Tải bản đầy đủ

CHAPTER 4. DATA ANALYSIS AND RESULT

Self-employed (including freelance)

13

4.3%

Part-timer/ Contract/ Temporary employee

13

4.3%

Not yet have a job

Student

13

10

4.3%

3.3%

3

1.0%

1

0.3%

3 - 6 mil. VND

78

26.0%

6 - 10 mil. VND

77

25.7%

10 - 15 mil. VND

15 - 20 mil. VND

72

21

24.0%

7.0%

20 - 25 mil. VND

9

3.0%

25 - 30 mil. VND

30 - 35 mil. VND

21

5

7.0%

1.7%

35 - 40 mil. VND

5

1.7%

40 - 45 mil. VND

1

0.3%

10

3.3%

2 members

28

9%

3 members

4 members

30

64

10%

21%

5 members

83

28%

6 members

48

16%

7 members

8 members

30

12

10%

4%

9 members

2

1%

10 members

3

1%

Housewife

Household monthly income

Less than 3 mil. VND

50 mil VND or more

Number of members in household

As can be seen, There were 143 males (48%) and 157 females (53%) participating the

study. Most of qualified respondents (54%) belonged to 26-34 years old, 44% were 1825 years old. Only 2% were more than 35 years old.

All respondents could recall their most-often-purchase retailer. Nguyen Kim, Thien Hoa

and Cho Lon were the three most popular merchandisers to be recalled with 41%, 18%

and 13%, respectively. There were about 8% of respondent who purchase most

frequently at the “other” small retailers.

Regarding demographic information, there were 46 respondents (15%) married. The

result also recorded 206 respondents (69%) to be employees of private or foreign

43

company and 42 people (14%) working for government enterprise and 9% unemployed

cases (yet have a job, student or housewife).

In average, there were about five members (4.86) in an urban household. 13.7 million

VND was the average household monthly income. This number reflected the living

standard of household in urban of Ho Chi Minh only and could not be projected to

Vietnam nationwide

Table 4-2: Average number in one household and average household monthly income

N

Minimum

Maximum

Mean

Number of members in household

300

2 members

10 members

4.86 members

Average household monthly income

300

2,900,000

70,000,000

13,699,667

4.2 Cronbach alpha reliability analysis

Table 4-3 represented the results of Cronbach alpha analysis. As can be seen, the general

alphas range from 0.7943 (store convenience) to 0.9636 (store service). Also, the general

alpha of each independent variable was higher than alpha-if-item-deleted of every item

in the construct. In summary, all of the construct used in the main survey were reliable in

an acceptable range of Cronbach alpha.

Table 4-3: Cronbach alpha result for main survey

Scale

Mean if

Item

Deleted

Scale

Variance

if Item

Deleted

Corrected

Item-Total

Correlation

Alpha if

Item

Deleted

Store Service: Alpha = 0.9636

EMPL1_The store's employees are very friendly

24.3967

46.8488

0.8286

0.9618

EMPL2_The store's employees are warm-hearted in

consulting customers

24.3467

45.6052

0.9091

0.9529

EMPL3_The store's employees are honest with

customers

24.4600

46.8178

0.8420

0.9602

24.2700

46.5121

0.8721

0.9569

24.1000

46.6120

0.9326

0.9508

23.9600

46.7810

0.9131

0.9528

41.6871

0.8654

0.9073

AFTE1_Free of on-site delivery and assembling

AFTE2_Offer considerate warranty service

AFTE3_After-sales service staffs are friendly and

helpful

Store Facilities: Alpha = 0.9301

FACI1_Facilities for rest at the store are

comfortable

23.9567

44

FACI2_Elevator, rest room and lightings at the store

are comfortable

FACI3_The placement of the aisles is appropriate

ATMO1_Has eye-catching interior design

ATMO2_Products display is appropriate

ATMO3_In-door movement is easy

24.2200

41.4297

0.7803

0.9187

24.3500

41.2383

0.8330

0.9112

24.5700

43.0887

0.7370

0.9239

24.2667

44.1159

0.7760

0.9190

24.3033

42.8274

0.7798

0.9182

Product and Marketing Communications: Alpha = 0.8988

MERC1_The store has wide range of brand and

product

29.3767

51.1185

0.6757

0.8852

MERC2_The store usually has products of new

arrival

29.4167

50.4245

0.7574

0.8763

MERC3_The store always has product I need (no

out-of-stock)

