INTRODUCTION
Background
Generation Z, also known as post-millennials, encompasses individuals born between 1995 and 2010, who are now entering young adulthood as college students This generation is characterized by a strong commitment to environmentally friendly products and sustainable practices Research indicates that Generation Z is well-informed about environmental issues and expects companies to take responsibility for social and environmental challenges They actively seek eco-friendly alternatives and are motivated to contribute to sustainability efforts.
India's demographic data reveals that 45% of its population is under the age of 25, while by the end of 2020, 40% of consumers in the United States are projected to belong to Generation Z (Empson, 2016).
By the end of 2020, Generation Z is expected to account for 40% of the global population (Amed et al., 2019), indicating that their socially conscious and change-oriented perspectives will greatly impact consumer behavior With the increasing prevalence of Generation Z consumers globally, this study will concentrate on understanding the consumption trends associated with this influential generational group.
Problem statement
The textile industry significantly harms the environment, accounting for 10% of global CO2 emissions and heavily relying on water, energy, and pesticides (Allwood et al., 2006; FAO-ICAC, 2015) The rise of "fast fashion," characterized by rapid production of inexpensive clothing trends, exacerbates this issue as demand surges, leading to increased resource consumption and textile waste (Joy et al., 2012; Rathinamoorthy, 2019) This trend negatively impacts environmental quality, necessitating a shift towards more sustainable practices (Kulshreshtha et al., 2017) Recycling textiles emerges as a viable solution, reducing the need for virgin fibers and minimizing the use of water, energy, and harmful chemicals in production (Vehmas et al., 2018; Dahlbo et al., 2017; Sandin and Peters, 2018) Embracing recycled clothing is crucial for mitigating the environmental consequences of the textile industry.
This study acknowledges several limitations that highlight opportunities for future research The reliance on a convenience sample of Generation Z consumers in India restricts the generalizability of the findings; thus, future studies should consider random sampling across diverse age groups for a more comprehensive understanding of consumer segments Additionally, while this research focused solely on purchase intentions, incorporating other attitude-intention-behavior models could provide deeper insights into consumer behavior Longitudinal studies may further enhance this understanding Future research should also investigate the mediating, moderating, and interactive effects within the Theory of Planned Behavior (TPB) model to clarify relationships among variables and improve predictive accuracy Moreover, exploring additional factors related to behavioral beliefs, normative beliefs, and perceived behavioral control could enrich the findings of subsequent studies.
This research paper highlights effective advertising strategies for promoting recycled clothing, emphasizing the environmental benefits it offers Marketing professionals should focus on ethics and personal commitment to inspire consumer purchases of recycled apparel Additionally, the report advocates for the development of marketing strategies that promote responsible consumption and raise awareness of environmental risks through social media By expanding campaigns on clothing recycling, the aim is to educate and engage Gen Z consumers, enhancing their ethical obligations and responsibility in purchasing decisions.
Purpose of research
This study aims to explore how Generation Z's inclination to purchase recycled clothing is shaped by factors such as environmental concern, perceived value, personal norms, and willingness to pay With a growing population and economic development, the demand for sustainable fashion is expected to rise, which poses challenges as increased clothing consumption leads to higher textile production and environmental degradation Generation Z is particularly aware of ecological issues and believes that businesses should address these challenges, demonstrating a willingness to shift towards eco-friendly products While previous research has primarily focused on the manufacturing aspect of recycled apparel, this study seeks to understand consumer behavior related to recycled clothing by applying the theory of planned behavior, thereby addressing a significant gap in the existing literature.
Research questions
In order to achieve the above research objectives and orientation for the research, our group has identified these questions to solve the following problems:
How do environmental concerts (EC), Personal Norm (PN), Willingness to pay premium (WPP) and Perceive Value (PV) factors influence Gen Z's intention to recycle clothes?
What impact does clothing recycling have on the environment and in the apparel industry?
What methods help effectively optimize the recycling of clothes?
Significance of research
Our research aims to clarify key issues, significantly contributing to the theoretical foundation of constructivism, particularly in our country This study will equip students with valuable data on the effectiveness of clothing recycling and the environmental impact of fast fashion trends Ultimately, the findings will enable businesses, manufacturers, and marketers to devise effective recycling communication strategies, including the promotion of eco-friendly products and legal measures to enhance quality of life.
LITERATURE REVIEW
Theoretical foundation
Structural equation modeling (SEM) is a powerful multivariate approach increasingly utilized in scientific studies to explore and evaluate causal relationships Unlike other modeling techniques, SEM assesses both direct and indirect effects of presumed causal links With a history spanning nearly a century, SEM has evolved through three generations, beginning with route analysis in the first generation (Wright, 1918-1921) The second generation saw the incorporation of factor analysis from the social sciences, enhancing SEM's capabilities The introduction of the "structural causal model" by Judea Pearl in 2000 and the integration of Bayesian modeling by Lee in 2007 signify the advent of the third generation of SEM.
For 16 years, ecologists have employed Structural Equation Modeling (SEM) to explore diverse hypotheses across multiple variables SEM allows for the analysis of complex causal relationships within ecosystems (Shipley 2002; Grace 2006) Chang highlighted the important connections between correlation and causation, enhancing our understanding of these concepts.
