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Article

Nexus between Environmental Consciousness and Consumers’ Purchase Intention toward Circular Textile Products in India: A Moderated-Mediation Approach

by
Mushahid Ali Shamsi
1,
Asiya Chaudhary
1,
Imran Anwar
2,*,
Rajarshi Dasgupta
3 and
Sachin Sharma
4
1
Department of Commerce, Aligarh Muslim University, Aligarh 202002, India
2
University Centre for Research and Development, Chandigarh University, Mohali 140413, India
3
Integrated Sustainability Centre (ISC), Institute for Global Environmental Strategies, Minato City 240-0115, Japan
4
IPE Global Ltd New Delhi, New Delhi 110024, India
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(20), 12953; https://doi.org/10.3390/su142012953
Submission received: 8 September 2022 / Revised: 22 September 2022 / Accepted: 29 September 2022 / Published: 11 October 2022
(This article belongs to the Special Issue Ecosystem Services and Human Wellbeing: Linking Science, Policy and Practices)
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Abstract

:
The textile industry has witnessed rapid growth due to fast fashion and the growing use of textile products, resulting in terribly increasing textile waste and biodiversity and humans. Therefore, a shift from a linear paradigm (take-make-use-discard) to a circular model of textiles production (take-make-use-recycle-remanufacture-reuse) is urgently required. Still, it can only be successful if consumers accept circular textile products (CTP). Hence, the study assesses the direct and indirect (via perceived risks and perceived benefits) influence of environmental consciousness on purchase intention. Moreover, the study also attempts to check the moderating role of product knowledge on the direct links between perceived risks, perceived benefits, and purchase intention such that the indirect effects of environmental consciousness (via perceived risks and perceived benefits) on purchase intention are conditioned at low/high levels of product knowledge. Collecting a sample of 409 respondents from the National Capital Region (NCR) and Aligarh in India, we used SEM to test the direct and indirect effects, while model-14 in Process Macro was used to measure conditional indirect effects. The results show that environmental consciousness directly influences purchase intention and perceived risks, and perceived benefits partially mediate the direct link between environmental consciousness and purchase intention. Further, product knowledge conditionally moderates the indirect effect of EC on PI (via perceived risks and perceived benefits) such that the mediating effects of perceived risks and perceived benefits significantly vary at low/high levels of product knowledge. The findings direct retail managers and decision-making bodies in the Indian textile industry to frame focused strategies for reducing textile waste and protecting the environment by developing bylaws in favor of circular economy and CTP.

1. Introduction

The textile industry is among the oldest industries in India, contributing to approximately 2.3% of the GDP, 13% of manufacturing, and is the fifth-largest apparel and textile exporter globally [1]. The industry has witnessed phenomenal expansion due to urbanization, augmenting disposable income, spectacular widening customer base, and retail penetration. One of the primary finished products in the industry is apparel, and a substantial portion of India’s domestic demand comprises products like apparel at INR 5478 billion, technical textiles at INR 1406 billion, and home furnishings totaling INR 518 billion [2]. The incredible fashion industry increases textile waste and bears terrible effects on biodiversity, the planet, and humans, compelling us to switch over to a circular economy (CE) where material use is reduced via re-using, recycling, and reproduction. Moving from a linear paradigm (take, make, use, discard) to a circular model, where waste and pollution are figured out to minimize, products and materials are designed for longer life, and natural systems to rejuvenate are now more important than ever.
Moreover, circular production encourages biodegradable and energy-efficient manufacturing and conserves raw resources [3], landfills, air pollution, and energy [4]. Kim et al. [5] identified that circular production required only a fifth of the materials and a seventh of the energy to produce a brand-new product. Additionally, it facilitated businesses to participate in ecological actions like preserving raw materials and adding value to a product. It surely provides a viable route for the Indian apparel and textiles industry, which uses an estimated 110 million tonnes of material yearly and generates more than 90 million tonnes of fashion trash that is disposed of in landfills or burned [6].
In the manufacturing of Circular Textiles Products (CTPs), waste and discarded clothing are transformed into new products by a variety of processes like sorting, dismantling, cleaning, refurbishing, replacing, and testing before being released into the market [7,8]. According to supply chain experts, such procedures fall under the category of closed-loop supply chain management. The phrase “design, control, and operations (of a system) to optimize value creation across the whole life cycle of a product with the dynamic recovery of value from multiple forms of return over time” is used to describe closed-loop supply chain management [9].
Remanufacturing is particularly common in China and other Asian nations, where laws and consumer expectations require that circular products be manufactured in a manner comparable to that of newer products [10]. However, CTPs are still in their nascent stages in India. Currently, just 1% of the material is estimated to be recycled [6]. The Indian textile and apparel industry needs urgent transformation. Indian suppliers and manufacturers stand to make considerable gains if they proactively adopt good practices and innovate through circular business models, blending towards the sustainable development goals approved by the UN in 2015.
Consumers are typically uninformed or ignorant of the remanufacturing or circular process and the resultant product, despite the fact that CTPs have been getting popular recently [11,12]. Krikke et al. [11] also pointed out that the lack of consumer knowledge and interest significantly hinders the shift from a linear economy to a circular economy. In addition, consumer decisions based on their assessments of the benefits and risks of CTPs can also help or hinder the success of the CE [10]. Hence, a suitable approach is called for to bring environmentally conscious consumers toward circular products [13], which necessitates generating awareness regarding the environmental benefits of adopting CE for their apparel needs.
Remanufacturing and recycling were the main topics of earlier research, which concentrated on supply and paid little attention to the factors affecting end-user demand [14,15,16]. As a result, the majority of earlier literature concentrated on remanufacturing and remanufactured products rather than CE and circular products (a broader concept). In addition, there are few studies, particularly in India, on circular textile products and their purchase intention among consumers, which demonstrates the research gap and suggests the need for research in the mentioned area. Muranko et al. [17] underline the importance of consumer behavior analysis in the circular business model. As a result, understanding consumers’ intentions about CTPs is unavoidable in order to build successful strategies for the production and consumption of CTPs.
The success of companies and their products depends on their customer base; hence, this paper focuses on adding to the literature concerning the consumer’s perception of Circular Textiles (CT). Though it was evident from previous research by Kumar et al. [18], Singhal et al. [19], Singhal et al. [20], Wang et al. [21], and Wang et al. [22] that several factors affect consumer’s intentions for remanufactured products, among them, perceived risk and benefits are the most frequent influencing factors. Perceived risks (PR) discourage consumers from making decisions, and perceived benefits (PB) encourage them to do so [20,23,24,25]. Additionally, past research has also proved that a customer’s Environmental Consciousness (EC) plays a crucial role in shaping their intentions for remanufactured, eco-friendly, and green products [18,26]. It is known that the perception, consciousness, and factors that affect consumers’ intentions are based on product knowledge [20,22,26]. Hence, without adequate product knowledge (PK), consumers cannot correctly contemplate a particular product’s risks and benefits. Similarly, if consumers are ignorant of the products, whether they are risky or beneficial for the environment, their consciousness towards them cannot be judged.
Therefore, the study’s objective is to consider the role of EC, PR, and PB in forecasting consumers’ purchase intention (PI) toward CTPs and evaluate the moderating role of consumers’ knowledge about CTPs. Considering this, the study aims to empirically test the direct influence of EC on PI and the indirect influence through the mediation of PR and PB while conditioning the indirect effects with the moderation of PK. Instrumenting PK as a second-stage moderator on the ‘risks-intention’ and ‘benefits-intention’ links would further deepen the insights into “how mediating effect of PR and PB differs for consumers with a high and low level of PK" (see Figure 1). The study significantly enriches the present understanding of the nexus between EC, PB, PR, PK, and PI and contributes to the literature. The following research questions are explored in accordance with the study’s stated objectives:
RQ1. 
Do environmental consciousness, perceived risks, and benefits of circular textile products influence consumers’ purchase intention?
RQ2. 
Do perceived risks and benefits mediate the linkage between environmental consciousness and purchase intention such that the direct influence of environmental consciousness on purchase intention is reduced or increased when perceived risks and benefits act as the mediator?
RQ3. 
Does the mediating effect of perceived risks and benefits between environmental consciousness and purchase intention differ at the low and high levels of product knowledge?

