CHAPTER 4 EMPIRICAL RESULTS 4.1 Descriptive Statistics of Data There 249 survey questionnaires were recovered, of which 245 were valid, four invalid. The sample background information includes sex, age, educational level, etc., the specific distribution shown in Table 4.1. Project Subdivision project Number of samples Percentage Sex Man 124 50.61% Woman 121 49.39% 25 years old or below 70 28.57% Age 26-35years old 135 55.10% 36-45years old 23 9.39% 45 years of age and the older 17 6.94% High school / Secondary school or below 21 8.57% Educational level Undergraduate 155 63.27% Master 67 27.35% Dr. or above 2 0.82% Civil servants 8 3.27% Institutions 24 9.80% Occupation Employees 128 52.24% Self-employed 13 5.31% Students 46 18.78% Others 26 10.61% 3 years or the less 105 42.86% Working time 3-8 years 56 22.86% 8-15years 56 22.86% 15years or the more 28 11.43% Monthly income No income 49 20.00%
Hometown less than 10,000CNY 143 58.37% 10000-20000CNY 33 13.47% 20000-50000CNY 11 4.49% More than50000cny 9 3.67% the north in China (Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia) 174 71.02% the east in China (Shanghai, Shandong, Jiangsu, Anhui, Jiangxi, Zhejiang, 31 12.65% Fujian) the central in China (Hubei, Hunan, Henan) 13 5.31% the south in China (Guangdong, Guangxi, Hainan) 1 0.41% the Southwest (Chongqing, Sichuan, Guizhou, Yunnan, Tibet) the northwest (Shaanxi, Gansu, Ningxia, Xinjiang, Qinghai) 15 6.12% 3 1.22% the Northeast (Heilongjiang, Jilin, 8 3.27% Liaoning) Hong Kong, Macao and Taiwan regions 0 0.00% Table 4.1 the Sample Distribution From the above statistics can found: (1)The gender distribution of the sample objects in this study is balanced, with the proportion of men and women were 50.61%, 49.39%. (2)Among the samples, the young people from 26 to 35 years old were the most, it is accounted for 55.10% of the total samples. the youth is the mainstream consumer groups of consumer electronics and home appliances, their consumer awareness is relatively high. And they are the best survey group. (3)the consumers with education undergraduate degree are accounted for 63.27%, the consumers with master degree are accounted for 27.35%. All of this shows that the vast majority of the surveyed respondents are the people with relatively
high cultural level, they have strong consumer attitudes, their corporate social responsibility and awareness are relatively deep. (4)In the different occupations, the most is employees, it is accounted for 52.24%. About work experience, the consumers who just enter the community are accounted for 42.86%.about monthly income, 58.37% of the people is less than ten thousand. (5)On the regional scale, especially in North China, it is accounted for 71.02% of the total sample. Followed by the East in China, it is accounted for 12.65% of the overall sample, in other regions, there is a small amount of distribution. All the samples are distributed in a wide range, so the results of the study can avoid the influence of some accidental factors that caused by the single sample constitution, and make the results of the study have more general application significance. For the choice of enterprises, basically it concentrated in these companies like Huawei, Apple, Haier. The main reason is that these enterprises have the high visibility, consumers have more opportunities to contact with them, while the related reports from media are more, so a number of consumers selected them for evaluation of the object. The details are shown in Table 4.2. Options Total Proportion Huawei 102 41.63% Samsung 17 6.94% Apple 38 15.51% Lenovo 16 6.53% Canon 1 0.41% Nikon 0 0% Siemens 4 1.63% Sony 3 1.22%
Dell 3 1.22% Haier 26 10.61% Gree 9 3.67% Midea 13 5.31% Others(please note) 13 5.31% Table 4.2 the evaluated enterprises distribution 4.2 Reliability Analysis The tables of each statistical results in this chapter are obtained from SPSS19.0. The result of each analysis is shown below. 4.2.1 Independent Variable Reliability (1)Safeguarding the Interests of Consumers Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables Reliability statistics Based on standardized items The number of items.892.895 4 From the data on the table above, it could be found that the contents of the questionnaire is valid, numerical is 0.892,greater than 0.7, and it is within the scope of credibility, so its reliability meet the requirements. (2)Protecting the Rights and Interests of Employees
Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables Reliability statistics Based on standardized items The number of items.921.921 4 From the data on the table above, it could be found that the contents of the questionnaire is valid, numerical is 0.921,greater than 0.9, and it is within the scope of credibility, so its reliability meet the requirements. (3) Protecting the Environment Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables Reliability statistics Based on standardized items The number of items.945.945 4 From the data on the table above, it could be found that the contents of the
questionnaire is valid, numerical is 0.945,greater than 0.9, and it is within the scope of credibility, so its reliability meet the requirements. (4)Charity Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables Reliability statistics Based on standardized items The number of items.936.936 2 From the data on the table above, it could be found that the contents of the questionnaire is valid, numerical is 0.936,greater than 0.9, and it is within the scope of credibility, so its reliability meet the requirements. 4.2.2 Intermediary Variable Reliability (1)the specification of consumer competent Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables
Reliability statistics Based on standardized items The number of items.924.924 3 From the data on the table above, it could be found that the contents of the questionnaire is valid, numerical is 0.924,greater than 0.9, and it is within the scope of credibility, so its reliability meet the requirements. (2)Consumer s Attitudes Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables Reliability statistics Based on standardized items The number of items.963.963 5 From the data on the table above, it could be found that the contents of the questionnaire is valid, numerical is 0.963,greater than 0.9, and it is within the scope of credibility, so its reliability meet the requirements. 4.2.3 Dependent Variable Reliability Consumer Purchase Behavior
Case processing summary N % Case Effective 245 100.0 Exclusive a 0.0 Total 245 100.0 a. In this program, the list of tables are deleted based on all variables. Reliability statistics Based on standardized items The number of items.936.936 3 From the data on the table above, it could be found that the contents of the questionnaire is valid, numerical is 0.936,which is higher than 0.9, and it is within the scope of credibility, so its reliability meet the requirements. 4.3 Validity Analysis and Factor Analysis 4.3.1 Independent Variable The test of KMO and Bartlett Kaiser-Meyer-Olkin was sampled with sufficient measure.941 Approximate chi-square 3248.344 The spherical inspection of df 91 Bartlett Sig..000 From the data on the table above, it could be found that the value of KMO about social responsibility scale is 0.941> 0.5, the P value of the chi-square statistic about Bartlett sphericity test is 0.000<0.01, it is quite significant (compared with the level about 1% ), that is to say, the data is well suited for factor analysis. The following is factor analysis: firstly, the principal component method was used to extract the 14 items of CSR, the factor that characteristic value is greater than 1 will be extracted. And then use the maximum variance method (orthogonal rotation) to obtain the each factor s load value. The results of the matrix and total variance interpretation about the factorial load matrix are shown on the table below.
The total variance of explain Ingre dients Total Initial eigenvalue The square and load of extract The square and load of rotate Variance Cumulative Variance Cumulative Variance Total Total % % % % % Cumulative % 1 9.046 64.611 64.611 9.046 64.611 64.611 5.956 42.543 42.543 2 1.189 8.493 73.105 1.189 8.493 73.105 4.279 30.562 73.105 3.789 5.639 78.744 4.664 4.746 83.490 5.411 2.937 86.426 6.312 2.231 88.657 7.305 2.179 90.836 8.250 1.783 92.619 9.215 1.536 94.156 10.201 1.436 95.591 11.190 1.360 96.951 12.169 1.206 98.158 13.157 1.120 99.278 14.101.722 100.000 Extraction method: the principal component analysis. From the data on the table above, it could be found that there are two terms of initial eigenvalue which the total is greater than one. They are 9.046 and 1.189. Therefore, 14 factors can be divided into two components.
