Research on factors affecting customer satisfaction when purchasing hair care cosmetics

ANALYZE DISTRIBUTION CHANNEL MEASUREMENT

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling


Adequacy.	.705
Bartlett's Test of Approx. Chi-Square Sphericity df	288,143 10
Sig.	.000

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Research on factors affecting customer satisfaction when using filter coffee products according to taste at Dong Xanh Coffee Production, Trading & Service Company Limited in Thua Thien Hue - 14
Mobile Phone Usage in Hanoi Inner City Area zt2i3t4l5ee zt2a3gsconsumer,consumption,consumer behavior,marketing,mobile marketing zt2a3ge zc2o3n4t5e6n7ts - Test the relationship between demographic variables and consumer behavior for Mobile Marketing activities The analysis method used is the Chi-square test (χ2), with statistical hypotheses H0 and H1 and significance level α = 0.05. In case the P index (p-value) or Sig. index in SPSS has a value less than or equal to the significance level α, the hypothesis H0 is rejected and vice versa. With this testing procedure, the study can evaluate the difference in behavioral trends between demographic groups. CHAPTER 4 RESEARCH RESULTS During two months, 1,100 survey questionnaires were distributed to mobile phone users in the inner city of Hanoi using various methods such as direct interviews, sending via email or using questionnaires designed on the Internet. At the end of the survey, after checking and eliminating erroneous questionnaires, the study collected 858 complete questionnaires, equivalent to a rate of about 78%. In addition, the research subjects of the thesis are only people who are using mobile phones, so people who do not use mobile phones are not within the scope of the thesis, therefore, the questionnaires with the option of not using mobile phones were excluded from the scope of analysis. The number of suitable survey questionnaires included in the statistical analysis was 835. 4.1 Demographic characteristics of the sample The structure of the survey sample is divided and statistically analyzed according to criteria such as gender, age, occupation, education level and personal income. (Detailed statistical table in Appendix 6) - Gender structure: Of the 835 completed questionnaires, 49.8% of respondents were male, equivalent to 416 people, and 50.2% were female, equivalent to 419 people. The survey results of the study are completely consistent with the gender ratio in the population structure of Vietnam in general and Hanoi in particular (Male/Female: 49/51). - Age structure: 36.6% of respondents are <23 years old, equivalent to 306 people. People from 23-34 years old accounting for the highest proportion: 44.8% equivalent to 374 people, people aged 35-45 and >45 are 70 and 85 people equivalent to 8.4% and 10.2% respectively. Looking at the results of this survey, we can see that the young people - youth account for a large proportion of the total number of people participating in the survey. Meanwhile, the middle-aged people including two age groups of 35 - 45 and >45 have a low rate of participation in the survey. This is completely consistent with the reality when Mobile Marketing is identified as a Marketing service aimed at young people (people under 35 years old). - Structure by educational level: among 835 valid responses, 541 respondents had university degrees, accounting for the highest proportion of ~ 75%, 102 had secondary school degrees, ~ 13.1%, and 93 had post-graduate degrees, ~ 11.9%. - Occupational structure: office workers and civil servants are the group with the highest rate of participation with 39.4%, followed by students with 36.6%. Self-employed people account for 12%, retired housewives are 7.8% and other occupational groups account for 4.2%. The survey results show that the student group has the same rate as the group aged <23 at 36.6%. This shows the accuracy of the survey data. In addition, the survey results distributed by occupational criteria have a rate almost similar to the sample division rate in chapter 3. Therefore, it can be concluded that the survey data is suitable for use in analysis activities. - Income structure: the group with income from 3 to 5 million has the highest rate with 39% of the total number of respondents. This is consistent with the income structure of Hanoi people and corresponds to the average income of the group of civil servants and office workers. Those People with no income account for 23%, income under 3 million VND accounts for 13% and income over 5 million VND accounts for 25%. 4.2 Mobile phone usage in Hanoi inner city area According to the survey results, most respondents said they had used the phone for more than 1 year, specifically: 68.4% used mobile phones from 4 to 10 years, 23.2% used from 1 to 3 years, 7.8% used for more than 10 years. Those who used mobile phones for less than 1 year accounted for only a very small proportion of ~ 0.6%. (Table 4.1) Table 4.1: Time spent using mobile phones Frequency Ratio (%) Valid Percentage Cumulative Percentage Alid <1 year 5 .6 .6 .6 1-3 years 194 23.2 23.2 23.8 4-10 years 571 68.4 68.4 92.2 >10 years 65 7.8 7.8 100.0 Total 835 100.0 100.0 The survey indexes on the time of using mobile phones of consumers in the inner city of Hanoi are very impressive for a developing country like Vietnam and also prove that Vietnamese consumers have a lot of experience using this high-tech device. Moreover, with the majority of consumers surveyed having a relatively long time of use (4-10 years), it partly proves that mobile phones have become an important and essential item in people's daily lives. When asked about the mobile phone network they are using, 31% of respondents said they are using the network of Vietel company, 29% use the network of of Mobifone company, 27% use Vinaphone