Vi
Truc Ho
Industrial
University of Ho Chi Minh City, Viet
Nam
E-mail: hotrucvi@iuh.edu.vn
Submission: 2/2/2020
Revision: 2/29/2020
Accept: 3/19/2020
ABSTRACT
The avoidance of advertising is highly relevant to
the audience, the general attitude towards the advertising and in some cases,
it will cause aversion, the boycott of a brand regardless of the one billion
designed advertising like how. This study aims to systematically examine and
review existing research conducted in the area of advertising
avoidance. By elaborating and summarizing various studies, the author provides
an overview of the main trends mentioned in the literature regarding avoiding
advertising. In this review, the author summarizes the four elementary schools
that researchers are aiming to evade advertising, including the intrinsic value
of advertising, customer perceptions, and testing for differences in personalizing
and the theory of time in advertising.
The avoidance of advertising has experimented under different media from
newspapers, television, the internet ... however, depending on the different
forms, the evading behavior of customers is different. Furthermore, the
constraints consider future studies to examine further discussion and the
proposed directions.
Keywords: advertising avoidance; customers' perceptions; intrinsic value; individual characteristics; time orientation
1.
INTRODUCTION
Avoiding advertising is an action in
which users reduce exposure to ads in different ways (Speck & Elliott,
1997). Research of the
Swedish Institute for Opinion Surveys (SIFO) shows
that people who avoid advertising on one medium almost always avoid it in all
the other media they use (Sifo,
2008).
There have been many studies using
different theories such as information theory (Chatterjee, 2005; Cho &
Cheon, 2004; Dildar & Helence, 2014; Ho, Phan & Phan, 2018; Prendergast, Tsang & Cheng, 2014), experience theory (Li & Huang, 2016; Jin
& Villegas, 2007; Ho, Phan & Phan, 2018), and the theory of social exchange consciousness
(Ketelaar et al., 2015) to explain consumer avoidance.
The first two theories suggest that
any factor that prevents an audience from accessing desired content as
"noise" (Prendergast, Tsang & Cheng, 2014), and it negatively affects judgment and behavior
(Kolb, 1984). The theory of social exchange shows that consumers consider an
exchange when their expected benefits make more sense or at least compensate
for costs or lose participation.
A new research direction recently
carried out by scientists is to avoid advertising based on the theory of time
in which time is considered a guide in behavior from a cultural perspective.
Each country has a different orientation but converges into a prominent
direction in three directions: past, present, or future (Davies &
Rojas-Méndez, 2005; Kaynak et al., 2013). Pagendarm and Schaumburg (2001) argue that people avoid advertising
because the ad position is not convenient and does not create an attraction for
customers to click to see.
Another reason is that the value of
advertising does not contain useful information or emotional value to customers
(Ho, Phan & Phan, 2018). According to Cho and Cheon (2004), customers avoid online
advertising because advertising hinders awareness. Besides, previous negative
experiences about advertising lead to judgments and decisions to avoid
advertising or behavioral bias (Kolb, 1984).
Faced with different products,
consumers refine their attention and focus on different efforts (Kim, Ghazizadeh & Hikosaka, 2015). Cho and Cheon (2004), Song and Jiang (2017)
grouped choices in three different aspects of advertising evasion, including
cognitive evasion, emotional evasion, and behavior. Rojas-Méndez and Davies
(2005) divide avoidance into two dimensions: partial and total avoidance.
Another research direction of Rojas-Méndez and Davies (2017) considers ad
evasion under two perspectives is behavioral and mechanical.
In summary, there are many different
studies done to learn about evading advertising from different perspectives,
using different theories, and experimenting in different media. Therefore, the
purpose of this study is to synthesize various studies and group them into
significant research direction to avoid advertising to contribute to a more
general view of advertising.
The advertising avoidance leads to the user's intent to skip
the advertising, and it is considered one of the biggest obstacles of
advertising. Depending on personal characteristics and other frameworks such as
demographics, target disruptions, and related issues, users may have different
ways to avoid advertising (Speck & Elliott, 1997).
According to Clancey
(1994), users avoid advertising by ignoring attention to advertising. Danaher
(1995) argues that when starting to appear during breaks between shows,
television viewers have several options: (a) to leave the room; (b) change to
another channel; (c) switch off the equipment; (d) mute the device sound; (e)
read books, magazines, newspapers ... (f) talk to other people in the room ...
Through preliminary
research, Rojas-Méndez and Davies (2005) have added the option of using
electricity voices during the ad. When researching for the online environment,
several additional observational variables are added, such as hated advertising,
ignoring and not paying attention, or using applications to block
advertisements, close the display window to avoid.
