Introduction

According to Shang & Zhu (2020), people spend at least 50% of the day on social networks like Facebook, Twitter, Instagram, etc. Therefore, promoting brands through these social media channels makes many people know your brand. Besides, website traffic will also increase because the traffic coming from social is very large and accessible. However, businesses need to invest sufficiently in advertising content to attract readers more effectively.

Cost Savings: Advertising through social media is the best way to improve sales for the business. Almost everything does not need to pay anything when conducting advertising on social networks (except, of course, when you run ads on Facebook and Google). Regardless of a small budget, if you know how to make an intelligent brand, vital viral. Your business name will be known to more people and develop faster than the traditional way of branding, and the cost minimized.

Customers Easily Interact with the Brand: Perhaps the most exciting thing about Social Media is the closer customer interaction with your brand. People can freely rate, comment, and give opinions about your products/services. Businesses will easily monitor and control the information flow and promptly respond to customer requests on social networks by Barreto (2013).

In addition, businesses need to make an effort to listen to criticisms and quickly correct them immediately. Don't let customer problems linger for too long if you want your business' reputation to take a hit by Boateng & Okoe (2015).

Market survey is more convenient: Previously, businesses had to hire an agency to conduct surveys in real life. Now let's take advantage of the power of social networks, combined with online survey tools, to do just that. Now sit at home and still capture the market.

Support for Search Engine Optimization (SEO) Work: Facebook, Google, Instagram, etc., are 3rd parties, not your property. The only thing that belongs to you is just your brand website. Therefore, all businesses' efforts to promote social networks need to be directed to the website, increasing website traffic. Google search rankings also improved. Social media marketing is a very effective form of marketing for businesses. It helps companies to increase sales and increase brand awareness in the market at a much cheaper cost than traditional marketing. It is an excellent opportunity for young people to learn, explore and develop their careers in digital marketing. Therefore, the article explores various factors affecting online shopping attitudes based on social media advertising in Vietnam.

Literature Review

Intention (INT)

The essential element in the model is the intention to perform (Chin, Lu & Wu, 2015). According to Cheng & Huang (2013), the intention to purchase social networks is the primary outcome variable of this study. Behavioral intention is understood as "the strength or weakness of a person's willingness to perform a particular behavior" by Cheung & To (2017). In this study, purchase intention on a social network is related to the respondents' intention to perform the act of clicking on an advertisement on a social network (e.g., Facebook) in search of relevant information by Kowsky (2020). Regarding this advertisement when appearing on social networks. Evaluating a customer's intent to perform a behavior will provide advertisers with the opportunity to see how customers will fulfill their intent.

Behavior in the Theory of Planned Behavior (TPB) refers to observable manifestations of conduct, which are done (or not done) concerning a goal. The relationship between intention and behavior has been found in many studies involving many different types of behavior, applied research in other contexts, particular, in a given situation, in a specific time by Wurran & Jennon (2020).

Behavior (BEH)

Behavior in the TPB model refers to observable manifestations of behavior, performed (or not performed) with a particular goal, in a given situation, at a specific time by Celebi (2015). Qamal & Ful (2020) also suggest that the most crucial premise for performing a behavior is the individual's intention to perform the behavior. Intention to perform a behavior is understood as "the degree of strength or weakness to which a person intends to achieve a particular behavior by Mahmoud (2012). The TPB theory holds that the stronger the intention to engage in a behavior, the more likely it is that the intention will be fulfilled. Unlike TRA, TPB theory offers three premises (instead of two) that determine the intention to perform a behavior: attitudes, subjective norms, and perceived behavioral control. In addition to the attitudinal factors and personal criteria mentioned in TRA, perceived behavioral control refers to the ease or difficulty of performing the behavior. It is believed to reflect the experience and the anticipated obstacle or impediment by Mir (2014). The TPB theory states that the more favorable attitudes, subjective norms, and ability to control behavior are perceived, the stronger the intention to perform the behavior (under consideration). It should also be noted that, in many empirical studies in different fields by Zhou & John (2020).

The TPB theory holds that salient beliefs are seen as decisive antecedents about an individual's intentions and actions. Three important cognitive types are confirmed in the TPB theoretical model, including cognitive behaviors considered to influence attitudes. Besides, normative perception is regarded as the premise of the subjective normative element; controlling perceived behavior is considered an antecedent of perceived behavioral control (Torres, 2015).