company's network and 13% use networks of other providers such as E-VN telecom, S-fone, Beeline, Vietnammobile. (Figure 4.1). Figure 4.1: Mobile phone network in use Compared with the announced market share of mobile telecommunications service providers in Vietnam (Vietel: 36%, Mobifone: 29%, Vinaphone: 28%, the remaining networks: 7%), we see that the survey results do not have many differences. However, the statistics show that there is a difference in the market share of other networks because the Hanoi market is one of the two main markets of small networks, so their market share in this area will certainly be higher than that of the whole country. According to a report by NielsenMobile (2009) [8], the number of prepaid mobile phone subscribers in Hanoi accounts for 95% of the total number of subscribers, however, the results of this survey show that the percentage of prepaid subscribers has decreased by more than 20%, only at 70.8%. On the contrary, the number of postpaid subscribers tends to increase from 5% in 2009 to 19.2%. Those who are simultaneously using both types of subscriptions account for 10%. (Table 4.2). Table 4.2: Types of mobile phone subscribers Frequency Ratio (%) Valid Percentage Cumulative Percentage Valid Prepay 591 70.8 70.8 70.8 Pay later 160 19.2 19.2 89.9 Both of the above 84 10.1 10.1 100.0 Total 835 100.0 100.0 The above figures show the change in the psychology and consumption habits of Vietnamese consumers towards mobile telecommunications services, when the use of prepaid subscriptions and junk SIMs is replaced by the use of two types of subscriptions for different purposes and needs or switching to postpaid subscriptions to enjoy better customer care services. In addition, the majority of respondents have an average spending level for mobile phone services from 100 to 300 thousand VND (406 ~ 48.6% of total respondents). The high spending level (> 500 thousand VND) is the spending level with the lowest number of people with only 8.4%, on the contrary, the low spending level (under 100 thousand VND) accounts for the second highest proportion among the groups of respondents with 25.4%. People with low spending levels mainly fall into the group of students and retirees/housewives - those who have little need to use or mainly use promotional SIM cards. (Table 4.3). Table 4.3: Spending on mobile phone charges Frequency Ratio (%) Valid Percentage Cumulative Percentage Valid <100,000 212 25.4 25.4 25.4 100-300,000 406 48.6 48.6 74.0 300,000-500,000 147 17.6 17.6 91.6 >500,000 70 8.4 8.4 100.0 Total 835 100.0 100.0 The statistics in Table 4.3 are similar to the percentages in the NielsenMobile survey results (2009) with 73% of mobile phone users having medium spending levels and only 13% having high spending levels. The survey results also showed that up to 31% ~ nearly one-third of respondents said they sent more than 10 SMS messages/day, meaning that on average they sent 1 SMS message for every working hour. Those with an average SMS message volume (from 3 to 10 messages/day) accounted for 51.1% and those with a low SMS message volume (less than 3 messages/day) accounted for 17%. (Table 4.4) Table 4.4: Number of SMS messages sent per day Frequency Ratio (%) Valid Percentage Cumulative Percentage Valid <3 news 142 17.0 17.0 17.0 3-10 news 427 51.1 51.1 68.1 >10 news 266 31.9 31.9 100.0 Total 835 100.0 100.0 Similar to sending messages, those with an average message receiving rate (from 3-10 messages/day) accounted for the highest percentage of ~ 55%, followed by those with a high number of messages (over 10 messages/day) ~ 24% and those with a low number of messages received daily (under 3 messages/day) remained at the bottom with 21%. (Table 4.5) Table 4.5: Number of SMS messages received per day Frequency Ratio (%) Valid Percentage Cumulative Percentage Valid <3 news 175 21.0 21.0 21.0 3-10 news 436 55.0 55.0 76.0 >10 news 197 24.0 24.0 100.0 Total 835 100.0 100.0 When comparing the data of the two result tables 4.4 and 4.5, we can see the reasonableness between the ratio of the number of messages sent and the number of messages received daily by the interview participants. 4.3 Current status of SMS advertising and Mobile Marketing According to the interview results, in the 3 months from the time of the survey and before, 94% of respondents, equivalent to 785 people, said they received advertising messages, while only a very small percentage of 6% (only 50 people) did not receive advertising messages (Table 4.6). Table 4.6: Percentage of people receiving advertising messages in the last 3 months Frequency Ratio (%) Valid Percentage Cumulative Percentage Valid Have 785 94.0 94.0 94.0 Are not 50 6.0 6.0 100.0 Total 835 100.0 100.0 The results of Table 4.6 show that consumers in the inner city of Hanoi are very familiar with advertising messages. This result is also the basis for assessing the knowledge, experience and understanding of the respondents in the interview. This is also one of the important factors determining the accuracy of the survey results. In addition, most respondents said they had received promotional messages, but only 24% of them had ever taken the action of registering to receive promotional messages, while 76% of the remaining respondents did not register to receive promotional messages but still received promotional messages every day. This is the first sign indicating the weaknesses and shortcomings of lax management of this activity in Vietnam. 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Research on factors affecting the decision to purchase gypsum board of Huy An private trading enterprise from institutional customers in Ho Chi Minh City - 13
Research on factors affecting the behavior of using international bank cards in Vietnam - 21
Research Contents Identify Factors Affecting Slow Growth In The Study.

