BBA4009 Au Lee Yau

BBA 4009

Competitive Analysis

AU LEE YAU

930524-01-6857

200033

CHRITINA LAU

MARCH 2015

TABLE OF CONTENT

Title Pages

Content 1

4.0 Chapter 4

4.0 Introduction4.1 Descriptive statistic of the collection 4.2 T-test of the data collection4.3 Hypothesis Testing4.4 Chapter summary

2-13

5.0 Chapter 5

5.0 Introduction5.1 Respondent Profile5.2 Discussion of the findings5.3 Recommendations5.4 Practical Implication5.5 Limitation of Study5.6 Conclusion

14-18

References 19

Coursework 20-21

4.0 Introduction

Page 1 of 20

This Chapter mainly represents the result of the data analysis. This result will use to

study the aim report the finding that we get from data analysis. Thus, in this research

data were analyzed using which several method to analysis such as Descriptive

statistic of the collection, T-test of the data collection, the hypothesis testing and the

last chapter summary.

4.1 Descriptive statistic of the collection

Table 4.1 Age of the respondents

Age Frequency Percentage (%)

Below 20

21-30

31-40

41 and above

30

35

20

15

30

35

20

15

Total 100 100

This results of age of respondents shown in table 4.1. The table show 30% of the

respondent (30 people respondents) is at the age below 20 years old, then follow by

35% (35 respondents) are in age between 21 until 30. Then, age from 31-40 have 20%

(have 20 respondents). Lastly, the age 41 and above there are 15respondents (15% of

the all respondents). Based on this statement the highest respondent age are between

21 until 30 years old and the lowest are the age 41 and above. Only 15 respondents

only.

Table 4.2 Gender of the respondents

Page 2 of 20

Gender Frequency Percentage (%)

Male

Female

50

50

50

50

Total 100 100

This results of gender of respondents shown in table 4.2. The findings show the both

male and female have same frequency and percentage. The male have 50respondents

(50% male respondents) and also the female also have 50respondents (50% male

respondents).

Table 4.3 marital status of the respondents

Marital Status Frequency Percentage (%)

Single

Married

60

40

60

40

Total 100 100

Table 4.3 show the result of the marital status of the respondents. This finding

shows the highest respondent is the single respondent which 60% (60 respondents). In

the others hand, there are 40 respondents in married respondents include also 40% out

of 100% respondents.

Table 4.4 Race of the respondents

Page 3 of 20

Race Frequency Percentage (%)

Malays

India

Chinese

30

25

45

30

25

45

Total 100 100

This results of race of respondents shown in table 4.4. The table show 30% of the

respondent (30 people respondents) is the Malay respondents, then follow by 25%

(25respondents) are Indian. Then, the Chinese have the highest rate 45 respondents

(45%). Based on this statement the highest respondent race are Chinese and the lowest

are the Indians.

Table 4.5 Religion of the respondents

Religion Frequency Percentage (%)

Christian

Islam

Hinduism

Buddhism

30

25

10

35

30

25

10

35

Total 100 100

The table 4.5 show 30% of the respondent (30 people respondents) is the chiristian

respondents, then follow by 25% (25respondents) are Islamic. Then, the Hindusim

only 10% in my respondents follow by Buddhism have 35% the highest rate of the all

religion, whereas the Hinduism are the weakest percentages only 10%.

Table 4.6 Education Level of the respondents

Page 4 of 20

Education Level Frequency Percentage (%)

Master degree

Bachelor degree

Advance Diploma

Diploma

30

25

35

10

30

25

35

10

Total 100 100

The table 4.6 show the education level of the all respondents the highest frequency is

the Advance Diploma are 30 respondents, follow by master degree 30respondents,

25respondents are Bachelor degree, and the lowest frequency is the Diploma level

only show 10%.

Table 4.7 Occupation of the respondents

Occupation Frequency Percentage (%)

Education

Finance

Service Industry

Others

25

25

35

15

25

25

35

15

Total 100 100

Table 4.7 show the result of the Occupation of the respondents. This finding shows

the highest respondent is the service industry which 35% (35 respondents). In the

others hand, there are same 25 respondents in the education and the finance

occupation 25%. the least occupation is the others act as students and worker only 15

respondents (15% out of 100%).