Advertising
avoidance classify into three aspects:
cognitive avoidance (tendency to ignore advertising; not to pay attention; not pay
attention despite attractive advertising), affective avoidance (hate
advertising; think that without advertising is better) and behavioral avoidance
(dynamically scroll through advertising; block advertising; remove them from
any website with a blocker app) (Cho & Cheon, 2004: Song & Jiang, 2017).
Ketelaar et al.
(2015) measured advertisement avoidance in terms of action with a statement
regarding active and passive avoidance with statements regarding ignoring
advertising in the studied media. Rojas-Méndez and Davies (2005) divide
advertising avoidance into two angles: partial avoidance (reading books,
newspapers, magazines, mute audio) and total avoidance (leaving the room;
moving to another channel).
Another research
direction of Rojas-Méndez and Davies (2017) considers it in two aspects:
behavioral avoidance (leaving the room; using a phone; reading books,
newspapers, magazines) and mechanical avoidance (turn off the TV; turn off the
sound). Noticeably, if Cho and Choen (2004) argue that behavioral avoidance
involves the use of mechanical means, Rojas-Méndez and Davies (2005) divide
into two directions, more specific in that behavior and mechanics. Other
studies consider advertising evading as a scale that combines behavioral
advertising, affective avoidance, and cognitive avoidance, but each aspect only
studies one to two items.
For example, Li and
Huang (2016) explored the advertising avoidance as follows: consumers
deliberately ignore any ads (cognitive avoidance), hate online behavioral ads
(affective avoidance), close or intercept online behavioral advertising
(behavioral avoidance). In short, depending on the different media and
different views of researchers that avoid advertising is divided into different
types.
2.
LITERATURE REVIEW
There are many reasons
for advertising avoidance in general and online advertising in particular,
which is one of the biggest obstacles for businesses. The research on
advertising avoidance is exploited under various aspects, which gather into
four research directions.
2.1.
Research direction from the
perspective of the intrinsic value of advertising
According to
Zimmerman and Bradley (2019), the intrinsic value has been characterized value
that something has in itself. Intrinsic value does not exist as an object but
is an attribute of the object. In particular, the intrinsic value that belongs
to the attributes of the advertisement. There has been a lot of research on
advertising evasion considering the intrinsic value of advertising.
Research by Ducoffe
(1996), advertising values is considered from
two angles: information value and entertainment value. At the same time,
incentive value is also a new angle to be considered in the advertising value
that was discovered and tested by Hightower (2008); Elisabeth (2009). Summary,
the value of information, entertainment, and stimulation are three main scales
that researchers experimented with and discovered.
According to
Ducoffe (1995), the information value of advertising is effective
when it suits the needs of customers. The information value of online
advertising is measured by usefulness, importance, providing lots of news
(Ducoffe, 1996; Edwards, Li &
Lee, 2002; Ho, Phan & Phan, 2018). Bracket and Carr (2001) added that the up-to-date information is also a part of the
value of advertising information when experimented with ads via mobile devices.
The results of studies have shown that informative advertising causes less
evasive behavior than advertising without useful information (Cho
& Cheon, 2004; Louise, Kerr &
Drennan, 2010).
Entertainment value
achieved through the fun, excitement, relaxation, or humor that advertising
provides (Ducoffe, 1995; Ho, Phan & Phan, 2018; Xu, 2006; Choi et al.,
2013). Many authors have demonstrated the influence of entertainment value on
advertising avoidance not only in traditional media (Ducoffe, 1995) but also
online environment (Ducoffe, 1996; Cho & Cheon, 2004; Choi et al., 2004).
According to Diaz, Hammond and McWilliam(1997); Edwards, Li and Lee. (2002); Cho
and Cheon (2004), there are an negative relationship between entertainment
value and advertising avoidance behavior. Specifically, if the user perceives a
higher level of entertainment, the harder it is to avoid advertising. According
to Xu (2007), entertainment value relates to the attitude of being fascinated
with the message that the advertisement brings, so that the less the customers
avoid.
Encouraging value
is considered in such content as grasping many trends, becoming smart
consumers, knowing much promotional information (Ho, Phan & Phan, 2018; Xu,
2007; Ducoffe, 1995), dimensions and determination format
of advertising (Chatterjee, 2005), authenticity (Dildar & Helence, 2014),
the interactivity that advertising brings, the popularity of advertising
(Okazaki, Molina & Hirose, 2012) ... Research results showed that the more
encouraging valuable the advertising is, the less likely it is for the viewer
to avoid it (Hightower, 2008).
