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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
NAŠE GOSPODARSTVO
OUR ECONOMY
pp. 56–73
ORIGINAL SCIENTIFIC PAPER
Citation: Moerth-Teo, J. Y., Bobek, V., 
& Horvat, T. (2021). The Effects of 
Consumers’ Buying Behavior on the 
E-commerce in Highly Developed 
Emerging Market and Developed 
Market: The Case of Singapore and 
Austria. Naše gospodarstvo/Our Economy, 
67(4), 56-73.  
DOI: 10.2478/ngoe-2021-0021.
DOI: 10.2478/ngoe-2021-0021
UDK: 658.89:004(592.3)(436)
JEL: L81, D91
RECEIVED: AUGUST 2020
REVISED: OCTOBER 2021
ACCEPTED: NOVEMBER 2021
Vol. 67 2021 No. 4
The Effects of Consumers’ Buying 
Behavior on the E-commerce in 
Highly Developed Emerging Market 
and Developed Market: The Case of 
Singapore and Austria
Jia Yun Moerth-T eo
University of Applied Sciences FH Joanneum, Austria
jia.moerth-teo@edu.fh-joanneum.at
Vito Bobek
University of Maribor, Faculty of Economics and Business, Slovenia
vito.bobek@um.si
Tatjana Horvat
University of Primorska, Faculty of Management, Slovenia
tatjana.horvat@fm-kp.si
Abstract
The e-commerce is becoming increasingly essential and principally relevant in 
the modern world, especially in the current pandemic. Due to the increased use 
of the Internet, the growth of e-commerce has escalated. This research focuses on 
the e-commerce environments of Singaporean and Austrian markets. It contains 
an outline touching on the theoretical parts and the conduct of an empirical 
study where the survey results from 206 participants were studied, analysed, 
and compared. The statistical methods chosen for this research were the t-test 
analysis and the correlation analysis. The empirical study served as a quantitative 
discussion on both countries' e-commerce markets. The analysis of the completed 
questionnaires provided a better and clear understanding of the buying 
behaviours and their potential impact on the e-commerce markets in Singapore 
and Austria. Considering the results from the comparisons, the research has also 
highlighted some interesting findings and differences in the buying behaviours 
of Singaporean and Austrian shoppers.
Keywords: e-commerce, pricing, buying behaviours, consumers, Singapore, 
Austria
Introduction
Fundamentally, e-commerce is a form of business with transactions of buying and 
selling goods or services over the worldwide net. From mobile shopping to online 
payment encryption and beyond, surrounding e-commerce is a wide variety of 
data, systems, and tools for online users, buyers, and sellers alike. Most businesses 
with an e-commerce presence use an e-commerce store and/or an e-commerce 

57
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
platform to conduct their online marketing and sales activi-
ties and oversee their logistics and fulfilment (Moore, n.d.). 
Since then, the growth of many e-commerce companies has 
ascended across the board.
The introduction and role of e-commerce platforms have 
created an enormous impact and have taken the entire world 
by storm. In recent years, there has been a trend observed 
in the rise of retail e-commerce globally. The worldwide 
e-commerce trend has been seen as an ever-increasing climb 
upwards and is forecasted to grow continuously upwards 
from 2021 to 2023. E-commerce is proliferating, that it is 
already slowly eating away parts of the shares from tra-
ditional retail (Wonderflow, 2019). Based on the OECD, 
they believe that the growth of e-commerce can increase 
the competition within retail markets, enhance consumer 
choices significantly, and prompt and facilitate innovation in 
the product distribution section.
Problem statement
This research focuses on the Singaporean and Austrian 
e-commerce markets, consumers' buying behaviours, and 
their potential impact on the e-commerce environment. 
Therefore, it would be insightful to look into the statistics of 
both countries' e-commerce scenes. 
Due to its enduring popularity and the increasing importance 
and relevance of e-commerce globally and especially in Sin-
gapore and Austria, it was compelling to delve deeper and 
take a closer look into this e-commerce topic. The research 
focused on the consumers' buying behaviours in a highly 
developed emerging market and a developed market, Sin-
gapore and Austria, respectively, and how the buying be-
haviours might potentially affect the e-commerce markets. 
A comparison between the buying behaviours was made to 
see if there are possibly any significant differences between 
a Singaporean consumer and an Austrian consumer. As time 
goes by, there are mutations and evolutions expected from 
the consumers' buying behaviours, no matter where one 
comes from initially.
Many factors have to be considered before getting into the 
final stage of purchasing something through an e-commerce 
platform. Therein lies a massive number of dynamic factors 
that may affect each consumer's buying behaviours. Based 
on Kotler and Armstrong, there are four categorical groups 
to classify the factors affecting the behaviours of consum-
ers, and they are psychological, personal, social, and cultural 
(The Open University, n.d.).
The research was conducted from many of the existing 
researches and studies. The majority of the past research 
revolved around the effects of e-commerce on consumers' 
buying behaviours. This research will hopefully contribute 
to the bigger picture with studies of the consumers' buying 
behaviours and how it might affect the e-commerce envi-
ronment, focusing on the Singaporean and Austrian e-com-
merce markets.
As online consumers ourselves, there are many factors that 
we will put into consideration before deciding to purchase 
something through an online platform. Therein lies a consid-
erable number of factors that may affect every consumer’s 
buying behaviours. Based on Kotler and Armstrong, four 
categorical groups classify the factors affecting consumers' 
behaviors: psychological, personal, social, and cultural (The 
Open University, n.d).
The research was conducted from many studies. The majority 
of them revolved around the impact and/or effects of e-com-
merce on consumers' buying behaviour. This research and 
its area of work will contribute to the big picture with studies 
of the consumers' buying behaviours and how they might 
impact the e-commerce market, focusing on the Singapore-
an e-commerce markets. 
Research question and hypotheses
The main research question formulated out of this study will 
be "How will the consumers' buying behaviours affect the 
e-commerce environment?". Based on the main research 
question, a sub-research question was then constructed: 
"Which type of factors may cause an impact on the consum-
ers' buying behaviours?” Hypothesis was created with the 
research questions being kept in mind: Consumers' buying 
behaviours may affect the e-commerce environment.
Literature Overview
As shown in Figure 1, the research focus will be the in-
tersection between the consumers' buying behaviours and 
e-commerce, which inter-joins both circles together. Factors 
regarding what may affect the consumers' buying behaviours 
and, subsequently, their consequences on the consumer side 
will be investigated in detail, and the factors that may affect 
the e-commerce business environment will also be studied. 
Based on the figure mentioned above, an overview of es-
sential literature regarding the identified focus, which 
explains the previous work and relevant theories related 
to this context, will be found in the following paragraphs. 
The journal papers and articles chosen for this review can 

