DOI QR코드

DOI QR Code

The Impact of SNS Advertisements on Online Purchase Intention of Generation Z: An Empirical Study of TikTok in Vietnam

  • NGO, Thi Thuy An (Faculty of Business Administration, FPT University, Can Tho Campus) ;
  • LE, Thi My Thanh (Faculty of Business Administration, FPT University, Can Tho Campus) ;
  • NGUYEN, Thanh Hieu (Faculty of Business Administration, FPT University, Can Tho Campus) ;
  • LE, Truong Giang (Faculty of Business Administration, FPT University, Can Tho Campus) ;
  • NGO, Gia Thinh (Faculty of Business Administration, FPT University, Can Tho Campus) ;
  • NGUYEN, Tran Duong (Faculty of Business Administration, FPT University, Can Tho Campus)
  • Received : 2022.02.10
  • Accepted : 2022.05.10
  • Published : 2022.05.30

Abstract

The study was carried out to investigate the factors affecting the online purchase intention of Vietnamese consumers, focusing on Generation Z (Gen Z), through the information provided on TikTok - a social media network. Besides, the study evaluates the influence of these factors on the intention to purchase online of Gen Z. Most important; the research aims to help businesses better understand the insight of their consumers. The data were collected from 250 people who were born in the 1995 to 2010 period, living in the South of Vietnam. The study was conducted from December 2021 to March 2022 and used two analytical methods, which are exploratory factor analysis and Structural Equation Modeling. Research results show that there are 4 factors of TikTok advertisements that affect the purchase intention of Gen Z consumers, including information, entertainment, trust, and social interaction, and they all have a positive impact on the online purchase intention. In which the information factor has the most significant impact on the online purchase intention of Gen Z consumers. Based on the research results, recommendations are made to help businesses that have sold or intend to sell products via TikTok, improve the effectiveness of advertisement through the TikTok channel.

Keywords

1. Introduction

Today, the strong development of the 4.0 era and the Internet along with the advancement of modern network connected devices such as tablets and smartphones, has led to the rapid development of communication media like Facebook, Instagram, Twitter, and TikTok. Among them, TikTok is the leader in the field of short music video social platforms focused on vertical reading. Besides, TikTok is also video creation and sharing application, in the context of movie editing and playback behavior (Jiang, 2019). As simple to make and easy to use application for video, TikTok became a powerful social media platform that has been considered one of the most popular social networking platforms around the world and has had a great influence on the perception and behavior of Generation Z (Gen Z), who was born between 1995 and 2010 (Francis & Hoefel, 2018). TikTok is also changing the way Gen Z uses social media. With Gen Z, TikTok is not only an entertainment social network with unlimited content; they can also use TikTok to make money by creating product marketing ads.

Most recently, according to a report from Influencer Marketing Factory, around 62% of Gen Z prefers to shop from online stores rather than going to stores. The report adds that Gen Z is mainly inspired by social media platforms about online shopping as they can get recommendations from different people who have also tried or used them. A study by Ahmed (2021) shows that around 40% of Gen Z follows different brands on social media platforms like Facebook, Instagram, Twitter, TikTok, etc. For the TikTok channel, Muliadi (2020) found that over 60% of TikTok users are comprised of Gen Z. Thereby, it can be seen that the close relationship between the nature of Gen Z and social networks has a great influence on the purchase intention of Gen Z. In short, this will be the main group of consumer goods worldwide in general and in Vietnam in particular. With the above potentials, keeping the mentality and approach to Gen Z customers is essential for the development of online businesses. Thereby, it shows that managers must study shopping behavior and purchase intention through the TikTok social network of Gen Z.

2. Literature Review

2.1. Generation Z

Gen Z is the generation born between 1995 and 2010 (Francis & Hoefel, 2018). Gen Z has the features of the “network generation” due to the highly developed digital era in which they were born. They are also described as the “Facebook generation”, “digital natives” or sometimes “iGeneration” (Tari, 2011). Gen Z youth have been brought up in the first truly mobile era (Palley, 2012). The Kaiser Family Foundation reports that Gen Z youth are exposed to more media than any other activity other than sleeping, with a 67-minute daily increase in the number of time participants spent for and corresponding to the media in 2009, compared with 2004 (Rideout et al., 2010).