Communalities

Initial	Extraction
C1	1,000	.359
C2	1,000	.431
C3	1,000	.508
C4	1,000	.503
C05	1,000	.646

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial		Eigenvalues	Extraction Sums of Squared Loadings
Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	2,447	48,936	48,936	2,447	48,936	48,936
2	.949	18,985	67,921
3	.742	14,839	82,760
4	.505	10,099	92,859
5	.357	7.141	100,000

Extraction Method: Principal Component Analysis.

Component Matrix(a)

Component
	1
C1	.599
C2	.656
C3	.712
C4	.709
C05	.804

Extraction Method: Principal Component Analysis. a 1 components extracted.

Rotated Component Matrix(a)

a Only one component was extracted. The solution cannot be rotated.

PAYMENT METHOD SCALE ANALYSIS

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling


Adequacy.	.729
Bartlett's Test of Approx. Chi-Square Sphericity df	249,323 6
Sig.	.000

Communalities

Initial	Extraction
P1	1,000	.611
P2	1,000	.452
P3	1,000	.614
P04	1,000	.651

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial		Eigenvalues	Extraction Sums of Squared Loadings
Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	2,328	58,192	58,192	2,328	58,192	58,192
2	.750	18,756	76,948
3	.524	13,109	90,057
4	.398	9,943	100,000

Extraction Method: Principal Component Analysis.

Component Matrix(a)

Component
	1
P1	.781
P2	.673
P3	.784
P04	.807

Extraction Method: Principal Component Analysis. a 1 components extracted.

Rotated Component Matrix(a)

a Only one component was extracted. The solution cannot be rotated.

PROMOTION PROGRAM SCALE ANALYSIS

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling


Adequacy.	.646
Bartlett's Test of Approx. Chi-Square Sphericity df	202,195 6
Sig.	.000

Communalities

Initial	Extraction
K1	1,000	.503
K2	1,000	.474
K3	1,000	.574
K04	1,000	.571

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial		Eigenvalues	Extraction Sums of Squared Loadings
Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	2.122	53,049	53,049	2.122	53,049	53,049
2	.924	23,105	76,154
3	.529	13,218	89,372
4	.425	10,628	100,000

Extraction Method: Principal Component Analysis.