Attitude (ATT)

One of the most important ways to understand customers, their feelings, and their behavior towards advertising is to study attitudes. Attitudes have played an essential role in the history of psychosocial research by Kowsky (2020). Attitudes here reflect a person's favorable or unfavorable evaluations, perceptions, and feelings about a particular behavior. There have been many studies related to the relationship between intention and behavior online in general and social networks. Rang (2020) found that intention to use Internet banking positively relates to behavior using Internet banking. Miner (2019) suggested that attitude towards advertising positively affects the intent to click to view the advertisement and online shopping frequency. In another study, Roares & Pinho (2020) found that people who have a positive attitude towards advertising influence their intention to perform behavior towards Web advertising.

In the context of social networks, research by Tabir & Ahmad & Foor (2020) shows that the intention to use social network has a positive influence on the actual use behavior to purchase online. Thih & Fang (2020) also found a significant, positive effect of intention on online purchasing behavior. In general, a behavior can be predicted by the intention to perform the behavior with considerable accuracy. Therefore, it is reasonable to assume a relationship between online purchase intention through social media advertising. Based on the above, we have the following hypothesis H1:

Hypothesis H1: Attitude (ATT) has a positive relationship with online shopping intention based on social media advertising in Vietnam.

Subjective Standards (SUB)

Subjective standards or normative perception is for buying goods on social networks. Subjective norm refers to the individual's perceived social pressure to perform or not perform a behavior by Wodgers & Thorson (2020). According to Gironda & Korgaonkar (2014), research for social networks, an example of subjective norm might be individuals or groups important in an individual's life, such as friends and social network members. Besides, personal standards will the family feel about using social networks, seeing ads on social networks by Lin & Kim (2016). The higher the perceived social pressure to perform each behavior on a social network, the greater the intention to perform that behavior. Since social media is social, it is reasonable to assume that others and peers or pressure from a family will influence a person's behavior. Lee & Hong (2016) showed that group norms positively influence group intention, group intention affects individuals' perceived advertising value. In turn, perceived advertising value positively affects an individual's perceived advertising value. Influence the user's behavior towards advertising on social networks, such as clicking on ads, paying attention to ads.

Similarly, Knoll (2015) also demonstrates that subjective norm positively affects the intention to click on advertisements appearing on social networks. Therefore, the personal standard can be seen as having a positive relationship with the behavior of activities on social networks. Based on the above, we have the following hypothesis H2:

Hypothesis H2: Subjective standards (SUB) positively affect online shopping intention based on social media advertising in Vietnam.

Control Perceived Behavior (CON)

Perceived behavioral control refers to the ease or difficulty of performing a particular behavior under consideration by Hadija, Barnes & Hair (2012). For two individuals with the same intention to engage in behavior, the one with a more vital perception of one's ability or control over the perceived behavior is more likely to act on Gironda & Korgaonkar's behavior (2014). Perceived behavioral control in the social media context refers to the perceived ability to view advertising on a social network. The ability to control the perceived behavior affects the intention to perform the behavior. In other words, people have a more substantial choice to perform the behavior if they feel that it is easy to perform the behavior by Hsu, Chang & Yansritakul (2017). Perceived behavioral control on intention is based on the fact that perceived behavioral control promotes an individual's assessment of the behavior's ability. Several studies have shown a positive relationship between the perceived ability to control behavior and the intention to perform the behavior. Chu, Kamal & Kim (2013) found a positive relationship between perceived behavioral control and intention to accept novelty. Based on the above, we have the following hypothesis H3:

Hypothesis H3: Control perceived behavior (CON) has a positive relationship with online shopping intention based on social media advertising in Vietnam.

In the context of social networks plus the complicated ongoing Covid-19 pandemic worldwide, Rauniar, et al., (2021) research showed that the intention to use social networks positively influences behavior to buy goods online. Covid-19 has affected almost every aspect of consumers' personal life, forcing businesses to be creative and react quickly to adapt to new trends and ways of consumption. Due to the highly infectious nature of the Covid-19 virus and the convenience of online ordering and delivery, contactless goods purchase and sale services have increased sharply. Covid-19 freight disrupted supply chains, reduced customer service and caused delivery delays. At the same time, modern consumers also raise expectations, becoming the norm in spending needs, creating new pressures for businesses. Therefore, even businesses that provide logistics and logistics services need to change their business models. Accordingly, changing business models, from production to distribution, transportation, and consumption, is the best solution to help businesses develop in the new situation by Huang & Dou (2020). We have the following hypothesis H4:

Hypothesis H4: Intention (INT) has a positive relationship with online shopping behavior based on social media advertising in Vietnam.

