Sharing Economy: Generation Z's Intention Toward Online Fashion Rental in Vietnam

Abstract

The last decade has seen the emergence of the idea of "sharing economy" as people are more aware of environmental issues. Although clothing businesses applying the model of sharing consumption have emerged recently, less research effort has been invested in this topic, especially in investigating young consumers' intention. The purpose of this study is to investigate factors driving Generation Z consumers' behavioral intention toward online fashion rental. In this research, a conceptual framework is proposed based on the Theory of Planned Behavior and Technology Acceptance Model. To test the research model and hypotheses, a survey of 375 students and pupils was conducted in Vietnam. All the scales' reliability and validity were assessed through Cronbach's Alpha and confirmatory factor analysis. Structural equation modeling was used to assess the relationship among constructs. The study results showed that attitude toward behavior, subjective norm and perceived behavioral control were positive contributors to Gen Z's intention to use online fashion rental. Besides, the positive relationships between attitude and two other factors - perceived usefulness and perceived ease of use - were also highlighted. Moreover, the findings provided empirical evidence for supporting the positive impact of interpersonal influence, e-WOM, and influencer e-marketing on subjective norm.

1. Introduction

Clothing is an essential item in every individual’s life and, thus, the fashion industry is among the biggest industries contributing $2.5 trillion to the world economy. However, this industry is also seen as the second dirtiest industry, only behind the oil industry in terms of pollution (Chaturvedi, Kulshreshtha, & Tripathi, 2020). Moreover, it is assessed to be one of the primary sources of environmental pollution and contributed to creating various ecological issues, such as water body pollution, waste Generation, air pollution (Desore & Narula, 2018). Environmental concerns on negative impacts of fast fashion have increased people awareness through education or propaganda, but the actual demands for fashion shopping shows no sign of slowing down (Gazzola, Pavione, Pezzetti, & Grechi, 2020). With that high demand on fashion, “sharing” consumption can be consider as an environmentally-friendly mode of consumption through renting, bartering, lending, trading and swapping of goods for temporary use (Lee & Huang, 2020).

Sharing economy is defined as “an economic activity in which web platforms facilitate peer-to-peer exchanges of diverse types of goods and services” (Aloni, 2016). Recently, sharing economy has gained utmost attention among marketers and researchers as a potentially profitable business model in all fields (Tu & Hu, 2018), and this economic model is expected to help diminish social problems, such as poverty, excessive consumption of resources, and environmental pollution. Renting clothes on online platform based on the principle of sharing economy would be an effective, convenient and eco-friendly solution to benefit both customers and marketers by sharing the cost of products and reducing the burden of ownership (Botsman & Rogers, 2010; Lang, Li, & Zhao, 2019; Lang & Armstrong, 2018).

The focal point of this study is Generation Z – the youngest and largest consumer group across all Generations till 2030 with high level of addiction to digital world as heavy users of information technology and innovation (Abdullah, Ismail, & Albani, 2018; Priporas, Stylos, & Fotiadis, 2017). Born during the digital era, this cohort is found to spend a high portion of their time engaging and expressing themselves online, which may influence their consumer behaviors (Nguyen & Nguyen, 2020). Other distinctive traits of Generation Z are high level of education with sound understanding of environmental issues and high desire to adopt eco-friendly products (Ao & Nguyen, 2020; Chaturvedi, Kulshreshtha, & Tripathi, 2020). Hence, they expected to contribute actively to environment protection by switching their consumption habit toward sharing consumption.

Despite the fact that collaborative fashion consumption has become a remarkable phenomenon, investigations on young consumers’ intention toward fashion rental in the context of developing country as Vietnam are limited (Lee & Huang, 2020). To fill this gap, this study applied the widely-accepted Theory of Planned Behavior (Ajzen, 1991) and Technology Acceptance Model (TAM) to explore the influence among variables that shape Vietnamese Gen Z’s behavioral intention toward online rental clothes.