Component Matrix(a)

Component
	1
K1	.709
K2	.688
K3	.758
K04	.755

Extraction Method: Principal Component Analysis. a 1 components extracted.

Rotated Component Matrix(a)

a Only one component was extracted. The solution cannot be rotated.

Appendix 5: MULTIPLE LINEAR REGRESSION ANALYSIS

( Theoretical model testing )

Regression

Variables Entered/Removed(b)

Model

Variables Entered

Variables Removed

Method

KMAI, TDO,

TOTAL, PRICE, CHANNEL, SIZE, TYPE(a)

Enter

a All requested variables entered. b Dependent Variable: THOAMAN

Model Summary

Model

R Square

Adjusted R Square

Std. Error of the Estimate

.548(a)

.300

.280

.26451

a Predictors: (Constant), KMAI, TDO, TTOAN, GIA, KENH, CLUONG, CLOAI

ANOVA(b)

Model

	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	7,258	7	1,037	14,820	.000(a)
	Residual	16,932	242	.070
	Total	24,190	249

a Predictors: (Constant), KMAI, TDO, TTOAN, GIA, KENH, CLUONG, CLOAI

b Dependent Variable: THOAMAN

Coefficients(a)

Model

	Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	1,383	.267		5.173	.000
	FAMILY	.166	.032	.284	5,233	.000
	SALARY	.125	.029	.232	4,245	.006
	CLASS	-.052	.028	-.102	-1.861	.064
	TDO	.081	.025	.183	3.319	.001
	CHANNEL	.147	.028	.291	5,329	.000
	TTOAN	.100	.024	.221	4,074	.000
	KMAI	.050	.029	.095	1,736	.084

a Dependent Variable: THOAMAN

Appendix 6: ANALYSIS OF VARIANCE BY AGE GROUP

Test of Homogeneity of Variances

Levene Statistic	df1	df2	Sig.
FAMILY	.142	2	247	.867
SALARY	.026	2	247	.974
CLASS	.510	2	247	.601
TDO	1,624	2	247	.199
CHANNEL	1,264	2	247	.284
TTOAN	.073	2	247	.930
KMAI	.009	2	247	.991

ANOVA

	Sum of Squares	Df	Mean Square	F	Sig.
FAMILY	Between Groups	.013	2	.006	.022	.978
	Within Groups	70,936	247	.287
	Total	70,949	249
SALARY	Between Groups	.301	2	.150	.446	.641
	Within Groups	83,177	247	.337
	Total	83,477	249
CLASS	Between Groups	.763	2	.382	1,027	.359
	Within Groups	91,768	247	.372
	Total	92,531	249
TDO	Between Groups	1,473	2	.736	1,505	.224
	Within Groups	120,836	247	.489
	Total	122,309	249
CHANNEL	Between Groups	.602	2	.301	.790	.455
	Within Groups	94,090	247	.381
	Total	94,692	249
TTOAN	Between Groups	.233	2	.116	.241	.786
	Within Groups	118,945	247	.482
	Total	119,177	249
KMAI	Between Groups	.909	2	.455	1,304	.273
	Within Groups	86,096	247	.349
	Total	87,005	249