In the early 1980s, pioneering ecologists Maddox and Antonovics utilized Structural Equation Modeling (SEM) in their research, laying the groundwork for its application in ecology Grace (2006) subsequently released the first comprehensive book on SEM, featuring substantial examples from various environmental studies Over the past decade, the use of SEM in ecological sciences has experienced significant growth, as highlighted by Eisenhauer et al (2015).
Confirmatory factor analysis and path analysis are essential statistical techniques for Structural Equation Modeling (SEM) Confirmatory factor analysis, rooted in psychometrics, evaluates latent psychological traits such as attitudes and satisfaction In contrast, path analysis, originating from biometrics, identifies causal relationships between variables through path diagrams Historically, simultaneous equations in econometrics illustrated path analysis By integrating these methodologies, SEM gained traction across various fields, including social sciences, business, medicine, and natural sciences, starting in the early 1970s.
2.1.2 EC, PN, WPP, PV, PIRC
Environmental Concern (EC) signifies a person's awareness and sensitivity to environmental issues, emphasizing the importance of protecting and preserving natural resources while recognizing the impact of human activities on the environment.
Personal Norms (PN) refer to the internalized beliefs and values that shape an individual's understanding of right and wrong, as well as socially acceptable behaviors These norms play a crucial role in influencing decision-making and behavior, particularly in scenarios involving moral dilemmas.
Willingness To Pay (WPP) refers to the highest price an individual is prepared to pay for a specific good or service This concept is frequently utilized to assess the value individuals assign to environmental goods and services, including renewable energy sources and natural habitats.
Perceived Value (PV) is the significance an individual assigns to a product or service, shaped by personal beliefs, values, and the perceived benefits versus costs involved.
Purchase Intention for Recycled Clothing (PIRC)
Purchase Intention for Recycled Clothing (PIRC) reflects the probability that consumers will buy garments made from recycled materials This intention is shaped by factors such as perceived quality, pricing, personal values, environmental awareness, and overall perceived value Understanding PIRC is crucial for assessing consumer behavior and evaluating the success of marketing strategies designed to promote sustainable fashion.
Background foundation
Fast fashion appeals to consumers due to its convenience and affordability (Bhardwaj and Fairhurst, 2010) Emotional triggers often drive impulse purchases, leading individuals to buy more than necessary for self-satisfaction (Verplanken and Sato, 2011) This behavior results in excessive clothing demand, contributing to a rapid turnover and short shelf life of fast fashion items.
Growing awareness of environmental issues among consumers, particularly Gen Z, is significantly influencing the apparel market This generation is increasingly concerned about the negative impact of fast fashion on the environment, leading to a shift towards more responsible consumption Gen Z's openness to innovative and creative ideas fosters a greater likelihood of embracing recycled clothing options, positioning them as a key driver in promoting sustainable fashion practices.
Generations are defined by their birth periods, influencing their attitudes and consumption behaviors during formative years (Meredith and Schewe, 1994; Schewe and Meredith, 2004) The contemporary fashion market is primarily shaped by Baby Boomers (1946–1964), Generation X (1965–1975), and Generation Y (1976–1994), each exhibiting distinct spending patterns (Pentecost and Andrews, 2010; Barber, 2010) For example, Baby Boomers tend to invest in fewer high-quality items, while Generation Y favors purchasing more low-cost, trendy clothing (Crewe and Davenport, 1992) Additionally, Generation Z (1995–2010) is emerging as a powerful consumer group, prioritizing sustainability and environmental awareness in their purchasing decisions (Seemiller and Grace, 2016; Adnan et al., 2017) This generation is increasingly inclined to support sustainable brands, making it essential for businesses to understand their unique buying habits (Petro, 2020).
Perceived control stems from control beliefs, which reflect the conditions that facilitate or hinder the adoption of specific activities (Ajzen, 1991) Research highlights several factors influencing eco-friendly behavior, such as the availability of green products, perceived convenience, consumer involvement, prior purchases, green pricing premiums, and perceived time and effort (Gleim et al., 2013; Biswas and Roy, 2015; Gleim and J Lawson, 2014; Joshi and Rahman, 2015) Among these, pricing stands out as the most significant barrier to adopting eco-friendly products, as they typically carry a higher cost due to increased production and processing expenses (Gleim et al., 2013; Yadav and Pathak, 2017; Zhao and Zhong, 2015) Additionally, Indian consumers exhibit high price sensitivity, making pricing a critical obstacle to the purchase and use of eco-friendly items (Nasir and Karakaya, 2014; Yadav and Pathak, 2017).
Young consumers often face limited purchasing power, making price a significant factor in their buying decisions (Grankvist and Biel, 2001) However, recent surveys indicate that eco-conscious Indian consumers are increasingly willing to pay premium prices for products that prioritize environmental sustainability (Prakash and Pathak, 2017; Kirmani and Khan, 2018) When the benefits of eco-friendly products are recognized and valued, price becomes less of a barrier to their purchasing behavior (Moser, 2015; de-Magistris and Gracia, 2016).
