The Reaction of Vietnam's Generation Z to Online TV Advertising

Abstract

The paper examines the reaction of the Z-Vietnam generation to online TV advertising (TVC), which elements of online TV advertising has a positive influence, which factors do not affect or negatively affect their consumption decisions for the advertised goods. Data for the study was collected from 300 Vietnam's Generation Z in Ho Chi Minh City through live interviews or questionnaires through Google Docs Forms, with over 30 questions. The six basic factors that influence the reactions of Generation Z consumers are information, entertainment, irritation, credibility, interaction, and advertising value. The research results show that, due to the influence of social media and generational characteristics, most consumers of the Generation Z in Vietnam have a favorable attitude towards online TV advertising, and they appreciate this form of advertising. Information element, irritation, credibility and entertainment have a strong and positive impact on TVC. The other two factors are advertising value and interaction, which does not significantly affect the reaction of this generation. This study needs to be checked and reviewed by subsequent studies on a larger scale and in a wider scope because the study only conducted random sampling on a small scale, did not meet the requirements for representation and generality.

1. Introduction

In order to sell products, the first thing a company needs to do is how to communicate the products to the public. Advertising is one of the simplest and most effective forms of communication. Accordingly, advertising is a potential communication message between advertisers and consumers. Whether or not the exchange is successful depends very much on the decision of the consumer based on the initial evaluation, spontaneous, combined classification to create the expected advertising value (Ducoffe & Curlo, 2000). Moreover, with early ad technology, many people don’t intend to buy advertising products. Besides that, the ads messages don’t really relate to consumer concern at exposure time (Ducoffe, 1996). Thus, several types of research are offering new advertising technologies with more accurate targeting. This is in line with the modern and effective marketing communication strategies towards the right approach for the needs of receiving information from consumers.

Along with the development of human society, advertising has grown and has become a popular and diversified form of communication, helping businesses convey the message to consumers. Studying the delayed effect of collaborative advertising in goodwill motivation, Machowska (2019) proposed a tool to control cooperative advertising that increased the goodwill of companies operating in a competitive market. Using case-based reasoning to predict consumer choices based on the similarities of comparable replacement sets, Seo, Kim, and Jo (2020) suggest an alternative method for conventional collaborative filtering to predict consumer choice, using casebased reasons. The results show that the similarity between equivalent alternatives that consumers consider to purchase is an important factor in predicting consumer choice. In addition, interactive effects have a positive effect on predictive accuracy. Park and Park’s research (Park & Park, 2019) on the influence of emotional images on customer attitudes indicated that uniforms with primary colors such as red, orange and green peas were found to have many playful, growing, and bold images. In addition, the impact of customer awareness and bias on the uniform color image of the airline crew shows the airline’s positive perception of the uniform color image and the more perceived images positive.

Advertisers today have a wide range of options at their disposal, including television advertisement or television commercial (referred to as a TVC online or TVC). With the characteristics of TVC, online TVC has the advantage that messages can be transmitted everywhere and at any time, impressing to the public more than other media by text, image, sound and motion in the ads. This combination has the same effect on many senses, making the receiver remember and remind the ads as well as the brand better. In addition, online TVC makes it easy and quick to interact with customers and advertisers. With TVC online, consumers are not forced to view ads; they can skip them. Due to the ability to attract the attention of many customers, online TVC gradually replaced the traditional media channels.

According to the results of the 2019 census, Vietnam’s population currently has more than 96 million people (Huy, 2019). With a large population, ranked 15th in the world, including about 66.1 million Internet users, accounting for about 70% of the population (Dammico.com, 2020), Vietnam is considered a fertile and promising land for online advertising and is a favorable environment for developing online videos. Online TVC allows marketers to have direct contact with customers anytime, anywhere. Using online advertising, marketers can easily find out what their customers are doing on the Internet: the websites they visit, the products that they are interested in, the messages that they send to their friends, and through that to know their needs. It’s better to meet the needs of customers than to bring them troubles. Online TVC not only helps the marketer reach the right target audience, but also the real customers. Marketers will not dominate customers but partner with them. The important thing is how to understand Internet users and the factors that affect their attitudes towards online TVC. Attitude towards advertising plays the role of an important intermediary in the choice of consumer brands, influencing the emotions of customers, so it plays a decisive role in consumers (Shimp, 1981).