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
be classified into two categories; factors driving consumers' 
buying behaviours and the rise of e-commerce. 
Figure 1. The research focus
Source: own research.
Factors driving consumers’ buying behaviours
Millions of consumers create and reinforce new online 
buying behaviours and habits (Columbus, 2020). V oinea and 
Filip (2011) have indicated that in recent years, there has 
been an emergence and rapid growth of new economic im-
portance, of the new types of consumer – also known as the 
new consumer - whose attitudes, aspirations, and purchasing 
patterns are different as compared to those existing behav-
iours in the past. Among the various reasons behind consum-
ers' buying behaviours, a few significant motivators will be 
discussed below. Said motivators are concerning competitive 
prices, customer service, customer reviews, and trust. 
Competitive prices
Previous research depicts that prices come into consum-
ers' minds before deciding factors (Guo et al., 2019). For 
many consumers, competitive pricing stays as the number 
one reason that attracts their attention and, as a result, pos-
itively affects their buying behaviours. The majority of the 
consumers are usually searching for product offers at very 
affordable or even discounted prices (Kerick, 2019). As per 
Urne (2020), competitive pricing remains one of the critical 
factors for success in e-commerce. 
Tanir (2018) states that the most crucial store features 
driving up to 80% of consumers' purchasing decisions is 
competitive pricing. He also mentioned that around 90% 
of the e-commerce shoppers are considered the 'masters' 
of deal hunting. Thanks to the advanced technology and 
comparison-shopping engines, consumers can now get 
alerts for multiple items from multiple e-commerce stores 
that further facilitate their comparison ability between the 
products offered. This comparison will allow the shoppers to 
get real-time information concerning the lowest best prices 
for their desired product or service.
Customer service 
Customer service remains one of the critical touchpoints 
that affect the buying behaviour of consumers. According to 
Wertz (2017), attracting new customers costs approximately 
seven times more than retaining the existing customer base. 
So, the provision of excellent customer service can increase 
sales and profits and aid the companies, in the long run, to 
stand out in the virtual competitive marketplace.
Customer reviews
Based on eMarketer (n.d.), a complete 61% of respondents 
said they had checked online reviews, blogs, and other 
online customer feedback before moving to the next step, 
purchasing the new product or service. More than 80% said 
that such evaluations had held at least some influence on 
their purchases.
This is further supported by research (Kaushik et al., 2018), 
which states that the reviews projected on the e-commerce 
platforms may help certain users during their decision-mak-
ing process regarding the product itself. A large number of 
helpful reviews also conveys more information about the 
product to a customer. Source credibility, review popularity, 
and usefulness play a vital role in the sales of the product. 
Their study also confirms the positive effect of the balance of 
reviews on product sales. Customer reviews can help elim-
inate any doubts that potential customers may have about 
their product or may even help when it comes to product 
selection (Charlton, 2012). 
Trust and loyalty
Trust is expected to be even more critical in e-commerce than 
in traditional commerce because of the paucity of rules and 
customs in the regulation of e-commerce and that because 
online services and products typically are not immediately 
verifiable by the consumers (Gefen and Straub, 2004). The 
research conducted by Teo and Liu (2005) concludes that 
consumers' trust in e-commerce vendors and their risk per-
ception can also be regarded as behavioural beliefs that may 
affect consumers' behavioural attitude – to purchase or not 
to purchase.
Frequently, the lack of trust is a fundamental reason many 
users will not purchase goods or services from e-commerce 
websites. Trust is considered the critical factor for maintain-
ing sustained relationships between the transacting consumer 
and the e-commerce seller (UK Essays, 2018). Coming 
hand-in-hand with trust comes the loyalty of the consumers. 
Without the glue of loyalty, even the best-designed e-busi-
ness model will collapse. Besides purchasing more from the 
business, loyal customers would frequently refer new friends 

59
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
and family members to the e-business, providing yet another 
rich source of profits. Referrals are considered lucrative in 
traditional commerce, but the Internet further amplifies this 
effect since the word 'mouse and keyboard' spreads even 
faster with just some clicks than word of mouth (Reichheld 
and Schefter, 2000).
Rise of e-commerce
Technology
The new generation can no longer remember a world 
without computers, emails, and cell phones (Taken Smith, 
2009).  Raja and Nagasubramani (2018) have reiterated the 
importance of technology, stating that today’s era of the 21st 
century is often regarded by many as an era of technology. 
Technology today plays a significant role in our life. It is 
frequently associated with growth, as it is seen as a basis of 
the growth of an economy. Information technology and the 
Internet have dramatically affected business operations and 
continue to affect business conduct dramatically. Markets, 
industries, and businesses are transformed by the ongoing 
technological wave (Dinu and Dinu, 2014). Business as a 
whole is changing, thanks to technology and its advance-
ments (Pierson, 2018).
A need for tech savviness
As more technological advances enter the picture and an 
entirely digital world is foreseen to emerge shortly, many 
people are “pushed” or even “forced” to educate themselves 
on the new technology to not be left behind and remain up to 
date with society. The more technologically literate one is, 
the better-prepared one will be able to adapt to any form of 
change (Pierson, 2018). Nowadays, upskilling in technology 
is becoming a necessity rather than a choice (Rao, 2020).
With our ever-changing environment and the shift from tra-
ditional to virtual settings, people need to be equipped with 
technical skills. Technology will empower the human race 
and will open up opportunities that were otherwise impos-
sible to reach before. Gupta (2006) illustrates the need to be 
computer literate. Employers nowadays prefer their workers 
who are computer literate to those who are not. Computer 
literacy contributes further to employee and productivity effi-
ciency, therefore making them more valuable to the company.
Explosive growth of e-commerce
In our current digital age, e-commerce plays a vital role in 
our lives. With the unfortunate ongoing global COVID-19 
pandemic that restricts people from heading out, many 
families will eventually replace their store and mall visits 
permanently with online grocery, apparel, and entertainment 
shopping (Columbus, 2020). This further contributes to the 
extensive growth of the e-commerce environment. 
Based on Kerick, the expected growth of e-commerce is to 
come from Asia and the US to Europe and throughout Africa 
to the Middle East. The e-commerce sector is expected to 
break the net, accounting for double-digit growth in all loca-
tions worldwide (Kerick, 2019). Taken Smith (2009) states 
that the annual growth rate of e-commerce is estimated to be 
up to 28% at the global level, while individual countries may 
even have much higher growth rates.
Methodology
A primary research process that is suitable for this thesis 
is presented by Karlsson (Karlsson, 2016). Based on this 
process, the actual methodology to achieve an efficient 
study has been derived and is illustrated in Figure 2. The 
first step starts with literature research. This is followed by 
the data collection stage, including preparing the questions 
suitable for the questionnaire and identifying potential par-
ticipants. The third step deals with the data analysis based 
on a quantitative review to identify possible correlations and 
derivations of factors. The evaluation and consolidation of 
the gathered results will represent the final step of this report.
Figure 2. The research focus
Source: own research.
Research gap
After conducting the first round of initial literature research, 
the studies have revealed that the majority of the literature 
reviews and focus were concentrated on the topic of e-com-
merce and was covered mainly on the contents such as 
e-commerce in general, consumer’s buying behaviours, risk 
assessments in e-commerce, factors determining consum-
ers’s e-satisfaction and consumer trust in e-commerce (Loo 
and Sze 2002; Lee et al. 2012; Singh and Sinha 2013; Nisa 
and Prabhakar 2017; Wagner et al. 2018; Dai et al. 2018).
A void in the research on comparing buying behaviors in 
e-commerce between a highly developed and a developed 

