Journal of Software Engineering and Applications, 2013, 6, 564-570
Published Online November 2013 (
Open Access JSEA
Impact of Internet Advertisement and Its Features on
E-Commerce Retail Sales: Evidence from Europe
Osama Harfoushi1, Bader Alfawwaz2, Bader Obeidat3, Ruba Obiedat1, Hossam Faris1
1Department of Business Information Technology, The University of Jordan, Amman, Jordan; 2Department of Computer Information
System, Al-albayt University, Mafraq, Jordan; 3Department of Business Administration, The University of Jordan, Amman, Jordan.
Received September 4th, 2013; revised October 1st, 2013; accepted October 10th, 2013
Copyright © 2013 Osama Harfoushi et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The stimulus to carry out this research is to investigate the relationship between internet advertisement and its features
on the total E-commerce sales of the top five countries of Europe. The units of analysis are the individuals of UK,
France, Italy, Germany and Netherland. Secondary data are collected from the reports of [1] (ADEX, 2010) and [2] (Eu-
rostats, 2011). To empirically determine the relationship between independent variable and dependent variable in the
European context, the study uses various statistical techniques, including OLS regression and correlation analysis tech-
niques. The empirical findings indicate that the Internet advertisement features of search advertisement and classified
advertisement have positive significant relationship with the E-commerce sales in Europe. The empirical findings indi-
cate negative significant relationship of display advertisement with the E-commerce sales in Europe. However, this
variable is also justified with the help of literature. Findings also demonstrate that search advertisement has strong posi-
tive relationship and it generates positive influence for the E-commerce sales as compared to the classified advertise-
ment and display advertisement. Firms and marketers which are investing in online advertisement will find these results
useful as they can get better sales and can use these features of online advertisement in order to maximize the sales of
their products and services.
Keywords: Features of Internet Advertisement; Display Advertisement; Search Advertisement; Classified
Advertisement; E-Commerce Sales; E-Commerce Sale in Europe
1. Introduction
Internet is becoming a new way to shop different prod-
ucts or services online. Although, it is a desire situation
for everyone to touch the products that he/she wants to
buy. However, Internet is playing a wider role in making
the shopping more easily as it is never before. The web
makes shopping much easier, and nowadays shopping is
not more than away from a click. A latest term is intro-
duced that is known as “Online Shopping”. Consumers
can directly shop product or services from the sellers
without any interaction of intermediate parties. There are
over 875 million consumers who have shopped online.
The number of Internet shoppers has increased by 40% in
two years [2] (Eurostats, 2011). These are the trends in
online shopping and these trends are increasing world-
wide. Besides buying products online, the ability to get
the services through a simple click makes it easier and
more comfortable. For instance, booking travel tickets,
getting concert or matches tickets and online banking are
some of the services which consumers love to get con-
veniently through Internet. When a consumer buys from
a business, it is called B2C; and, when business buys
from another business, it is known as B2B.
Just like other direct marketing channels such as tele-
vision and catalogs, Internet is also becoming a signifi-
cant marketing channel. The Internet supports two-way
communications between consumer and merchant. The
web provides interactive shopping channel, which is not
bounded by time and geographical condition. Moreover,
it supports a variety of alternatives to approach extensive
retailing activities over Internet. Like marketing the
products in traditional market, similar in the context of
Internet, products or services are also use to be marketed.
Many modern merchants and organizations have devel-
oped their pages to promote or market their products and
services over worldwide Web.
Impact of Internet Advertisement and Its Features on E-Commerce Retail Sales: Evidence from Europe 565
In European countries, the Internet market is at devel-
oped stage, although in European countries many people
avoid shopping from an E-store. Lack of trust is one of
the most frequently cited reasons for consumers not to
purchase from the Internet [3] (Turban, 2011). The users
of Internet in Europe have been recorded 105,096,093 [4]
(Stats, 2011). The number of Internet users is increasing
rapidly in Europe and around the globe. Beside that the
number of internet users in Europe is increasing, simi-
larly, the number of Internet shoppers is also increasing.