Multiple Comparisons

Bonferroni

Dependent Variable

(I) DOTUOI	(J) DOTUOI	Mean Difference (IJ)	Std. Error	Sig.	95% Confidence Interval
						Lower Bound	Upper Bound
FAMILY	age(25-35)	age(36-45)	.0043	.07493	1,000	-.1763	.1849
		age(46-55)	-.0156	.09650	1,000	-.2483	.2170
	age(36-45)	age(25-35)	-.0043	.07493	1,000	-.1849	.1763
		age(46-55)	-.0199	.09522	1,000	-.2494	.2096
	age(46-55)	age(25-35)	.0156	.09650	1,000	-.2170	.2483
		age(36-45)	.0199	.09522	1,000	-.2096	.2494
SALARY	age(25-35)	age(36-45)	.0450	.08114	1,000	-.1505	.2406
		age(46-55)	.0965	.10450	1,000	-.1553	.3484
	age(36-45)	age(25-35)	-.0450	.08114	1,000	-.2406	.1505
		age(46-55)	.0515	.10310	1,000	-.1970	.3000
	age(46-55)	age(25-35)	-.0965	.10450	1,000	-.3484	.1553
		age(36-45)	-.0515	.10310	1,000	-.3000	.1970
CLASS	age(25-35)	age(36-45)	.0902	.08523	.873	-.1152	.2956
		age(46-55)	-.0499	.10976	1,000	-.3145	.2146
	age(36-45)	age(25-35)	-.0902	.08523	.873	-.2956	.1152
		age(46-55)	-.1401	.10830	.591	-.4012	.1209
	age(46-55)	age(25-35)	.0499	.10976	1,000	-.2146	.3145
		age(36-45)	.1401	.10830	.591	-.1209	.4012
TDO	age(25-35)	age(36-45)	.0846	.09780	1,000	-.1511	.3204
		age(46-55)	.2173	.12595	.257	-.0862	.5209
	age(36-45)	age(25-35)	-.0846	.09780	1,000	-.3204	.1511
		age(46-55)	.1327	.12427	.860	-.1668	.4323
	age(46-55)	age(25-35)	-.2173	.12595	.257	-.5209	.0862
		age(36-45)	-.1327	.12427	.860	-.4323	.1668
CHANNEL	age(25-35)	age(36-45)	.1037	.08630	.692	-.1043	.3117
		age(46-55)	.0917	.11114	1,000	-.1762	.3596
	age(36-45)	age(25-35)	-.1037	.08630	.692	-.3117	.1043
		age(46-55)	-.0120	.10966	1,000	-.2763	.2523
	age(46-55)	age(25-35)	-.0917	.11114	1,000	-.3596	.1762
		age(36-45)	.0120	.10966	1,000	-.2523	.2763
TTOAN	age(25-35)	age(36-45)	-.0660	.09703	1,000	-.2998	.1679
		age(46-55)	-.0509	.12496	1,000	-.3521	.2503
	age(36-45)	age(25-35)	.0660	.09703	1,000	-.1679	.2998
		age(46-55)	.0151	.12330	1,000	-.2821	.3123
	age(46-55)	age(25-35)	.0509	.12496	1,000	-.2503	.3521
		age(36-45)	-.0151	.12330	1,000	-.3123	.2821
KMAI	age(25-35)	age(36-45)	.0879	.08255	.864	-.1111	.2869
		age(46-55)	.1639	.10631	.374	-.0924	.4201
	age(36-45)	age(25-35)	-.0879	.08255	.864	-.2869	.1111
		age(46-55)	.0759	.10490	1,000	-.1769	.3288
	age(46-55)	age(25-35)	-.1639	.10631	.374	-.4201	.0924
		age(36-45)	-.0759	.10490	1,000	-.3288	.1769

Appendix 7: VARIANCE ANALYSIS BY REVENUE GROUP

Test of Homogeneity of Variances

Levene Statistic	df1	df2	Sig.
FAMILY	1,275	5	244	.275
SALARY	.482	5	244	.790
CLASS	1,836	5	244	.106
TDO	.842	5	244	.521
CHANNEL	1,162	5	244	.329
TTOAN	.218	5	244	.955
KMAI	2,086	5	244	.068

ANOVA

	Sum of Squares	df	Mean Square	F	Sig.
FAMILY	Between Groups	1,995	5	.399	1,412	.220
	Within Groups	68,954	244	.283
	Total	70,949	249
SALARY	Between Groups	1,272	5	.254	.755	.583
	Within Groups	82,206	244	.337
	Total	83,477	249
CLASS	Between Groups	.707	5	.141	.376	.865
	Within Groups	91,824	244	.376
	Total	92,531	249
TDO	Between Groups	1,502	5	.300	.607	.695
	Within Groups	120,807	244	.495
	Total	122,309	249
CHANNEL	Between Groups	2,087	5	.417	1,100	.361
	Within Groups	92,605	244	.380
	Total	94,692	249
TTOAN	Between Groups	7.006	5	1.401	3,048	.011
	Within Groups	112,172	244	.460
	Total	119,177	249
KMAI	Between Groups	.769	5	.154	.435	.824
	Within Groups	86,236	244	.353
	Total	87,005	249

