Skip to main content

ORIGINAL RESEARCH article

Front. Commun., 01 December 2023
Sec. Advertising and Marketing Communication
Volume 8 - 2023 | https://doi.org/10.3389/fcomm.2023.1296174

The influence of key opinion leaders on consumers' purchasing intention regarding green fashion products

  • College of Policy Science, Ritsumeikan University, Ibaraki, Osaka, Japan

Using Key Opinion Leaders (KOLs) is an emerging marketing strategy to promote green fashion products. However, research on the influence of KOLs on consumers' purchase intentions for green fashion products remains insufficient. Therefore, this study investigated how KOLs gained consumer trust and affected their green purchase intentions by applying the stimulus-organism-response (SOR) framework. Based on a literature review, this study considers KOL features, including reputation, perceived fit, and production involvement, and KOL content features, including content quality, aesthetic quality, and interactive content. To empirically verify these relationships, we conducted an online survey of Vietnamese consumers. We collected four hundred valid responses and employed structural equation modeling (SEM) to test the hypotheses based on the SOR framework. Of the six latent variables, KOL's perceived fit and interactive content were positively associated with consumer trust and strengthened their intention to make green purchases. Given the limited knowledge and low awareness of organizations of green products, this study recommends leveraging KOLs as a powerful marketing method to provide consumers with a more comprehensive understanding of the benefits associated with green fashion products. Furthermore, the limited applicability of the SOR framework (two of the six latent variables were significant) reveals the need for more studies on KOLs by further testing the SOR framework in different contexts or using alternative frameworks.

1 Introduction

The overproduction and overconsumption of cheap clothing make the fashion industry and its supply chain massive contributors to climate change, waste accumulation, and air, land, and ocean pollution (Boström and Micheletti, 2016; Niinimäki et al., 2020). The fashion industry is considered to be one of the largest contributors to climate change, with approximately 10% of the world's greenhouse gas emissions, releasing 1.2 billion tons of carbon dioxide annually (Shukla, 2022). Furthermore, if the current rate is maintained, emissions are expected to increase by over 50% by 2030 (Shukla, 2022). Despite the considerable environmental impact of the fashion industry, retailers now seek low-priced products that offer design flexibility while maintaining high quality to remain competitive (Doyle et al., 2006). Therefore, fast fashion, which offers trendy items in large volumes at affordable prices and is widely accessible to customers, is becoming a prominent business model (Doyle et al., 2006). Bhardwaj and Fairhurst (2010) predicted that the influence of fast fashion would persistently shape the fashion industry and consumer behavior in clothing purchases throughout the upcoming decade.

Given the rise of fast fashion that led to a massive environmental impact, the global demand for sustainable products is emerging and is expected to be the inevitable choice of customers (Weber, 2019; Vâtâmânescu et al., 2021). The increase in the number of environmentally conscious customers has opened new markets for numerous businesses (Cherian and Jacob, 2012). This market provides lucrative opportunities for companies to meet the growing demand for sustainable products, driving innovation and promoting environmentally responsible approaches when developing eco-innovation throughout the supply chain (Paparoidamis et al., 2019). By aligning their offerings with the values and aspirations of these discerning consumers, businesses can meet the demands of the emerging market and contribute to sustainable development (Paparoidamis et al., 2019; Erzurumlu et al., 2023). As the influence of sustainability continues to permeate consumer consciousness, forward-thinking enterprises are poised to thrive by embracing environmentally friendly practices and delivering products that resonate with the evolving value of the global marketplace.

The green movement has evolved notably and has become an integral aspect of the global economy (Palevich, 2012). It encompasses a paradigm of sustainable manufacturing and collaborative supply chain practices (Palevich, 2012). This movement adopts a comprehensive approach that spans various stages, including production, storage, packaging, transportation, and distribution, and incorporates standards, technologies, and applications that are friendly to the environment and people (Palevich, 2012). As societal awareness of environmental impacts continues to grow, a recent study by Mastercard (2021), conducted in 24 countries, revealed that 58% of adults are now more aware of their environmental footprint, with an overwhelming 85% expressing their willingness to take personal action to address environmental and sustainability concerns in 2021.

Recognizing the urgent need to tackle climate change and protect the environment (Posas, 2007; Tan et al., 2021), the integration of the green movement into various sectors, including the fashion industry, is steadily gaining momentum (Kutsenkova, 2017). The adoption of green fashion products and the promotion of sustainable practices are inevitable in this industry. This movement aimed to improve the ethical treatment of workers while reducing textile waste and environmental degradation (Kutsenkova, 2017). Decelerating global production and consumption aims to cultivate a sustainable and long-term fashion industry (Kutsenkova, 2017). In recent years, a shift toward a more sustainable fashion industry has been supported by the widespread use of Internet technology (Akram et al., 2022; Ikram, 2022). For example, the rise of e-Commerce platforms and social media has allowed fashion brands to connect and reach a wider customer and promote their sustainable practices (Plantin and Daneback, 2009; Zailskaite-Jakšte and Kuvykaite, 2010; Ikram, 2022). Driven by the power of the Internet, this green movement in the fashion industry is expected to advance sustainability, transparency, and accountability in the fashion industry (Ikram, 2022).

Because of the need to support the green movement worldwide and adapt to the strong development of Internet technology, promoting green fashion products using Key Opinion Leaders (KOLs) is currently a popular marketing method (Li and Du, 2011) and a product-selling strategy (Hua et al., 2021). KOLs are the key people who have led public opinion (Valente and Pumpuang, 2007; Steensma, 2015). They can be an individual or organization with expertise and influence in any field. These people also attract numerous fans with similar tastes; therefore, they “influence the opinions, attitudes, beliefs, motivations, and behaviors of others” (Valente and Pumpuang, 2007). This word originated from research on influence conducted in the 1940s by the communication theorist Paul Lazarsfeld, who doubted the relationship between the effect of mass media and its impact on public opinion (Katz and Lazarsfeld, 1964). Concepts that are similar to KOLs (e.g., influencers and brand ambassadors) are often assimilated; however, it is essential to recognize that each actor holds distinct characteristics and plays a unique role in the implementation of marketing strategies. According to Influencity (n.d.), “influencers” encompass a broader scope than KOLs; in fact, KOLs are often considered to be a subset of influencers. Both KOLs and influencers have the ability to impact the opinions and behaviors of their audiences, but KOLs are typically recognized for their expertise and knowledge in a specific field, industry, or domain. They often provide insights that are influential in their niche. In contrast, influencers may not necessarily be experts in any specific field. Another related term that is often used in marketing is “brand ambassador.” Brand ambassadors represent and promote a specific brand or product (Rehmet and Dinnie, 2013). They often have a close relationship with the brand and work to improve the visibility, loyalty, and advocacy of the brand, using their reputation (Harris and de Chernatony, 2001; Goutam, 2013). Although KOLs and influencers can serve as brand ambassadors, not all brand ambassadors are necessarily KOLs or influencers (Rehmet and Dinnie, 2013). Therefore, while there is some overlap in the roles of KOLs and brand ambassadors, a key distinction lies in the expertise associated with KOLs (He and Jin, 2022). Notably, the standardized criteria for defining the expertise level of a KOL vary by industry, context, and individual perspectives; thus, the criteria is subjective.

In this study, wherein we focus on green fashion products, KOLs encompass a diverse group of individuals. For example, KOLs can include fashion bloggers and vloggers who offer style advice, models who use their social media presence to showcase their work, local celebrities, such as actors, singers, and TV personalities, who can significantly impact fashion trends, designers who promote their brands and collections, and sustainable fashion advocates. Influencers can also be considered as KOLs; micro-influencers with niche followings can have significant influence within specific fashion segments, and macro-influencers can have an extensive reach and influence the mass demographics (Thomala, 2023). All these individuals possess a substantial social-media following and have expertise in their respective fields.

Because KOLs have a strong influence on their fans, who are important sources of potential consumers, this suggests that their impact can have the power to influence consumers' purchase decisions, brand perception, and marketing strategies. Previous studies have shown that KOLs play a crucial role in fashion designers and brands trying to dominate the fashion industry market (Zou and Peng, 2019), contributing to brand building and brand image in the field of skincare products (Xiong et al., 2021), and affecting motivation and attitudes toward the promotion of agricultural products (Liao et al., 2021). Researchers have also explored the effectiveness of KOL collaborations in influencer marketing campaigns, highlighting their role in promoting engagement rates, reach, and returns on investment (Chen X. et al., 2020; Ge and Guo, 2022; Priyandhini et al., 2022). Businesses can choose different types of KOLs to shape consumer opinions, attitudes, and purchase decisions, based on factors such as audience size, expertise, and relevance to specific industries.

Some studies have revealed the factors that influence consumer knowledge, commitment, and general awareness of green products (Kaufmann et al., 2012; Vazifehdoust et al., 2013; Kumar and Ghodeswar, 2015). However, studies examining how KOLs influence consumers' purchase intentions toward green products remain insufficient (Joshi and Rahman, 2015). Furthermore, KOLs play a fundamental role in influencing consumer purchase behaviors (Che et al., 2017; Alotaibi et al., 2019; Qin, 2020). Despite this recognition, academic exploration of this marketing strategy remains fragmented, as highlighted by Meffert (2009) and Vrontis et al. (2021). Further research is required to understand the influence of KOLs on consumer purchases. To fill this research gap, this study investigates whether KOLs have gained customers' trust and increased their purchase intention toward green fashion products. This study has two research objectives. First, it investigates the influences of KOLs on consumers' green trust and purchase intentions. Second, it investigates how KOLs can be used as external stimuli to generate trust and purchase intention among consumers.

To attain these research objectives, this study adopts the stimulus-organism-response (SOR) framework of Mehrabian and Russell (1980), which enables a quantitative analysis of the influence of KOLs on consumer green trust and purchase intentions. An online survey was administered to Vietnamese consumers, and the collected data were analyzed using structural equation modeling (SEM), a widely adopted approach to capture consumer purchase behavior due to its ability to examine complex relationships among various influencing factors (Golob, 2003; Bollen and Noble, 2011; Carvalho and Chima, 2014).

The remainder of this paper is organized as follows. A review of the relevant literature is presented in Section 2; based on the results of this evaluation, hypotheses are developed. Section 3 introduces the research methodology used in this study, including how variables were measured and the data collected. Section 4 presents our empirical findings. Finally, Section 5 presents our conclusions.

2 Literature review and hypotheses development

This study used literature reviews to establish the characteristics of KOLs, including their features and content. Using the SOR framework, we analyzed the impact of KOL-derived factors on consumer purchasing intentions.

2.1 SOR framework

The purchasing intentions of consumers can be influenced by a wide range of elements, such as price, product availability, social conventions, brand loyalty, and the marketing strategies of manufacturers. Personal characteristics, such as emotions, habits, lifestyle, personal norms, and environmental awareness, also play a pivotal role in shaping consumers' purchasing intentions (Joshi and Rahman, 2015). The SOR framework of Mehrabian and Russell (1980) is commonly used to investigate consumers' online purchase intention and behavior, indicating that stimuli (S) can affect consumers' behavior and emotional state. Stimuli are categorized based on several attributes that affect how consumers perceive them as an internal state (Zhang and Benyoucef, 2016). The dominant organism (O) is an internal process linking stimuli to consumer responses (Zhang and Benyoucef, 2016). It comprises of the perceptual, physical, emotional, and philosophical activities of consumers (Bagozzi, 1986), with the aim of investigating their intentions. This framework suggests that humans respond to climate in three stages: exposure to an ecological stimulus (S), the formation of internal organism (O), and response (R), with R referring to humans respond to environmental stimuli. Humans are organisms that produce emotional and psychological components, as well as mood, emotions, and response-related attitudes; thus, the SOR framework has been widely used, especially to capture consumption behavior with various components (Table 1).

