap, C. S. F. (2015). How does the theory of consumption values contribute to place identity and sustainable consumption? Int. J. Consum. Stud. 39, 597–607. doi: 10.1111/ijcs.12231
Liu, F. (2022). Driving green consumption: exploring generation Z consumers’ action issues on sustainable fashion in China. Stud. Soc. Sci. Hum., 1, 25–49. Available online at: https://www.paradigmpress.org/SSSH/article/view/343
Lou, X., and Li, L. M. W. (2021). The relationship between identity and environmental concern: a meta-analysis. J. Environ. Psychol. 76:101653. doi: 10.1016/j.jenvp.2021.101653
Mak, T. M., Yu, I. K., Tsang, D. C., Hsu, S., and Poon, C. S. (2018). Promoting food waste recycling in the commercial and industrial sector by extending the theory of planned behavior: a Hong Kong case study. J. Clean. Prod. 204, 1034–1043. doi: 10.1016/j.jclepro.2018.09.049
McNeill, L., and Moore, R. (2015). Sustainable fashion consumption and the fast fashion conundrum: fashionable consumers and attitudes to sustainability in clothing choice. Int. J. Consum. Stud. 39, 212–222. doi: 10.1111/ijcs.12169
Miniero, G., Codini, A., Bonera, M., Corvi, E., and Bertoli, G. (2014). Being green: from attitude to actual consumption. Int. J. Consum. Stud. 38, 521–528. doi: 10.1111/ijcs.12128
Moitra, R., Khattar, A., and Desai, E. (2025). Second hand clothing: a circular economy strategy for sustainable consumption. J. Mark. Soc. Res. 2, 606–611. doi: 10.61336/jmsr/25-02-58
Mundel, J., Soopramanien, D., and Huddleston, P. (2021). Affordable luxuries: comparing American and Chinese millennial consumers. Asia Pac. Manag. Rev. 26, 215–225. doi: 10.1016/j.apmrv.2021.02.003
Nazarie, W. N. F. W. M., Roslan, A. H., Rahman, M. F. A., Hassan, M. H. A., and Shari, W. (2025). Exploring consumer intentions towards second-hand clothing among generation Z in Malaysia. J. Adv. Res. Bus. Manag. Stud. 38, 17–25. doi: 10.37934/arbms.38.1.1725
Obschonka, M., Silbereisen, R. K., Cantner, U., and Goethner, M. (2014). Entrepreneurial self-identity: predictors and effects within the theory of planned behavior framework. J. Bus. Psychol. 30, 773–794. doi: 10.1007/s10869-014-9385-2
Okur, N., Saricam, C., Iri, A. R., and Sari, I. (2023). Analyzing the impact of Covid-19 on sustainable fashion consumption with a model based on consumer value perceptions. J. Fash. Mark. Manag. 27, 826–850. doi: 10.1108/jfmm-10-2021-0272,
Paul, J., Modi, A., and Patel, J. (2016). Predicting green product consumption using theory of planned behavior and reasoned action. J. Retail. Consum. Serv. 29, 123–134. doi: 10.1016/j.jretconser.2015.11.006
Pivato, S., Misani, N., and Tencati, A. (2007). The impact of corporate social responsibility on consumer trust: the case of organic food. Bus. Ethics Eur. Rev. 17, 3–12. doi: 10.1111/j.1467-8608.2008.00515.x
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., and Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88:879. doi: 10.1037/0021-9010.88.5.879,
Riesgo, S. B., Lavanga, M., and Codina, M. (2022). Drivers and barriers for sustainable fashion consumption in Spain: a comparison between sustainable and non-sustainable consumers. Int. J. Fashion Des. Technol. Educ. 16, 1–13. doi: 10.1080/17543266.2022.2089239
Savari, M., and Khaleghi, B. (2023). Application of the extended theory of planned behavior in predicting the behavioral intentions of Iranian local communities toward forest conservation. Front. Psychol. 14:1121396. doi: 10.3389/fpsyg.2023.1121396,
Sharma, M., Luthra, S., Joshi, S., and Kumar, A. (2020). Developing a framework for enhancing survivability of sustainable supply chains during and post-COVID-19 pandemic. Int J Log Res Appl 25, 433–453. doi: 10.1080/13675567.2020.1810213
Sheth, J. N., Sethia, N. K., and Srinivas, S. (2010). Mindful consumption: a customer-centric approach to sustainability. J. Acad. Mark. Sci. 39, 21–39. doi: 10.1007/s11747-010-0216-3
Shim, S., Eastlick, M. A., Lotz, S. L., and Warrington, P. (2001). An online prepurchase intentions model. J. Retail. 77, 397–416. doi: 10.1016/s0022-4359(01)00051-3
Smith, J. R., Terry, D. J., Manstead, A. S. R., Louis, W. R., Kotterman, D., and Wolfs, J. (2007). Interaction effects in the theory of planned behavior: the interplay of self-identity and past behavior. J. Appl. Soc. Psychol. 37, 2726–2750. doi: 10.1111/j.1559-1816.2007.00278.x
Srinivasan, R. (2015). Exploring the impact of social norms and online shopping anxiety in the adoption of online apparel shopping by Indian consumers. J. Internet Commer. 14, 177–199. doi: 10.1080/15332861.2015.1008891
Steiger, J. H. (2006). Understanding the limitations of global fit assessment in structural equation modeling. Personal. Individ. Differ. 42, 893–898. doi: 10.1016/j.paid.2006.09.017,
Stolz, K. (2022). Why do(n’t) we buy second-hand luxury products? Sustainability 14:8656. doi: 10.3390/su14148656
Tabachnick, B. G., and Fidell, L. S. (2001). Using multivariate statistics. 4th Edn. Needham Heights, MA: Allyn and Bacon.
