1. Introduction
During the explosive growth of the 4th industrial revolution, the role of digital economy has become pivotal in everyday lives. Digital economy is defined as an economy that is mainly based on digital technology; especially, it deals with electronic transactions based on the application of digital technology (Bukht & Heeks, 2017). Initially, a customer’s decision-making process has been researched from the perspective of the traditional business concept that buying action was conducted directly at selling points (Verhoef & Franses, 2003). Hence, consumer behavior has been studied within the market characterized by unstable demand for commodities together with high impulse buying decision which is made at the point of purchase (Koufaris et al., 2001). Recently, there has been an increasing number of businesses using the Internet to conduct business functions, including sales and distribution. The Internet has led to the rise of the computer-mediated market transactions in which products can be introduced and broadcasted to the buyers (Ngai, 2003). As a result, the process by which online customers’ decisions are received great attention from global researchers (Teo, 2006). While there have been numerous studies on digital consumer behavior, the analysis of customer behavior in the era of COVID-19 still needs to be examined. It is essential that more studies of consumer behavior in new context should be conducted to provide businesses and potential investors with meaningful implications.
The purpose of this paper is to explore factors that affect customer purchase decision in the online environment via digital business platforms, particularly after the COVID-19 pandemic and in the case of Vietnamese customers. Since the economic reforms started in 1986, Vietnam has rapidly grown from one of the poorest countries in the world to a lower middle-income country. By considering the rapid growth, investigating factors that affect Vietnamese customers’ decisions is necessary for better development of businesses. In particular, due to the COVID-19 pandemic, customers decision making has been shifted toward online and environmental friendly issues. Based on the consideration, the purpose of this research is to examine the effects of propensity to trust, system assurance on customers’ trust in purchasing decisions in the online environment and effects of trust, attitude, satisfaction, quality of web/app design on customers’ purchasing decisions. This study proposes the following research questions: i) How do perceived size and reputation, propensity to trust, and system assurance affect customers’ trust in purchasing decisions in the online environment? and ii) How do trust, attitude, satisfaction, quality of web/app design affect customers’ purchasing decisions?
2. Literature Review
The term “consumer behavior,” which refers to the way emotions, attitudes, and preferences affect purchasing behavior, first has appeared in the early 1950s as a separate social science concept closely related to the field of marketing (Tadajewski, 2009). Kardes et al. (2011) has defined consumer behavior as all consumer activities involved in the purchasing, utilizing, and removing of goods and services and in complying with the process of emotional, mental, and behavioral responses. Consumer behavior, in other words, has included personal thoughts and feelings experienced by individuals and the subsequent actions in purchasing processes (Familmaleki et al., 2015). The term also has dealt with all influential factors in the environment such as reviews from other consumers, commercials, price comparison, product labels and packaging (Chaniotakis et al., 2010). Consumers are the starting point and the end point of marketing; therefore, analyzing and understanding purchasing as well as consuming behavior are essential challenges for marketers (Lyons et al., 2005). Also, it is important to understand how purchase decisions are made and how products or services are consumed or experienced (Kardes et al., 2011). Different approaches have been made to develop intention-based theories and provide comprehensive explanations of factors that affect purchasing decisions of consumers (Oliveira et al., 2017).