TABLE 1
www.frontiersin.org

Table 1. Studies using the SOR framework to address consumers' purchase intentions.

2.2 Research model

Regarding the KOL features, this study considers reputation, perceived fit, and production involvement as stimuli (S). Regarding KOL's content features, the stimuli (S) encompass content quality, aesthetic quality, and interactive content. In this study, organism (O) refers to the level of green trust, whereas response (R) represents the subsequent behavioral outcomes displayed by individuals after exposure to these stimuli (Figure 1).

FIGURE 1
www.frontiersin.org

Figure 1. Research model.

2.2.1 Green trust

Trust is a complex social phenomenon that encompasses various interactions between human and technological actors, including behavioral, social, technological, psychological, and organizational aspects (Salam et al., 2005). In the e-Commerce context, trust refers to a positive expectation and attitude toward the ability and goodwill of trading partners to fulfill their obligations (Beldad et al., 2010). Trust is widely recognized as a critical and influential factor in numerous products (Dutta and Bhat, 2016), and green products are no exception. According to Chen (2010), green trust refers to the willingness to rely on a product or service based on beliefs or consumers' positive attitudes toward the expectations derived from its credibility, benevolence, and environmental performance. The strength of consumers' beliefs in companies claiming eco-friendliness directly impacts their evaluation of and attitude toward green products (Lee et al., 2012).

One of the most important innovations in recent years has been the advent of Internet technology. This transformative technology has revolutionized the way organizations operate, offering them unprecedented opportunities to expand their services beyond the confines of traditional retail sales, commercial property, and physical stores (Baen, 2000). Internet technology has also provided organizations with a platform to connect with customers (Yerpude and Singhal, 2018), and to reach wider audiences (Plantin and Daneback, 2009; Zailskaite-Jakšte and Kuvykaite, 2010) without the barriers of time and geographical limitations. However, technical methods of building credibility and integrity are insufficient for forging enduring relationships of trust between consumers and online e-commerce businesses (Salam et al., 2005). The lack of physical clues and interactions in online environments makes it difficult to establish trust among consumers. Therefore, to address this issue and bolster confidence, using a third-party Internet-based intermediary that assumes responsibility for seamless transactions, when transacting parties cannot physically interact, has emerged as a viable solution (Atif, 2002).

KOLs present themselves as potential solutions to foster trust (Che et al., 2017; Alotaibi et al., 2019) by sharing personal experiences, providing reviews, and offering recommendations for products and services (De Veirman et al., 2017). According to Yin et al. (2019), KOLs with a substantial following have a greater capacity to influence public opinion than professionals. By acting as spokespersons for brands and products, KOLs can establish connections with consumers, bridge the gap, and instill trust in the online marketplace.

Lou and Yuan (2019) and Wang et al. (2021) studied the relationship between content features and their impact on consumer trust. Factors such as authenticity, transparency (Busser and Shulga, 2019), and credibility (Shamim and Islam, 2022) have had a notable impact on consumer trust. Consumers tend to perceive KOLs as authentic and trustworthy sources of information when deciding to purchase a product (Schwemmer and Ziewiecki, 2018). Consequently, when KOLs incorporate green messaging into their content, they foster a sense of authenticity, credibility, and transparency among consumers, strengthening their trust in the sustainability of a product.

Based on this, this study defines green trust generated by KOLs as the confidence and belief levels that consumers place in the features and content features of KOLs when purchasing green products. Green trust in this context reflects consumer perceptions that KOLs have a genuine concern for environmental issues, knowledge, and experience to provide reliable guidance and recommendations regarding green products.

2.2.2 Features of key opinion leaders (KOLs) and green trust

When defining KOLs, popularity is often a primary feature for identifying influential figures (Rapanos, 2023). However, in the virtual realm of the Internet, wherein consumers lack physical interaction with products, false advertising on online platforms is an issue. This issue underscores the importance of credibility on consumer trust (Keh and Xie, 2009; Besalú et al., 2021). Therefore, this study measures reputation as one feature of KOLs, based on their popularity and credibility.

Furthermore, the effectiveness of a product's marketing campaign is tied to how well the spokesperson's image matched the brand of the product (Zou and Peng, 2019). When the chosen spokesperson represents the brand, it creates a compelling narrative that resonates with consumers and is effective in humanizing the brand, while evoking empathy (Fleck-Dousteyssier et al., 2014). KOLs serve as brand spokespersons and brand images, and green fashion products are showcased in KOLs' uploaded content. Therefore, this study considers the variable perceived fit as a feature of KOLs that demonstrates the link and degree of relevancy between the KOLs' image and their “green posts,” both of which affect consumer trust.

Moreover, the participation of KOLs in endorsing and engaging with products is considered a pivotal factor in shaping consumer trust and behavior in the modern digital landscape (Yuan et al., 2022; Lau et al., 2023). This involvement is more than just promotional; it establishes a sense of authenticity and reliability in the eyes of consumers, through opinions, reviews, and recommendations for products. When KOLs share their personal experiences and opinions, consumers perceive it as genuine endorsements, rather than traditional advertising. Negative product reviews are more likely to be trusted and spread, but favorable reviews lead to increased brand interest and buying intentions (Xue and Zhou, 2011). Therefore, this study examined variable production involvement as a KOL feature, referring to the degree of involvement of the KOL in the recommended product.

Based on the justifications above, this study proposes the following hypotheses.

H1: Green trust is positively related to KOL's reputation.

H2: Green trust is positively related to KOL's perceived fit.

H3: Green trust is positively related to KOL's production involvement.

2.2.3 KOL's content feature and green trust

The use of KOL-created content on an e-commerce platform is a pervasive phenomenon that attracts consumers and increases product sales (Lin et al., 2020). This movement provides KOLs with an integrated platform to build their brand as a go-to resource for purchases by sharing expert knowledge with interactive materials relevant to their niche sectors (Influencity, n.d.). Compared with brand-generated commercials, influencer-produced branded content is believed to be more authentic and natural and serves as a direct connection with potential consumers (Adweek, 2015). A KOL audience varies depending on the type of KOL, but they should all share the ability to produce high-quality content and provide content based on their understanding of audience preferences to effectively engage audiences and market brands. However, Agichtein et al. (2008) stated that Internet content varies drastically from “excellent” to “abusive” or “spam,” which may be due to the increase in the availability of content and accessibility. Therefore, this study considers content quality as a feature of the content generated by KOLs, based on its value, credibility, accuracy, and adaptability to consumers' needs.

Consumers are more likely to connect with content that contains high aesthetic quality, be it a post, video, or website. Niu and Liu (2012) indicated that the aesthetic features of videos play a crucial role in distinguishing high-quality professional videos from low-quality amateur videos. Cai and Xu (2011) also highlighted the importance of aesthetic elements such as color, graphics, and website style, which can improve consumer purchasing experiences. Because the importance of aesthetic quality in consumer shopping experiences is undeniable, we examined the aesthetic quality of content as an independent variable, to determine the content features (of KOLs) that can affect consumer trust.

Finally, regarding experiential consumption, one way to effectively build genuine connections with consumers is by exploring interactive content, to encourage user participation (Labrecque, 2014). Interactive content generated by KOLs refers to content that actively engages and involves the audience, allowing them to participate, interact, and communicate in two ways with the KOL. Unlike passive content, such as text or images, interactive content encourages the audience to actively engage with KOL's content and enables them to contribute, provide feedback, or participate in various activities (Hennig-Thurau et al., 2004). Interactive content generated by KOLs can make consumers feel more involved in their engagement with the content, such as interacting with KOLs on a live stream (video) or responding to consumers' questions regarding the products in a post (picture). Moreover, with the expansion of social media platforms and e-commerce, the new source of “word of mouth,” influencer/KOL marketing, can be a way to satisfy consumers' desire for product suggestions (Hennig-Thurau et al., 2004; Labrecque, 2014). Such interactive-content features can promote consumer interaction and aid in establishing a relationship between a business and its target audience (Labrecque, 2014). Therefore, we examined different types of interactive content to assess the content quality on the Internet.

Therefore, to evaluate the characteristics of the content created by KOLs, this study investigated “content quality,” “aesthetic quality,” and “interactive content” as independent variables. Based on these justifications, we propose the following hypotheses:

H4: Green trust is positively related to KOL's content quality.

H5: Green trust is positively related to KOL's aesthetic quality.

H6: Green trust is positively related to KOL's interactive content.

2.2.4 Green trust and green purchase intention

Green purchasing is the practice of purchasing eco-friendly products and services while avoiding products that have detrimental impacts on the environment and human health (Chan, 2001). Intentions refer to factors that affect consumer motivation and behavior in the green purchasing process (Ramayah et al., 2010). Green purchase intention relates to consumers' possibilities and desire to purchase environmentally friendly products. Green trust is one factor that affect green purchase intentions (Chen and Chang, 2012). Several researchers have illustrated the positive relationship between green trust and green purchase intention. Ahmad and Zhang (2020) indicated that green trust positively affects green purchase intention in e-service quality because consumer green trust is a crucial determinant of green purchases. Dong et al. (2022) indicated that the Chinese intention to buy green agricultural products through e-commerce is affected by green trust. Existing literature indicates that consumers' intention to purchase green products is positively affected by green trust. Therefore, the following hypothesis is proposed.

H7: Green purchase intention is positively related to consumers' green trust.

3 Material and methods

3.1 Sample and questionnaire design

An online survey was conducted to collect information and evaluate the research model. The questionnaire used in the study was divided into two parts. The first part focused on demographic variables, such as gender, age, income, and the respondents' knowledge and experience about green fashion products, whereas the second part included constructs related to the impact of KOLs on participants' intentions to purchase green fashion products. Participants were asked to evaluate the influence of KOLs on their purchasing intentions, allowing the researchers to gather data on their perceptions and attitudes toward KOLs' recommendations in the context of green fashion products.

In the survey, we also provided the respondents with a definition of green fashion products: “Green fashion is similar to sustainable, slow, and eco-friendly fashion. It's part of the global sustainable fashion movement that aims to decrease the social and environmental impact of apparel production and consumption.” However, it is important to note that despite the positive attitudes toward eco-innovations and sustainability in surveys market, the market perception of green products and sustainable practices is often correlated to consumer expectations (Byrka et al., 2016). In green fashion, the goal is to mitigate the social and environmental impacts of clothing; however, there is variability in achieving environment-friendly products, which may arise from factors such as sustainable materials, energy efficiency, pollution prevention, ethical manufacturing practices, and transparent labeling (Dangelico and Pujari, 2010; Cervellon and Carey, 2011). The challenge lies in the ensuring that these products adhere to eco-friendly standards throughout their entire lifecycle.

3.2 Measurements of variables

Table 2 lists the measurement items for the latent variables. The 39 items for KOL features, KOL content features, green trust, and green purchase intention were drafted based on literature research and then modified after a pretest with a group of 29 participants to fit this study's purposes and to see if all the survey questions were understandable. We used a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) as a calculating tool for all the measurement items. One item was eliminated due to low factor loading (<0.7), as recommended by Chin (1998). The deleted item was R1 (I prefer to buy green fashion products recommended by KOLs with numerous subscribers/followers).