Willingness to pay (WPP) serves as a crucial indicator of consumer behavior towards environmentally friendly products Therefore, it is hypothesized that WPP positively correlates with purchase intention for eco-friendly products (PIRC).
Attitudes toward behavior are shaped by beliefs about potential outcomes, influencing decision-making (Ajzen, 1991) Research indicates that consumers with strong environmental attitudes are more likely to buy eco-friendly products (Casalo and Escario, 2018; Ha and Kwon, 2016; Pagiaslis and Krontalis, 2014) In India, environmental concern (EC) is a significant predictor of eco-friendly behavior (Chaudhary and Bisai, 2018; Prakash and Pathak, 2017; Verma et al., 2019) Environmental consciousness is defined as the evaluation of facts and behaviors with environmental repercussions (Fransson and Garling, 1999) Studies show that environmentally conscious young consumers intend to purchase eco-friendly goods to mitigate their environmental impact (Kumar et al., 2019; Muralidharan and Xue, 2016) EC influences attitudes, subjective norms, and perceived behavioral control, thereby affecting purchasing intentions (Chen and Tung, 2014; Paul et al., 2016) EC has both direct and indirect effects on the intention to buy green brands and products with eco-labels (Hartmann and Apaolaza-Ibanez, 2012; Kulshreshtha et al., 2019) It positively impacts the decision to purchase eco-friendly products, serving as a key predictor of such behavior among European Americans (Eom et al., 2016) Additionally, Asian consumers also show a favorable correlation between EC and green product preferences (Jaiswal and Kant, 2018), indicating EC's strong predictive power for the desire to buy recycled clothing.
Promoting pro-environmental behavior is heavily influenced by personal moral norms (PN), which significantly shape individuals' intentions and actions towards eco-friendly practices Recent research indicates that young consumers exhibit strong personal moral norms, guiding their intentions to engage in environmentally responsible behavior.
Personal norms are the beliefs individuals hold about themselves and their moral obligation to act ethically As noted by Schwartz (1977), these norms manifest as a sense of duty to behave in specific ways They reflect the moral standards and responsibilities that individuals prioritize when engaging in particular behaviors.
Numerous studies highlight the critical role of personal norms in fostering environmentally-friendly behavior Research indicates that consumers' acceptance of eco-friendly innovations is largely influenced by their environmental values and norms (Jansson, 2011) Furthermore, personal norms significantly contribute to the adoption of green products, underscoring their importance in promoting sustainable consumer choices (Gleim et al., 2013; Nguyen et al., 2018).
Empirical studies have demonstrated a positive correlation between personal norms and pro-environmental behavior Research by Jansson et al (2010) and Ha and Janda (2012) indicates that personal norms influence the adoption of green mobility and energy-efficient products Additionally, Dolnicar (2010) explored how personal norms affect the intention to engage in environmentally friendly practices during vacations Mehmetoglu (2010) further corroborated this relationship, showing that a sense of moral obligation towards environmental protection is positively associated with pro-environmental behavior.
2.2.6 The theory of planned behavior
The theory of planned behavior (TPB), proposed by Ajzen in 1991, is utilized in this study to examine behaviors related to insufficient volitional control, particularly in the context of fast fashion consumption This consumption often stems from impulsive decision-making, making the TPB framework particularly relevant for understanding these behaviors.
The Theory of Planned Behavior (TPB), proposed by Ajzen in 1991, posits that human behavior can be predicted based on individuals' intentions, which are shaped by three distinct belief structures: behavioral beliefs, normative beliefs, and perceived behavioral control Behavioral beliefs relate to the outcomes of engaging in an activity, while normative beliefs reflect the influence of others' perceptions on one's actions Perceived behavioral control encompasses factors that may facilitate or hinder the performance of the activity The TPB model has been widely utilized to understand consumers' eco-friendly purchasing behaviors, with studies demonstrating its effectiveness in explaining environmentally responsible apparel choices This research aims to explore the objective beliefs that impact behavioral intentions to purchase recycled clothing through the lens of the TPB model.
Recent studies indicate that enhancing the Theory of Planned Behavior (TPB) with domain-specific constructs can boost its predictive accuracy (Yadav and Pathak, 2017; Chen and Tung, 2014) Notably, perceived value (PV) has been identified as a significant factor influencing consumers' intentions to purchase eco-friendly products (Cheung et al., 2015; Wang et al., 2019) Consequently, we have incorporated PV as an additional construct within the TPB framework.
Perceived value (PV) is defined as the customers’ overall assessment of the benefits they receive relative to what they sacrifice (Zeithaml, 1988) According to Chen and Chang (2012), PV reflects consumers’ perception of a product or service's importance based on its usefulness In the current marketplace, customer value plays a crucial role, as consumers often envision the value they anticipate from their purchases (Woodruff, 1997) Research indicates that PV significantly impacts customers’ decision-making processes and buying intentions (Chen and Chang, 2012; Yadav and Pathak).