The following model
showed that the factors affect the intention of advertising and advertising
avoidance.
Figure 1: The intrinsic value of the
advertising module
In this research direction, many
published works have experimented on various media: banner and pop-up
(Chatterjee, 2005); social networking site (Ho, Phan & Phan, 2018); mobile device (Okazaki, Molina & Hirose, 2012; Sung-Hee, 2016; Xu, 2006); online
environment (Dilar & Hellen, 2014) ... Depending on the studies conducted
in different locations, subjects, and media, the impact level of the factors is
different.
However, the common ground of all
studies was that the attitude towards advertising strongly influenced the
avoidance of advertising. These studies report consumer distrust about advertising,
leading to a strong tendency to avoid advertising. Besides, according to the
result of Sung-Hee (2016), value
advertising affects directly to avoidance. In short, the internal values of the
advertising can have a direct impact on the evading of the ad and also
indirectly through user behavior. However, the higher the advertising value,
the more likely it will be to avoid advertising. At the same time, depending on
the media and audience characteristics, the value of information,
entertainment, or encouragement has different levels of impact on avoiding
advertising.
2.2.
Research direction from the
perspective of customers' perceptions
When talking about
perception, we always have to keep in mind that we perceive the world not as it
is, but as we think it is (Durmaz & Diyarbakirlioglu, 2011). Customer
perceptions represent the way consumers handle and interpret information,
express the opinion of the consumer about the product or service, which
directly affects consumer behavior (Mcneal, 2007). By the different approaches,
marketers can directly influence user perceptions (Berenbaum & Larkin, 2007).
Mainly, in
advertising avoidance aspect, the perception of customers focus on advertising
hindering the cognitive goal by limiting the number of related actions to user
goals (Cho & Cheon, 2004; Li & Huang, 2016; Ho, Phan & Phan, 2018);
aware of advertising clutter (Cho & Cheon, 2004), customers have negative
experiences from previous (Cho & Cheon, 2004; Li & Huang, 2016) or
information privacy concerns (Okazaki, Molina &
Hirose, 2012; Gurau & Ranchhod, 2009).
The study of
Chaterjee (2008) discovered that consumers felt that they interrupted their
goals when advertising appears. Perceived goal impediment caused by advertising
on Internet media is much more than traditional media because it is considered
to be more goal and task-oriented (Cho & Cheon, 2004).
That means that
when they want to continue to see something on the website, they are forced to
click on the advertising and complete the processing of the information
compelled to click on the advertising and get done with the information
processing on the advertiser's site or compulsively click close the ad to
resume the original task online.
Perceived goal
impediment was measured by items as makes harder, disrupts the flow of texting,
disrupts or hinders from using other content/services, disrupts receiving
desired incoming content, infringes on control, intrudes on search for desired
information (Cho & Cheon, 2004; Edwards, Li & Lee, 2002; Speck & Elliott, 1997, Shin & Lin, 2016).
It is these activities that cause discomfort for users, which in turn leads to
avoiding advertising (Nettelhorst & Brannon,
2012).
Cluttered
advertising is considered as the presence of a large amount of non-editorial
content (Ha & Mccann, 2008). Fennis and Bakker (2001) have applied
information theory in advertising research, saying that because consumers have
limited ability to process information, overloading causes users to react
negatively, from that leads to outrage and avoiding advertising (Ha &
Litman, 1997). When researching on advertising clutter, the scales are measured
as exclusiveness, irritation, excessiveness (Seyedghorban, Tahernejad &
Matanda, 2015). Specifics, if advertising clutters, consumers are likely to
have difficulty in discriminating between messages, leading them to disregard
all messages in this space (Cho & Cheon, 2004).
Theory of
experience (Kolb, 1984) shows that people make decisions based on
their prior negative experiences. Researchers point out that consumers with
experience will be the basis for shaping their future attitudes and behaviors (Hong
& Sternthal, 2010). According to Cho and Cheon (2004), consumers' negative
experience about advertising is deceptive, exaggerated, incorrectly targeted,
or leads users to inappropriate sites.
The other aspects
concerning experience such as awareness of the lack of usefulness of
advertising (Obermiller, Spangenberg & Maclachlan, 2005); intrusive advertising,
hateful ads, annoying, annoying ads (Guesenhues, 2017); or the feeling of
disappointment in advertising, not receiving the benefits and motivation when
watching ads ... (Li & Huang, 2016; Ho, Phan & Phan, 2018). Also, the lack of utility of advertising or the
promotion of inadequate incentives can lead to avoiding advertising (Obermiller,
Spangenberg & Maclachlan, 2005).