2. Theory and Hypotheses Development

Previous research on the market acceptability of circular products relied on one’s readiness to pay [3,27,28,29]. PI has been proposed as a new way to analyze consumer behavior in recent studies [23,30,31,32]. According to Wang et al. [32], PI augurs consumers’ buying actions. Wang et al. (2013) also identified that purchasing attitude (AT), perceived behavioral control (PBC), perceived risks (PR), perceived benefits (PB), and product knowledge (PK) all impact PI of remanufactured automobile accessories. Furthermore, Cerri et al. [33] and Nascimento et al. [34] find that EC influences people’s perceptions and PI. As a result, this study made an attempt to develop a conceptual representation that evaluates the influence of EC, PR, PB, and PK on the PI of CTPs. The current study focused on circular textiles to fulfill the goals of the CE, i.e., to optimize resource usage, with a particular emphasis on non-rural and factory waste, to generate more harmony and parity between the economic system, the environs, and the community [35]. Sustainable operations are crucial in upcoming markets, where sustainable executions related to a firm’s commercial strategies may boost business performance even during recessions [36,37].

2.1. Environmental Consciousness (EC) and Consumers’ Purchase Intention (PI)

Anderson Jr. and Cunningham [38] were the first to initiate an investigation on the consumers who are responsible environmental consumers, who are more likely to consider environmental problems while making decisions. The present study defines environmentally responsible consumers as those who want to meet their requirements while contributing to social well-being and environmental sustenance.
EC refers to elements influencing one’s proclivity to participate in eco-friendly practices [39,40]. Considering the advancements in research in the existing field and widespread information available to buyers, issues in reference to the impact of human consumption on sustainability have attracted people’s interest, including even those who were either not interested in or aware of environmental issues. EC has strengthened consumers’ PI [41,42].
EC is defined by Roberts [43] and subsequently demonstrated by Brochado et al. [44] in their study as “consumers who base their purchasing decisions on knowledge regarding negative impacts of consumer behavior on the environment”. According to Peattie and Collins [42], responsible environmental consumption is only feasible if consumers are ecologically conscious because it incorporates sustainability factors into consumer decision-making.
A study by Samarasinghe [45] on green customers recognized consumption activities as a representation of the EC of consumers to acquire, consume, and discard eco-friendly items. Thus, EC may be viewed as a factor that impacts people’s perceptions and, as a result, PI [33,34]. Individuals who purchase eco-friendly items have some amount of EC [46,47], which steers the beneath hypothesis:
H1: 
EC positively influences the PI of consumers towards CTPs.

2.2. Perceived Risks (PR) and Consumers’ Purchase Intention (PI)

PR refers to a person’s beliefs about the apprehensions regarding reliability and prospective negative repercussions of acquiring a product [22,48], including its physical performance or quality, financial and social aspects, the life of the product, etc., [49]. Circular items are fundamentally more uncertain for users than fresh products in the market, as the purchase of these products is associated with a higher level of PR due to the inclusion of unknown factors like former uses of the product, a lack of prior trials, and a lack of market recognition of the producer [21]. PR and uncertainties are considered impediments that dissuade consumers from buying circular products. Chang and Tseng [50] discovered that PR is a critical element that negatively impacts customers’ PI. Chen and Chang [51] also concluded that PR negatively influences the PI of information and technology items. According to De Medeiros et al. [52], PR is adversely related to buying intentions of circular products. After considering the above literature, we hypothesize that:
H2: 
PR negatively influence the PI of consumers toward CTPs.

2.3. Perceived Benefits (PB) and Consumers’ Purchase Intention (PI)

Consumer’s value proposition has received increased attention in research and adoption due to its significance in forecasting PI and gaining a viable market edge [53,54]. Benefits can be regarded as one of two things: (1) environmental advantages like low-energy consumption, solid or hazardous waste, etc., [55] or (2) lower pricing in comparison to fresh products [3,32]. Firms employ green production practices to minimize the harmful influence of their operations on the natural environment [12,56].
A consumer may be tempted to acquire the CTP after acknowledging the given benefits, such as low cost, incentives, and discounts [57], as the price of CTP usually falls by 40–60% in comparison to new products [58]. In order to promote sales, it has been observed that the manufacturers often allow an incentive to customers who exchange their discarded items, even though they do not fall under the take-back legislation [59]. As a result, the more significant CTPs perceive environmental and personal advantages, the greater their value and consumption. Hence, in order to investigate the impact of PB on consumers’ PI, the following hypothesis is developed:
H3: 
PB positively influences the PI of consumers toward CTPs.

2.4. Perceived Risks (PR) and Perceived Benefits (PB) as the MEDIATOR between Environmental Consciousness (EC) and Purchase Intention (PI) Relationship

PR is the apprehensions of a consumer while considering a specific purchasing activity [60]. It negatively impacts various decisions, like investing in diverse assets, entering the employment market, or purchasing any product [61]. PR varies from product to product [32] and is often investigated as a multifaceted and complex construct [32,49,62] that affects consumers’ PI. The previous literature [21,22,24,25] supports that PR negatively affects the consumers’ PI. The positive influence of constructs like a green wash, personality traits, word of mouth, green awareness, and product knowledge on PI is reduced when PR is introduced as a mediator in such relations [63,64,65,66].
On the other hand, PB is defined as a construct that quantifies the advantages of circular items in terms of reduced prices, nature’s conservation, and higher sustainable outcomes [32,57]. PB positively influence consumers’ purchase intention [19,24,32]. It is observed that when benefits play as mediators in relation to constructs like social influence, AT, and subjective norms with PI, the influence of these relationships becomes stronger [67,68].
The literature also suggests that users of circular products are influenced by ecological and financial considerations [18,41,42]. Somehow, investigations on the mediating effect of PB and PR on the relation of EC-PI are limited. Therefore, knowing the mediating effect of risk and benefits on the above relation becomes essential and interesting. Exploration in this area would surely be a unique addition to knowledge and literature. Consequently, the following hypotheses are proposed:
H4: 
PR mediates the linkage between EC and PI such that the direct influence of EC on PI is reduced when PR act as the mediator.
H5: 
PB mediates the linkage between EC and PI such that the direct influence of EC on PI is increased when PB act as the mediator.

2.5. Product Knowledge (PK) as the Moderator on the Relationships between Perceived Risks (PR), Perceived Benefits (PB), and Purchase Intention (PI)

Various researchers have confirmed the notion that PR and PB are the major determinants of PI for any individual [21,24,51,52]. PR and PB have not acted simply as direct antecedents of PI but also as a mediator between cognitive factors and PI [63,64,65,66,67], and as a moderator between cognitive and contextual factors and PI [69,70,71,72]. Earlier research has also affirmed that the perception of consumers with intense PK regarding CT is different from that of consumers without PK when it comes to PR, PB, and other cognitive and contextual factors related to products PI [19,73] and contended that consumers with a PK, when exposed to PR, its effect tend to be less negative and when exposed to PB, it gets out rightly positive [23,32,74,75]. This presumption embraces that the effect of PR would be weaker and PB would be stronger on the intention for the consumers with a higher PK compared to those with lesser PK. Hence the study hypothesizes that:
H6: 
PK moderates the direct negative relationship between PR and PI such that it gets less negative at a high level of PK.
H7: 
PK moderates the direct positive relationship between PB and PI such that it gets more positive at a high level of PK.

2.6. Conditional Mediation Effect of Perceived Risk and Benefits on the Direct Relationship between Environmental Consciousness (EC) and Purchase Intention (PI) with Product Knowledge (PK) as the Moderator

PK can be explained as an individual’s understanding of certain information (e.g., features, warranty, performance, pricing, and quality) about a particular product [23,76]. It significantly impacts customer PI and, consequently, behavior [77]. According to Hazen et al. [28], consumers of circular products are often concerned about the quality of the product, as they possess various apprehensions regarding its former life. As a result, a consumer with comprehensive knowledge could more efficiently analyze and process product-related information [75]. Literature reports that consumers who do not know about circular products consider them with inferior attributes, which limits their willingness to pay [29] and purchase decisions [26].
Conversely, consumers who are more knowledgeable have a stronger inclination to acquire them [29,30]. Hence, the more people learn about CTP and its features, the more they would buy them. Product perceptions differ among consumers with different levels of PK [78,79]. For example, Matsumoto et al. [74] manifested that PK positively affected the PI of Japanese and US consumers towards circular products. In contradiction, Wang et al. [32] revealed that PK has a negative influence on the PI of Chinese consumers regarding such items. According to Hauser and Lund’s [80] findings, enlightened consumers can comprehend that the attributes and functioning of circular products are equally good as that of new products.
Through empirical investigations and analytical modeling, it is assumed that direct and indirect relationships of PR and PB with PI will be influenced by the level of a consumer’s knowledge about the circular product. A consumer with less PK would be unaware of all the benefits and hold risk apprehensions about CTPs. Vice-versa, a consumer possessing intense PK may perceive more significant benefits and have lesser risk apprehensions. Cohesively, a consumer’s level of PK regarding CTPs would play a regulating (moderating) role in deciding the quantum of direct and indirect influence of EC on PI via intervening variables, PB and PR. How so ever; there is a paucity of studies that holds the conditional moderating effect of PK with the mediating role of PR and PB on the consciousness-intention relationship and investigates whether the mediating effect of PR and PB on the EC-PI relationship differs for consumers who have a different level (high and low) of PK. Hence, corresponding to the above literature, the study postulates the following hypotheses:
H8: 
The mediating effect of PR between EC and PI is most negative at a low level (−1 SD) of PK and least negative at a high level (+1 SD) of PK.
H9: 
The mediating effect of PB between EC and PI is least positive at a low level (−1 SD) of PK and most positive at a high level (+1 SD) of PK.