Previous model
2.3.1 Research of key paper: Investigating the determinants of behavioral intentions of generation Z for recycled clothing: an evidence from a developing economy
This research paper explores the factors influencing Generation Z's intention to purchase recycled clothing in India, based on data collected from five universities with 497 usable responses Key findings reveal that environmental concern, perceived value, personal norms, and willingness to pay significantly impact purchase intentions, with willingness to pay, environmental concern, and perceived value identified as the primary predictors The study offers essential insights for marketers of recycled clothing and fills a research gap in consumer behavior related to recycled clothing consumption.
This research has notable limitations that highlight opportunities for future exploration Firstly, the use of a non-random sample of Generation Z consumers from India limits the generalizability of the findings Future studies should incorporate diverse age groups with random sampling to enhance understanding across various consumer segments Secondly, while this study focused on purchase intention, subsequent research could investigate consumer behavior through different models that consider attitude, intention, and behavior Longitudinal studies would also provide valuable insights Lastly, future research should examine the mediation, moderation, and interaction effects of various factors within the Theory of Planned Behavior (TPB) model to deepen the understanding of variable relationships and improve predictive accuracy.
Future studies could also explore various other factors related to beliefs about behavior, norms and perceived behavioral control.
2.3.2 Research of support paper 2 : Factors Affecting Young Consumers’ Intention to Purchase Upcycled Fashion Products – A Case Study in Vietnam
This article explores the relationship between buyer attitudes and intentions, specifically examining the factors that influence young Vietnamese consumers' willingness to purchase recycled fashion products By surveying 400 young adults aged 18 to 34 in Hanoi and Ho Chi Minh City, the study analyzes the impact of five key factors: environmental concerns, social value, uniqueness value, financial risk perception, and perceived quality risk.
This study has notable limitations, primarily its focus on a small sample of consumers in Hanoi, Vietnam, which restricts the ability to generalize findings to other regions or age demographics Additionally, it overlooks significant factors influencing consumer intentions, such as aesthetic and emotional value, as well as media influence, which are essential in understanding the willingness to purchase upcycled fashion products.
2.3.3 Research of support paper 1 : Generation Y's moral obligation and purchase intentions for organic, fair-trade, and recycled apparel products
This study examined Generation Y's (Gen Y) knowledge, attitudes, ethical obligations, and purchasing intentions regarding organic, fair trade, and recyclable clothing An online survey of 442 participants revealed a significant lack of awareness about clothing with corporate social responsibility (CSR) attributes among Gen Y Statistical analyses, including t-tests and multiple linear regressions, indicated that moral obligations positively influence purchase intentions, particularly among women, who exhibit stronger moral and attitudinal commitments towards garments made from organic materials, fair trade labels, and recycled materials These findings highlight Gen Y's potential as ethical consumers, suggesting opportunities for future CSR initiatives in the apparel industry.
The research indicates that Generation Y's purchasing intentions for clothing are significantly influenced by their ethical responsibilities and attitudes toward Corporate Social Responsibility (CSR) attributes However, the ability to generalize these findings is limited due to the study's geographical focus Future research could enhance understanding by visually depicting CSR attributes and comparing them with the current study's results.
Research development
The hypothetical SEM model employs matching groups to thoroughly analyze problem factors, overcoming the limitations of other models that fail to classify specific variables based on geography and age This approach incorporates both exogenous and endogenous variables, providing a more comprehensive understanding of the issue at hand.
Structural equation modeling (SEM) serves as a key analytical tool for evaluating cause-and-effect relationships involving latent variables (Hair, 2015) By simultaneously analyzing the complex interactions among multiple exogenous and endogenous factors, SEM addresses the limitations of bivariate analyses (Hair, 2015) Its strong theoretical foundation and empirical support, combined with the direct relevance of its variables to the research, enhance its clarity and simplicity, making the interpretation of the analysis findings more straightforward.
In the proposed model, exogenous variables such as EC, PN, WPP, and PV serve as independent factors determined externally, influencing the endogenous variable, PIRC, which the model aims to predict The model establishes PIRC's value based on these exogenous variables To assess the model's effectiveness, the researchers utilized widely recognized fit indices, confirming that the overall model demonstrates a satisfactory fit according to the goodness-of-fit statistics (Hair, 2015).
The proposed model consists of exogenous variables, which are independent, and endogenous variables that rely on other variables within the model Goodness-of-fit statistics indicate that the model aligns well with the data, while fit indices are utilized to evaluate its overall performance.
METHODOLOGY
Research design
The team opted for a direct approach by conducting a survey using a questionnaire aimed at evaluating various research scales and models The study's goal is to identify and measure the factors influencing the purchasing decisions of Generation Z while eliminating those with no impact To ensure relevance, the questionnaire was translated into Vietnamese for local consumers Following its completion, the team conducted surveys at several universities in Vietnam, targeting individuals over 18 years old The questionnaire, created using Google Form Utilities, included basic personal information and utilized the Likert scale for responses.
Questionnaire design
A structured questionnaire was used to collect data for this research, based on the framework designed from the results of the preliminary study The questionnaire was divided into two parts:
• Part I: Personal information, which included gender, age, industry, and personal income This information was gathered to understand the characteristics of the participants and their demographics.
The survey content encompassed statements addressing key factors like environmental concern, personal norms, willingness to pay, perceived value, and purchase intention for recycled clothing Participants rated these statements using a 5-point Likert scale, where 1 indicated "Strongly Disagree" and 5 signified "Strongly Agree."