With the
characteristics of an online environment, where there is a high level of
interaction, information privacy is increasingly concerned and becomes an
urgent issue because of the level of personal information collection and
information storage its duration. (Okazaki, Molina & Hirose, 2012).
According to
research by Smith, Milberg and Burke (1996), to
measure information privacy concerns, there are four aspects to include: proper
access to the personal information collection, errors, and unauthorized
secondary use ... Malhotra, KIM and Agarwal (2004) based on
Smith, Milberg
and Burke (1996) developed an extended
scale to measure Internet users based on a social contract theory consisting of
three elements: collection, control, and awareness of privacy practices.
Okazaki, Molina and Hirose
(2012) also agree with the scales in information privacy concerns of Malhotra, Kim and Agarwal (2004) when they experimented with mobile
advertising.
The results of
these studies suggest that hindering cognitive goals is a significant factor in
avoiding advertising, but paying little attention to advertising
incompatibilities. Besides, previous negative experiences about advertising
lead to judgments and decisions to discover ads, leading to behavioral bias. In
short, when customers have a negative experience, they often have a terrible
attitude towards advertising, from which to form advertising avoidance.
Therefore, creating a good impression with customers is something that
businesses should be a concern.
2.3.
Research direction from testing the
difference in advertising avoidance
In this research
direction, the researchers focused on the differences in advertising avoidance
that come from characteristics that belong to individuals, namely gender,
marital status, age, income, submission, education ... (Speck & Elliott,
1997; Gregorio, Jung & Sung, 2017), religious character (Fam, Walle & Erdogan,
2004; Ketelaar et al., 2015). In particular, Speck and Elliott (1997) examined
advertising evasion predictions in 946 American respondents with different
races on four media: magazines, newspapers, television, and radio.
The results
indicate that racial origin does not affect advertising avoidance behavior, but
age and income are the best demographic predictors in the media for their
ability to avoid advertising audience. Also, factors such as household size,
education level, and marital status have different impacts depending on each
specific media:
Table 1: Summary of some
cases of avoidance behavior
Media |
Where there is an act of avoiding
advertising |
Magazine |
Respondents have
a high income, small household size. |
Newspaper |
Respondents are
old, have high education and income. |
Television |
Respondents are
young or have a high income. |
Radio |
Respondents are
young and unmarried. |
Source:
Speck and Elliott (1997)
Following
experiments in the US, the research results of Gregorio, Jung and Sung (2017)
obtained similar results with Speck and Elliott (1997) on the influence of age
and income on four types of media: magazines, newspapers, television, and
radio. However, in contrast to the results of Speck and Elliott (1997),
Gregorio, Jung and Sung (2017) find significant differences among ethnic
groups: African-Americans have shown the least level of advertising avoidance
for all four media analyzed, and also show attitudes affected to positive for
advertising.
This is also an
area that Speck and Elliott (1997) had not exploited intensely when the authors
focused the survey sample on two racial groups, white and black, but not
identified by ethnic origin. Extensive research with the 2002 sample size by
Gregorio, Jung and Sung (2017) has demonstrated that different racial
backgrounds have different degrees of advertising evasion.
The study of
Ketelaar et al. (2015) shows that religious people are less likely to avoid
advertising than non-religious individuals. At the same time, it proves the
opposite of Fam, Walle and Erdogan (2004) that religious followers have a more
negative attitude towards advertising, especially ads related to political
views, ads for controversial products and services such as alcohol, drug
leaves, and contraceptives.
Thus, in addition
to age and income are two demographic variables that have quite similar effects
on advertising avoidance behavior, ethnic origin, religion, household size,
educational level, status multipliers are variables that always change in
different experimental environments.
2.4.
Research direction involves a
theoretical of time
Taking a theoretical view of time as a recent approach, researchers
learn about advertising avoidance based on a time perspective, including time
allocation and time orientation.
The recent first approach of Rojas-Méndez and Davies (2017) is to
use time allocation theory, considering time as a scarce resource (Wolburg,
2001) to save, spend, waste, and lost. In this approach, Rojas-Méndez and
Davies (2017) have time under two aspects: time planning and time pressure to
avoid advertising behavior.
In it, time pressure
is a perception that time is not enough to do all that is needed, and time
planning is considered the basis for understanding time allocation decisions (Brodowsky
& Anderson, 2000). Research results show that avoidance behavior varies by
country; the British, when pressured by time, tend to avoid behaviorally and
for those who plan time to avoid the local mechanical aspect (turn off the
television, turn off the volume ...).
In Chile, they often
have a time plan and tendency to avoid advertising in terms of behavior
(leaving the room, talking on the phone, reading books, reading newspapers
during the advertising period). However, in this study, athough looking at a
different time perspective, researchers are still looking to experiment and
compare avoidance advertising between different time-oriented.
Another area of research that is also of great
interest to researchers is the consideration of avoiding time-based
advertising. Time orientation is the tendency of a person to focus on value,
and use consistently as a specific reference frame in the past, present, or
future (Lin & Mowen, 1994). Accordingly, advertising often includes a call
to action now or soon, but the reasons for buying or using products and
services may vary between individuals with a past orientation, present, or
future (Rojas-Méndez
& Davies, 2005; Kuswati,
2011; Kaynak, Kara
& Apil, 2011).
Kaynak et al. (2013)
are focusing on the viewpoint of time as a feature of the culture in which the
authors focus their research on advertising evasion and empirical comparisons
between countries, also known as text comparisons cross-culture. A pioneer in
this ad-dodging study is author Rojas-Méndez & Davies (2005), who developed
a time-oriented theory to apply to ad-avoidance on television advertising and
compare the differences between two different cultures in England and Chile, in
which the England is considered a country with a past orientation and Chile is
identified as a country with a current orientation.
The research results
show that it is not possible to apply advertising to all countries at the same
time because the experiments between the two countries have two different time
orientations showing different beliefs, attitudes, and behavior of avoidance. Furthermore, research has confirmed that people
have faith in advertising, but people with a past orientation have a negative
attitude towards advertising, and those with a current orientation have a
positive attitude.
However, Kuswati
(2011) finds contradiction with an exploration of Rojas - Méndez and Davies (2005), who discovered the behavioral pattern of avoiding
viewing television advertising on time orientation. The beliefs and attitudes
used by Rojas - Méndez and Davies (2005) cannot be used because it does not indicate an appropriate
kindness index when the context of another study.
Kuswati (2011),
using a nested model by adding structured relationships, found that individuals
with current and future directions do not have absolute faith in advertising on
television. Therefore, this study indicates that an individual may have a
positive belief in advertising but negative behaviors in which they try to
avoid seeing it. Also, there is a direct relation from attitude to time
orientation, in particular, the present and the future orientation without
mediating beliefs like the discovery of Rojas-Méndez and Davies (2005).
The use of an
integrated model also helps Kuswati (2011) discover a direct relationship in
the past and present directions to the act of avoiding watching television
advertisements. Two significant influences: the past-oriented individual
negatively influences the behavior of avoiding seeing it while the
present-oriented individual positively affects the behavior of avoiding seeing
it.
Another study by the
authors Kaynak, Kara and Apil (2011)
experiments for TV advertising at Georgian concludes that time orientation and
advertising attitude are considered as predictors of advertising avoidance
behavior. A recent study by Kaynak et al. (2013) at Georgian and Macau also
discovered that some people are future-oriented but not excited about
advertising, and they will switch to another channel and participate in other
activities during the advertising period.
In summary,
the authors in the past we can see a contradiction through the findings of the
authors. If Rojas-Méndez and Davies (2005) assert that past-oriented people
have behaviors to avoid advertising and those with other orientations do not.
Kuswati (2011) argues that people with a present and future orientations tend
to avoid them if advertisements do not relate to the areas in which they are interested.
Meanwhile, when studying in Macau, confirmed that these subjects avoided
advertising but in different ways (Kaynak, Kara & Apil, 2011). Thereby, we see that
there is still much debate around the issue of avoiding advertising based on
this time-oriented theory.
2.5.