2. Literature Review and Hypothesis Development

2.1. Generation Z and Sharing Economy

Generation Z (Gen Z) or “Post-millennials” are those born between 1995 and 2010 (Seemiller & Grace, 2016). This young generation has their daily lives completely saturated with the Internet as they spend about 10 hours per day online and a whopping 96 percent of them own a smartphone (Livingstone, 2018). In a recent survey by Nielsen (2018), 99% of Vietnam’s Generation Z are Facebook users, 77% are on Zalo (i.e., a local social network app) and 90% watch TV daily. They are also the most photographed generation and often need new fashion to post on their social network (Frazier, 2019). This massive fashion consumption may result in overconsumption, which is waste of resources and money (Won & Kim, 2020). For that reason, this price-elastic young consumers often look for possible saving-consumption (Shatto & Erwin, 2017).

On the other hand, Generation Z are highly educated and has sound sense of environmental issues as these social activists are willing to pay 10–15% more on eco-consious clothes (Abdullah, Ismail, & Albani, 2018). In Vietnam, this generation is considered as leading light in fashion and consumer goods (Brandsvietnam, 2018). These future Vietnamese golden consumers will be main driver of social and consumption patterns changes as they play important role in family purchase decision (Nguyen & Nguyen, 2020). Hence, it is expected that this generation cohort will participate actively in changing the consumption trend toward environmental products and sharing consumption. Toward this trend, fashion renting online turns to be an attractive and effective solution for these young consumers in their digital life. This rental business model may lengthen the lifespan of fashion products than the previously long-term possession (Won & Kim, 2020).

Renting clothes on online platform based on the principle of sharing economy is collaborative consumption, where people share their and underutilized their clothes for money or for free via online platforms (Won & Kim, 2020). This would be an effective, convenient and eco-friendly solution to benefit both customers and marketers by sharing the cost of products and reducing production emissions and clothing waste (Armstrong, Niinimäki, Lang, & Kujala, 2016; Lang & Armstrong, 2018). Because of its huge potential benefits for businesses, customers as well as environment, an increasing number of customers has switched to rent fashion rather than purchase them (Yuan & Shen, 2019). The model of online renting clothes services has become more and more popular worldwide such as Girl Meets Dress and Fashion on hire in the U.K., Rent the Runway and Bag Borrow or Steal in the U.S., Meilizu in China, Lend My Trend in Australia (Lang, Li, & Zhao, 2019), and Vietnam cannot be an exception. In fact, renting clothes in Vietnam is still limited mainly to wedding and performance costumes, leaving high possibility to apply this business model, especially in this dynamic e-commerce market. Our study will provide fundamentals of behavioral intention of this targeted Gen Z toward online renting clothes.

2.2. Theoretical Model

This study combines TPB and TAM to predict and analyze the factors that can affect the customers’ willingness to engage in fashion rentals as illustrated in the model below.

Theory of Planned Behavior, as an extended of Theory of Reasoned Action (TRA), is a core model constructed by three concepts attitude, subjective norm and perceived behavioral control in order to predict and explain consumer behavior in different research contexts (Ajzen, 2010). This theory is widely adopted to study environmentally-friendly buying preferences of customers (Yazdanpanah & Forouzani, 2015). Despite its power, TPB model may be inadequate to predict behavior via online platform, as online users may strongly be influenced by e-word of mouth and e-marketing activities. Therefore, we choose to combine TPB with Technology Acceptance Model (TAM) to achieve better understanding of Gen Z’s behavioral intention to use online fashion rentals. TAM was firstly introduced by Fred Davis in 1986 (Davis, Bagozzi, & Warshaw, 1989). It is an adaptation of the theory of reasoned action (TRA) and mainly designed for modeling user acceptance of information technology base on three main constructs: perceived usefulness, perceived ease of use and attitude. These two models has widely been applied in many other studies of consumer behavior (Chaturvedi, Kulshreshtha, & Tripathi, 2020; Le, Ngo, Trinh & Nguyen, 2020; Nguyen, Nguyen, & Nguyen, 2019).

Perceived usefulness

Perceived usefulness is defined as ‘the degree to which a person believes that using a particular technology will enhance his or her job performance’ (Davis, Bagozzi, & Warshaw, 1989). As the results of some previous TAM studies, perceived usefulness has a possible impact on enhancing user’s attitude toward usage. In particular, studies by Teo (2010) and Weng, Yang, Ho, and Su (2018) found that the attitude toward behavior was significantly affected by predicting usefulness in major of education. In line with other research, perceived usefulness plays important role in shaping attitude toward online airline tickets purchasing (Renny, Suryo, & Siringoringo, 2013), online shopping (Juniwati, 2014), and e-payment (Lai, 2017). This study supposes that when people perceive advantages from using online fashion rental services, their attitude become more positive. Therefore, the first hypothesis is developed.