The Rotate Component Matrix a The enterprises are committed to providing environmental products or services The enterprises are actively involved in environmental governance and protection The evaluation about company's environmental protection the enterprises try their best to minimize environmental pollution in the production. The enterprises focus on the product which environmental protection of raw materials and packaging are done well. The enterprises often provide a variety of assistance to vulnerable groups in the society The evaluation about the enterprise s charity the enterprise often support charitable donations and various types of charitable activities. The enterprises improve the career management for their staffs. The enterprises provide employees with a safe working environment and good working conditions The evaluation about the protection of enterprises-employees rights and interests. The enterprises provide employees with the good pay and benefits. The enterprises did not make false advertising, do not exaggerate the effectiveness of their products and services. The evaluation about the safeguard the interests of consumers the enterprises can provide consumers with the safe qualified products and good service. The enterprises can quickly deal with consumers complaints and returns requirements. Ingredients 1 2.829.319.820.295.819.313.798.363.765.289.758.297.749.376.653.505.643.569.275.847.258.828.357.795
The enterprises will not disclose or illegally use consumer's personal information. The enterprises pay attention to the staffs professional ethics. Extraction method: the principal component. Rotation Method: a Kaiser standardized orthogonal rotation method..377.729.563.634 a. The rotation weaken after three iterations. From the rotate component matrix above, it could be found that there are three factors whose load values in different factors variable(dimensions) are greater than 0.5(red words), therefore, there are three factors repeated, the repeated factors need to be removed. The excluding independent variables: The test of KMO and Bartlett Kaiser-Meyer-Olkin was sampled with sufficient measure.926 Approximate chi-square 2366.904 The spherical inspection of df 55 Bartlett Sig..000 From the data on the table above, it could be found that the value of KMO about social responsibility scale is 0.926> 0.5, the P value of the chi-square statistic about Bartlett sphericity test is 0.000<0.01, it is quite significant (compared with the level about 1% ), that is to say, the data is well suited for factor analysis. The following is factor analysis: firstly, the principal component method was used to extract the 11 items of CSR, the factor that characteristic value is bigger than 1 will be extracted. And then use the maximum variance method (orthogonal rotation) to obtain the each factor s load value. The results of the matrix and total variance interpretation about the factorial load matrix are shown on the table below.
The total variance of explain Initial eigenvalue The square and load of extract The square and load of rotate Ingre Variance Cumulative Variance Cumulative Variance Cumulative dients Total % % Total % % Total % % 1 7.055 64.133 64.133 7.055 64.133 64.133 4.911 44.641 44.641 2 1.172 10.653 74.786 1.172 10.653 74.786 3.316 30.145 74.786 3.778 7.072 81.858 4.399 3.630 85.488 5.384 3.491 88.979 6.284 2.578 91.556 7.266 2.414 93.970 8.206 1.871 95.841 9.179 1.627 97.469 10.166 1.509 98.978 11.112 1.022 100.000 Extraction method: the principal component analysis. From the data on the table above, it could be found that there are two terms of initial eigenvalue which the total is greater than one. They are 7.055 and 1.172. Therefore, 11 factors can be divided into two components.
The Rotate Component Matrix a The enterprises are committed to providing environmental products or services The enterprises are actively involved in environmental governance and protection The evaluation about company's environmental protection the enterprises try their best to minimize environmental pollution in the production. The enterprises focus on the product which environmental protection of raw materials and packaging are done well. The enterprises often provide a variety of assistance to vulnerable groups in the society The evaluation about the enterprise s charity the enterprise often support charitable donations and various types of charitable activities. The enterprises improve the career management for their staffs. Ingredients 1 2.842.322.831.303.828.309.808.361.770.295.759.300.745.334 The enterprises did not make false advertising, do not exaggerate the effectiveness of their products and services. The evaluation about the safeguard the interests of consumers the enterprises can provide consumers with the safe qualified products and good service. The enterprises can quickly deal with consumers complaints and returns requirements. The enterprises will not disclose or illegally use consumer's personal information Extraction method: the principal component. Rotation Method: a Kaiser standardized orthogonal rotation method.284.846.270.832.375.809.392.738
The Rotate Component Matrix a The enterprises are committed to providing environmental products or services The enterprises are actively involved in environmental governance and protection The evaluation about company's environmental protection the enterprises try their best to minimize environmental pollution in the production. The enterprises focus on the product which environmental protection of raw materials and packaging are done well. The enterprises often provide a variety of assistance to vulnerable groups in the society The evaluation about the enterprise s charity the enterprise often support charitable donations and various types of charitable activities. The enterprises improve the career management for their staffs. Ingredients 1 2.842.322.831.303.828.309.808.361.770.295.759.300.745.334 The enterprises did not make false advertising, do not exaggerate the effectiveness of their products and services. The evaluation about the safeguard the interests of consumers the enterprises can provide consumers with the safe qualified products and good service. The enterprises can quickly deal with consumers complaints and returns requirements. The enterprises will not disclose or illegally use consumer's personal information Extraction method: the principal component. Rotation Method: a Kaiser standardized orthogonal rotation method.284.846.270.832.375.809.392.738 a. The rotation weaken after three iterations.
