Syrian consumers: beliefs, attitudes, and behavioral responses to internet advertising.
Mahmoud, Ali Bassam
Introduction
Advertising is a standard promotional tactic that is designed to
reach a target audience and to either affect behavior or to introduce,
persuade, and/or remind consumers of an offer (Nihel 2013). Advertising
messages could be delivered through various mediums (e.g. TV, radio, and
magazines). Some scholars characterize advertising as ubiquitous and an
important part of the fabric of modern life (Shavitt et al. 1998).
Advertising has advanced with technological innovation, now common
throughout the world. Several new advertising mediums are emerging and
these have paved the way for advertisers to increase their interactivity
with target consumers. Berthon et al. (1996) were the first researchers
to investigate how advertising might operate on the internet and they
characterized it as a new medium in the marketing communication mix.
Other researchers differentiated between offline and online advertising,
suggesting that traditional media (print, TV, and radio) is based on
messages that are connected to entertainment, whereas the internet is
better viewed as an information-based medium Lei (2000). Further debate
over how to characterize the internet followed. Wolin et al. (2002: 88)
reason that the internet also possesses an entertaining component. They
see internet advertising as a broad format that consists of
"commercial content paid for by sponsors, designed for audiences,
delivered by video, print, audio, graphics or animation". Recently,
the internet has been regarded as the most powerful advertising media
(Radbata, Kubenka 2012).
With an estimated amount of $2,660,000 as an expenditure on
internet advertising in the Middle East by the year 2013 (Dubai Press
Club 2010), Advertisers targeting Syrian consumers are well aware of the
promise of the internet as an advertising. The escalation of internet
advertising has grown rapidly in Syria, and is exhibited in a wide
variety of forms (e.g. websites, banner ads, rich media ads, web logs,
electronic mail ads, and online social network advertising). While some
researchers have addressed the internet as a very effective advertising
medium Pabedinskaite, Rojute-Gaukstiene (2004), Wolin et al. (2002)
refered to the internet as a source of challenges and opportunities for
advertisers, and that includes the need for investigating internet
users' beliefs, attitudes, and even their behavioral responses
towards this type of advertising espcially when it comes to the results
of previous research which considered consumer attitudes towards
advertising as an indication of advertising effectiveness (e.g. Russell
et al. 1994; Ducoffe 1996; Mehta 2000; Wolin et al. 2002; Wolin,
Korgaonkar 2005; Karson et al. 2006; Wang, Sun 2010a, 2010b; Sun, Wang
2010; Mahmoud 2012a, 2012b). Effective internet advertising could
promote for purchase intentions towards advertised products (Sathish et
al. 2011). Therefore, modelling the relationships among beliefs about,
attitudes and behaviors towards internet advertising, through the
results of the current study, could help advertisers produce
conveniently advertising messages that reach audience more effectively
in the Syrian context. Yet while research and practice have identified
the promise of internet advertising, little is known about the impact of
internet advertising in the Syrian context as the literature has largely
focused on developed nations (Sun, Wang 2010; Wang, Sun 2010a, 2010b;
Kamal, Chu 2012). See Mahmoud (2012a, 2012b) for preliminary research
into research focusing on developing countries such as Syria. Therefore,
the aim of the present study is to validate scales measuring beliefs and
attitudes towards internet advertising with respect to the Syrian
cultural context and test a model (see Fig. 1) linking beliefs,
attitudes, and behaviors related to internet advertising. This model is
proposed on the basis of previous research and will utilize structural
equation modeling.
Literature review and research hypotheses Beliefs
Beliefs have been conceptualized as predictions held by people in
regard to the possibilities that their knowledge about a referent is
true (Wyer, Albarracin 2005) or, alternatively, that an event or state
of affairs has or will occur (Fishbein, Ajzen 1975; Eagly, Chaiken
1998). Mahmoud (2012a: 92) defined beliefs about internet advertising as
all knowledge that one could perceive as correct for internet
advertising. So consumers could perceive internet advertising as good
source of product information (JuPak 1999). Likewise, consumers may be
entertained by internet advertising as it may involve tactics such as
interactivity and multimedia (Watson et al. 1998). Conversely, internet
offers may be a source of irritation as advertising may cause feelings
of confusion if information is perceived as intense (Ducoffe 1996). Some
users of the internet may install ad blockers, which are software that
prevent internet ads from downloading on the browsed website (McCormally
2000). As well as, internet advertising could be perceived as promoting
lifestyles embodied by types of products and brands advertised online
(Pollay, Mittal 1993; Mahmoud 2012b). Internet advertising could be a
symbol
of materialism as it encourages people to achieve satisfaction
through consumption (Pollay, Mittal 1993). Falsity refers to the belief
about advertising as a source of false information and deceptive claims
(Nadilo 1998). Wolin et al. (2002) argue that internet advertising has
the ability to shape internet users' values; therefore, it could be
a cause of values corruption.
Attitudes
In general, attitudes refer to the positive or the negative
cognitive dispositions that one person holds towards a referent. In this
regard, some attitude theorists (e.g. Fazio 1989) propose that attitudes
be thought of as object-evaluation associations. That is, an attitude
can be viewed as a simple two-node semantic network, with one node
representing the object, the second node the global evaluation of the
object, and the link between the two nodes the strength of the
association (Fabrigar et al. 2005: 80). Lutz (1985: 53) defines
attitudes towards advertising, in general, as a learned predisposition
to respond in a consistently favorable or unfavorable manner to
advertising. In the context of the internet, Mahmoud (2012a: 92) refers
to attitudes towards internet advertising as a general predisposition to
like or dislike advertising messages delivered online.
Behavioral responses
Overall, behavioral responses towards advertising are prompted
actions that consumers take after exposure to an ad. Such behaviors
could be actioned through seeking of further information after watching
the ad (Nedungadi et al. 1993). In the case of internet advertising,
behavioral responses are mostly defined as "clicking on ad"
and "leaving the website showing the ad" (e.g. Wolin et al.
2002; Wang, Sun 2010a, 2010b).
Beliefs about and attitudes towards internet advertising
The investigation of the relationship between beliefs about and
attitudes towards advertising goes back to the early 1990s when Alwitt,
Prabhaker (1992) found that negative affection towards advertising was
related to the perception of advertising as a source of irritation.
Later studies have confirmed the significant role that beliefs about
advertising could play in predicting consumers' attitudes towards
advertising (Wolin et al. 2002; Yang 2003; Wang, Sun 2010a, 2010b;
Kamal, Chu 2012b; LiMing et al. 2013). Some dimensions of beliefs about
internet advertising like information (Shavitt et al. 1998; Zhou, Bao
2002; Usman et al. 2010; Eze, Lee 2012; Zabadi et al. 2012; Mahmoud
2012b; Mir 2012; Saxena, Khanna 2013), entertainment (Shavitt et al.
1998; Zhou, Bao 2002; Eze, Lee 2012; Mahmoud 2012b; Saxena, Khanna
2013), and irritation (Zabadi et al. 2012; Mahmoud 2012b; Saxena, Khanna
2013) are found to be more predictive for attitudes towards internet
advertising than other dimensions of beliefs.
Based on the above review we can state hypothesis one (H1) as
follows:
(H1): Beliefs about internet advertising will significantly
influence attitudes towards it.
Attitudes and behavioral responses towards internet advertising
Previous research results exhibit a robust relationship between
attitudes and behavioral responses towards internet advertising (Mehta
2000; Wolin et al. 2002; Sohail, Saeed 2004; Wang, Sun 2010a; Mir 2012;
Kamal, Chu 2012b). In other words, positive attitudes towards internet
advertising will probably be accompanied with favorable behavioral
responses towards internet advertising (e.g. clicking on banners for
more details about products advertised). Likewise, negative attitudes
will lead to unfavorable responses towards internet advertising (e.g.
leaving websites showing ads). For an instant, Mehta (2000) found that
consumers with favorable affection towards advertising are more likely
to recall brand advertised. Wolin et al. (2002) concluded that the more
positive attitudes towards advertising were, the greater the likelihood
would be to produce favorable behavioral responses to internet ads.
Wang, Sun (2010a; 2010b) proved, through a cross-cultural investigation,
that positive behaviors regarding clicking on internet ads are
significantly associated with favorable attitudes towards advertising.
Inspecting people attitudes and behaviors towards social media
advertising in a Middle Eastern country, Kamal, Chu (2012b) found that
behaviors towards social media advertising are significantly predicted
by attitudes.
[FIGURE 1 OMITTED]
With regard to the previous review, consideration to (H1), and
Baron, Kenny (1986) approach to hypothesizing mediations, we propose the
following hypothesis (H2):
(H2): Attitudes will fully mediate the relationship between beliefs
and behavioral responses towards internet advertising.
Methods
We adopt a quantitative procedure in analyzing the data for the
present study. We collect our data through a cross-sectional
correlational field study design (Tharenou et al. 2007).
Sample
We select randomly 384 electronic mail addresses of active internet
users from one internet service provider operating in Syria. An online
survey was sent in an e-mail to the randomly selected users and this
yielded 288 valid responses for our statistical analyses.
Measures
Measures of the present study are validated concerning the Syrian
Arab culture (see Table 1).
First, scale items to measure variables are translated from English
to Arabic and then back-translated from Arabic to English in purpose of
eliminating items that give different meanings upon this procedure.
Aiming to improve the translation accuracy, bilingual third parties are
asked to conduct the back-translation (Sun, Wang 2010a). Then we ask
academicians from the department of Marketing & International Trade
in the Higher Institute of Business Administration (HIBA), and the
department of Business Administration in Damascus University in Damascus
to evaluate the Arabic wording for our scales' items to guarantee
that our measures are face-validated. As recommended by many researchers
(e.g. Tharenou et al. 2007), our questionnaire is piloted before
distributed. The pilot study involves 57 internet users. The purpose of
this procedure is to guarantee a good understanding and acceptance by
respondents, so some questions may need deleting or modifying. Second,
measures are factor-analyzed using the approach of Principal Component
Analysis and Varimax rotation (see Table 2) to check for the
dimensionality of the scales measuring beliefs and attitudes. Third,
measures are assessed for reliability using Cronbach alpha to check for
their internal consistency (see Table 3).
Results
Demographic data description
As table 4 exhibits, our respondents consist of (56.94%) men and
(43.06%) women. The majority of the respondents hold a bachelors degree
(43.06%), with age ranging between 20 to less than 30 years (65.97%),
and a monthly income of less than 10,000 SYP or unemployed.
Hypotheses testing
The model testing hypotheses of the present study (Fig. 1) is
evaluated through the statistical method of structural equation modeling
(SEM) using SPSS-AMOS (v. 18) software. Bootstrapping is used as well to
confirm the significance of mediations exhibited in the model regardless
of normality of our data (Byrne 2010). We use the following statistics
in testing the goodness of fit: Chi-square ([chi square]) (Bollen 1989);
normed fit index (NFI) (Bentler, Bonett 1980); comparative fit index
(CFI) (Bentler 1990); root mean square residual (RMR) (Hu, Bentler
1995); and root mean square error of approximation (RMSEA) (Browne,
Cudeck 1993). Those statistics will help to test for how good the model
is in fitting the collected data.
Table 5 shows the results of the proposed model testing. The values
of RMR (0.036 < 0.05) (Hu, Bentler 1995), CFI (0.958 > 0.9)
(Bentler 1990), and NFI (0.942 > 0.9) (Bentler, Bonett 1980) indicate
a good fit for the proposed model. However, RMSEA (0.88 > 0.08)
demonstrates a poor fit of the proposed model for our data (Joreskog,
Sorbom 1989)--besides there are three insignificant paths: Social
Role--Attitude (P-value = 0.281 > 0.05), Materialism [right arrow]
Attitude (P-value = 0.218 > 0.05), and Falsity [right arrow] Attitude
(P-value = 0.176 > 0.05). Therefore, our model needs to be revised,
and then retested. AMOS suggests adding two new paths (Entertainment
[right arrow] Click on ad; Irritation [right arrow] Leave website) as
modification indices to improve the model fitting for the data.
Therefore, we eliminate the insignificant paths, draw the new suggested
two paths, and retest the alternative model. Table 6 shows the results
of testing the alternative model. All paths are significant. The
goodness of fit statistics show that the alternative model is presenting
a good fit for our data. In this regard, we notice that [c.sup.2] value
is insignificant ([chi square] df = 1.076, P-value > 5%), the normed
fit index is higher than 0.9 (NFI = 0.982), the comparative fit index is
higher than 90% (CFI = 0.999), the root mean square residual is less
than 0.05 (RMR = 0.032), and the root mean square error of approximation
is less than 0.08 (RMSEA = 0.020) (Joreskog, Sorbom 1989; Hu, Bentler
1995; Bentler 1992; MacCallum et al. 1996). Consequently, we conclude
that the alternative model expresses a good fitting for our data. As
well as, Table 8 shows that all indirect effects are significant. That
is, we come to a decision that H1 and H2 are partially supported in the
light of the following results (see Fig. 2).