H1a: Perceived usefulness has a positive relationship with attitude regarding online fashion rental services.

Perceived ease of use

Davis, Bagozzi, and Warshaw (1989) described perceived ease of use as “the degree to which a person believes that using a particular system would be free of physical and mental effort”. TAM posits that perceived ease of use has a direct positive effect on attitude toward using the system. Many studies were conducted to validate TAM by using perceived ease of use and perceived usefulness as two independent variables and attitude toward behavior as the dependent variable (Weng, Yang, Ho, & Su, 2018; Juniwati, 2014; Lai, 2017; Renny, Suryo, & Siringoringo, 2013; Teo, 2010). The results show that perceived usefulness is significantly correlated with attitude. As the same way, perceived ease of use also has positive impacts on attitude. Based on the above arguments, the easier the using of online renting clothes is, the better consumers’ attitude become. Hence, the proposed hypothesis is:

H1b: Perceived ease of use has a positive relationship with attitude regarding online fashion rental services.

Interpersonal influence

Interpersonal is one of the dimensions that has intensive impact on subjective norms (Bhattacherjee, 2000). It is referred to the change in one’s behavior due to others’ feelings or opinions. This influence might reflect the compliance and acceptance with others’ expectation. Besides, the strong influence of proximate people was posited and emphasized, such as friends, family and co-workers (Hsu, Yen, Chiu, & Chang, 2006; Hung, Chang, & Yu, 2006). Regarding online fashion rentals, Tu and Hu (2018) found that the positive relationship between interpersonal influence and subjective norms was significant. Hence, this study assumes that:

H2a: Interpersonal influence has a positive relationship with attitude regarding online fashion rental services.

Electronic word of mouth (E-WOM)

Hennig-Thurau and Walsh (2003) defined E-WOM as comments either positive or negative which are made by customers regarding product or service to an amount of people through the Internet. E-WOM is also considered to be an important platform that allows consumers to communicate and transfer their thoughts to others (Godes & Mayzlin, 2004). Besides, Fong and Burton (2008) argued that E-WOM is more effective when compared to traditional word of mouth due to the ease of use and the width of range.

WOM which can be considered in terms of peers influence generated by co-workers, relatives or friends has positive relationship with subjective norms (Bhattacherjee, 2000; Teo, 2010). Numerous studies have validated the significant influence of word of mouth on subjective norm (Bhattacherjee, 2000; Husin, Ismail, & Rahman, 2016). Hence, some authors also suggest the influence of E-WOM on subjective norms (Doma, Elaref, & Abo Elnaga, 2015; Jalilvand & Samiei, 2012). For the young people who mostly make discussions on Internet as Gen Z, following these articles, the study suggests the hypothesis:

H2b: E-WOM has a positive relationship with subjective norms regarding online fashion rental services.

Influencer e-marketing

Brown and Fiorella (2013) defines that influencer marketing is “typically a non-customer or business incentivized to recommend/create content about a business brand or product.” Influencer marketing can appear as an entirely new marketing strategy mostly through the internet. As previous studies, it may affect the subjective norm of individuals (Chopra, Avhad, & Jaju, 2020), which is defined as the social impact on human thinking. In addition, influencer marketing on social networks is seen as a virtual word of mouth, but it works differently than word of mouth. Consumers are much more likely to positively perceive and react to a message that comes from a trusted personal over a sponsored post that comes from a company (Theocharis & Papaioannou, 2020). The research focuses on Gen Z who is significantly and directly affected by famous people or influencers on Internet. Hence, the following hypothesis is proposed:

H2c: Influencer e-marketing has a positive relationship with subjective norms regarding online fashion rental services.

Attitude toward behavior

Following the results of TRA or TPB research, attitude is one of the major determinants that shape behavioral intention (Ajzen, 1991). This involves favorable or unfavorable assessment, emotional feelings, and behavioral propensity (Lee & Huang, 2020). The positive impacts of attitude on behavioral intention are explored and proved in many studies in different fields (Ajzen, 2010; Chew & Abdul Adis, 2018; Fusilier, Harrison, & Worley, 1996; Jalilvand & Samiei, 2012; Juniwati, 2014). Regarding to renting clothes, attitude also is one of the main determinants that positive influences on intention to hire (Lee & Chow, 2020; Tu & Hu, 2018). This study suggests the hypothesis:

H3: Attitude toward behavior has a positive relationship with behavioral intention regarding online fashion rental services.