Vietnam, characterized by a young population, is in a period of “golden population structure” (Thien, 2019) and strong Generation Z. According to the predictions of Nielsen (2018), by 2025, Vietnam’s Generation Z will account for about 25% of the country’s labor workforce, equivalent to 15 million people. This shows that the number of potential Generation Z consumers in 2025 is quite large. Nielsen’s study (2018) also pointed out that, if a brand wants to attract the population of Vietnam’s Generation Z, that brand needs to pay close attention to the characteristics of this generation. That is:

- Social media become a essential part of their life: Vietnam’s Generation Z spends most of its time on social media websites and video source platforms like Instagram, Facebook and YouTube. They share a certain type of content on specific social channels. Survey results show that 90% of Generation Z watches television every day.

- Vietnam’s Generation Z is more demanding than the previous generations: born and raised in the prosperous period of the country, the Generation Z is more demanding. Not only it supports brands that reflect Vietnamese values and culture and have timeless or classic brand associations, but the nation’s Generation Z is also interested in various social issues including social responsibility, environmental issues and gender equality.

- Vietnam’s Generation Z prefers new discoveries and experiences: 75% would love to experience and discover new brands. The remainder (25%) is likely to consider a brand carefully before buying and is unlikely to switch brands.

Attracting the attention of the Generation Z with advertising media in general and online TVC is a challenge. Therefore, in this study, the authors aim to answer the following research questions: Is there a relationship between the Generation-Z consumers and online TVC? If there is a relationship, what is the impact of online TVC on Generation-Z consumers?

2. Literature Review

Beside research on advertising, there have been many studies on attitudes to advertising that have been published. There are some outstanding works like Mackenzie and Lutz (1989), Pollay and Mitall (1993), Shavitt, Lowrey, and Haefner (1998), Lee and Tai (2006), Lim, Yap, and Lau (2010), Becker, Lee, and Nobre (2010), Kussusanti, Tjiptoherijanto, Halim, and Furinto (2019), among others. Mackenzie and Lutz (1989) have identified attitudes to advertising as an important structure that mediates the impact of advertising on brand attitudes and buying intent. They presented the latest theory of attitudes to advertising formation, reported empirical test results, and offer further improvements to the theory based on observed results. Pollay and Mitall (1993) proposed a seven-factor model (product information, social image information, hedonic amusement, good for economy, fostering materialism, corrupting values, and falsity/no-sense) to study attitudes to advertising and tested on two independent samples: Collegians (188) and householders (195). The results showed that most of the respondents expressed conflict between the appreciation of personal use and the economic value of advertising and the fear of cultural degradation.

Shavitt, Lowrey, and Haefner (1998) reported that a lot of Americans say they prefer it rather than dislike advertising in general. They find advertising generally to be informative and helpful in guiding their own decision making. At the same time, Americans tend to feel more confident in advertising claims when focusing on their actual purchasing decisions. Lee and Tai (2006) focus on understanding how young consumers (Generation Y) in economies transform perceptions of Western multinational companies, which factors influence their consumption preferences for Western products and media channels influence the level of Western product purchases and brands. The findings suggest that most young consumers have a favorable attitude towards Western products and objects, and they have high appreciation, especially for global brands. Research by Lim, Yap, and Lau (2010) examines the response to Internet advertising among Malaysian Young. Research findings show that they are moderate Internet users, they have a positive attitude and like advertising on the Internet.

Becker, Lee, and Nobre (2010) showed that, when considering the amount of time spent on computers, the way consumers search for information and where to buy products, Portuguese and USA consumers rate stores highly for items costing less than $500, and search engines came second; South Korean and Turkish consumers consider search engines to be the main one; Turkish consumers give a higher rating (for both price levels) to a companies’ websites compared to other countries, which would not have been intuitive. Kussusanti, Tjiptoherijanto, Halim, and Furinto (2019) examine the effect of informational justice on post-recovery satisfaction, and the effect of post-recovery satisfaction on behavioral intentions in e-commerce. The results of this study indicated that: (1) informational justice and post-recovery satisfaction has a positive effect, and (2) service failure severity acts as a moderator between postrecovery satisfaction and behavioral intentions.