Electronic commerce (E-commerce) has referred to the act of purchasing products and services via digital communications (Chaffey et al., 2019). The early stage of electronic commerce has been mainly focused on transactions among corporations though it was relatively restricted due to technical difficulties and financial costs (Gibbs et al., 2003). Nonetheless, by the 1990s, e-commerce rapidly has become popular among web due to the advancements and widespread accessibility of the Internet (Wymbs, 2000). From 1995 onwards, there have been several major digital commerce services available including household names such as Amazon or eBay (Javalgi et al., 2004). During this “golden age” era of online shopping, many businesses has started to utilize websites to build their presence and to transact online (Singhal, 2016). People also has begun to invest in Internet and e-commerce stocks; as a result, the “dot-com bubble” has been formed during this period (Wheale & Amin, 2003). Through the rises and falls, e-commerce has been proven its value to companies and customers (Tzavlopoulos et al., 2019). Progress in technology, as well as in the economy, has undoubtedly fueled the expansion of e-commerce (Nanda et al., 2021). Dai and Kauffman (2002) have been predicted that electronic commerce will play a crucial role in the economy’s development as it promotes international trading and investments. As the market grows, corporations must conduct studies on online consumer behavior to adapt to the new age of digitalization (Wymbs, 2011). Examinations of buyers’ perceptions in the purchasing process will allow us to forecast future e-commerce trends (Gudigantala et al., 2016). Additionally, consumer expectations such as product availability, delivery transparency, affordable shipping, and a smooth transaction are key factors to the success of a business (Goetzinger et al., 2006). Prior to this, there is a plethora of research on the consumer behavior of offline shopping (Pantano et al., 2020). However, unlike its conventional counterpart, e-commerce can have dissimilar influences on customers (Benlian et al., 2012).
The pandemic has had a great impact on the behavior of customers and has led to substantial changes in the way a typical customer makes buying decisions (Mehta et al., 2020). This has spurred several research to identify characteristics that influence customer behavior during this time. Mason et al., (2020) have analyzed the effects of ongoing COVID-19 pandemic and the authorities’ interventions on U.S. consumer behaviors and concluded that consumers tended to increase their virtual shopping and online purchasing. There are research studies that confirmed the expected changes in customer behavior in the early stage of crisis (e.g., Jha & Pradhan, 2020; Majercakova & Rostasova, 2021). Instead of applying preventive measures strictly to curb the pandemic through lockdown, isolation, and social distancing, some countries have now applied policies to maintain a safe threshold of cases, and gradually restore production and business activities (Jiang et al., 2021). Due to the insufficient number of research papers that examine changes in customer behavior in the era of the COVID-19 pandemic, more research needs to be conducted to fill the gap and continue to contribute to the understanding of customer behavior.
3. Theoretical Background
Psychological theories such as the theory of reasoned action (Fishbein & Ajzen, 1975) and the theory of planned behavior (Ajzen, 1985) have supported to explain consumer attitude, intention, and behavior. Fishbein and Ajzen (1975) have proposed the theories with a view to analyzing the psychological processes among beliefs, attitudes, intentions, and behaviors. According to TRA (Ajzen, 1988; Fishbein & Ajzen, 1975), there have been three main components of human behavior: 1) Attitude towards behavior as the key determinants of behavioral intention; 2) Subjective norm as the perceptions’ way of some groups or individuals; and 3) Perceived behavioral control with factors which probably promote or impede the behavior’s performance. Blackwell et al. (2001) have reported that consumers pass through several phases when they intend to buy certain products. The model of consumer behavior has been formed with buying processes including recognition of the problem, searching information, comparing consideration sets, purchasing, and after purchase behaviors (Blackwell et al., 2001). Demographic and social-economic characteristics have been analyzed in almost all studies that examine customer buying decision processes (e.g., Sarigollu et al., 2021). However, attitude and behavioral characteristics are also emphasized as important determinants of store brand proneness when compared to demographic and socio-economic characteristics (Baltas, 1997).
According to Szymanski and Busch (1987), perceptions of quality and products were major factors affecting individual buying decisions prior to demographic, psychological, and shopping behaviors. According to Gleim et al. (2019), two main factors that affect green behaviors of an individual include internal factors such as interest, altruism, willingness to conduct research and external factors such as organizational influence, media influence, and governmental influence. Manstead (2018) has stated external factors include culture, social class, personal influence, family, and situation. Cheung and To (2019) have addressed internal and external factors that affect the relationship between consumers’ attitude towards going green and green purchase behavior by applying an extended model of value-attitude-behavior.