30.0800

52.1207

0.5856

0.8959

MERC4_The store offer prestige and high quality

products

29.7200

50.0150

0.7665

0.8751

PROM1_The store has attractive promotions

programs

29.5700

49.3295

0.7715

0.8741

PROM2_The store often celebrate events for loyal

customers

30.0833

50.1034

0.6713

0.8861

29.8533

49.5503

0.6937

0.8834

8.6900

9.1711

0.5633

0.8205

9.2633

6.7164

0.7344

0.7095

8.9933

6.8227

0.7752

0.6640

9.8733

8.7464

0.5691

0.7893

CONV2_The store has convenient parking lot and

helmet keeping

10.2900

7.5109

0.6863

0.6646

CONV3_The opening hours of the store is

convenient

10.1167

8.4245

0.6599

0.6971

8.8367

5.3545

0.6383

0.7662

9.0500

5.5661

0.7829

0.6156

PROM3_The store has many advertising programs

Perceived Price: Alpha = 0.8249

PRIC1_The store offer value-for-money products

PRIC2_I can buy products at cheaper price at the

store

PRIC3_The prices at the store are very competitive

Store Convenience: Alpha = 0.7943

CONV1_The store is easily accessible

Consumer loyalty: Alpha = 0.8131

LOYA1_The store would be my first choice

LOYA2_I consider myself loyal to the store

45

LOYA3_Even in the case of price increase, I also

would like to buy products from the store

9.4000

6.3478

0.5713

0.8128

4.3 Exploratory factor analysis

The following rotated component matrix (Table 4-4) showed the results of exploratory

factor analysis with principle component extraction and varimax rotation method.

As indicated, all of items were loaded appropriately in their construct from 0.44

minimum score (The store always has product I need) to 0.88 greatest score (Offer

considerate warranty service). Although the loading score of MERC_3 (The store always

has product I need) was less than 0.5. This item was not too small to be removed out of

the study because of its content value in merchandising factor (Nguyen, 2011)

46

Table 4-4: EFA rotated component matrix for main survey

Item

1

AFTE2_Offer considerate warranty service

0.88

EMPL2_The store's employees are warm-hearted in consulting customers

0.84

AFTE3_After-sales service staffs are friendly and helpful

0.84

EMPL3_The store's employees are honest with customers

0.82

AFTE1_Free of on-site delivery and assembling

0.80

EMPL1_The store's employees are very friendly

0.76

Component

2

3

4

FACI1_Facilities for rest at the store are comfortable

0.79

FACI3_The placement of the aisles is appropriate

0.77

FACI2_Elevator, rest room and lightings at the store are comfortable

0.75

ATMO1_Has eye-catching interior design

0.74

ATMO3_In-door movement is easy

0.70

ATMO2_Products display is appropriate

0.68

PROM1_The store has attractive promotions programs

0.79

PROM2_The store often celebrate events for loyal customers

0.73

PROM3_The store has many advertising programs

0.72

MERC2_The store usually has products of new arrival

0.71

MERC4_The store offer prestige and high quality products

0.58

MERC1_The store has wide range of brand and product

0.55

MERC3_The store always has product I need (no out-of-stock)