For online advertising, there have been many studies dealing with published consumer attitudes such as Ducoffe (1996), Aydoğan, Aktan, and Aysuna (2016), Tsang, Ho, and Liang (2004), Zha, Li, and Yan (2015), Cho (2004), Wolin, Korgaonkar, and Lund (2002). Ducoffe (1996) considered (1) whether information, entertainment and stimulation, hypothetical premises for advertising value, would be meaningful and consistent predictions about how consumers value advertising Web advertising, and (2) how advertising value relates to the attitude towards Web advertising. The results of his research indicate that Web advertising is widely used and valuable, a little more information than value and less entertainment than value. Discussing the value of web advertising and student attitudes to web advertising, Aydoğan, Aktan, and Aysuna (2016) showed the viability of web advertising as an alternative to traditional media. The rapid expansion of this ad to websites requires a better understanding of user awareness about web advertising because media attributes can influence consumer attitudes towards advertising. The premise of advertising value is irritation, informativeness, credibility, and entertainment, also be combined. Regarding consumer attitudes towards mobile advertising, empirical research by Tsang, Ho, and Liang (2004) indicated that (1) consumers often have negative attitudes for advertising on mobile devices unless they specifically agree with it, and (2) has a direct relationship between consumer attitudes and consumer behavior.

Zha, Li, and Yan (2015) found that perceived information, perceived entertainment and credibility contribute to the formation of attitude towards web advertising, which further impacts on the use of web advertising to retrieve information. Meanwhile, it positively moderates the credibility transfer from non-web advertising to web advertising. Cho (2004), when researching why people avoid advertising on the Internet, developed a comprehensive theoretical model that explains avoiding advertising on the Internet on three variables: perceived goal impediment, perceived ad clutter, and prior negative experience. The results of the study indicated that the perceived target impediment was found to be the most important premise explaining avoiding advertising on the Internet. To test the beliefs, attitudes and behavior of web users towards web advertising, Wolin, Korgaonkar, and Lund (2002) used the model of Pollay and Mittal (1993). The results showed that the belief factorsproduct information, hedonic pleasure, and social role and image-related positively correlated with the attitude of the audience towards web advertising. In addition, the higher the income and education of respondents, the more negative their behavior towards web advertising.

When learning about consumer attitudes towards advertising, Wang, Zhang, Choi, and D’Eredita (2002) measured consumer attitude toward advertising to build brands and drive consumption based on traditional media and on the Internet. Their aim is to understand the cognitive difference between Internet-based advertising and traditional advertising for both branding and directional purposes. The results confirm that the Internet and the web have the potential to better support targeted consumers, thus providing great potential for Internet-based advertising. Studying young consumer attitudes towards SMS advertising, Waldt, Rebello, and Brown (2009) found that entertainment value, information and reliability of SMS advertising are positively correlated with consumers. On the other hand, the study also found that consumers are aware of the stimulating aspect of SMS advertising inversely correlated with consumer attitudes towards SMS advertising. Based on the rising transparency and omnipresence of price and discount information through web and mobile platforms, research by Luo and Lee (2018) on the effect of discount format after buying with consumers’ perception of loss and willingness to return the effect of postpurchase discount format shows that post-purchase discount information may increase consumers’ perception of monetary loss, which may affect consumers’ decision to return the product, potentially increasing the operating costs borne by retailers. From here, the authors proposed a new conceptual framework to understand consumers’ perceptions, attitudes and behaviors (loss awareness, readiness to return) when recognizing different formats of the discount promotion (absolute value compared to a percentage discount) after purchasing the product.

When examining the influence of personal product knowledge on the predictive power of behavioral models, (Byun, 2018) showed the difference in attitudes explained by two beliefs (perceived usefulness and easy to use) is relatively small when the survey respondents have a lower amount of product knowledge. The results indicated that respondents should have a certain amount of knowledge about the target system to form trust and determine correct behavior. The study also examined the differences between male and female consumers about their attitudes toward online advertising. Le, Ngo, Trinh, and Nguyen (2020), in their research on the main factors affecting customers’ decision to use mobile banking services in Vietnam, have indicated that social influence is the most powerful factor, followed by compatibility and some other factors such as perceived ease-of-use, perceived trust, etc. Dinh and Doan’s study (2020) examined the influence of consumers on sender’s perceptions of accepting online reviews (a type of eWOM) in Vietnam that showed the variables: Quality messages, Source reliability, Perception usefulness of messages, Identified sender identification, Reliability of received messages, and Acceptance of messages that achieve validity and reliability in research. This study contributes to an understanding of the determinants that affect the acceptability of eWOM information, which are information factors and factors related to consumer skepticism.

