Trend of domestic and international market during period 2003-2006

Trend of domestic and international market during period 2003-2006

I TASK 1

1.1 Introduction

Everpia Vietnam is a company from Korea which invested in Vietnam since abouttwo decades ago The company specializes in bedding furnishings With the famousbrand name Everon, Everpia has produced a lot of products which is served for the sleep

of Vietnamese Some of Everpia products are blankets, mattresses, quilts, sheets, pillows,etc, … Everpia Vietnam now has three factories in Dong Nai, Gia Lam (Hanoi).With theambition of expanding the market in Vietnam, Everpia wants to build one moremanufacture building in the North of Vietnam to meet the need of customers Beforedoing other necessary tasks, the first stage of this project is to carry out the suitablelocation for new branch Our team is delegated to implement this study and we must findthe most suitable one depend on the following criteria:

 The location we choose need to have a number of small and medium Vietnameseenterprises (SMEs) specializing in textiles There will be more potentialsubcontractors of Everia

 The more geographically concentrated textiles SMEs, the more likely this areawill be selected Everia likes to choose the location where have more focused ontextiles The advantage of that is short distance between Everia and subcontractors

to reduce costs, increase efficiency

 Everia likes province with better production capacity and behavior of textileSMEs towards their partners

It is difficult to find the province that satisfies all above criteria, so EverpiaVietnam decides to select three provinces which satisfy the first two criteria to study.They are: Hanoi, Hai Duong, and Nam Dinh From the study in three provinces, we willchoose the best one for Everpia’s new branch

1.2 Methodology

1.1.2 Data collection plan

To find the most suitable place for Everpia, our team will carry out the plan forcollection of necessary data (primary data and secondary data)

http://www.worldatlas.com In GSO, our team also can find the information on theactivities of firm and its size

In secondary data, we get information from reputed institution so the correctness ofthe data we collect can be ensured However, the data from these organizations can notcover all the information that Everpia needs

b Primary data:

The primary data comes when we carry out our survey We will collect data ourselvesbasing on what we need to know about the potential of 3 provinces that we will doresearch The primary data can be collected by many ways, such as interview, postal orface-to-face questionnaire Although with direct interview, sample selection is moreaccurate and we can understand the behavior of interviewees, we should not choose thismethod because of its high cost and long time when we carry out interview all firms Inaddition, people can do not want to talk with stranger and answer may be refused.Therefore, we should choose questionnaires in this case However, because of thedifference between different firms’ location, we will choose face-to-face questionnairefor some around firms and with distant ones, we will use postal questionnaires This willhelp us save time and money when carry out the survey

An important point is that the questionnaires must relate to the objective of ourresearch It is to find out firm’s production capacity and their behavior towards clients Inaddition, we also need to know the information about their fixed capital, the number ofemployees, employees’ education and skills, the education and experience ofmanagement and credibility in debts, liquidity, and delivery on time

Another advantage of this method is that the information is collected by ourselves so

we can ensure the quality of the survey as well as the accuracy of the questions we want

to ask However, we can not cover all the range that we want to do research because itspends a long time as well as costs a lot of money The solution for this is the samplingmethod which will be presented in the next stage.

1.2.2 Sampling method

Because of the high cost and time-consuming when we collect data from all firms, weneed to use sampling method before collecting primary data A sample also allowsinvestigating more detail information In three chosen provinces, assuming that there are

400 firms of textile, we will take a sample of 100 firms to do the study (equally to 25% oftotal firms)

There are many methods of sampling such as random, systematic, stratified, stage, and so on Each method has itself advantage as well as disadvantage However, inthis case, our team decides to choose multistage sampling Although this method hassome disadvantages (such as only a small number of firms are selected or the chosenfirms may be not reflect the whole firms in areas when we use random method in anystage); it helps us to cut down number of firms and reduce cost It can clearly see that if

multi-we collect data from all firms in areas, the money and time multi-we must spend is very high.Beside that, if we choose other method, it is easy to make error because of large number

of firms in the population Therefore, multistage is the most suitable one in this case Allthe steps of sampling will be detailed in the following part

To get data including detail of all firms such as names, addresses, telephone, businessactivities, etc … from 3 selected provinces; we enter the Agency for SME development(ASMED) of MPI and the Vietnam Chamber of Commerce and Industry (VCCI) Fromthese organizations, we also get the sampling frame as well as the proportion of codes.After this stage, we know the number of firms in each provinces and digit (Figure 1)

Figure 1 Number of firms in 3 provinces.