3. Material and Methods

The authors have hypothesized a conceptual framework measuring EC direct and indirect influence on respondents’ PI of CTPs via the mediating influence of PB and PR. Moreover, the study also checks for the conditional indirect effect of EC on PI (via perceived benefits and risks) at low (−1 SD) and high (+1 SD) levels of PK. Using Google Forms, an online survey was conducted to collect the data sample of 409 respondents from India’s National Capital Region (NCR) and Aligarh city. The study used SEM in AMOS v23 to test the direct and indirect effects (mediation), whereas model-14 in Process Macro was used for checking conditional indirect effects (moderated-mediation).

3.1. Questionnaire Development

Five latent constructs (viz., environmental consciousness, perceived risks, perceived benefits, product knowledge, and purchase intention) are integrated into the study’s structured questionnaire. Initially, a brief introductory passage was included in the questionnaire informing the respondent about the aims of the study and what CTPs are and how they can be helpful in conserving the environment and lead to sustainability. Further, two sections made up the questionnaire. The first section of the survey asks about the respondents’ demographic properties, awareness, and previous purchasing experience of CTPs (Yes/No). The second section comprises measurement scales (borrowed from extant literature) to measure the latent constructs. The survey instrument adopts a seven-point Likert-type scale. The questionnaire and sources of adoption for measurement scales along with their standardized loadings are mentioned in the appendix (see Appendix A).

3.2. Participants, Pilot Study, and Main Survey

The study’s online survey concentrates on educated consumers, mostly graduates and post-graduates living in Aligarh, New Delhi, and India’s National Capital Region (NCR), as it is believed that educated consumers are often more environmentally conscious and may have better knowledge of CTPs. Before conducting the main survey, we followed a two-fold piloting process to validate the survey instrument. First, the survey instrument was reviewed by eight consumers (four each from New Delhi and Aligarh), and four academicians/researchers having expertise in marketing and consumer behavior research. Their recommendations were embraced to improve and modify the language and subjective tone of the measurement items. Second, we took a sample of 87 consumers from New Delhi and Aligarh to pre-test the reliability of the questionnaire before carrying out the main survey. Following the pilot survey, the main survey was conducted in February and March 2022, adopting a systematic-random mall-intercept sampling approach. We approached every fifth customer exiting the mall. To keep the anonymity and minimal physical contact (a precautionary step due to COVID-19), we generated a QR code linking to an online questionnaire and asked the respondents to scan the QR code to access the questionnaire. As a token of gratitude, we also offered a carry bag (a CTP) to those respondents who consented to participate in the survey. The survey stretched for more than 39 days (from 22 February to 31 March), and about 600 participants scanned the QR code and consented to fill out the survey. However, we received only 467 completed surveys by the closure of the survey, i.e., the end of March 2022.

3.3. Data Preparation

The survey data collected were first put into cleaning and screening procedures. At first, the data were checked for missing cases and improper responses. Upon the examination, 16 missing cases and 23 improper responses were found, and hence they were deleted. The study also tested for statistical outliers by implementing Cook’s distance method. As per the recommendation of Pituch and Stevens [81], a response is said to be an outlier if showing Cook’s statistics above 1. Upon checking the results, 19 responses showed Cook’s statistics > 1; hence, these responses were also deleted from the dataset, and we obtained a final data sample of 409 responses. Young consumers between the ages of 20 and 30 make up the majority of responses (51.30% of the responses), justifying that Indian youth are more environmentally aware and conscientious than other age groups [82]. Table 1 displayed below exhibits the demographic properties of the respondents. We also assessed the common method variance using the full-collinearity approach following Ned Kock’s recommendation [83]. We sequentially made every latent variable an outcome variable and checked for VIF values for the rest of the variables ensuring that the VIF values are below the threshold of 3.3 [83]. The results confirmed that no variable showed a VIF value greater than 3.3 hence the data remains free from common method variance.

4. Results

4.1. Measurement Model: Fit Indices, Reliability, and Validity

After completing the data screening step, the data were processed to establish parameters of the measurement model, fit indices, convergence, and divergence through the CFA model in AMOS 23. Initially, the study instrumented five latent constructs manifesting 19 observed items. The final CFA model was made up of 19 observed items converging with their respective latent constructs with a standardized loading as low as 0.715 hence confirming the average extracted variance (AVE) for each latent construct above the threshold of 0.50 [84,85], hence, referring to enough convergence. Model fit indices (see Table 2) have been found in the excellent category concluding that the data fit the model well. Further, for establishing the reliability of the measurement scales, Cronbach’s alpha and composite reliabilities were also computed, and the statistics of both reliabilities were found well within the prescribed range (>0.70), thus, warranting the reliability of the data [84,86].
The covariance-based SEM also assumes that the data meet the criteria of divergence among the latent constructs. Fornell and Larcker’s [91] approach suggests comparing the squared root value of AVE (bold diagonal values in Table 3) of each latent construct with their bivariate correlations (off-diagonal values) with other latent constructs, and divergence is assumed to persist among the latent constructs if bold diagonal values are greater than off-diagonal values. Results from Table 3 conform with the criteria and, thus, meet the assumption of divergent validity. We also followed HTMT ratio approach to ensure discriminant validity. Table 4 confirms that HTMT ratios among latent variable are found below the threshold of 0.85. Bivariate correlations among the variables (see Table 3) conform to the study’s hypotheses, while Table 3 also evinces the descriptive statistics, mean, and standard deviation for each latent construct. Moreover, skewness and kurtosis statistics have also been reported for assuming the multivariate normality of the data. As per Kline’s recommendation [92], if skewness and kurtosis statistics are within the −1 and +1 range, the data tends to hold multivariate normality.

4.2. Direct Effects

The study proposes three hypotheses related to measuring the direct influence of EC (H1), PR (H2), and PB (H3) on PI. Table 5 manifests that EC (β = 0.413; C.R. = 5.912; S.E. = 0.070; p-value < 0.01) and PB (β = 0.389; C.R. = 4.423; S.E. = 0.046; p-value < 0.01) significantly augment the respondents’ PI towards CTPs; thus, both the hypotheses H1 and H3 stand accepted. However, the results also maintained that PR significantly reduces PI (β = −0.276; C.R. = −3.715; S.E. = 0.043; p-value < 0.01) towards the use of CTPs, resulting in acceptance of hypothesis H2.

4.3. Indirect Effects (Mediation Analysis)

The study also postulates the mediating role of PR (H4) and PB (H5) on the direct nexus between EC and PI. Indirect effects were calculated using the bias-corrected percentile method with 5000 bootstraps. The results of mediation analysis evidence that PR negatively mediates the direct influence of EC on PI (β = −0.091; S.E. = −0.021; CIs at 95% = −0.132, −0.049); hence, hypothesis H4 was accepted. Further, the results having reference to mediating effect of PB between EC and PI were also found in conformity with the hypothesis H5 (β = 0.113; S.E. = 0.024; CIs at 95% = 0.066, 0.161). The finding deduces that the direct influence of EC on PI is enhanced when PB comes in between as a mediator.

