The reaction of z generation to online television advertisement
Ao Thu Hoai/ MICA 2018 Proceedings
International Conference on Marketing in the Connected Age (MICA-2018), October 6th, 2018
Danang City, Vietnam
The Reaction of Z Generation to Online Television
Advertisement
Ao Thu Hoai*
aFaculty of Marketing, University of Finance – Marketing, Ho Chi Minh City, Vietnam
A B S T R A C T
Online advertisement or online television advertisement (TVC) are the most effective ways of communication.
Researchers and marketers have turned their attention and resources into this channel, exploring the rules and
reactions of those who accept advertising. The Z generation is a particularly important group of customers
nowadays, representing the behavioral group and the unique qualities of people in the era of science and
technology with many historic turning points. In fact, how did they react to TVC? There are some general
studies about online advertising with consumers. These studies are not very meaningful because each group of
customers will have reactions that can be completely different from each other online advertising methods. By
quantitative research, combined with the analysis of secondary material, this study is based on the
communication model of some prior scholars to test a behavioral study of the Z generation with TVC online.
Keywords: Online advertising; TVC; Z generation; Reaction.
1. Introduction
In order to sell products, the first thing a company needs is how to communicate the products to the public.
Advertising is one of the simplest and most effective forms of communication. In the past, the customers
received a huge amount of advertising messages, they often did not have the means to pay attention to all
(Ducoffe, 1996). Moreover, with early ad technology, many people don't intend to buy the advertising products.
Besides that, the ads messages don't really relate to consumer concern at exposure time. (Ducoffe, 1996). Thus,
several researches 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 of consumers.
There are many media tools for advertising, 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 receiver
remember and remind the ads as well as the brand better. In addition, online TVC makes it easy and quick to
interact between customers and advertisers. With TVC online, consumers are not forced to view ads, they can
skip. Due to the ability to attract the attention of many customers, online TVC gradually replaced the traditional
media channels.
According to a report by Nielsen (2012), 33% of the internet users hate the advertisement, and 26% like it.
However, true contextual ads are easily accepted. In particular, Asians are generally more inclined to TVC (41%
* Corresponding author. E-mail address: aothuhoai@gmail.com
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like, 26% share, 31% buy). With a large number of online users in Vietnam, the internet environment is the
communication channel for online video development. Online TVC allow 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 partnering with them (Vollmer & Precourt, 2008). The
important thing is how to understand internet users and the factors that affect their attitudes towards online TVC.
Because of the attitude of thought, the effect on emotions results in behavioral influences (Nguyen Xuan Lan et
al., 2010). And the attitude is a central role in consumer decision-making (Nguyen Xuan Lan et al., 2010).
In Vietnam, according to a report by the Vietnam Internet Association (11/2017), there are more than 64
million Internet users, ranked 6th in Asia and 12th in the world. This is really a great ground for the development
of the online TVC market. In particular, the majority of users are young. Young consumers are the target
audience for many brands as they are accessible to the latest trends as well as the fastest new technologies.
The Z generation (also known as Post Millennials, the iGeneration, or the Homeland Generation) is the
demographic behind The Millennials. We still have no exact time when the group started or ended, but it is
understood to be from the mid-1990s to the early 2000s. In 2015, Epinion Global has a more in-depth study on
The Z generation in Vietnam with 710 responses, Epinion has discovered seven characteristics of The Z
generation in Vietnam such as:
They do not like to spend time to go out, just enjoy being online, calling and staying home, they are most
comfortable when interacting with others through a screen.
They tend to be inseparable from mobile phones, preferring to spend time searching for information, products
and brands on their technology devices.
They have become more skeptical of the Internet, they seem to have a lot of experience accessing online
information, which suggests that the origin of shared information is not necessarily obtained from reliable
sources. And they want to get more proof of the authenticity of the information and the censorship of
reputable organizations.
They are interested in social issues and want to do something for themselves and society.
They can have "immature" syndrome because they have grown up in a relatively stable economy. Thus, they
completely lack personal autonomy and independence.
They are confident and knowledgeable with the help of technology equipment.
They cannot lack the Internet because they are the ones who constantly monitor and update the trend, online
information at any time and cannot miss even a very small and even not very noticeable information about
the famous.