From the total variance of the explain on the table above, it could be found that there two factors with Eigen values greater than one were extracted in total. The two components of the total variance are account for 74.786% >50%, in a word, the content validity is higher. From the Rotate Component Matrix on the table above, we can found that the factor-load-value in the matrix is greater than 0.5(blue words),they all were concentrate on the same factor variable (dimension),while other factor-load-value in the matrix is less than 0.5. In summary description, the original four dimensions of corporate social responsibility(safeguarding the interests of consumers, protecting the rights and interests of employees, protecting the environment, charity), the division of the dimensions after analyzing the data is inconsistent, so the scale of the structural validity need to be corrected. Therefore, the independent variables of corporate social responsibility was divided into two dimensions to study, they are charity and safeguarding the interests of consumers. Charity includes the following aspects: The enterprises are committed to providing environmental products or services; The enterprises are actively involved in environmental governance and protection; The enterprises focus on the product which environmental protection of raw materials and packaging are done well; The enterprises often provide a variety of assistance to vulnerable groups in the society; The enterprise often support charitable donations and various types of charitable activities, and the enterprises improve the career management for their staffs. Safeguarding the interests of consumers includes the following aspects: The enterprises did not make false advertising, do not exaggerate the effectiveness of their products and services; The enterprises can provide consumers with the safe qualified products and good service; The enterprises can quickly deal with consumers complaints and returns requirements; The enterprises will not disclose or illegally use
consumer's personal information. 4.3.2 Intermediate Variable (1)The regression analysis of consumer's subjective norm The test of KMO and Bartlett Kaiser-Meyer-Olkin was sampled with sufficient measure.760 Approximate chi-square 558.374 The spherical inspection of Bartlett df 3 Sig..000 From the data on the table above, it could be found that the value of KMO about consumer's subjective norm is bigger than 0.5, the value of the chi-square statistic about Bartlett is quite significant, that is to say, the data is well suited for factors analysis. The following is factor analysis: because there only one factor that characteristic value is bigger than one, so it will be extracted. The total variance of explain Ingredients Initial Eigen value The square and load of extract Total Variance % Cumulative % Total Variance % Cumulative % 1 2.605 86.833 86.833 2.605 86.833 86.833 2.225 7.490 94.324 3.170 5.676 100.000 Extraction method: the principal component analysis. From the data on the table above, it could be found that the factors of consumer purchase behavior scale for its interpretation of the total variance were 86.833%, this indicate that the data has a good structural validity. (2)Consumer s Attitudes The test of KMO and Bartlett Kaiser-Meyer-Olkin was sampled with sufficient measure.914 The spherical inspection of Bartlett Approximate chi-square 1460.764 df 10 Sig..000 From the data on the table above, it could be found that the value of KMO about
consumer's attitudes is bigger than 0.5, the value of the chi-square statistic about Bartlett is quite significant, that is to say, the data is well suited for factors analysis. The following is factor analysis: because there only one factor that characteristic value is bigger than one, so it will be extracted. The total variance of explain Ingredients Initial Eigen value The square and load of extract Total Variance % Cumulative % Total Variance % Cumulative % 1 4.362 87.241 87.241 4.362 87.241 87.241 2.229 4.580 91.821 3.178 3.554 95.375 4.124 2.476 97.852 5.107 2.148 100.000 Extraction method: the principal component analysis. From the data on the table above, it could be found that the factors of consumer purchase behavior scale for its interpretation of the total variance were 87.241%, this indicate that the data has a good structural validity. 4.3.3 Dependent Variable The test of KMO and Bartlett Kaiser-Meyer-Olkin was sampled with sufficient measure.770 Approximate chi-square 621.723 The spherical inspection of df 3 Bartlett Sig..000 From the data on the table above, it could be found that the value of KMO about consumer's attitudes is bigger than 0.5, the value of the chi-square statistic about Bartlett is quite significant, that is to say, the data is well suited for factors analysis. The following is factor analysis: because there only one factor that characteristic value is bigger than one, so it will be extracted.