4.4. Interaction Effects (Moderation Analysis)

We proposed hypotheses H6 and H7, conceptualizing the moderating role of PK on the direct linkages of PR, and PB on PI, respectively. Hypothesis H6 advances that the negative influence of PR on PI alleviates at a high level of PK and the results are found in support of H6 (β = −0.084; S.E. = 0.116; CIs at 95% = −0.143, −0.025). Further, hypothesis H7 puts forward that the positive direct linkage between PB and PI gets even stronger at high levels of PK, and the results from Table 5 support the hypothesis H7 (β = 0.109; S.E. = 0.029; CIs at 95% = 0.052, 0.166).

4.5. Conditional Indirect Effects (Moderated-Mediation Analysis)

The authors also theorized the conditional indirect effect of EC on PI (via the mediation of PR and PB) at low (−1 SD) and high (+1 SD) levels of PK and proposed two hypotheses, H8 and H9, respectively. The study uses model−14 in Process Macro v4.0 for SPSS with a bias-corrected percentile method to measure conditional indirect effects at 5000 bootstraps [92]. Hypothesis H8 puts forward that the mediating effect of PR between EC and PI is conditioned by PK, and the indirect effect of EC on PI (via PR) is most negative when respondents perceive PK at a low level (−1 SD) and vice-versa. The results from Table 5 conform with hypothesis H8 and infer that the conditional indirect effect of EC on PI (via PR) is most negative (β = −0.139; S.E. = −0.015; CIs at 95% = −0.168, −0.110) and highly significant at low level (−1 SD) of PK, and least negative and insignificant (β = −.055; S.E. = −0.031; CIs at 95% = −0.116, 0.006) at a high level (+1 SD) of PK.
Moreover, hypothesis H9 proffers that the mediating role of PB between EC and PI is least positive at the low level (−1 SD) of PK and most positive at the high level (+1 SD) of PK. The results are found consistent with hypothesis H9 and conclude that the mediating role of PB between EC and PI gets weakest (β = 0.084; S.E. = 0.027; CIs at 95% = 0.031, 0.137) at a low level (−1 SD) of PK and strongest (β = 0.146; S.E. = 0.130; CIs at 95% = 0.109, 0.183) at a high level (+1 SD) of PK.

5. Discussion

Numerous studies have been conducted in various contexts to predict consumer PI related to remanufactured products using a variety of theories, approaches, and dimensions with cognitive, contextual, social, intellectual, economic, and demographic variables. These studies have successfully encapsulated the concept of consumer intention and behavior [19,21,22,23,93]. An investigation about the circular economy or circular products has recently gained momentum. Numerous studies have recognized the essential factors responsible for accepting circular products in different economies [94,95,96,97,98]. Among these crucial factors, PR, PB, EC, and PK are considered the most relevant ones. [20,99,100]. The present study cognized the moderated-mediating role of these factors for considering consumer’s PI towards CTPs in such a way that the influence of EC on PI with the mediating effect of PR would be weakest, and PB would be strongest for the consumers who have adequate knowledge of product and vice versa.
The study’s proposed hypotheses assumed that EC, PR, and PB would directly impact PI. The findings supported that EC (H1) and PB (H3) have a direct positive influence on consumers’ PI toward CTPs with coefficients of 0.413 and 0.389, respectively. [33,34,57,58]. In contrast, findings also supported that PR (H2) is a negative predictor of PI with a standardized coefficient of -.276, inferring that PR negatively influence consumers’ PI toward CTPs [50,52]. Signifying the positive influence of EC and PB on PI, the study infers that consumers who are conscious of the environment and presume social-economic and environmental benefits tend to possess high PI for CTPs compared to others who are unaware of CTPs and assume risks (having a negative influence). Considering the impact of EC, PB, and PR, it may be posited that people who care about the environment are inclined to change their behavior for ecological benefits [18]. Consumers will be more motivated to buy CTPs after learning about their benefits, such as low cost, incentives, discounts, or ecological sustenance [19,57].
On the contrary, it has also been discovered that consumers get disinterested and hesitate to buy CTPs when perceiving risks related to a product’s quality, safety, and durability [19]. While testing the PB and PR as an intervening variable between EC and PI, it was discovered that PB favorably influences consumer PI toward CTPs while PR adversely affects it. Although EC has a considerable direct influence on PI, the mediating effect of PB makes it much more robust and reinforcing, proving that consumers perceive both social and economic advantages in buying CTPs [67,68].
In contrast, PR has a negative mediating impact on the EC-PI relation and dampens the direct positive influence of EC on PI. Therefore, the relationship between EC and PI is weakened by risk perception, resulting in a lower chance of acquiring CTPs [19,63,65]. As a result, when CTP’s intention to purchase is examined to their EC, it can be concluded that PB and PR serve as partial mediators which support H4 and H5 of the study.
Additionally, the moderating influence of PK on PB-PI and PR-PI relations postulates that when consumers have knowledge of the CTP, they presume benefits in purchasing it. Their lack of knowledge results in risks assumption. An adequate level of knowledge strengthens the relationship between PB-PI and lessens the adverse effect of risk on the PI. In contrast, a low-level or no PK increases risk perception and weakens the PR-PI relation (see Figure 2). As a result, the negative effect of risk is amplified, and the positive influence of benefits’ is reduced [29,30,73]. The apparent interactive influence of PK on consumers supports hypotheses H6 and H7, highlighting the need for awareness initiatives and campaigns to promote CE and CTPs in India (see Figure 3).
We also postulated that the mediating effect of PR between EC and PI is the most negative at the low level of PK and the least negative at the high level of PK. Further, the mediating effect of PB between EC and PI is the least positive at the low level (−1 SD) of PK and the most positive at the high level (+1 SD) of PK. Results were found to confirm hypotheses H8 and H9 (see Figure 2), which delineate that PR and PB work as more vital mediators in establishing the relationship between EC and PI, but their effect will vary with the level of PK of consumers.
Earlier studies have tested the direct effect of EC, PB, and PR on PI and concluded that consumers’ buying intention toward remanufactured/recycled/circular products had enhanced with the increased consciousness of the environment and perceptions about the associated benefits. However, it is reduced with the increased assumption about the related risks. The current study accounts for the conditional interactive role of PK on the indirect relation between EC and PI, surmising that the indirect effect of EC on PI via PR would be most negative for the consumers with low CTP knowledge and least negative for the consumers with high CTP knowledge. The results confirm the above notion suggesting that the negative mediating effect of PR gets the most negative (β = −0.139), consequently making the direct nexus between EC and PI the most negative for consumers with low knowledge of CTPs. In contrast, the same indirect negative mediating influence of PR becomes the least negative and insignificant (β = −0.055) for consumers having a high knowledge of CTPs, thereby making the direct influence of EC on PI least negative and promising.
On the contrary, the intervening effect of PB between EC and PI becomes less influential for consumers with low-CTP knowledge (β = 0.084) compared to consumers with high-CTP knowledge (β = 0.146). This finding confirms the study’s proposed notion that a more knowledgeable consumer would perceive more benefits and fewer risks or vice-versa. This notion consequently strengthens or weakens the indirect influence of EC on PI (via PB and PR) by the moderation effect of PK.

6. Conclusions and Implications

The study of consumer buying behavior and intention is crucial for promoting a circular economy and circular products [101]. Sustainable production and consumption goals will not be achieved until consumers accept or develop PI towards circular textile products. This research develops a comprehensive theoretical model that assesses Indian consumers’ PI for CT products, with the results having implications for both theory and practice. Primarily, the research on the conditional indirect effect of EC on PI (moderated-mediated by PR and PB with the interaction of PK) significantly expands the knowledge on the direct and indirect relationship between EC and PI. Earlier studies have investigated simplistic direct and indirect effects of EC, PB, PR, and PK on PI, without accounting for the mediation of PR, PB, and moderation of PK on EC-PI relation and determined the indispensable factors influencing the PI of Indian consumers toward circular products. However, the present study supplements this notion by adding the conditional interaction effect of PK on the mediated relationships (via PB and PR) between EC and PI such that PR and PB act as mediators more strongly for the consumers who possess knowledge about the CT product than those who do not.
This study has important implications for society and the textile industry as well. Considering the results, the study recommends that nations’ CE, sustainable development goals, and pollution reduction targets can be achieved when consumers’ attitude is positively shaped toward circular and remanufactured product acceptance through the dissemination of comprehensive PK. The more knowledge consumers have about CTPs, the more they are aware of the associated social-economic and environmental benefits of adopting CTPs and their contribution toward the well-being of society thereby helping in creating a sustainable environment for society.
Further, the findings provide guidelines to the government, retail managers, and decision-making bodies in the textile industry of India for making more focused strategies for reducing textile waste and pollution and conserving virgin resources, and environmental protection by developing bylaws in favor of a circular economy and CTPs. Further, the findings also help in developing develop acquaintances and disseminating knowledge about CTPs, among the consumers, through awareness initiatives and campaigns to promote and generate awareness regarding CE and CTP.
This study provides a vision to textile managers, suppliers, manufacturers, and businesses in India and other emerging markets, where the CTP is still in the nascent stage, that they stand to make considerable gains if they proactively adopt CE in their textile manufacturing. Further, the findings also help in effective circular business strategies for creating market demand through education and awareness-raising communication campaigns, making CTP available in the market, and providing proper knowledge of the characteristics and benefits of CTP. Similarly, companies should expand the demand for CTPs comparing the quality and pricing of CTPs with the new products in the market. This strategy would help them eliminate or minimize perceived contamination risk. Hence, the study would also help managers develop strategic campaigns and policies to counter the consumer’s negative perception of CTPs.