Subjective norms

Subjective norm is the second determination of intention in the TPB model. It was defined by Ajzen (1991) as perception of social pressures of whether or not to undertake a given behavior. Many previous studies indicated that subjective norm has impact on the behavioral intention toward various fields such as food (Shin & Hancer, 2016), health (Caso, Carfora, Starace, & Conner, 2019), advertising (Sanne & Wiese, 2018) and shopping online (Hasbullah et. al., 2016). Hence, this study assumes that subjective norm has positive effects on the behavioral intention of clothes renting.

H4: Subjective norm has a positive relationship with behavioral intention regarding online fashion rental services.

Perceived behavioral control

Ajzen (1991) introduced perceived behavioral control into his theory of planned behavior as a determinant behavioral intention. Perceived behavioral control means an individual’s perception regarding the ease or difficulty in undertaking the behavior. Following Ajzen’s theory of planned behavior, most psychosocial theories of health behavior have incorporated perceived behavioral control as a major determinant of intention to engage in health behavior (Wallston, 2001). Besides, some studies in other fields also supported for the significant impact of this variable on behavioral intention (Hilverda, Van Gils, & De Graaff, 2018; Kim, Ham, Yang, & Choi, 2013). This study also proves the influence of perceived behavioral control on behavioral intention by proposed hypothesis:

H5: Perceived behavioral control has positive relationship with behavioral intention regarding online fashion rental services.

Behavioral intention

Behavioral intention reflects the tendency according to which a person wants to take a specific action, and it can be measured by a person’s willingness to have an experience or the effort of person makes to take an action. According to TPB model of Ajzen (1991), it is pointed out that behavioral intention is the best way to predict individual behavior. In other words, when people have stronger intention to take some actions, then the probability of taking the action will be higher. This study proposes that three main factors: attitude, subjective norm, and perceived behavioral control have a significant positive correlation with behavioral intention of customer to engage in online renting clothes service.

Figure 1: Proposed Research Model and Hypotheses

3. Research Methodology

3.1. Measure and Questionnaire Development

This research applied convenience sampling method focusing on undergraduate students and pupils across Vietnam in early 2020. The questionnaire was designed with two sections: (1) demographics and social network usage information and (2) measument items on Likert scale. In the second part, there are 29 items measuring nine constructs in the research model. Each scale includes three to four items, all are defined and adapted from relevant existing literature, as in Table 1. Behavioral intention, attitude toward behavior, subjective norm, perceived behavioral control, perceived usefulness, perceived ease of use, interpersonal influence, were measured using item scales of Tu and Hu (2018). The scale measuring E-WOM was adopted by Doma, Elaref, and Abo Elnaga (2015). Besides, based on the definition of influencer e-marketing, the present study creates and develop an item scale to measure this variable. All scale items originally in English and were professionally translated into Vietnamese. All of the items were measured with a 5-point Likert scale, ranging from strongly disagree (1) to strongly agree (5).

Table 1: The Definition of Variable Operability and Reference Scales

3.2. Sample and Data Collection

A pilot study was conducted with 15 university students and colleges in order to test their understanding of composition of survey questions, time determination to complete the survey, and ascertain the face validity of the measurement scales. The number of respondents for the pretest study was considered sufficient as suggested by Hair, Black, Babin, and Anderson (2010). Some minor changes were made to the wording of the questions. In the final round, survey questions were send through mailing system addressing undergraduates students, colleges and pupils in big cities of Vietnam such as Hanoi, Hue, Thanh Hoa and Ho Chi Minh City. After removing incomplete and inconsistent answers, 375 responses were found valid for further analysis. This is in line with a good sample size to apply SEM (Kline, 2011). The data were cleaned and processed by SPSS26 and AMOS20 software to testing hypotheses.

Demographic profiles of respondents including age, gender, educational level, and source of spending for clothes as the majority of them are in school as may not have income themselves (details are shown in Table 2).

Table 2: The Demographic Characteristics

4. Research Findings

Since the proposed model applied in this research were adopted from the literature, we evaluate the scale reliability and validity by applying Cronbach’s Alpha and Confirmatory factor analysis (CFA), respectively. After that, Structural equation modeling (SEM) was used to assess the relationship among constructs.

4.1. Scale Reliability and Validity

Cronbach’s Alpha was used to perform an evaluation of the “internal consistency reliability’’ of scale. The Cronbach’s Alpha calculated for each scale ranges from 0.814 (for BI) to 0.882 (for AB), all were higher than 0.7, showing satisfactory level of reliability (Hair et al., 2010). In addition, we also examined estimated loadings and assessed average variance (AVE) extracted composite reliability (CR) for each indicator to establish the convergent validity of the data (Fornell & Larcker, 1981). As shown in Table 3, all the factor loadings of the construct items were statistically significant (p < 0.01) with the value range from 0.616 to 0.882, exceeding the cutoff value of 0.60. Furthermore, all the AVEs and CRs were higher than 0.5 and 0.7, respectively, showing that nine constructs have high levels of convergent validity and internal consistency reliability (Hair et al., 2010).

Table 3: The Acceptance Level of Model Fit

The Confirmatory factor analysis (CFA) was used to examine measurement model fit and the convergent and discriminant validity of the data (Hair et al., 2010). The results of CFA demonstrated a good level of fit: x² (Chi-square) = 1.258; CMIN/df = 1.258, p < 0.001; GFI (goodness of fit index) = 0.926; CFI (comparative fit index) = 0.983; TLI (Tucker Lewis index) = 0.980; and RMSEA (root mean square error of approximation = 0.026. All t-tests of the observed variables were significant at the 0.001 level. The results prove that all the model fit indexes are appropriate and the matching between model and collected data is meaningful.

4.2. The Structural Model and Hypothesis Testing

4.2.1. Correlation Among the Constructs

Before testing the proposed hypotheses, we checked for correlations among the applied variables. As shown in Table 4, there is no possible serious multi-collinearity problem. Moreover, the square root of AVE is greater than its highest correlation with any other constructs and the MSV value was smaller than AVE, therefore, the discriminant validity of all the variables in this model was confirmed. In conclusion, all constructs included in this study demonstrated adequate reliability, convergent validity, and discriminant validity.

Table 4: Discriminant Validity for the Measurement Model

4.2.2. Structural Path Analysis

Structural equation modeling (SEM) was applied to test the structural model of this study. According to Hair et al. (2010), SEM is used by researchers to examine the overall fit of the model and to test the relative strengths of the individual causal paths. The structural model was shown to achieve good level of fit with GFI = 0.913, CFI = 0.969, RMSEA = 0.035, TLI = 0.965, PCLOSE = 1.000, and Chi-square/df = 1.450. Hence, the results indicate that the model provided considerable insights with regards to direct and indirect antecedents of online fashion rental.

The results in Table 4 showed that all the hypothesized relationship was found positive and significant as expectation. Acceptance of hypotheses H1a and H1b confirmed a positive relationship between Perceived Usefulness (PU) and Perceived ease of use (PEU) on attitude of Generation Z consumers toward rental clothes online. In addition, hypotheses H2a, H2b, and H2c were all significant at 0.001, which means that Interpersonal influence, E-WOM and Influencer e-marketing had positive impacts on the subjective norm.

Regarding TPB model, all three variables ATT, SN, PBC were found to have positive effects to BI. This finding confirmed the results of the previous findings that Attitude, Subjective norm and Perceived behavioral control positively influence young consumers’ intention (Nguyen, Nguyen, & Nguyen, 2019), especially intention to use online fashion rental (Lee & Huang, 2020). Furthermore, the result emphasized that among three variables, PBC had the highest level of impact on BI compared to AB and SN.

5. Discussion and Implications

The sharing economy is believed to bring huge potential to sustainable environment through collaborative consumption practices. Although clothing businesses applying the model of sharing consumption have emerged recently, academic research on this topic is still limited (Park & Armstrong, 2017). This study aims to provide a more precise understanding of antecedents on intention to use online fashion rental among Vietnamese Generation Z consumers. The combination of TPB model and TAM model were used to give better understanding on behavioral intention of consumers via online platform. Eight hypotheses were tested and all of them received support from data. Consistent with TPB model, all three antecedents in our proposed model: attitude, subjective norm and perceived behavioral control were positive contributors to intention toward renting clothes online. This study supported results from previous research in the area of online fashion renting (Lee & Huang, 2020; Lee & Chow, 2020).

The findings of this study suggested that Generation Z consumers’ intention to pursue online fashion renting is influenced by their attitudes, subjective norms, and their perception regarding how easy it is to rent clothes via online platform. Among these three direct antecedents, the latter had highest impact on intention of young generation to hire fashion items online. This may result from the fact that fashion renting in Vietnam is only limited in wedding and performance costumes rather than daily clothes. Therefore, when considering whether to engage in an unfamiliar activity such as hiring regular clothes online, young consumers may consider the difficulty or ease of the action. This could suggest that the online platform for hiring clothes should be designed in a consumer-friendly mode with useful information for clients.

Furthermore, to shape young consumers’ attitude toward renting clothes online, it is also important to raise their awareness of sharing consumption benefits. Their attitude can be influenced by perceiving that hiring clothes online is useful as and easy to apply. For young consumer perspective, this service could utilize their benefits as it save their time and money but give them chances to try different fashion stuffs. Otherwise, businesses pursuing collaborative consumption should strive to engage customers with this type of consumption and its convenience. For developing country like Vietnam where this kind of service is still rare, businesses can begin by provide both brick–and–mortar shopping along with online service for clients’ experience of fashion rental. Also, the online platform should be organized with collections for different occasions, categories, and brands so that consumers can easily find what they need. By streamlining the rental process, online fashion rental could become more efficient and attractive to young consumers of Generation Z (Lee & Chow, 2020).

In our study, subjective norm, although proven to be significant and positive antecedent of behavioral intention, shows lesser impact than attitude and perceived behavioral control. This is different from previous empirical studies by Lee and Chow (2020) and Lee and Huang (2020) that subjective norm is the best direct predictor of online fashion rental. Such difference may because the target of this study, Generation Z, is found to be more individualistic and self-directed than other generations (Singh & Dangmei, 2016), so they may consider their own opinions and concerns more than others’.

Another finding of this paper was that subjective norm is significant influenced by three elements: interpersonal influence, E-WOM, and influencer e-marketing. Such results may partly be because of two reasons. Firstly, Internet access and e-commerce in Vietnam is developing very fast so consumers are surrounded by huge amount of online information. Secondly, Gen Z members are those who are born and raised with social web and are highly depend on technology (Singh & Dangmei, 2016), therefore they are easily influenced by comments, judge or sharing from other Internet users and influencers. Therefore, business managers of this service may apply different online advertising and sharing channels to touch the intention of young consumers on renting clothes.

6. Contribution, Limitations, and Future Research Directions

With distinctive characteristics, marketing to Generation Z can be a challenge that requires more insights in specific context. By applying TPB and TAM models to examine behavioral intention of Generation Z toward online fashion rental, this study enriched the literature of sharing consumption in a developing context as well as provided better understandings on this young generation.

Another main contribution compared to prior studies is the combination of TPB theory and three constructs of TAM model: E-WOM, Influencer e-marketing, and subjective norm. This study will contribute as an example of valid model for further research with the similar concern and provide deeper look into different components of the theory. Base on the findings of this paper, online platform service if proved to be a convenient and attractive way to target Generation Z as customers and e-marketing using KOLs can be useful to increase their awareness and engagement.

Table 5: Estimates of Structural Equation Coefficients

In the Vietnamese context, topics of online fashion rental is fresh with limited existing research. This study provided fundamental implications for managers, marketers, and policymakers with a new trend for online fashion rental targeted young people in the form of sharing economy.

Due to exploratory nature of this study, there are limitations, which may suggest directions for further research opportunities. First, this research adopted a convenience sampling method that may limit the possibility of representing the whole Generation Z. Future research could use a larger and more representative sample. Otherwise, different generations such as X or Y can be included for further comparison purpose. Second, the sample used in this study was mainly distributed to the young customers who has not experienced online fashion renting. Thus, it would be interesting to examine more comprehensive attitude-behavior by comparing between those experienced with online fashion renting and those are without this experience. Lastly, future studies may explore the possibilities of mediation, moderation of various factors in the TPB and TAM model for better understanding of relationships among variables.

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