2.2. TikTok

TikTok is a famous social media app that lets in customers create, watch, and proportion 15-second movies shot on cell phones. With its customized feeds of quirky brief movies set to song and sound results, the app is first rated for its addictive nice and excessive stages of engagement. Even expert or non-expert content creators can upload different types of videos with filters, songs, stickers, and many other effects to make their videos more attractive (D’souza, 2021).

2.3. Purchase Intention

Purchase Intention is a type of subjective consumer behavior in which users are more likely to buy a certain product or service in a given situation based on their prior experience and desire (Keller & Kotler, 2016). This is a complicated process involving user behavior, perception, and mode. According to Belch and Belch (2009), purchase intention is the preference or the tendency of consumers to buy a brand or take actions related to purchases that are determined by the possibility of consumers purchasing a product or service. And the buying decision is most likely to be made after evaluating that product or service. A study by Keller (2001) indicates that there are many external factors that influence the consumer’s intention to select and purchase the products or services.

2.4. Research Framework and Hypotheses

The theory of planned behavior is one of the most important theories of behavior decisions that show the influences of individual variables, social circumstances, and non-volitional determinants on the purchase intention of customers (Ajzen, 2020; Han & Kim, 2010). Three aspects influence consumers’ buying decisions: psychological factors, individual traits, and societal factors (Ajzen, 1991). The ABC theory (Attitude, Behavior, and Context) offers a useful framework for investigating consumer behaviors (Katz, 1937). Other research aimed to directly incorporate variables including product information, prices, external driving factors, and product quality to investigate their direct impact on purchasing behavior (Cheung et al., 2019; Lee et al., 2015; Shin et al., 2017).

2.4.1. Information (INF)

Informational advertising on TikTok: The information element is the ability to effectively provide information related to the product to be advertised to consumers. When using ads on TikTok, information is an important factor because customers will find the necessary information about the products they want to buy and use. It’s also critical that the information is accurate, clear, and useful to the consumer. Based on research on customer perceived value and attitude toward advertising (Ducoffe, 1996; Eze & Lee, 2012; Lana & Bẹnamin, 2001; Ling et al., 2010; Petrovici & Marinov, 2005;) information is an important factor in this research, so the authors propose hypothesis H1 as follows:

H1: Information on TikTok has a positive effect on Gen Z purchase intention.

2.4.2. Entertainment (ENT)

Entertainment is the level of emotion brought to the user when viewing an ad. Entertainment in online advertising positively impacts consumers’ perceived values and attitudes (Ducoffe, 1996). A high level of enjoyment and attraction in the process of interacting with the media will positively affect their feelings and moods (Nguyen et al., 2013), indicating entertainment in online advertising has a positive impact on consumers’ perceived value and attitudes, so the authors propose hypothesis H2 as follows:

H2: Entertainment on TikTok has a positive effect on Gen Z purchase intention.

2.4.3. Trust (TRU)

Trust is the user’s level of trust in advertising on TikTok. Advertising credibility refers to the degree of trust consumers have in the advertising message and is based on trust placed in the source of the advertisements and the advertiser (MacKenzie & Lutz, 1989). Trust has been shown to have a direct, positive effect on the attitude towards advertising, brand attitude, and purchase intention of consumers (Goldsmith et al., 2000). Trust is an important factor in this research, so the authors propose hypothesis H3 as follows:

H3: Trust in TikTok has a positive effect on Gen Z purchase intention

2.4.4. Disturbance (DTB)

Marketing activities such as advertising frequently appear distracting, annoying, and offensive to consumers (Ducoffe, 1996). When customers are uncomfortable seeing an advertisement, they underestimate its worth (Brackett & Carr, 2001). The ads that continuously appear with high frequency will cut off the excitement when watching videos, making the audience lose good feelings. Based on research on customer perceived value and attitude (Ducoffe, 1996), advertising orientation; (Lana et al., 2001), study the attitude toward mobile advertising (Haghirian & Madlberger, 2005; Tsang et al., 2004). Since the disturbance is an important factor affecting the interest of consumers in an advertisement, the authors propose hypothesis H4 as follows:

H4: Disturbance on TikTok has a negative effect on Gen Z purchase intention.