With the advancement of modern science and technology, the Internet has become a crucial business platform for commercial activities (Clement et al., 2020). Therefore, the knowledge of consumers’ decision-making process and their attitudes toward online shopping is essential for businesses in planning marketing strategies or adjusting existing strategies (Mazurova, 2017). There is a considerable number of discussions conducted to ascertain the factors affecting customers’ buying decisions when purchasing products online at e-commerce vendors (Ali & Bhasin, 2019). Various aspects have been used to identify attitudes toward online shopping, namely, consumer trust (Doney & Cannon, 1997; Teo & Liu, 2007), the quality of e-commerce website design (Chen et al., 2010; Udo, Marquis, 2002), and consumer satisfaction (Giao et al., 2020; Muylle et al., 2004; Zviran et al., 2006). Researchers (e.g., Lee & Turban, 2001) has stated that empirical studies about consumer trust in online shopping are relatively insufficient, which to some extent obstructs an overall understanding of consumer trust in online buying actions. This research paper focuses on customers’ purchasing intentions in the online environment in Vietnam. The suggested model is based on theories and related literature reviews on customer trust, customer satisfaction, and quality of e-commerce websites. Proposed factors affecting consumer buying decisions in this study include trust (perceived size and reputation, system assurance, propensity to trust), customer attitude, customer satisfaction, and the quality of website design.
4. Hypothesis Development
4.1. Effects of Consumer Trust on Online Purchasing Decisions
B2C e-commerce activities are indirect interactions that take place between customers and e-commerce vendors through websites or applications (Vakeel et al., 2017). Since there are uncertainties involved with online transactions, consumer trust plays a pivotal role in many financial interactions. As a result, trust has been argued as an essential factor affecting successful proliferation (Gefen, 2000). Lee and Turban (2001) have concluded that trust is formed by customer expectations and behavioral intentions. Based on literature review, trust is a multi-dimensional concept. The significant dimensions of trust rely on the condition of interactions (Bendoly et al., 2005; Walczuch & Lundgren, 2004), and trust contains two behavioral elements: intention and cognition (Bollen, 1989). This research paper uses three sub-factors of trust: perceived size and reputation, system assurance, and propensity to trust. Prior research has provided sufficient evidence that lacking customer trust is the main obstacle to attracting the participation of consumers on e-commerce vendors (Jarvenpaa & Tractinsky, 1999). In other words, trust is the most effective method of reducing perception of risk and an essential antecedent to actual purchasing decisions (Doney & Cannon, 1998; Mayer et al., 1995). Therefore, this study hypothesizes the following:
H1: Consumer trust positively affects purchasing decisions in the online environment.
4.2. Effects of Propensity to Trust on Trust of Online Purchasing Decisions
individual’s willingness or the tendency to trust or distrust others. Individual’s propensity to trust is influenced by cultural background, personality type and previous experiences (Mayer et al., 1995). Individuals are considerably different from each other in their propensity to trust due to dispositional trust rooted in the good nature of people (Mcknight & Chervany, 2001). When information about trustworthiness is ambiguous, propensity to trust, or an individual's inclination to trust, is connected with intention to trust, but not when information about trustworthiness is explicit (Gill et al., 2005). Researchers have had a comparatively consistent conclusion that propensity to trust is related to customer trust. Therefore, this study hypothesizes the following:
H2: The individual’s propensity to trust is positively related to customer trust in purchasing decisions in the online environment.
4.3. Effects of System assurance on Trust of Online Purchasing Decisions
Teo and Liu (2007) have defined system assurance as the reliability and security of an online transaction system. As mentioned by Ganguly et al. (2010), the ambiguity or uncertainty of online transactions could have led to insufficient trust. The assessment of system assurance originally has taken place in the realms of security and dependability of the transactions on e-commerce websites. These transactions have involved sharing private information of credit or debit cards (Kini & Choobineh, 1998). Therefore, ensuring system safety has been considered as one of the important factors that make customers trust and, thereby, promote online purchases. Therefore, this study hypothesizes the following:
H3: System assurance positively influences customer trust in purchasing decisions in the online environment.