TABLE 2
www.frontiersin.org

Table 2. Measurement items.

3.3 Data collection and analysis

We conducted an online survey for data collection. The study population comprised of Vietnamese participants who regularly used at least one social-media platform and followed at least one Vietnamese KOL. Vietnam is a developing country, with a growing economy and rapidly changing market. Companies in such environments are increasingly utilizing KOLs as a marketing method for influencing consumer behavior and perception (Vietnam Briefing News, 2023). Furthermore, a large proportion of the Vietnamese population is actively engaged in various social-media platforms (Nguyen et al., 2020). As online surveys were conducted through social-media platforms, the demographic's high social-media usage made it convenient to access the target group for gathering data. By focusing on a demographic that is not only representative of a growing economy (with a rapidly changing market), but also heavily engaged in digital channels, we aim to provide conclusions that are applicable to similar economies or regions where online and social-media usage plays a pivotal role in consumer behavior.

Following snowball sampling, we used our accounts (Instagram, Facebook, Line, and Zalo) to invite acquaintances to participate and asked them to complete a questionnaire. As snowball sampling allows researchers to access a population that may be difficult to identify or define clearly (Naderifar et al., 2017), in this case, individuals who regularly use at least one social media platform and follow at least one Vietnamese KOL. By leveraging participant networks and referrals, snowball sampling exploited existing connections within social media and influencer communities, making it a convenient and cost-effective approach (Naderifar et al., 2017). Furthermore, this method helped overcome sampling bias by including individuals who actively engaged with social media platforms and followed Vietnamese KOLs, which could provide a more representative sample. To test these hypotheses, data were collected from March to April 2023 via an online survey. A total of 400 participants were recruited for this study. Hypotheses (Figure 1) were tested using SEM, which can effectively account for complex relationships between multiple variables and handle latent variables (Carvalho and Chima, 2014). A two-step approach was used to perform SEM analysis. First, a measurement model was used to determine the adequacy of latent variable indicators. Confirmatory factor analysis (CFA) was performed to evaluate the fit of the measurement model including factor loading, Cronbach's α, composite reliability (CR), and average variance extracted (AVE), ensuring that the observed variables adequately represented their respective latent constructs. Second, a structural model was examined to test the hypothesized relationships between the latent variables. This step allowed for the evaluation of the direct and indirect effects among KOL features, KOL content features, green trust, and green purchase intention. Several model fit indices such as the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), Incremental Fit Index (IFI), Fmin, Standardized Root Mean Square Residual (SRMR), and Normed Fit Index (NFI) were used to evaluate the overall fit of the SEM model. Furthermore, because the knowledge level of green fashion products could have a confounding effect on the relationship between green trust and green purchase intention, as indicated by previous relevant studies (e.g., Hossain et al., 2022; Sultana et al., 2022; Asif et al., 2023), we tested if the knowledge level of green fashion products (which was analyzed on a scale of 1–5, wherein 1 = No knowledge about green fashion products and 5 = Know very well about green fashion products) had a confounding effect on the relationship, by employing linear regression analysis (Pourhoseingholi et al., 2012). Data analyses were performed using R version 4.3.0 (The R Foundation, Vienna, Austria).

4 Results

4.1 Sample characteristics

Table 3 provides the sociodemographic characteristics of the sample from which the data were collected and a comparison with the Vietnamese population. According to the table, 81.25% of the respondents were under the age of 45, with 31.50% of the respondents aged 18–25, indicating a predominantly young sample. In terms of sex distribution, 28.25% were male and 71.75% were female. This disparity can be attributed to the influence of researchers' social networks on their participant selection. Almost all acquaintances who were approached to participate in the study and helped distribute the questions were female, with their genuine interest in the subject related to green fashion products, thus inadvertently contributing to the over-representation of females in the sample. Although the study sample had an over-representation of females, with respect to the population gender ratio, the work pertains to Vietnam, wherein females consume more apparel than males (Statista Market Insights., 2023). Consequently, comparing the gender ratio only with the general population may have over-emphasized the gender bias in this study. Given the Vietnamese market's largest segment is women's apparel, with a market volume of USD 3.25 billion in 2023 (Statista Market Insights., 2023), the larger representation of females in our study sample reflects the context of the Vietnamese market to a certain degree. Finally, the income levels of the respondents were relatively consistent across the different ranges, indicating a balanced distribution across income brackets. The sample of this study deviates slightly from the distribution of the Vietnamese population; notably, the income of 85% of the population ranges from VND 5,000,000 to VND 30,000,000 per month.

TABLE 3
www.frontiersin.org

Table 3. Sociodemographic characteristics of survey respondents.

Regarding the knowledge of green fashion products and their purchasing experiences with purchasing based on KOL recommendations, Table 4 reveals that approximately 33.75% of the respondents reported having no or limited knowledge of green fashion products, equal to the percentage that claimed to have a good understanding of the subject matter. Among the respondents, 32.50% stated that they had a general level of knowledge. Furthermore, 42.75% of respondents reported not purchasing green fashion products, followed by 38.50% who reported having bought green fashion products but had not yet followed a KOL's recommendations. Among the 18.75% of the respondents who demonstrated experience buying green fashion products following a KOLs' recommendations, most of the respondents had bought them <5 times.

TABLE 4
www.frontiersin.org

Table 4. Respondents' knowledge and experience about green fashion products.

4.2 Measurement model

Although the measurement items were adapted from previous studies, it was crucial to test the validity and reliability of the measurement items to test the survey instruments. The results of the four measures, including factor loadings, Cronbach's alpha, CR, and AVE, are presented in Table 5. According to Fornell and Larcker (1981), the factor loading of each variable corresponding to a topic should be greater than the threshold value of 0.7, which indicates that each potential variable is representative. The factor loading results are acceptable except for R1 (coefficient = 0.68); therefore, this factor was dropped. Furthermore, the values of Cronbach's α should be > 0.7 to verify the reliability (Bujang et al., 2018), the CR should be >0.6, and the AVE of each latent variable should be >0.5 (Awang, 2015, 2018). The results of the findings all exceeded these criteria, indicating good reliability, convergent validity, and discriminant validity, and confirming that the constructs were statistically diverse (Table 3).

TABLE 5
www.frontiersin.org

Table 5. Construct reliability and validity.

4.3 Structural model

In this study, an analysis of the SEM model was used to verify hypotheses 1–7. The findings of the research model's goodness-of-fit (GFI) indicators revealed that the GFI was acceptable, as indicated in Table 6.

TABLE 6
www.frontiersin.org

Table 6. Results of model fitness tests.

Regarding the SEM diagram and the results shown in Figure 2, it is worth noting that an R-squared (R2) value >0.2 is considered substantial and acceptable (Hair et al., 2021). In this study, the R2 values for green trust and purchase intention were 0.812 and 0.868, respectively, indicating that the SEM results were acceptable.

FIGURE 2
www.frontiersin.org

Figure 2. Results of the structural model (hypothesis testing). Solid lines represent statistically significant paths. Dotted lines represent statistically insignificant paths. Significance levels: ***p < 0.001; **p < 0.01.

The structural equation model analysis results in Table 7 indicated that a KOL's reputation did not have a significant impact on green trust (R, path coefficient = −0.298, p = 0.079); thus, H1 is not supported. KOL's perceived fit had a significantly positive impact on green trust (PF, path coefficient = 0.629, p < 0.001), supporting H2. KOL's production involvement (PI) did not have a significant impact on the green trust of the product (path coefficient = −0.021, p = 0.862); thus, H3 is not supported. The KOL content quality did not have a significant impact on green trust (CQ, path coefficient = −0.033, p = 0.691); thus, H4 is not supported. KOL's aesthetic quality did not have a significant impact on green trust (AQ, path coefficient = −0.054, p = 0.655); thus, H5 is not supported. KOL's interactive content had a significant positive direct influence on green trust (IC, path coefficient = 0.691, p < 0.001), supporting H6. Green trust had a significantly positive direct influence on green purchase intention (GT, path coefficient = 0.932, p < 0.001), supporting H7. Furthermore, the linear regression analyses revealed that the knowledge level did not present a confounding effect (Green Trust: β = 0.049, p > 0.05; Green Purchase Intention: β = 0.223, p > 0.05), indicating that the significance of H7 was not affected by the knowledge level.

TABLE 7
www.frontiersin.org

Table 7. Hypothesis testing results.

5 Discussion

Descriptive analysis demonstrates an interesting finding regarding the gap between the knowledge of green fashion products and consumer purchasing behavior. Although they have a good understanding of these products, a considerable number of respondents reported not purchasing green fashion products, indicating a gap between consumer awareness and purchase attitudes (Table 4). This finding aligns with those of Tang et al. (2014) and Vecchione et al. (2015). The difference between the stated importance of conserving the environment and the actual behavior to act refers to the green gap (Mahoney, 2011), which existed for several reasons, such as poor perceptions of quality, lack of green product availability, and brand loyalty to conventional products (Gleim and Lawson, 2014). In the case of Vietnam, the main barriers to purchasing green products identified in a previous study corresponded to the lack of information and confidence in green claims, sellers, certifications (Nguyen and Dekhili, 2019). Furthermore, factors such as high prices, limited product availability, perceived lack of trustworthiness in eco-labels, and inadequate information play a significant role in hindering consumers from making green purchases (Nguyen et al., 2017). Owing to the current situation in Vietnam and the reasons behind this green gap, utilizing KOLs as a stimulus to enhance the green trust of the product and drive consumers' intentions to make green purchases could be a viable strategy to influence the actual purchasing behaviors of consumers.

5.1 Influence of KOLs on consumers' green trust and green purchase intentions

Among the six features of KOLs and KOLs' content, only perceived fit (H2) and interactive content (H6) were positively related to consumer green trust, thereby strengthening respondents' intention to make green purchases (H7), as shown in Table 7.

Therefore, the empirical findings of this study exhibit limited applicability of the SOR framework to the influence of KOLs on Vietnamese consumers' green purchase intentions. Previous studies have demonstrated mixed findings regarding the applicability of SOR findings when applying this framework to different products and mediating mechanisms (organisms), highlighting the influence of KOLs on purchase intention (Mohd Suki, 2016; Zhang R. et al., 2023). The effectiveness of the SOR framework in explaining the influence of KOLs on consumer purchase intentions depends on the products and mediating mechanisms (Gong et al., 2022; Zhang R. et al., 2023).

Zhang R. et al. (2023) investigated the impact of virtual and real KOLs on consumers' purchase intentions for search and experience goods using the SOR framework. These results indicate notable similarities with our findings on the influence of KOLs on consumer purchase intentions. Both studies underscore the role of KOLs in shaping consumer purchase intentions, highlighting the need for companies to use KOLs to recommend their products. Furthermore, both studies show a positive mediating function of trust in the KOL-consumer relationship. However, Zhang R. et al. (2023) showed that there were significant differences between KOLs' influences on purchase intention in different product types, considering different mediating mechanisms; that is, perceived trust was significantly mediated in the generation of purchase intentions for experiential products but not for search products, in which the results differed from our study. In our study, green fashion products (e.g., clothing, footwear, and accessories) can be categorized as search goods in terms of quality and applicability, which can be objectively assessed based on the information-searching behavior before purchase, with a low degree of information asymmetry (Zhang R. et al., 2023). However, green products can also be considered as experience goods due to the necessity of subjective post-use experiences for quality assessment (Zhang R. et al., 2023). Because green products often involve considerations related to their environmental impact, durability, and long-term benefits, consumers may not have enough information to accurately assess their quality, engaging them in a sensory and ethical exploration that extends beyond mere evaluability. These differences in the characteristics of green fashion products transcend the definitions of either search or experiential goods experimented with by Zhang R. et al. (2023), thus extending the application of the SOR framework to a KOL's influence on purchase intentions regarding green products.