2.4.5. Social interaction (INT)

The level of contact between users with advertising types is referred to as social interaction. It is defined as a way for people to effectively connect regardless of location or time (Ngo & Mai, 2017). The researchers discovered that the social interaction variable had a significant impact on online buying intentions in a study on the impact of social network advertising on customers’ purchase intentions (Ngo & Mai, 2017). Therefore, we propose hypothesis H5 as follows:

H5: Social Interaction on TikTok has a positive effect on Gen Z purchase intention.

The conceptual framework of this research is demonstrated in Figure 1.

Figure 1: Research Framework

3. Methodology

3.1. Research Method

This study was carried out through three main phases, including (1) Expert study, (2) Pilot study, and (3) Empirical study.

(1) Expert study: Expert discussion is often used by researchers in cases where they want to clarify and deepen the data, the high level of expertise of the research problem (Nguyen & Nguyen, 2011). In this research, the expert study was conducted using a qualitative method to determine the influencing factors and re-evaluate the questionnaire through the mock interview process.

(2) Pilot study: Pilot studies are small-scale, preliminary studies that aim to investigate whether crucial components of the main study – usually a randomized controlled trial (RCT) – will be feasible (Thabane et al., 2010). The study was conducted through a quantitative research method with 80 respondents to confirm and discover more factors affecting the purchase intention of Gen Z through TikTok.

(3) Empirical study: conducted by quantitative research method through the online survey. Collected data are used to test the research model and research hypotheses.

3.2. Questionnaire Design and Sampling Method

Questionnaire design: The questionnaire was designed based on a 5-point Likert scale with the principle from lowest to highest (from 1: Fully disagree to 5: Fully agree) (Zainudin et al., 2016), comprising two main sessions. The first session aims to collect respondents’ private information as qualitative data, including questions about gender, education, income, location of residence, employment, frequency of purchases, and others are among the question used to gather demographic information from respondents (Sheard, 2018). In the second session, questions focus on how TikTok influences Gen Z’s intention to purchase online.

Sampling method: A non-probability convenience sampling was implemented to minimize time, expense, and effort compared to other sampling methods because the research took place in the context of social isolation caused by the Covid-19 outbreak.

Sample size: For EFA exploratory factor analysis, the sample size must be at least five times the total observed variable (Hair et al., 1998). In addition, if the study uses exploratory factor analysis, the sample size should be at least 200 (Gorsuch, 1983). In this study, the total observed variable on the official scale is 23 observed variables for exploratory factor analysis, so the minimum sample size to be achieved is 23 * 10 = 230 samples. However, for this study to be more effective and reliable, the authors plan to collect data from 250 respondents.

3.3. Data Collection and Analysis

The data were collected via an online survey in a Google form that was shared in public groups on social networking platforms such as Facebook, Zalo, Instagram, and TikTok or sent directly to respondents via email, or Facebook Messenger. Besides, we use random direct survey methods at high schools and universities in southern Vietnam. The survey was conducted from February 02, 2021, to March 09, 2021, and received 250 valid responses from survey participants.

The collected data were analyzed using SPSS 22.0 software through descriptive statistics, frequency tables, reliability testing of scales, exploratory analysis, regression, T-test, and ANOVA in-depth analysis.

4. Results

4.1. Profile of Respondents

The profile of respondents is demonstrated in Table 1. Accordingly, the respondents compose people of both male and female, aged between 12 and 27 years old. They have an active account on the TikTok social network, and they have bought or/and will buy goods through this social networking platform. The results show that 118 male respondents take up 47.2% and 129 female equivalents to 51.6% of total respondents. Regarding age, the 19–22 age group takes up 39.6% of respondents, and a number of people from 23 to 27 years old account for 32%, showing that respondents intend to buy goods online quite a lot in this age range. Most respondents have an income of lower than 3 million Vietnam Dong (VND) and over 10 million VND. The time using TikTok also partly affects the intention to shop online. Among 250 respondents, the number of people who spends from 1 to 2 hours a day on TikTok is 79, ranking first place. On the other hand, only 36 respondents use more than 3 hours a day on TikTok.