4.4. Effects of Perceived size and reputation on Trust of Online Purchasing Decisions
The term reputation refers to “the extent to which buyers believe a seller is professionally competent or honest and benevolent” (Doney & Cannon, 1997). A company's reputation is a valuable intangible asset based on its past performance and behavior (Iwu-Egwuonwu, 2010). However, reputation is a delicate asset that can be easily tarnished or damaged, as in cases of scandals (Teo & Liu, 2007). Furthermore, a vendor’s size refers to its overall size and market position (Son et al., 2014). Consumers have been aware of the size and reputation differences among Internet retailers, and these differences influenced their perceptions of store trustworthiness, risk perception, and proclivity to patronize a store (Jarvenpaa et al., 2000). Large brands typically have better consumer credit than e-commerce vendors. Therefore, this study hypothesizes the following:
H4: The perceived size and reputation positively affect customer trust in purchasing decisions in the online environment.
4.5. Effects of Quality of website design on Attitude, Satisfaction, and Online Purchasing Decisions
Websites are mediate platforms designed and developed by organizations to enable and facilitate business activities using the Internet (Udo & Marquis, 2002). While there exists no universally accepted definition for quality of website design, the following issues have applied to measure the quality of website design including cohesion and consistency, navigation, response time, advertisement, interactivity, graphics and aesthetics issues, frames and other features such as payment or discount (Chen, 2006). Quality of website/ application is found to influence other antecedents of purchasing decisions like satisfaction, loyalty, and trust (Yoon, 2002). In B2C e-commerce, quality of website/ application is concluded to affect customer satisfaction (Lin, 2007). Some studies have showed the significance of these impacts on customers’ purchasing intention that elicit or spur purchasing decisions (Abou-Shouk & Khalifa, 2017; Mulyana et al., 2020). Therefore, this study hypothesizes the following:
H5: The quality of website design positively influences on trust, attitude, satisfaction, and purchasing decisions in the online environment.
4.6. Effects of Attitude on Online Purchasing Decisions
According to Eagly and Chaiken (1998), attitude is defined as a psychological tendency expressed by evaluating a particular entity with some degree of favor and disfavor. It is a long-lasting favorable or negative appraisal system, feelings, and a proclivity towards pros or cons action of a social object (Erevelles & Fukawa, 2013). It affects an individuals’ decision in every action and the way they respond to obstacles, incentives, and rewards. Attitude includes the following four distinct components: (1) emotions or feelings, (2) beliefs or opinions held consciously, (3) inclination for action, and (4) positive or negative responses to stimuli (Teo & Pian, 2004). The effects of attitude on purchasing decisions on online environment have been confirmed by studies of Warayuanti and Suyanto (2015) and Gunawan and Huarng (2015). Therefore, this study hypothesizes the following:
H6: Attitude has a positive impact on customers’ purchasing decisions in the online environment.
4.7. Effects of Satisfaction on Online Purchasing Decisions
Customer satisfaction refers to the feeling of happiness or disappointment after perceiving the performance of a product or service in comparison to customers’ expectations (Ullah, 2012). Manufacturers and sellers should put themselves in customers’ position to see expectation and consumers’ satisfaction from products or services (Ramani & Kumar, 2008). Prior studies have analyzed both consumers’ formulation of their pre-purchase decisions and the way they form their long-term relationships with website vendors. The results have indicated that satisfaction plays a pivotal role in consumer’s purchasing decisions, both in direct and indirect ways (Kidane & Sharma, 2016). Therefore, this study hypothesizes the following:
H7: Customer satisfaction positively affects online customers’ purchasing decisions in the online environment.
5. Methodology
The purpose of the study is to sample opinions of customers in the online environment to determine critical factors that affect their behaviors. The respondents were selected randomly to represent Vietnamese consumers. An online survey was designed and utilized to collect data from customers who have experiences of e-commerce. Questionnaire items were developed based on the previous literatures. Before the main survey was conducted, the questionnaire was tested by some experienced internet users, who were asked to fill in the form and critically evaluate each item. After questionnaire items were modified, the main survey was distributed to the most well-known social networks in Vietnam including Facebook, Zalo, and Lotus. To attract more respondents, public groups on Facebook were selected and offered gifts. The sample size was estimated according to the formula proposed by Kaufmann et al., (2012). The survey was open for about 2 weeks and a total of 356 respondents completed the survey with the response rate of 83%.