80% of the Internet users in Europe have bought or or-
dered goods or services for private use over the Internet
[2] (Eurostats, 2011). Basically, there are certain factors
which are encouraging Internet shopping, such as secure
payments, accessibility and demonstration of Retailers or
merchants and physical existence of the products [5]
(Todd, 1997).
When talking about Internet advertisement, few things
have been observed on the Internet world. Due to the low
cost, high speed on Internet, and accessibility to different
products, Internet is becoming a most acceptable plat-
form for the shopping purpose. Internet is becoming a
novel platform for attracting consumer’s attention by the
online advertisement [6] (Rowley, 2001). It has been ob-
served that companies are spending huge amount of money
for advertisement on interactive media. According to the
Euro stats, the database of statistics, Euro.21 billion has
been spending on the Internet advertisement from the FY
2010 to FY 2011 [7] (Eurostats, 2011). As companies are
spending huge amount of money, it is significant to
measure whether this huge amount of money generates
desirable outcomes or not. Moreover, there might be
huge potential in online advertisement as the stats indi-
cates that Internet users increase from 16% to 65.7%
from 2000 to 2008 around the globe [8] (Internet world
stats, 2008). If we talk specifically about Europe, then
according to the stats of world bank, Internet users being
recorded are 61.3% of the total population of entire
Europe [9] (World Bank, 2010). The exact figure re-
corded by the Internet world stats of Internet users in
Europe as by 2011 is 1.5 billion (Statistics, 2011). The
stats indicates that companies need to emphasize on
online advertisement in Europe more and more as there is
huge potential in the European online market.
2. Literature Review
Literature review is based on overview of Internet adver-
tisement, and overview of features of online advertise-
ment which put impact on the consumer purchase inten-
2.1. Overview of Internet Advertisement
Advertising is defined as “any paid form of non-personal
communication of ideas and information about products
in the media with the objective of creating brand image
[10] (Armstrong, 2010). Long time ago the marketing on
Television and Print media was the major source of ad-
vertisement, but in today’s world Internet marketing has
become another major source of online advertisement.
Internet is flattering powerful force in many promotion
initiatives and efforts [10] (Armstrong, 2010). To cover
up this platform of advertising companies are planning
for the growth of online retailing, but for this purpose
they are definitely in need of correct estimates of online
purchasing behaviors [11] (Gerald Lohse, 2000). “In the
Internet environment, consumers do not need to conform
to the expectations of others when making a purchase,
and they all have informational influence that enables
them to make good decisions. Internet Advertisement is
becoming a significant tool that is used to market the
products and services by the industrial and non-industrial
organizations [12] (RAVIKUMAR, 2012). Furthermore
studies indicate that electronic business also come up
with the new forms of advertisement such as banners,
pop ups, videos, content and other advertisement links
[13] (Manchanda, 2006).
According to an estimate the total expenditure of
online advertisement is around $66.6 billion in all over
the world [14] (The Wall Street Journal, 2004). Due to
this fact companies which are planning to enhance their
online operations on the Internet platform they are look-
ing for the exact measures and estimates which can tell
them that whether there is consumer response or not.