Tang, K. H. D. (2023). State of the art in textile waste management: a review. Text 3, 454–467. doi: 10.3390/textiles3040027
Tang Fat Sang, S. T. T., and Peng, X. B. (2025). Understanding the factors influencing individuals’ intention to buy second-hand clothing: a Mauritius perspective. Int. J. Res. Bus. Soc. Sci. 14, 27–45. doi: 10.20525/ijrbs.v14i2.3901
Taylor, M., White, K. M., Caughey, L., Nutter, A., and Primus, A. (2023). Unique and cheap or damaged and dirty? Young women’s attitudes and image perceptions about purchasing secondhand clothing. Sustainability 15:16470. doi: 10.3390/su152316470
The UN Alliance for Sustainable Fashion 2025 Home—the UN Alliance for sustainable fashion. Available online at: https://unfashionalliance.org/
Theodorou, A., Hatzithomas, L., Fotiadis, T., Diamantidis, A., and Gasteratos, A. (2023). The impact of the COVID-19 pandemic on online consumer behavior: applying the theory of planned behavior. Sustainability 15:2545. doi: 10.3390/su15032545
Uncles, M. D., Dowling, G. R., and Hammond, K. (2003). Customer loyalty and customer loyalty programs. J. Consum. Mark. 20, 294–316. doi: 10.1108/07363760310483676
United Nations Economic Commission for Europe (UNECE) 2018 Fashion and the SDGs: what role for the UN? Available online at: https://unece.org
Vehmas, K., Raudaskoski, A., Heikkilä, P., Harlin, A., and Mensonen, A. (2018). Consumer attitudes and communication in circular fashion. J. Fash. Mark. Manag. 22, 286–300. doi: 10.1108/jfmm-08-2017-0079,
Verain, M. C., Snoek, H. M., Onwezen, M. C., Reinders, M. J., and Bouwman, E. P. (2021). Sustainable food choice motives: the development and cross-country validation of the sustainable food choice questionnaire (SUS-FCQ). Food Qual. Prefer. 93:104267. doi: 10.1016/j.foodqual.2021.104267
Wang, Y., Min, Q., and Han, S. (2015). Understanding the effects of trust and risk on individual behavior toward social media platforms: a meta-analysis of the empirical evidence. Comput. Human Behav. 56, 34–44. doi: 10.1016/j.chb.2015.11.011
Wicaksono, P. A., Sari, D. P., Azzahra, F., and Sa’adati, N. A. (2024). Analysis of consumer behavior in purchasing second-hand fashion products: an extended theory of planned behavior model. Int. J. Sustain. Dev. Plann. 19, 2955–2964. doi: 10.18280/ijsdp.190813
Woo, E., and Kim, Y. G. (2019). Consumer attitudes and buying behavior for green food products. Br. Food J. 121, 320–332. doi: 10.1108/bfj-01-2018-0027
Xie, X., Hong, Y., Zeng, X., Dai, X., and Wagner, M. (2021). A systematic literature review for the recycling and reuse of wasted clothing. Sustainability 13:13732. doi: 10.3390/su132413732
Yan, R., Diddi, S., and Bloodhart, B. (2021). Predicting clothing disposal: the moderating roles of clothing sustainability knowledge and self-enhancement values. Clean. Resp. Consump. 3:100029. doi: 10.1016/j.clrc.2021.100029
Yang, J., Mamun, A. A., Reza, M. N. H., Yang, M., and Aziz, N. A. (2024). Predicting the significance of consumer environmental values, beliefs, and norms for sustainable fashion behaviors: the case of second-hand clothing. Asia Pac. Manag. Rev. 29, 179–194. doi: 10.1016/j.apmrv.2024.01.001
Zhao, H., Gao, Q., Wu, Y., Wang, Y., and Zhu, X. (2013). What affects green consumer behavior in China? A case study from Qingdao. J. Clean. Prod. 63, 143–151. doi: 10.1016/j.jclepro.2013.05.021
Keywords: second-hand clothing, sustainability, theory of planned behavior, environmental concern, mindful consumption
Citation: Sharma H, Arya B, Bisht V and Kumar H (2025) Fashionably sustainable: extending the theory of planned behavior to predict intentions to purchase second-hand clothes. Front. Sustain. 6:1695052. doi: 10.3389/frsus.2025.1695052
Edited by:
Praveen Goyal, Birla Institute of Technology and Science, IndiaReviewed by:
Aleksandra Figurek, University of Nicosia, CyprusTahira Javed, China Three Gorges University, China
Javier Ramirez, Corporación Universitaria Taller Cinco, Colombia
Copyright © 2025 Sharma, Arya, Bisht and Kumar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Bhavana Arya, YmhhdmFuYS5hcnlhQGphaXB1ci5tYW5pcGFsLmVkdQ==
Harshita Sharma1