The survey questionnaire was designed with two sections. In the first section, general questions including demographic information such as age, gender, residence, monthly income and Internet usage experience such as frequency, and purposes of using internet and online purchasing experience such as percentages of buying goods and products online, preferred e-commerce, product types that were purchased, intention to buy goods and products online, etc. In the second section, respondents were asked to indicate the extent to which they agree or disagree with the statements on the google form survey. Five-point Likert scale ranging from 1 - Strongly Disagree to 5 - Strongly Agree were applied for main questions. As the survey targeted Vietnamese internet users, the survey was translated into Vietnamese. Table 1 below summarizes the list of indicators used to measure each variable and the source.
Table 1: Measures of Model Variables
Source: Doney and Cannon (1997), Gefen (2000), Jarvenpaa et al. (2000), Jarvenpaa and Tractinsky (1999), Teo and Liu (2007), Kini and Choobineh (1998), Gefen (2000), Tadajewski (2009), Udo and Marquis (2002), Palvia (2009)
6. Data Analysis
6.1. Demographics
Online customers frequently have used the internet for multiple reasons, including studying, working, entertaining, searching for news and information, and shopping online. The results have showed that the majority of online shoppers in Vietnam were women under 35. As shown in the survey, the most common scale of monthly income has been \(\$\)220; individuals with the salary of \(\$\)220 to \(\$\)440 have taken up 58.4% to 25.8% of the whole nation’s population. Besides, Shopee is the most popular e-commerce vendor in Vietnam, where nearly 90% of Vietnamese customers have made transactions. Cosmetics have been the most popular commodities which account for 61.2% of consumers’ visits, followed closely by clothes (49.9%), gadgets (44.7%), food (40.4%). Nearly 85% of Vietnamese indicated their intentions to continue buying products online, which implies positive prospects for e-commerce vendors in Vietnam. Respondents’ demographic characteristics are summarized in Table 2 below:
Table 2: Summary of Demographics
This study conducted reliability test. As shown in Table 3, Cronbach’s alphas were greater than 0.7.
Table 3: Results of Construct Reliability
6.2. Hypothesis Testing
The results of structural equational modeling using the data from 356 respondents are shown in Figure 1:
Figure 1: Structural Equation Modelling
The results of indicators from the structural equation modeling have showed the results of CMIN/df are good fit. The results of GFI has been 0.939 that is acceptable as it is greater than 0.9. The results of GFI have showed 1.000, therefore, the results are satisfactory. The results of RMSEA was 0.000, therefore the results have showed good as it is smaller than 0.06. In addition, the results of PCLOSE showed 1.000, therefore the results have confirmed the model fit as it is smaller than 0.08. Therefore, overall, the result have showed acceptable. Meanwhile, SEM assumptions have fulfilled in terms of normality, reliability test, and validity test. The results were summarized in Table 4:
Table 4: Results of Regression Analysis
*** Significant at 0.01 level ; ** Significant at 0.05 level
Based on the results of regression analysis, p-value of propensity to trust showed greater than significance level of 0.05. Therefore, the effects of propensity to trust on trust showed insignificant, while other hyptheses have been accepted. The results of hypotheses testing using the structural equation modeling have been summarized in Table 5:
Table 5: Results of Hypothesis Testing
6.3. Results of ANOVA test and Independent Sample T-Test
One-way ANOVA test and independent sample T-test were conducted to check the statistical differences between the means of age, income, and gender. In other words, ANOVA test has been applied to check whether age, gender and income influence the decision to buy products on website or mobile application. Therefore, ANOVA results can provide useful information for e-commerce vendors to adjust their business to fit each group of the customers. Another ANOVA test results have showed that online purchasing decision of the respondents were not different based on age groups and income levels. The ANOVA result in this research study showed inconsistent with that of Slabá (2019), who proved that there were statistically significant differences among several age groups. The inconsistency in the research results have revealed the diversity of customer behaviors in different contexts. Regarding gender, independent sample’s t-test has showed that there is no significant difference in the purchasing decision based on gender.