Gong et al. (2022) highlighted the significance of both KOL and content features in shaping purchase intention within short video platforms using the SOR framework. Although both studies shared the same hypotheses on the influence of KOL features on purchase intention, the results were different. In contrast to the findings of Gong et al. (2022), in which reputation (H1) and perceived fit (H2) were statistically significant and positively correlated with purchase intention, our research demonstrates a different outcome, in which only perceived fit (H2) exhibits a statistically significant positive relationship with purchase intention. Furthermore, in terms of content features, whereas our study primarily mentioned KOL's generated content features and their impact on green purchase intention, Gong et al. (2022) introduced content features in the context of short video platforms (aesthetic quality and content richness), which were omitted in our study. Furthermore, it is crucial to emphasize that, as the central focus of Gong et al. (2022) is general purchase intention, our study specifically targets the purchase intention of green products.

Because our findings demonstrate the limited applicability of the SOR framework, further studies are needed required for to identifying the factors that influence the relationship between KOLs and green purchase intentions in different research contexts, for example, considering different products and mediating mechanisms by exploring these factors using the SOR framework in other contexts than Vietnam, while exploring alternative theoretical frameworks.

Green trust is not related to KOL's reputation (H1). This result contrasts with the conclusions of Einwiller (2003) and Gong et al. (2022), who emphasize the role of reputation in strengthening trust when making a purchase decision. A possible explanation for the lack of significance in this study could refer to the “green” factor of products, where the relationship between KOL's reputation and green trust can differ from that in another context. Trust in green products is demonstrated to depend on green attribute transparency (Deng and Yang, 2021), where tangible proof of their environmental benefits is highlighted; therefore, depending on a KOL's reputation alone does not always provide this proof. Consumers may seek specific information, such as sustainable material usage, reduction in carbon footprint, or ethical sourcing, before trusting the green claims and depending solely on the reputation of the KOL. For example, a prevalent issue in contemporary green product advertising is greenwashing, the practice of exaggerating or falsely claiming environmentally friendly attributes in marketing and advertising (de Freitas Netto et al., 2020). Consumers are often skeptical about green products due to the prevalence of greenwashing (Aji and Sutikno, 2015). A good reputation among KOLs alone may not be sufficient to convince consumers of a brand's genuine commitment to sustainability. They may require more concrete evidence, such as third-party certifications or transparent sustainability practices. Therefore, brands must back up their reputations with verifiable data and certifications and actual evidence of sustainability, as well as focus on post-use experiences in the context of green products and sustainability.

Green trust is positively related to KOL's perceived fit (H2). This indicates that the degree of relevance and matching between KOLs' image, temperament, style, content atmosphere, recommended products, and green intention to purchase have a strong relationship. This result is consistent with that of Putri and Agus (2019) and Gong et al. (2022). Followers often identify with KOLs and aspire to adopt their lifestyles, values, and choices. When KOLs demonstrate a perceived fit with green products, followers perceive them as congruent with the desired image or identity they associate with the KOL. This identification and aspiration drive followers to align their consumption choices with a KOL's endorsement, results in a higher intention to purchase green products. The results also demonstrate that achieving a good fit between a KOL's image and the recommended products will lead to higher purchase intention among consumers.

Green trust is not related to KOL's production involvement (H3), although a previous study revealed a favorable effect on consumer trust in a previous study (Fledderus et al., 2013). One explanation for the lack of significance in this finding could be attributed to the Vietnamese context, where the mainstreaming of social media platforms has indeed contributed to the rise of KOLs and their self-proclaimed status (Báo Công an Nhân dân diên tu˙, 2022). With the widespread accessibility of social media and its ability to reach audiences, individuals have established themselves as authorities or experts in specific fields. They create content that resonates with their audience and, over time, amass dedicated followers who trust and value their opinions. However, not all self-proclaimed KOLs necessarily possess the expertise or qualifications they claim to possess. The ease of creating an online presence and the lack of stringent verification processes on social media platforms can lead individuals to exaggerate their qualifications or knowledge to gain credibility and followers. Consequently, some self-proclaimed KOLs may lack the necessary expertise, or individuals claiming expertise in their purported fields may pose a significant challenge to consumers in discerning genuine and reliable sources of information, ultimately resulting in a lack of trust. Therefore, consumers may become skeptical and hesitant to accept recommendations or guidance from KOLs, regardless of their authenticity or actual expertise, leading to the diminished importance of production involvement by KOLs. Furthermore, knowledge of green fashion products can be perceived as complex (Niinimäki, 2011). In such cases, the reputation and perceived fit of KOLs could play a crucial role in fostering a sense of reliability among consumers when promoting trust in green products, thus diminishing the importance of KOL's production involvement in recommending these products.

Green trust was not related to content quality (H4) or aesthetic quality (H5), although it had been found to have a favorable effect on consumer trust in a previous study by Gong et al. (2022). The absence of significance in this finding may be because consumers' knowledge regarding green fashion products is still limited and superficial, with a lack of in-depth understanding and low awareness of organizations that promote green products (Cherian and Jacob, 2012). This also applies to the study's research population, where the number of respondents who reported having no, little, or general knowledge of green fashion products was 6.00, 27.75, and 32.50%, respectively, accounting for 66.25% of the survey respondents. Consequently, the quality of the presented content may not have a significant impact on consumer trust, despite its importance. Furthermore, the lack of importance of aesthetic quality on consumers' green trust of consumers could be attributed to factors such as subjectivity (as consumers have diverse tastes and preferences, relying solely on aesthetic factors may not necessarily build trust universally) and our perception of substance (as consumers prioritize substance over style for building trust). Although aesthetics can initially attract attention, consumers ultimately consider the value, quality, and reliability of information of products or services, which affects their purchasing intentions (Chang and Wildt, 1994; Tsiotsou, 2006). If an offering lacks these essential elements, aesthetic appeal alone is unlikely to foster trust. This indicates a potential gap between the perceived importance of content and aesthetic quality and their actual influence on purchase intentions in the context of green fashion products. Therefore, future research should further investigate the influence of KOLs' content and aesthetic qualities on consumers' green purchase intentions. Understanding how these specific attributes of KOL-generated content affect consumers' decisions to embrace green products can provide valuable insights for businesses and marketers.

Green trust is positively related to KOL's interactive content (H6). Although previous studies mentioned the importance of interactive marketing (Haeckel, 1998; Wibowo et al., 2021) and its effects on customer satisfaction and loyalty (Aslam et al., 2015), there is insufficient research confirming the impact of interactive content on customer purchasing behaviors. The empirical findings of this study show that interactive content allows KOLs to interact effectively with consumers and create genuine connections with a sense of satisfaction and contentment by demonstrating their knowledge, expertise, and authenticity in real-time interactions, thus establishing a higher level of credibility and trustworthiness in green fashion products. Furthermore, advertising in interactive formats leads to a higher consumer attitude toward and higher intentions (Shen et al., 2015). Through interactive formats, such as live streaming (Lyu et al., 2022) and SNS (e.g., Instagram or Facebook) story features, KOLs can create question-and-answer sessions, multiple-choice, and so on, which can create two-way direct communication (Wibowo et al., 2021). Using these features, KOLs can address specific questions, clarify doubts, and provide in-depth explanations of the environmental benefits, features, and sustainability aspects of products by sharing personal experiences, providing reviews, and offering recommendations for products and services (De Veirman et al., 2017). This can improve information processing and facilitate a better understanding of green products, leading to higher levels of green trust and greater purchase intention. Emotional connection is a crucial element of social media settings that affect consumer attitudes and purchase intentions (Sheth and Kim, 2017). Given the characteristics of interactive content, KOLs can foster a sense of emotional connection with their customers, actively engage and involve their followers, and create a more personalized and relatable experience. This emotional connection and identification with KOL's features (reputation and perceived fit) can strengthen followers' trust in KOL's recommendations and opinions regarding green products. Consequently, green purchase intentions are positively influenced.

Green purchase intention is positively related to consumers' green trust (H7). This aligns with the conclusions drawn by Ahmad and Zhang (2020) and Dong et al. (2022), who show that consumers' green trust is a critical determinant of green purchase intention. The results also emphasize the role of promoting green purchase intentions in the online context by choosing KOLs as a marketing strategy to promote sustainable fashion consumption and foster a more environmentally conscious society.

5.2 Policy implications

Our study revealed that the use of KOL and content features can foster green trust and subsequently influence intentions to purchase green products. Therefore, when using KOL as a marketing strategy, green fashion product enterprises should pay special attention to KOL's perceived fit and interactive content because the linkage between KOL's image and their green-posted content, and the interactions in content between KOLs and consumers were related to KOL's influence on green purchase intention.

KOLs can enhance their strong perceived fit with green fashion products by aligning their values with sustainability and engaging in interactive content that fosters meaningful interactions with customers. Through KOL's recommendations, consumers can not only increase their trust in products but also enhance their understanding of the environmental value of green fashion products. By strategically leveraging KOL's features and content features, green fashion enterprises can use the power of influencer marketing to drive positive consumer behavior toward sustainable choices.

It is crucial to note that consumers' knowledge of green products remains limited and superficial, with a lack of green knowledge and low awareness of green product organizations (Cherian and Jacob, 2012; James and Montgomery, 2017). Consequently, when consumers face decision-making situations, especially when purchasing green products, a lack of trust can diminish their willingness to purchase green products. To address this issue, recommendations should take advantage of KOLs to provide consumers with a more comprehensive understanding of the benefits of green fashion products. For example, KOLs and green manufacturing companies must work collaboratively to foster consistent, positive, and multi-frequent green consumption through well-orchestrated KOL participation. To ensure ethical practices, a robust punishment mechanism should be established to address instances of “misleading” marketing in which KOLs disseminate inaccurate information, for example, about the accuracy of environmental claims in advertisements, along with information on product packaging (Polonsky et al., 1998).

5.3 Limitations and future research topics

This study has limitations. First, it examines how the KOL recommendations shape green buying intentions. However, there is a gap between buying intentions and actual behavior (Tang et al., 2014; Vecchione et al., 2015; ElHaffar et al., 2020). Second, the purchase of green products involves complicated psychological and behavioral interactions influenced by several variables, including price, quality, product brands, and the level of consumers' environmental concerns (Sheikh et al., 2014; Joshi and Rahman, 2015; Chen Y. S. et al., 2020). However, these aspects were not covered in this study due to model and variable restrictions.