Table 1: Profile of Respondents

4.2. Cronbach’s Alpha Reliability Coefficient

Cronbach’s alpha analysis was utilized in the study to determine the reliability of the scale of the components in the proposed theoretical model. In addition, this analysis method is applied to test the correlation between the observed variables and the total variable. The results in Table 2 reveal six total variables in the model include Information (INF), Entertainment (ENT), Trust (TRU), Disturbance (DTB), and Social interaction (INT).

Table 2: Cronbach’s Alpha Test Results

The analysis results show that the Cronbach’s Alpha coefficient for all constructions that range from 0.689 to 0.876 after observation (Table 2) meet the requirements of the test (Cronbach’s Alpha coefficient more than or equal to 0.60; adjusted Total Correlation value greater than or equal to 0.3) (George & Mallery, 2003). The test results proved highly reliable relationships between the observed variables and the total variable of the model.

4.3. Exploratory Factor Analysis (EFA)

The research results from Exploratory Factor Analysis (EFA) after eliminating two items with loading factors below 0.5, including ENT3 (0.487) and ENT1 (0.476), recorded that the KMO index was 0.792 (above 0.50) and Barlett testing was statistically significant at the level of less than 0.05 to meet the requirement for EFA analysis. Moreover, the EFA result revealed that all the scales of constructs met the requirements of the number of factors extracted (05 factors were extracted as per the proposed research model), the cumulative extracted variance equal to 55.53% (above 50%), Eigenvalues were 4.421; 2.580; 1.767; 1.505; 1.335 (higher than 1). The loading factors were very high (the highest was INF = 0.903 and the lowest was TRU3 = 0.516) (see Table 3). Therefore, five constructs in the research model with 17 items were extracted to meet the requirement of convergent validity and discriminant validity (Hair et al., 2010).

Table 3: Exploratory Factor Analysis

4.4. Structural Equation Modeling (SEM)

The study used Structural Equation Modeling (SEM) to analyze the correlation between the components in the model, including Information (INF), Entertainment (ENT), Trust (TRU), Disturbance (DTB), and Social Interaction (INT), and Purchase Intent (PI). The SEM analysis results are presented in Figure 2 and Table 4.

Figure 2: The Result of Full Model

Table 4: Hypotheses Testing Results

Notes: ***P < 0.01; **P < 0.05; *P < 0.1.

The Chi-square (χ2 /df) value is 1.434 < 3; the Comparative Fit Index (CFI) value is 0.917 > 0.9, and the value of Root Mean Square Error of Approximation (RMSEA) is 0.042 < 0.06. Therefore, it can be concluded that the model is a good fit, and all scales are acceptable.

The results of SEM analysis indicate that with a Sig of 0.66 > 0.05, the DTB variable does not have a significant effect on the PI. On the other side, TRU and ENT variables with Sig less than 0.05 (0.026 and 0.019, correspondingly) show a significant influence on the PI. In the same way with variables TRU and ENT, the INT and INF have the Sig values of 0.000 (AMOS symbol *** is sig equivalent to 0.000), indicating the relationship of these variables with PI is significant. In short, the results of the SEM analysis show a significant impact of four independent variables (TRU), (ENT), (INT), and (INF) on the dependent variable (PI).

According to the results presented in Table 4 and Table 5, the independent components of the model have a positive and significant influence on the dependent variable as follows:

Table 5: Standardized Regression Weight

Social Interaction (INT) and Purchase Intent (PI) have a positive and significant association with an index of 0.32 and an influence level of 0.29. This means having better social interaction via TikTok videos leads to an increase in the online purchase intention of a person.