Measurement scales
The template is based on the construction scale theory and previous studies on behavioral intentions of generation Z for recycled clothing in Viet Nam consists of
The study examines several key factors influencing college student learning through social networking applications, including concern (4 items), personal norms (3 items), willingness to pay (3 items), perceived value (4 items), and purchase intention for recycled clothing (4 items) A five-level Likert scale was utilized, ranging from 1 (Strongly disagree) to 5 (Strongly agree), to measure these variables effectively.
The natural environment is a major concern for me.
I am willing to reduce my consumption to protect the environment.
Significant social changes are necessary to safeguard the natural environment.
Stricter enforcement of anti-pollution laws is needed.
Personal norms I have a personal obligation to conserve natural resources.
I should do what I can to conserve natural resources
I strongly feel the need to use recycled clothing.
Willingness to I would pay more for environmentally WPP1 Jang et al.
I am willing to pay an extra percentage for recycled clothing that supports environmental sustainability efforts.
I feel proud to own recycled clothing, despite its higher cost.
Perceived value The environmental benefits of recycled clothing provide me with good value.
I purchase recycled clothing because of its environmentally conscious production.
I buy recycled clothing because it is eco-friendly and has a positive impact on the environment.
I purchase recycled clothes because it has more environmental benefit than conventionally produced clothes
Purchase In the future, I will consider purchasing PIRC1 Paul et al. intention for recycled clothing recycled clothing because it is less polluting.
I plan to spend more on recycled clothing instead of conventional clothing.
I expect to buy recycled clothing because of its positive environmental contributions.
I am definitely interested in buying recycled clothing in the near future.
Sampling
A survey was conducted with 295 participants, revealing that 54.2% were female and 45.8% were male The majority of respondents, 74.6%, were aged between 18 and 20, while 25.4% were aged 21 to 26 Notably, 79.3% of participants were university students, with the remaining demographics including 2.4% office staff, 3.1% freelancers, 6.1% business owners, and 9.2% from other professions Income levels showed that approximately 70% earned less than 5 million VND, followed by 19.1% earning between 5 to less than 10 million VND, 6.1% with incomes ranging from 10 to less than 20 million VND, and 5.8% earning above 20 million VND.
A larger sample size in a study reduces estimation errors and enhances population representation However, gathering extensive samples requires significant time, effort, and financial resources throughout collection, testing, and analysis stages Therefore, it is crucial to thoughtfully consider sample size to ensure balance and efficiency Due to time and resource limitations, the group could not survey a substantial number of samples, prompting them to utilize established formulas to aid in the sampling process.
The minimal sample size, according to research by Hair, Anderson, and Black
(1998), should be five times the total observed variable Researchers examine elements using the following formula (Comrey, 1973; Roger, 2006): n = 5 *m (m is number of question)
The minimum sample size needed, according to research by Tabachnick and Fidell
(1996), is: n = 50 +8 *m (m is number of independent variables)
After an eight-day data collection duration and based on these two formulations, we have the following results:
To enhance the validity and persuasiveness of our analysis, we estimate a target sample size of approximately 200, although the minimum required sample size is 50.
Collection method
The average time for survey participants to complete the study was approximately 3-5 minutes The survey links were distributed through popular student forums, including community groups, survey switch groups, and relevant blogs, as well as via messaging platforms like Messenger, Instagram, and Zalo Data collection commenced in early April 2023, and by April 20, 2023, a total of 295 responses were recorded However, after a thorough review, only 267 responses were deemed valid for analysis, as 28 forms were excluded for being either irrelevant or unsuitable for the research objectives.
DATA ANALYSIS
Respondent demographics
In a survey conducted over two weeks, 295 responses were collected, resulting in 266 valid submissions, yielding a validity rate of 90.1% after excluding 29 non-qualified answers Demographic analysis revealed that 53.8% of respondents were female and 46.2% were male, with a significant majority (75.2%) aged between 18 and 20, followed by 24.8% in the 21 to 26 age range The largest group of respondents identified as students (80.1%), with smaller percentages from business (6%), freelancers (3.4%), office staff (1.9%), and other occupations (8.6%) Additionally, 69.5% of participants reported a monthly income below 5 million.
Among the respondents, 4.9% reported monthly earnings between 5 to below 10 million, while 13 individuals (5.3%) claimed earnings exceeding 20 million In the past six months, 41.9% of 111 participants purchased fashion products made from recycled materials 1-3 times, with 34.3% not making any purchases Additionally, 13.6% bought such products 4-6 times, while 6% and 4.1% reported purchases 7-9 times and over 10 times, respectively.
Age From 18 to 20 years old
Measurement scale
Before analysis, it's crucial to assess the suitability of the observed variables and the research model used in the study The research model includes latent variables represented by observable indicators, which are interrelated and influence each other's values Evaluating these factors is essential for accurate analysis The outer loadings index measures the relevance of each observed variable, with values above 0.7 indicating high factor relevance, as suggested by Joy et al (2012) In this research, all variables exceed the 0.7 threshold, confirming their validity and reliability for analysis, as detailed in Table 4.2.