0.44

CONV2_The store has convenient parking lot

0.79

CONV3_The opening hours of the store is convenient

0.75

CONV1_The store is easily accessible

0.69

5

PRIC2_I can buy products at cheaper price at the store

0.85

PRIC3_The prices at the store are very competitive

0.83

PRIC1_The store offer value-for-money products

0.51

47

Table 4-5: Total variance explained

Initial Eigen Values

Component

Total

% of

Cumulative

Variance

%

Extraction Sums of Squared

Loadings

% of

Cumulative

Total

Variance

%

Rotation Sums of Squared

Loadings

% of

Cumulative

Total

Variance

%

1

12.59

50.35

50.35

12.59

50.35

50.35

5.29

21.16

21.16

2

2.04

8.17

58.52

2.04

8.17

58.52

4.28

17.12

38.28

3

1.68

6.72

65.24

1.68

6.72

65.24

3.93

15.74

54.01

4

1.36

5.42

70.66

1.36

5.42

70.66

2.76

11.04

65.06

5

1.16

4.64

75.31

1.16

4.64

75.31

2.56

10.25

75.31

6

0.82

3.30

78.60

7

0.67

2.70

81.30

8

0.65

2.58

83.88

9

0.48

1.92

85.81

10

0.44

1.76

87.57

11

0.41

1.62

89.19

12

0.34

1.38

90.57

13

0.31

1.24

91.81

14

0.29

1.15

92.96

15

0.27

1.09

94.05

16

0.26

1.05

95.11

17

0.24

0.97

96.08

18

0.21

0.83

96.91

19

0.19

0.76

97.67

20

0.18

0.72

98.39

21

0.14

0.55

98.94

22

0.13

0.53

99.47

23

0.06

0.23

99.70

24

0.04

0.18

99.88

25

0.03

0.12

100.00

48

Table 4-5 represented Total Variance Explained from the EFA. The Total Variance

Explained of five factors was 75.31%, higher than 60%, a standard of a good analysis

(Nguyen, 2011). This meant that the five explored factors explained 75.31% variance of

the observed variables.

Extraction Method: Principal Component Analysis.

Table 4-6: KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy.

0.9065

Approx. ChiSquare

Bartlett's Test of Sphericity

7,308

Df

300

0.000

Sig.

Table 4-6 showed the results of KMO and Bartlett test. KMO was greater than 90%,

indicating a very-good EFA result (Kaiser, 1974). Also, P value of Bartlett test was less

than 5%, concluding that the correlation matrix among variables was not an identity

matrix and indicating the correlation among variables.

4.4 Multiple linear regression

Table 4-7: Regression model summary

R

0.822

Change Statistics

R

Square

Adjusted

R

Square

Std. Error of

the Estimate

0.676

0.670

0.657

R

Square

Change

0.676

F

Change

df1

122.495

5.000

df2

294.000

Sig. F

Change

0.000

a. Predictors: (Constant), Perceived Price, Store Convenience, Store Facilities, Store Service,

Product and Marketing Communications

b. Dependent Variable: Consumer loyalty

Table 4-7 showed the regression model summary in which R square and adjusted R

square were represented. R square equal to 0.676, indicating that 68% variability of

consumer loyalty was predicted from five dependent variables. Adjusted R square

(0.670) was really closed to R square; the difference was 0.676 – 0.670 = 0.6%. This

meaning that if the model is derived from the population rather than a sample, it would

account for 0.6% less variance in the outcome of dependent variable.

49

Table 4-8: ANOVA F test

Sum of

Squares

Df

Mean Square

Regression

264.496 5

52.899

Residual

126.963 294

0.432

Total

391.459 299

F

Sig.

0.000a

122.495

a. Predictors: (Constant), Perceived Price, Store Convenience, Store Facilities, Store Service,

Product and Marketing Communications

b. Dependent Variable: Consumer loyalty

Another output of linear regression was analysis of variance (ANOVA) which can be

seen in the table 4-8. This analysis tests whether the model is significantly good at

predicting the outcome. F-ratio represents the ratio of the improvement in predicting the

result from fitting model (regression), to the inaccuracy that still exists in the model

(residual). F value was much greater than 1, indicating that the improvement from fitting

the regression model was much higher than the inaccuracy within the model. P value

was less than 0.001, thus we can conclude that the model is significantly better at

predicting the consumer loyalty outcome.

Table 4-9: Multiple linear regression result for main survey

Model

Unstandardized

Coefficients

T

0.248

0.143

0.285

Std.

Error

0.184

0.041

0.046

0.170

0.322

1.345

3.456

6.165

0.201

0.052

0.206

0.106

0.159

0.035

0.037

0.127

0.183

B

(Constant)

Store Service

Store Facilities

Product and

Marketing

Communications

Store Convenience

Perceived Price

Standardized

Coefficients

Dependent Variable: Consumer loyalty

Beta

Collinearity

Statistics

Sig.

Tolerance

VIF

0.180

0.001

0.000

0.456

0.404

2.192

2.475

3.898

0.000

0.394

2.540

3.064

4.306

0.002

0.000

0.647

0.609

1.546

1.641

Finally, the result of regression was revealed in the above table 4-9. As can be seen,

Store Service, Sore Facilities, Product and Marketing Communications, Store

Convenience and Perceived Price have positive standardized beta and p value < 0.005,

50

indicating a significant positive relationship between each of them and dependent

variable (consumer loyalty)

The result of regression model was also generated. The following figure 4-1 showed that

consumer loyalty (Y) is determined by five independent factors Store Service (X1),