Information (INF) and Purchase Intent (PI) have a positive and significant association with an index of 0.39 and an influence level of 0.42. Thereby, the more information audiences get from TikTok videos, the higher possibility of buying goods from the online channels they have.

Trust (TRU) has a direct and positive influence on Purchase Intent (PI), with a correlation of 0.14. According to the findings, having a high level of trust has a good impact on the purchase intention of consumers (with an influence level of 0.15).

Entertainment (ENT) has a positive and significant impact on Purchase Intent (PI) of 0.6 with a value of 0.17 influence level. The results illustrate that the higher the Entertainment, the more direct impact on Purchase Intent (PI).

5. Discussion and Managerial Implications

5.1. Discussion

The research results show that there are four factors affecting the purchase intention of consumers, including information, entertainment, trust, and social interaction. They all have positive impacts on the purchase intention of Gen Z consumers. Meanwhile, the disturbance factor has been removed because the P-value (Sig.) is greater than 5%, meaning that the disturbance factor has not significantly influenced purchase intention. The study also found that the negative impact of the distraction factor is quite large. The results of the standardized regression coefficients confirm that disturbance (DTB) is the factor that has a strong impact on purchase intention.

According to research results, the product information communicated to the customer is one of the factors affecting the customer’s attitude. When consumers have a positive attitude toward a product or service, it is most likely that they will purchase it (Nguyen et al., 2020, 2021). So, improving customer attitude is necessary to improve the consumers’ purchase intention. Therefore, manufacturers must provide more information about their products on their websites, social media, and other platforms (Bamoriya & Singh, 2012).

The findings suggest that interactivity is a social factor that influences Purchase Intent for products advertised on TikTok to some extent. Therefore, family, friends, and community may influence consumer buying behavior. Since collectivism will have an impact on purchase intentions; Subjective standards for products will be high if collectivism has good knowledge, beliefs, and attitudes towards the products advertised on the TikTok platform. Besides, social interaction is reflected in the fact that users can use text, images, videos, and links to follow and share new products with other users. Consumers will have a higher purchase intention if the ads through social networks bring them more interaction and sociality. At the same time, highly interactive messages to social communities from influential individuals will strongly affect consumers’ attitudes and behavioral intentions (Le et al., 2021).

Entertainment is a basic and mandatory requirement for advertising programs and activities, which is the ability to provide information and entertain viewers. Only when consumers perceive these two values can they create a positive attitude towards advertising. According to Ngo and Mai (2017), the more an advertisement via TikTok brings entertainment to consumers, the more intention to purchase products they will have. The entertainment of advertising is not only measured by activities that bring joy and comfort to consumers but also reflected in the content that the advertisement is conveying; the simplicity, ease of understanding, and uniqueness are also a way to help users not get bored when receiving advertising information. Advertising credibility is a statement of credibility and is always perceived in the mind of the listener (Adler & Rodman, 2000). The credibility of an advertisement is influenced by various factors, especially the reputation of the company and the reputation of the messenger. Trust has been shown to have a direct, positive effect on the attitude towards advertising, brand attitude, and purchase intention of consumers (Goldsmith et al., 2000). For this factor, the components include advertising on social media is honest because partly comes from people who already know about the information of the product/service/brand, contributing to the purchase decision and advertisement is trustworthy.

The factor of distraction is the only factor that negatively affects the attitude and purchase decision of the Gen Z. These effects include feeling bothered by ads, annoyed when ads appear on users’ Newsfeed, feeling ads are dishonest, distracting users, and being harassed by user types of banner ad image or video (Dinh & Le, 2016).