Multiple Comparisons

Bonferroni

Dependent Variable

(I) Q3MH	(J) Q3MH	Mean Difference (IJ)	Std. Error	Sig.	95% Confidence Interval
						Lower Bound	Upper Bound
FAMILY SALARY	Revenue(10-15) Revenue (16-20) Revenue(21-25) Revenue(26-30) Revenue(31-35) Revenue > 35 Revenue(10-15) Revenue (16-20) Revenue(21-25)	Revenue (16-20) Revenue (21-25) Revenue(26-30) Revenue(31-35) Revenue > 35 Revenue(10-15) Revenue(21-25) Revenue(26-30) Revenue(31-35) Revenue > 35 Revenue(10-15) Revenue(16-20) Revenue(26-30) Revenue(31-35) Revenue > 35 Revenue(10-15) Revenue (16-20) Revenue(21-25) Revenue(31-35) Revenue > 35 Revenue(10-15) Revenue (16-20) Revenue (21-25) Revenue(26-30) Revenue > 35 Revenue(10-15) Revenue(16-20) Revenue(21-25) Revenue(26-30) Revenue(31-35) Revenue (16-20) Revenue (21-25) Revenue (26-30) Revenue (31-35) Revenue > 35 Revenue(10-15) Revenue(21-25) Revenue(26-30) Revenue(31-35) Revenue > 35 Revenue(10-15) Revenue (16-20)	-.1236	.10355	1,000	-.4306	.1833
			-.0951	.11095	1,000	-.4239	.2338
			-.1213	.12278	1,000	-.4852	.2427
			.1743	.14686	1,000	-.2610	.6097
			.0778	.18201	1,000	-.4618	.6173
			.1236	.10355	1,000	-.1833	.4306
			.0286	.09032	1,000	-.2392	.2963
			.0024	.10452	1,000	-.3075	.3122
			.2980	.13197	.373	-.0932	.6892
			.2014	.17023	1,000	-.3032	.7060
			.0951	.11095	1,000	-.2338	.4239
			-.0286	.09032	1,000	-.2963	.2392
			-.0262	.11185	1,000	-.3578	.3054
			.2694	.13785	.777	-.1392	.6780
			.1728	.17482	1,000	-.3454	.6910
			.1213	.12278	1,000	-.2427	.4852
			-.0024	.10452	1,000	-.3122	.3075
			.0262	.11185	1,000	-.3054	.3578
			.2956	.14754	.693	-.1418	.7330
			.1990	.18256	1,000	-.3422	.7402
			-.1743	.14686	1,000	-.6097	.2610
			-.2980	.13197	.373	-.6892	.0932
			-.2694	.13785	.777	-.6780	.1392
			-.2956	.14754	.693	-.7330	.1418
			-.0966	.19955	1,000	-.6881	.4950
			-.0778	.18201	1,000	-.6173	.4618
			-.2014	.17023	1,000	-.7060	.3032
			-.1728	.17482	1,000	-.6910	.3454
			-.1990	.18256	1,000	-.7402	.3422
			.0966	.19955	1,000	-.4950	.6881
			-.0364	.11306	1,000	-.3716	.2988
			-.0088	.12114	1,000	-.3680	.3503
			.0477	.13406	1,000	-.3497	.4451
			.2118	.16035	1,000	-.2635	.6872
			.1459	.19873	1,000	-.4432	.7350
			.0364	.11306	1,000	-.2988	.3716
			.0276	.09862	1,000	-.2648	.3199
			.0841	.11412	1,000	-.2542	.4224
			.2483	.14409	1,000	-.1789	.6754
			.1823	.18586	1,000	-.3686	.7333
			.0088	.12114	1,000	-.3503	.3680
			-.0276	.09862	1,000	-.3199	.2648