Store Facilities (X2), Product & Marketing Communication (X3), Store Convenience

(X4) and Perceived Price (X5). The relationship between independent and dependent

variables is thus described in the following equation

Y = 0.170X1 + 0.322X2 + 0.206X3 + 0.127X4 + 0.183X5

X1: Store Service

β1= 0.170

Adjusted R2 = 0.670

X2: Store facilities

β2= 0.322

Y: Consumer

Loyalty

β3= 0.206

X3: Product &

marketing

communication

Y = 0.170X1 + 0.322X2 +

X4: Store convenience

β4= 0.127

0.206X3 + 0.127X4 + 0.183X5

X5: Perceived price

β5= 0.183

Figure 4-1: Result of multiple linear regression

4.5 Hypotheses assessment and discussion

Hypothesis H1b: The store service positively affects consumer loyalty

In Table 4-7, Store service had positive standardize beta (0.170) and P value < 0.005.

We can conclude that store service positively affected consumer loyalty. Hypothesis 1b

was thus supported. Jinfeng and Zhilong (2009) also confirmed the significant

relationship between employee service and consumer loyalty. Our study generalized the

51

result to accept the positive relationship of store service including employee service &

after-sales service and consumer loyalty

Hypothesis H2b: There is a positive relationship between store facilities and consumer

loyalty

Store facilities, in the same way, was posited to positively affect consumer loyalty with

standardized beta = 0.322 and P value = 0.001. We consequently accepted the H2b.

While only physical facilities is supported to significantly correlate with consumer

loyalty (Jinfeng and Zhilong, 2009), our research provided further conclusions about the

combined effects of both physical facilities and store atmosphere on consumer loyalty of

a store

Hypothesis H3b: Product & marketing communication is positively related to

consumer loyalty

The result in table 4-7 illustrated for the positive relationship between merchandising &

marketing communication and consumer loyalty (Standardized beta = 0.206, P value

<0.005). H3b was thus supported. Besides, this conclusion also complemented the result

of Thang and Tan study (2003) which identifies the two separate relationship between

merchandising and promotions towards store preference

Hypothesis H4b: The store convenience positively related to consumer loyalty

Store convenience was recorded to have the smallest standardize beta (0.127). However,

this factor was still posited to positively related to consumer loyalty (P value = 0.002).

This indicated that, the location and the accessibilities of a store also play an important

part in shaping consumer loyalty. Jinfeng and Zhilong (2009) also find the relationship

in their recent retailer equity study. We thus accepted the H4b

Hypothesis H5b: There is a positive relationship perceived price and consumer loyalty

Finally, H5b was also supported when perceived price was recorded to have 0.183 beta

score and P value < 0.005. This result explained an undeniable fact in many emerging

countries that price consideration always stays at one the top priorities for consumers to

select a store and purchase products.

52

Generally, the study satisfactorily achieved research objectives by identifying the

relationship between key store images and consumer loyalty. Statistically, the research

fulfill most of requirements about reliability such as

• Cronbach’s alpha represent a good reliability (0.79 – 0.96)

• The multi-collinearity of all five independent variables in regression model was in an

acceptable range (1.546 – 2.540), indicating that the model typically accept certain

degree collinearity between the predictors

• Adjusted R Square is closed to R square, ensuring the reliable estimation from

population

Additionally, the study also found that store images dimensions affect differently on

consumer loyalty. The results of regression revealed the derived importance score of

each factors based on standardized beta. As can be seen, store facilities had the strongest

impact on consumer loyalty with beta score = 0.322. The second most important factor

was product & marketing communication (0.206), followed by perceived price (0.183)

and store service (0.170). Store convenience was indentified to be the least important

factor with 0.127 beta score. Meanwhile, Jinfeng and Zhilong (2009) explored that store

convenience was the strongest factor impacting consumer loyalty, followed by physical

facilities, employee service and perceived price.

4.6 Summary

This chapter represented the results of the main survey including sample descriptive

information, Cronbach alpha reliability analysis, exploratory factor analysis, multiple

linear regression, hypotheses assessment and discussion.

Descriptive information of the sample showed the demographic characteristics such as:

gender, age, most-often-purchased store, marital status, occupation and household

monthly income. Cronbach alpha results revealed that all items were used in an

acceptable reliability (general alpha of each factor ranged from 0.7943 to 0.9636). All

five factors were explored to be appropriately loaded into their predefined constructs.

Finally, multiple linear regression showed the significant relationship of store service,

store facilities, product & marketing communication, store convenience and perceived

53