Beliefs as predictors of attitudes towards internet advertising
Attitudes towards internet advertising are directly influenced
positively by information (Estimate = 0.155, P-value < 0.01, r =
0.382), and entertainment (Estimate = 0.35, P-value < 0.01, r =
0.382); and negatively by irritation (Estimate = -0.258, P-value <
0.01, r = -0.437) and values' corruption (Estimate = -0.141,
P-value < 0.01, r = -0.375).
Beliefs as predictors of behaviors towards internet advertising
Irritation positively influences consumers' behaviors of
bouncing away from websites that show the ads (Estimate = 0.368, P-value
< 0.01, r = 0.282). Entertainment positively influences
consumers' behaviors of clicking on internet ads for further
information concerning advertised products (Estimate = 0.245, P-value
< 0.01, r = 0.494).
Attitude as a mediator between internet advertising beliefs and
behaviors
Attitudes fully mediate the relationships between beliefs of
information (P-value < 0.01), irritation (P value < 0.01), and
values' corruption (P-value < 0.01) and the behaviors clicking
on online ads, and partially mediate the relationship between
entertainment (P-value < 0.01) and the behaviors of clicking on
internet ads.
Attitudes fully mediate the relationships between beliefs of
information (P-value < 0.05), entertainment (P-value < 0.05), and
values' corruption (P-value < 0.05) and the behaviors of leaving
websites showing the ads, and partially mediate the relationship between
irritation (P-value < 0.05) and the behaviors of leaving websites
showing the ads.
Discussion
The present study finds that Syrian consumers perceive beliefs
about internet advertising as a multi-dimensional construct (i.e.
information, entertainment, the social role, materialism, falsity,
values corruption, and irritation), and attitude as a uni-dimensional
construct. This result concurs with previous findings of the literature
(e.g. Alwitt, Prabhaker 1992; Wolin et al. 2002; Wang, Sun 2010b;
Mahmoud 2012a, 2012b).
[FIGURE 2 OMITTED]
Irritation is found to exert a direct effect on Syrian
consumer's behavioral responses of leaving the website that
presents the ads. For example, if consumers get encountered with a
website bearing many ads, those consumers will probably feel confused
and consequently leave the ads-bearing site. That is, consumers who
perceive of internet ads as being irritating or confusing will probably
drive Syrian consumers to leave the website showing the ads, regardless
of whether he or she holds favorable or unfavorable affects towards
internet advertising in general. This result is considered a significant
contribution to the current literature as beliefs could directly
influence consumer behavioral responses towards internet advertising.
Our results also show that entertainment directly influences Syrian
consumers' responses towards clicking on internet ads to get
additional information related to the advertised product. So, perceiving
internet advertising as a source of entertainment (e.g. containing flash
games) may predict consumers to click on internet ads, even if Syrian
consumers hold negative attitudes to internet advertising in general.
Proving a direct relationship between entertainment and clicking on
internet ads, a contribution has been made to current literature
demonstrating that beliefs could be directly linked to behavior.
Attitudes towards internet advertising is found to mediate fully
the relationship between some beliefs (i.e. information, irritation, and
values corruption) and the behavioral response of clicking on internet
ads (Shavitt et al. 1998; Wolin et al. 2002; Zhou, Bao 2002; Yang 2003;
Wang, Sun 2010a, 2010b; Usman et al. 2010; Eze, Lee 2012; Zabadi et al.
2012; Kamal, Chu 2012b). Additionally, attitudes are found to partially
mediate the relationship between entertainment and clicking on internet
ads. This finding implies that Syrian consumers with positive beliefs
about internet advertising will probably form favorable attitudes
towards it and consequently enhance the possibility of clicking on
internet ads. Moreover, Syrian consumers who like internet advertising
in general, will likely click on internet ads, even if they describe
those ads as entertaining or not.
The present study finds that attitudes toward internet advertising
in general mediates fully the relationship between some beliefs (i.e.
information, entertainment, and values corruption) and the behavioral
response of leaving the website showing the ads (Shavitt et al. 1998;
Wolin et al. 2002; Zhou, Bao 2002; Yang 2003; Wang, Sun 2010a, 2010b;
Usman et al. 2010; Eze, Lee 2012; Zabadi et al. 2012; Kamal, Chu 2012b).
In addition, attitude towards advertising will mediate partially the
relationship between irritation and leaving the website showing ads.
That is, when Syrian consumers hold positive beliefs about internet
advertising, they probably develop favorable affection and consequently
are less possible to leave a website with an advertising content. As
well as, Syrian consumer with positive attitudes towards internet
advertising will probably keep navigating the website, even if they find
internet ads irritating or not.
Implications
Researchers are advised to consider using the validated scales used
in the present study, when they measure public beliefs about and
attitudes towards advertising in the Syrian or even in the Arab country
contexts.
Advertisers promoting in Syria are encouraged to influence Syrian
consumers' beliefs about internet advertising to be more positive
and less negative. That could be through working towards having internet
advertising more informative (e.g. Providing timely product-related
information), more entertaining (e.g. including flash games within
internet ads, or enclosing amusing pictures), less irritating and
confusing (e.g. avoiding high volumes of ads within a website), and less
values corruptive or pro-values through enhancing targeting tools in a
way preventing kids from being exposed to inappropriate ads (e.g. Most
social networks ads are accurately communicated to targeted segments of
consumers). So consumers will mostly have more favorable affection and
that leads to more favorable behavioral responses towards internet ads
in respect to click on them or the period of time that consumers spend
exposing to them.
Limitations and suggestions for future research
The results of this research in regard to the relationships between
beliefs, attitudes, and behaviors towards internet advertising may need
further investigation in cases of other electronic advertising media
(e.g. SMS ads) or other traditional advertising media (e.g. newspapers,
magazines, or radio ads) to test the validity of our results across
different advertising medium types (e.g. Mittal 1994; Mahmoud 2010).
A cross-sectional method is used in the present study, That is,
some researchers make criticism of using cross-sectional design in
testing causal relationships (e.g. Reisel et al. 2010). So, it is
recommended to conduct further investigations for our results using a
longitudinal design, as having longitudinal data will help check
consistency across waves. Besides, this research lacks the use of
qualitative data, which could contribute in giving more meaningful
results when used in accompany with quantitative data (Tharenou et al.
2007).
Caption: Fig. 1. The Proposed Model
Caption: Fig. 2. The Alternative Path Model
doi:10.3846/btp.2013.31
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Ali Bassam Mahmoud
Arab International University, Faculty of Business Administration,
Department of Marketing, Damascus University, Faculty of Economics,
Department of Business Administration, Damascus, Syria
E-mail: elguitarrista@live.com
Received 21 June 2013; accepted 08 October 2013
Ali Bassam MAHMOUD is an Assistant Professor of marketing at Arab
International University. Dr Mahmoud holds a PhD in Management Sciences
with focus on Organizational Behavior (Higher Institute of Business
Administration) and a PhD in Marketing with a focus on Consumer Behavior
(Damascus University). Dr Mahmoud has published widely in local,
regional, and international refereed journals.
Table 1. Measures used in the present study
Dimension Item Recoded Source Scale
Information is a good N/A Ducoffe 1996 Likert
source of
product
information
provides timely N/A Likert
information
provides N/A Likert
meaningful
information
about the
product use of
other consumers
provides useful N/A Likert
information
about new
products
Entertainment is entertaining N/A Wolin et al. Likert
is pleasing N/A 2002; Likert
is fun to use N/A Ducoffe Likert
is exciting N/A 1996; Likert
Wang,
Sun 2010a,
2010b
Social Role It lets me know N/A Pollay, Likert
what is in Mittal
fashion and 1993;
what I should Wolin
buy for keeping et al.
a good social 2002
image
tells me what N/A Likert
people like
myself are
buying and
using
helps me know N/A Likert
which products
will or will
not reflect the
sort of person
I am
Materialism make you buy N/A Wolin et al. Likert
things you 2002
don't really
need
Increases N/A Likert
dissatisfaction
among consumers
by showing
products which
some consumers
can't afford
Is making us a N/A Likert
materialistic
society--
interested in
buying and
owning things
Makes people N/A Likert
buy
unaffordable
products just
to show off
Falsity Helps the R Wang, Sun Likert
consumer buy 2010a, b;
the best brand Wolin
for the price et al.
I don't believe N/A 2002; Likert
online ads Burnett
Is not N/A 2000) Likert
objective
Irritation Is irritating N/A Ducoffe Likert
Is confusing N/A 1996 Likert
Is annoying N/A Likert
insults N/A Likert
people's
intelligence
Values Makes people N/A Wang, Sun Likert
Corruption live in a world 2010a, b;
of fantasy Wolin
takes undue N/A et al. Likert
advantage of 2002)
children
Leads children N/A Likert
to make
unreasonable
purchase
demands on
their parents
Attitude Overall, I N/A Wolin et al. Likert
consider online 2002; Wang,
advertising as Sun
a good thing 2010a, b
Overall, I like N/A Likert
online
advertising
Overall, I N/A Likert
regard online
advertising as
an essential
thing
Overall, N/A Likert
watching online
advertising is
important to me
Overall, online R Likert
advertising is
not interesting
to me
Behavioral When I see N/A Wolin et al. Likert
Response online 2002
advertisement,
I click on it
for further
information
When I see N/A Likert
online
advertisement,
I leave the
website
Table 2. Factor analysis
Item Information Entertainment Social Materialism
Role
inf01 0.777
inf02 0.887
inf03 0.44
inf04 0.589
ent01 0.577
ent02 0.878
ent03 0.85
ent04 0.446
soc01 0.691
soc02 0.728
soc03 0.608
mater01 0.763
mater02 0.527
mater03 0.74
mater04 0.76
fals01
fals02
fals03
irr01
irr02
irr03
irr04
vc01
vc02
vc03
att01
att02
att03
att04
att05
Eigenvalue 2.582 2.519 1.845 2.421
%Variance 10.326 10.074 7.379 9.685
Item Falsity Irritation Values Attitude
Corruption
inf01
inf02
inf03
inf04
ent01
ent02
ent03
ent04
soc01
soc02
soc03
mater01
mater02
mater03
mater04
fals01 0.434
fals02 0.83
fals03 0.779
irr01 0.816
irr02 0.631
irr03 0.795
irr04 0.66
vc01 0.788
vc02 0.86
vc03 0.511
att01 0.355
att02 0.756
att03 0.762
att04 0.808
att05 0.786
Eigenvalue 2.051 2.892 2.287 2.55
%Variance 8.206 11.567 9.148 50.996
Table 3. Reliability test
Factor Items # Alpha
Information 4 0.712
Entertainment 4 0.757
Social Role 3 0.639
Materialism 4 0.750
Falsity 3 0.681
Irritation 4 0.807
Values Corruption 3 0.727
Attitude 5 0.743
Table 4. Demographic description
Variable Values Frequency % Frequency
Gender Males 164 56.94
Females 124 43.06
Total 288 100
Education High School or less 26 9.03
Intermediate Diploma 88 30.56
or Some years of
College
Bachelor 124 43.06
Postgrads 50 17.36
Total 288 100
Age Less than 20 years 64 22.22
From 20 to less than 190 65.97
30 years
30 years and above 34 11.81
Total 288 100
Income Unemployed or of less 155 53.82
than 10,000 SYP
10,000 to less than 58 20.14
20,000 SYP
20,000 to less than 37 12.85
30,000 SYP
30,000 SYP and above 38 13.19
Total 288 100
Variable Values Minimum Maximum
Gender Males
Females
Total
Education High School or less
Intermediate Diploma
or Some years of
College
Bachelor
Postgrads
Total
Age Less than 20 years 18 Years 50 Years
From 20 to less than
30 years
30 years and above
Total
Income Unemployed or of less 0 (Unemployed) 350,000 SYP
than 10,000 SYP
10,000 to less than
20,000 SYP
20,000 to less than
30,000 SYP
30,000 SYP and above
Total
Table 5. Proposed Model Results
The Proposed Model
The Relationship Estimate S.E.
Information [right arrow] Attitude 0.185 0.058
Entertainment [right arrow] Attitude 0.35 0.044
Social Role [right arrow] Attitude -0.042 0.039
Materialism [right arrow] Attitude 0.044 0.036
Falsity [right arrow] Attitude 0.055 0.041
Irritation [right arrow] Attitude -0.286 0.05
Values Corruption [right arrow] Attitude -0.16 0.035
Attitude [right arrow] Click on ad 1.011 0.075
Attitude [right arrow] Leave website -0.562 0.103
Chi-square P-value = 0.000 [chi square]/df = 3.232
NFI 0.942
CFI 0.958
RMR 0.036
RMSEA 0.880
The Relationship
Information [right arrow] Attitude C.R. P-value
Entertainment [right arrow] Attitude
Social Role [right arrow] Attitude 3.211 0.001
Materialism [right arrow] Attitude 7.995 0.000
Falsity [right arrow] Attitude -1.077 0.281
Irritation [right arrow] Attitude 1.233 0.218
Values Corruption [right arrow] Attitude 1.352 0.176
Attitude [right arrow] Click on ad -5.75 0.000
Attitude [right arrow] Leave website -4.619 0.000
Chi-square P-value = 0.000 [chi square]/df 13.533 0.000
NFI 0.942 -5.476 0.000
CFI 0.958
RMR 0.036
RMSEA 0.880
Table 6. Alternative Model Results
Alternative Model Results
The Relationship Estimate
Information [right arrow] Attitude 0.155
Entertainment [right arrow] Attitude 0.35
Irritation [right arrow] Attitude -0.258
Values Corruption [right arrow] Attitude -0.141
Attitude [right arrow] Click on ad 0.866
Attitude [right arrow] Leave website -0.243
Irritation [right arrow] Leave website 0.368
Entertainment [right arrow] Click on ad 0.245
Click on ad P-value = 0.375 [chi square]/df = 1.076
NFI 0.982
CFI 0.999
RMR 0.032
RMSEA 0.020
The Relationship S.E. C.R. P-value
Information 0.056 2.79 0.005
Entertainment 0.039 9.072 0.000
Irritation 0.047 -5.493 0.000
Values Corruption 0.033 -4.263 0.000
Attitude 0.084 10.252 0.000
Attitude 0.119 -2.034 0.042
Irritation 0.109 3.373 0.000
Entertainment 0.072 3.423 0.000
Click on ad P-value = 0.375
[chi square]/df = 1.076
NFI 0.982
CFI 0.999
RMR 0.032
RMSEA 0.020
Table 7. Descriptive statistics and inter-correlations
Variables Mean S.D.
Information 4.24 0.50
Entertainment 3.31 0.68 0.27 **
Social Role 3.37 0.79 0.25 ** 0.47 **
Materialism 2.91 0.85 -0.04 0.31 **
Falsity 2.51 0.70 -0.38 ** -0.09
Irritation 2.03 0.59 -0.31 ** -0.13 *
Values Corruption 3.12 0.83 -0.27 ** -0.09
Attitude 3.59 0.57 0.38 ** 0.50 **
Click on ad 2.92 0.93 0.27 ** 0.45 **
Leave website 2.01 1.05 -0.14 * -0.33 **
Variables
Information
Entertainment
Social Role
Materialism 0.35 **
Falsity -0.23 ** 0.02
Irritation -0.08 0.28 ** 0.35 **
Values Corruption -0.16 ** 0.29 ** 0.24 ** 0.37 **
Attitude 0.25 ** 0.02 -0.18 ** -0.44 **
Click on ad 0.25 ** 0.03 -0.15 * -0.34 **
Leave website -0.25 ** 0.01 0.17 ** 0.28 **
Variables
Information
Entertainment
Social Role
Materialism
Falsity
Irritation
Values Corruption
Attitude -0.38 **
Click on ad -0.21 ** 0.62 **
Leave website 0.17 ** -0.31 ** -0.36 **
** P < 0.01; * P < 0.05
Table 8. Mediation effect confirmation--Indirect effects
significance
Dimension Values Irritation Entertainment
Attitude Corruption
Click on ad 0.022 * 0.031 * 0.03 *
Leave website 0.001 ** 0.001 ** 0.001 **
Dimension Information Attitude
Attitude
Click on ad 0.031 * ...
Leave website 0.002 ** ...
** P < 0.01; * P < 0.05