Methods of Research

Stemming from the research objective, the authors have theoretically systematized and synthesized previous research results to form the initial research model. Next, the authors build a questionnaire and conduct a formal quantitative study through a questionnaire with a research sample of 500 consumers who regularly shop online to determine the factors affecting purchasing behavior. Besides, online digitalization is based on the social network of users in Vietnam.

After obtaining the required number of votes, the author group cleaned the data, coded the necessary information in the questionnaire, entered and analyzed the data using SPSS 20.0 and Amos software. The data after being entered analyzed according to the following process.

First of all, descriptive statistics of user data participating in the questionnaire, the aim is to see an overview of social network users in Vietnam.

Secondly, the analysis evaluates the scale's reliability to check the consistency of the statements/questions of a scale by Hair, Anderson, Tatham & Black (2010).

Analysis of Cronbach Alpha aims to eliminate variables with correlation coefficients with small sum variables and test the Cronbach Alpha coefficients. Cronbach's alpha coefficient is a coefficient that allows assessing whether certain observed variables belonging to a research variable (latent variables, factors) are appropriate. Hair, et al., (2010) gave the following evaluation rule.

Cronbach Alpha < 0.6. The factor scale is inappropriate (maybe in the research environment, the subject has no perception of that factor); 0.6 - 07: Acceptable with new studies. 0.7 - 0.8: Acceptable 0.8 - 0.95: good >= 0.95: Acceptable but not good, should consider observed variables that may have the phenomenon of "coincidence".

The correlation coefficient of the total variable is the coefficient for the variable, the degree of "linkage" between an observed variable in the factor and the other variables. It reflects the degree of contribution to the notional value of the aspect of a particular observed variable. The criterion to evaluate whether a variable contributes to the factor is that the correlation coefficient of the total variable must be greater than 0.3. If the observed variable has a total correlation coefficient of less than 0.3, it must be excluded from the evaluation.

Thirdly, Exploratory Factor Analysis: The Exploratory Factor Analysis (EFA) method of Exploratory Factor Analysis (EFA) helps evaluate two essential types of scale values: convergent and discriminant. The EFA method of factor analysis belongs to the group of interdependence techniques. There is no dependent variable and independent variable, but it relies on the correlation between variables (interrelationships). EFA is used to reduce k observations into a set of F (F<k) more significant factors. This reduction is based on the linear relationship of factors with primitive variables (observed variables).

According to Hair, et al., (2010), factor loading is the criterion to ensure the practical significance of EFA: Factor loading > 0.3 is considered to be the minimum; Factor loading > 0.4 is deemed to be essential; Factor loading > 0.5 is deemed to be of practical significance.

The condition for exploratory factor analysis is to satisfy the following requirements: Factor loading > 0.5 by Hair, Anderson, Tatham & Black (2010).

KMO coefficient test (Kaiser-Meyer- Olkin) - KMO coefficient is the indicator used to consider the appropriateness of factor analysis and Bartlett test. If 0.5 < KMO < 1: then factor analysis is appropriate because it shows enough observed variables to form a factor. Bartlett test has statistical significance (Sig. < 0.05): This is a statistical quantity used to consider the hypothesis that variables do not correlate in the population. If this test is statistically significant (Sig. < 0.05), the observed variables are connected to the people. Percentage of variance > 50%: This shows the percentage variation of the observed variables. Considering the variation is 100%, this value showed how much the factor analysis explains.

Fourthly, after having the results of factor analysis, one factor was separated to explain two other factors that were renamed. Therefore, the authors test the reliability of the scales again. The results of the separated scales are reliable according to the requirements stated in the above step.

Finally, analyze the linear structure model (SEM).

After the authors assessed the scale's reliability, factor analysis discovered that the scales ensure high reliability and cohesion were considered for correlation and model analysis linear structure to test the research model and hypotheses. The authors conclude and propose governance implications.

Research Results

Testing of Cronbach's Alpha

Table 1 showed that Cronbach's alpha for the intention (INT) meets this technique's requirements. Specifically, Cronbach's Alpha values of the intention (INT) is 0.972, and Cronbach's Alpha if Item Deleted (>0.6). In this study, with the research context as social networks to study customers' attitudes towards buying advertised goods in the social network environment, the results show that the authors apply and correct scale drawn from previous studies.