A summary of the research related to
advertising avoidance
Table 2: A summary of
advertising avoidance
Media |
Authors |
Year |
Research direction |
Aspect to avoidance |
Banner and Pop – up |
Chatterjee |
2005 |
Intrinsic value |
Cognitive avoidance Physical
avoidance |
Media (newspaper, magazine, radio, television) |
Speck and Elliott |
1997 |
Personal characteristics |
Behavioral avoidance |
Gregorio, Jung and Sung |
2017 |
Behavioral avoidance |
||
Social networking site |
Kelly, Gayle and Drennan |
2010 |
Customers'
perceptions |
Cognitive avoidance Behavioral avoidance |
Ho, Phan and Phan |
2018 |
Intrinsic value Customers'
perceptions |
Cognitive avoidance Behavioral avoidance |
|
Mobile device |
Okazaki, Molina and Hirose |
2012 |
Intrinsic value |
Behavioral avoidance |
Digital media |
Ketelaar et al. |
2015 |
Personal characteristics |
Active
avoidance Passive
avoidance |
Television |
Rojas-Méndez and Davies |
2017 |
Allocated time |
Partial
avoidance |
Rojas-Méndez and Davies |
2005 |
Time Orientation |
Partial
avoidance Total avoidance |
|
Kaynak et al. |
2013 |
Behavioral avoidance |
||
Online environment |
Cho and Cheon (2004) |
2004 |
Customers'
perceptions |
Behavioral avoidance Effective avoidance Cognitive avoidance |
Dildar and Helence (2014) |
2014 |
Intrinsic value |
Behavioral avoidance |
|
Jin and Villegas |
2012 |
Customers'
perceptions |
Overall behavior |
|
Li and Huang |
2016 |
Customers'
perceptions |
Overall behavior |
With the above summary, we find that there is quite a bit
of research done to explore different advertising perspectives. Also, the
authors conducted experiments on many different media such as online
environment, social networks, mobile devices, digital media, television,
banners, and pop-ups. .. to learn the different influences in media on avoiding
advertising.
However, from the perspective of
avoiding advertising on time-oriented theory, currently, the number of studies
is quite limited, focusing only on experiments in some countries and the
results of the authors are still causing controversy, debate, especially this
study was done only on the media on television, but in other media, it has not
been studied in depth. Thereby, we see that there is still much debate around
the issue of avoiding advertising based on this time-orientation theory and
that there is a need for empirical research in different countries to help
researchers the most comprehensive and comprehensive picture.
3.
DISCUSSION
Through the analysis of the literature, we find that there are quite
several studies using research methods with different perspectives on the
experimental selection on different media such as online environment, social
networks, mobile devices, digital media, television, banners, and pop-ups ...
Currently, the research findings discovered that the study dodges advertising
to different schools.
If the schools of intrinsic value, customer awareness about advertising
and the difference in demographic characteristics have been studied quite a lot
and the results bring a high uniformity, avoid advertising on the time-oriented
theory the number of studies is quite limited, focusing only on experiments in
many countries and on television advertising.
Therefore, in the future, more research on advertising evasion based on
time-orientation theory in different media, as well as experiments in different
countries, will be needed to help researchers built the most general picture of this
advertising avoidance. Besides, examining the different schools of advertising
evasion gives us a better overview of advertising so that businesses can
understand the cause of advertising avoidance to made appropriate solutions for
business.
REFERENCES
Berenbaum,
D., & Larkin, T. (2007). How to Talk to Customers, Create A Great
Impression Every Time With Magic. Communico Ltd.: San Francisco, 63.
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.
Brodowsky, G. H., & Anderson, B. B. (2000). A
cross-cultural study of consumer attitudes toward time. Journal of Global Marketing, 13(3), 93-109.
Chatterjee, P. (2005). Changing banner ad executions on
web: Impact on Click-throughs and communication outcomes. Advances in Consumer
Research, 32, 51-57.
Cho, C. H., & Cheon, H. J. (2004). Why do people
avoid advertising on the internet. Journal
of Advertising, 33(4), 89-97.
Choi, S. M., Kim, E.,
Kim, S., & Yeh, Y. H. (2013). Factors Affecting Advertising
Avoidance on Online Video Sites. The
Journal of Advertising and Promotion Research, 2(1), 87-121.
Clancey, M. (1994). The television Audience Examined. Journal Advertising Research, 39(5),
27-37.
Danaher, P. J. (1975). What Happens to Television
Ratings During Cornmcrcial Breaks?. Journal or Adcertising Research, 35, 37-48.
Davies, G., & Rojas-Méndez, J. I. (2005). Avoiding
Television Advertising: Some Explanations from Time Allocation Theory. Journal of Advertising Rearch, 45(1),
34-48.
Diaz,
A. N., Hammond, K. &
Mcwilliam, G.
(1997). A
Study of Web Use and Attitudes Amongst Novices, Moderate Users and Heavy Users. EMAC,
1624‐1635.
Dildar, H., &
Helence, L. (2014). Online Video Advertisement Avoidance: Can Interactivity
Help?. Journal of Applied Business Research,
30(1), 43-49.
Ducoffe, R. H. (1995). How Consumers Assess the Value of
Advertising. Journal of Current Issues
& Research in Advertising, 17(1), 1-18.
Ducoffe, R. H. (1996). Advertising Value and Advertising on the Web. Journal of Advertising Research, 36(5), 21‐35.