Table 3 Outer loading, VIF, AVE and Composite Reliability (Smart PLS 4.0)
Purchase intention for recycled clothing
The author assesses the reliability of observed variables by examining their internal consistency, which reflects how well the items within a variable measure the same construct Numerous studies suggest that Composite Reliability (CR) is a superior indicator of internal consistency compared to Cronbach's Alpha (CA), as CA's reliability estimates can fluctuate based on the number and variance of items (Hair et al., 2012) Nonetheless, the author incorporates both CR and CA in the evaluation process.
In this study, the correlation among items within the same latent variable is assessed using Composite Reliability (CR) and Cronbach's Alpha (CA) According to Hair et al (2017), both CR and CA values must exceed 0.7 to confirm the internal consistency and reliability of the measurements, indicating that the items are effectively measuring the same construct The results show that all variables achieved CR and CA values greater than 0.7, demonstrating a high level of consistency and compatibility among the observed variables.
According to Hair et al (2014), to prevent multicollinearity in a measurement model, it is essential for the variables to maintain a low Variance Inflation Factor (VIF) Multicollinearity arises when variables exhibit high correlations, potentially compromising the model's validity A VIF value below 5 is recommended to confirm the absence of multicollinearity among the variables.
The Variance Inflation Factors (VIFs) for the variables in this study range from 1.277 to 3.186, all of which are below the threshold of 5 This indicates that there is no evidence of collinearity within the research model's data, confirming that the variables are appropriate for further analysis.
The author utilized Average Variance Extracted (AVE) to assess the convergent validity of the scale, which indicates the extent to which a scale correlates positively with other measures of the same variable (Hair et al., 2013) According to Hair et al (2013), an AVE value exceeding 0.5 signifies that over 50% of the variance in the respective items is accounted for by the variable Conversely, an AVE below 0.5 suggests that error variance surpasses explained variance, leading to the exclusion of that variable from the analysis.
The study reveals that all variables exhibit acceptable convergent validity, with AVE values exceeding 0.5, ranging from 0.635 to 0.750 Notably, the Personal Norms variable demonstrates the strongest convergent validity at 0.750, indicating a high correlation among its items Conversely, the Environmental Concern variable shows the weakest convergent validity with an AVE of 0.635, suggesting a lower correlation among its items.
In their study, Wiegard and Breitner (2019) utilized the cross-loading coefficient to assess the validity of the model's variables This coefficient reflects the extent of association between an observed variable and other factors within the model The analysis results, as shown in Table 4.4, reveal that each observed variable exhibits external loading coefficients that surpass the cross-loading coefficients of variables from other factors, indicating strong validity within the model.
EC PIRC PN PV WPP
The analysis presented in Table 4.4 indicates that the loading coefficients for variables EC1, EC2, EC3, and EC4 are 0.839, 0.774, 0.779, and 0.794, respectively, all of which exceed their corresponding cross-loadings Similarly, the variables PIRC, PN, PV, and WPP also demonstrate loading coefficients that surpass their cross-loadings This suggests that all variables in the study exhibit a high discriminant value, indicating a low degree of correlation among them, with each variable effectively representing a distinct factor.
The author assesses the discriminant validity of each variable in the model using two key indices: the Average Variance Extracted (AVE) index and the Latent Variable Correlations (LVC) Discriminant validity measures how distinct a factor is from others within the model, determined by comparing the square root of AVE with the correlation coefficients among the factors According to Fornell & Larcker (1981) and Joe et al (2011), a model demonstrates adequate discriminant validity when the square root of AVE for each factor exceeds its correlation with other factors Following the evaluation of loadings and cross-loadings coefficients, which reflect the connections between observed variables and factors, the author further investigates the AVE and LVC indices presented in Table 4.4, revealing the interrelationships among the factors.
Table 5 Fornell & Larcker (Smart PLS 4.0)
EC PIRC PN PV WPP
The bolded value in Table 4.4 signifies the square root of the Average Variance Extracted (AVE), indicating how effectively a factor accounts for its indicators This value surpasses the Latent Variable Correlation (LVC), which measures the correlation between two factors According to Fornell & Larcker’s criteria, this confirms the discriminant validity of the model, ensuring that each factor is distinct from one another The sample data utilized in the analysis aligns with the discriminant criteria of the research model, grounded in the theoretical framework and literature review.
The author conducted a multicollinearity test using the VIF method to assess the reliability of the research model Multicollinearity occurs when two or more factors are highly correlated, potentially compromising the model's integrity According to Hair et al (2013), a VIF value should not exceed 5 to mitigate multicollinearity concerns Table 4.2 reveals that all factors in the model have VIF values significantly below this threshold, with the highest at 3.186 for PV4 and the lowest at 1.562 for PIRC4 This indicates that the research model's data is free from multicollinearity, confirming the independence of the factors involved.
After analyzing the factors in the measurement model, the variables are valid and affect the final results, the author continues to analyze in the structural model.