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
market has been identified. Furthermore, a lack of research 
was observed on the linkage between the consumers' buying 
behaviors and its potential impact on the e-commerce envi-
ronment. The possibility of a linkage has received limited 
research attention. Certain factors, for example, the avail-
ability of a product, have also received relatively limited 
attention in the research fields towards the e-commerce 
settings. Hence, this research study further enriches and con-
tributes to the already available data and information with a 
study on the factors that may affect the consumers' buying 
behaviors in a highly developed market, Singapore and a 
developed market, Austria, and if these buying behaviors 
would potentially affect the e-commerce environment.
Research design
For the empirical part of this research, a questionnaire was 
structured and designed on QuestionPro, distributed to 
willing participants. A convenience sample of 80 partici-
pants for each country was selected and expected, totaling 
160 participants. Eighty participants are expected from 
Singapore, and the other 80 participants are expected from 
Austria. The statement with a total of 160 responses was 
assumed as the results would then be sufficient to arrive and 
contribute to a significant statistical statement. However, 
this research project aims to gather as many participants 
as possible within the research timeframe of two weeks. 
This was planned as there are drop-outs or invalid datasets 
to be anticipated during the questionnaire collection phase. 
In questionnaires, it is always better to have a more signif-
icant number of participants than the intended target, as this 
may also reduce the accidental risk of having an extreme or 
biased group (Hydrocephalus Association, n.d.).
When the questionnaire was completed, the participants 
were sent an online link through various communication 
platforms – mainly through personal contacts and social 
media to reach a bigger audience. The collation of results 
would come before the data analysis, as shown in Figure 
3. The data will be analyzed in due course with the SPSS 
statistical software, version 26. 
Pre-testing the questionnaire
Based on the works of Converse and Presser (1986), pre-test-
ing of a survey is a crucial way to pinpoint problem areas, 
reduce respondent burden, determine whether or not the re-
spondents are interpreting the questions correctly, and ensure 
that the order of questions does not influence the way the 
respondent might answer. They have also stated that pre-test-
ing, in other words, is a critical examination of the survey in-
strument that will help determine if the survey will function 
adequately as a valid and reliable social science research tool.
Once the setup of the draft questionnaire was completed, a 
round of pre-testing was conducted.  The draft questionnaire 
was sent out to two participants from Singapore and two 
participants from Austria. Pre-testing displayed the possible 
pitfalls of the questionnaire and, at the same time, tested 
if the questions made sense to the participants and if they 
would be able to understand what this research wishes to 
convey to them fully.
Figure 3. The research design
Source: own research.
Questionnaire
Two sets of the same questionnaire were designed and con-
structed on Question Pro. The first questionnaire set was 
designed for the Singaporean participants and the second 
one for the Austrian participants. There was a complete set 
of 15 questions for the entire questionnaire. Some of the 
questions in the questionnaire have employed the usage 
of a 5-point Likert scale. The Likert (1932) scale remains 
one of the most commonly used instruments for measur-
ing the participants' opinions, preferences, and/or attitudes 
(Leung, 2011, p. 412). Leung (2011, p. 412) has indicated 
that a typical Likert scale question consists of several items 
with around 4 to 7 points of categories each. Furthermore, 
Sachdev and Verma (2004, p. 104) have stated that ques-
tion(s) with a 5-point Likert scale was most recommended 
by researchers, as it would reduce the frustration level of the 
respondents and increase the response rate its quality. In the 
following paragraphs, the questions from the questionnaire 
are examined and discussed. 
The beginning of the questionnaire started with the generic 
questions of gender and age.  The age group depicts a variety 
of different options ranging from 23 and under to 56 and 
above. The age groups were specifically structured this way 
with references made to the generation chart as seen below 
in figure 14, which would enable the ability to construct a 
comparison and observe if there are any differences between 

61
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
the participants' buying behaviours based on their age group-
ings – take, for example, the buying behaviours between the 
Generation Xs (1965 – 1980) as compared to the Generation 
Zs (1997 to 2012). 
Once the general questions are out of the way, the construc-
tion and structure of the remaining questions were created 
to be the perfect match and the right fit for this fundamental 
research's objectives and aims. First of all, the question asked 
is how often the participants will purchase from brick-and-
mortar stores: How often do you purchase from a retail store?
Once the participants have completed this question, the fol-
lowing question will be similar. However, the participants 
were questioned on how often they purchased from an 
e-commerce store for this time around. The reasoning behind 
this question was to check if e-commerce has increased the 
frequency of the participants' making purchases from the 
online store. After that, the participants will rate and choose 
from the Likert scale, ranging from strongly disagree to 
strongly agree to the previous statement that e-commerce 
has indeed increased the frequency of the participant making 
purchases: How often do you purchase from an e-commerce 
store? Has e-commerce increased the frequency of you 
making purchases?
Upon completion, the participants were prompted to the next 
question, which continued the first two frequency questions. 
This time around, the question was adjusted to fit the subject 
of COVID-19. As the pandemic made its entry known in 
2019, it has increased the importance and relevance of 
e-commerce to the entire world. As a result, the participant 
was also asked with a Likert scale agree/disagree question, 
whether COVID has increased the frequency of them making 
purchases from e-commerce. Following this question, the 
participants will be prompted further and questioned on how 
often they have made purchases due to COVID-19 from an 
e-commerce store: Has COVID increased the frequency of 
you making purchases from e-commerce? How frequent have 
you purchased due to COVID-19 from an e-commerce store?
The participants were presented with three options: purchas-
ing from retail stores, e-commerce stores, or both. For this 
questionnaire, the participants were not redirected or linked 
to another question to prevent the loss of useable datasets. 
No matter which option they choose, all participants will 
be prompted to the same question next:  Do you prefer to 
purchase from: retail stores or e-commerce stores or both?
The next question was designed to understand the reason(s) 
behind why participants prefer to purchase from retail 
stores. For this question, participants were able to choose the 
multiple answers where they deemed fit. Do they have the 
option to input other reasons under the 'Others' option if the 
answers provided do not fit into their consideration: Which 
of the factors below positively affect your buying behaviours 
from a retail store?
Next, a similar question was set for the participants. 
However, this question was designed to find out and under-
stand the factors and motivations behind the participants' 
buying behaviors from an e-commerce store. Likewise, par-
ticipants could choose one or more factors, should the listed 
factors positively affect and support their buying behaviours 
from any e-commerce stores. When participants cannot 
locate a factor that supports their buying behaviours, they 
have the 'Others' option to pen down their factor(s): Which 
of the factors below positively affect your buying behaviours 
from an e-commerce store?
The following question was designed to understand which 
factors have increased the frequency of the participants 
making purchases from the e-commerce store: Which of the 
factors below has increased your purchases from an e-com-
merce store?
The participants were asked for the reasons and/or moti-
vation behind why they have stopped purchasing from an 
e-commerce store. For this question, participants were also 
able to choose multiple answers for the reasons behind 
why they have stopped purchasing from an e-commerce 
store. An additional option of 'Have not stopped purchas-
ing online' was provided for the participants who have not 
stopped purchasing from e-commerce. In a similar fashion 
as the previous questions, participants were able to input 
other factors. Should they not be able to find a factor that 
has stopped them from purchasing online: Have you stopped 
purchasing from an e-commerce store because of …?
The final two questions were added to the questionnaire and 
updated to the 5-point Likert scale measurement, which will 
enable a deeper analysis of the gathered datasets obtained 
from the participants. For the second last question, partici-
pants were asked to rate the importance they placed on the 
six factors listed below, from a scale of 1 being not impor-
tant at all to a 5, which is Essential. Participants were able to 
rate each factor with the range provided, from Not important 
to Essential. On a scale from 1 to 5, please rate the impor-
tance of the factors below before you would purchase from 
an e-commerce store: availability of product, competitive 
pricing, convenience, customer service, customer reviews, 
loyalty/trust. 
The last question was aimed to tackle and understand the 
impact of the five factors on how each of the said factors will 
stop the participants from purchasing from an e-commerce 
store. Participants were able to choose from a scale of 1, 
being no impact at all, to a 5, a powerful impact. Participants 

