Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
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Sugarmaa Purevkhuu and Javkhlan Munkhbold. (2021). Demographic
and Cultural Factors Influencing the Adoption of B2C E-Commerce in
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Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
p- ISSN 2775-3735 e-ISSN 2775-3727
DEMOGRAPHIC AND CULTURAL FACTORS INFLUENCING THE
ADOPTION OF B2C E-COMMERCE IN SCO REGION
Sugarmaa Purevkhuu and Javkhlan Munkhbold
University of International Business and Economics, Beijing, China
E-mail: [email protected], 15611203132@163.com
ARTICLE INFO ABSTRACT
Received:
September, 26
th
2021
Revised:
October, 12
nd
2021
Approved:
October, 14
th
2021
In the era of digitalization, e-commerce is providing
exceptional opportunities to access domestic and
international markets and is believed to be one of the
main tools for poverty reduction and development
acceleration. Shanghai Cooperation Organization (SCO),
as one of the main intergovernmental organizations in
Eurasia, is taking measures to develop e-commerce in the
region. However, SCO member states vary in terms of e-
commerce experience due to dissimilar economic
situations and cultural differences. The purpose of this
paper is to examine the factors that affect B2C e-
commerce adoption in the SCO region. The main objective
of the study is to integrate the demographic
characteristics with Hofstede’s cultural dimensions in
order to determine the factors of e-commerce adoption
among customers in SCO member states. The result shows
that in SCO countries, e-commerce is more spread
amongst young females who are currently employed, and
therefore have high education levels and incomes. From
the perspective of the national culture, SCO member
countries with high individualism, low uncertainty
avoidance, and low indulgence level have more e-
commerce customers than the other SCO member states.
KEYWORDS
E-Commerce, B2C, Developing Countries, Shanghai
Cooperation Organization, SCO
This work is licensed under a Creative Commons
Attribution-ShareAlike 4.0 International
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1081
INTRODUCTION
Digitalization speed, substantial growth of internet penetration, and recently, the
restrictions caused by COVID-19 has accelerated the e-commerce growth and according
to United Nations Conference on Trade and Development (UNCTAD) news, in 2019 the
worldwide e-commerce sales raised up to $26.7 trillion, which is equivalent to 30% of
global GDP, and 4% up from 2018. Since e-commerce is characterized as one of the main
criteria for information technology revolution (Nanehkaran, 2013) and heart of
Sustainable Development Goals, many researchers have developed e-commerce adoption
and implementation frameworks related to consumers and online enterprises. Consumer
related researches are focusing on behavioral issues and segmentation; the researches on
enterprises are mostly analyzing store features, credibility and reputation, and online
shopping tools (Huseynov & Yıldırım, 2016). However, the prevailing amount of these e-
commerce studies are focusing on consumers and enterprises of developed countries, and
very few are conducted on developing or least developed countries (Boateng, Hinson,
Heeks, & Molla, 2015). As developed countries are mostly hyper-digitalized, developing
and least developing countries are lagging behind and in danger to fall behind being
unable to transform data into a digital value (World Bank, 2020). The lack of sufficient
infrastructural, socio-economic and sometimes even the absence of national strategies as
well as reliable scholarly researches have formed a major obstacle in e-commerce
adoption and usage in developing countries (Kimery, 2011). Moreover, there is a lack of
researches about cultural influence combined with demographics data on e-commerce
adoption and usage focusing on developing countries or even on regional blocs (Ayob,
2021). Herein, the Shanghai Cooperation Organization (SCO) region, which has almost
half of the world's population from developing and transition economies, becomes the
perfect niche for the research.
The objective of this paper is to examine B2C e-commerce adoption in member
states of SCO, by integrating demographic characteristics with Hofstede’s cultural
dimensions. The next section is a literature review, which is followed by a research
method section that comprises used data and its sources. The fourth section is a result and
discussion and the final section is a conclusion, followed by a list of references.
LITERATURE REVIEW
Shanghai Cooperation Organization (SCO), one of the main intergovernmental
organizations in Eurasia, was established in 2001 and has eight member states: China,
Russia, Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan Pakistan, and India. As home to
nearly half of the world’s population, SCO member states cover three-fifths of the
Eurasian continent and contribute about 20 percent to world GDP.
Since 2019 SCO is taking measures to develop e-commerce in the SCO region: one
of the main topics of the talks held in Tashkent on November 2
nd
, 2019, was the prospect
of economic partnership among SCO member states and the adoption of the trade and
economic cooperation program until 2035. Following that in November 2020, member
states have signed the “Statement by the SCO Heads of State Council on Cooperation in
the Digital Economy”. Furthermore, on 7
th
June 2021, SCO Secretariat and Alibaba
Group delegation had an online meeting, whereas SCO Secretary-General Vladimir
Norov stated that member states are developing draft documents aimed at unlocking
potential and using opportunities to increase digitalization in the region.