7. Limitations and Future Research

Although the study contributes significantly to the existing literature on CE, remanufacturing, and green practices in the textile industry, there are still some limitations. A longitudinal design might result in a better understanding of the tested relationships because the study uses a cross-sectional design, which might not account for causality and may cause the perception to change over time. This study was conducted based on a sample of 409 consumers from Aligarh and the National Capital Region of India. Although the sample sizes from each area are still relatively small, the authors made an effort to maintain the heterogeneity of the data by selecting consumers from three different Indian regions: New Delhi (the country’s capital) and the National Capital Region (NCR), and Aligarh city. To generalize the results, a larger sample from each region while including more representative cities would be sufficient.
Further, this study has mainly focused on the role of EC in developing PI of consumers for CT products which is conditionally mediated by PR and PB (moderation via PK). Other cognitive variables like the price of the product, perceived quality, sustainability of the product, image, and safety may also be included in future studies. Lastly, this study has used PK as a stage-2 conditional moderator; future studies may consider applying two-staged conditional moderation taking gender as a stage-1 moderator, and investigating how the mediating influence of PR and PB varies for males and females while conditioned by low/high levels of product knowledge.

Author Contributions

Conceptualization, M.A.S. and A.C.; methodology, I.A.; data curation, R.D.; writing—original draft preparation, M.A.S. and I.A.; writing—review and editing, I.A., A.C. and S.S.; supervision, A.C. and R.D.; funding acquisition, R.D. and All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Data was anonymized, even no personal information like contact numbers or/and email addresses were solicited, so this study was exempted for ethical approval by Institutional Ethics Committee of Aligarh Muslim University.

Informed Consent Statement

Informed consent was obtained from all individual participants included in the study. Respondents were informed in advance about the theme for the questionnaire and a set of sample questions was provided to them before sending the full survey instrument.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Appendix A. Questionnaire Items with Their CFA Loadings and Source of Adoption

Construct Name and Measurement ItemCFA Loadings
Environmental Consciousness (EC)
(Source: Suki, 2016; Singhal et al., 2019 [20]; Schlegelmilch et al., 1996)
“I am willing to make extraordinary efforts to purchase circular textile products to protect the environment.”0.717
“Given a choice, I will prefer to purchase a circular textile product because it is less harmful to the environment.”0.830
“I will purchase circular textile products because it contributes towards the sustainability of the environment.”0.791
“I would prefer circular textile products over fresh textile products because it helps in limiting environmental pollution.”0.751
Perceived Risks (PR)
(Source: Singhal et al., 2019 [20]; Wang et al., 2013 [32])
“I sam afraid that the frequent maintenance of circular textile products will waste my time and money.”0.715
“I apprehend that circular textile products will have poor performance.”0.826
“I fear that the use of circular textile products might lead to skin issues/problems.”0.774
Perceived benefits (PB)
(Source: Singhal et al., 2019 [20]; Forsythe et al., 2006)
“I will buy circular textile products because of their lower price”.0.782
“I will purchase circular textile products because I will be able to buy more textile products at a low price”.0.783
“I will purchase circular textile products because they will be available at a discount”.0.818
“I will purchase circular textile products if I get an exchange offer in return for my used textiles”.0.733
Product knowledge (PK)
(Source: Michaud & Llerena, 2011 [3]; Wang et al., 2013 [32])
“I am familiar with the remanufacturing process of circular textile products”. 0.742
“I am familiar with the performance and features of circular textile products”. 0.868
“I am familiar with the price level of circular textile products”. 0.797
“I am familiar with the quality warranty of remanufactured products”. 0.853
Purchase Intention towards CTPs
(Source: Calvo-Porral & Lévy-Mangin, 2020; Singhal et al., 2019 [20])
“I will buy circular textile products in the future”.0.793
“I am likely to buy circular textile products”.0.758
“I will continue buying circular textile products”.0.781
“I am excited to buy circular textile products”.0.789