Durmaz, Y., & Diyarbakirlioglu, I. (2011). A Theoritical Approach To The Role Of
Perceptıon On The Consumer Buyıng Decısıon Process. Business Management Dynamics, 1(3), 17-21.
Edwards,
S. M., Li, H., & Lee, J. H. (2002). Forced
exposure and psychological reactance: Antecedents and consequences of the
perceived intrusiveness of pup‐up ads. Journal of Advertising, 31(3), 83‐95.
Elisabeth,
J. (2009). Network
Television Streaming Technologies and the Shifting Television Social Sphere,
Paper presented Media in Transition 6: Stone and Papyrus, Storage and Transmission. International Conference 2009 Massachusetts Institute of
Technology.
Fam,
K. S., Waller, D., & Erdogan,
B. Z. (2004). The influence of religion on attitudes towards the
advertising of controversial products. European Journal of Marketing,
38(5/6), 537-555.
Fennis, B. M., &
Bakker, A. B. (2001). Stay Tuned—We Will Be Back Right after these
Messages: Need to Evaluate Moderates the Transfer of Irritation in Advertising.
Journal of Advertising, 30(3),
15–25. doi:10.1080/00913367.2001.10673642.
Gesenhues, A. (2017). 37% of consumers say ads placed next to offensive content impact brand
perception - Marketing Land. [online] Marketing Land. Available at:
https://marketingland.com/37-consumers-say-adsplaced-next-offensive-content-impact-brand-perception-217504
[Accessed 19 Nov. 2018]
Gregorio, H., Jung, J.
H., & Sung, Y. (2017). Advertising
Avoidance: A Consumer Socialization Perspective. Online Journal of Communication and Media Technologies, 7(3), 1-26.
Gurau, C., &
Ranchhod, A. (2009). Consumer privacy issues in mobile c commerce: a
comparative study of British, French and Romanian consumers. Journal of Consumer Marketing, 26(7),
496–507.
Ha, L., &
Mccann, K. (2008). An integrated model of advertising clutter in offline and
online media. International Journal of
Advertising, 27(4), 569-592. doi: 10.2501/ S0265048708080153.
Ha, L., &
Litman, B. R. (1997). Does Advertising Clutter Have Diminishing and Negative
Returns? Journal of Advertising,
26(1), 31–42. doi:10.1080/00913367.1997.10673516.
Hightower,
R. T. (2008). Hulu: Video & Effective Advertising.
Ho, T. V., Phan, T.
N., & Phan T. S. T. (2018).
Advertising avoidance and brand awareness - A research about video ads form on
social network sites of the youth in Ho Chi Minh city. Can Tho University Journal of
Science,
54(4D), 159-167.
Hong,
J., & Sternthal, B. (2010). The Effects of Consumer Prior
Knowledge and Processing Strategies on Judgments. Journal of Marketing Research,
47(2), 301–311.
doi:10.1509/jmkr.47.2.301.
Jin,
C. H., & Villegas, J. (2007). Consumer Responses to Advertising on the Internet: The Effect of
Individual Difference on Ambivalence and Avoidance. CyberPsychology & Behavior, 10(2), 258-266.
Kaynak,
E., Kara, A.,
& Apil, A. R. (2011). An
investigation of people’s time orientation, attitudes, and behavior toward
advertising in an international context. Journal
of Global Marketing, 24(5), 433–452.
Kaynak,
E., Clement, A. K., Chow, S. F., & Apil, A. R. (2013). Pattern of similarities/differences in time
orientation and advertising attitudes. Asia
Pacific Journal of Marketing and Logistics, 25(4), 631-654.
Kelly, L., Gayle,
K., & Drennan. J. (2010). Avoidance of Advertising in Social Networking Sites:
the teenage perspective. Journal of
Interactive Advertising, 10(2), 16‐27.
Ketelaar, P., Konig,
R. P., Smit, E. G., & Thorbjornsen. H. (2015). In ads we
trust: religiousness as a predictor of advertising trustworthiness and
avoidance. Journal of Consumer
Marketing, 32(3), 190-198.
Kim, H. F., Ghazizadeh,
A., & Hikosaka, O. (2015). Dopamine Neurons Encoding Long-Term Memory
of Object Value for Habitual Behavior. Cell,
163(5), 1165–1175. doi:10.1016/j.cell.2015.10.063.
Kolb,
D. (1984). Experiential Learning:
Experience as the Source of Learning and Development. New Jersey:
Prentice-Hall.
Kuswati, R. (2011). A Nested Model of Analyzing An Influence of Time
Orientation on Behaviour of Avoiding Television Advertising. Proceeding Narratives of Sustainable Development,
335-374.
Li, W., &
Huang, Z. (2016). The Research of Influence Factors of Online Behavioral
Advertising Avoidance. American Journal
of Industrial and Business Management, 6(9), 947-957.
Lin,
X., & Mowen, J.C. (1994). Time
Orientation and Consumer Behaviour: Theoretical and Scale Development. American Marketing Association, Summer, 277-83.
Louise,
K., Kerr, G., & Drennan, J. (2010).
Advoidance of Advertising in Social Networking Sites: The Teenage Perspective. Journal of Interactive Advertising, 10( 2), 16-27.
Malhotra, N. K., Kim, S., & Agarwal, J. (2004). Internet
users’ information privacy concerns (IUIPC): The construct, the scale, and a
causal model. Information Systems
Research, 15(4), 336–355.
Mcneal,
J. U. (2007). On Becoming A Consumer,
The Development Of Consumer Behavior Patterns In Childhood. Elsevier Inc.: USA, 19.
Nettelhorst, S. C., & Brannon, L. A. (2012). The effect of advertisement
choice on attention. Computers in Human
Behavior, 28(2), 683-687.
Obermiller, C.,
Spangenberg, E., & Maclachlan, D. (2005). Ad Skepticism:
The Consequences of Disbelief. Journal
of Advertising, 34(3), 7-17.
Okazaki, S., Molina,
F. J., & Hirose, M. (2012). Mobile
advertising avoidance: exploring the role of ubiquity. Electronic Markets, 22(3), 169–183. doi:10.1007/s12525-012-0087-1.
Pagendarm, M., &
Schaumburg, H. (2001). Why Are Users Banner-Blind? The Impact of Navigation
Style on the Perception of Web Banners. Journal
of Digital Information, 2(1), 33-45.
Prendergast,
G. P., Tsang, S. L.,
& Cheng, R. A. (2014).
Predicting handbill avoidance in Hong Kong and the UK. European Journal of Marketing, 48(1/2), 132-146.
Rojas-Méndez, J. I., & Davies, G. (2005). Avoiding television advertising: some
explanations from time allocation theory. Journal
of Advertising Research, 45(1), 34-48.
Rojas-Méndez, J.
I., & Davies, G. (2017). Time
Pressure and Time Planning in Explaining Advertising Avoidance Behavior. Journal of Promotion Management, 23(4),
481–503.
Seyedghorban, Z., Tahernejad, H.,
& Matanda, M.
J. (2015). Reinquiry into Advertising Avoidance on the Internet: A
Conceptual Replication and Extension. Journal
of Advertising, 45(1), 120–129.
Shin, W., &
Lin, T. T.-C. (2016). Who avoids location-based advertising and why?
Investigating the relationship between user perceptions and advertising
avoidance. Computers in Human Behavior,
63, 444-452.
Sifo Research International. (2008). Advertising Advoidance: The Quiet Consumer Revolt. Stockhom: SIFO
Research International.
Smith,
H. J., Milberg, S. J.,
& Burke, S. J. (1996). Information privacy: measuring
individuals' concerns about organizational practices. MIS Quarterly, 20(2), 167-196.
Song, H., & Jiang. Y. (2017). Online Personalized Advertising Avoidance by
Chinese Consumers: The Effect of Consumer Good Types. Noble
International Journal of Business and
Management Research, 01(06), 107-117.
Sung-Hee, J. (2016). An exploratory study on
avoidance of mobile video ad: role of perceived ad value, ad
intrusiveness and motivations to view mobile video. Asian Journal of Information and Communications, 8(2), 78-95.
Speck, P. S., &
Elliott, M. T. (1997). Predictors of Advertising Avoidance in Print and
Broadcast Media. Journal of Advertising,
26, 61-76.
Wolburg,
J. (2001). Misplaced marketing: Why television is the “wrong” environment for
public service advertising campaigns. Journal
of Consumer Marketing, 18(6), 471-473.
Xu, D. J. (2006). The influence of personalization in
affecting consumer attitudes toward mobile advertising in China. The Journal of Computer Information Systems,
47(2), 9–19.
Zimmerman,
M. J.,
& Bradley, B. (2019). Intrinsic
vs. Extrinsic Value. The Stanford Encyclopedia of Philosophy. Edward N. Zalta (ed.). URL =
<https://plato.stanford.edu/archives/spr2019/entries/value-intrinsic-extrinsic/>.