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
were able to rate each factor with the range provided, from 
No impact to Powerful impact. On a scale from 1 to 5, 
please rate the impact of the factors below why you would 
stop purchasing from an e-commerce store: bad experience 
from previous buys, mistrust, negative customer reviews, not 
having the ability to choose and touch the product.
Results
A total response rate of 242 was collected from both groups 
of the target audiences. As predicted from the beginning, 
there would be a drop-out of the participants expected. 
From the Singaporean participants, 20 participants have 
dropped out before completing the entire questionnaire, 
and the drop-out rate sums up to 19.4%. For the Austrian 
participants, 16 of the participants have dropped out before 
completing the entire questionnaire, and the drop-out rate 
sums up to 15.5%. Once the drop-out datasets had been 
removed, there were 206 useable datasets. An equal number 
of participants have been obtained from both groups, 103 
Singaporeans and 103 Austrians, ranging between 23 and 
over 56 years of age. 
Out of the 103 Singaporean participants, 75 of them were 
females, and 38 were males. The majority of the participants, 
83 of them, were between 24 to 39 years old, followed by 
24 under the age group of 23 and 6 in 40 to 55. The average 
time that each participant took to complete the question-
naire was approximately around 3 to 4 minutes. There were 
also 103 participants obtained, of which 35 of them were 
females, and 82 were males. The majority of the partici-
pants, 98 of them falls under the age group between 24 to 
39 years old, followed by 8 participants under the age group 
of 23 and under, followed by 10 participants who belong to 
the age group of 40 to 55 years and lastly 1 participant in the 
age group of 56 and above. The average time taken by the 
Austrian participants to complete the questionnaire took a 
little longer than the Singaporean participants, and the par-
ticipants needed approximately 5 minutes to complete the 
questionnaire. 
Exciting findings
Frequency of purchases for Singaporeans and Austrians
Based on the questionnaires’ findings as observed in Table 
1, 37 of the participants from Singapore purchased at least 
once a month from a retail store. This option contributed to 
the majority of choices chosen by the participants, followed 
by 29 participants who purchased at least twice a month, 22 
participants who purchased more than five times a month, 
and 15 of them who purchased only once in a year or less. 
According to the responses from the Austrians, as seen in 
table 1, 36 of the participants purchased at least once a month 
from a retail store, and another 36 of them purchased at least 
twice a month. These two options contributed to the majority 
of the responses chosen by the participants, followed by 22 
of them who purchased more than five times a month and 9 
of them who purchased only once in a year or less.
As seen in Table 2, most of the participants in Singapore, 33, 
answered with purchasing once a month. Followed by 28 of 
the participants who purchased at least twice a month, then 
25 who purchased more than five times a month, and lastly, 
17 purchased once in a year or less from the e-commerce 
stores. In Austria 51 participants have chosen that they 
purchased once in a month from e-commerce stores. This 
group constitutes the majority. They were followed by 31 
who purchase at least twice a month, 13 who purchase once 
in a year or less, and lastly, eight who purchase more than 
five times in a month.
Table 1. Frequency of purchases from retail stores
Frequency of Purchases (Retail) Country 23 and under 24 to 39 40 to 55 TOTAL
Once in a year or less
Singapore 4 10 1 15
Austria - 7 2 9
Once in a month
Singapore 5 31 1 37
Austria 4 30 2 36
At least two times a month
Singapore 5 22 2 29
Austria 2 30 4 36
More than five times a month
Singapore 4 16 2 22
Austria - 20 2 22
Source: own research.

63
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
Taking the worldwide pandemic and the stringent restric-
tions into account, the participants were also questioned if 
the COVID-19 has increased the frequency of purchasing 
from an e-commerce store. Table 4 depicts the participants' 
responses. It can be observed that the responses obtained 
were similar to the previous statement. In Singapore 75% of 
the participants have agreed that COVID-19 has increased 
the frequency of them making purchases from an e-com-
merce store, with 47 strongly agreeing and 31 of the partic-
ipants who have agreed to this statement. Of the remaining 
participants, 13 felt neutral, 10 of them disagreed, and 2 of 
the participants strongly disagreed. In Austria 64% of the 
participants have agreed to this statement, with 34 strongly 
agreeing and 32 agreeing. The remaining participants indi-
cated that they were neutral or disagreed with this statement, 
with 17 feeling neutral, 15 of them disagreeing, and 5 of the 
participants strongly disagreeing.
Next, the participants were questioned if e-commerce has 
increased the frequency of them making purchases. Table 3 
displays the overview of the participants' responses in Singa-
pore and Austria. In Singapore 74% of the participants have 
either chosen the strongly agree or agree, with 43 of them 
choosing strongly agree and 34 of the participants choosing 
to agree. The remaining participants have either taken the 
neutral stand, disagreed, or strongly disagreed with this 
statement. Sixteen of the participants felt neutral to this state-
ment, whereas eight disagreed, and lastly, 2 of them strongly 
disagreed with the statement. As in Austria, 52% of partic-
ipants agreed with the statement of e-commerce increasing 
the frequency of them making purchases. Out of this, 47 of 
the participants have indicated that they agreed to this state-
ment, and seven have chosen the strongly agree option. The 
remaining participants have chosen that they felt neutral to 
the question, with 28 of them, followed by ten who disagreed 
and 11 who strongly disagreed with this statement.
Table 2. Frequency of purchases from e-commerce stores
Frequency of Purchases (E-commerce) Country 23 and under 24 to 39 40 to 55 TOTAL
Once in a year or less
Singapore 5 12 - 17
Austria 2 8 3 13
Once in a month
Singapore 9 21 3 33
Austria 3 43 5 51
At least two times a month
Singapore 3 22 3 28
Austria 1 28 2 31
More than five times a month
Singapore 1 24 - 25
Austria - 8 - 8
Source: own research.
Table 3. Frequency of purchases increased from online stores due to e-commerce
Question: E-commerce has increased the frequency of you making purchases from e-commerce.
 Country Strongly Disagree Disagree Neutral Agree Strongly Agree
Singapore 2 8 16 34 43 How much do you 
agree/disagree to this 
statement?
Austria 11 10 28 47 7
Source: Own research.
Table 4. Frequency of purchases increased from online stores due to COVID-19
Question: E-commerce has increased the frequency of you making purchases from e-commerce.
 Country Strongly Disagree Disagree Neutral Agree Strongly Agree
Singapore 2 10 13 31 47 How much do you 
agree/disagree to this 
statement?
Austria 5 15 17 32 34
Source: own research.