Page 5 of 20

Table 4.8 Monthly Income of the respondents

Monthly Income Frequency Percentage (%)

Below 1500

1501 – 2000

2001 – 2500

2500 and above

10

15

20

55

10

15

20

55

Total 100 100

Table 4.3 show the result of the Monthly income of the respondents. This finding

shows the highest respondent have income 2500 and above which 55%

(55respondents). In the others hand, there are 20 respondents in income between 2001

– 2500 include also 20% out of 100% respondents. Next the income between 1501-

2000 have 15respondents (15%) and the lowest frequency is the income below 1500

only 10respondents (10%only).

Table 4.9 Living Area of the respondents

Living Area Frequency Percentage (%)

City

Village

80

20

80

20

Total 100 100

Table 4.9 show the result of the living area of the respondents. This finding shows the

highest respondent stay in city are 80% (80 respondents). In the others hand, there are

20 respondents stay in village respondents include also 20% out of 100% respondents.

Page 6 of 20

Table 4.10 buy the SME’s product of the respondents

Buy the SME’s product Frequency Percentage (%)

Yes

No

60

40

60

40

Total 100 100

Table 4.10 show the result of the buy the SME’s product of the respondents. This

finding shows the highest respondent is yes to buy the SME’s product which 60% (60

respondents). In the others hand, there are 40 respondents in respondents say No to

buying SMEs product include also 40% out of 100% respondents.

4.2 T-test of the data collection

A statistical examination of two population means. A two-sample t-test examines

whether two samples are different and is commonly used when the variances of two

normal distributions are unknown and when an experiment uses a small sample size.

For example, a t-test could be used to compare the average floor routine score of the

U.S. women's Olympic gymnastics team to the average floor routine score of China's

women's team.

There are main types of the t-test may be used, for example:

1. One-sample t-test is used to compare a sample mean with a known population

mean or some other meaningful, fixed value

Page 7 of 20

2. Independent samples t-test is used to compare two means from independent

groups. Two separate sets of independent and identically distributed samples

are obtained, one from each of the two populations being compared. For

example, suppose we are evaluating the effect of a medical treatment, and we

enrol 100 subjects into our study, then randomly assign 50 subjects to the

treatment group and 50 subjects to the control group.

3. Paired samples t-test is used to compare two means that are repeated

measures for the same participants - scores might be repeated across different

measures or across time. It can also use to compare paired samples, as in a two

treatment randomized block design.

4. In this research, the independent samples test will used to test whether gender

is significant towards packaging.

Table 4.11: Independent sample test between gender and packaging

The result of T-test is shown in

Page 8 of 20

t-Test: Two-Sample Assuming Unequal Variances

Variable

1Variable

2Mean 14.4 18.12

Variance52.0816

333.5771

4Observations 50 50Hypothesized Mean Difference 0df 94t Stat -2.84212

P(T<=t) one-tail0.00274

8

t Critical one-tail1.66122

6

P(T<=t) two-tail0.00549

6

t Critical two-tail1.98552

3

table 4.11 above. The result show that the difference in the mean of 14.4 and 18.12

with the Variance of 52.08163 and 33.57714 for the male and female on the packaging

were insignificant. The t-value is 0.005496, in this result we can concluded that there

is has significant different of the packaging between male and female respondents.

Table 4.12: Independent sample test between gender and purchase decision


Variabl

e 1Variabl

e 2Mean 15.26 18.42

Variance40.8493

917.5138

8Observations 50 50Hypothesized Mean Difference 0df 84

t Stat-

2.92484


5


7P(T<=t) two-tail 0.06443t Critical two-tail 1.98861

The result of T-test is shown in table 4.12 above. The result show that the difference

6in the mean of 15.26 and 18.42 with the Variance of 40.84939 and 17.51388 for the

male and female on the purchase decision were insignificant. The t-value is 0.006443,

in this result we can concluded that there is no significant different of the purchase

decision between male and female respondents.

Page 9 of 20

Table 4.13: Independent sample test between gender and price


Variable

1Variable

2Mean 14.32 17.2

Variance22.2220

423.5918

4Observations 50 50Hypothesized Mean Difference 0df 98t Stat -3.0087


7


1

P(T<=t) two-tail1.00333

5


7 The result of T-test is shown in table 4.13 above. The result show that the difference

in the mean of 14.32 and 17.2 with the Variance of 22.22204 and 23.59184 for the

male and female on the price were insignificant. The t-value is 1.003335, in this result

we can concluded that there is has no significant different of the purchase decision

between male and female respondents.