Structural Model
Model fit is a crucial metric for evaluating how well a proposed model aligns with available data According to Marko et al (2022), the standardized root mean square residual (SRMR) is recommended for this assessment, as it measures the variance between the implied and observed correlation matrices A strong model fit is indicated by SRMR values below 0.10 or 0.08 (Hu and Bentler, 1999) To avoid model misspecification, Henseler et al (2014) advocate for using SRMR as a quality-of-fit statistic in PLS-SEM analysis In this study, the SRMR was recorded at 0.078, qualifying the model fit (Hu and Bentler, 2000) Additionally, the normed fit index (NFI), which compares the model's Chi-square value to a reference, indicates a good fit with values above 0.75 (Bentler & Bonett, 1980) The NFI in this study was 0.756, suggesting a suitable model fit.
The coefficient of determination, represented by R Square, evaluates the accuracy of a structural model by measuring the correlation between actual and predicted values of a latent variable R Square values range from 0 to 1, with higher values indicating a more accurate model According to Joe and Partner (2011), R Square values of 0.75 are deemed high, 0.50 average, and 0.25 low, providing a clear framework for assessing model performance.
Table 7 's variable PIRC has an R-Square value of 0.586, which indicates a moderate amount of independent variable explanation.
Bootstrap methods, as outlined by Hair et al (2013), involve randomly sampling data and repeatedly estimating the model as the data varies This process generates a series of T-statistics to assess the model's significance In this study, the researchers calculated the T-Value using 295 data points to evaluate the significance of the structural path.
In a study involving 5,000 samples, a T-statistics value of at least 1.96 is required to establish significant relationships at a 0.05 significance level, corresponding to a 95% confidence interval (Joe and Partner, 2011) It is noted that as the significance level decreases, the T-statistics value increases; for instance, a significance level of 0.1 yields a T-value of 1.65, while 2.58 is the threshold for 0.01 To validate the hypotheses and assess their reliability, researchers must examine the P-value, with lower P-values indicating reduced reliability A P-value below 0.05 is essential for determining the adequacy of the study model.
Original Sample Standard T-statistics P values sample
Hypothesis H1 predicts that PIRC is negatively influenced by EC Based on Table
The analysis revealed that Hypothesis H1 is unsupported, as indicated by a P-Value greater than 0.05 and a path coefficient of β=-0.066 Conversely, Hypothesis H2 is supported, with a significant path coefficient of β=0.169 and a P-Value of 0.010 Hypothesis H3 was accepted, demonstrating a strong positive effect of PV on PIRC, with a path coefficient of β=0.648 and a P-Value of 0.000 In contrast, Hypothesis H4 was not supported, showing non-significant results with a path coefficient of β=0.070 and a P-Value of 0.161.
Result of verify research hypothesis
The contents of Hypothesis Results
H1 Environmental concern (EC) has negatively influenced Purchase intention for recycled clothing (PIRC)
Purchase intention for recycled clothing
Purchase intention for recycled clothing
H4 Willingness to Pay influences Purchase intention for recycled clothing (PIRC)
The data analysis results indicate that hypotheses H2 and H3 are accepted, while hypothesis H1 is rejected, revealing that environmental concern (EC) negatively affects the purchase intention for recycled clothing Additionally, hypothesis H4 is also dismissed, as the willingness to pay adversely influences the purchase intention for recycled clothing (PIRC).
CONCLUSION AND RECOMMENDATIONS
Research Summary
This study aimed to explore the factors influencing Generation Z's behavioral intentions towards recycled garments in Vietnam The findings indicate that the objectives of the research have been successfully met.
1 Identify the factors affecting the purchase intention of young consumers towards recycled fashion products in Viet Nam.
2 Measure the influence of each factor on young consumers' decision to buy recycled clothes in Viet Nam.
3 Propose some solutions to raise awareness of young consumers towards the recycled products in Viet Nam.
4 Test the correctness of the model.
5 Finally, propose and call for some recommendations from the research results to increase the awareness of young people in Viet Nam on the issue of buying and using recyclables for the environment.
This study examines the awareness levels of young consumers in Vietnam regarding their purchasing decisions related to recycled fashion Utilizing a research model, the study analyzes data collected from a sample of 295 young consumers, highlighting key insights into their attitudes and behaviors toward sustainable fashion choices.
Nam The research model has been verified through many steps to ensure its practical application.
The findings of this study reveal a significant divergence from previous research, which indicated that various factors positively influence the purchase intention of recycled fashion products In contrast, this study conducted in Vietnam demonstrates a different reality, where the relationships between environmental consciousness (EC) and both perceived intrinsic rewards of consumption (PIRC) and willingness to pay (WPP) with PIRC yield negative results.
In conclusion, young people's environmental consciousness varies significantly across regions, influenced by their living environments A report from India highlights that awareness of environmental issues linked to fast fashion is growing, emphasizing the need to educate Generation Z on becoming informed consumers In contrast, while young people in Vietnam are aware of recycled garments, their understanding of their importance is still developing, leading to concerns about the willingness to invest in recycled fashion products This illustrates that similar issues can yield different outcomes based on the surrounding context.
Theoretical implications
This research explores how environmental concern, perceived value, personal norms, and willingness to pay affect Generation Z's intention to purchase recycled clothing in Vietnam, utilizing the theory of planned behavior.
