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DA NANG UNIVERSITY OF ECONOMICS
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The Trend of Purchasing Online of People in Da Nang
Subject: STATISTICS FOR BUSINESS AND ECONOMICS
Instructor: Mr. Nguyen Van Cang
Class: 39K07-CLC
1. Le Thi To Nhu2. Do Thu Trang3. Dang Thi Hoa4. Nguyen Thi My Linh
2014-2015
ContentsI. INTRODUCTION.................................................................................................................................3
A. Background:....................................................................................................................................3
B. Target..............................................................................................................................................4
C. Subject.............................................................................................................................................4
D. Research’s Method..........................................................................................................................4
II. CONTENT............................................................................................................................................5
A. Survey.............................................................................................................................................5
B. The result of Survey:.......................................................................................................................6
C. Variables summary..........................................................................................................................7
D. Data processing...............................................................................................................................8
1. SEARCH......................................................................................................................................8
2. TIMES.......................................................................................................................................10
3. ITEMS.......................................................................................................................................11
4. TRUST.......................................................................................................................................12
5. PAY...........................................................................................................................................14
6. FRIEND.....................................................................................................................................15
7. DISCOUNT...............................................................................................................................15
8. DIST..........................................................................................................................................16
9. TRANS......................................................................................................................................17
E. Hypothesis Testing........................................................................................................................18
1. Mean of times buying online.....................................................................................................18
2. Age & Times..............................................................................................................................18
F. Simple Regression Model.................................................................................................................19
1. Time & Trust.............................................................................................................................19
2. Multiple Regression Model of “Times” and the most important variables:..............................21
III. CONCLUSION................................................................................................................................22
A. Main characteristics of the objective.............................................................................................22
B. Advantages and Disadvantages during the research.....................................................................22
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I. INTRODUCTION
A. Background:According to the development in economy, standard of living of Vietnamese people is also
increasing. The more rising demand shopping of Vietnamese people is, methods of marketing,
selling, purchasing do witness significant change, too. Typically, in recent years, beside
traditional selling, selling online has existed and step by step has been outweighing the former.
This method of selling is developing rapidly, especially in urban areas, among classes of
students, employees and housewives… This is the matter we would like to discuss in our paper:
the trend of purchasing online of Vietnamese people, and in detail people in Da Nang.
Some facts of online-selling in Vietnam
In essence, online-selling is one part of e-commerce. In fact, e-commerce is applied the most
successfully in the area of selling onlineTheir business is selling goods such as clothes, shoes,
accessories, cosmetics and electronics… Some famous websites mentioned here are
lamchame.com, raovat.vn, rongbay.vn…..
Whenever you carry out a survey on students in Da Nang, we can conclude that the trend of
online-purchasing is becoming more and more popular.
As a result, what is the exact explanation for the strong development of trend of online-
purchasing?
First of all, the advantages of this method of purchasing are undeniable.
- Time is precious, which is taken advantage by online-selling. It takes only few minutes to
surf the web, choose whatever you want and then complete your purchase with only one click
while the traditional ways require you to go to brick and mortar stores, which costs you time and
energy.
- Another big advantage of purchasing online is price. Online goods have lower price
because the online owners don’t have to rent infrastructure and cover as large amount of money
for advertising as owners of brick and mortar stores. Furthermore, consumers can easily compare
prices of different suppliers and decide which to buy with the most reasonable price.
- Finally, online-purchasing enables buyers to get access with a more variable range of
goods instead of going to shopping mall. After considering prices, designs and models of goods,
buyers can have a wiser decision.
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However, anything has its two sides and the disadvantages of online-purchasing are
unavoidable.
- The biggest disadvantage is the quality of goods. When joining this method of shopping,
consumers can not directly see or touch the goods before making their decisions. The quality of
goods is still unknown. Online-selling is now in an alarming situation which includes stealing
information, financial fraud, advertising harassment, selling counterfeit goods.