References

  1. India Brand Equity Foundation. TEXTILES AND APPAREL. 2022. Available online: https://www.ibef.org/download/1659942959_Textiles_and_Apparel-PPT-June_2022.pdf (accessed on 15 July 2022).
  2. Hari, D.; Mitra, R. Circular Textile and Apparel in India Policy Intervention Priorities and Ideas. New Delhi: Centre for Responsible Business (CRB). 2022. Available online: https://c4rb.org/wp-content/uploads/2022/04/Circular_Apparel_Status_Paper_140422.pdf (accessed on 6 July 2022).
  3. Michaud, C.; Llerena, D. Green Consumer Behaviour: An Experimental Analysis of Willingness to Pay for Remanufactured Products. Bus. Strategy Environ. 2011, 20, 408–420. [Google Scholar] [CrossRef]
  4. McConocha, D.M.; Speh, T.W. Remarketing: Commercialization of remanufacturing technology. J. Bus. Ind. Mark. 1991, 6, 23–37. [Google Scholar] [CrossRef]
  5. Kim, H.J.; Raichur, V.; Skerlos, S.J. Economic and environmental assessment of automotive remanufacturing: Alternator case study. Int. Manuf. Sci. Eng. Conf. 2008, 48517, 33–40. [Google Scholar] [CrossRef]
  6. Mehta, T. Circular Textiles: An Urgent Call for Shift. Available online: https://www.indiaretailing.com/2022/02/08/fashion/circular-textiles-an-urgent-call-for-shift/ (accessed on 18 March 2022).
  7. Steinhilper, R. Recent trends and benefits of remanufacturing: From closed loop businesses to synergetic networks. In Proceedings of the Second International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Tokyo, Japan, 11–15 December 2001; pp. 481–488. [Google Scholar] [CrossRef]
  8. Maples, G.E.; Heady, R.B.; Zhu, Z. Parts remanufacturing in the oilfield industry. Ind. Manag. Data Syst. 2005, 105, 1070–1083. [Google Scholar] [CrossRef]
  9. Guide, V.D.R., Jr.; van Wassenhove, L.N. The Evolution of Closed-Loop Supply Chain Research. Oper. Res. 2009, 57, 10–18. [Google Scholar] [CrossRef]
  10. Chen, X.; Cao, J.; Kumar, S. Government regulation and enterprise decision in China remanufacturing industry: Evidence from evolutionary game theory. Energy Ecol. Environ. 2021, 6, 148–159. [Google Scholar] [CrossRef]
  11. Krikke, H.; Hofenk, D.; Wang, Y. Revealing an invisible giant: A comprehensive survey into return practices within original (closed-loop) supply chains. Resour. Conserv. Recycl. 2013, 73, 239–250. [Google Scholar] [CrossRef]
  12. Zhu, Q.; Sarkis, J.; Lai, K.H. Supply chain-based barriers for truck-engine remanufacturing in China. Transp. Res. Part E Logist. Transp. Rev. 2014, 68, 103–117. [Google Scholar] [CrossRef]
  13. Gallaud, D.; Laperche, B. Circular Economy, Industrial Ecology and Short Supply Chain; John Wiley & Sons: Hoboken, NJ, USA, 2016. [Google Scholar]
  14. Ferguson, M.E.; Toktay, L.B. The effect of competition on recovery strategies. Prod. Oper. Manag. 2006, 15, 351–368. [Google Scholar] [CrossRef]
  15. Atasu, A.; Sarvary, M.; Van Wassenhove, L.N. Remanufacturing as a marketing strategy. Manag. Sci. 2008, 54, 1731–1746. [Google Scholar] [CrossRef] [Green Version]
  16. Jiménez-Parra, B.; Rubio-Lacoba, S.; Vicente-Molina, A. An approximation to the remanufactured electrical and electronic equipment consumer. In Proceedings of the 6th International Conference on Industrial Engineering and Industrial Management, Istanbul, Turkey, 3–6 July 2012; pp. 433–440. [Google Scholar]
  17. Muranko, Z.; Andrews, D.; Newton, E.J.; Chaer, I.; Proudman, P. The pro-circular change model (P-CCM): Proposing a framework facilitating behavioural change towards a circular economy. Resour. Conserv. Recycl. 2018, 135, 132–140. [Google Scholar] [CrossRef]
  18. Kumar, A.; Prakash, G.; Kumar, G. Does environmentally responsible purchase intention matter for consumers? A predictive sustainable model developed through an empirical study. J. Retail. Consum. Serv. 2021, 58, 102270. [Google Scholar] [CrossRef]
  19. Singhal, D.; Jena, S.K.; Tripathy, S. Factors influencing the purchase intention of consumers towards remanufactured products: A systematic review and meta-analysis. Int. J. Prod. Res. 2019, 57, 7289–7299. [Google Scholar] [CrossRef]
  20. Singhal, D.; Tripathy, S.; Jena, S.K. Acceptance of remanufactured products in the circular economy: An empirical study in India. Manag. Decis. 2019, 57, 953–970. [Google Scholar] [CrossRef]
  21. Wang, Y.; Hazen, B.; Mollenkopf, D. Consumer value considerations and adoption of remanufactured products in closed-loop supply chains. Ind. Manag. Data Syst. 2018, 118, 480–498. [Google Scholar] [CrossRef]
  22. Wang, S.; Wang, J.; Yang, F.; Li, J.; Song, J. Determinants of consumers’ remanufactured products purchase intentions: Evidence from China. Int. J. Prod. Res. 2020, 58, 2368–2383. [Google Scholar] [CrossRef]
  23. Wang, Y.; Hazen, B. Consumer product knowledge and intention to purchase remanufactured products. Int. J. Prod. Econ. 2015, 181 Pt B, 460–469. [Google Scholar] [CrossRef]
  24. Choi, J.; Lee, A.; Ok, C. The effects of consumers’ perceived risk and benefit on attitude and behavioral intention: A study of street food. J. Travel Tour. Mark. 2013, 30, 222–237. [Google Scholar] [CrossRef]
  25. Wahjudi, D.; Gan, S.; Anggono, J.; Tanoto, Y. Factors Affecting Purchase Intention of Remanufactured Short Life-Cycle Products. Int. J. Bus. Soc. 2018, 19, 415–428. [Google Scholar]
  26. Wang, Y.; Huscroft, J.R.; Hazen, B.T. and Zhang, M. Green information, green certification and consumer perceptions of remanufactured automobile parts. Resour. Conserv. Recycl. 2016, 128, 187–196. [Google Scholar] [CrossRef]
  27. Guide, V.D.R., Jr.; Li, J. The Potential for Cannibalization of New Products Sales by Remanufactured Products. Decis. Sci. J. 2010, 41, 547–572. [Google Scholar] [CrossRef]
  28. Hazen, B.T.; Overstreet, R.E.; Jones-Farmer, L.A.; Field, H.S. The role of ambiguity tolerance in consumer perception of remanufactured products. Int. J. Prod. Econ. 2012, 135, 781–790. [Google Scholar] [CrossRef]
  29. van Weelden, E.; Mugge, R.; Bakker, C. Paving the way towards circular consumption: Exploring consumer acceptance of refurbished mobile phones in the Dutch market. J. Clean. Prod. 2016, 113, 743–754. [Google Scholar] [CrossRef] [Green Version]
  30. Gaur, J.; Amini, M.; Banerjee, P.; Gupta, R. Drivers of Consumer Purchase Intentions for Remanufactured Products: A Study of Indian Consumers Relocated to the USA. Qual. Mark. Res. Int. J. 2015, 18, 30–47. [Google Scholar] [CrossRef]
  31. Jimenez-Parra, B.; Rubio, S.; Vicente-Molina, M.-A. Key drivers in the behavior of potential consumers of remanufactured products: A study on laptops in Spain. J. Clean. Prod. 2014, 85, 488–496. [Google Scholar] [CrossRef]
  32. Wang, Y.; Wiegerinck, V.; Krikke, H.; Zhang, H. Understanding the purchase intention towards remanufactured product in closed-loop supply chains: An empirical study in China. Int. J. Phys. Distrib. Logist. Manag. 2013, 43, 866–888. [Google Scholar] [CrossRef]
  33. Cerri, J.; Testa, F.; Rizzi, F. The more I care, the less I will listen to you: How information, environmental concern and ethical production influence consumers’ attitudes and the purchasing of sustainable products. J. Clean. Prod. 2018, 175, 343–353. [Google Scholar] [CrossRef]
  34. Nascimento, E.R.; Costa, M.F.; Oliveira, K.K. Persuasive communication on the internet via Youtube: Is it possible to increase environmental concern and consumer involvement with sustainability? Theory Pract. Admin 2015, 5, 1–24. [Google Scholar] [CrossRef]
  35. Ghisellini, P.; Cialani, C.; Ulgiati, S. A review on circular economy: The expected transition to a balanced interplay of environmental and economic systems. J. Clean. Prod. 2016, 114, 11–32. [Google Scholar] [CrossRef]
  36. Jabbour, C.J.C. In the eye of the storm: Exploring the introduction of environmental issues in the production function in Brazilian companies. Int. J. Prod. Res. 2010, 48, 6315–6339. [Google Scholar] [CrossRef]
  37. Seles, B.M.R.P.; de Sousa Jabbour, A.B.L.; Jabbour, C.J.C.; Latan, H.; Roubaud, D. Do environmental practices improve business performance even in an economic crisis? Extending the win-win perspective. Ecol. Econ. 2019, 163, 189–204. [Google Scholar] [CrossRef]
  38. Anderson, W.T., Jr.; Cunningham, W.H. The socially conscious consumer. J. Mark. 1972, 36, 23–31. [Google Scholar] [CrossRef] [Green Version]