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
This brings us to the next question, where the participants 
were questioned on how frequently have they purchased due 
to the pandemic from an e-commerce store. As observed 
in Table 5, most of the participants in Singapore, 41, have 
purchased at least two times a month. Twenty-five have in-
dicated that they purchased more than five times a month, 
followed by 23 purchasing once a month and the last 14 
participants purchasing once in a year or less. While most 
of the Austrian participants, 40 of them, have answered that 
they purchased once in a month, whereas 29 have purchased 
at least two times a month. Twenty-one of the participants 
has answered that they purchased once in a year or less, 
followed by 13 of them who have purchased more than five 
times a month from an e-commerce store.
Preferences of Singaporean and Austrian shoppers
Table 6 depicts an overview of the Singaporean partic-
ipants buying preferences. As observed in the table, most 
of the participants, 79, have chosen to purchase from both 
retail and e-commerce stores. Out of these 79 participants, 
58 belong in the age group of 24 to 39 years, 15 belong to 
the age group 23 and under, and six from 40 to 55 years of 
age. For the participants who have not chosen both options, 
17 of them have chosen that they preferred to purchase 
from e-commerce stores. Out of these 17 participants, 15 
belonged to the age group 24 to 39, and 2 belonged to 23 and 
under. The remaining 7 participants chose their preference 
as purchasing from retail stores. Six of them belonged to the 
age group 24 to 39, and 1 of them belonged to 23 and under.
The primary purchasing preference of the Austrians also lies 
in both options, with a total of 57 participants. Out of these 
57 participants, 51 belonged to the age group of 24 to 39 
years, followed by three from age group 23 and under and 
three from age group 40 to 55. The second more popular 
option was to purchase from the retail stores, with 32 partic-
ipants who have chosen this option. Of these 32 participants, 
23 were in the age group of 24 to 39 years, followed by 6 of 
them who were 40 to 55 years of age, and lastly, three who 
belonged to the age group 23 and under. The 'least' popular 
option was to purchase from e-commerce stores, with 14 
participants who have chosen it. Out of the 14 participants, 
13 belonged to 24 to 39 and only 40 to 55.
Table 5. Frequency of purchases due to COVD-19 from e-commerce stores 
Frequency of Purchases (due to COVID-19) Country 23 and under 24 to 39 40 to 55 TOTAL
Once in a year or less
Singapore 3 11 - 14
Austria 2 15 4 21
Once in a month
Singapore 8 14 1 23
Austria 3 36 1 40
At least two times a month
Singapore 6 30 5 41
Austria 1 26 2 29
More than five times a month
Singapore 1 24 - 25
Austria - 10 3 13
Source: own research.
Table 6. Participants’ buying preferences 
Preference(s) Country 23 and under 24 to 39 40 to 55 TOTAL
To purchase from retail stores
Singapore 1 6 - 7
Austria 3 23 6 32
To purchase from e-commerce stores
Singapore 2 15 - 17
Austria - 13 1 14
Both
Singapore 15 58 6 79
Austria 3 51 3 56
Source: own research.

65
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
Reasons for preferences on purchases 
Next, the participants were asked the reason(s) that positive-
ly motivated their preferences to purchase from the retail 
stores. Participants were allowed to choose for more than 
one of the reasons where they deemed fit. Table 7 depicts an 
overview of the breakdown of the participants' motivation(s) 
that drives their preferences to shop in the retail stores. A 
total of 87 participants have chosen that they like to shop at 
the retail stores because of the ability to choose and touch 
the product they wish to purchase what comes next after 
their first preference was the availability of the product(s) in 
stores, where 62 of the participants have picked this option. 
Followed by 45 participants who think that competitive 
pricing drives their preferences, 36 of them have loyalty/trust 
with the retail stores. Two of the participants have provided 
other reasons, and the factors given were; the service factor 
and that the participant enjoys the human interaction with 
the service staff as well as the ambiance of the store, whereas 
the next participant has indicated that for the fashion buys, 
he/she would be able to try on the physical item as well as 
being able to know the quality of the item that they wished to 
purchase as well as being able to examine the craft.
Similarly in Austria, the bulk of the participants, 88 of them, 
have answered that they enjoyed choosing and touching 
their product before purchase. The following popular 
options were the product's availability, with 57 participants 
who opted for this choice, and the loyalty/trust the 56 par-
ticipants had and felt towards the retail stores. This was 
followed by 25 of the participants who felt motivated by the 
competitive pricing offered by the stores and lastly, one who 
had provided another factor, the ability to get the specific 
product that he/she was looking for instantly.
Next, the participants were questioned about the positive 
motivation(s) driving their shopping preferences through 
e-commerce stores. Participants were also able to opt for 
more than one factor, should the factor(s) fit their preferences. 
Table 8 shows that in Singapore the most significant portion 
of the choices went to convenience, with 87 participants who 
opted for it. Following this factor, 79 of the participants felt 
Table 7. Reasons behind participants’ retail store preferences
Retail Stores Country 23 and under 24 to 39 40 to 55 TOTAL
Availability of Product
Singapore 10 48 4 62
Austria 4 47 6 57
Competitive pricing
Singapore 8 33 4 45
Austria 3 19 3 25
Enjoy the ability of being able to choose 
and touch the product
Singapore 16 67 4 87
Austria 4 74 10 88
Loyalty/trust
Singapore 11 23 2 36
Austria 5 47 4 56
Others
Singapore - 1 1 2
Austria - 1 - 1
Source: own research.
compelled by the competitive pricing offered by e-commerce 
stores. Ranking closely was customer reviews, where 77 
participants have chosen as the reason that motivated them 
to purchase from e-commerce. Forty-eight participants have 
chosen the product's availability, with loyalty/trust trailing 
behind with 42 votes. Lastly, thirty-two participants have 
chosen customer service, and there was another option chosen, 
and the factor is written the ability to have more variety in the 
choices for the purchase that he/she wishes to make.
Competitive pricing came out as the most chosen factor 
that drove the Austrian participants' preferences, with 
83 votes (Table 8). Convenience was voted as the second 
favourite factor, with 73 participants who have chosen it. 
Following very closely behind comes the factor availability 
of the product, with 72 counts. Fifty-one participants have 
chosen customer reviews, 12 have chosen loyalty/trust with 
the e-commerce stores, followed by one who has inputted 
another factor; the factor provided was the possibility of 
a more extensive selection of choices for the item he/she 
wishes to purchase, and if the participant is looking for 
something unique, he/she would be able to find it faster in 
the e-commerce store.
The participants were further prodded with the five factors. 
They were questioned about which of the factors would 