- Another big problem is online payment. Security is another challenge to online payment.
Facing with these difficulties, E-commerce has been growing fast and has larger and larger
number of users. To get know more about this matter, we would like to analyze the trend of
purchasing online of people in Da Nang, therefore can have a deeper understanding.
B. Target- Finding what factors mainly affect the behavior of buying online of Da Nang people
- Practice what we learn about statistic subject
C. Subject- Subject: resident in Da Nang
D. Research’s Method- Data source
+ Primary source: we collected information from people in Da Nang
+ Secondary source: we collected information from the Internet, reports in magazines,
newspapers…
- Form: surveys in form of multiple-choice questions and filling information
- Quantity: 40, In which 36 are applicable
After datas are all collected, we generalize and classify datas on base of the knowledge that we
have learned. Soft-wares used is SPSS to complete this paper
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II. CONTENT
A. SurveyVariables are divided in to 2 subgroups that include variable impacting on this issue we think, as
followed:
Internal factors:
AGE: (Unit: year old)
SEX: Sex = Male as 1 and Sex = Female as 0
INCOME:. (Unit: million VND)
SEARCH (Searching information online): (Unit: Time/a week)
JOB: JOB=0 is student, JOB=1 is worker, JOB=2 is unemployment.
TRUST: This variable is measured following the incremental range from 1 to 10. The more
they believe in the quality of goods sold online, the more they shop.
TIMES: How many times do you buy online?
Society conditions:
FRIEND: Whether friends or relative usually introduce about goods sold online or not.
FRIEND = 1 as YES, FRIEND = 0 as NO
DIST (Distance): How far is shops-online?(Unit: km)
PAY (Payment): Prepayment or deferred payment can have different effects on shopping
online. PAY = 1 as Prepayment, Pay = 0 as Deferred payment
DISC: It means whether the cost of shopping online is cheaper or more expensive than the
cost of shopping directly. DISC =1 is cheaper. DISC = 0 is more expensive.
TRANS (Transportation): How fast is the transportation
Other Factors:
Items: which goods do the customers usually buy most.
B. The result of Survey:Total responses Valid responses Invalid responses
5
40 36 4
(4 responses are invalid because questionnaires are not completed)
No. SEX AGE JOB INC Items TIMES SEARCH PAY FRIEND DISC TRANS DIST TRUST
1 1 24 1 3.8 Cloth 10 2 0 0 0 2 2 8
2 1 26 1 4.3 Cloth 12 6 1 1 1 3 5 9
3 1 30 1 4.0 Cloth 10 7 0 1 1 3 10 8
4 0 19 0 0.5 Cloth 2 20 0 1 1 1 5 3
5 0 35 1 7.8 Household 8 1 0 0 0 3 500 9
6 1 20 0 1 Book 1 10 0 0 1 1 3 0
7 0 37 1 3.2 Cloth 2 3 0 0 1 3 20 8
8 1 25 2 0.7 Equipment 6 7 1 1 0 14 5 9
9 0 34 1 5.6 Book 22 6 0 1 0 14 5 10
10 0 40 1 4.5 Food 2 7 1 1 1 2 10 2
11 0 20 0 2 Accessory 2 7 0 0 0 7 2 3
12 1 26 1 6.6 comestic 18 5 1 1 1 5 3 8
13 0 21 0 1.5 Cloth 1 1 0 0 1 2 600 1
14 0 30 2 2.0 Book 1 10 0 0 1 3 8 0
15 0 44 1 8.8 Food 12 2 0 0 1 3 5 8
16 0 21 1 1.0 Comestic 1 5 0 0 0 2 8 1
17 1 33 1 7.0 Cloth 20 1 0 0 1 8 5 9