	Revenue(26-30)	.0565	.12212	1,000	-.3055	.4185
		Revenue(31-35)	.2207	.15051	1,000	-.2255	.6669
		Revenue > 35	.1548	.19088	1,000	-.4111	.7206
	Revenue(26-30)	Revenue(10-15)	-.0477	.13406	1,000	-.4451	.3497
		Revenue (16-20)	-.0841	.11412	1,000	-.4224	.2542
		Revenue(21-25)	-.0565	.12212	1,000	-.4185	.3055
		Revenue(31-35)	.1642	.16109	1,000	-.3134	.6417
		Revenue > 35	.0983	.19933	1,000	-.4926	.6892
	Revenue(31-35)	Revenue(10-15)	-.2118	.16035	1,000	-.6872	.2635
		Revenue (16-20)	-.2483	.14409	1,000	-.6754	.1789
		Revenue(21-25)	-.2207	.15051	1,000	-.6669	.2255
		Revenue(26-30)	-.1642	.16109	1,000	-.6417	.3134
		Revenue > 35	-.0659	.21788	1,000	-.7118	.5800
	Revenue > 35	Revenue(10-15)	-.1459	.19873	1,000	-.7350	.4432
		Revenue (16-20)	-.1823	.18586	1,000	-.7333	.3686
		Revenue(21-25)	-.1548	.19088	1,000	-.7206	.4111
		Revenue(26-30)	-.0983	.19933	1,000	-.6892	.4926
		Revenue(31-35)	.0659	.21788	1,000	-.5800	.7118
CLASS	Revenue(10-15)	Revenue (16-20)	-.0231	.11950	1,000	-.3773	.3311
		Revenue(21-25)	.0306	.12803	1,000	-.3489	.4102
		Revenue(26-30)	.0837	.14168	1,000	-.3363	.5038
		Revenue(31-35)	.0638	.16947	1,000	-.4386	.5662
		Revenue > 35	.1968	.21004	1,000	-.4259	.8194
	Revenue (16-20)	Revenue(10-15)	.0231	.11950	1,000	-.3311	.3773
		Revenue(21-25)	.0537	.10423	1,000	-.2553	.3627
		Revenue(26-30)	.1069	.12061	1,000	-.2507	.4644
		Revenue(31-35)	.0869	.15229	1,000	-.3645	.5384
		Revenue > 35	.2199	.19644	1,000	-.3624	.8022
	Revenue(21-25)	Revenue(10-15)	-.0306	.12803	1,000	-.4102	.3489
		Revenue (16-20)	-.0537	.10423	1,000	-.3627	.2553
		Revenue(26-30)	.0531	.12907	1,000	-.3295	.4357
		Revenue(31-35)	.0332	.15907	1,000	-.4384	.5047
		Revenue > 35	.1661	.20174	1,000	-.4319	.7642
	Revenue(26-30)	Revenue(10-15)	-.0837	.14168	1,000	-.5038	.3363
		Revenue (16-20)	-.1069	.12061	1,000	-.4644	.2507
		Revenue(21-25)	-.0531	.12907	1,000	-.4357	.3295
		Revenue(31-35)	-.0199	.17026	1,000	-.5246	.4848
		Revenue > 35	.1130	.21067	1,000	-.5115	.7375
	Revenue(31-35)	Revenue(10-15)	-.0638	.16947	1,000	-.5662	.4386
		Revenue (16-20)	-.0869	.15229	1,000	-.5384	.3645
		Revenue(21-25)	-.0332	.15907	1,000	-.5047	.4384
		Revenue(26-30)	.0199	.17026	1,000	-.4848	.5246
		Revenue > 35	.1330	.23028	1,000	-.5497	.8156
	Revenue > 35	Revenue(10-15)	-.1968	.21004	1,000	-.8194	.4259
		Revenue (16-20)	-.2199	.19644	1,000	-.8022	.3624
		Revenue(21-25)	-.1661	.20174	1,000	-.7642	.4319
		Revenue(26-30)	-.1130	.21067	1,000	-.7375	.5115
		Revenue(31-35)	-.1330	.23028	1,000	-.8156	.5497
TDO	Revenue(10-15)	Revenue (16-20)	.0514	.13706	1,000	-.3549	.4577
		Revenue(21-25)	.1007	.14685	1,000	-.3346	.5361

Research on factors affecting customer satisfaction when purchasing hair care cosmetics - 12

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