  39. de Leaniz, P.M.G.; Crespo, A.H.; Lopez, R.G. Customer responses to environmentally certified hotels: The moderating effect of environmental consciousness on the formation of behavioral intentions. J. Sustain. Tour. 2018, 26, 1160–1177. [Google Scholar] [CrossRef] [Green Version]
  40. de Lima, E.B.; Costa, C.S.R.; Felix, G.R. Guilt and pride emotions and their influence on the intention of purchasing green products. Consum. Behav. Rev. 2019, 3, 70–84. [Google Scholar] [CrossRef]
  41. Kushwah, S.; Dhir, A.; Sagar, M. Ethical consumption intentions and choice behavior towards organic food. Moderation role of buying and environmental concerns. J. Clean. Prod. 2019, 236, 117519. [Google Scholar] [CrossRef]
  42. Peattie, K.; Collins, A. Guest editorial: Perspectives on sustainable consumption. Int. J. Consum. Stud. 2009, 33, 107–112. [Google Scholar] [CrossRef]
  43. Roberts, J.A. Green consumers in the 1990s: Profile and implications for advertising. J. Bus. Res. 1996, 36, 217–231. [Google Scholar] [CrossRef]
  44. Brochado, A.; Teiga, N.; Oliveira-Brochado, F. The ecological conscious consumer behaviour: Are the activists different? . Int. J. Consum. Stud. 2017, 41, 138–146. [Google Scholar] [CrossRef]
  45. Samarasinghe, R. Is social psychological model sufficient: Empirical research gaps for understanding green consumer attitudinal behavior. Int. J. Adv. Res. Manag. Soc. Sci. 2012, 1, 28–54. [Google Scholar]
  46. Aagerup, U.; Nilsson, J. Green consumer behavior: Being good or seeming good? J. Prod. Brand Manag. 2016, 25, 274–284. [Google Scholar] [CrossRef]
  47. Nuttavuthisit, K.; Thøgersen, J. The importance of consumer trust for the emergence of a market for green products: The case of organic food. J. Bus. Ethics 2017, 140, 323–337. [Google Scholar] [CrossRef]
  48. Slovic, P. Perceived risk, trust, and democracy. Risk Anal. 1993, 13, 675–682. [Google Scholar] [CrossRef] [Green Version]
  49. Grewal, D.; Gotlieb, J.; Marmorstein, H. The moderating effects of message framing and source credibility on the price-perceived risk relationship. J. Consum. Res. 1994, 21, 145–153. [Google Scholar] [CrossRef]
  50. Chang, E.C.; Tseng, Y.F. Research note: E-store image, perceived value and perceived risk. J. Bus. Res. 2013, 66, 864–870. [Google Scholar] [CrossRef]
  51. Chen, Y.S.; Chang, C.H. Greenwash and green trust: The mediation effects of green consumer confusion and green perceived risk. J. Bus. Ethics 2013, 114, 489–500. [Google Scholar] [CrossRef]
  52. De Medeiros, J.F.; Ribeiro, J.L.D.; Cortimiglia, M.N. Influence of perceived value on purchasing decisions of green products in Brazil. J. Clean. Prod. 2016, 110, 158–169. [Google Scholar] [CrossRef]
  53. Bolton, R.N.; Drew, J.H. A multistage model of customers’ assessments of service quality and value. J. Consum. Res. 1991, 17, 375–384. [Google Scholar] [CrossRef]
  54. Cronin, J.J., Jr.; Brady, M.K.; Hult, G.T.M. Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. J. Retail. 2000, 76, 193–218. [Google Scholar] [CrossRef]
  55. Abdulrahman, M.D.A.; Subramanian, N.; Liu, C.; Shu, C. Viability of remanufacturing practice: A strategic decision making framework for Chinese auto-parts companies. J. Clean. Prod. 2015, 105, 311–323. [Google Scholar] [CrossRef]
  56. Mollenkopf, D.; Stolze, H.; Tate, W.L.; Ueltschy, M. Green, lean, and global supply chains. Int. J. Phys. Distrib. Logist. Manag. 2010, 40, 14–41. [Google Scholar] [CrossRef]
  57. Govindan, K.; Shankar, K.M.; Kannan, D. Application of fuzzy analytic network process for barrier evaluation in automotive parts remanufacturing towards cleaner production–a study in an Indian scenario. J. Clean. Prod. 2016, 114, 199–213. [Google Scholar] [CrossRef]
  58. Jena, S.K.; Sarmah, S.P. Price and service co-opetiton under uncertain demand and condition of used items in a remanufacturing system. Int. J. Prod. Econ. 2016, 173, 1–21. [Google Scholar] [CrossRef]
  59. Liu, Z.; Tang, J.; Li, B. and Wang, Z. Trade-off between remanufacturing and recycling of WEEE and the environmental implication under the Chinese fund policy. J. Clean. Prod. 2017, 167, 97–109. [Google Scholar] [CrossRef]
  60. Cox, D.F.; Rich, S.U. Perceived risk and consumer decision-making—the case of telephone shopping. J. Mark. Res. 1964, 1, 32–39. [Google Scholar] [CrossRef]
  61. Guiso, L.; Paiella, M. The Role of Risk Aversion in Predicting Individual Behaviors. SSRN 608262. 2004. Available online: https://ssrn.com/abstract=608262 (accessed on 10 November 2021).
  62. Jacoby, J.; Kaplan, L.B. The Components of Perceived Risk; special volumes; Association for Consumer Research: Chicago, IL, USA, 1972; pp. 382–393. [Google Scholar]
  63. Tarabieh, S.M.Z.A. The impact of greenwash practices over green purchase intention: The mediating effects of green confusion, Green perceived risk, and green trust. Manag. Sci. Lett. 2021, 11, 451–464. [Google Scholar] [CrossRef]
  64. Wu, T.; Wu, Y.J.; Tsai, H.; Li, Y. Top management teams’ characteristics and strategic decision-making: A mediation of risk perceptions and mental models. Sustainability 2017, 9, 2265. [Google Scholar] [CrossRef] [Green Version]
  65. Zhang, J.; Xiang, P.; Zhang, R.; Chen, D.; Ren, Y. Mediating effect of risk propensity between personality traits and unsafe behavioral intention of construction workers. J. Constr. Eng. Manag. 2020, 146, 04020023. [Google Scholar] [CrossRef]
  66. Zhang, W.; Sun, L.; Wang, X.; Wu, A. The influence of AI word-of-mouth system on consumers’ purchase behaviour: The mediating effect of risk perception. Syst. Res. Behav. Sci. 2022, 39, 516–530. [Google Scholar] [CrossRef]
  67. Prabhakaran, S.; Vasantha, D.S.; Sarika, P. Effect of social influence on intention to use mobile wallet with the mediating effect of promotional benefits. J. Xi’an Univ. Archit. Technol. 2020, 12, 3003–3019. [Google Scholar]
  68. Ponnapureddy, S.; Priskin, J.; Vinzenz, F.; Wirth, W.; Ohnmacht, T. The mediating role of perceived benefits on intentions to book a sustainable hotel: A multi-group comparison of the Swiss, German and USA travel markets. J. Sustain. Tour. 2020, 28, 1290–1309. [Google Scholar] [CrossRef]
  69. Ismail, S.; Mohd Mokhtar, S.S. The Actual Purchase of Herbal Products in Malaysia: The Moderating Effect of Perceived Benefit. European Proceedings of Social & Behavioural Sciences. In Proceedings of the International Soft Science Conference, Morioka, Japan, 23–25 October 2019; 2019; pp. 83–88. [Google Scholar] [CrossRef]
  70. Saxena, C.; Baber, H.; Kumar, P. Examining the moderating effect of perceived benefits of maintaining social distance on e-learning quality during COVID-19 pandemic. J. Educ. Technol. Syst. 2021, 49, 532–554. [Google Scholar] [CrossRef]
  71. Zwikael, O.; Pathak, R.D.; Singh, G.; Ahmed, S. The moderating effect of risk on the relationship between planning and success. Int. J. Proj. Manag. 2014, 32, 435–441. [Google Scholar] [CrossRef]
  72. Gozukara, E.; Ozyer, Y.; Kocoglu, I. The Moderating Effects of Perceived Use and Perceived Risk In Online Shopping. J. Glob. Strateg. Manag. 2014, 2, 67. [Google Scholar] [CrossRef]
  73. Zhang, M.; Zhu, M.; Liu, X.; Yang, J. Why should I pay for e-books? An empirical study to investigate Chinese readers’ purchase behavioural intention in the mobile era. Electron. Libr. 2017, 35, 472–493. [Google Scholar] [CrossRef]
  74. Matsumoto, M.; Chinen, K.; Endo, H. Comparison of US and Japanese consumers’ perceptions of remanufactured auto parts. J. Ind. Ecol. 2017, 21, 966–979. [Google Scholar] [CrossRef]
  75. Lin, L.; Chen, C. The influence of the country-of-origin image, product knowledge and product involvement on consumer purchase decisions: An empirical study of insurance and catering services in Taiwan. J. Consum. Mark. 2006, 23, 248–265. [Google Scholar] [CrossRef] [Green Version]
  76. Biswas, A.; Sherrell, D.L. The influence of product knowledge and brand name on internal price standards and confidence. Psychol. Mark. 1993, 10, 31–46. [Google Scholar] [CrossRef]
  77. Chang, T.Z.; Wildt, A.R. Price, product information, and purchase intention: An empirical study. J. Acad. Mark. Sci. 1994, 22, 16–27. [Google Scholar] [CrossRef]
  78. Blair, M.E.; Innis, D.E. The effects of product knowledge on the evaluation of warranteed brands. Psychol. Mark. 1996, 13, 445–456. [Google Scholar] [CrossRef]
  79. Laroche, M.; Bergeron, J.; Goutaland, C. How intangibility affects perceived risk: The moderating role of knowledge and involvement. J. Serv. Mark. 2003, 17, 122–140. [Google Scholar] [CrossRef]