18 1 20 0 0.5 Cloth 2 21 0 0 1 3 10 2
19 1 25 1 4.5 Equipment 1 1 1 0 0 5 600 1
20 0 42 1 6.2 Household 21 7 0 0 1 6 10 10
21 1 33 1 3.3 Comestic 1 2 0 0 1 3 8 5
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22 0 28 1 4.0 Tour 1 1 1 0 0 4 600 5
23 0 19 0 1.0 Accessory 1 7 0 1 1 2 20 8
24 0 30 1 5.0 Equipment 2 2 0 0 1 3 30 9
25 0 20 0 1.5 Cloth 1 2 1 1 1 2 10 2
26 0 28 1 4.7 Book 4 1 1 0 0 2 16 9
27 0 20 0 0.8 Cloth 4 7 0 0 1 3 10 10
28 1 32 1 5.6 Cloth 3 1 0 0 1 7 40 2
29 1 26 1 6.2 Equipment 10 3 0 0 1 4 45 10
30 1 27 1 2.0 Cloth 5 7 0 0 0 5 40 7
31 1 21 0 1.5 Book 3 5 0 0 1 1 35 2
32 0 36 1 2.8 Household 4 2 1 0 1 7 30 8
33 0 29 1 5.3 Equipment 8 1 0 0 1 7 1 10
34 0 23 1 2.5 Cloth 2 3 0 0 1 14 1 2
35 0 23 1 2.0 Cloth 1 3 0 0 1 30 1 1
36 1 21 0 1.0 Cloth 2 7 1 0 1 1 10 4
C. Variables summaryVariable Quantitative/
Qualitative
AGE Quantitative
SEX Qualitative
INCOME Quantitative
SEARCH Quantitative
JOB Qualitative
TRUST Qualitative
FRIEND Qualitative
DIST Quantitative
PAY Qualitative
DISC Qualitative
TRANS Quantitative
TIMES Qualitative
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D.
E. Data processing
GIOI TINH
Frequency Percent Valid Percent Cumulative Percent
Valid nu 21 58.3 58.3 58.3
nam 15 41.7 41.7 100.0
Total 36 100.0 100.0
TUỔI
N Minimum Maximum Mean Std. Deviation
tuoi 36 19 44 27.44 6.905Valid N
(listwise)36
Cong viec
Frequency PercentValid
PercentCumulative
Percent
Valid student 10 27.8 27.8 27.8
worker 24 66.7 66.7 94.4
unemployment
2 5.6 5.6 100.0
Total 36 100.0 100.0
Thu nhap
N Minimum Maximum Mean
thu nhap 36 0 9 3.46Valid N (listwise) 36
1. SEARCHThe variable of “Search” tells how many time customer searches for goods online every week.
Classes Frequency Relative frequency(%)
1-5 21 58.3
6-10 13 36.2
>10 2 5.5
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From the graph and table above, we can see that most people search for information of goods
sold via Internet for less than 10 times a week. (94.5% ) Only 2 of 36 observations spend more
than 20 times a week for searching.The more people search for information about the goods, the
more people tend to shopping. That means the people who spend much time on searching for the
goods are likely to buy more.
Arithmetic
meanRange Variance
Standard
DeviationCoefficient of variation
5.08 20 21.907 4.681 92.15%
Formulas:
x=x1+x2+…+xn
n=∑ x i
n=5.08
R = the largest value – the smallest value = 21 – 1 = 20
Var = ∑i
n
(x i− x)2
n=21.907
SD = √Var=4.681
CV = SDx
=4.6815.08
×100 %=92.15 %
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From these results, we can see that:
The average time the respondents searched for information online last year was 5.08 (times). The
numerical difference between the smallest and largest values of times searching online is 20
(times) and the standard deviation of variable “times” equals to 4.681. We can see they have a
very large difference among customers about the number of times searching online. We can see
that the coefficient of variation is fairly high, about 92.15%. It means that Da Nang customers
have far different tendency of searching information online.