Moreover, there are 100, 80 and 220 textiles firms in Ha Noi, Hai Duong and Nam

Dinh respectively, so the sample will includes 25 firms in Hanoi, 20 ones in Hai Duong

and 55 ones in Nam Dinh However, we must make sure that the proportion of each

sub-industry in the sample is the same as in the population The stratified method is used in

this stage

According to ISIC Rev.3.1 code 17, we have the code for three-digit sub-industries

that Everia is interested in :

 171 – Spinning, weaving and finishing of textiles

 172 – Manufacture of other textiles

 173 – Manufacture of knitted and crocheted fabrics and articles

Stratifying variable is sub-industries with code 171, 172, 173

Due to the proportion of codes we have in prior stage, with Ha Noi, we have the

sample includes:

 Firms with code 171: 5 firms

 Firms with code 172: 12 firms

 Firms with code 173: 8 firms

We will take sample of 5 firms with code 171; 12 firms with code172; 8 firms with

code 173 in Ha Noi These firms in each code are chosen by random sampling

400 firms

Hanoi

100 firms

Hai Duong 80 firms

Finally, we do the same steps in Ha Noi with Hai Duong and Nam Dinh Thus,

we will do research with:

+In Hai Duong

 4 firms with code 171

 6 firms with code 172

 10 firms with code 173

+In Nam Dinh

 14 firms with code 171

 23 firms with code 172

 18 firms with code 173

Figure 2 Number of firms after multistage sampling

To sum up, we have following steps:

1 2.3 Survey method

After choosing 100 firms to do research, we must know what type of survey we willuse- Questionnaire or Interview or Focus group? Selected survey method must be themost suitable in situation of Everpia For this survey, our team decides to choose face-to-face questionnaire for some around firms and with distant ones, we will use postalquestionnaires This will help us save time and money when carry out the survey Postal questionnaire is sent to firms that we want to survey We also can use e-mail

or tax in this case to help these firms can het our questionnaire earlier Firms can answerour question freely with much time However, the response of firms with this kind ofsurvey is very low and sometimes they can not understand the question so Everpia cannot receive necessary information Therefore, we need to explain clearly about ourpurpose of this questionnaire and also need send it to the people who have highresponsibility in these companies such as managers or marketing departments

Construct the sampling frame

Determine sample size and suitable

sample method

Determine number of firms of each code in each province in sample

Choose sample

the questions However, the cost of traveling is very high so we just apply face to facequestionnaire with some around firms which have no response to postal questionnaire

1.2.4 Questionnaire

Questionnaires are used in our survey method Thus, we need be careful to design aseries of questions As the prior part concerned, an important point is that thequestionnaires must relate to the objective of our research It is to find out firm’sproduction capacity and their behavior towards clients In addition, we also need to knowthe information about their fixed capital, the number of employees, employees’ educationand skills, the education and experience of management and credibility in debts, liquidity,and delivery on time

Due to this aim, our questionnaire includes:

-Question 1 to 4 : general information and classifying firms-Question 5 to 12 : assessing employees and managers-Question 13 to 20: checking activities of firms and their behaviortowards clients and partners

Different formats are applied i.e multiple choice (question 2- 7, 9), rating scale (question 10), yes-no format (question 8, 13, 16), open-ended question (question11, 12,

14, 15, 17-20)

II TASK 2

Representative values, histogram and cross table for the data set taken from a survey on a sample of students at the University of New South Wales, Australia.