Future research could pursue the following: First, research can investigate other variables relevant to green products in the empirical analytical model by varying the price, quality, product brands, level of consumer environmental concern, and so on. Second, the green consumption behavior generated by KOLs can be compared with the green purchasing behavior by other marketing methods, such as traditional marketing channels. Thus, one can find more efficient ways to encourage green product purchases. Third, future studies can adopt a more comprehensive approach than SOR to understand the complexities of KOLs' influence on sustainable consumer behavior, by exploring the impacts of KOLs beyond Vietnam and investigating in different cultural contexts; for example, future studies can consider environmental awareness and consumer preferences. This will help in promoting the understanding of whether the influence of KOLs on green purchase intentions is universal, or if it varies across cultures. Fourth, integrating other theoretical frameworks with the SOR framework can provide a more comprehensive understanding of how KOLs impact consumer behavior toward sustainable consumption. For example, future studies can apply the Theory of Planned Behavior (TPB) and further extend the TPB to investigate KOLs' impact on consumer attitude, subject norm, and perceived behavioral control, while considering additional constructs, such as perceived value and the customers' willingness to pay a premium, to measure its appropriateness in determining consumer purchase intention and behavior toward green products (Yadav and Pathak, 2017). Furthermore, future studies can consider the Social Identity Theory to explore how social identities can impact an individual's behavior and attitude (Sierra and McQuitty, 2007). By applying this theory and carrying out further analyses, scholars can explore the social dimensions of how KOLs can cultivate a sense of belonging and identification and promote sustainable consumption practices. This approach can provide insights into the intricate dynamics of the context. Fifth, in the realm of promoting sustainable consumption, future studies should fill the gap between buying intentions and actual consumer behavior toward the purchase of green products, by investigating psychological dimensions, such as self-cognition and self-awareness, that influences consumer intentions. Sixth, to address the issue of gender bias, future studies should develop a design that considers a gender ratio that aligns with the market consumption patterns, with the representative sample of male and female participants reflecting the actual distribution of consumers in the market. This approach can provide a more accurate and comprehensive perspective on the subject, thus, enhancing the overall validity and generalizability of the findings.

Previous studies examined the correlation between the educational levels and green purchasing behaviors of customers (Zhao et al., 2014; Goh and Wahid, 2015; Witek and Kuzniar, 2021), emphasizing its relevance in understanding consumer behavior in the context of green purchase. Therefore, future studies could further explore the relationship between the educational levels and green purchasing behaviors of customers under the influences of KOLs, to gain a more comprehensive understanding of the market.

Future studies should also consider incorporating qualitative methods to provide a more comprehensive perspective on social-media marketing. This approach can provide valuable insights into the reasons behind consumer behaviors and attitudes, while offering an in-depth understanding of the complex dynamics involved in the adoption of green products and the impact of KOL endorsements. Previous studies demonstrate the effectiveness of integrating both quantitative and qualitative analyses methods. For example, Zou and Peng (2019) carried out a quantitative analysis based on the survey and a qualitative analysis based on three focus groups (from interviews), to investigate the influence of KOLs on the Chinese fashion market. By incorporating qualitative analyses methods, future investigations can acknowledge the complexities of consumer behavior and KOL influence.

Notably, our study did not consider certain factors related to participants' lifestyle and generation, known to influence the consumer purchasing intention toward green products. For instance, “sustainability” often aligns with a specific lifestyle (Evans and Abrahamse, 2009), suggesting that consumers who follow sustainable lifestyles are likely to make more informed and conscious choices. Furthermore, Generation Z and Millennials are generally considered to be an environmentally conscious group and are knowledgeable on sustainable living than previous generations (Su et al., 2019), thus, highlighting the importance of consumer age in such surveys.

6 Conclusion

This study aimed to fill a research gap by examining the features of KOLs that influence consumer trust and their purchase intentions toward green fashion products. This study provides valuable information for marketers, brands, and policy makers looking to leverage KOLs as an influential marketing strategy to promote sustainable consumption and foster a more environmentally conscious society. KOLs and their generated content serve as tools for building green trust, which can positively influence consumers' intentions to adopt more sustainable practices and make environmentally conscious purchase decisions. Through an analysis of the influence of KOLs on consumer purchase intention in Vietnam, this study contributes to more targeted and impactful marketing strategies that aim to promote green fashion consumption.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

Ethical approval was not required for the study involving human participants in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants in accordance with the national legislation and the institutional requirements.

Author contributions

KT: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Visualization, Writing—original draft. TU: Funding acquisition, Project administration, Software, Supervision, Writing—review & editing.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Ritsumeikan University.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcomm.2023.1296174/full#supplementary-material

References

Adweek (2015). 10 Reasons why influencer marketing is the next big thing. Available online at: https://www.adweek.com/performance-marketing/10-reasons-why-influencer-marketing-is-the-next-big-thing/ (accessed on September 8, 2023).

Google Scholar

Agichtein, E., Castillo, C., Donato, D., Gionis, A., and Mishne, G. (2008). “Finding high-quality content in social media,” in WSDM'08 - Proceedings of the 2008 International Conference on Web Search and Data Mining. doi: 10.1145/1341531.1341557

CrossRef Full Text | Google Scholar

Ahmad, W., and Zhang, Q. (2020). Green purchase intention: Effects of electronic service quality and customer green psychology. J. Clean. Prod. 267, 122053. doi: 10.1016/j.jclepro.2020.122053

CrossRef Full Text | Google Scholar

Aji, H. M., and Sutikno, B. (2015). The extended consequence of greenwashing: perceived consumer skepticism. Int. J. Bus. Inf. 10, 433.

Google Scholar

Akram, S. V., Malik, P. K., Singh, R., Gehlot, A., Juyal, A., and Ghafoor Shrestha, S. (2022). Implementation of digitalized technologies for fashion industry 4.0: opportunities and challenges. Scient. Progr. 2022, 7523246. doi: 10.1155/2022/7523246

CrossRef Full Text | Google Scholar

Alotaibi, T. S., Alkhathlan, A. A., and Alzeer, S. S. (2019). Instagram shopping in Saudi Arabia: what influences consumer trust and purchase decisions? Int. J. Adv. Comput. Sci. Applic. 10, 1181. doi: 10.14569/IJACSA.2019.0101181

CrossRef Full Text | Google Scholar

Asif, M. H., Zhongfu, T., Irfan, M., and Işik, C. (2023). Do environmental knowledge and green trust matter for purchase intention of eco-friendly home appliances? An application of extended theory of planned behavior. Environ. Sci. Pollut. Res. 30, 37762–37774. doi: 10.1007/s11356-022-24899-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Aslam, T., Hamid, K., and Arshad, M. S. (2015). The effects of interactive marketing, customer satisfaction and flashes on customer loyalty. EuroEconomica. 34, 27–38.

Google Scholar

Atif, Y. (2002). Building trust in e-commerce. IEEE Internet Comput. 6, 978365. doi: 10.1109/4236.978365

CrossRef Full Text | Google Scholar

Awang, P. (2018). Pendekatan Mudah SEM (Structural Equation Modeling). Selangor: MPWS Rich Resources.

Google Scholar

Awang, Z. (2015). SEM Made Simple: A Gentle Approach to Learning Structural Equation Modelling. Selangor: MPWS Rich Resources.

Google Scholar

Baen, J. (2000). The effects of technology on retail sales, commercial property values and percentage rents. J. Real Estate Portf. Manag. 6, 607. doi: 10.1080/10835547.2000.12089607

CrossRef Full Text | Google Scholar

Bagozzi, R. P. (1986). Attitude formation under the theory of reasoned action and a purposeful behaviour reformulation. Br. J. Soc. Psychol. 25, 95–107. doi: 10.1111/j.2044-8309.1986.tb00708.x

CrossRef Full Text | Google Scholar

Báo Công an Nhân dân diên tu˙ (2022). Bài 1: Kols và Nhũng Măt Trái (Article 1: Kols and Their Downsides). Báo Công an Nhân dân diên tuú.

Google Scholar

Beldad, A., De Jong, M., and Steehouder, M. (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Comput. Hum. Behav. 26, 13. doi: 10.1016/j.chb.2010.03.013

CrossRef Full Text | Google Scholar

Besalú, R., Pont-Sorribes, C., and Martí, A. (2021). Perceived credibility of tweets by opinion leaders during the COVID-19 pandemic in Spain. Int. J. Commun. 15, 5158–5185.

Google Scholar

Bhardwaj, V., and Fairhurst, A. (2010). Fast fashion: Response to changes in the fashion industry. Int. Rev. Retail Distr. Consumer Res. 20, 165–173. doi: 10.1080/09593960903498300

CrossRef Full Text | Google Scholar

Bollen, K. A., and Noble, M. D. (2011). Structural equation models and the quantification of behavior. Proc. Nat. Acad. Sci. USA. 108, 15639–15646. doi: 10.1073/pnas.1010661108

PubMed Abstract | CrossRef Full Text | Google Scholar

Boström, M., and Micheletti, M. (2016). Introducing the sustainability challenge of textiles and clothing. J. Cons. Policy 39, 367–375. doi: 10.1007/s10603-016-9336-6

CrossRef Full Text | Google Scholar

Bujang, M. A., Omar, E. D., and Baharum, N. A. (2018). A review on sample size determination for cronbach's alpha test: a simple guide for researchers. Malaysian J. Med. Sci. 25, 9. doi: 10.21315/mjms2018.25.6.9

PubMed Abstract | CrossRef Full Text | Google Scholar

Busser, J. A., and Shulga, L. V. (2019). Involvement in consumer-generated advertising: effects of organizational transparency and brand authenticity on loyalty and trust. Int. J. Contemp. Hospit. Manage. 31, 685. doi: 10.1108/IJCHM-10-2017-0685

CrossRef Full Text | Google Scholar

Byrka, K., Jedrzejewski, A., Sznajd-Weron, K., and Weron, R. (2016). Difficulty is critical: the importance of social factors in modeling diffusion of green products and practices. Renew. Sustain. Energy Rev. 62, 63. doi: 10.1016/j.rser.2016.04.063

CrossRef Full Text | Google Scholar

Cai, S., and Xu, Y. (2011). Designing not just for pleasure: effects of web site aesthetics on consumer shopping value. Int. J. Electr. Comm. 15, 405. doi: 10.2753/JEC1086-4415150405

CrossRef Full Text | Google Scholar

Carvalho, de, J., and Chima, O. F. (2014). Applications of structural equation modeling in social sciences research. Am. Int. J. Contemp. Res. 4, 6–11.

Google Scholar

Cervellon, M. C., and Carey, L. (2011). Consumers' perceptions of'green': Why and how consumers use eco-fashion and green beauty products. Crit. Stud. Fashion Beauty 2, 117–138. doi: 10.1386/csfb.2.1-2.117_1

CrossRef Full Text | Google Scholar

Chan, R. Y. K. (2001). Determinants of Chinese consumers' green purchase behavior. Psychol. Market. 18, 1013. doi: 10.1002/mar.1013

CrossRef Full Text | Google Scholar

Chang, T. Z., and Wildt, A. R. (1994). Price, product information, and purchase intention: an empirical study. J. Acad. Market. Sci. 22, 1002. doi: 10.1177/0092070394221002

CrossRef Full Text | Google Scholar

Che, J. W. S., Cheung, C. M. K., and Thadani, D. R. (2017). “Consumer purchase decision in Instagram stores: The role of consumer trust,” in Proceedings of the Annual Hawaii International Conference on System Sciences. doi: 10.24251/HICSS.2017.004

CrossRef Full Text | Google Scholar

Chen, X., Ji, L., Jiang, L., Miao, S., and Shi, C. (2020). More bang for your buck: Effective KOL marketing campaign in emerging short-video markets. SSRN Electr. J. doi: 10.2139/ssrn.3655819

CrossRef Full Text | Google Scholar

Chen, Y. S. (2010). The drivers of green brand equity: green brand image, green satisfaction, and green trust. J. Bus. Ethics 93, 307–319. doi: 10.1007/s10551-009-0223-9

CrossRef Full Text | Google Scholar

Chen, Y. S., and Chang, C. H. (2012). Enhance green purchase intentions: The roles of green perceived value, green perceived risk, and green trust. Manage. Decis. 50, 502–520. doi: 10.1108/00251741211216250

CrossRef Full Text | Google Scholar

Chen, Y. S., Huang, A. F., Wang, T. Y., and Chen, Y. R. (2020). Greenwash and green purchase behaviour: the mediation of green brand image and green brand loyalty. Total Quality Manag. Bus. Excell. 31, 194–209. doi: 10.1080/14783363.2018.1426450

CrossRef Full Text | Google Scholar

Cherian, J., and Jacob, J. (2012). Green marketing: a study of consumers' attitude towards environment friendly products. Asian Soc. Sci. 8, 117. doi: 10.5539/ass.v8n12p117

CrossRef Full Text | Google Scholar

Chin, W. W. (1998). The partial least squares approach to structural equation modelling. Mod. Methods Bus. Res. 295, 295–336.