Table 1 Testing of Cronbach's Alpha for Intention (INT)
Code	Intention (INT)	Cronbach's Alpha if Item Deleted
INT1	You often intend to click to buy goods when the ads appear on Facebook	0.964
INT2	You often pay attention to the ads that appear on Facebook	0.950
INT3	You usually intend to find information in the ads that appear on Facebook	0.960
Cronbach’s alpha: 0.972

Table 2 showed that Cronbach's alpha for the behavior (BEH) meets this technique's requirements. Specifically, Cronbach's Alpha values of the behavior (BEH) is 0.908, and Cronbach's Alpha if Item Deleted (>0.6).

Table 2 Testing of Cronbach's Alpha for Behavior (BEH)
Code	Behavior (BEH)	Cronbach's Alpha if Item Deleted
BEH1	You often click to see the ads appear in the Newsfeed section on Facebook	0.889
BEH2	You often click to see the ads that appear on your page on Facebook	0.851
BEH3	You often click to buy goods advertised on the Newsfeed section on Facebook	0.890
BEH4	You often click to buy goods advertised on your page on Facebook	0.891
Cronbach’s alpha: 0.908

Table 3 showed that customers intend to buy goods with advertising on social networks. Some studies mentioned that the scales are usually geared towards measuring customer purchase intention or measuring customer satisfaction to measure customer intent to engage in online word-of-mouth about advertisements appearing on social networks. Research results showed that all of Cronbach's alpha is ≥ 0.6. Cronbach's Alpha coefficient has a variable value in the interval [0,1]. The test results showed a total correlation coefficient (≥ 0.3). Cronbach's Alpha coefficient ≥ 0.6 should meet the requirements of reliability. This scale is also used to measure the intention to buy goods through viewing ads on the social network community.

Table 3 Testing of Cronbach's Alpha for Attitude (ATT)
Code		Attitude (ATT)		Cronbach’s Alpha
ATT1		You see Facebook ads as good		0.933
ATT2		You like advertising on Facebook		0.939
ATT3		You think Facebook advertising is essential		0.952
ATT4		It can be said that your attitude towards Facebook advertising, in general, is good		0.925
Cronbach’s alpha: 0.952
Code	Subjective standards (SUB)		Cronbach’s Alpha
SUB1	Most of the people who are important to you feel that it is good to see ads on Facebook		0.804
SUB2	Your family think it's a good idea to watch ads on Facebook and impressive		0.821
SUB3	Friends think Facebook ads are a good idea and are trustworthy		0.861
SUB4	You want to do what your family thinks you should do		0.806
Cronbach’s alpha: 0.861
Control perceived behavior (CON)
CON1	You can control the purchase of goods when viewing ads on Facebook		0.948
CON2	For you, buying goods when viewing Facebook ads is easy		0.954
CON3	Retail banking staffs are always polite, considerate, and welcoming to customers		0.964
CON4	You feel comfortable in making purchase behavior when viewing ads on Facebook		0.945
Cronbach’s alpha: 0.964

In this study, we measured the buying behavior of Facebook users to buy advertised goods on social networks. The authors focus on researching the behavior of viewing ads and purchase goods on the most popular social network in Vietnam, Facebook, from the perspective of social network users to measure the perception of social network users. for ads that appear in the Newsfeed of Facebook users. From that direction, the authors use a scale of buying behavior when viewing ads on social networks, which is used and adjusted from the scale in related studies. Table 4 showed that the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) is 0.848 (>0.5). This result is consistent with the actual data investigated by 500 customers who often see ads and buy goods on social networks. Cumulative is 84.537 %.

Table 4 KMO and Bartlett's Test for Factors Affecting Online Shopping Behavior Based on Social Media Advertising in Vietnam
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		0.848
Bartlett's Test of Sphericity	Approx. Chi-Square	9721.684
	df	171
	Sig.	0.000
Extraction Sums of Squared Loadings: Cumulative is 84.537%

Figure 2, 3 showed that the purchase intention of goods viewed on an advertisement of a social network. Besides, the assessment of the scale of the online shopping behavior based on social media advertising in Vietnam including: CMIN/DF = 3.695 (<5.0), GFI = 0.901 (>0.8), TLI = 0.952 (>0.9), CFI = 0.962 (> 0.9) and RMSEA = 0.076 (<0.08).

Testing Sem for Factors Affecting Online Shopping Behavior Based on Social Media Advertising in Vietnam

Table 5 showed three factors affecting online shopping intention and intention factors affecting online shopping behavior based on social media advertising in Vietnam with a significance level of 0.01. Three factors include: (1) Attitude (ATT), Subjective Standards (SUB), and Control Perceived Behavior (CON).