Table 4.14: Independent sample test between gender and customer loyalty


Variable 1

Variable 2

Mean 13.62 17.68Variance 13.05 17.28

Page 10 of 20

673 327Observations 50 50Hypothesized Mean Difference 0df 96

t Stat

-5.211

99

P(T<=t) one-tail5.35E

-07


881

P(T<=t) two-tail1.07E

-06


984

The result of T-test is shown in table 4.14 above. The result show that the difference

in the mean of 13.62 and 17.68 with the Variance of 13.05673 and 17.28327for the

male and female on the customer loyalty were insignificant. The t-value is 1.07, in

this result we can concluded that there is no significant different of the customer

loyalty between male and female respondents.

4.3 Hypothesis Testing

The analysis of the variance (ANOVA) is used to compare the difference between

more than two means at the same time. The necessary assumption must be met before

we conducting the ANOVA. Hence, we assumption for ANOVA are the same as those

t-tests. There are two assumption focused on the are

a) Population normality – population from which the samples have been drawn

should be normal. Check this for each group using normality statistics such as

Page 11 of 20

skewness and Shapiro – Wilk.

b) Homogeneity of variance – the Homogeneity of variance scores in each group.

Thus, let we using the t-test, Levene’s test determined whether the variances is equal,

or unequal.( Coakes &Steed 2007)

Table 4. 15 One way ANOVA between age, race, religion, education level, occupation

and income with packaging.

Anova: Single Factor

SUMMARY

Groups CountSum

Average

Variance

Column 1 6775

129.1667

1604.167

Column 2 6750 125 1000

Column 3 6825 137.5 4187.5

Column 4 5650 130 8875

ANOVASource of Variation SS df MS F

P-value F crit

Between Groups

487.3188 3

162.4396

0.044435

0.987157

3.12735

Within Groups

69458.33 19

3655.702

Total69945.

65 22

The result of ANOVA is shown in Table 4.15. In this situation, the F value is

0.044435, and this is not significant level at the 0.987. This means there is no

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significant between the packaging and the factor of the age, race, religion, education

level, occupation, and income. it can show that the analysis of the variance from the

ANOVA table indicated that F statistic produced is found to be significant at level

0.05 level. We can conclude that this regression models reaches statically significant

as p value less than 0.05.In my Conclusion, in this one way ANOVA testing we can

concluded there is no significant relationship between age, race, religion, education

level, occupation and income. This is because all the significant value is more than

0.05.

4.4 Chapter summary

In this chapter, the three hypothesis proposed is earlier tested. Using sample of 100

respondent, the data obtained from the Johor jaya area. First, the questionnaire was

distributed randomly. This is aim to determine the effect of new packaging toward

purchase decisions, customer loyalty and also price. Two level of statistical analysis

were conducted in two ways. The first level involved using the basic descriptive

analysis. In this analysis, we used the frequencies of the demographic data. The

second level of analysis is the ANOVA (t-test and one way). In my summary, based

on the test conducted, 2 hypothesis is reject and 1 hypothesis is acceptable. This

research shows that only purchase decisions and customer loyalty will affected if

there are a new packaging to SME’s product, there is no relationship between the

packaging and the price of the product.

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5.0 Introduction

Packaging is the technology of enclosing or protecting products for distribution,

storage, sale, and use in SMEs product. Packaging also refers to the process of design,

evaluation, and production of packages. Packaging can be described as a coordinated

system of preparing goods for transport, warehousing, logistics, sale, and end use. The

importance of the Packaging in the SME’s product is a marketing tool used to reflect

the brand and to sell the product inside. This tool used design elements such as color,

font, description and logo to drive consumers to buy the product.

5.1 Respondent Profile

We will discuss in this chapter about the result of the finding in this research. To

easy understanding in the discussion, we will separate into three parts namely, 5.0, 5.3

and 5.6.

The main objectives in my investigation is to study the aim of the effect of

packaging to SME’s product in purchase decisions, price, and the customer loyalty.

In order to access the objective, the three specific objectives of this study have been

formulated as follows: Firstly, to determine whether the new packaging of SME will

Page 14 of 20

affect the customer loyalty on that product. Then, to examine whether consumer

willing to pay more for the SME product after a new packaging. Lastly, to test the

purchase decisions when the SMS product have a new packaging.

In my research, the researcher can get the data result from the respondents to

make sure their research is complete and also to test their objectives. In this research,

the main objective is to indicate the effect of packaging to SME’s product in purchase

decisions, price, and the customer loyalty. Number of the respondents contain of 100

person and they are all come from Johor Jaya. The researchers are categorized the

demographic data according to the age, race, religion, education level, occupation and

income and also marital status. In this research, there are 50 male’s respondents and

50 female respondents in same 50% percentages out of 100%.