Those companies which are strategizing for the growth
of retailing on Internet they are certainly in need of reli-
able estimates for the growth of Internet shopping [15]
(Lohse, 2000). Without any doubt significant increase
has been observed in the internet advertisement sector. It
is proven to become another platform which is drawing
the attention of companies towards itself. It is commonly
observed that companies are allocating a significant
amount for the purpose of online advertisement. Internet
advertising stats swathe areas that narrate to publicity
brands over the internet and comprise banner advertising,
advertising performance, search engine advertising/PPC
advertising, and further development and stats associated
to internet advertising. According to [16] (Grabstats,
2008) revenue of internet advertisement has 38% growth
from 2000-2008. Internet advertisement is effectual if it
is talented to produce an instant retort from the customers
[17] (Tse, 2005). More importantly three features are
used in internet advertisements which are Multimedia
feature, Pictures and content features. These features
have been used by the model proposed by [18] (Rutgars,
2.2. Features of Online Advertisemen
Display is a form of expression which includes Anima-
Open Access JSEA
Impact of Internet Advertisement and Its Features on E-Commerce Retail Sales: Evidence from Europe
tion, Videos and moving pictures [19] (Rosenkrans,
2007). The display feature includes many technologies
such as flash, Java ads, pop ads and moving images [20]
(Yoo, 2004). Furthermore consumer has better percep-
tion and positive buying behavior when they see the
moving advertisement, colored ads, Java ads or videos on
any E-commerce website [17] (Tse, 2005). This is why
companies are focusing on the development of digital
advertisements on the interactive media to grab the atten-
tion of more and more customers. Companies that con-
struct thematic associations flanked by the game and the
product’s make would summon an encouraging persuade
on consumer approach toward that particular brand or
make [21] (Wise, 2008).
Another major internet advertisement features are the
search and classified advertisement. Without any doubt
search and classified advertisement become more attrac-
tive and appealing for the customers who are looking for
online shopping purpose [22] (Loiacono, 2008). Further a
study indicate that search and classified advertisement
are the most ideal and put efficient influence on the con-
sumer perception for the particular products are services
on the Internet as compared to the content advertisements
[23] (Kumar, 2008). Search and classified advertisement
are working as an effective tool in drawing the viewer
attention towards itself. However, there are certain draw-
backs of this online advertisement feature. The main
drawback of this feature is this that it takes some time in
order to download the picture and appear on to the
viewer’s screen. A study finding shows that normally a
consumer wait for 15 seconds for any picture to down-
load so that he/she can view it (Adam, 2003). So it ap-
pears that if a picture or image would not be down-
loading before 15 seconds then consumer will switch
towards any other website or E-store for the shopping
2.3. E-Commerce Retail Saleson Internet
It is significantly important to study the total E-com-
merce sales patterns and trends in the specific area. Sev-
eral studies [24] (Häubl, 2000), [25] (Andrews, 2000),
[26] (Bakos, 2000), have conducted empirical research
about consumer purchase or in other words saleson the
internet. These studies were basically trying to figure out
the difference between traditional and online environ-
ment. Literature shows a strong relationship between the
internet advertisement and E-commerce retails sales on
the Internet. Findings show that if the internet advertise-
ment has increased the E-commerce sales are also in-
creased. Finding of a study indicates “Consumers who
felt that Web sites improved their perceptions of brands
saw more advantages in Web advertising and they intend
to purchase from that website” [27] (Ronald and Barbara,
2002) Most of the studies were on the price and brand
choice in an online environment and results indicated
that there is a blend of evidence for the role of informa-
tion in the virtual environment.
Andrews (2000) [25] finds that “the brand loyalty co-
efficient in a multinomial logic model is lower for online
versus offline grocery shopping, but online shoppers se-
lect from a smaller consideration set of brands, thereby
remaining loyal to a smaller number of brands”.
This is the research gap in literature and to fulfill this
gap we have conducted the similar study by using the
secondary data of European countries.
3. Theoretical Framework
The theoretical framework of “impact of Internet Adver-
tisement and its features on E-commerce Retail Sales:
Evidence from Europe”
Source: Adapted from [37] (Wei et al., 2010).
H1: Classified Advertisement has positive relationship
with the E-commerce sales in European countries.
H2: Display Advertisement has positive relationship
with the E-commerce Sales in European countries.
H3: Search Advertisement has positive relationship
with the E-commerce Sales in European countries.