Google Scholar

Clement, M., Proppe, D., and Rott, A. (2007). Do critics make bestsellers? Opinion leaders and the success of books. J. Media Econ. 20, 77–105. doi: 10.1080/08997760701193720

CrossRef Full Text | Google Scholar

Dangelico, R. M., and Pujari, D. (2010). Mainstreaming green product innovation: Why and how companies integrate environmental sustainability. J. Bus. Ethics 95, 471–486. doi: 10.1007/s10551-010-0434-0

CrossRef Full Text | Google Scholar

de Freitas Netto, S. V., Sobral, M. F. F., Ribeiro, A. R. B., and Soares, G. R. D. L. (2020). Concepts and forms of greenwashing: a systematic review. Environ. Sci. Eur. 32, 1–12. doi: 10.1186/s12302-020-0300-3

CrossRef Full Text | Google Scholar

De Veirman, M., Cauberghe, V., and Hudders, L. (2017). Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude. Int. J. Advert. 36, 1348035. doi: 10.1080/02650487.2017.1348035

CrossRef Full Text | Google Scholar

Deng, Y. Y., and Yang, Y. C. (2021). Exploring the role of green attributes transparency influencing green customer citizenship behavior. Br. Food J. 124, 223. doi: 10.1108/BFJ-03-2021-0223

CrossRef Full Text | Google Scholar

Dom, S. M. S. M., Ramli, H. S. B., Chin, A. L. L., and Fern, T. T. (2016). Determinants of the effectiveness of celebrity endorsement in advertisement. J. Dev. Areas 50, 33. doi: 10.1353/jda.2016.0033

CrossRef Full Text | Google Scholar

Dong, X., Zhao, H., and Li, T. (2022). The role of live-streaming e-commerce on consumers' purchasing intention regarding green agricultural products. Sustainability 14, 374. doi: 10.3390/su14074374

CrossRef Full Text | Google Scholar

Doyle, S. A., Moore, C. M., and Morgan, L. (2006). Supplier management in fast moving fashion retailing. J. Fashion Market. Manag. 10, 272–281. doi: 10.1108/13612020610679268

CrossRef Full Text | Google Scholar

Dutta, N., and Bhat, A. (2016). Exploring the effect of store characteristics and interpersonal trust on purchase intention in the context of online social media marketing. J. Int. Comm. 15, 239–273. doi: 10.1080/15332861.2016.1191053

CrossRef Full Text | Google Scholar

Einwiller, S. (2003). When reputation engenders trust: an empirical investigation in business-to-consumer electronic commerce. Electr. Markets 13, 196–209. doi: 10.1080/1019678032000092246

CrossRef Full Text | Google Scholar

ElHaffar, G., Durif, F., and Dub,é, L. (2020). Towards closing the attitude-intention-behavior gap in green consumption: A narrative review of the literature and an overview of future research directions. J. Cleaner Prod. 275, 122556. doi: 10.1016/j.jclepro.2020.122556

CrossRef Full Text | Google Scholar

Erzurumlu, S. S., Deets, S., Nersessian, D., and Rodgers, V. L. (2023). Strategic engagement of business with sustainable development goals: a systems thinking approach. Bus. Strat. Environ. 32, 4954–4969. doi: 10.1002/bse.3402

CrossRef Full Text | Google Scholar

Evans, D., and Abrahamse, W. (2009). Beyond rhetoric: The possibilities of and for “sustainable lifestyles.” Environ. Polit. 18, 486–502. doi: 10.1080/09644010903007369

CrossRef Full Text | Google Scholar

Fleck-Dousteyssier, N., Michel, G., and Zeitoun, V. (2014). Brand personification through the use of spokespeople: an exploratory study of ordinary employees, CEOs, and celebrities featured in advertising. Psychol. Market. 31, 677. doi: 10.1002/mar.20677

CrossRef Full Text | Google Scholar

Fledderus, J., Brandsen, T., and Honingh, M. (2013). Restoring trust through the co-production of public services: a theoretical elaboration. Public Manag. Rev. 16, 848920. doi: 10.1080/14719037.2013.848920

CrossRef Full Text | Google Scholar

Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. J. Market. Res. 18, 104. doi: 10.1177/002224378101800313

CrossRef Full Text | Google Scholar

Ge, J., and Guo, J. (2022). “The synergistic effect of sales discount and mobile advertising: how KOL influence online education community purchases,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). doi: 10.1007/978-3-031-05014-5_20

CrossRef Full Text | Google Scholar

Gleim, M., and Lawson, S. J. (2014). Spanning the gap: An examination of the factors leading to the green gap. J. Consumer Market. 31, 988. doi: 10.1108/JCM-05-2014-0988

CrossRef Full Text | Google Scholar

Goh, Y. N., and Wahid, N. A. (2015). A review on green purchase behaviour trend of Malaysian consumers. Asian Soc. Sci. 11, 103. doi: 10.5539/ass.v11n2p103

CrossRef Full Text | Google Scholar

Golob, T. F. (2003). Structural equation modeling for travel behavior research. Transpor. Res. B. 37, 1–25. doi: 10.1016/S0191-2615(01)00046-7

CrossRef Full Text | Google Scholar

Gong, X., Ren, J., Zeng, L., and Xing, R. (2022). How KOLs influence consumer purchase intention in short video platforms: mediating effects of emotional response and virtual touch. Int. J. Inf. Syst. Serv. Sector 14, 287576. doi: 10.4018/IJISSS.287576

CrossRef Full Text | Google Scholar

Goutam, D. (2013). Influence of brand ambassadors on buying behavior of soft drinks: with reference to Belgaum City. Int. J. Res. Bus. Manage. 1, 9–18.

Google Scholar

Guo, J., Li, Y., Xu, Y., and Zeng, K. (2021). How live streaming features impact consumers' purchase intention in the context of cross-border e-commerce? A research based on SOR theory. Front. Psychol. 12, 767876. doi: 10.3389/fpsyg.2021.767876

PubMed Abstract | CrossRef Full Text | Google Scholar

Haeckel, S. H. (1998). About the nature and future of interactive marketing. J. Inter. Market. 12, 63–71. doi: 10.1002/(SICI)1520-6653(199824)12:1<63::AID-DIR8>3.0.CO;2-C

CrossRef Full Text | Google Scholar

Hair, F. H., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., and Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Cham: Springer Link. doi: 10.1007/978-3-030-80519-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Harris, F., and de Chernatony, L. (2001). Corporate branding and corporate brand performance. Eur. J. Market. 35, 441–456. doi: 10.1108/03090560110382101

CrossRef Full Text | Google Scholar

He, W., and Jin, C. (2022). A study on the influence of the characteristics of key opinion leaders on consumers' purchase intention in live streaming commerce: based on dual-systems theory. Electr. Comm. Res. 9, 1–18. doi: 10.1007/s10660-022-09651-8

CrossRef Full Text | Google Scholar

Hennig-Thurau, T., Gwinner, K. P., Walsh, G., and Galmer, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the Internet? J. Inter. Market. 18, 38–52. doi: 10.1002/dir.10073

CrossRef Full Text | Google Scholar

Hewei, T., and Youngsook, L. (2021). Factors affecting continuous purchase intention of fashion products on social E-commerce: SOR model and the mediating effect. Entert. Comput. 41, 100474. doi: 10.1016/j.entcom.2021.100474

CrossRef Full Text | Google Scholar

Hossain, I., Nekmahmud, M., and Fekete-Farkas, M. (2022). How do environmental knowledge, eco-label knowledge, and green trust impact consumers' pro-environmental behaviour for energy-efficient household appliances? Sustainability 14, 16513. doi: 10.3390/su14116513

CrossRef Full Text | Google Scholar

Hu, X., Huang, Q., Zhong, X., Davison, R. M., and Zhao, D. (2016). The influence of peer characteristics and technical features of a social shopping website on a consumer's purchase intention. Int. J. Inf. Manag. 36, 5. doi: 10.1016/j.ijinfomgt.2016.08.005

CrossRef Full Text | Google Scholar

Hua, Y., Bao, L., and Wu, X. (2021). The product-selling strategy under direct and indirect value identification. J. Cleaner Prod. 279, 123591. doi: 10.1016/j.jclepro.2020.123591

CrossRef Full Text | Google Scholar

Hussain, A., Hooi Ting, D., Zaib Abbasi, A., and Rehman, U. (2022). Integrating the S-O-R model to examine purchase intention based on Instagram sponsored advertising. J. Prom. Manage. 29, 2108185. doi: 10.1080/10496491.2022.2108185

CrossRef Full Text | Google Scholar

Ikram, M. (2022). Transition toward green economy: Technological innovation's role in the fashion industry. Curr. Opin. Green Sustain. Chem. 37, 100657. doi: 10.1016/j.cogsc.2022.100657

CrossRef Full Text | Google Scholar

Influencity (n.d.). KOLs vs. Influencers: What They Are and What Differentiates Them. Available online at: https://influencity.com/resources/guide/what-are-kols-and-what-sets-them-apart-from-influencers (accessed September 8 2023).

Google Scholar

James, A. M., and Montgomery, B. (2017). “Connectivity, understanding and empathy: how a lack of consumer knowledge of the fashion supply chain is influencing socially responsible fashion purchasing,” in Textile Science and Clothing Technology. doi: 10.1007/978-981-10-2131-2_3

CrossRef Full Text | Google Scholar

Joshi, Y., and Rahman, Z. (2015). Factors affecting green purchase behaviour and future research directions. Int. Strat. Manage. Rev. 3, 128–143. doi: 10.1016/j.ism.2015.04.001

CrossRef Full Text | Google Scholar

Katz, E., and Lazarsfeld, P. F. (1964). Personal Influence, Foundations of Communications Research. Washington, DC: Free Press.

Google Scholar

Kaufmann, H. R., Panni, M. F. A. K., and Orphanidou, Y. (2012). Factors affecting consumers' green purchasing behavior: an integrated conceptual framework. Amfiteatru Econ. 14, 50–69.