2.1 Representative values, quartiles, and histogram

2.1.1 Expected salary (USD/year)

a The representative values:

In order to find out the performance of the students at the University of New SouthWales, Australia, we must go through the representative values which show its bestpicture The representative values are mean, mode, median and coefficient of skewness(COS)

 Mean = 48 699.8, this data represents that the average salary which each ofstudent expects per year is $48 699.8

 Median = 40 000 This means there are 50 per cent students expect their salary ismore than 40 000 USD per year and 50 per cent of them satisfy with salary of lessthan 40 000 USD per year

 Mode = 40 000, it shows the salary which are expected by the most students (95ones) a year

 The skewness of data distribution:

The shape of distribution is represented by Coefficient of skewness(COS)

Applying the formular:

C of S= 3* (mean-median)/ standard deviation

=> C of S= 3(48 699.8-40 000)/ 53 756.61= 0.4855

As C of S is positive, the distribution is skewed to the right

We have: Mean > Median = Mode

b Quartiles (Q)

Q1=30,000 (USD)

Q2= 40,000 (USD)

Q3= 50,000 (USD)

c.Histogram

Histogram for expected salary of students at the University of

South Wales, Australia

>20,

00

0-30,000

>30,

00

0-40,000

>40,

00

0-50,000

>50,

00

0-60,000

>60,

00

0-70,000

>70,

00

0-80,000

>80,

00

0-90,000

>120,000-800,000

Expected salary (USD/year)

a The representative values:

 Mean = 22.48, this means that the average age of student in this university

 The skewness of data distribution:

The shape of distribution is represented by Coefficient of skewness(COS)

Applying the formular:

C of S= 3* (mean-median)/ standard deviation

=> C of S= 3 (22.48-21)/6.38 = 0.696

We have: Mean >Mode > Median

As C of S is positive, the distribution is skewed to the right

Three values (mean, median, and mode) are not much deviation; most of observations

are around them

a The representative values:

 Mode: Chinese >> Most of students have cultural background is Chinese

b Chart

Proportion of number of students between different cultural

Anglosaxon Chinese Germanic Indian Latin Slavonic Other

From this chart, we can see clearly the proportion between students have differentcultural background Almost students have cultural background is Chinese with 71%

of all students This result is approximately as triple as the total of all other culturalbackgrounds There is 13% students have background is Anglo-Saxon and thispercentage get the second biggest proportion The lowest number of students herehave background are Latin and Slavonic In conclusion, the proportion betweennumber of students come from different cultural background is unequal

2.1.4 Indicate why and when you would prefer one measure over another

Mean, median and mode are three measures of central tendency Each measure hasboth advantages and disadvantages, so it is necessaryto determine when we use eachmeasure to support our aims To get the best choice, we have to understand clearly aboutcharacteristics of each measure

Mean is a type of average which is easy to calculate and widely understood In the

calculation of the mean, the value of every items is included so it can be determined witharthimetical exactness and is representative for the whole set of data Another advantage

of mean is that mean is supported by mathematical theory and is suited to further statisticanalysis Besides advantages, there are several disadvantages of mean The value of mean

may not correspond to any actual value Beside that, the mean could be affected byoutliers (extremely high and low values), so the figure given is inappropriate andmisleading The mean is useful for statistical analysis and for predicting future resultswhen there are no extreme values in the data set For example, in the case of expectedsalary, we use mean when we want to analysis statistic about students’ expected salaryand when we want to predict the average of expected salary in the future (It can be over

48, 699.8 USD/year)

The median of a set of data values is the middle value of the data set when it has

been arranged in ascending order That is, from the smallest value to the highest value Itmay be more useful than the mean when there are extreme values in the data set as it isnot affected by the extreme values Median is easy to understand and calculate It is notaffected by outlying values, so it could be used when the mean is misleading However,median fails to reflect the whole data set, it is not suitable for further statistical analysis.Therefore, median should be used in comparing changes in a ‘middle of the road’ valueover the time

Mode is the value that occurs most often in the data set The mode is useful when the

most common item, characteristic or value of a data set is required For example, if wewant to find out at what age, the highest percentage of students in the University of SouthWales contributes, we use mode Mode is easy to find and is unaffected by a few extremevalues Unlike mean and median, mode could be used for data which are not numerical.For example, when we determine the representative value of cultural background ofstudents at the University of New South Wales, Australia, we can not find the mean andthe median but we still can find out the mode is Chinese Another advantage of mode is

in the distribution, it could be the value of an actual items However, mode is probablyunrepresentative and it only represents the most common value because no account of ahigh proporation of the data is taken by mode In addition, it does not take every value

into account so the mode can reflect the whole data set (BPP professional education.