2. TIMESClasses Frequency Relative frequency(%)
1-5 24 66.68
6-10 6 16.67
11-15 2 5.55
16-20 2 5.55
>20 2 5.55
10
Arithmetic mean Range Variance
Standard
Deviation
Coefficient of
variation
5.72 21 38.721 6.223 108.7%
x = x1+x2+…+xn
n=∑ xi
n=5.72
R = the largest value – the smallest value = 21
Var = ∑i
n
(x i− x)2
n=38.721
SD = √Var=6.223
CV = SDx
x 100 %=108.7 %
The average times shopping online last year is 5.72 (times). The numerical difference between
the smallest and largest values of times shopping online is 21 (times) and the standard deviation
of variable “times” equals to 6.223.We can see they have a very large difference among
customers about the number of times shopping online. We can see that the coefficient of
variation is too high which equals to 108.7%.It means that Da Nang customers have far different
decisions on shopping online which is expressed through the number of times shopping online.
3. ITEMS
Items - mat hang mua sam
Frequency Percent Valid Percent Cumulative Percent
Accessory 2 5.6 5.6 5.6
Book 5 13.9 13.9 19.4
Cloth 15 41.7 41.7 61.1
comestic 1 2.8 2.8 63.9
Comestic 2 5.6 5.6 69.4
Equipment 5 13.9 13.9 83.3
Food 2 5.6 5.6 88.9
Household 3 8.3 8.3 97.2
Tour 1 2.8 2.8 100.0
Total 36 100.0 100.0
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From the pie-chart above, 41.67% of 36 people choose clothes as their favorite online-bought
goods, the rest buy another items. That means, to some extent, clothes and related stuff are more
attractive to the customers. In fact, it’s really convenient to buy clothes online: time-saving, easy
to find, feedback and see the plot… Instead of spending much time going around streets to find
something suit you, now you only need a click: all styles, all sizes are ready to serve. See that,
there is one person choosing tour. Nowaday, selling tour-online is developing and I think in the
future, this item will become more popular.
4. TRUSTThis variable is measured following the incremental range from 0 to 10. 0 means totally distrust,
10 means totally trust in the quality of online goods.
Classes Frequency Relative frequency(%)
0-3 14 38.9
4-7 4 11.1
8-10 18 50.0
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As we can see, most people rate their trust in quality of online goods above the median. The
highest rate is 19.4% at 8. Those interpretations tell us people have quite good attitude towards
the quality of online goods. The attitude comes from their own experience, or from what they
heard of. When buyers have good experience, they will have good attitude, and then they trust
you more. As the result, they buy more
Arithmetic
meanRange Variance
Standard
DeviationCoefficient of variation
5.64 10 12.866 3.58 63.59%
x =x1+x2+…+xn
n=∑ xi
n=5.64
R = the largest value – the smallest value = 10 – 0 = 10
Var = ∑i
n
(x i− x)2
n=12.866
SD = √Var=3.58
CV = SDx
=63.59 %
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Prepayment 27.8%
72.2%
From these results, we can see that:
The average trust rate of respondents shopping online last year is 5.64. Most respondents fairly
trust on online shopping. The numerical difference between the smallest and largest values of
trust degree is 10 and the standard deviation of variable “trust” equals to 3.58. We can see they
have a quite large difference among customers about trust rate on online shopping.
5. PAYThis variable tells us which type of payment customers prefer: prepayment or deferred payment.
Frequency Percent Valid Percent Cumulative Percent
tra sau 26 72.2 72.2 72.2tra truoc 10 27.8 27.8 100.0
Total 36 100.0 100.0
Methods of payment
Deferred payment; 75%
Prepayment; 25%
From the pie chart, we can conclude that deferred payment is preferred by most customers. The
number of people who prefer deferred payment is approciate three times as many as prepayment.