4. Research Methodology
This section of the study will discuss the research meth-
odology use to find out the relationship between inde-
pendent variables and dependent variables. The method-
ology of this study will be quantitative and based on
secondary data collection. Cross sectional data of differ-
ent countries of Europe has been collected. Countries are:
United Kingdom (UK), Germany, France, Netherland
and Italy. Ten years data has been collected from 2001 to
2010. These countries are from the Europe zone and
these countries are among the top five countries among
other countries of Europe in usage of Internet, spending
on Internet Advertisement and purchasing or sales from
the Internet by the consumers. The data for all three in-
dependent variables which are Display Ads, Classified
Ads and Search Ads are collected from the reports of
IAB ADEX [28] (ADEX, 2001), [29] (ADEX, 2002), [30]
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Impact of Internet Advertisement and Its Features on E-Commerce Retail Sales: Evidence from Europe 567
(ADEX, 2003), [31] (ADEX, 2004), [32] (ADEX, 2005),
[33] (ADEX, 2006), [34] (ADEX, 2007), [35] (ADEX,
2008), [36] (ADEX, 2009) and [1] (ADEX, 2010). The
data of dependent variable is collected from a report or a
book. The report is [37] (Jeffrey, 2010) and the book is
[38] (Zenithoptimedia, 2011). An Email was sent to Ze-
nithoptimedia team to provide this book in order to col-
lect the right data. No other agency or publisher, or any
other journal is offering such report; even Gallup is not
recording the Internet Advertisement data so data was
collected by personal efforts. Total 50 observations have
been recorded as five European countries have been
chosen and their ten years of data has been collected.
The data is analyzed by using E-views 5. All the data
was first recorder in MS-Excel then arrange the data in
E-view and apply different tests. Descriptive test has
been applied for the analysis of properties of data. De-
scriptive analysis consists of Mean, Median, Standard
Deviation, Skewness, Kurtosis and number of observa-
tions as well. In addition with descriptive test, correlation
matrix is also generated which tells us the extent of rela-
tionship between the independent variables and the de-
pendent variables. This correlation matrix is good in or-
der to check the variables relationship between inde-
pendent and independent variables and independent to
dependent variables. Furthermore, Ordinary Least Square
(OLS) regression test is also applied to estimates the de-
sirable results. It shows us the dependence of dependent
variables to independent variables. R square and Ad-
justed R square is also estimated which tells us the effect
of multicollinearity between the independent variables.
Also Durbin test results calculated which tells us the
problem of Autocorrelation in the results. This OLS re-
gression is used because it is important to check the de-
pendency of the variables to each other. Moreover, it is
also important to check whether there is effect of multi-
collinearity or not? Also it tells the problem of Autocor-
relation which is also important to check in the data.
General model equation of the study which is statisti-
cally estimated to signify the relationship is as under.
 
ESALE = Total E-commerce Sales
CLASS = Classified Advertisement
SEARCH = Search Advertisement
DESPLAY = Display Advertisement
5. Results & Discussions
This section presents the empirical findings regarding the
relationship that exists among variables selected for the
study. First of all it presents the descriptive or summary
statistics, which shows the properties of the data. This
section also presents the OLS regression results and cor-
relation Matrix results, as well as theoretical discussion
on results of these models. Interpretation of each result
will be done in this section.
Table 1 depicts the descriptive statistics for the inde-
pendent and dependent variables which are considered.
As the sample of the study includes the 05 countries and
the data period covered for ten years ranging from
2001-2010, so the total number of observations become
fifty. The sample of the study reveals that average of
classified Advertisement is 250.44; the mean of Display
Advertisement is 344.36. Similarly the average of search
advertisement is 555.12 and the average of dependent
variable which is E-commerce Sales is 20.66. Further the
standard deviation of classified Advertisement is 271.15;
the standard deviation of Display Advertisement is
317.29. Similarly the standard deviation of search adver-
tisement is 665.54 and the standard deviation of depend-
ent variable which is E-commerce Sales is 19.02. In ad-
dition to Mean and Standard Deviation other descriptive
results are also given which are median, skenewss, kur-
tosis and probability of each variable.