5.2. Managerial Implications

Through the study, the factors and levels affecting the purchase intention of Gen Z have been identified. Therefore, to improve the online purchase intention of Gen Z, the authors propose several solutions as follows:

According to the survey, information (INF) is the most important factor affecting the purchase intention of Gen Z. There are more and more products at different quality levels on the market. Consumers increasingly consciously seek information before owning it. TikTok’s display time is very short, which makes it difficult for advertisers. Advertisers need to make advertising content attractive, informative, and concise in the time allowed by the TikTok platform. Therefore, advertisers need to carefully study their target customers, thereby coming up with long-term strategies for advertising on the TikTok platform. Videos need to have a consistent theme that makes it easier for customers to look up information in the next videos. If the content of your ad is too long, you can split it up into clips and present curious information for customers to look up the next item. Manufacturers and advertisers must provide complete product information such as packaging, uses, or product notes. Businesses can set up pages and online portals where information about products can be exchanged, as well as information about manufacturers. Finally, set up consulting services to impart knowledge to consumers so that they better understand the potential and uses of the products. Furthermore, sales pages can inform customers about product features and consequences, which will increase their trust and confidence in the product, leading to Purchase Intent; Thereby improving customers’ trust in the products advertised through the TikTok platform as well as promoting the online shopping process of the Gen Z.

Social interaction (INT) influences the purchase intention of Gen Z. This shows that TikTok users tend to exchange information with other users to make product ownership decisions. For example, users can ask questions in the comments section to ask for the opinions of people who have used the product. Users can also read the comments of people who have experienced the product for more information. Advertiser engagement metrics also help build customer trust. If the TikTok page has a lot of likes, followers, comments, etc., it will create a better first impression for TikTok users. Advertisers should build good social engagement metrics by establishing a long-term strategy and encouraging users to interact with videos with attractive content by following the trend of target customers.

Trust (TRU) influences the purchase intention of Gen Z. Users to consider TikTok as a reference source for shopping and are considered trustworthy. Users have trusted TikTok. Advertisers can leverage the influence of TikTokers to build trust for their brand. Advertisers who want to be sustainable need to verify the credibility of the advertising information. When users have confidence in your information, they will be more likely to refer other users to use your channel to search for information.

Entertainment (ENT) influences the purchase intention of Gen Z. Users love creative, funny videos. Users tend to stay on the TikTok platform longer than on other platforms. This factor helps advertisers navigate video styles and content on TikTok. Advertisers can choose to create novel products or use reverse thinking to find new directions for their advertising. Advertisers can refer to the trends of target customers—present content in a novel way and combine products in a humorous way.

6. Conclusion

The study was conducted to analyze the factors of TikTok influence the online purchase intention of Gen Z. According to the analysis results of the SEM model of 250 observational samples proved that the factors of information, entertainment, trust, and social interaction of videos on TikTok directly and positively affects the purchase intention of Gen Z consumers. Subjective criteria factors affect the intention to buy products based on the regression results with 95% confidence that all four independent variables in the model affect Gen Z’s online purchase intention. From the research results, the authors found that the information factor has the most significant influence on the purchase intention of Gen Z consumers via the TikTok channel. Besides, the social interaction variable has a significant impact on consumers’ online purchase intention. The research results help us better understand how Vietnamese consumers feel about products advertised on the TikTok platform. Thereby providing solutions to enhance and improve the online purchase intention of customers. Moreover, the study of consumer behavior-based products will give a more accurate view and assessment for companies looking to grow the market through the TikTok platform.

References

  1. Adler, R. B., & Rodman, G. (2000). Understanding human communication (7th ed). Texas: Harcourt College Publishers.
  2. Ahmed, A. (2021). 97 percent of Gen Z consumers use social media platforms as their main source of shopping inspiration. https://www.digitalinformationworld.com/2021/03/report-97-percentof-gen-z-consumers.html
  3. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
  4. Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324. https://doi.org/10.1002/hbe2.195
  5. Bamoriya, H., & Singh, R. (2012). SMS Advertising in India: Is TAM a robust model for explaining intention? Organizations and Markets in Emerging Economies, 3(1), 89-101. https://doi.org/10.15388/omee.2012.3.1.14277
  6. Belch, G. E., & Belch, M. A. (2009). Advertising and promotion: An integrated marketing communications perspective (8th ed). New York: McGraw-Hill.
  7. Brackett, L. K., & Carr, B. N. (2001). Cyberspace Advertising vs. other media: Consumer vs. mature student attitudes. Journal of Advertising Research, 41(5), 23-32. https://doi.org/10.2501/JAR-41-5-23-32
  8. Cheung, M. L., Pires, G. D., & Rosenberger III, P. J. (2019). Developing a conceptual model for examining social media marketing effects on brand awareness and brand image. International Journal of the Economics of Business Research, 17(3), 243-261. https://doi.org/10.1504/IJEBR.2019.098874
  9. D'Souza, D. (2021). What is TikTok? https://www.investopedia.com/what-is-tiktok-4588933
  10. Dinh, T. M., & Le, T. H. L. (2016). Research on consumer attitudes in Ho Chi Minh City for online advertising on the social network Facebook. Retail Trade, 20, 1-13.
  11. Ducoffe, R. H. (1996). Advertising value and advertising on the Web. Journal of Advertising Research, 36(5), 21-35.
  12. Eze, U. C., & Lee, C. H. (2012). Consumers' attitude towards advertising. International Journal of Business and Management, 7(13), 94-108. https://doi.org/10.5539/ijbm.v7n13p94
  13. Francis, T., & Hoefel, F. (2018). 'True Gen': Generation Z and its implications for companies. https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/true-gengeneration-z-and-its-implications-for-companies
  14. George, D., & Mallery, P. (2003). Using SPSS for Windows step by step: A simple guide and reference (4th ed). UK: Pearson Education.
  15. Goldsmith, R. E., Lafferty, B. A., & Newell, S. J. (2000). The impact of corporate credibility and celebrity credibility on consumer reaction to advertisements and brands. Journal of Advertising, 29(3), 43-54. https://doi.org/10.1080/00913367.2000.10673616
  16. Gorsuch, R. L. (1983). Factor analysis (2nd ed). Mahwah: Lawrence Erlbaum Associates.
  17. Haghirian, P., & Madlberger, M. (2005). Consumer attitude toward advertising via mobile devices-An empirical investigation among Austrian users. Austria Journal of Advertising Research, 15, 44. https://doi.org/10.14143/ajar.2005.1544
  18. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed). NJ: Prentice-Hall.
  19. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed). NJ: Prentice-Hall.
  20. Han, H., & Kim, Y. (2010). An investigation of green hotel customers' decision formation: Developing an extended model of the theory of planned behavior. International Journal of Hospitality Management, 29(4), 659-668. https://doi.org/10.1016/j.ijhm.2010.01.001
  21. Jiang, X. Y. (2019). Research on TikTok is based on user-centric theory. Scholink Inc.: Applied Science and Innovative Research, 3(1), 28. http://doi.org/10.22158/asir.v3n1p28
  22. Katz, D. (1937). Attitude measurement as a method in social psychology. Social Forces, 15(4), 479-482. http://www.jstor.org/stable/2571413 https://doi.org/10.2307/2571413
  23. Keller, K. L. (2001). Building customer-based brand equity: Creating brand resonance requires carefully sequenced brand-building efforts. Marketing Management, 10(2), 15-19. http://anandahussein.lecture.ub.ac.id/files/2015/09/article-4.pdf
  24. Keller, K. L., & Kotler, P. (2016). Marketing management (15th ed). London: Pearson Education Limited.