Google Scholar

Keh, H. T., and Xie, Y. (2009). Corporate reputation and customer behavioral intentions: the roles of trust, identification and commitment. Ind. Market. Manage. 38, 732–742. doi: 10.1016/j.indmarman.2008.02.005

CrossRef Full Text | Google Scholar

Kühn, S. W., and Petzer, D. J. (2018). Fostering purchase intentions toward online retailer websites in an emerging Market: An S-O-R perspective. J. Internet Commer. 17, 1463799. doi: 10.1080/15332861.2018.1463799

CrossRef Full Text | Google Scholar

Kumar, P., and Ghodeswar, B. M. (2015). Factors affecting consumers' green product purchase decisions. Market. Intell. Plan. 33, 330–347. doi: 10.1108/MIP-03-2014-0068

CrossRef Full Text | Google Scholar

Kutsenkova, Z. (2017). The sustainable future of the modern fashion industry. Honors Thesis, The Dominican University of California. doi: 10.33015/dominican.edu/2017.HONORS.ST.02

CrossRef Full Text | Google Scholar

Labrecque, L. I. (2014). Fostering consumer-brand relationships in social media environments: the role of parasocial interaction. J. Inter. Market. 28, 134–148. doi: 10.1016/j.intmar.2013.12.003

CrossRef Full Text | Google Scholar

Lau, M. M., Ng, P. M. L., Chan, E. A. H., and Cheung, C. T. Y. (2023). Examining purchase intention for luxury fashion: Integrating theory of reasoned action, with affect-behavior-cognition (ABC) model, identity and social identity theories. Young Consum. 24, 114–131. doi: 10.1108/YC-07-2022-1557

CrossRef Full Text | Google Scholar

Lavuri, R., Chiappetta Jabbour, C. J., Grebinevych, O., and Roubaud, D. (2022). Green factors stimulating the purchase intention of innovative luxury organic beauty products: Implications for sustainable development. J. Environ. Manage. 301, 113899. doi: 10.1016/j.jenvman.2021.113899

PubMed Abstract | CrossRef Full Text | Google Scholar

Lee, N., Choi, Y. J., Youn, C., and Lee, Y. (2012). Does green fashion retailing make consumers more eco-friendly? The influence of green fashion products and campaigns on green consciousness and behavior. Clothi. Text. Res. J. 30, 67–82. doi: 10.1177/0887302X12446065

CrossRef Full Text | Google Scholar

Li, F., and Du, T. C. (2011). Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs. Dec. Support Syst. 51, 190–197. doi: 10.1016/j.dss.2010.12.007

CrossRef Full Text | Google Scholar

Liao, M. J., Zhang, J., Wang, R. M., and Qi, L. (2021). Simulation research on online marketing strategies of branded agricultural products based on the difference in opinion leader attitudes. Inf. Proc. Agric. 8, 528–536. doi: 10.1016/j.inpa.2020.12.001

CrossRef Full Text | Google Scholar

Lin, F., Tian, H., Hu, B., and Zhao, J. (2020). “Implications of rewards and punishments for content generations by key opinion leaders,” in Wuhan International Conference on e-Business- WHICEB 2020 Proceedings.

Google Scholar

Lou, C., and Yuan, S. (2019). Influencer marketing: how message value and credibility affect consumer trust of branded content on social media. J. Inter. Advert. 19, 1533501. doi: 10.1080/15252019.2018.1533501

CrossRef Full Text | Google Scholar

Lyu, W., Qi, Y., and Liu, J. (2022). Proliferation in live streaming commerce, and key opinion leader selection. Electr. Commer. Res. 4, 1–31. doi: 10.1007/s10660-022-09605-0

CrossRef Full Text | Google Scholar

Mahoney, S. (2011). Study: Green Gap is Bigger Than Ever. Marketing Daily. Available online at: https://www.mediapost.com/publications/article/148938/study-green-gap-is-bigger-than-ever.html (accessed September 8, 2023).

Google Scholar

Mastercard (2021, April 12). Consumer Passion for the Environment Grows as a Result of the Pandemic. Mastercard Newsroom. Available online at: https://www.mastercard.com/news/insights/2021/consumer-attitudes-environment/ (accessed September 17, 2023).

Google Scholar

Meffert, J. J. (2009). Key opinion leaders: where they come from and how that affects the drugs you prescribe. Dermatol. Ther. 22, 262–268. doi: 10.1111/j.1529-8019.2009.01240.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Mehrabian, A., and Russell, J. A. (1980). An Approach to Environmental Psychology. London: The MIT Press.

Google Scholar

Meng, Y., Mok, P. Y., and Jin, X. (2010). Interactive virtual try-on clothing design systems. Comput. Aided Des. 42, 310–321. doi: 10.1016/j.cad.2009.12.004

CrossRef Full Text | Google Scholar

Mohd Suki, N. (2016). Green product purchase intention: impact of green brands, attitude, and knowledge. Br. Food J. 118, 2893–2910. doi: 10.1108/BFJ-06-2016-0295

CrossRef Full Text | Google Scholar

Naderifar, M., Goli, H., and Ghaljaie, F. (2017). Snowball sampling: a purposeful method of sampling in qualitative research. Strides Dev. Med. Educ. 14, 67670. doi: 10.5812/sdme.67670

CrossRef Full Text | Google Scholar

Nguyen, C., Nguy?n, N., and Duong, A. (2020). The relationships of social media marketing, consumer engagement and purchase intention. Test Eng. Manage. 2, 24653–24666.

Google Scholar

Nguyen, T. N., Phan, T. T. H., Cao, T. K., and Nguyen, H. V. (2017). Green purchase behavior: mitigating barriers in developing countries. Strategic Direct. 33, 4–6. doi: 10.1108/SD-04-2017-0064

CrossRef Full Text | Google Scholar

Nguyen, T. P., and Dekhili, S. (2019). Sustainable development in Vietnam: an examination of consumers' perceptions of green products. Bus. Strat. Dev. 2, 127–136. doi: 10.1002/bsd2.48

CrossRef Full Text | Google Scholar

Niinimäki, K. (2011). From disposable to sustainable: the complex interplay between design and consumption of textiles and clothing. Doctoral Dissertations, Aalto University.

Google Scholar

Niinimäki, K., Peters, G., Dahlbo, H., Perry, P., Rissanen, T., and Gwilt, A. (2020). The environmental price of fast fashion. Nat. Rev. Earth Environ. 1, 189–200. doi: 10.1038/s43017-020-0039-9

CrossRef Full Text | Google Scholar

Niu, B., Yu, X., Li, Q., and Wang, Y. (2023). Gains and losses of key opinion leaders' product promotion in livestream e-commerce. Omega 117:102846. doi: 10.1016/j.omega.2023.102846

CrossRef Full Text | Google Scholar

Niu, Y., and Liu, F. (2012). What makes a professional video? A computational aesthetics approach. IEEE Trans. Circ. Syst. Video Technol. 22, 1037–1049. doi: 10.1109/TCSVT.2012.2189689

CrossRef Full Text | Google Scholar

Palevich, R. (2012). The Lean Sustainable Supply Chain How to Create a Green Infrastructure with Lean Technologies. Washington, DC: Pearson.

Google Scholar

Paparoidamis, N. G., Tran, T. T. H., Leonidou, L. C., and Zeriti, A. (2019). Being innovative while being green: an experimental inquiry into how consumers respond to eco-innovative product designs. J. Product Innov. Manage. 36, 12509. doi: 10.1111/jpim.12509

CrossRef Full Text | Google Scholar

Plantin, L., and Daneback, K. (2009). Parenthood, information and support on the internet. A literature review of research on parents and professionals online. BMC Family Pract. 10, 34. doi: 10.1186/1471-2296-10-34

PubMed Abstract | CrossRef Full Text | Google Scholar

Polonsky, M. J., Bailey, J., Baker, H., Basche, C., Jepson, C., and Neath, L. (1998). Communicating environmental information: are marketing claims on packaging misleading? J. Bus. Ethics 17, 281–294. doi: 10.1023/A:1005731914135

CrossRef Full Text | Google Scholar

Posas, P. J. (2007). Roles of religion and ethics in addressing climate change. Eth. Sci. Environ. Polit. 7, 80. doi: 10.3354/esep00080

CrossRef Full Text | Google Scholar

Pourhoseingholi, M. A., Baghestani, A. R., and Vahedi, M. (2012). How to control confounding effects by statistical analysis. Gastroenterol. Hepatol. Bed. Bench 5, 79.

PubMed Abstract | Google Scholar

Priyandhini, B., Mona, N., and Oktaviani, D. (2022). “The Role of the Key Opinion Leader (Kol) Specialist in Handling the #BelajarDimanaAja Campaign on Hangeul Academy by Schoters through Instagram to Increase Brand Awareness,” in Proceedings of The 5th International Conference on Vocational Education Applied Science and Technology 2022. doi: 10.3390/proceedings2022083038

CrossRef Full Text | Google Scholar

Putri, C. R., and Agus, A. A. (2019). “Analysis of key opinion leadership on instagram to online beauty product purchase,” in Proceedings - 2019 2nd International Conference of Computer and Informatics Engineering: Artificial Intelligence Roles in Industrial Revolution 4.0, IC2IE 2019. doi: 10.1109/IC2IE47452.2019.8940885

CrossRef Full Text | Google Scholar

Qin, M. (2020). The Impact of Influencers on Young People's Buying Decisions.

Google Scholar

Ramayah, T., Lee, J. W. C., and Mohamad, O. (2010). Green product purchase intention: some insights from a developing country. Resour. Conserv. Recycl. 54, 1419–1427. doi: 10.1016/j.resconrec.2010.06.007

CrossRef Full Text | Google Scholar

Ramezaninia, M., and Shokouhyar, S. (2020). Analyzing the effects of visual aesthetic of Web pages on users' responses in online retailing using the VisAWI method. J. Res. Inter. Market. 14, 147. doi: 10.1108/JRIM-11-2018-0147

CrossRef Full Text | Google Scholar

Rapanos, T. (2023). What makes an opinion leader: expertise vs popularity. Games Econ. Behav. 138, 355–372. doi: 10.1016/j.geb.2023.01.003

CrossRef Full Text | Google Scholar

Rehmet, J., and Dinnie, K. (2013). Citizen brand ambassadors: motivations and perceived effects. J. Destin. Market. Manag. 2, 31–38. doi: 10.1016/j.jdmm.2013.02.001

CrossRef Full Text | Google Scholar

Salam, A. F., Iyer, L., Palvia, P., and Singh, R. (2005). Trust in e-commerce. Commun. ACM 48, 72–77. doi: 10.1145/1042091.1042093

CrossRef Full Text | Google Scholar

Scher, J. U., and Schett, G. (2021). Key opinion leaders—a critical perspective. Nat. Rev. Rheumatol. 17, 119–124. doi: 10.1038/s41584-020-00539-1

CrossRef Full Text | Google Scholar

Schwemmer, C., and Ziewiecki, S. (2018). Social media sellout: the increasing role of product promotion on YouTube. Soc. Media Soc. 4, 2056305118786720. doi: 10.1177/2056305118786720

CrossRef Full Text | Google Scholar

Shamim, K., and Islam, T. (2022). Digital influencer marketing: how message credibility and media credibility affect trust and impulsive buying. J. Global Schol. Market. Sci. 32, 2052342. doi: 10.1080/21639159.2022.2052342

CrossRef Full Text | Google Scholar

Sheikh, F. Z., Mirza, A. A., Aftab, A., and Asghar, B. (2014). Consumer green behaviour toward green products and green purchase decision. Int. J. Multidispl. Eng. 5, 1–9.