Table 2 depicts the correlation Matrix in which corre-
lation results of each variable is given. As there are three
independent variables i.e. Classified Advertisement, Dis-
play Advertisement, Search Advertisement and one de-
pendent variable i.e. E-commerce Sales, so correlation
results with respect to each variable is given. Correlation
tells us the extent of relationship between two variables.
Correlation result between the variable itself such as
Display Ad of Display Ad is strongly significant or 1 and
vice versa. Correlation results between Classified and
Display Advertisement is 0.83 which shows strong rela-
Table 1. Descriptive statistics.
Mean 250.4400 344.3600 20.66200 555.1200
Median 153.0000 232.0000 15.85000 302.0000
Maximum 874.0000 1272.000 83.50000 2731.000
Minimum 5.000000 7.000000 0.800000 16.00000
Std. Dev. 271.1560 317.2999 19.02158 665.5494
Skewness 0.990382 1.065653 1.513656 1.615724
Kurtosis 2.415678 3.432945 4.853007 4.860979
Jarque-Bera8.885124 9.853965 26.24635 28.96978
Probability0.011766 0.007248 0.000002 0.000001
Sum 12522.00 17218.00 1033.100 27756.00
Sum Sq. Dev.3602754. 4933282. 17729.20 21704847
Observations50 50 50 50
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Impact of Internet Advertisement and Its Features on E-Commerce Retail Sales: Evidence from Europe
Open Access JSEA
Table 2. Correlation matrix.
CLASSIFIED 1 0.830893671771689 0.869408346196187 0.818317189838863
DISPLY 0.830893671771689 1 0.831313355900985 0.792074170206665
ECOMSALE 0.869408346196187 0.831313355900985 1 0.959616746708359
SEARCH 0.818317189838863 0.792074170206665 0.959616746708359 1
tionship. Similarly, correlation results between classified
and E-commerce sales are 0.86 which also shows strong
relationship. Correlation results between Classified and
Search Advertisement is 0.81 which is strong relation-
ship. Correlation results between Display and E-com-
merce sales are 0.83 which is a strong relationship. Cor-
relation results between Display and Search is 0.79
which is also strong relationship. Correlation results be-
tween E-commerce Sales and Search is 0.95 which also
shows strong relationship with each other. Correlation
results between Search and Classified Advertisement is
0.81 which is a strong relationship.
Table 3 depicts the random effect model estimated
through OLS (Ordinary Least Square) regression. The
Search Advertisement value of probability is 0.000
which shows it has very high or strong significant impact
on the dependent variable which is E-commerce sales.
Similarly the P-value of Classified Advertisement is
0.005 which also shows it has a significant impact on the
E-commerce Sales. Whereas, results indicate that the P-
value of Display Advertisement is 0.1791, which is
greater the confidence of interval so it has weak impact
on E-commerce Sales. Although it has some impact of
E-commerce sales but that impact is low. T-stats of clas-
sified advertisement is 2.88 which is more than 2 so it
shows significant positive impact of Classified Ad on
dependent variable which is E-commerce Sales. Same in
the case of Search Advertisement, the T-stats is 11.16
which is also more than 2 and it shows a significant posi-
tive impact on E-commerce sales. But when we see the
results of Display advertisement the T-stats is 1.36 which
is less than 2 so it shows negative impact on the depend-
ent variable which is E-commerce Sales. The value of R
square is 0.944 which is more than 0.90 which shows
that there is the effect of multicollinearity between the
independent variables. By seeing the Adjusted R square
which is basically for more than two independent vari-
ables shows that there is multicollinearity effect between
classified Ads, Search Ads and Display Ads. The Durbin
Watson result should be more than 1.96 only than there
will be no problem of autocorrelation, so when we see
the results of Durbin Watson test in Table 3, its value is
1.057 which is less than 1.96 and it means there is no
problem of autocorrelation. Overall the random effect
model best explain the association among variable.