3. Data and Methods

3.1. Research Hypothesis

Based on previous studies on the impact of independent variables (information, entertainment, irritation, credibility, interaction, advertising value) of TVC online and the reaction of generations on the TVC online, this study puts forward the following hypotheses (see Figure 1):

Figure 1: The research hypothesis of consumer reaction of Z-Vietnam generation to TVC online

Source: Authors synthesized on the basis of research results

H1: There is a positive relationship between the information (INF) of TVC online and the reaction of Generation Z.

H2: There is a positive relationship between the entertainment (ENT) of TVC online and the reaction of Generation Z.

H3: There is a negative relationship between the irritation (IRR) of TVC online and the reaction of Generation Z.

H4: There is a positive relationship between the credibility (CRE) of TVC online and the reaction of Generation Z

H5: There is a positive relationship between the interaction (INT) of TVC online and the reaction of Generation Z.

H6: There is a positive relationship between the advertising value (VAL) of TVC online and the reaction of Generation Z.

3.2. Data

In the preliminary study phase, 30 questionnaires were sent to four small groups for testing. Each questionnaire consists of observation variables that measure the reaction of Generation-Z consumer to online TVC. 30 questionnaires were returned, all could be used for analysis. Scales were evaluated through Cronbach’s Alpha confidence test and the coefficients of coefficients were calculated. As a result, many variables with low confidence coefficients and low correlation coefficients will be rejected. The research data was collected on the basis of a questionnaire with more than 30 questions and sent to 330 people of Generation Z who participate in using this social network and are directly affected by TVC online. Generation Z’s response to online TVC ads was recorded. The research samples are shown in Table 1.

Table 1: Research Samples

Source: Compiled by the authors based on research results

Accordingly, all the research problems are measured through recording the feel of Generation Z to the impact of online TVC. This is the questionnaire for the score. Each answer is evaluated by measuring the Likert 5 point scale (1 = strongly disagree 2 = disagree 3 = no opinion 4 = disagree, 5 = strongly agree) (Likert, 1967). The questions in this questionnaire are built and tested to suit the conditions of Vietnam.

3.3. Research Mode

In this study, the authors used SPSS 22 and applied quantitative research to the regression model, including six independent variables studied in the model: Information of online TVC (INF), Entertainment of online TVC (ENT), Irritation of online TVC (IRR), Credibility of online TVC (CRE), Interaction (INT), Value of online TVC (VAL) and a dependent variable is Attitudes towards online TVC (ATT). The main regression model developed according to the dependent variable has the following form:

\(\begin{aligned} \text { ATTi,t }=& \beta 0+\beta 1 * \mathrm{INFi}, \mathrm{t}+\beta 2 * \mathrm{ENTi}, \mathrm{t}+\beta 3^{*} \mathrm{IRRi}, \mathrm{t}+\\ & \beta 4^{*} \mathrm{CREi}, \mathrm{t}+\beta 5^{*} \mathrm{INTi}, \mathrm{t}+\beta 6^{*} \mathrm{VALi}, \mathrm{t}+\varepsilon \mathrm{i}, \mathrm{t} \end{aligned}\)

Where:

- β0, β1, β2, β3, β4, β5 and β6 are correlation coefficients.

- εi,t is error random variance.