  25. Lana, K. B., & Benjamin, N. C. (2001). Cyberspace advertising vs. other media: Consumer vs. matures student attitudes. Journal of Advertising Research, 41(5), 23-34. https://doi.org/10.2501/JAR-41-5-23-32
  26. Le, T. V., Alang, T., & Tran, Q. T. (2021). How YouTube Influencers impact customers' purchase intention: An empirical study of cosmetic brands in Vietnam. Journal of Asian Finance, Economics, and Business, 8(9), 101-111. https://doi.org/10.13106/JAFEB.2021.VOL8.NO9.0101
  27. Lee, C. K. C., Levy, D. S., & Yap, C. S. F. (2015). How does the theory of consumption values contribute to place identity and sustainable consumption? International Journal of Consumer Studies, 39(6), 597-607. https://doi.org/10.1111/ijcs.12231
  28. Ling, K. C., Piew, T. H., & Chai, L. K. (2010). The determinants of consumers' attitude towards advertising. Canadian Social Science, 6(4), 114-126. https://doi.org/10.3968/1082
  29. MacKenzie, S. B., & Lutz, R. J. (1989). (PDF) an empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(2), 48-65. https://doi.org/10.2307/1251413
  30. Muliadi, B. (2020). Council post: What the rise of TikTok says about generation Z. https://www.forbes.com/sites/forbestechcouncil/2020/07/07/what-the-rise-of-tiktok-saysabout-generation-z/?sh=5268cdb56549
  31. Ngo, M. T., & Mai, V. N. T. (2017). Analyzing the impact of advertising through social networks on the purchase intention of consumers in Can Tho City. Can Tho University Journal of Science, 48, 66. https://doi.org/10.22144/ctu.jvn.2017.631
  32. Nguyen, D. T., & Nguyen, T. M. T. (2011). Market research. Ho Chin Minc: Vietnam National University, Ho Chi Minh City Press.
  33. Nguyen, N., Duffy, B. G., Shulmeister, J., & Quigley, M. C. (2013). Supplementary information: Palynology and geochemistry data and methods, and section age model. Journal of Business and Management, 61(4), 99-114. https://doi.org/10.112521314/1410331-53
  34. Nguyen, N. T., Nguyen, L. H. A., & Tran, T. T. (2021). Purchase behavior of young consumers toward green packaged products in Vietnam. Journal of Asian Finance, Economics, and Business, 8(1), 985-996. https://doi.org/10.13106/jafeb.2021.vol8.no1.985
  35. Nguyen, T. K. C., Nguyen, D. M., Trinh, V. T., Tran, T. P. D., & Cao, T. P. (2020). Factors affecting intention to purchase green products in Vietnam. Journal of Asian Finance, Economics, and Business, 7(4), 205-211. https://doi.org/10.13106/jafeb.2020.vol7.no4.205
  36. Palley, W. (2012). Gen Z: Digital in their DNA. http://www.jwtintelligence.com/wpcontent/uploads/2012/04/F_INTERNAL_Gen_Z_0418122.pdf
  37. Petrovici, D., & Marinov, M. (2005). Determinants and antecedents of general attitudes towards advertising. European Journal of Marketing, 41(3), 307-326. https://doi.org/10.1108/03090560710728354
  38. Rideout, W. J., Foehr, U. G., & Roberts, D. F. (2010). Generation M[superscript 2]: Media in the lives of 8- to 18-year-olds. (2010.). Generation, 51, 631.
  39. Sheard, J. (2018). Quantitative data analysis. In: Williamson, K., & Johanson, G., (Eds.), Research methods: Information, systems, and contexts (2nd ed., pp. 429-452). Netherlands: Elsevier. https://doi.org/10.1016/B978-0-08-102220-7.00018-2
  40. Shin, D. H., Lee, S., & Hwang, Y. (2017). How do credibility and utility play in the user experience of health informatics services? Computers in Human Behavior, 67, 292-302. https://doi.org/10.1016/j.chb.2016.11.007
  41. Tari, A. (2011). Z generation. Hanoi: Tericum Konyvkiado.
  42. Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L. P., Robson, R., Thabane, M., Giangregorio, L., & Goldsmith, C. H. (2010). A tutorial on pilot studies: The what, why, and how. BMC Medical Research Methodology, 10(1), 1. https://doi.org/10.1186/1471-2288-10-1
  43. Tsang, M. M., Ho, S. C., & Liang, T. P. (2004). Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce, 8(3), 65-78. https://doi.org/10.1080/10864415.2004.11044301
  44. Zainudin, A., Asyraf, A., & Mustafa, M. (2016). The Likert scale analysis using parametric-based Structural Equation Modeling (SEM). Computational Methods in Social Sciences, 4(1), 13-21. http://cmss.univnt.ro/wp-content/uploads/vol/split/vol_IV_issue_1/CMSS_vol_IV_issue_1_art.002.pdf