B2C e-commerce in SCO member states
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One of the most reliable B2C e-commerce indicators is the UNCTAD B2C e-
commerce index. Table 1 shows SCO member states ranking in UNCTAD B2C e-
commerce index from 2016-2020:
Table 1. SCO member states’ UNCTAD B2C e-commerce index
Member State
2016*
2017**
2018**
2019***
2020***
China****
64
65
63
56
55
India
90
83
80
73
71
Kazakhstan
88
51
53
57
60
Kyrgyzstan
109
117
114
111
97
Pakistan
105
120
117
114
116
Russia
47
43
42
40
41
Tajikistan
-
-
-
129
121
Uzbekistan
108
106
86
93
107
* Ranking among 137 countries
** Ranking among 151 countries
*** Ranking among 152 countries
**** China Mainland
Although China is leading in terms of e-commerce sales in the world, it was ranked
55
th
because UNCTAD variables are focused on connection quality and banking services
rather than e-commerce sales scale. Overall the average ranking of SCO member states in
the UNCTAD B2C e-commerce index was 83
rd
in 2020.
According to the Digital 2021 Global Overview Report, SCO member states have
1.8 billion internet users and only 545 million of them made the online purchase and/or
paid bills online. The detailed data is shown below:
Table 2. SCO member states internet penetration rate and
B2C e-commerce statistics.
Member
State
Total
population
(million)
**
Total
internet
users
(million)
Internet
penetration
(%)
Users, who make an
online purchase
and/or pays bills
online (million)
Online
shoppers’
percentage
(%)
China*
1402
939.8
65.2%
459
48.8 %
India
1380
624
45%
26
4.3%
Kazakhstan
18.75
15.47
81.9%
3.8
24.3%
Kyrgyzstan
6.59
3.32
50.4%
0.16
5%
Pakistan
221
61.34
27.5%
5
8%
Russia
144.1
124
85%
49
39.6%
Tajikistan
9.53
3.36
34.9%
0.43
12.8%
Uzbekistan
34.2
18.6
55.2%
1.3
7.1%
* China Mainland
** World Bank
As shown above, the B2C e-commerce situation varies among SCO member states.
In summary, the overall e-commerce purchase statistics are low: as of January 2021, the
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1083
average internet penetration in SCO member states was 56 percent, and only 19 percent
of total internet users made online purchases and/or paid bills online. Without doubt there
are economic, infrastructural and politic factors on e-commerce adoption in SCO member
states. However, this paper will precisely focus on demographic and cultural factors of e-
commerce adoption in SCO region.
Factors affecting adoption of e-commerce and hypotheses development
Demographic factors:
As e-commerce consumers consist of heterogonous groups with different needs and
expectations, from the beginning of the 2000s researchers started analyzing the socio-
demographic factors impacting the online purchase of consumers (Huseynov & Yıldırım,
2016) Based on researches it was concluded that age, education, gender, employment,
and income have a significant influence on consumers’ intention to purchase online
(Afizah, Erlane & Jamaliah 2009; Beneke & Du, 2010).
• Age
According to James (Gentry & Mittelstaedt, 2017), retailers and marketers should
consider different age groups, as they have different online purchasing behavior.
McCloskey and Leppel (McCloskey & Leppel, 2010), reported that people born in 1930-
1945 are not likely to use information technologies and therefore don’t purchase online
much. Moreover, Generation Y (1981-1996) use internet more than Generation X (1965-
1980), but the percentage of online purchases is prevailing among Generation X (Lissitsa
& Kol, 2016). As for Generation Z (1997-2012), Viera (Viera et.al, 2020) characterized
them as generations with trust and experience in technologies, who are doing a lot of
research before purchasing and like to share their opinions on digital platforms.
Hypothesis 1: Online purchase is prevalent among young consumers of SCO member
states.
• Gender
Gender difference in e-commerce has been observed from diverse perspectives,
such as the perceived risk of online behavior (Garbarino & Strahilevitz, 2004), and
technology acceptance (Ali & Qing, 2007) etc. In terms of technology acceptance and
usage, several studies state that men are more technology-oriented, and therefore use the
internet more than women (Villarejo, Peral & Arenas, 2014). In line with these studies,
Slyke (Slyke et.al, 2010) reported that products sold on e-platforms are more focused on
men and therefore men purchase online more frequently than women. The reasons why
women purchase less than men were proposed by several researchers and the majority of
conclusions stated that women have lower trust and higher perceived risk towards online
shopping (Gichang & Jialin, 2009). However, a study by Wu revealed that even though
men use online banking more frequently than women, apparently women have more trust
to the online platforms security than men (Wu, Quyen & Rivas, 2016). Therefore, we
propose that men purchase online more than women in SCO member states.
Hypothesis 2: Online purchase is prevalent among male consumers of SCO member
states.
• Education
Better educated consumers don’t only use the information technology for diverse
tasks, comprehensive search, but also use their cyber-fluency to find products that match
their needs. (Punj, 2011). Therefire some studies even concluded that education level
influences the adoption, usage of e-commerce and the online shopping behavior. Delia
found that education has an impact on online purchases regularity and how consumers
perceive the products (Delia, 2012). Consumers with higher education consider price as
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an important factor for product perception, whereas users with low education consider
service quality and subjective norms important in online shopping. Thus far, according to
Bradford and Whitacre, less educated people even avoid the internet because they assume
that digital content is concentrating on better-educated consumers (Bradford & Whitacre,
2003).
Hypothesis 3: Online purchase is prevalent among higher educated consumers of SCO
member states.