The tot al variance of explain Ingredients Initial Eigen value The square and load of extract Total Variance % Cumulative % Total Variance % Cumulative % 1 2.660 88.674 88.674 2.660 88.674 88.674 2.174 5.793 94.467 3.166 5.533 100.000 Extraction method: the principal component analysis. From the data on the table above, it could be found that the factors of consumer purchase behavior scale for its interpretation of the total variance were 88.674%, this indicate that the data has a good structural validity. 4.4 Regression Analysis In this paper, this paper turns on analysis each regression to reveal the relationship between variables. In the following analysis, if the independent variables are corporate social responsibility, then I will use multiple linear regression to analysis. Because corporate social responsibility has two dimensions, that is to say there are two independent variables. While if the independent variables are consumer's subjective norm or consumer attitudes, then I will use a linear regression analysis, because both of them have the only one dimension, that is to say there is one independent variables. For regression analysis of multiple linear regression, we need to verify whether the data exists multi-collinearity and serial correlation problem, and then determining whether the data suitable for multiple linear regression analysis. However, for the linear regression analysis, there is no multi-collinearity and sequence correlation, so there is no need to test. For the analysis of direct effects, the forcible entry method will be used. 4.4.1 Regression analysis of corporate social responsibility and consumer purchase behavior From the tables of model summation and coefficient, it could be found that the value of model Durbin-Watson is near two. There is no auto-correlation of residuals, it
indicate that there is no sequence correlation problem; And their VIF values are between 0-10, this indicate that the regression model and data fitting degree are better, there is no multi-collinearity problem. To sum up, the data suitable for multiple regression analysis. Model Summary b Model R R -squared Adjusted R-squared Standard error of estimate Durbin-Watson 1.705 a.497.492.71239775 1.800 a. Predictors: (Constant), REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 2 Anova b Model Sum Of Square df Mean Square F Sig. 1 Return 121.182 2 60.591 119.389.000 a Residual 122.818 242.508 Total 244.000 244 a..predictors: (Constant), REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 4 As it can be seen from the two tables above, the overall fit coefficient (R) was 0.705, the determination coefficient(r -squared) was 0.497, the correction coefficient (adjusted R-squared) was 0.492. It Indicate that the data which regression equation can explain the total variance was 49.2%, sig was 0.000<0.05. It shows that the two components significantly explained the dependent variable.
Coefficient a Non - normalized Standard Collinearity Model coefficient Standard B deviation coefficient Trial version t Sig. statistics Tolerance VIF 1 (Constant) 9.984E-17.046.000 1.000 REGR factor score 1 for analysis 2 REGR factor score 2 for analysis 2.633.046.633 13.870.000 1.000 1.000.311.046.311 6.812.000 1.000 1.000 a. Dependent variable: REGR factor score 1 for analysis 4 As it can be seen from the table, the regression coefficients of independent variables are:0.633 and 0.311,they are significant, and can enter the regression equation. That is to say; charity (X 1 ),safeguarding the interests of consumers(x 2 ),the influence coefficient of consumers' purchasing behavior are followed by 0.633, 0.311.They are significant, and have directly positive effects. Charity (X 1 ) the impact of consumer purchase behavior is greater than the impact of safeguarding the interests of consumers(x 2 )on consumers purchase behavior. Therefore, the regression equation of the relationship between corporate social responsibility and consumer behavior :Y=0.633X 1 +0.311X 2 +9.984E-17 4.4.2 Regression analysis of corporate social responsibility and consumer's subjective norm From the tables of model summation and coefficient, we can found that the value of model Durbin-Watson is near two. There is no auto-correlation of residuals, it indicate that there is no sequence correlation problem; And their VIF values are between 0-10, this indicate that the regression model and data fitting degree are better, there is no multi-collinearity problem. To sum up, the data suitable for multiple regression analysis.