Table 3. Ordinary lease square regression statistics.
Dependent Variable: ECOMSALE
Method: Panel Least Squares
Date: 07/08/12 Time: 05:41
Sample: 2001 2010
Cross-sections included: 5
Total panel (balanced) observations: 50
Variable CoefficientStd. Error t-StatisticProb.
C 3.7656450.971634 3.8755800.0003
CLASSIFIED 0.0143390.004964 2.888314*0.0059
DISPLY 0.0054500.003995 1.3643910.1791
SEARCH 0.0205880.001844 11.16664*0.0000
R-squared 0.944537Mean dependent var20.66200
Adjusted R-squared0.940920S.D. dependent var 19.02158
S.E. of regression4.623442Akaike info criterion5.976774
Sum squared resid983.3060Schwarz criterion 6.129736
Log likelihood 145.4194F-statistic 261.1296
Durbin-Watson stat1.057464Prob(F-statistic) 0.000000
Note: Shows significance at 1% level of significance.
6. Discussion on Hypothesis Testing
This section presents the discussion on each hypothesis
which we propose on the basis of substantive literature.
Empirical reflection on each hypothesis will be analyzed
to decide whether hypothesis projected have a significant
or insignificant relationship. As the results of T-stats and
P-value of classified Advertisement is good and shows
significant relationship with the E-commerce sales so on
the basis of that we accept the H1. When we talk about
H2, the P-value and T-statistics is not substantial and not
showing significant relationship with the dependent
variable which is E-commerce sales but in theory it has
positive significant relationship with the E-commerce
sales. Findings of a study says “The results of an experi-
ment indicate that if a display ad is placed on a website
then the ad should be highly congruent with the site than
it will bring effective results for the advertiser” [39] (Eric,
Impact of Internet Advertisement and Its Features on E-Commerce Retail Sales: Evidence from Europe 569
2004). Moreover another finding which is particularly
about effect of banner advertisement on the consumer
purchase intension, they also proved that display or im-
age advertisement has strong positive impact on con-
sumer buying or purchases on Internet. Purchases ulti-
mately mean the sales on Internet [40] (Ronald, 2002).
So in the light of these results in literature we might ac-
cept the H2 and accept the statement that Display Ads
has strong significant positive relationship with the total
E-commerce sales. In addition to H1 results, when we
see the t-stats and p-value of H3 it also shows positive
significant relationship with the E-commerce sales by
these values we accept the H3.
7. Conclusion and Recommendations
The aim of this research stream was to empirically de-
termine the impact of Internet advertisement and its fea-
tures on E-commerce sales. The empirical seating of the
study is provided by the Internet retail sales of Europe.
The determinants or the dimensions of independent vari-
able are further divided into three categories: The Dis-
play Advertisement, The Classified Advertisement and
The Search Advertisement. The empirical finding of the
study suggests that Internet advertisement is significantly
associated with the E-commerce sales in the European
countries. Empirical findings are: 1) the independent
variables which are classified advertisement and the
search advertisement have positive relationship with the
E-commerce sales; and 2) independent variable which is
display advertisement has negative relationship with the
E-commerce sales. This study does not find any relation-
ship between display advertisement and the E-commerce
purchases/sales. However, with the help of literature [39]
(Eric, 2004) and [40] (Ronald, 2002), these studies show
that banner advertisement or display advertisement has
positive relationship with the E-commerce purchases/
sales in the European context. Overall, the results of the
study are best aligned with the previous studies ex-
pounded in the literature [39] (Eric, 2004), [11] (Gerald
Lohse, 2000) and [41] (Wei et al., 2010). This research
stream will hopefully contribute to the recent literature
on the determinations of Internet advertisement and their
effect on total E-commerce sales in European countries.
In summary, this research study is related to the sales
done by the consumers or individuals in Europe.
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