• Employment and income
A higher level of education leads to better employment opportunities and therefore
has a positive effect on higher earnings (OECD, 2019). Moreover, income level is not
only a significant factor for store shopping, but also a positive approach for e-commerce
adoption and purchase (Ahasanul, Sadeghzadeh & Khatibi, 2011). Furthermore, online
customers are not only employed, but also wealthier than traditional store consumers.
Depending on earnings, customers with higher income prefer to save time and shop
online, whereas customers with lower income prefer to save money (Punj, 2011).
Hypothesis 4: Online purchase is prevalent among employed consumers of SCO member
states.
Hypothesis 5: Online purchase is associated with higher income in SCO member states.
Cultural factors:
One of the internationally recognized theories to understand cultural differences is
Hofstede’s cultural dimensions model, which was first published in the late 1970s, and
updated in 1991 and 2010. As for now it has six cultural dimensions:
• Power distance index
Power distance index (PDI) measures the country’s power distribution and how
citizens accept disposal of it. Due to unequal power distribution, most Asian countries
have a high PDI index and hierarchical relationship between boss and employee (Grazzini
et al., 2020). As for SCO member states, China and India have a high power distance
index, which affects the consumer behavior and leads to less trust in online shopping
(Rinne, Steel & Fairweather, 2013).
Hypothesis 6: Online purchase is prevalent among SCO member states with a lower PDI.
• Individualism versus collectivism
Individualism (IDV) versus collectivism (COL) dimension refers to ties between
people in society. In an individualist society, the connection between people is low and
there is no significant support between members. Despite the fact that in collectivist
cultures people have higher trust to e-platforms, individualist country citizens are more
likely to try various e-platforms and to switch between them (Hofstede & Minkov, 2010).
Hypothesis 7: Online purchase is prevalent among SCO member states with higher IDV.
• Masculinity versus femininity
The masculinity (MAS) versus femininity (FEM) dimension characterizes whether
gender has aninfluence on society's roles or not. Most Asian countries are characterized
as feminine, as there is no strong differentiation between genders, whereas western
countries are referred to as masculine, because of their competitive nature. E-commerce is
preferred by feminine society, and citizens of a masculine culture have higher user-
friendliness of the platform (Pratesi et.al., 2021).
Hypothesis 8: Online purchase is prevalent among SCO member states with lower MAS.
• Uncertainty avoidance index
The uncertainty avoidance index (UAI) describes the degree to which individuals
respond and tolerate uncertainties and ambiguities. Countries with high UAI prefer to
constrain uncertainty by various rules and codes, and are often characterized as less prone
to accept risks (Pratesi et.al., 2021). On contrary, people from lower UAI countries are
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1085
willing to accept risks, and expected to faster adopt modern technologies and therefore,
the e-commerce (Hwang & Lee, 2012).
Hypothesis 9: Online purchase is prevalent among SCO member states with lower UAI.
• Long-versus short-term orientation
Short-term oriented cultures focus on virtues related to the past and current
situations, while long-term oriented focus on the upcoming situations. Therefore, long-
term-oriented cultures make long-lasting businesses only with trusted partners.
Researchers found that collectivism and long-term orientation are positively correlated
with trust disposition and help to build trust in e-commerce (Hallikainen & Laukkanen,
2018).
Hypothesis 10: Online purchase is prevalent among long-term-oriented SCO member
states.
• Indulgence versus restraint
Indulgence (IVR) versus restraint is the sixth and last cultural dimension by
Hofstede G. This dimension reveals how society reacts to basic human needs and what
social norms are followed. Societies that have weaker controls over feelings and needs
are considered as indulgent countries, while countries with strict social norms considered
as restraint. According to Yavuz’s study, in indulgent society friends, leisure, equal
gender roles, freedom of speech are considered as important. On contrary, restrained
countries focus more on: savings, moral discipline, and order in the nation (Yavuz, 2014).
As restraint countries mostly value duty over pleasure and interested in savings, we
hereby propose the following hypothesis:
Hypothesis 11: Online purchase is prevalent among restraint SCO member states.
RESEARCH METHOD
The following research model will be used to test above eleven hypotheses:
The World Bank Global FINDEX data is currently the most significant dataset on
financial inclusion and used to analyze economic situations of individual countries and
regional or financial blocs such as ASEAN, SAARC and WAEMU. The B2C e-
commerce adoption and usage among SCO member states are analyzed based on
measurement “if the participant purchased something online in the past year” from latest
FINDEX dataset. Moreover, the five independent demographic variables and account
ownership data are also derived from FINDEX. In total this study analyzed 11227 face-
to-face interviews with SCO citizens (China 3627, India 3000, Kazakhstan 1000, Pakistan
1600, and Russia 2000); whereas 26 respondents did not mention their age, 32 education
level and 161 respondents’ online purchase data are missing.
Six independent variables such as cultural country-level dimensions (power
distance and uncertainty indexes, individualism, masculinity, orientation term and
indulgence) are derived from Hofstede’s site (www.hofstede-insights.com) and measured
in scale from 0 to 100. Plus we assume that GDP per capita and account ownership is
correlated with internet penetration and online purchase, and thereby include them as
control variables in the study.