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NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
Table 8. Reasons behind participants’ e-commerce store preferences
E-commerce Stores Country 23 and under 24 to 39 40 to 55 TOTAL
Availability of Product
Singapore 6 41 1 48
Austria 6 59 7 72
Competitive pricing
Singapore 11 62 6 79
Austria 5 71 7 83
Convenience
Singapore 17 65 5 87
Austria 6 60 7 73
Customer Reviews
Singapore 16 57 4 77
Austria 4 43 4 51
Customer Service
Singapore 5 26 1 32
Austria 1 10 - 11
Loyalty/trust
Singapore 7 31 4 42
Austria - 12 - 12
Others
Singapore - 1 - 1
Austria - 1 - 1
Source: own research.
increase the frequency of their purchases from e-com-
merce. The collated results are displayed and seen in Table 
9. The top voted factor in Singapore, with 81 counts were 
convenience. Next up, 68 of the participants have chosen 
competitive pricing as the factor that increased their fre-
quency of e-commerce purchases. Customer reviews were 
next, with 52 votes. They were followed by the product's 
availability with 46 votes, and 21 have chosen customer 
Table 9. Factors that increases the frequency of e-commerce purchases
Factors increasing the frequency of 
purchases e-commerce
Country 23 and under 24 to 39 40 to 55 TOTAL
Availability of Product
Singapore 4 39 3 46
Austria 5 56 5 66
Competitive pricing
Singapore 8 54 6 68
Austria 5 56 7 68
Convenience
Singapore 13 64 4 81
Austria 4 45 6 55
Customer Reviews
Singapore 7 40 5 52
Austria 3 25 3 31
Customer Service
Singapore 2 18 1 21
Austria - 7 - 7
Loyalty/trust
Singapore 4 20 2 26
Austria - 7 - 7
Others
Singapore - 2 - 2
Austria - 2 - 2
Source: own research.

67
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
service. Two have chosen others and have provided the 
factors that have increased the frequency of their purchases. 
The first given factor was the ongoing promotion campaign, 
and an example of the 11.11 promotion was provided. The 
next factor was the delivery right to their doorstep, especial-
ly if the participant purchases something heavy or bulky, he/
she will not have to carry the heavyweight back home.
The most voted factor in Austria was competitive pricing, 
with 68 counts (Table 9). The next factor was the product's 
availability, with 66 of the participants who had opted for 
it. Convenience was voted next, with 55 votes. This was 
followed by customer reviews with 31 votes, seven chosen 
customer service, and seven opted for the loyalty/trust factor. 
Last but not least, 2 of the participants have chosen others but 
have failed to provide any reasoning behind their choices.
Lastly, the participants were questioned about the factor(s) 
that have stopped them from purchasing from e-commerce. 
The overview of the data collected from the Singaporean 
participants can be observed in Table 10. Based on the data 
collected, the most off-putting factor to the Singaporeans 
were negative customer reviews, with 61 votes behind this 
option. The next factor chosen the most was the bad ex-
perience obtained from their previous buys with 52 votes, 
followed by the factor of not having the ability to choose 
and touch the product they wished to purchase with 37 
votes. Thirty-two participants have opted for uncompetitive 
pricing, followed by 29 who have chosen mistrust as the 
factor that has stopped them from purchasing from e-com-
merce stores. Lastly, 25 of them have indicated that they 
have not stopped purchasing from e-commerce stores, and 
1 participant has chosen the other option and has indicated a 
not applicable statement for him/her.
A big part of the participants in Austria, 48 of them, have 
opted not to stop purchasing from e-commerce (Table 10). 
The next most voted factor, with 35 votes, was negative 
Table 10. Factors that have stopped participants from purchasing from e-commerce
Factors that have stopped the purchases 
e-commerce
Country 23 and under 24 to 39 40 to 55 TOTAL
Bad Experience from Previous Buys
Singapore 9 41 2 52
Austria 2 26 4 32
Mistrust
Singapore 3 24 2 29
Austria - 19 1 20
Negative Customer Reviews
Singapore 9 48 3 61
Austria 3 29 3 35
Not having the ability of being able to 
choose and touch the product
Singapore 6 30 1 37
Austria 2 21 2 25
Uncompetitive Pricing
Singapore 7 25 - 32
Austria 1 10 1 12
Have not stopped purchasing online
Singapore 3 20 2 25
Austria 3 42 3 48
Others
Singapore - 1 - 1
Austria - 3 - 3
Source: own research.
customer reviews, followed by 32 votes who have opted for 
terrible experiences from previous buys. Twenty-five of the 
participants have chosen that they have stopped purchas-
ing from e-commerce because of not having the ability to 
choose and touch the product they wished to purchase, and 
20 of them have chosen mistrust as the factor. Last but not 
least, the least voted factor was uncompetitive pricing with 
12 votes, and 3 of the participants have opted for the others 
option. The participants provided the other factors that have 
stopped them from purchasing from e-commerce were; the 
potential CO
2
 impact on the environment, supporting the 
local economies, and having only bad delivery options.