After the data collected is processed by SPSS version 22nd. The work is done in formal research include: preliminary evaluation of the scale; factor analysis of discovery; correlation analysis; regression analysis; analysis of variance (ANOVA). In analyzing, evaluating and verifying scales, we will continue to exclude, group, or classify the component variables according to their characteristic groups and be appropriately named by the exploratory factor analysis (EFA). The scale is based on previous studies by researchers such as Ducoffe (1996), Prendergast, Liu, and Poon (2009), Ko, Cho, and Roberts (2005). The scale of Information, Entertainment, Irritation, and Advertising value is based on Ducoffe’s (1996). Scale of Credibility is based on Prendergast, Liu, and Poon (2009). The Interaction component scale is based on Ko, Cho, and Roberts (2005). The Relevant Demographics are based on Waldt, Rebello, and Brown (2009) model. Then the scales were adjusted and supplemented through qualitative research to suit consumers in Vietnam. In the preliminary study phase, 30 questionnaires were sent to four small groups for testing. Each questionnaire consists of observation variables that measure the reaction of Generation-Z consumer to online TVC. 30 questionnaires were returned, all could be used for analysis. Scales were evaluated through Cronbach’s Alpha confidence test and the coefficients of coefficients were calculated. As a result, many variables with low confidence coefficients and low correlation coefficients will be rejected.

4. Results and Discussion

With a 95% confidence level, there are four factors that influence the consumer reaction of Vietnam’s Generation Z for online TVC. The correlation between independent and dependent variables is shown in Table 2.

Table 2: Correlation coefficient matrix between independent and dependent variables

To test for significant differences, we conducted the one-sample T-test. The result will help us make a decision whether the hypothesis should be accepted or rejected. Compared to the mean value to the neutral point, it will indicate whether there is a positive or negative influence. After encoding the measurement variables and analyzing correlations between variables, we analyze the regression with the Enter method. In this method, four independent variables (INF, ENT, IRR, INT) and one dependent variable (ATT) are included in the model. Regression results are shown in Table 3.

Table 3: Results of regression analysis

As a result of the regression analysis, with four variables are accepted (enough strong) and two variables are rejected (very weak), the authors write the following regression equations:

\(\mathrm{ATT}=0.447 \mathrm{INF}+0.270 \mathrm{ENT}+0.441 \mathrm{IRR}+0.339 \mathrm{CRE}\)

It means:

Reaction of Vietnam’s Generation Z to online TV advertising = 0.447 (Information) + 0.270 (Entertainment) + 0.441 (Irritation) + 0.339 (Credibility).

Regression of variables is satisfactory (sig. <0.05) and positive. Therefore, we can conclude that the following hypotheses are accepted:

H1: There is a positive relationship between the information of TVC online and the reaction of Generation Z.

H2: There is a positive relationship between the entertainment of TVC online and the reaction of Generation Z.

H3: There is a negative relationship between the irritation of TVC online and the reaction of Generation Z.

H4: There is a positive relationship between the credibility of TVC online and the reaction of Generation Z.

From accepted hypotheses, we conclude that INF, ENT, IRR, CRE variables are confirmed to have an effect on Y. This shows that values of information, entertainment, and credibility have a positive impact on the behavior of Generation-Z consumers to online TVC, the irritation has negative impact on online TVC.

The major result of this study is to show the factors that strongly influence the reaction of Generation-Z consumers to online TVC. An additional contribution of this research is to continue to affirm the importance of the factors affecting the reaction of Generation Z to online TVC through quantitative research. It shows that the information and irritation most strongly influence the reaction of consumers to online TVC.

5. Conclusions

From the above research results, it can be seen that the response of Vietnam’s Generation Z to online sales advertising on TV has a significant difference between six independent variables. With 95% confidence, the variables INF, IRR, CRE and ENT have a strong, positive impact on TVC online. Interestingly, unlike the previous generations, the Vietnam’s Generation Z responded positively to the irritation (IRR) of TVC online. In addition, VAL and INT variables have little impact on the reaction of this generation.

Limitations of the study include: restrictions related to the sample because of the random sampling method, and the sampling range was small and limited in some areas, so the sample did not meet the requirements of representativeness and generality. The second constraint is the ability to convert and apply international scales in Vietnam. In particular, it was not possible to measure some variables. The third limitation is technical analysis. SPSS analysis software can do exploratory factor analysis (EFA), but not confirmatory factor analysis (CFA) and no advanced analytical techniques like other software. The fourth constraint is the ability to design questionnaires. However, this study will help business leaders decides the selection criteria to create a better TVC online, suitable for the demand of Generation Z and organizations’ objectives.