Model Summary b Model R R -squared Adjusted R-squared Standard error of estimate Durbin-Watson 1.742 a.550.547.67335660 2.022 a..predictors: (Constant), REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 3 Anova b Model Sum Of Square df Mean Square F Sig. 1 Return 134.275 2 67.137 148.073.000 a Residual 109.725 242.453 Total 244.000 244 a. Predictors: (Constant), REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 3 As it can be seen from the two tables above, the determination coefficient (adjusted R -squared) was 0.547, it Indicate that the data which regression equation can explain the total variance was 54.7%, sig was 0.000<0.05. It shows that the two components significantly explained the intermediate variable(subjective norms). Coefficient a Non - normalized Standard Collinearity Model coefficient Standard B deviation coefficient Trial version t Sig. statistics Tolerance VIF 1 (Constant) 2.851E-16.043.000 1.000 REGR factor score 1 for analysis 2 REGR factor score 2 for analysis 2.573.043.573 13.289.000 1.000 1.000.471.043.471 10.934.000 1.000 1.000 a. Dependent: REGR factor score 1 for analysis 3 As it can be seen from the table, the regression coefficients of independent
variables are:0.573 and 0.471,they are significant, and can enter the regression equation. That is to say; charity (X 1 ),safeguarding the interests of consumers(x 2 ),the influence coefficient of consumers' purchasing behavior are followed by 0.573, 0.471.They are significant, and have directly positive effects. Charity (X 1 ) for the impact of consumer's subjective norm is greater than the impact of safeguarding the interests of consumers(x 2 )on consumer's subjective norm. Therefore, the regression equation of the relationship between corporate social responsibility and consumer's subjective norm:m 1 =0.573X 1 +0.471X 2 +2.851E-16. 4.4.3 Regression analysis of corporate social responsibility and consumer attitude From the tables of model summation and coefficient, it could be found that the value of model Durbin-Watson is near two. There is no auto-correlation of residuals, it indicate that there is no sequence correlation problem; And their VIF values are between 0-10, this indicate that the regression model and data fitting degree are better, there is no multi-collinearity problem. To sum up, the data suitable for multiple regression analysis. Model Summary b Model R R -squared Adjusted R-squared Standard error of estimate Durbin-Watson 1.767 a.588.584.64485669 1.965 a. Predictors: (Constant), REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 2 Anova b Model Sum Of Square df Mean Square F Sig. 1 Return 143.367 2 71.683 172.382.000a Residual 100.633 242.416 Total 244.000 244
Model Summary b Model R R -squared Adjusted R-squared Standard error of estimate Durbin-Watson 1.767 a.588.584.64485669 1.965 a. Predictors: (Constant),REGR factor score 2 for analysis 2, REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 2 As it can be seen from the two tables above, the determination coefficient(adjusted R-squared) was 0.584, it Indicate that the data which regression equation can explain the total variance was 58.4%, sig was 0.000<0.05. It shows that the two components significantly explained the intermediate variable(consumer attitude). Coefficient a Non - normalized Standard Model coefficient Standard B deviation coefficient Trial version t Sig. 1 (Constant) 3.073E-16.041.000 1.000 REGR factor score analysis 2 REGR factor score analysis 2 1 for 2 for.611.041.611 14.796.000.463.041.463 11.218.000 a. Dependent variable REGR factor score 1 for analysis 2 As it can be seen from the table, the regression coefficients of independent variables are:0.611and 0.463, they are significant, and they all go through the regression equation. That is to say; charity (X 1 ),safeguarding the interests of consumers(x 2 ),the influence coefficient of consumers' purchasing behavior are followed by 0.611, 0.463.They are significant, and have directly positive effects. Charity (X 1 ) for the impact of consumer's attitude is greater than the impact of safeguarding the interests of consumers(x 2 )on consumer's attitude. Therefore, the
regression equation of the relationship between corporate social responsibility and consumer's attitude :M 2 =0.611X 1 +0.463X 2 +3.073E-16. 4.4.4 The regression analysis of consumer's subjective norm and consumer's purchase behavior Model Summary Model R R -squared Adjusted R-squared Standard error of estimate 1.791 a.626.624.61281912 a. Predictors: (Constant), REGR factor score 1 for analysis 3. Anova b Model Sum Of Square df Mean Square F Sig. 1 Return 152.742 1 152.742 406.718.000 a Residual 91.258 243.376 Total 244.000 244 a. Predictors: (Constant), REGR factor score 1 for analysis 3. b. Dependent variable: REGR factor score 1 for analysis 2 As it can be seen from the two tables above, the determination coefficient (adjusted R -squared) was 0.624, it Indicate that the data which regression equation can explain the total variance was 62.4%.