The results of a survey by market research firm Kantar Millward Brown on The Z generation in 2017 shows a
clearer Z generation, including the Z generation in Vietnam, the Philippines, and Indonesia. And Thailand.
Growing up in technological maturity since the mid-1990s, the Z generation is the most technologically
advanced generation today. The Z generation likes to communicate through images, using multiple social
networks simultaneously to connect. This group of young people is less likely to watch television, listen to the
radio, or read newspapers than in previous generations: only 52% watched television for more than an hour a
day, compared to 77% in the 20-34 age group. In particular, this new consumer group is hated by advertisers and
wants the brands to respect their online space. According to the survey, 22% of the Z generation in Vietnam
reacted negatively to pop-up ads (automatic windows that popped up on the news site, even when viewers did
not click on it). The biggest opportunity for marketers is to connect this generation with ads that are likely to
invite them to participate: 58% of the Z consumers are positive about the ads. With funny content, 51% give
priority to compelling stories, 50% for good music, and 22% pay attention to celebrities.
Attracting the attention of the Z generation with advertising media in general and online TVC is a challenge.
Therefore, the research team has chosen the topic: "The reaction of Z generation consumers for online TVC”. In
this study, the authors identified a number of research questions as follows:
- Is there a relationship between the Z generation consumers and online TVC?
- If there is a relationship, how impact of online TVC to the consumer Z?
2. Literature review
Since the development of advertising for many years, there have been many researches on attitude toward
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advertising. Some outstanding works like Mackenzie & Lutz (1989), Pollay & Mitall (1993), Ducoffe (1996),
Shavitt et al., (1998), Bracket & Carr (2001).
Mackenzie & Lutz (1989) model focused on attitude-toward-the-ad, the factors included are ad perception, ad
credibility, attitude toward advertiser, attitude toward advertising and mood (Figure 1). The attitude-toward-the-
ad model points at the attitude toward any specific advertisements which like a process of specification of
attitude toward advertising.
Fig. 1. Attitude-toward-the-ad Model (Lutz & MacKenzie, 1989)
Pollay & Mitall (1993)’s seven factor model laid the foundation for the forming of attitude toward
advertising. The seven factors are product information, social role and image, hedonic pleasure, good for the
economy, falsity, corrupt values and materialism. This model was mainly used for the research on traditional
media rather than online advertising, so the author thought about it in this research.
Fig. 2. Attitude toward advertising (Ducoffe, 1996).
In his work, Shavitt (1998) thought credibility and demography are important factors which should be added
into Ducoffe (1996) model. The importance of credibility and trust was stressed by Shavitt (1998). The ad
credibility was also supported by Mackenzie and Lutz (1989) who focused on the attitude-toward-the-ad. In this
research, the author focuses on college students who have the similar demographics, so demography factor will
not be considered.
Bracket & Carr (2001) which researched attitude toward advertising in web environment validated Ducoffe
(1996) model and added two variables: credibility and relevant demographics to extend Ducoffe (1996) model.
The model was displayed below (Figure 2).
Gustaf and Ruxandra (2012) combined the whole Lutz and MacKenzie (1989) model with Ducoffe (1996)
model which was used to explain factors of attitude toward advertising in the former. The attitude-toward-the-ad
model mainly reflects the instrument, in detail advertisement itself, while the attitude toward advertising aims at
institution (Sandage & Lechenby, 1980).
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Fig. 3. Bracket & Carr (2001) model
Mehta (2000) stated that consumers’ beliefs and attitudes toward advertising are important indicators of
advertising effectiveness.
Wang, Zhang and D’Eredita (2002), Zhang and Chingning (2005), Ducoffe (1996), Brackett and Carr (2001),
Ling et al., (2010) and Saadeghvaziri and Seyedjavadin (2011), have all used parts of or all factors included in
the model to do research.
The objects of this study are college students who have the same demographics, therefore we will skip the
demography factor. The final model, which is called Ducoffe (1996) extended model is presented below in
Figure 4.