  80. Hauser, W.; Lund, R.T. The Remanufacturing Industry: Anatomy of a Giant; Department of Manufacturing Engineering; Boston University: Boston, MA, USA, 2003. [Google Scholar]
  81. Pituch, K.A.; Stevens, J.P. Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and IBM’s SPSS; Routledge: New York, NY, USA, 2015. [Google Scholar]
  82. Prakash, G.; Singh, P.; Yadav, R. Application of consumer style inventory (CSI) to predict young Indian consumer’s intention to purchase organic food products. Food Qual. Prefer. 2018, 68, 90–97. [Google Scholar] [CrossRef]
  83. Kock, N. Common method bias in PLS-SEM: A full collinearity assessment approach. Int. J. E-Collab. 2015, 11, 1–10. [Google Scholar] [CrossRef] [Green Version]
  84. Bagozzi, R.P.; Yi, Y. On the evaluation of structural equation models. J. Acad. Mark. Sci. 1988, 16, 74–94. [Google Scholar] [CrossRef]
  85. Hair, J.F.; Anderson, R.E.; Tatham, R.L.; Black, W.C. Multivariate Data Analysis; Printice Hall: Englewood Cliffs, NJ, USA, 1998. [Google Scholar]
  86. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tatham, R.L. Multivariate Data Analysis, 6th ed.; Pearson Education International: New Jersey, NY, USA, 2006. [Google Scholar]
  87. Wheaton, B.; Muthen, B.; Alwin, D.F.; Summers, G.F. Assessing reliability and stability in panel models. Sociol. Methodol. 1977, 8, 84–136. [Google Scholar] [CrossRef]
  88. Shevlin, M.; Miles, J.N.V. Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personal. Individ. Differ. 1998, 25, 85–90. [Google Scholar] [CrossRef]
  89. Hu, L.; Bentler, P.M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Modeling A Multidiscip. J. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  90. MacCallum, R.C.; Browne, M.W.; Sugawara, H.M. Power analysis and determination of sample size for covariance structure modeling. Psychol. Methods 1996, 1, 130. [Google Scholar] [CrossRef]
  91. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Market. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  92. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; Guilford Publications: New York, NY, USA, 2017. [Google Scholar]
  93. Kline, R.B. Structural Equation Modeling; Guilford: New York, NY, USA, 1998. [Google Scholar]
  94. Chen, Y.; Wang, J.; Jia, X. Refurbished or remanufactured?—An experimental study on consumer choice behavior. Front. Psychol. 2020, 11, 781. [Google Scholar] [CrossRef]
  95. Dissanayake, D.G.K.; Weerasinghe, D. Towards circular economy in fashion: Review of strategies, barriers and enablers. Circ. Econ. Sustain. 2021, 1, 25–45. [Google Scholar] [CrossRef]
  96. Gomes, G.; Moreira, N.; Ometto, A. Role of consumer mindsets, behaviour, and influencing factors in circular consumption systems: A systematic review. Sustain. Prod. Consum. 2022, 32, 1–14. [Google Scholar] [CrossRef]
  97. Kim, I.; Jung, H.; Lee, Y. Consumers’ Value and Risk Perceptions of Circular Fashion: Comparison between Secondhand, Upcycled, and Recycled Clothing. Sustainability 2021, 13, 1208. [Google Scholar] [CrossRef]
  98. Kuah, A.; Wang, P. Circular economy and consumer acceptance: An exploratory study in East and Southeast Asia. J. Clean. Prod. 2020, 247, 119097. [Google Scholar] [CrossRef]
  99. Pretner, G.; Darnall, N.; Testa, F.; Iraldo, F. Are consumers willing to pay for circular products? The role of recycled and second-hand attributes, messaging, and third-party certification. Resour. Conserv. Recycl. 2021, 175, 105888. [Google Scholar] [CrossRef]
  100. Wagner, M.M.; Heinzel, T. Human perceptions of recycled textiles and circular fashion: A systematic literature review. Sustainability 2020, 12, 10599. [Google Scholar] [CrossRef]
  101. Chaudhary, A.; Shamsi, M. Need of post-consumer textile waste management via circular economy. Int. J. Mod. Trends Sci. Technol. 2020, 6, 197–213. [Google Scholar] [CrossRef]
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Figure 1. Hypothesized Model.
Figure 1. Hypothesized Model.
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Figure 2. Two-way interaction effect of product knowledge on “PR → PI” link.
Figure 2. Two-way interaction effect of product knowledge on “PR → PI” link.
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Figure 3. Two-way interaction effect of product knowledge on “PB → PI” link.
Figure 3. Two-way interaction effect of product knowledge on “PB → PI” link.
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Table
Table 1. Respondent’s demographic profile (N = 409).
Table 1. Respondent’s demographic profile (N = 409).
Variable NameCategoryFrequencyPercentage (%)
AgeLess than 20 years5613.70
20–30 years21051.30
31–40 years8019.60
Above 40 years6315.40
GenderMale23056.20
Female17943.70
EducationUp to intermediate5613.70
Graduate20550.10
Post-graduate and above14836.20
Monthly incomeBelow ₹ 30,00022254.30
Between ₹ 30,001–60,00011227.40
Between ₹ 60,001–90,000358.60
Above ₹ 90,000409.80
Awareness of CTP?Yes26665.00
No14335.00
Purchased CTP before?Yes14735.90
No26264.10
Note: CTP = Circular textile product.
Table
Table 2. CFA model fit Indices, Alpha, CR, and AVE.
Table 2. CFA model fit Indices, Alpha, CR, and AVE.
ModelCMIN/DFGFITLICFIRMSEA
CFA Model1.8080.9530.9690.9750.045
Recommended ValueAcceptable Range [1,2,3,4]≥0.90≥0.95≥0.95<0.07
[87][88][89][89][90]
Variable NameNo of itemsAlpha (α)CRAVE
Purchase intention40.8740.8810.609
Environmental consciousness40.8420.8560.596
Perceived risks30.8250.8330.594
Perceived benefits40.8630.8710.607
Product knowledge40.8450.8510.664
Table
Table 3. Correlations, divergent validity, and descriptive statistics.
Table 3. Correlations, divergent validity, and descriptive statistics.
Variable NameMeanSDSkewnessKurtosisPIECPRPBPK
Purchase intention5.4911.126−0.2270.7560.780
Environmental
consciousness		5.7471.0980.099−0.7520.545 **0.772
Perceived risks3.9301.408−0.424−0.404−0.433 **−0.446 **0.771
Perceived benefits4.9791.323−0.6800.1510.486 **0.48 **−0.364 **0.779
Product knowledge5.4391.050−0.6920.4320.538 **0.546 **−0.405 **0.460 **0.815
Note: ** Correlations are significant at 5%. PI = Purchase intention; EC = Environmental consciousness; PR = Perceived risks; PB = Perceived benefits; PK = Product knowledge.
Table
Table 4. HTMT ratios for divergent validity.
Table 4. HTMT ratios for divergent validity.
Variable NameECPIPRPBPK
Environmental consciousness
Purchase intention0.776
Perceived risks0.1820.211
Perceived benefits0.4180.3950.212
Product knowledge0.6460.6230.1410.565
Table
Table 5. Standardized direct, indirect, conditional indirect, and moderation effect.
Table 5. Standardized direct, indirect, conditional indirect, and moderation effect.
Independent VariablesDirect EffectIndirect EffectConditional Indirect Effect
On PIOn PI
via PR		On PI via PBOn PI via PROn PI via PB
At low
PK
(−1 SD)		At high
PK
(+1 SD)		At low
PK
(−1 SD)		At high
PK
(+1 SD)
Environmental consciousness0.413 ***−0.091 **0.113**−0.139 **−0.055 NS0.084 **0.146 **
Perceived risks−0.276 ***––––––
Perceived benefits0.389 ***––––––
PR*PK (Interaction effect)−0.084 **––––––
PB*PK (Interaction effect)0.109 **––––––
R20.421––––––
Note: Standardized effects are significant at 5%, i.e., ** p < 0.05, and 1%, i.e., *** p < 0.01 level. NS: Insignificant path. PI = Purchase intention; PR = Perceived risks; PB = Perceived benefits; PK = Product knowledge.
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Shamsi, M.A.; Chaudhary, A.; Anwar, I.; Dasgupta, R.; Sharma, S. Nexus between Environmental Consciousness and Consumers’ Purchase Intention toward Circular Textile Products in India: A Moderated-Mediation Approach. Sustainability 2022, 14, 12953. https://doi.org/10.3390/su142012953

AMA Style

Shamsi MA, Chaudhary A, Anwar I, Dasgupta R, Sharma S. Nexus between Environmental Consciousness and Consumers’ Purchase Intention toward Circular Textile Products in India: A Moderated-Mediation Approach. Sustainability. 2022; 14(20):12953. https://doi.org/10.3390/su142012953

Chicago/Turabian Style

Shamsi, Mushahid Ali, Asiya Chaudhary, Imran Anwar, Rajarshi Dasgupta, and Sachin Sharma. 2022. "Nexus between Environmental Consciousness and Consumers’ Purchase Intention toward Circular Textile Products in India: A Moderated-Mediation Approach" Sustainability 14, no. 20: 12953. https://doi.org/10.3390/su142012953

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