Prior research has utilized the theory of planned behavior to explore consumers' intentions to purchase recycled clothing, highlighting key factors such as behavioral beliefs, normative beliefs, and perceived behavioral control In their study, Pallavi Chaturvedi, Kushagra Kulshreshtha, and Vikas Tripathi emphasize that these elements significantly influence purchasing intentions for green clothing, particularly in contexts where individuals face incomplete volitional control.
Recent research highlights the influence of Personal Norms (PN) and Perceived Value (PV) on Gen Z consumers' intentions in India, as demonstrated by the work of Pallavi Chaturvedi, Kushagra Kulshreshtha, and Vikas Tripathi Our analysis indicates that these factors are also relevant in Vietnam However, while Environmental Concerns (EC) and Willingness to Pay Premiums (WPP) significantly affect intentions in India, they do not play a crucial role for Gen Z consumers in Vietnam regarding their intention to purchase recycled clothing These findings suggest that the existing theories can enhance our understanding of consumer intentions, offering varied interpretations across different cultural contexts.
In the research conducted by Pallavi Chaturvedi, Kushagra Kulshreshtha, and Vikas Tripathi, it was initially found that Environmental Concerns (EC), Personal Norms (PN), Perceived Value (PV), and Willingness to Pay Premium (WPP) positively influenced the Purchase Intention on Recycled Clothing (PIRC) However, in our study focused on Vietnam, EC and WPP were excluded due to data analysis results, while PN and PV were validated as significant factors This research highlights the established relationship between PN and PV, emphasizing their importance in influencing PIRC.
Limitations and Recommendations for future research
This research offers valuable insights into Vietnamese consumers' attitudes and behaviors regarding recycled clothing, but it is important to recognize certain limitations Acknowledging these limitations can pave the way for future research to enhance and expand upon the findings of this study.
Despite the rising interest in sustainable fashion in Vietnam, many consumers remain unaware of the environmental advantages of recycled clothing, which may hinder demand To address this gap, future research should focus on strategies to enhance consumer awareness and educate them on the positive environmental impact of recycled apparel.
Cultural attitudes significantly influence Vietnamese consumers' willingness to buy second-hand clothing, differing from perceptions in other countries Factors such as tradition, social norms, and hygiene perceptions shape these attitudes To enhance the acceptance of recycled clothing in Vietnam, future research should focus on understanding and addressing these cultural barriers.
The availability of recycled clothing in Vietnam is currently restricted, primarily found in second-hand markets or online platforms that may not be easily accessible to all consumers This limited accessibility could hinder the growth of demand for recycled clothing Future studies should investigate strategies to enhance the availability of recycled clothing, potentially through collaborations with mainstream retailers.
Vietnamese consumers often view recycled clothing as inferior to new garments, which may hinder the growth of demand for sustainable fashion in Vietnam To address this issue, future studies should focus on assessing the quality of recycled clothing and exploring strategies to enhance its appeal and meet consumer expectations.
Vietnamese consumers tend to be price sensitive regarding recycled clothing, often viewing it as less valuable compared to new apparel This perception may hinder the growth of demand for recycled clothing in Vietnam Future studies should focus on strategies to enhance the perceived value of recycled clothing among consumers.
This research offers important insights into Vietnamese consumers' attitudes and behaviors regarding recycled clothing The findings highlight strategies to improve the perceived value of recycled apparel in Vietnam, ultimately promoting sustainable fashion in the region.
To enhance the perceived value of recycled clothing in Vietnam, it is essential to raise public awareness about its benefits This can be achieved through targeted advertising campaigns, leveraging social media platforms, and collaborating with sustainable fashion influencers to promote the advantages of wearing recycled apparel.
Collaborating with local designers to develop stylish recycled clothing collections can significantly elevate the perceived value of recycled fashion in Vietnam By infusing contemporary trends into these collections, recycled clothing becomes a fashionable choice rather than a less appealing option, appealing to consumers' desire for trendy and sustainable apparel.
Recycled clothing offers an affordable and budget-friendly fashion alternative, making it an attractive option for a broader audience, particularly for those who may not have the means to invest in luxury or high-end apparel.
Vietnam is known for its beautiful natural landscapes, and therefore, highlighting the environmental benefits of recycled clothing can resonate with the population.
By emphasizing the positive impact that recycled clothing has on the environment, the perceived value of the product can increase, encouraging individuals to choose it over conventional clothing.
Hosting sustainable fashion events that highlight recycled clothing can effectively raise awareness and enhance its perceived value These events, which may feature fashion shows, pop-up shops, and clothing swaps, serve as educational platforms, informing attendees about the advantages of recycled clothing and fostering a commitment to sustainable fashion practices.
While enhancing the perceived value of recycled clothing through affordability is beneficial, it risks initiating price wars with traditional clothing Additionally, collaborating with local designers can elevate the perceived value of recycled garments, but this strategy may not guarantee a corresponding rise in sales.
Future research is essential to address current limitations and devise strategies that promote sustainable fashion in Vietnam By implementing these recommendations, we can encourage individuals to opt for recycled clothing instead of conventional options, paving the way for a more sustainable future.
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