68
NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
Analysis based on t-test
In order to analyse the factors that may or may not affect the 
consumers' buying behaviours t-test analysis was chosen. 
A convenient significance value of 0.05% was assumed 
throughout this entire research.
A significance value of 5% was assumed and utilized 
throughout this entire research. Table 11 shows an overview 
of the t-test analysis results for the Likert scale question 11, 
on how vital the six factors, namely availability of a product, 
competitive pricing, convenience, customer service, 
customer reviews, and loyalty/trust, are for the participants 
before they would purchase from e-commerce. The exhib-
ited p-values for Singapore show that the only factor with 
p-value higher than 0.05 was availabity of product. Thus, the 
null hypothesis could not be rejected. Thus, the availability 
of product may not affect Singaporean consumers' buying 
behaviour in e-commerce settings. For all other factors the 
null hypothesis could be rejected since the p-value was 
lower than the assumed significance value of 0.05. As a 
result, competitive pricing, convenience, customer service, 
customer reviews and loyalty/trust might affect Singaporean 
consumers' buying behaviour (s) in e-commerce settings.
Table 11. Results of t-test for question 11
One-sample t-test (Sig. (2-tailed))
Factors tested Singapore Austria
Availability of Product 0.771 0.006
Competitive Pricing 0.000 0.415
Convenience 0.008 0.000
Customer Service 0.004 0.237
Customer Reviews 0.000 0.000
Loyalty/Trust 0.002 0.810
Source: own research.
According to results of the t-test in the Austrian sample 
(Table 11), availability of product, convenience and 
customer reviews play an important role in the Austrian 
consumers' buying behavior(s) in e-commerce settings. In 
these three cases the p-value was lower than the 0.05 and the 
null hypothesis could be rejected. On the other hand, com-
petitive pricing, customer services and loyalty/trust might 
not affect the Austrian consumers' buying behaviour(s) in 
the e-commerce settings since they exhibit p-values lower 
than 0.05 and the null hypothesis for these factors could not 
be rejected.
Table 12 provides an overview of the t-test analysis results 
for the Likert scale question 12, on how the five factors, 
namely bad experience from previous buys, mistrust, 
negative customer reviews, inability to choose and touch the 
product, and lastly uncompetitive pricing, would stop the 
Singaporean and Austrian consumers from purchasing from 
the e-commerce.
Table 12. Results of t-test for question 12
One-sample t-test (Sig. (2-tailed))
Factors tested Singapore Austria
Bad Experience from Previous Buys 0.001 0.422
Mistrust 0.000 0.110
Negative Customer Reviews 0.246 0.000
Inability to Choose and Touch the 
Product
0.328 0.328
Uncompetitive Pricing 0.775 0.000
Source: own research.
The t-test analysis conducted for Singapore on the factors 
bad experience from previous buys and mistrust have 
revealed p-values lower than 0.05. The null hypothesis could 
be rejected. Thus, these two factors might affect Singapore-
an consumers' buying behaviour(s) in e-commerce settings. 
While negative customer reviews, inability to choose and 
touch the product and uncompetitive pricing might not affect 
Singaporean consumers' buying behaviour(s) in e-com-
merce, since for these three factors the p-values are higher 
than 0.005 and the null hypothesis could not be rejected.
While, the t-test results for Austria (Table 12) show that 
bad experience from previous buys, mistrust and inability 
to choose might not affect the Austrian consumers' buying 
behaviour(s) in the e-commerce settings since the p-values 
for these factors are higher than 0.05 and the null hypothesis 
could not be rejected. On the other hand, negative customer 
reviews and uncompetitive pricing revealed p-values lower 
than 0.05 and the null hypothesis could be rejected. Thus, 
negative customer reviews and uncompetitive pricing might 
affect the Austrian consumers' buying behaviour(s) in the 
e-commerce settings.
Correlation analysis
Subsequently, after conducting the t-test analyses, a cor-
relation analysis between the six factors was also tested 
with Pearson's correlation test and the study of each of its 
significance values. Pearson’s r varies between +1 and -1, 
where +1 is a perfect positive correlation, and -1 is a perfect 
negative correlation. With a value of 0, it means that there is 
no linear correlation at all (Ezspss, n.d.).

69
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
Table 13 depicts an overview of the datasets obtained from 
the Pearson correlation analysis on the six factors: availabil-
ity of a product, competitive pricing, convenience, customer 
service, customer reviews, and loyalty/trust for the Singapo-
rean participants. It can be observed that with the Pearson's 
correlation test for the availability of product shows a small, 
moderate correlation strength to competitive pricing, con-
venience, service and reviews with statistically significant 
Pearson Correlation r-values among of 0.248 and 0.366, and 
even lower r-value for loyalty/trust, which is not statistically 
significant.
The correlation analysis results for the competitive pricing 
show weak correlation with convenience, service, reviews 
and loyalty/trust with statistically insignificant r-values 
among 0.016 and 0.190. Thus, there is no evidence of the 
existence of the correlation. As for convenience the r-values 
regarding other factors are statistically significant and exibit 
values among 0.269 and 0.404, providing evidence of weak 
correlation among convenience on one hand and service, 
review and loyalty/trust on the other. Correlation among 
customer service and reviews amounts to 0.323 and is statis-
tically significant, while correlation among customer service 
and loyalty/trust resulted in 0.361 and is also statistically 
significant. And the last pair of factors is correlation among 
customers reviews and loyalty/trust, where the statistically 
significant r-value is 0.280.
Table 14 depicts an overview of the datasets obtained from 
the Pearson correlation analysis on the six factors: availabil-
ity of a product, competitive pricing, convenience, customer 
service, customer reviews, and loyalty/trust for the Austrian 
Table 13. Pearson correlation analysis for Singapore
Factors tested Pricing Convenience Service Reviews Loyalty/Trust
Availability of Product 0.248 0.294 0.289 0.366 0.130
   Sig. (2-tailed) 0.012 0.003 0.103 0.000 0.189
Competitive Pricing - 0.118 0.019 0.190 0.016
   Sig. (2-tailed) - 0.233 0.847 0.055 0.870
Convenience - - 0.306 0.404 0.269
   Sig. (2-tailed) - - 0.002 0.000 0.006
Customer Service - - - 0.323 0.361
   Sig. (2-tailed) - - - 0.001 0.000
Customer Reviews - - - - 0.280
   Sig. (2-tailed) - - - - 0.004
Source: own research.
Table 14. Pearson correlation analysis for Austria
Factors tested Pricing Convenience Service Reviews Loyalty/Trust
Availability of Product 0.062 0.018 -0.046 -0.004 0.066
   Sig. (2-tailed) 0.533 0.853 0.645 0.970 0.507
Competitive Pricing - -0.044 0.049 0.160 0.154
   Sig. (2-tailed) - 0.657 0.623 0.107 0.121
Convenience - - 0.217 -0.162 0.072
   Sig. (2-tailed) - - 0.028 0.101 0.470
Customer Service - - - 0.166 0.366
   Sig. (2-tailed) - - - 0.094 0.000
Customer Reviews - - - - 0.121
   Sig. (2-tailed) - - - - 0.224
Source: own research.