7. Conclusions
7.1. Summary
This study empirically investigated antecedents for Vietnamese consumers’ purchasing decisions in e-commerce vendors. The results of this research have revealed that perceived size and reputation and system assurance positively affect customers’ trust while the effect of propensity to trust on trust has not been significant. The results also have showed that effects of consumers’ trust, attitude, satisfaction, and the quality of website design on purchase decisions in the online environment have showed significant. The result of the model has provided useful implications for B2C businesses that target the Vietnamese market and consumers. The results of the structural equation model have showed that customers’ attitudes toward purchasing products, satisfaction with online shopping experiences, customer trust, and the quality of web/app design all influenced Vietnamese customers’ purchasing decisions in an online environment conducted via websites or mobile applications. Regarding the effect size, customer trust has had the highest impact on customer decision among the variables with implication that increasing customer trust in e-commerce vendors can significantly increase purchasing decision of goods and services. Perceived size and reputation have had significant impacts on customer trust, therefore large-scale e-commerce suppliers with a high reputation would be more likely to gain customer trust than smaller-scale e-commerce vendors. Customer purchase decisions have been influenced by the quality of web/app design. Consumers’ purchasing decisions are influenced by the quality of web/ app design both directly and indirectly; therefore, improving the quality of web/app design would aid businesses in cultivating a favorable customer attitude, providing satisfying buying experiences, and gaining customers’ trust.
7.2. Managerial and Policy Implication
Apart from the traditional business model where buyers can interact with sellers directly and examine goods cautiously, buyers first interact with e-commerce vendors through a website or application. Most Vietnamese people are still not used to buying goods online due to their apprehension about the quality of goods or insecurity of online payment. Many consumers are attracted by stunning images and graphics on websites or applications, while other consumers may not be attracted by those that vendors post themselves since there are chances that sellers might not be truly honest about their products. Therefore, the best way for businesses to build customer trust is to improve website effectiveness. Short loading time, ease of navigation, high-quality graphics usage, and interactivity are factors that can be improved. Secondly, e-commerce vendors should avoid exaggerating product quality and provide detailed information to build the trust. Thirdly, a secure payment system needs to be developed by a professional who can support customers’ purchase decision. Minimizing unnecessary procedures to make the purchase process secure, quick, and convenient will help improve efficiency the buying process. Customers are becoming more and more cautious about providing payment information on the internet. Therefore, various forms of payment provide customers with more options in paying, including those who are afraid of paying in advance. There are many popular payment methods, such as payment on delivery, advance payment by bank transfer, payment through 3rd party, payment via ATM cards or Mastercard, etc.
This study provides managerial implications. With the presence of Internet, the role of customer relationship management has been addressed to build better relationships with customers in the context of online environment. Online businesses have adopted advanced technologies, such as recommender system, customized services, and interactivity via virtual reality to enhance satisfaction and loyalty, while such technologies also help minimize customer dissatisfaction and complaints. The results of this study have confirmed that building customer loyalty and trust are key factors for the success of an online business. Online businesses should put better effort to improve customer satisfaction, minimize complaints with prompt and customized responses, and make suggestions to customers about product services or after-sale services in professional manner. In particular, the results of this study implied that business transactions with considerations of sustainability and environment issues should be addressed in the era of post COVID-19.
7.3. Limitations
Due to the time and financial constraints, the research has some limitations as listed below. (1) The coverage of the study is limited to a sample of 356 respondents who are mostly Vietnamese. Future research can be carried out with surveys conducted on global customers to examine the differences in consumer behavior due to cultural backgrounds. (2) Together with technology innovation, there might emerge new selling channels that affect customers’ buying decisions. Future researchers can extend and update the model for better evaluation and examination.
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