Table 5 Testing Coefficients for Factors Affecting Online Shopping Behavior Based on Social Media Advertising in Vietnam
Relationships			UnstandardizedEstimate	Standardized Estimate	SE.	CR.	P	Results
INT	<---	ATT	0.114	0.138	0.030	3.754	***	Accepted
INT	<---	SUB	0.145	0.143	0.040	3.605	***	Accepted
INT	<---	CON	0.550	0.555	0.039	14.020	***	Accepted
BEH	<---	INT	0.369	0.581	0.029	12.912	***	Accepted

Table 6 showed that the bootstrap test results are very good with a sample of 100.000 for the customers who often see ads and buy goods on social networks by Facebook.

Table 6 Testing Bootstrap With 100.000 Samples for Factors Affecting online Shopping Behavior Based on Social Media Advertising in Vietnam
Parameter			SE	SE-SE	Mean	Bias	SE-Bias
INT	<---	ATT	0.030	0.000	0.106	-0.008	0.001
INT	<---	SUB	0.048	0.001	0.134	-0.010	0.001
INT	<---	CON	0.047	0.001	0.548	-0.002	0.001
BEH	<---	INT	0.031	0.000	0.363	-0.006	0.001

Conclusion & Managerial Implications

Conclusion

Social advertising has emerged as a new form of engagement, and social media advertising differs from traditional advertising. Social media advertising provides customers with control and a request to view proactively. With the increasing number of Internet and social network users in the world in general and Vietnam, this context is creating very favorable conditions for the development of advertising on social networks. Therefore, assessing the factors affecting the buying behavior of goods advertised on social networks from the fundamental theory of consumer behavior brings significant contributions both in theory and practice. With that in mind, this study uses the theory of planned behavior to study the buying behavior of goods through advertising on social networks in Vietnam. Specifically, this study evaluates the factors affecting the buying behavior of goods viewed on social networks by users of social networks (Facebook) in Vietnam. Research results showed that research data support hypotheses H1, H2, H3, and H4. Specifically, the intention to buy goods viewed ads has a positive relationship with Vietnamese consumers' behavior on social networks. This study can be one of the critical studies in Vietnam to help explain the buying behavior of goods advertised on social networks in Vietnam, helping to make suggestions for businesses that intend to buy goods to use social media for advertising.

Managerial Implications

Social media is still evolving, and research on it is just beginning. In addition to the above-mentioned academic contributions, the research results also suggest some suggestions for businesses intending to use social networks for advertising as follows:

• Managerial implications for improving the control perceived behavior (0.555). Advertisers need to build customer trust in the company. As researchers have pointed out, there are three aspects of faith: trustworthiness, honesty, and goodwill. The first two aspects refer to the fulfillment of the promise made, while beneficence refers to the ability to behave in cooperation beyond the pledge. Therefore, a company that wants to gain customers' trust needs to pay attention to all three aspects above. Specifically, in advertising on social networks, advertisers need to build trust in such aspects as building trust in the company's social networking site, building customers' confidence in the brand. The company's brand is advertised on social networks.

• Managerial implications for improving the subjective standards (0.143). Advertisers need to be aware that brand trust positively influences consumers' intention and behavior to view ads. As a result, can shape the intent to purchase products, suggesting these products to friends and related people. Therefore, the company needs to focus on maintaining its commitments to its brand and exercise careful communication management to ensure that all information is released about the translated product, service is valid. Good command of the company's fan page or brand community will help members maintain and develop feelings for the company. The above efforts of the company will give customers relaxation and enjoyment to ensure that they have a connection with the company, thereby leading to trust in the company's brand and the intention to buy and act micro-purchase formed.

Managerial implications for improving the attitude (0.138). Advertisers need to build trust in a company's social media site. Trust in social networks can be enhanced by the benefits that social networks bring (including utility benefits and social interaction benefits). The degree to which customers express trust in social networking sites can influence customers' perceptions of brands and purchase intentions. Thus, the advice for advertisers here is that if they want to increase customers' trust in social networking sites, it is through increasing the valuable benefits and social interaction benefits perceived by customers. Specifically, customers depend on information to identify, compare, and choose products. Therefore, to increase practical benefits, companies need to provide better information about products and services. Because this helps customers feel confident and improves their attitude. In addition, the company can use social networking sites to interact with customers to understand customers better, create a sense of community participation, connect with the community, thereby increasing the perception of customers interaction in the customer's mind leads to increased customer trust.

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