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The detailed definitions of variables are included below:
Table 3. Definition of variables
Variable
Definition
Source
Dependent variable
E-commerce
adoption
Participant purchased online in the past year=1; no=0
FINDEX
Independent variables (Demographic factors)
Age
Age of participants
FINDEX
Gender
Male=1, female=0
FINDEX
Education
Primary=1, secondary=2, tertiary=3
FINDEX
Employment
Employed=1; unemployed=0
FINDEX
Income level
Poorest=1; Second=2; Middle=3; Fourth=4; Richest=5
FINDEX
Independent variables (Cultural factors)
Power distance
The degree to which citizens accept country’s
distribution of power.
Hofstede
Individualism
Ties between people in society, whereas
individuals take care of themselves or families.
Hofstede
Masculinity
The degree to which gender has an influence on
society's roles.
Hofstede
Uncertainty
avoidance
The degree to which individuals respond and
tolerate uncertainties and ambiguities.
Hofstede
Long-term
orientation
The degree to which society relays to the future
to solve the problems.
Hofstede
Indulgence
The degree to which society reacts to basic human
needs and what social norms are followed.
Hofstede
Control variables
Account
ownership
Have an account at a financial institution=1;
Don't have an account at a financial institution=0
FINDEX
GDP per capita
Gross domestic production divided by population.
World bank
Data limitations
Cultural dimensions of Kyrgyzstan, Tajikistan and Uzbekistan are missing on
Hofstede’s site and according to the Digital 2021 Global Overview Report consumers of
these three countries are comparatively not active in online purchases: total amount of
users who made an online purchase and/or paid bills online in Kyrgyzstan is 0.16 million,
Tajikistan is 0.43 million and Uzbekistan is 1.3 million, which is relatively low compared
to other five SCO countries. Moreover, there is a certain gap of researches on cultural
dimensions of these three countries and only relying on studies by Seyil and Dadabaev,
we assume that Kyrgyzstan, Tajikistan and Uzbekistan are masculine collectivist
countries with different cultural dimensions (Seyil, 2013; Dadabaev T, 2004). As
Hofstede study did not cover these three countries data and researches are not up to date,
we will focus on five SCO member states, namely, China, India, Pakistan, Kazakhstan
and Russia and analyze demographic and cultural dimensions data of these five countries.
Descriptive analysis
In this study we have conducted three descriptive analyses: two correlation
analyses on GDP and demographic factors and one on cultural dimensions of SCO
member states.
In order to test control variables, we conducted the analysis on GDP per capita
with internet penetration rate, global cyber security index and total population of SCO
member states. The economic classification of five member states is derived from
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1087
FINDEX; the global cyber security index is from International Telecommunication
Union; GDP per capita and total population data are from World Bank; and internet
penetration rate from Digital 2021 Global Overview Report. The detailed data is included
below:
Table 4. Correlation analysis of GDP and internet factors
SCO
member
states
Economic
classification
(income)
GDP per
capita
(USD mln)
Internet
penetration
rate (%)
Global cyber
security
index
Total
population
(mln)
China
upper-middle
10500
65.2
92.53
1402
India
lower-middle
1900
45
97.5
1380
Kazakhstan
upper-middle
9055
81.9
93.15
18.75
Pakistan
lower-middle
1193
27.5
64.88
221
Russia
upper-middle
10126
85
98.06
144.1
GDP per capita (USD mln)
1
Internet penetration rate (%)
.903*
1
Global cyber security index
.574*
.730
1
Total population (mln)
-.118*
-.285
.312
1
* Correlation is significant at the 0.01 level (2-tailed).
Five member states of SCO are countries with upper and lower-middle income,
whereas the average GDP is USD 6555 million, internet penetration rate is 61%, and
global cyber security index is 90. Based to correlation analysis results, stated on Table 4,
we can see that our control variable, the GDP per capita, is positively correlated with an
internet penetration rate at 0.90 and global cyber security index at 0.57. This proves our
assumption that GDP has an impact on internet penetration and online purchase.
The second correlation analysis we conducted on demographic factors of SCO
individuals. The analysis on FINDEX dataset from 11227 face to face interviews with
SCO citizens shows us that majority of respondents are employed female, who have
secondary education, middle income and average age of 42. Therefore, the correlation
analysis is significant (Table 5).
Based on above analysis we can state that our second control variable, the
account at financial institution, is significantly correlated with online purchasing, showed
on Table 5 (.274). Online purchase is also positively correlated with employment also
secondary and tertiary education, but negatively correlated with primary education that
suggests higher the education higher the online purchase adoption, whereas age and
gender is not. Also from the income side we see that online purchase is positively
correlated with those who has more earnings such as Fourth 20% of income level holders
also the Richest 20% of the population but negatively correlated with the less income
owners such as poorest 20%, second 20%, middle 20% level income owners. This proves
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the statement from OECD report, which states that a higher level of education leads to
better employment opportunities and therefore has a positive effect on higher earnings.
Lastly, we analyzed cultural dimension of SCO member states (Table 6).
Table 6. Hofstede’s cultural dimensions of SCO member states
SCO
member
states
Power
distance
index
Indivi-
-dualism
Mascu-
-linity
Uncertainty
avoidance
Long-term
orientation
Indulgence
China
80
20
66
30
87
24
India
77
48
56
40
51
26
Kazakhstan
88
20
50
88
85
22
Pakistan
55
14
50
70
50
0
Russia
93
39
36
95
81
20
Total
average
78.6
28.2
51.6
64.6
70.8
18.4
Five member states of SCO, namely China, India, Kazakhstan, Kyrgyzstan and
Pakistan are collectivist countries with high power distance index (total average score is
78.6). Citizens consider themselves as members of group and value personal
interdependence. As region with strong hierarchy in power distribution it mostly has a
strategy, aimed to bring benefits in the future (long-term orientation average is 70.8).
Citizens of member states have high uncertainty avoidance (total average score is 64.6)
and restraint score, which means that they value principles more than practice and follow
strict social norms. Four member states beside Russia show strong characteristics of
masculine countries and thereby gender plays an important role in society. Overall, the
difference between SCO members shows unique distribution to the study to show how
the individual in different countries adopt online purchasing and interact differently in e-
commerce activities.
RESULT AND DISCUSSION
In total eleven independent and two control variables were analyzed. Based on the
dataset from FINDEX we have characterized not only the individual profiles of SCO
customers but also figured out the average national culture dimensions of SCO member
states. The detailed result of the correlation is included in Table 8:
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1089
Table 8. Overall correlation findings of e-commerce users in SCO
Dependent variable
Purchased online in the past year
Independent variables
Demographic characteristics of SCO
National cultural characteristics
Age
Negative
Power distance
Positive
Gender
Negative
Individualism
Negative
Education
Primary-negative
Secondary-positive
Tertiary-positive
Masculinity
Positive
Employment
Positive
Uncertainty avoidance
Negative
Income
Poorest-negative
Second-negative
Middle-negative
Fourth-positive
Richest-positive
Long-term orientation
Positive
Indulgence
Positive
Control variables
Account ownership percentage among five SCO member states
Positive
GDP per capita of five SCO member states (USD million)
Positive
To test the hypotheses, regression was conducted to estimate the connection
between independent variables and the e-commerce purchasing behavior of respondents.
To see the deep down relationship between domestic and cultural factors and the e-
commerce behavior of customers in 5 SCO countries we conducted 3 types of regression
analyses, including control variables; demographic variables; national culture variables
separately and finally run all variables.
Table 9. Regression analysis of control variables
Source
SS
df
MS
Number of obs
F (5, 11060)
=
=
11,066
1031.38
Model
Residual
241.187672
1293.53355
2
11,063
120.593836
.116924301
Prob> F
R=squared
=
=
0.0000
0.1572
Total
1534.72122
11,065
.138700517
Adj R squared
Root MSE
=
=
0.1570
.34194
Purchased online
Coef.
Std. Err.
t
P > | t |
[95% Conf. Interval]
Has an account at
financial institution
.1753525
.0070598
24.84
0.000
.161514
.189191
GDP per capita
.0000257
7.86e-07
32.76
0.000
.0000242
.0000273
_CONS
-.1243408
.0071869
-17.30
0.000
-.1384284
-.1102533
Table 9 shows the control variables only of account ownership and GDP per capita
while Table 11 shows the demographic variables only and Table 12 shows the results of
all dimensions of national cultural factors. At last Table 12 combines not just individual
but also country-level variables with the control variables. Overall, the modulated R2
increased evidently from 0.1572 to 0.3365 from Table 9 to Table 12
Table 10. Regression analysis of demographic variables
Source
SS
df
MS
Number of obs
F (5, 11060)
=
=
11,042
451.53
Model
Residual
475.060579
1054.9924
11
11,030
43.1873253
. 096547543
Prob> F
R=squared
=
=
0.0000
0.3105
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Total
1530.0529
8
11,041
.138579203
Adj R squared
Root MSE
=
=
0.3098
.30927
Purchased online
Coef.
Std. Err.
t
P > | t |
[95% Conf. Interval]
Age
-.007239
.0001902
-38.05
0.000
-.0076119
-.0068661
Gender
.0170075
.0062368
-2.73
0.006
-.0292327
-.0047823
Secondary
.0139949
.0068112
2.05
0.040
.0006438
.0273461
Tertiary
.1109274
.010173
10.90
0.000
.0909865
.1308682
Employment
.030998
.0064828
4.78
0.000
.0182905
.0437055
Second 20
.0173501
.0094741
1.83
0.067
-.0012208
.0359211
Middle 20
.0587375
.0094624
6.21
0.000
.0401895
.0772856
Fourth 20
.0980209
.0094282
10.40
0.000
.0795399
.1165019
Richest 20
.1467252
.009541
15.38
0.000
.1280231
.1654272
Has an account at
finacial institution
.137837
.006641
20.76
0.000
.1248195
.1508545
GDP per capita
.0000351
7.93e-07
44.21
0.000
.0000335
.0000366
_CONS
.0543776
.0117373
4.63
0.000
.0313703
.0773849
As for individual demographic factors, Table 10 and Table 12 show that the
results support Hypotheses 1, 3, 4, and 5 that online purchasing is more widely spread
among younger buyers who have a higher education level, and are currently employed
with a higher salary. But Hypothesis 2 is not supported just because females are more
active when it comes to online purchasing than men. The result is not so surprising
because some other studies have already found these results before and there are both
theoretical and methodological reasons to support these results. Men are much more
active internet and technology users but in the last decade more and more women are
introduced to the internet and became active users of online platforms especially when it
comes to e-commerce platforms (Hernández, Jiménez, & Martín, 2011). In some
platforms, female customers’ quantities have already exceeded the male customers’
quantities (Stafford, Turan, & Raisinghani, 2004).
Table 11. Regression analysis of cultural variables
Source
SS
df
MS
Number of obs
F (5, 11060)
=
=
11,066
457.37
Model
Residual
262.958855
1271.76236
5
11.060
52.591771
. 114987555
Prob> F
R=squared
=
=
0.0000
0.1713
Total
1534.72122
11,065
. 138700517
Adj R squared
Root MSE
=
=
0.1710
.3391
Purchased online
Coef.
Std. Err.
t
P > | t |
[95% Conf. Interval]
Power distance index
0
(omitted)
Individualism
.0019896
.0005732
3.47
0.001
.0008661
.0031131
Masculinity
0
(omitted)
Uncertainty avoidance
-.0017931
.0002086
-8.59
0.000
-.0022021
-.0013842
Long-term orientation
0
(omitted)
Indulgence
-.0096963
.0010453
-9.28
0.000
-.0117453
-.0076473
Has an account
at fnancial institution
.2063323
.0076082
27.12
0.000
.1914188
.2212458
GDP per capita
.0000355
1.64e-06
21.60
0.000
.0000322
.0000387
_CONS
.0248185
.0139067
1.78
0.074
-.0024411
.0520782
In national culture factors, Table 11 and Table 12 support Hypotheses 7, 9 also
11 that countries with higher individualism index, low uncertainty avoidance index, and
low indulgence or more restraint have higher rates of e-commerce purchasing behavior in
the population (Zhao, 2011). On the other hand, Hypotheses 6, 8, and 10 did not match
the initial expectations. The results show that 3 of the 6 cultural dimensions including
power distance, masculinity, and long-term orientation does not show the relationship in
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1091
e-commerce purchasing behavior between SCO countries. These variables show omitted
results because they have collinearity with other variables, which means they cannot be
considered as independent variables in this study.
Table 12. Overall regression analysis
Source
SS
df
MS
Number of
obs
F (14, 11027)
=
=
11,042
399.40
Model
Residual
514.811458
1015.24152
14
11.027
37 .772247
.09 2068697
Prob> F
R=squared
=
=
0.0000
0.3365
Total
1530.05298
11,041
.138579203
Adj R-squared
Root MSE
=
=
0.3356
.30343
Purchased online
Coef.
Std. Err.
t
P > | t |
[95% Conf. Interval]
Age
.0069661
.0001882
-37.02
0.000
-.0073349
-.0065972
Gender
-.0254468
.0061482
-4.14
0.000
-.0374984
-.0133952
Secondary
.0720114
.007501
9.60
0.000
.0573081
.0867147
Tertiary
.198597
.011306
17.57
0.000
.1764353
.2207588
Employment
.0276907
.0063838
4.34
0.000
.0151773
.0402041
Second 20
.0227114
.009306
2.44
0.015
.0044699
.0409528
Middle 20
.0597245
.0092899
6.43
0.000
.0415147
.0779343
Fourth 20
.0927008
.0092592
10.01
0.000
.0745511
.1108504
Richest 20
.1317881
.0093907
14.03
0.000
.1133806
.1501956
Power distance index
0
(omitted)
Individualism
.0042886
.005162
8.31
0.000
.0032767
.0053004
Masculinity
0
(omitted)
Uncertainty
avoidance
-.0038616
.0002061
-18.74
0.000
-.0042656
-.0034577
Long-term
orientation
0
(omitted)
Indulgence
-.013404
.0009443
-14.19
0.000
-.015255
-.011553
Has an account at
financial institution
.1466091
.0071126
20.61
0.000
.1326672
.160551
GDP per capita
.0000495
1.52e-06
32.62
0.000
.000466
.0000525
_CONS
.2731722
.0159773
17.10
0.000
.2418538
.3044905
Previous studies showed that the power distance index does show the level of
trust in society, the final result on online purchasing behavior is not significant, maybe
the interaction and relationship between the sellers and the buyers in e-commerce
platforms virtual (Kim, Urunov, & Kim, 2016). As a result, power differences between
these 2 parties are more invisible in the online relationships despite the power distance of
the society. For masculinity, the researchers assume that just because women are more
active in e-commerce purchasing than men it is distinct that e-commerce is more female
abundant, also 4 of 5 SCO countries in this study have high more than 50 as a masculinity
index therefore the tests did not show any results for this matter. Also, all of 5 SCO
countries in this study are relatively long-term oriented, all have more than 50 as a long
term oriented index in Hofstede study, therefore the results did not show any significance,
and in future we would like to see more difference between those countries that are more
short-term oriented comparing to these 5 SCO countries. At last, control variables, GDP
per capita, and account ownership in financial institutions are significantly and positively
related to online shopping adoption.
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1092 http://eduvest.greenvest.co.id
Table 13. Summary of results
Hypothesis
Remarks
H1
Online purchase is prevalent among young consumers of SCO
member states.
Supported
H2
Online purchase is prevalent among male consumers of SCO
member states.
Not supported
H3
Online purchase is prevalent among higher educated
consumers of SCO member states.
Supported
H4
Online purchase is prevalent among employed consumers of
SCO member states.
Supported
H5
Online purchase is associated with higher income in SCO
member states.
Supported
H6
Online purchase is prevalent among SCO member states with
a lower PDI.
Not supported
H7
Online purchase is prevalent among SCO member states with
higher IDV.
Supported
H8
Online purchase is prevalent among SCO member states with
lower MAS.
Not supported
H9
Online purchase is prevalent among SCO member states with
lower UAI.
Supported
H10
Online purchase is prevalent among long-term-oriented SCO
member states.
Not supported
H11
Online purchase is prevalent among restraint SCO member
states.
Supported
CONCLUSION
As one of the most important economic region in Eurasia, SCO is devoted to
developing e-commerce in the region. But SCO member states vary in terms of e-
commerce experience due to dissimilar economic situations and cultural differences. Do
individual and cultural factors affect e-commerce in these countries and who are the main
customers of online purchasing platforms in SCO countries? In this study, we attempted
to answer this question by examining the factors that are affecting B2C e-commerce
adoption in the SCO region. The main objective of this study is to integrate the
demographic characteristics with Hofstede’s cultural dimensions to determine the factors
of e-commerce adoption among consumers in SCO member states.
This study derived data from multiple different sources, for individual
demographic characteristics including age, gender, education, employment, and income
we used The World Bank Global FINDEX as a source and in total this study analyzed
11227 face-to-face interviews with SCO populations from China, India, Kazakhstan,
Pakistan and Russia. For demographic characteristics including power distance,
individualism, masculinity, uncertainty avoidance, long-term orientation, and indulgence
we used data from Hofstede’s site (www.hofstede-insights.com). Therefore, the results of
this study show the importance of not just academic but also practical purposes.
First, the definition of e-commerce costumers in SCO is a complex combination
in terms of demographics. E-commerce platforms are mostly used by those who are
younger females with higher education and also in the workforce, who have more income
than the others. This study shows that although SCO member states have signed the
“Statement by the SCO Heads of State Council on Cooperation in the Digital Economy”
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1093
assured to increase further adoption in the e-commerce field, the main part of the current
e-commerce users are young individuals with higher education and incomes. E-commerce
is widely used only among those who have the possibility and accessibility to the
technology, and more importantly, who have paying abilities. Also, this study makes a
remark that links the 2 different aspects and shows that not only individual characteristics
are important to study e-commerce but also national culture factors. Therefore, we
suggest the governments to design and make more policies to encourage online shoppers
not just from individuals’ perspectives but also from the national level by developing
more favorable socio-values such as trust.
Overall, government officials in SCO countries need to extend the e-commerce
customers varieties including especially those who have less income with low education
in the population. There is a significant difference between e-commerce users and non-
users that the officials should pay more attention to. Also on the country level, e-
commerce development in SCO country is definitely connected to cultural values.
National culture can’t be changed in a short time; the government should seek to increase
more favorable values in the whole society.
Although this study has certain contributions, there are some limitations. First,
this study only collected data from 5 SCO countries; therefore there is a gap for future
research including the other 3 SCO countries’ data. Also, there is a room for more
country-level controls. Moreover this research did not cover the physiological factors of
the purchasing behaviors of the customers; therefore it can be extended to more
behavioral studies.
REFERENCES
Afizah Hashim, Erlane K Ghani, Jamaliah Said (2009) Does consumers' demographic
profile influence online shopping? : An examination using Fishbein’s theory.
Canadian Social Science. Vol 5, No 6.
Ahasanul Haque, Javad Sadeghzadeh, Ali Khatibi. (2011). Identifying potentiality online
sales in Malaysia: a study on customer relationships online shopping. Journal of
applied business research 22(4)(4)
Ali Yayla, Qing Hu. (2007). User acceptance of e-commerce technology: a meta-analytic
comparison of competing models. European conference on information systems.
Alyoubi, Adel A. (2015). E-commerce in developing countries and how to develop the
during the introduction of modern systems. International conference on
communication, management and information technology.
Ayob, Abu H. (2021). E-commerce adoption in ASEAN: who and where? Future
Business Journal, 7(1), 1–11.
Beneke, J., Scheffer, M., & Du, W. (2010). Beyond price - An exploration into the factors
that drive young adults to purchase online. International Journal of Marketing
Studies, 2, 212–222.
Bradford Mills F, Whitacre Brian E. (2003). Understanding the non-metropolitan-
metropolitan digital divide. Growth change. 34(2):219-43
Dadabaev T. (2004). Post-soviet realities of society in Uzbekistan. Central Asian survey,
23(2), 141-146
Delia Sorana Varvara Mityko. (2012). Consumers’ education level impact on the
perception of the search experience credence products-empirical evidence. Journal
of internet and e- business studies. Vol. 2012, Article ID 617588, 8.
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1094 http://eduvest.greenvest.co.id
Garbarino E, Strahilevitz M. (2004). Gender differences in the perceived risk of buying
online and the effects of receiving a site recommendation. Journal of Business
Research 57(7):768-775
Gentry, James W. & Mittelstaedt, Robert A. (2017). The rapidly aging world:
implications for marketing. Global business review
Gichang Cho, Stephanie Koh Jialin. (2009). Influence of gender on internet
commerce: an explorative study in Singapore. Journal of internet commerce.
Grazzini, L., Acuti, D., Mazzoli, V., Petruzzellis, L., & Korschun, D. (2020). Standing for
politics: What consequences for brands? Italian Journal of Marketing.
https://doi.org/10.1007/
Hallikainen Heli, Tommi Laukkanen. (2018). National culture and consumer trust in e-
commerce. International journal of information management 38(2018)97-106
Hernández, Blanca, Jiménez, Julio, & Martín, M. José. (2011). Age, gender and income:
do they really moderate online shopping behaviour? Online Information Review.
Hofstede, G. and Minkov, M. (2010). Cultures and Organizations: Software of the Mind.
New York: McGraw-Hill
Huseynov, Farid, & Yıldırım, Sevgi Özkan. (2016). Behavioral Issues in B2C E-
commerce: The-state-of-the-art. Information Development, 32(5), 1343–1358.
Hwang Y, Lee KC. (2012). Investigating the moderating role of uncertainty avoidance
cultural values on multidimensional online trust. Information management 49(3-
4):171-176
Kim, Eungkyu, Urunov, Roman, & Kim, Hyungjoon. (2016). The effects of national
culture values on consumer acceptance of e-commerce: Online shoppers in Russia.
Procedia Computer Science, 91, 966–970.
Kimery, Kathryn M. (2011). Cultural influences on the adoption of electronic commerce:
initial results from Japan and the United States. International Business & Economics
Research Journal.
Laruelle, Marlene, & Peyrouse, Sebastien. (2015). Globalizing Central Asia: Geopolitics
and the challenges of economic development. New York: Routledge.
Lissitsa S, Kol O. (2016). Generation X vs. Generation Y-A decade of online shopping.
Journal of Retail Consumer Service 31:304-312
McCloskey, Donna W. & Leppel, Karen. (2010). The impact of age on electronic
commerce participation: an exploratory model. Journal of electronic commerce in
organizations, Volume 8, issue 1, pp 41-60
Najimudinova, Seyil. (2013). Organisational culture dimensions of the Kyrgyz industrial
companies. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 22(1), 427–
444.
Nanehkaran, Yaser Ahangari. (2013). An introduction to electronic commerce.
International Journal of science and technology research.
OECD. (2019). Education at a Glance 2016 OECD Indicators. OECD Publishing,
http://dx. doi. org/10.1787/eag-2012-en, accessed.
Pratesi Francesca, Lala Hu, Riccardo Rialti, Lamberto Zollo, Monica Faraoni. (2021)
Cultural dimensions in online purchase behavior: Evidence from a cross-cultural
study. Italian journal of marketing.
Sugarmaa Purevkhuu and Javkhlan Munkhbold
Demographic and Cultural Factors Influencing the Adoption of B2C E-Commerce in SCO
Region 1095
Punj G. (2011). Income effects on the relative importance of two online purchase goals:
saving time versus saving money? Elsevier, DOI: 10.1016/j.jbusres.2011.03.003
Rinne T., Steel D., Fairweather J. (2013) The role of Hofstede’s individualism in national-
level creativity. Creativity research journal, Vol.25, Issue-1
Seyil Najimudinova. (2013). Organizational culture dimensions of the Kyrgyz industrial
companies. Ç.Ü. Sosyal Bilimler Enstitüsü Dergisi, Cilt 22, Sayı1, 2013, Sayfa 427-
444
Slyke, C.V., Bélanger, F., Johnson, R.D., & Hightower R. (2010). Gender-Based
Differences in Consumer E-Commerce Adoption. Communications of the
Association for Information Systems, 26,
Stafford, Thomas F., Turan, Aykut, & Raisinghani, Mahesh S. (2004). International and
cross-cultural influences on online shopping behavior. Journal of Global
Information Technology Management, 7(2), 70–87.
Viera Jorge, Rui Frade, Raquel Ascenso, Ines Prates & Filipa Martinho. (2020).
Generation Z and Key-Factors on e-commerce: A study on the Portuguese tourism
sector. Administrative Science.
Villarejo-Ramos, Peral-Peral & Arenas-Gaitan. (2014). From digital divide to psycho-
digital divide: elders and online social networks. Comunicar.
World Bank. (2020). Discussion note: Embedding Digital Finance in e-Commerce
Platforms during the COVID-19 Pandemic.
Wu, W.Y, Quyen P., Rivas, A. (2016) How e-services capes affect customer online
shopping intention: The moderating effects of gender and online purchasing
experience. Information Systems and E-Business Management 5(3), 689–715.
Yavuz Yasar. (2014). Master’s thesis: Indulgence and restraint in Turkey.
Zhao, Fang. (2011). Impact of national culture on e‐government development: a global
study. Internet Research.