5.2 Discussion of the findings

In this research, the figure of the analysis regarding to people from age 41 and

above shows only 15%. This is because they have affect by the price and purchase

decisions. They have a weak price and purchase decisions because most of all already

entire in their life.

The secondly we make a investigate the between the race and the packaging, the

results show that Chinese has the highest rate in all the races. This is because most of

the Chinese very likely the wrap or packaging of the SMEs product and also the most

Chinese has the improvement buying decisions.

The most weakest religion that has effect is the Hinduism, this is due to the

Page 15 of 20

Hinduism is very loyal to their religion, they are tradition and focused in their cultural

in social attitudes. The Hinduism show the percentages only 10%.

Next, the effect between the education level and the packaging displays the

Diploma level has the weakest effect. This is because the Diploma student require to

focus in their study and have least buying decisions.

Occupation in range others has the low percentages, only present the 10% out

of 100%. This is because most of the occupation are the students and worker, the have

also weak purchase decisions

The income below 1500 has the lowest percentages in the research. Only 10%

percentages, this mean that the lower income has choose the lower price product and

no influences of the packaging. The lower income affect the buying decision to

pretend save cost. Finally, the all price and customer loyalty also purchase decision in

all race, age, religion, education, occupation, income has no effect to the packaging to

SME’s product.

5.3 Recommendations

In my study, the most of the greatest effect is Packaging to the SME’s product. This

is because the nowadays, annually in the competitive world we have to have a nice

wrapping and design for the packaging only these can make a differentiate from

others SME’s products.

The price has low effect than the packaging, we can explain through if the buyer

has greater purchase decision normally they buy the brand product with the nice look

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packaging. Thus, the purchase decision and the customer loyalty can be change when

the packaging is more attract the buyer and the buyer will try another product with

classic and luxury packaging.

5.4 Practical Implication

The Government undergoes SME development feature prominently in all of the

Government's economic development plans over the years. Over the recent decade, a

clear policy for accelerating the development of SMEs has been charted through

specific strategies outlined in the Second Industrial Master Plan, Third Outline

Perspective Plan and Eight Malaysia Plan.Broadly, strategies to promote the

development of SMEs have been formulated against the backdrop of a changing and

challenging economic environment. To further enhance the Government's role, and for

greater coordination and focus in SME development, the National SME Development

Council was established in June 2004.

The company will develop the packaging by Shifting comparative advantage.

Globalization of trade, investment and production has substantially altered

comparative advantages between large and small firms.

5.5 Limitation of Study

The study of the case has several limitation, there are all divided into 3 limitation.

the beginning this research only focus in specific in one area only, the research range

is narrow. besides, the research time is only four month during my study, this will

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limited the time to get the respond from the respondents. the third limitation is the

there are some of the respondents are in cooperative with the questionnaire, this may

affect the analysis the data.

5.6 Conclusion

Packaging is the technology of enclosing or protecting products for distribution,

storage, sale, and use in SMEs product. The mainly objectives is the new packaging

of SME’s product affect the customer loyalty on that product. Then, The consumer are

willing to pay more on the new packaging in whether high or low prices. The

purchase decision affect by the new packaging SME’s product.

All the hypothesis and objectives of the research is all approved in my research.

Page 18 of 20

References

1. http://en.wikipedia.org/wiki/Student%27s_t-test

2. http://support.minitab.com/en-us/minitab-express/1/help-and-how-to/basic-

statistics/inference/supporting-topics/test-of-means/types-of-t-tests/

3. http://www.bnm.gov.my/?ch=en_press&pg=en_press_all&ac=1279&lang=en

4. http://www.tradeforum.org/Export-Strategies-for-Small-Firms/#sthash.2yLkFCy4

Page 19 of 20

http://www.tradeforum.org/Export-Strategies-for-Small-Firms/#sthash.2yLkFCy4

http://www.bnm.gov.my/?ch=en_press&pg=en_press_all&ac=1279&lang=en

http://support.minitab.com/en-us/minitab-express/1/help-and-how-to/basic-statistics/inference/supporting-topics/test-of-means/types-of-t-tests/

http://support.minitab.com/en-us/minitab-express/1/help-and-how-to/basic-statistics/inference/supporting-topics/test-of-means/types-of-t-tests/

http://en.wikipedia.org/wiki/Student's_t-test

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BBA4009 Au Lee Yau