This fact is so understandable. Almost people feel afraid of the risk they may face when making
prepayment.
muc do tin tuong0-3 4-7 8-10
hinh thuc tra tien
tra sau 11 2 13 26
tra truoc
3 2 5 10
Total 14 4 18 36
We can see that if customer’s trust increase, they’d prepayment.
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Yes 25%
no 75%
6. FRIENDThe variable “Friend” tells whether friends or relatives of customer tell them about online goods.
Encode 1 as yes, 0 as no
ban be hoac nguoi than gioi thieu
Frequency Percent Valid Percent Cumulative Percent
khong 27 75.0 75.0 75.0
co 9 25.0 25.0 100.0
Total 36 100.0 100.0
Friends usually tell customer about online goods
Not usually; 83%
Usually; 17%
From the pie chart, we see that friends do not usually tell buyers about online goods. Only 25%
say yes to the question.
This fact is not good for the sellers. Customers always are the best ones for marketing for the
goods. A friend tells another about the wonderful goods she bought online, and how fast the
delivery is, and how nice the after-sales service the seller provides.It’s what all the sellers want.
7. DISCOUNTThis variable tells us the price of online good is cheaper or more expensive than the goods sold
at stores. Encode 1 as cheaper, 0 as not cheaper
mua re hoac dat hon
Frequency Percent Valid Percent Cumulative Percent
dat 10 27.8 27.8 27.8
re 26 72.2 72.2 100.0
Total 36 100.0 100.0
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Expensive 27.8%
72.2%
Price of online goods in comparison with offline goods
Cheaper; 82%
Cheaper; 18%
From the pie chart, we can see that most of the online goods are sold at lower price than at the
store. This is an advantage of buying online. Lower price is reasonable because online shops do
not have to pay for the location; they hire fewer staffs and most retail stores of small size don’t
have to pay tax. As operating cost is much lower, the price of goods and services they provide
must be lower.
8. DISTANCEThe variable “Distance” tells the distance between customer’s house and the store where they
buy the goods.
DISTANCE
MiN Max Mean
khoang cach
1.00 600 75.361
We can see from the histogram that the
most usual distance between store and
customer’s house is less than 100 km.
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9. TRANSThis variable tells us the average time buyers receive their goods after they make online order.
Classes(day) Frequency Relative frequency
1-6 27 75%
7-14 8 22.2%
>14 1 2.8
From the table and histogram, we can see that the most common delivery time is between 3 and
5 days. The shops may be in the same city or in the city nearby or the goods are shipped by air.
Some people says they wait more than 10 days for the goods to be delivered, in this case, these
goods might be shipped by road from another city or another country.
The length of delivery time is another factor affecting the decision of buyers to buy online or
not. If the time is too long, they might think of another way to buy the good.
Arithmetic
meanRange Variance
Standard
DeviationCoefficient of variation
5.14 29 30.352 5.509 107.17%
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x=x1+x2+…+xn
n=∑ x i
n=5.14
R = the largest value – the smallest value = 30 - 1 = 29
Var = ∑i
n
(x i− x)2
n=30.352
SD = √Var=5.509
CV = SDx
=5.5095.14
× 100 %=107.17 %
From these results, we can see that:
The average delivery time is 5.14 (days). The numerical difference between the smallest and
largest values of delivery time is 29 (days) and the standard deviation of variable
“transportation” equals to 5.509. We can see they have a very large difference among customers
about the delivery time of goods. There are many single extreme values that make the average
value is not an exact representation of all values. Thus it is necessary to consider about the
relative term or the coefficient of variation. We can see that it is fairly high, about 107.17%
F. Hypothesis Testing
1. Mean of times buying onlineH0 : μ=5
H1: μ>5
One-Sample Test
Test Value = 5
t dfSig. (2-tailed)
Mean Difference
95% Confidence Interval of the
Difference
Lower Upper
ban mua online bao nhieu lan trong nam qua
.696 35 .491 .722 -1.38 2.83
Sig. (2-tailed) < 0.05 : Reject H0, accept H1. It’s mean consumers buy more than 5 goods last year.