Google Scholar

Shen, G. C. C., Chiou, J. S., Hsiao, C. H., Wang, C. H., and Li, H. N. (2015). Effective marketing communication via social networking site: the moderating role of the social tie. J. Bus. Res. 69, 2265–2270. doi: 10.1016/j.jbusres.2015.12.040

CrossRef Full Text | Google Scholar

Sheth, S., and Kim, J. (2017). Social media marketing: the effect of information sharing, entertainment, emotional connection and peer pressure on the attitude and purchase intentions. GSTF J. Bus. Rev. 5, 1839.

Google Scholar

Shukla, N. (2022). Fast Fashion Pollution and Climate Change. Earth Org. Available online at: https://earth.org/fast-fashion-pollution-and-climate-change/#:~:text=Fashion%20and%20its%20supply%20chain,and%20the%20aviation%20industry%20combined (accessed September 17, 2023).

Google Scholar

Sierra, J. J., and McQuitty, S. (2007). Attitudes and emotions as determinants of nostalgia purchases: An application of social identity theory. J. Market. Theory Pract. 15, 201. doi: 10.2753/MTP1069-6679150201

CrossRef Full Text | Google Scholar

Statista Market Insights. (2023). Apparel - Vietnam. Statista. Available online at: https://www.statista.com/outlook/cmo/apparel/vietnam (accessed September 17, 2023).

Google Scholar

Steensma, D. P. (2015). Key opinion leaders. J. Clin. Oncol. 33, 3213–3214. doi: 10.1200/JCO.2015.63.1275

CrossRef Full Text | Google Scholar

Su, C. H., Tsai, C. H., Chen, M. H., and Lv, W. Q. (2019). US sustainable food market generation Z consumer segments. Sustainability 11, 3607. doi: 10.3390/su11133607

CrossRef Full Text | Google Scholar

Sultana, N., Amin, S., and Islam, A. (2022). Influence of perceived environmental knowledge and environmental concern on customers' green hotel visit intention: Mediating role of green trust. Asia-Pacific J. Business Admin. 14, 223–243. doi: 10.1108/APJBA-08-2021-0421

CrossRef Full Text | Google Scholar

Tan, X., Zhu, K., Meng, X., Gu, B., Wang, Y., Meng, F., et al. (2021). Research on the status and priority needs of developing countries to address climate change. J. Cleaner Prod. 289, 125669. doi: 10.1016/j.jclepro.2020.125669

CrossRef Full Text | Google Scholar

Tang, Y., Wang, X., and Lu, P. (2014). Chinese consumer attitude and purchase intent towards green products. Asia-Pacific J. Bus. Admin. 6, 84–96. doi: 10.1108/APJBA-05-2013-0037

CrossRef Full Text | Google Scholar

Thomala, L. L. (2023). Influencer/Kol Marketing in China- Statistics and Facts. Statistica. Available online at: https://www.statista.com/topics/9579/influencer-marketing-in-china/#topicOverview (accessed October 21 2023).

Google Scholar

Till, B. D., and Busler, M. (1998). Matching products with endorsers: attractiveness versus expertise. J. Consum. Market. 15, 576–586. doi: 10.1108/07363769810241445

CrossRef Full Text | Google Scholar

Tsiotsou, R. H. (2006). The role of perceived product quality and overall satisfaction on purchase intentions. Int. IJC 30, 207–217. doi: 10.1111/j.1470-6431.2005.00477.x

CrossRef Full Text | Google Scholar

Valente, T. W., and Pumpuang, P. (2007). Identifying opinion leaders to promote behavior change. Health Educ. Behav. 34, 881–896. doi: 10.1177/1090198106297855

PubMed Abstract | CrossRef Full Text | Google Scholar

Vâtâmânescu, E. M., Dabija, D. C., Gazzola, P., Cegarro-Navarro, J. G., and Buzzi, T. (2021). Before and after the outbreak of Covid-19: linking fashion companies' corporate social responsibility approach to consumers' demand for sustainable products. J. Cleaner Prod. 321, 128945. doi: 10.1016/j.jclepro.2021.128945

CrossRef Full Text | Google Scholar

Vazifehdoust, H., Taleghani, M., Esmaeilpour, F., Nazari, K., and Khadang, M. (2013). Purchasing green to become greener: factors influence consumers' green purchasing behavior. Manag. Sci. Lett. 3, 2489–2500. doi: 10.5267/j.msl.2013.08.013

CrossRef Full Text | Google Scholar

Vecchione, M., Feldman, C., and Wunderlich, S. (2015). Consumer knowledge and attitudes about genetically modified food products and labelling policy. Int. J. Food Sci. Nutr. 66, 329–335. doi: 10.3109/09637486.2014.986072

PubMed Abstract | CrossRef Full Text | Google Scholar

Vietnam Briefing News (2023). Cross-Border and Digital Advertising in Vietnam: An Overview. Available online at: https://www.vietnam-briefing.com/news/digital-advertising-vietnam.html/ (accessed September 30, 2023).

Google Scholar

Vogler, D., and Eisenegger, M. (2019). “Corporate scandals as denial of reputation,” in The Routledge Companion to Media and Scandal. doi: 10.4324/9781351173001-42

CrossRef Full Text | Google Scholar

Vrontis, D., Makrides, A., Christofi, M., and Thrassou, A. (2021). Social media influencer marketing: a systematic review, integrative framework and future research agenda. Int. J. Consumer Stud. 45, 617–644. doi: 10.1111/ijcs.12647

CrossRef Full Text | Google Scholar

Wang, H., Ding, J., Akram, U., Yue, X., and Chen, Y. (2021). An empirical study on the impact of e-commerce live features on consumers' purchase intention: from the perspective of flow experience and social presence. Information 12, 324. doi: 10.3390/info12080324

CrossRef Full Text | Google Scholar

Wang, J., Ding, K., Zhu, Z., Zhang, Y., and Caverlee, J. (2020). “Key opinion leaders in recommendation systems: Opinion elicitation and diffusion,” in WSDM 2020 - Proceedings of the 13th International Conference on Web Search and Data Mining. doi: 10.1145/3336191.3371826

CrossRef Full Text | Google Scholar

Weber, F. (2019). “Demand for sustainable tourism,” in Corporate Sustainability and Responsibility in Tourism. doi: 10.1007/978-3-030-15624-4_16

CrossRef Full Text | Google Scholar

Wibowo, A., Chen, S. C., Wiangin, U., Ma, Y., and Ruangkanjanases, A. (2021). Customer behavior as an outcome of social media marketing: the role of social media marketing activity and customer experience. Sustainability 13, 189. doi: 10.3390/su13010189

CrossRef Full Text | Google Scholar

Witek, L., and Kuzniar, W. (2021). Green purchase behavior: the effectiveness of sociodemographic variables for explaining green purchases in emerging market. Sustainability 13, 209. doi: 10.3390/su13010209

CrossRef Full Text | Google Scholar

Xiong, L., Cho, V., Law, K. M. Y., and Lam, L. (2021). A study of KOL effectiveness on brand image of skincare products. Enter. Inf. Syst. 15, 1924864. doi: 10.1080/17517575.2021.1924864

CrossRef Full Text | Google Scholar

Xue, F., and Zhou, P. (2011). The effects of product involvement and prior experience on Chinese consumers' responses to online word of mouth. J. Int. Consum. Market. 23, 45–58. doi: 10.1080/08961530.2011.524576

CrossRef Full Text | Google Scholar

Yadav, R., and Pathak, G. S. (2017). Determinants of consumers' green purchase behavior in a developing nation: applying and extending the theory of planned behavior. Ecol. Econ. 134, 114–122. doi: 10.1016/j.ecolecon.2016.12.019

CrossRef Full Text | Google Scholar

Yang, Y., Tang, Y., Zhang, Y., and Yang, R. (2021). Exploring the relationship between visual aesthetics and social commerce through visual information adoption unimodel. Front. Psychol. 12, 700180. doi: 10.3389/fpsyg.2021.700180

PubMed Abstract | CrossRef Full Text | Google Scholar

Yerpude, S., and Singhal, T. K. (2018). Internet-of-things-based customer relationship management - A research perspective. Int. J. Eng. Technol. 7, 10860. doi: 10.14419/ijet.v7i2.7.10860

CrossRef Full Text | Google Scholar

Yin, X., Wang, H., Yin, P., and Zhu, H. (2019). Agent-based opinion formation modeling in social network: a perspective of social psychology. Phys. A. 532, 121786. doi: 10.1016/j.physa.2019.121786

CrossRef Full Text | Google Scholar

Yuan, L., Xia, H., and Ye, Q. (2022). The effect of advertising strategies on a short video platform: evidence from TikTok. Ind. Manage. Data Syst. 122, 1956–1974. doi: 10.1108/IMDS-12-2021-0754

CrossRef Full Text | Google Scholar

Zailskaite-Jakšte, L., and Kuvykaite, R. (2010). Internet based communication with target audiences: case study of higher education institutions. Econ. Manage.

Google Scholar

Zhang, H., Liang, X., and Moon, H. (2020). Fashion cewebrity involvement in new product development: scale development and an empirical study. J. Bus. Res. 120, 52. doi: 10.1016/j.jbusres.2020.01.052

CrossRef Full Text | Google Scholar

Zhang, K. Z. K., and Benyoucef, M. (2016). Consumer behavior in social commerce: a literature review. Dec. Supp. Syst. 86, 95–108. doi: 10.1016/j.dss.2016.04.001

CrossRef Full Text | Google Scholar

Zhang, P., Chao, C. W. (Fred), Chiong, R., Hasan, N., Aljaroodi, H. M., and Tian, K. (2023). Effects of in-store live stream on consumers' offline purchase intention. J. Retail. Cons. Serv. 72, 103262. doi: 10.1016/j.jretconser.2023.103262

CrossRef Full Text | Google Scholar

Zhang, R., Ma, B., Li, Y., Chen, F., Yan, J., Lin, Y., et al. (2023). “The effect of key opinion leader type on purchase intention: considering the moderating effect of product type,” in Lecture Notes in Business Information Processing. doi: 10.1007/978-3-031-32302-7_10

CrossRef Full Text | Google Scholar

Zhao, H. H., Gao, Q., Wu, Y. P., Wang, Y., and Zhu, X. D. (2014). What affects green consumer behavior in China? A case study from Qingdao. J. Clean. Prod. 63, 21. doi: 10.1016/j.jclepro.2013.05.021

CrossRef Full Text | Google Scholar

Zimand Sheiner, D., Kol, O., and Levy, S. (2021). It makes a difference! Impact of social and personal message appeals on engagement with sponsored posts. J. Res. Inter. Market. 15, 210. doi: 10.1108/JRIM-12-2019-0210

CrossRef Full Text | Google Scholar

Zou, Y., and Peng, F. (2019). “Key opinion leaders' influences in the chinese fashion market,” in Fashion Communication in the Digital Age. doi: 10.1007/978-3-030-15436-3_11

CrossRef Full Text | Google Scholar

Keywords: key opinion leader (KOL), green trust, green purchase intention, green fashion products, SOR framework

Citation: Tran KV and Uehara T (2023) The influence of key opinion leaders on consumers' purchasing intention regarding green fashion products. Front. Commun. 8:1296174. doi: 10.3389/fcomm.2023.1296174

Received: 18 September 2023; Accepted: 10 November 2023;
Published: 01 December 2023.

Edited by:

Shu-Yueh Lee, University of Wisconsin–Oshkosh, United States

Reviewed by:

Yuanzhe Li, Nanyang Technological University, Singapore
Nela Filimon, University of Girona, Spain

Copyright © 2023 Tran and Uehara. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Takuro Uehara, takuro@fc.ritsumei.ac.jp

Download