Coefficient a Non - normalized Standard Model coefficient Standard B deviation coefficient Trial version t Sig. 1 (Constant) -1.099E-16.039.000 1.000 REGR factor score analysis 3 1 for.791.039.791 20.167.000 a. Dependent variable: REGR factor score 1 for analysis 2 As can be seen from the table, the regression coefficients of independent variables are:0.791, they are significant, and they all go through the regression equation. That is to say; the impact of consumer's subjective norm(m1) have directly positive effects on consumer's purchase behavior. Therefore, the regression equation of the relationship between consumer's subjective norm and consumer's purchase behavior: Y=0.791M 1-1.099E-16. 4.4.5 The regression analysis of consumer attitudes and consumer purchase behavior Model Summary Model R R -squared Adjusted R-squared e 1.806 a.649.648.59342509 a. Predictors: (Constant), REGR factor score 1 for analysis 2. Anova b Model Sum Of Square df Mean Square F Sig. 1 Return 158.427 1 158.427 449.880.000 a Residual 85.573 243.352 Total 244.000 244
Model Summary Model R R -squared Adjusted R-squared e 1.806 a.649.648.59342509 a. Predictors: (Constant), REGR factor score 1 for analysis 2. b. Dependent variable: REGR factor score 1 for analysis 2 As it can be seen from the two tables above, the determination coefficient (adjusted R-squared) was 0.648, it Indicate that the data which regression equation can explain the total variance was 64.8%. Coefficient a Non - normalized Standard Model coefficient Standard B deviation coefficient Trial version t Sig. 1 (Constant) -1.325E-16.038.000 1.000 REGR factor score analysis 2 1 for.806.038.806 21.210.000 a..dependent variable: REGR factor score 1 for analysis 2 As can be seen from the table, the regression coefficients of independent variables are:0.806, they are significant, and they all go through the regression equation. That is to say; the impact of consumer's attitudes(m2) have directly positive effects on consumer's purchase behavior. Therefore, the regression equation of the relationship between consumer's attitudes and consumer's purchase behavior: Y=0.806M 2-1.325E-16. 4.5 Research hypothesis validation results In this study, the independent variables of corporate social responsibility related to the following dimensions: safeguarding the interests of consumers, protecting the rights and interests of employees, protecting the environment, charity. Each
dimension is designed multiple problems, through the validity analysis of the recovery data, I found a suitable dimension for the study of my paper-charity and safeguarding the interests of consumers. So I will change the four original dimensions as the two dimensions. Hypothesis H1:Corporate social responsibility has the direct positive impact on consumer purchasing behavior. H1-1:Enterprises have the direct positive impact on protection consumer rights and interests of the consumer purchase behavior. H1-2:Corporate commitment about public welfare has a direct positive impact on consumer buying behavior. H2:Corporate social responsibility has a positive impact on consumer subjective norms. H2-1:Corporate responsibility has a positive impact about protecting consumers rights and interests on subjective norms. H2-2:Corporate responsibility for public welfare has a positive impact on consumer subjective norms. H3:Consumer subjective norms have a positive impact on consumer buying behavior. H4:Corporate social responsibility has a positive impact on consumer attitudes. H4-1:Corporate responsibility about protecting consumer interests has a positive impact on consumer attitudes. H4-2:Corporate responsibility about protecting the rights and interests of employees has a positive impact on consumer attitudes. H5:Consumer attitudes have a positive impact on consumer buying behavior. Validation results Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant