Critical Factors Influencing Consumer Online Purchase Intention for Cosmetics and Personal Care Products in Vietnam

  • NGUYEN, Lan (Faculty of Accounting and Auditing, Van Lang University) ;
  • LE, Hoa Chi (School of Information Technology and Digital Economics, National Economics University) ;
  • NGUYEN, Thuy Thu (NEU Business School, National Economics University)
  • Received : 2021.05.15
  • Accepted : 2021.08.02
  • Published : 2021.09.30


With the rapid development of the Internet, online shopping has grown so fast that almost any good or service can be sold online today. The popularity and rapid growth of e-commerce signal a huge market opportunity for e-retailers. From the organizational perspective, it is necessary to evaluate and explore what drives customers to buy their products or to use their services. This study, therefore, aims to explain the online purchase intention and its determinants of Vietnamese customers for cosmetics and personal care products. Quantitative data was collected from an online survey conducted among university students, then was put into SPSS and AMOS for further analysis. Descriptive statistics, Cronbach's alpha test, exploratory factor analysis (EFA), regression analysis, and SEM were used to examine data from 434 valid answers. The research findings reveal that four factors positively affect purchase intention: Shopping enjoyment has the most significant impact, followed by trust, benefit, and website quality. On the other hand, perceived risk negatively influences purchase intention. While the cosmetics and personal care industry is thriving with a huge number of producers and consumers throughout the world, this study contributes to the existing literature in terms of capturing customers' needs and developing effective strategies to attract more online users.


1. Introduction

In 1992, the Internet became a magical portal into the techno-future, ushering in a new era of commerce and trade. After its progression into a global network of connectivity, the Internet has grown from a technical technology system into a helpful marketing tool for both domestic and international markets. During that time, electronic commerce then developed globally and became well known as e-commerce. According to Statista, global retail e-commerce sales amounted to US$ 3.53 trillion, and e-retail revenue is expected to rise to US$ 6.54 trillion in 2022 (Leong et al., 2018). The continuous growth in revenue shows that e-commerce has tremendous business potentials. This significant increase is due to an increase in mobile Internet usage as well as the proliferation of social networking sites (Leong et al., 2018). Thus, it is not shocking that 53% of Internet users worldwide used mobile devices for online shopping in 2017. These days, owing to the enormous increase of Web users and online transactions, e-commerce is deemed the key component of the modern business environment (Lu & Wang, 2018). Compared to conventional shopping, which is typically associated with crowding, congestion, time constraints, parking space, or travel costs, purchasing online is preferable because it is much more convenient. E-commerce, therefore, helps customers control everything and enables them to purchase products or services online from anywhere.

Today, e-commerce can be sustained at a much lower cost than traditional business models. It has become an extremely important channel for retailers, powered by quicker delivery, lower prices, and faster buying time. Additionally, e-commerce entails little extra investment (a website is adequate) from businesses and allows access to markets generally regarded as out of reach (Hernández et al., 2009). With the benefits and opportunities that e-commerce provides, companies can expand their businesses all over the globe and connect to individuals worldwide. The success and development of global e-commerce platforms such as Amazon, Alibaba, Shopee have set an example for businesses to change their business model from brick-and-mortar to brick-and-click (Hernández et al., 2009). Many companies have had online stores to enable customers to browse information and purchase products/services at a comparatively low cost through direct contact (Kim et al., 2005).

In Vietnam, purchasing Internet-based products is increasing at an exponential rate. Approximately 66% of the Vietnamese population are Internet users, and 47% took part in online shopping and made online transactions (Vietnam E-commerce and Digital Economy Agency, 2020). Vietnamese online market generated a sale of US$12 billion in 2019 with an estimated growth of 29% in the following years until 2025 (Vietnam E-commerce Association, 2020). Among the most popular items of e-commerce, the cosmetics and personal care market are considered one of the strongest sales conductors. Vietnam’s beauty market had a value of $2.35 billion in 2018 with a wide range of distribution networks, supported by the flourishment of cosmetics stores and the rise of online distribution channels. Accordingly, about 34% of purchase is performed in online web stores and department stores, and 26% of Vietnamese shopped for beauty products once every two to three months online (Vietnam E-commerce Association, 2020). Higher living standards, a steady rise in average income, and the rapid development of social networks have all contributed to the cosmetics and personal care market’s robust revenue growth. Notably, easy access to the Internet, especially by using mobile phones, allows customers to stay up-to-date with beauty trends faster and search for product information more easily.

Despite the benefits and positive outcomes that e-commerce brings, consumers are still reluctant to purchase on e-commerce websites (Dachyar & Banjarnahor, 2017). Customers’ hesitation to purchase arises from several problems with online shopping. Trust in online payment methods is still low because only a small proportion believes that online shopping is safe. Most Internet users only use the Internet to search for information, price, and reviews about products, but they hesitate to make online payments or product reservations. They would prefer shopping in the physical stores and buying items they saw on the site to purchasing online. Additionally, lack of purchase intention is a significant challenge to the growth of e-commerce. Therefore, businesses must investigate various aspects of the online market and consumers’ purchasing habits to fulfill customers’ needs, thus converting potential visitors into customers, and increasing current consumer purchases (Forsythe & Shi, 2003). In the context of e-commerce, identifying key factors that affect customers’ purchase intention helps e-retailers attract more browsers and enable their websites to reach customers more efficiently.

So far, many researchers and practitioners have studied antecedents of online purchase intention (Dachyar & Banjarnahor, 2017; Choon Ling et al., 2011); however, only a small proportion of studies has been conducted in Vietnam, and knowledge of online shopping in Vietnam is still limited (Phuong & Dat, 2017). Furthermore, these studies just reviewed the general e-commerce market instead of specific industries like cosmetics and personal care. With the circumstances of online cosmetics and personal care purchases, this study examined variables that have rarely been mentioned in previous research. The results are also different in that it focuses on the millennial generation, as opposed to previous studies, which include all generations.

Purchasing online has accelerated, particularly during the global crisis of COVID-19, and it may result in a massive shift in purchasing behavior across the entire market. For experience and touch products like cosmetics and personal care, such a focus elaborates complicated issues in identifying key factors that affect customer behavior and provides successful beauty direct marketing strategies. Considering the potentials for strong expansion of the Vietnam e-commerce market, the findings also suggest strategic directions for beauty companies to sell products more effectively.

The rest of this paper is structured as follows. In Section 2, the research problem statements and hypotheses are presented. In Section 3, the questionnaire design and sample analysis are listed. In Section 4, data collection and analysis are examined. Finally, conclusions and discussions are organized in Section 5.

2. Literature Review

One of the most vital business issues is understanding consumers’ behavior and convincing them to purchase products more. To predict customers’ behavior correctly, so many studies on the importance of purchase intention have been carried out. Purchase intention is defined as a measure of the strength of one’s intention to perform a specific behavior or make the decision to buy a product or service. (Truong, 2018). According to Ajzen (1991), intentions are assumed to show how individuals are inclined to carry out certain behaviors; if people have a greater intention to buy something, they are more likely to make the actual purchase. The theory of reasoned action (TRA) suggests that customer behavior can be predicted from the intention that corresponds directly in terms of action, objective, and context to that customer’s behavior (Ajzen & Fishbein, 1980). A considerable number of authors also have acknowledged that purchase intention is a significant predictor for the actual decision to buy (Kim et al., 2008). In the context of e-commerce, purchase intention is concluded to highly impact online shopping behavior and finally leads to action in real life.

Over the past decade, both internal and external factors are explored as influences on online purchasing intention. However, unlike simple IT adoption, online beauty buying behavior entails not only IT adoption but also hedonic consumption activity. Online consumers, especially millennials, must possess the characteristics of both hedonic-oriented IT adopters and buyers. In this study, the authors examine five variables, which are trust, benefit, perceived risk, shopping enjoyment, and website quality in relationship with purchase intention. Specifically, trust is believed to be the most critical factor in securing customer loyalty, engagement, and strongly related purchasing intention (Hsu et al., 2014). Hong and Cha (2013) further noted that e-commerce companies should reduce the perceived risk due to the importance of risk reduction in online purchase intention (Crespo et al., 2009). Furthermore, online marketers should emphasize the advantages of online purchasing, either directly or indirectly, because the greater the benefits of online buying are regarded by consumers, the greater their intention to use the Internet for information search (Kim et al., 2004). Enjoyment also needs to be further studied as it is found to be a strong indicator of intention towards online shopping (Rehman et al., 2013). If consumers enjoy their online shopping experience, they have a more optimistic outlook on online shopping and are more likely to embrace the Internet as a shopping channel.

However, academic studies on five distinct stated significant features in the link with online purchasing intention for the cosmetics and personal care sector in Vietnam appear to be lacking. Thus, this research tries to better understand the role of various factors in the intention of beauty shopping.

2.1. Trust

Numerous studies have attempted to explain the strong influence of trust on the customers’ intention to purchase online. Trust is claimed to be a crucial factor for a company’s success in e-commerce (Lu et al., 2010). Furthermore, Lee and Choi (2011) add that trust plays a vital role in promoting exchange relationships and improving the long-00term relationship. Consumers do not want to participate in e-commerce because of a lack of trust (Kim et al., 2008). Trust is defined as the extent to personal assurance that the online stores will fulfill their commitments, act as anticipated, and pay attention to their buyers (Dachyar & Banjarnahor, 2017). Trust is also characterized as the consumers’ faith that e-business will not behave opportunistically (e.g., taking advantage of a situation) (Hong & Cha, 2013). In e-commerce, vendors are responsible for delivering useful information and helping customers to achieve their goals successfully. When there is a considerable degree of threat and uncertainty in online transactions, the importance of trust is even more important (Kim et al., 2008). In purchasing online, several parties will typically be involved, leading to different “trust objectives” to be evaluated (Hsu et al., 2014). While Kim et al. (2008) proposed that the company’s reputation, privacy issues, security concerns, and information quality greatly influence customers’ trust, Jarvenpaa et al. (2000) found that an online shop’s size and reputation determine consumer trust in the website. Thus, we hypothesize the following regarding trust for online purchase intention.

H1: Trust is positively related to online purchase intention.

2.2. Website Quality

Undoubtedly, for companies, a Website is a valuable tool for promoting their products and services to generate revenue from potential customers. Customers’ online purchase intention tends to be impacted by their understanding of the website quality. Therefore, companies ought to build appealing websites with useful content to draw more customers to their businesses. Multiple website layers, functionalities, qualities, and user ability to distinguish between different website characteristics are the factors for estimating website quality (Al-Qeisi et al., 2014). In addition, relevance, usefulness, up-to-datedness, and consistency of information are significant quality features of information websites. To be more specific, the aesthetic and layout design of the websites have a huge effect on their appearance (Sánchez-Franco & Roldán, 2005), which, in turn, affects the emotional responses of users. Effective navigation increases the ability of users to predict and conceptually go through website controls. And a viewer with a positive experience of a website is more likely to become a potential customer.

Perceived website quality is related to trust because using the website is the first perceptual glimpse of the vendor’s existence, reinforcing first impressions. As a result, if customers find the website to be of high quality, they are more likely to have a high level of trust in the online retailer’s competence, authenticity, and benevolence, as well as feel a desire to buy. Distrust is a concern that e-commerce businesses must address in terms of infrastructure and payment systems. If an e-retailer can provide a high level of convenience when purchasing online and build a payment system that can be used by a large number of people, it is likely that more people would shop online, whether payable in cash or uses the bank accounts (Wang et al., 2015). Therefore, we hypothesize the following regarding website quality for online purchase intention and website quality for trust.

H2: Website quality is positively related to online purchase intention.

H3: Website quality is positively related to trust.

2.3. Perceived Risk

Perceived risk is considered a salient factor to influence consumer behaviors when purchasing online. This is because online shopping generally entails greater uncertainty levels than in-store shopping (Chiu et al., 2009; Jarvenpaa et al., 2000). Risk is explained as a customer’s belief of uncertainty regarding possible consequences from online transactions (Kim et al., 2008). Despite many benefits of online shopping, buyers are unable to observe, touch or experience the items before deciding to purchase (Al-Debei et al., 2015). They appear, therefore, to perceive a greater degree of risk. Hence, it can be expected that the greater the worries of customers, the lower the intention of shopping online. Researchers have investigated different risks relating to online purchase intention; for example, Jacoby and Kaplan (1972) classified perceived risks into seven functional categorizations: financial risk, performance risk, physical risk, psychological risk, social risk, time risk, and opportunity cost risk. In the context of e-commerce, three types of risk are assumed to be prevalent: financial risk, product risk, and information risk (Bhatnagar et al., 2000). It is normal for buyers to be reluctant to purchase on the Internet when they notice the risks that could be unbearable compared to the traditional shopping method with the instantaneous shopping transaction (Dachyar & Banjarnahor, 2017). When the transaction is carried out, the e-vendors collect identities, email addresses, and purchasers’ contact information. Some vendors may leak out data to spammers, salespeople, and advertising agencies (Kim et al., 2008). In various ways, the prohibited gathering and sale of personal information could affect actual users, from simple spamming to deceptive credit card payments and identity fraud. As a result, lack of privacy is a primary concern for many online users (Katawetawaraks & Wang, 2011). In other words, if consumers perceive online shopping as risky, their intention to shop online will decrease. Therefore, we hypothesize the following regarding perceived risk for online purchase intention.

H4: Perceived risk is negatively related to online purchase intention.

2.4. Benefit

Although the Internet poses some dangers, it offers tremendous benefits to customers from a different perspective. The benefit is described as the extent to which a consumer will get advantages from the online transaction with a specific website (Dachyar & Banjarnahor, 2017). Many studies (Mandilas et al., 2013; Tanadi et al., 2015) have presented persuasive evidence about the significant role of benefit or its identified factor in increasing the behavioral intention to purchase on the Internet. The perceived value of online shopping can be determined by the level of product satisfaction and the advantage of online shopping (Tanadi et al., 2015). Individuals measure the value between what advantages are obtained and what sacrifices are made by performing activities based on utility’s net gain. Margherio (1998) stated that customers purchase on the Internet because they perceive benefits such as expanded convenience, cost savings, time savings, diversity of products, and payments to choose from compared to conventional shopping. When buyers benefit from an online transaction with certain websites, they are more likely to conduct online payments. Therefore, it could logically explain that one of the most important factors influencing consumers’ willingness to buy online is the utility and rewards of doing so. For this reason, we hypothesize the following regarding the benefit of online purchase intention.

H5: Benefit is positively related to online purchase intention.

2.5. Shopping Enjoyment

For the e-commerce context, hedonistic motivation is an important and frequently studied element in the acceptance of information systems. Perceived enjoyment has a direct impact on the online purchase intention, thus making websites more enjoyable would provide many benefits to online retailers (Van der Heijden & Verhagen, 2004). Enjoyment is an adaptive reaction and an inherent motivation that refers to the performance of a task without any obvious reinforcement apart from the process of conducting it. Enjoyment represents the hedonic or intrinsic characteristics of IT usage (Chiu et al., 2009). Online shopping enjoyment is defined as perceived satisfaction emerging from the website experience, the level to which customers generally perceive the behavior of using the website as enjoyable. Shopping enjoyment is correlated with temporary emotional reactions such as fulfillment, joy, and dominance (Koufaris et al., 2001). Consumers who love shopping get pleasure from shopping and spend time browsing for items (Seock & Bailey, 2008). The pleasure derived from visiting a website may increase online purchase intent amongst buyers by adding to a pleasurable shopping experience, and it is therefore critical for web-based businesses to comprehend the influence of website enjoyment. Entertainment components should be introduced to websites to attract consumers who appreciate shopping enjoyment such as offering users responsive communities to motivate customers to buy online (Seock & Bailey, 2008). Thus, we hypothesize the following regarding website quality for online purchase intention.

H6: Shopping enjoyment is positively related to online purchase intention.

The proposed model (Table 1) contains variables trust, website quality, perceived risk, benefit, shopping enjoyment, and online purchase intention. Overall, we expect that trust, benefit, shopping enjoyment, and website quality are likely to positively influence purchase intention, and perceived risk negatively affects purchase intention. Furthermore, website quality is expected to be positively related to trust (Figure 1).

Table 1: Results of Demographics Profile

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Figure 1: Research Model

3. Research Methods and Materials

The impact of trust, perceived risk, benefit, shopping enjoyment, and website quality on online purchase intention has been examined in this research. The authors used the quantitative survey method to distribute and collect data. An online survey was conducted among students in universities in Vietnam. The student samples’ validity might be questioned because the student population does not appropriately represent the general population (Yoo et al., 2000). However, Ahmad (2002) argued that university students reflect one of the most dynamic age categories in online shopping. University students, therefore, are considered an adequate sample to study. A pilot analysis of the questionnaire was carried out to validate the feasibility, consistency, reliability, and comprehensiveness of the questionnaire. For easy interpretation, the survey questionnaire is accessible in various sections, written explicitly by using plain language to encourage participants to provide accurate details.

All variables were measured with multiple items, which are listed in Table 1. The questionnaire has two parts. Part A is demographic information. Part B is respondents’ feedback about trust, perceived risk, benefit, shopping enjoyment, and website quality towards online purchase intention. Close-ended questions with a 5-point Likert type, which is a type of psychometric response scale in which responders specify their level of agreement to a statement typically in five points: (1) Strongly disagree; (2) Disagree; (3) Neither agree nor disagree; (4) Agree; (5) Strongly agree.

Before the official survey, a test was carried out to check the questionnaire’s validity and reliability. The collected data came from 462 participants, of which 28 questionnaires were invalid since the respondents provide a lack of online shopping experience or information. Hence, 434 answers were usable. The data was then analyzed using the analytical tool Statistical Package for the Social Sciences (SPSS) version 20 and Analysis of Moment Structures (AMOS) version 24. Different types of analyses were executed to test the hypotheses, including reliability and validity analysis, correlation analysis, and regression analysis. The hypothesized relationships among the constructs in the study were also analysed by employing structured equation modelling (SEM).

Based on the survey, 12.0% of the total respondents are males, and 87.1% are females. In terms of age distribution, participants’ age ranges from 15 to 35 years old, in which the majority of them were between 19–25 (89.2%). There are three education levels listed in the research: a high-school diploma, bachelor’s degree, and master’s degree. Most of the respondents have had an education at diploma level, accounting for 90.3% of the total sample. For frequency analysis, most of the respondents purchase cosmetics and personal care products at least one or more times per year (41.2%), and the second-highest purchase frequency is at least once a month (35.9%). The categories mainly earn below 9 million VND each month (93.3%), and 9–15 million VND being only 5.3%. Only 32 of 434 participants (7.4%) have never purchased cosmetics and personal care products online. However, 15 of them ensured that they plan to make online purchases. This indicates that e-commerce will continue to develop in the future.

4. Results and Discussion

4.1. Reliability and Validity

The mean value for all variables ranges between 3.47 and 3.96. Website quality has the highest mean (3.96), with a standard deviation of 0.685, follows by trust, benefit, perceived risk, shopping enjoyment, and purchase intention with a mean value of 3.94 (SD = 0.633), 3.83 (SD = 0.610), 3.82 (SD = 0.667), 3.60 (SD = 0.719), 3.47 (SD = 0.641) respectively. This reveals that respondents have an average level of agreement towards trust, website quality, perceived risk, benefit, shopping enjoyment. All the variables score a standard deviation lower than 1, which shows that the scores were clustered closely around the mean.

Reliability is the most common index to test the stability of items in a questionnaire. It is used to verify whether the scale items measure the framework in question; a value of 0.70 or higher is considered acceptable (Taber, 2018). Cronbach’s coefficient alpha was used to test the inter-item consistency of the scale in this study. As shown in Table 2, the results reliability analysis for all variables is greater than the recommended level and shows good reliability with Cronbach’s alpha exceeding 0.7 in each construct.

Table 2: Results of the Measurement Model

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The KMO test and Bartlett’s sphericity test were used in the factor analysis process. The results show that KMO is 0.788 and ensure the requirement 0.5 < KMO < 1. Bartlett is 2587.706 with a p-value = 0.000 < 0.05, so all of the variables in each component are correlated with each other.

Confirmatory factor analysis (CFA) was used to test the instrument’s convergent and discriminant validity. Both indicator loadings and average variance extracted (AVE) were tested for convergent validity. As shown in Table 3, all AVE values are higher than the recommended level of 0.5. All five components show high load factor values, and all variables load significantly on only one factor. The results of this analysis provide indications of the validity of the model. The discriminant validity is supported when the correlations between that construct and other constructs are less than variances extracted by the constructs. The square roots of the AVEs for the dataset were all greater than the correlations presented on the diagonals in Table 3, thus suggesting that purchase intention and the other four factors were clearly distinct. The measurement model was first tested to examine the proposed models’ goodness of fit (Table 4). The model exemplifies good fit to analysed data as confirmed by CMIN/df = 1.948 (<3), CFI = 0.954 (>0.9), GFI = 0.943 (>0.9), RMSEA = 0.047 (<0.06) suggested by Hu and Bentler (1999).

Table 3: Results of Model Validity

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***p < 0.001, **p < 0.01, *p < 0.05.

Table 4: Results of Fit Indices

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4.2. Hypotheses Testing and Discussion

The authors used the Structured equation modeling (SEM) technique to test mentioned hypotheses after examining the measurement validity and reliability. As shown in Table 5, most of the hypotheses are supported except for H5. For the regression analysis, the adjusted R2 is 0.448, which indicates that trust, perceived risk, benefit, and shopping enjoyment can interpret 44.8% of the variation in purchase cosmetics and personal care products online. This also means that other variables should explain the remaining 55.2%.

Table 5: Results of Hypotheses Testing

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The results indicate that while trust (β = 0.169, p < 0.05), benefit (β = 0.163, p < 0.05), shopping enjoyment (β = 0.529, p < 0.01) have significant positive effects, perceived risk (β = -0.113, p < 0.05) has negative effect on the intention to purchase cosmetics and personal care products online. However, purchase intention is not influenced by website quality (p = 0.313). On the other hand, website quality (β = 0.491, p < 0.05) is found to have a positive relationship with trust.

In this study, H1 emphasizes that when trust increases, the online purchase intention increases. It can also be inferred from this finding that customers have a high level of trust in cosmetics and personal care stores, and they believe that purchasing on these websites is trustworthy. In other words, if customers have a good awareness of company reputation, seller integrity, website popularity, they are more likely to purchase online. This is in line with the finding of Kim et al. (2008).

In terms of perceived risk, H2 states that purchase intention is negatively correlated with risks perceived by customers. This result is consistent with the results of previous research, which show that a major barrier to online shopping is a security issue, as customers are concerned about transaction security and data privacy. In addition to this, customers prefer to touch and feel beauty products before jumping to purchase decisions. They worry that e-sellers might deliver low-quality, damaged or fake products. And if problems with products happen, they need to contact online stores to get support, which is difficult. This result supports the findings of Mittal (2013).

In H3, it appears that the greater the advantages of online shopping perceived by consumers are, the greater is the intention to purchase products. Benefits come from advantageous attributes of online shopping in comparison with brick-and-mortar stores. Consumers agree that they can organize a suitable time to do shopping online, save money on sales occasions and buy a variety of products without traveling a far distance. This finding is aligned with the previous studies that stated benefit has a positive impact on purchase intention (Tanadi et al., 2015; Jarvenpaa & Toad, 1996).

In relation to shopping enjoyment, H4 demonstrates that shopping enjoyment has a significant impact on online purchase intention. This result is consistent with previous studies of Rehman et al. (2013) and Chiu et al. (2009), who showed that shopping enjoyment is a salient indicator for intention to buy online. Consumers enjoying the online shopping experience are more likely to have the intention to use the Internet as a shopping medium.

Finally, although H5 indicates that the effect of website quality on purchase intention is not supported in this study, H6 reveals that website quality positively influences trust. The relationship between trust and website quality is consistent with research conducted by Chang and Chen (2008). The result also suggests that website quality provides concrete clues that can be used to intentionally create consumer trust in a retailer’s competence and reputation.

Overall, shopping enjoyment is the most influential. This result was expected hedonic orientation motives have a significant effect on Vietnamese online purchase intention. Customers want to feel relaxed and pleasured when they buy items online, especially when they are cosmetics and personal care products. Young customers, mainly millennials who have been growing in the digital revolution, have distinct characteristics from previous generations. This causes consumers to have high expectations for the experience they receive when using a product or service. They are looking for enjoyment, comfort, social connection, and a pleasurable experience in addition to gathering information to shop online.

5. Conclusion

This study aims to provide a better picture of variables affecting purchase intention in the e-commerce environment. To be specific, purchase intention for cosmetics and personal care products is determined by trust, perceived risk, benefit, and shopping enjoyment. Furthermore, trust is influenced by website quality. Based on the proposed model of the linkages between the constructs, the results statistically support most of the proposed hypotheses. This study is thus useful in terms of throwing light on a thriving area in Vietnam namely the cosmetics and personal care industry and it may pave the way for future research on the topic.

For the cosmetics and personal care products, the findings demonstrate that shopping enjoyment should be considered first for predicting customers’ online purchase intention. Therefore, online stores should provide enjoyable shopping experiences such as offering a relaxing and stimulating shopping atmosphere to attract more customers. Moreover, websites can provide potential buyers with more ways to try beauty products to improve customers’ experience, such as augmented reality (AR) so that buyers can see how a product would look like on them.

Besides, as online beauty purchasers consider trust as a strong factor before making purchase decisions, a suggestion for e-vendors is to provide buyers with clear and updated information about products. Additionally, for businesses that only run in the e-market, the Website is their only means of publicity, and the quality of the Website is of major importance. Thus, companies should exploit websites’ navigability, usability, and design to increase customers’ trust. At the same time, creating a safe system and a reliable payment mechanism to alleviate the risks of online shopping is essential for online retailers.

In this study, the findings also imply that online marketers should stress online purchase benefits (e.g., time productivity, accessibility, comparatively lower prices, information consistency) directly or indirectly within the marketing communications process as the benefits of online shopping perceived by customers are relevant to intention to buy cosmetics and personal care products online.

Although this study has explained and provided guidelines for beauty businesses by deriving the scale of different factors influencing customers’ purchase intention, it has some limitations. As behavioral intention development is an ongoing phenomenon, a longitudinal study would perhaps be more appropriate. Besides, this study measured behavioral intention instead of actual consumer behavior. To overcome this limitation, future research can investigate factors affecting customers’ actual behavior. Another limitation can be related to the sample characteristics, which is the gender gap as the majority of the respondents are female in the age group of 18 to 25. Subsequent research may wish to address such limitations.


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