Fig. 4. The model formed in this research - Ducoffe (1996) extended model
Research models suggested in this study that the model be incorporated from the elements is said to have
influenced the response of consumers to Z to online TVC in the previous research. The model proposed in this
work is one that combined factors thought to influence Z consumers reaction in previous studies. These studies
include Ducoff, Cyril et al's, Chinging Wang et al's model. In this work, we will suggest the hypothesis and
reach the goal of research based on the above documents.
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Fig. 5. The research model of consumer reaction of Z generation to TVC online (Hoai et al)
3. Methodologies and Data
The hypothesis: This research is described in the diagram of figure 5. First of all, based on the theoretical
basis and the issues of practices, some of the major works to be done. To verify the model, a quantitative
description is the appropriate method. Firstly, a set of tools and scientific methods are used to test and get a
complete set of scales to meet the requirements in terms of the mathematical statistics in the analysis and
processing of data. This data will be used to evaluate the response of the generation Z to online TVC. Secondary,
data for this study were collected from the scientific articles, monographs, essays from a number of universities
in Vietnam and abroad.
The proposed hypotheses are:
H1: There is a positive relationship between the information of TVC online and the reaction of the Z generation.
H2: There is a positive relationship between the entertainment of TVC online and the reaction of the Z
generation.
H3: There is a negative relationship between the irritation of TVC online and the reaction of the Z generation.
H4: There is a positive relationship between the credibility of TVC online and the reaction of the Z generation.
H5: There is a positive relationship between the interactive of TVC online and the reaction of the Z generation.
H6: There is a positive relationship between the relevant demographics of TVC online and the reaction of the Z
generation.
H7: There is a positive relationship between the value of TVC online and the reaction of the Z generation.
The measurement model of testing as well as theoretical models and hypothesis will be done by the research
with 330 samples with overs 30 questions. In this section, the reaction of the generation Z is based on the
measuring questionnaire theory. The reaction of the generation Z to online TVC is through the measurement
recorded the remarks from the perspective of the people who have joined the social network use is subject to the
direct impact from online TVC. Accordingly, all the research problems are measured through the record the feel
of the 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 is built and tested to suit the conditions of
Vietnam.
After the data collected is processed by SPSS version 22th. 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 to be appropriately named by the exploratory factor
analysis (EFA).
The scale is based on previous studies by researchers such as Ducoffe (1996), Prendergast et al (2009),
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Bracket & Carr (2001) model, Ko et al. (2005). The scale of Information, Entertainment, Irritation, Advertising
value is based on Ducoffe's (1996). Scale of Credibility is based on Prendergast et al (2009). The Interactive
component scale is based on Ko et al. (2005). The Relevant Demographics is based on Bracket & Carr (2001)
model. Then the scales were adjusted and supplemented through qualitative research to suit consumers in
Vietnam.
There are seven concepts 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), Attitudes towards online TVC (ATT).
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 the Z generation consumer to online
TVC. 30 questionnaires were returned, all could be used for analysis. Scales were evaluated through the
Cronbach 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.
Initially, this research included eight measures of 37 variables. In particular, some observational variables are
from previous studies and others are new. Based on preliminary research with small samples (30 samples), some
variables are less meaningful according to experts' opinion and are removed, leading to 34 observation variables
belonging to seven scales as shown in the table, namely:
Information of online TVC scale includes 4 observation variables: INF_1, INF_2, INF_3, INF_4.
Entertainment of online TVC scale includes 4 observable variables: ENT_1, ENT_2, ENT_3, ENT_4.
Irritation of online TVC scale includes 5 observation variables: IRR_1, IRR_2, IRR_3, IRR_4, IRR_5.
Credibility of online TVC scale includes four observation variables: CRE_1, CRE_2, CRE_3, CRE_4.
Interactive scale includes 5 observation variables: INT_1, INT_2, INT_3, INT_4, INT_5.
Value of online TVC scales includes 4 observation variables: VLA_1, VLA_2, VLA_3, VLA_4.
Attitudes towards online TVC scale includes 4 observation variables: ATT_1, ATT_2, ATT_3, ATT_4.
Demographic scales with 3 observation variables: sex, education level, income.
Quantitative research was conducted by interviewing internet users in Hochiminh city through direct
interview, and indirect interview via “Google doc form”. Data collection is used to test the model and analyze
consumer attitudes toward social ads. Samples are selected by convenient method. The data analysis method
used in this study is linear structural model.
The size of the sample in this research was based on the requirement of Exploratory Factor Analysis (EFA)
and multivariate regression:
Equation 1: For Factor EFA Exploratory Analysis: Based on the research by Hair, Anderson, Tatham and
Black (1998) the expected sample size is at least five times the total number of observation variables. This is the
appropriate sample size for this research using factor analysis (Comrey, 1973; Roger, 2006). n = 5 * m
Equation 2: For multivariate regression analysis, the minimum sample size to be calculated is n = 50 + 8 * m,
where m is the number of independent variables (Tabachnick and Fidell, 1996).
Therefore, to as our principle is not missing samples we choose the number of samples satisfy both formula.
The estimated sample size of this study was n = 300.
4. Results and discussion
With a 95% confidence level, there are four factors that influence the consumer reaction to the Z generation
for online TVC. The model is shown below:
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Fig. 6. The reaction model of Z generation on TVC after testing
The one-sample T test contributes to the test of significant difference, the result will help us make a
decision whether the hypothesis should be accepted or rejected. Compared 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 (Y) are included in the model.
Table 1: Regression coefficient
Standardized
Coefficients
Unstandardized coefficients
Collinearity Statistics
Tolerance VIF
Model
t
Sig.
B
Std. Error
0.038
Beta
1
(Constant)
INF
4.924E-17
0.447
.000
1.000
0.038
0.038
0.038
0.447
11.875
7.171
0.000
0.000
0.000
1.000
1.000
1.000
1.000
1.000
1.000
ENT
0.270
0.270
0.441
IRR
0.441
11.731
INT
0.339
0.038
0.339
9.013
.000
1.000
1.000
As a result of the regression analysis, with 4 variables are accepted (enough strong) and 2 variables are
rejected (very weak), the authors write the following regression equations:
Y= 0.447INF + 0.270ENT + 0.441IRR + 0.339INT
It means:
Z Generation Consumer Response to online TVC = 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 the Z
generation.
H2: There is a positive relationship between the entertainment of TVC online and the reaction of the Z
generation.
H3: There is a negative relationship between the irritation of TVC online and the reaction of the Z generation.
H4: There is a positive relationship between the credibility of TVC online and the reaction of the Z
generation.
From accepted hypotheses, we conclude that INF, ENT, IRR, INT 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 the Z generation consumers to online TVC, the irritation has negative impact to online TVC.
The major result of this study is to show the factors that strongly influence the reaction of the generation Z
consumers to online TVC. The contribution of this research is in addition to continuing to affirm the importance
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Ao Thu Hoai/ MICA 2018 Proceedings
of the factors affecting the reaction of the Z generation to online TVC through quantitative research. It shows
that the information and irritation that most strongly influence the reaction of consumers to online TVC.
5. Conclusions
With the effort and scope, this study has achieved the following results. Firstly, systemizing the basic theories
of the Z generation, TVC online, review of the scholarly content of previous work such as Chingning Wang's
Model of Research, Ping Zhang, Risook Choi, and Michael DíCredita (2002), a model of consumer attitudes
toward advertising by Uchenna Cyril, Eze, Chai Har & Lee (2011)…etc. Secondly, doing evaluation and
commenting on previous research models, then suggesting a model that is based on the reference with 7
dependent variables. Thirdly, successfully testing a model and shows a 95% reliability of a psychometric test,
which indicates that their levels of influence is similar to the reaction of the Z generation consumer to online
TVC.
Limitations of study include: restrictions related to the sample because of 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 create questionaire.
However, this study will help business leaders decides the selection criteria to create a better TVC online,
suitable to the demand of the Z generation’s and organizations’ objectives.
Thist article is a summary of a full research report some details have been skipped. Please contact the authors
if you are interested and need more information.
About Reseach Group:
1. Leader: Ao Thu Hoai (Phd.), University of Finance and Marketing, Vietnam
2. Members: Nguyen Thi My Nhan, Dau Thi Phuong, Pham Ngoc Quynh, Nguyen Hong Tam, Nguyen Thi
Oanh (University of Finance and Marketing, Vietnam)
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