2. Age & TimesH0 : Age and times don’t have Contact correlationH1 : Age and times have Contact correlation
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Correlations
tuoi
ban mua online bao nhieu lan trong nam
qua
Spearman's rho
tuoi Correlation Coefficient
1.000 .460**
Sig. (2-tailed) . .005
N 36 36
ban mua online bao nhieu lan trong nam qua
Correlation Coefficient
.460** 1.000
Sig. (2-tailed) .005 .
N 36 36
**. Correlation is significant at the 0.01 level (2-tailed).
Sig. (2-tailed) < 0.05 : Reject H0, accept H1. It’s mean Age and times have Contact correlation
G. Simple Regression Model
1. Time & TrustTime: y
Trust: x
Population regression model y = β 0+β1 xi + ε
In which,
y: The number of time buying online
x: Whether the trust in buying online
Coefficients
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
muc do tin tuong 1.127 .226 .650 4.981 .000
(Constant) -.631 1.506 -.419 .678
Y = -0.636+ 1.127 X
Model Summary
R R Square
Adjusted R
Square
Std. Error of
the Estimate
.650 .422 .405 4.800
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ANOVA
Sum of Squares df Mean Square F Sig.
Regression 571.708 1 571.708 24.809 .000
Residual 783.514 34 23.045
Total 1355.222 35
The independent variable is muc do tin tuong.
In conclusion,
We have b1 = 1.127=> the average times of buying goods online increase by 1.127 (times) when
consumers trust increse 1 unit buying online.
We have b0 = -0.636=> when consumers don’t believe in buying online, they won’t buy
anything.
We have R2 = 0.422 => It means that the variable “Trust” determine about 42% of the value of
times. In other words, the belief of customers determines about 42% of the number of times the
customers shop online. This number is larger, so it proves it plays an important role in the
behavior of online shopping.20
2. Multiple Regression Model of “Times” and the most important variables:We consider:
Time: y Friend: x1
Trust: x2 Discount: x3
Multiple Regression Model
y¿̂
¿ = b0 + b1x1 + b2x2 + b3x3
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t Sig.B Std. Error Beta
1 (Constant) -1.182 2.103 -.562 .578
ban be hoac nguoi than gioi thieu
1.971 1.900 .139 1.037 .307
muc do tin tuong 1.095 .233 .631 4.696 .000
mua re hoac dat hon
.329 1.825 .024 .181 .858
a. Dependent Variable: ban mua online bao nhieu lan trong nam qua
y¿̂
¿ = -1.182+ 1.971x1 + 1.095x2 + 0.329x3
We have:
+b1 = 1.971 means that the number of times buying online will increase on average by
1.971times when the respondents get the suggestions from friends or relatives.
+ b2= 1.095means that the number of times buying online will increase on average by 1.095
when trust on buying online increase 1 unit
+ b3= 0.329 mean that the average times of buying goods online increase by 0.329 times when
the respondents think the goods are cheaper.
Model Summary
Model RR
SquareAdjusted R
SquareStd. Error of the
Estimate
1 .665a .442 .390
R2 = 0.442 => It means that these three variables determine about 44.2% of the value of times.
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III. CONCLUSION
A. Main characteristics of the objectiveThrough our survey and analysis, we can see that there are a number of factors influencing on
the trend of shopping online, including both objective and subjective factors.
Even though we have tried our best, there may still be mistakes during the research due to the
range of time and knowledge. However, through this research, we have learned a lot about
carrying out survey and analyze data collected so that we could give out useful information for
the ones who have been and will be doing online business.
B. Advantages and Disadvantages during the research Disadvantages:
- Finding suitable independent variables that make it easy to collect data.
- Group members cannot directly communicate with one another to discuss and complete the
assignment.
Advantages:
- We receive much help from the instructor as well as our friends during the research.
------THANK YOU------
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