2005)

2.2 Cross tables and charts show the distribution of data

2.2.1 Cross tables and charts show the distribution of data by cultural background

and expected salary

Bin salary Anglosaxon Chinese Germanic Indian Latin Other Slavonic Grand Total

20, 000- 30, 000

30, 000- 40, 000

40, 000- 50, 000

50, 000- 60, 000

60, 000- 70, 000

70, 000- 80, 000

80, 000- 90, 000

90, 000- 100, 000

100, 000- 120, 000

120, 000- 800, 000

Slavonic Other Latin Indian Germanic Chinese Anglosaxon

Chart 2.2.1 The distribution of data by cultural background and expected salary

This above chart and cross table reflects the correlation between expected salary andcultural background Chinese students get the highest percentage in almost groups ofsalary, except in the group of 100,000-120,000 USD/year, just equal to Anglo-Saxon(each conduced 33.33 % of all) The two biggest amounts of student were 109 and 68Chinese who want to earn from 30,000 to 40,000 USD/year and 40,000-50,000 USD/yearrespectively Chinese students not only appear in all of group, but also contributed thelarge percentage number of students in high expected salary groups Especially, Chinesestudents made up approximately 72% people who have expected salary at least 120,000USD per year On the other hand, the number of Indian and Germanic students is not bigand in general most of them expect level of salary is medium (over 30,000 -80, 000 USD/year).

2.2.2 Cross tables and charts show the distribution of data by gender and expected salary

Bin salary female male Grand Total

Bin salary

gender

Chart 2.2.2 The distribution of data by gender and expected salary

The chart and cross table above illustrate the connection between gender andexpected salary The biggest number of students which included 85 females and 60 malesexpect to earn from 30,000 to 40,000 USD per year The sencond top with totally 102people want to have the salary from 40,000 to 50,000 per year Suprising, only 12 of 206male students expect the salary of more 80,000 per year, just as a half as the femalevolume It seems that female studens of the University of New South Wales, Australiawere harder than male so much so the salary which they expect also higher

In addition, generally, female take the higher percentage in all groups of salary,except the group of 70,000-80,000 USD/year when the number of male were four peoplemore than that of female Especially, in the salary group of 80,000-90,000 USD/year,female contribute 100% The second biggest difference between two genders is in 2groups, 50,000-60,000 and 60,000-70,000 (USD/year), when the number of femaleexpected these levels of salary is as two times as the amount of male

In the low level of expected salary (from 10,000-50,000 USD/year), the proportionbetween two genders is very small, even equal to 1 in salary group of 10,000-30,000USD/year.

III TASK

According to the report for domestic and international markets of quarterly sales (inVND millions) of Binh Minh Company during period 2003-2006, we can reflect data byfollowing graphs:

3.1 Trend of domestic and international market during period 2003-2006

Binh Minh Company's quarterly sales (2003-2006)

Chart 1: Trends of domestic and international market

According to chart 1, we can easily recognize the change and general trends of BinhMinh Company’s sale in domestic and international market from 2003 to 2006 Ingeneral, Sales in foreign countries were often higher than the ones in domestic market Inthe first quarter of 2003, export sales was approximate 9 times more than domestic saleswhile at the last quarter in this period, the domestic sales were about 12 millions VNDmore than the export sales In addition, international market showed a downward trend.The sales of export goods dropped dramatically (from $80.5 at the first quarter of year

2003 to $1.8 at the fourth quarter of year 2006) This shows that products of Binh Minhdid not met the demand of customer on the foreign market In summary, Binh Minh has