70
NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 67 No. 4 / December 2021
participants. The availability of product shows a very weak 
statistically insignificant correlation to competitive pricing, 
convenience, service, reviews and loyalty/trust.  Thus, there 
is no evidence that this correlation does exist within this 
sample population. Similarly, there is no proof of correlation 
among convenience and reviews, and among convenience 
and loyalty/trust, as there are relatively low statistically 
insignificant r-values. However, there is a weak statistical-
ly significant correlation among convenience and service. 
Furthermore, there is no statistically significant correlation 
among customer service and customer reviews, and among 
customer reviews and loyalty/trust. But correlation among 
customer service and loyalty/trust is proven to be statistical-
ly significant with r-value of 0.366.
Interpretation of Results
The main hypothesis “Consumers' buying behaviours may 
affect the e-commerce environment.” can be divided into 
two parts considering a positive or negative effect of selected 
factors related to customer behaviours to the e-commerce 
environment. 
Regarding the positive factors in Singapore, the one-sample 
t-test analyses showed that the participants placed higher 
importance on certain factors before they purchased from 
e-commerce. It was found that the following factors: com-
petitive pricing, convenience, customer service, customer 
reviews, and loyalty/trust, may play a role towards the 
contribution of a positive effect and impact on their buying 
behaviours in the e-commerce environment. Availability of 
product was ruled out with the t-test analysis, and thus it 
was implied that this factor might not affect their buying 
behaviour(s) for the e-commerce. As for Austria, the results 
of t-test analysis have shown that the following factors: 
product availability, convenience, and customer reviews, 
may positively affect customers’ buying behaviour(s) in the 
e-commerce environment. Competitive pricing, customer 
service, and loyalty/trust were ruled out and may not cause 
any positive impacts on their buying behaviour(s).
Regarding the negative effect in Singapore and based on 
the t-test, the factors identified were bad experiences from 
previous buys and the sense of mistrust that would impact 
their buying behaviour(s) negatively. The following factors 
were ruled out from the one-sample t-test and thus would 
not negatively affect the Singaporeans' buying behaviour(s): 
negative customer reviews, inability to choose and touch the 
product, and lastly, uncompetitive pricing. In Austria, the 
results of the t-test have disclosed that negative customer 
reviews and uncompetitive pricing might negatively affect 
and impact their buying behaviour(s) in the e-commerce 
environment for the Austrians. The remaining factors, 
bad experience from previous buys, mistrust, the inabili-
ty to choose and touch the product, were tested and ruled 
out as having any adverse effects on the Austrians' buying 
behaviour(s).
Based on the outputs received from the Pearson's correla-
tion tests, some weak signs of correlation, be it positive or 
negative, between the five factors existed. For this research's 
case, it was discovered from the sample of Singapore that 
when the factor availability of the product was chosen, it 
was also highly likely that the following factors competi-
tive pricing, convenience, and customer reviews, would be 
selected well. Also, as most of the correlations were rela-
tively weak, with r-values ranging from 0.2 to 0.4, it indi-
cates weak relationships between the tested factors. With 
double-checking conducted on the results with the signifi-
cance test, the outcomes have proven that specific correla-
tions may have existed between the factors. There were no 
negative correlations detected from the Singapore sample. 
For the Austrians, it was discovered from the sample dataset 
that when the factor customer service was chosen, it was 
probable that the factor loyalty/trust would be selected. 
The majority of the correlations were relatively weak, with 
r-values ranging from 0.01 to 0.3, which indicated weak 
relationships between the tested factors. However, after 
conducting a check with the significance test results, some 
of the outcomes could not prove the correlations between 
the factors. On the other hand, several negative correla-
tions were detected, for example, the factor availability of 
the product and its correlation with the factor of customer 
service. It could be interpreted that when the Austrians chose 
product availability, they are less likely to have also chosen 
customer service. However, a check with the significance 
test has shown otherwise and, as such, holds insufficient 
evidence to confirm that the negative correlations existed. 
Conclusion
The data collected has revealed that most Singaporean con-
sumers and a majority of the Austrian consumers mostly 
purchase once a month from the retail stores. Similarly, 
these two groups of sample consumers also purchase once 
a month from e-commerce. Based on the findings observed 
from the statement "E-commerce has increased the fre-
quency of you making purchases," it can be observed that 
Singaporean participants feel that they are generally more 
impacted by e-commerce. A higher number of the Singapo-
reans, 43 of them, feel a solid agreement to the prior state-
ment than 7 of the Austrians' strong agreements. Lastly, the 
overall agreement rate (between agree and strongly agree) of 
74% from the Singaporeans was also higher than the Austri-
ans' agreement rate at 52%.

71
Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
A considerable portion of the Singaporean and Austrian con-
sumers have indicated that they prefer to shop from retail 
and e-commerce stores. Seventy-nine of the Singaporeans 
and 57 of the Austrians have chosen both retail and e-com-
merce as their preferences. For the remaining sample, which 
has not chosen both as a preference, it can be gathered that 
32 of the Austrians prefer to shop from retail stores, and 
17 of the Singaporeans prefer to shop from e-commerce. 
Overall, it can be concluded from this sample data that Sin-
gaporeans may hold a higher preference towards purchasing 
from e-commerce in general, as compared to the Austrians.
The primary motivator that may have positively impacted 
the buying behaviours of most Singaporeans and Austrians 
to purchase from retail stores was the ability to choose and 
touch the product(s) that they wish to buy. Following behind 
very closely was the factor availability of the product as the 
second most chosen motivator by both sample groups. 
Next, briefly will discuss the motivators that positively push 
and support the Singaporeans and Austrians to purchase 
from e-commerce stores. Based on the data, it was observed 
that convenience was the top motivator that most Singapo-
reans have chosen, which may positively impact their online 
buying behaviours. The second most chosen factor was 
competitive pricing. Whereas for the Austrian participants, 
the bulk has chosen competitive pricing as the primary 
motivator that may positively impact their online shopping 
preferences and following very closely behind was the 
chosen factor, convenience. 
Statistical t-test analysis was conducted on the responses 
obtained from both of the sample groups. It was observed 
from the results that for Singaporeans, competitive pricing, 
convenience, customer service, customer reviews, and 
loyalty/trust are the five factors that may positively impact 
washing behaviours in e-commerce settings. As for the 
Austrian consumers, it was discovered that their results were 
different from that of the Singaporean consumers. The listed 
four factors: availability of the product, convenience, and 
customer reviews, were found to have a potentially positive 
impact on the Austrian consumers' buying behaviour(s) in 
the e-commerce settings. 
Similarly, the statistical t-test analysis was also conducted on 
the data samples to identify the potential negative impact(s) 
a factor may have on the participants' buying behaviours. 
As derived from the obtained results, it was seen that bad 
experiences from their previous buys and mistrust could po-
tentially negatively impact Singaporean consumers' online 
buying behaviours. As for the Austrian consumers, the 
following factors that may have posed negative impact(s) 
on their online buying behaviours were negative customer 
reviews and uncompetitive pricing.
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Jia Yun Moerth-Teo, Vito Bobek, Tatjana Horvat: The Effects of Consumers’ Buying Behavior on the  
E-commerce in Highly Developed Emerging Market and Developed Market: The Case of Singapore and Austria
Učinki nakupnega vedenja potrošnikov na 
e-trgovino na visoko razvitem nastajajočem trgu in 
razvitem trgu: primer Singapurja in Avstrije 
Izvleček
E-trgovina postaja v sodobnem svetu vse bolj pomembna in predvsem aktualna, zlasti v trenutni pandemiji. Zaradi povečane 
uporabe interneta je rast e-trgovine eskalirala. Ta raziskava se osredotoča na e-trgovinski okolji singapurskega in avstrijskega 
trga. Vsebuje oris, ki se dotika teoretičnih delov in izvedbe empirične študije, v kateri smo proučili, analizirali in primerjali 
rezultate anketiranja 206 udeležencev. Za to raziskavo sta bili izbrani statistični metodi analiza t-testa in korelacijska analiza. 
Empirična študija je služila kot kvantitativna razprava o trgih e-trgovine obeh držav. Analiza izpolnjenih vprašalnikov je 
omogočila boljše in jasno razumevanje nakupnega vedenja in njegovega možnega vpliva na trge e-trgovine v Singapurju in 
Avstriji. Glede na rezultate primerjav je raziskava izpostavila tudi nekaj zanimivih ugotovitev in razlik v nakupnem vedenju 
singapurskih in avstrijskih kupcev.
Ključne besede: e-trgovina, oblikovanje cen, nakupno vedenje, potrošniki, Singapur, Avstrija