Investigation of the characteristics charity contribution by Jaguar Cars Employees

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Executive Summary

Many companies participate in Corporate Social Responsibilities so as to improve their public image thereby helping them retain their customers and government favours. In this report the findings of a research that was carried out by Jaguar Cars to find out how people contribute to charities are presented. The study mainly focused on Jaguar employees as the participants.

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Introduction

This report presents the findings of a research that was carried out by Jaguar Cars to find out how people contribute to two charities funds: medical research fund, and children and young people research fund. The data was collected from 281 Jaguar employees. The data analysis was carried out using the following statistical methods: descriptive statistics, One Way ANOVA, linear regression and chi-square test. The results of the study are presented below.

Findings of the study

The data collected in this study were analysed using a number of statistical tools such as descriptive statistics, Anova analysis, linear regression, and Chi Square test.

Descriptive Statistics

Descriptive statistics tool was used to organize and have a basic understanding of the data collected by the questionnaires (Kohli, 2014). Here central tendencies such as medium and mean, pie charts and frequencies were used. The results of the descriptive statistics analysis that was carried out is shown in the tables and figures below. The discussion of the results have also been provided below each or figure or both.

Descriptive statistics of medical research and children funds data

Table 1 and figure 1 below shows a summary of response by respondents with respect to their donation towards medical research. The results show that quite a number of people do not contribute towards medical research.

Table 1a: Measure of central tendencies

Statistics
Fund_MR
N Valid 231
Missing 0
Mean .32
Median .00
Mode 0
Sum 74

Table 1b: Proportion of respondents donating towards medical research fund

Medical Research fund SPSS output result
  Frequency Percent Valid Percent Cumulative Percent
Valid No 157 68.0 68.0 68.0
Yes 74 32.0 32.0 100.0
Total 231 100.0 100.0  

Proportion of those who donated for Children and Young people

In order to get the proportion of the participants who donated for children and Young people, descriptive statistics of the data was done. The results are shown in tables 2 and figure 2 below.

Table 2: Proportion of respondents donating towards children and young people fund

Children and Young People Fund
  Frequency Percent Valid Percent Cumulative Percent
Valid No 148 64.1 64.1 64.1
Yes 83 35.9 35.9 100.0
Total 231 100.0 100.0  

Interpretation of the results

From table 1b and figure 1, it is observed that only 32% percent of the employees contributed towards medical research fund, while rest did not. From table 2 and figure, it is observed that only 35.9% percent of the employees contributed towards children and young people fund, while rest did not. This does not mean rest who do not contribute towards medical research contribute towards children and young people and vice versa. Some of the employees may contribute to both children and young people fund and medical research fund, while others may not contribute towards for all the two charity. Failure by some employees not contributing towards the charities may be due to a number of reasons, one being unwillingness and the other being lack of knowledge. That is, some participants may be unwilling to contribute towards the charity while may not understand the reasons for these contributions.

From table 1a above, it is observed that mean of the data is 0.32 and medium is 0. This mean has no meaning as data were divided into 1s and 0s where 1 represented a YES correspondence and 0 represented a NO correspondence.

Amount to be donated by the employees

In order to get the general understanding on how people usually contribute towards these charities, descriptive statistics analysis of the survey data was done, the results are shown in table 3 below. The analysis was done in SPSS (IBM SPSS 22). It is important to note that the results have been slightly modified to include only relevant information.

Table 3: Employees’ contributions

Range of donation Frequency/ Number of Respondents Percent Cumulative Percent  
1 0 50 21.6 21.6  
2 1 – 5 73 31.6 53.2  
3 6 – 10 42 18.2 71.4  
4 11 – 15 11 4.8 76.2  
5 16 – 20 18 7.8 84.0  
6 21 – 25 17 7.4 91.3  
7 26 – 30 9 3.9 95.2  
8 31 – 35 4 1.7 97.0  
9 36 – 40 7 3.0 100.0  
10 Total 231 100.0    

Table 4: Mean and mode of Money donation and children fund

Statistics
  Children Fund Money donation
N Valid 231 231
Missing 0 0
Mean .36 3.10
Median .00 2.00
Mode 0 2
Sum 83 716

Interpretation of the results

From table 4 it is observed that mode of the donation is 2. From table 3 the 2 corresponds to £1 – £5 class.  This is also observed in figure 3.This means that most of those who were surveyed contributed between £1 and £5. This was followed by those who did not contribute anything, while those who contributed between £31 and £35 contributed the least (see figure 3 for a clearer picture). The mean of contributions was 3.1 which lies within £6 – £10 class (see figure 3 and table 4). It may therefore be concluded that mean contribution lies between £6 and £10.

Reasons for contributions

In order to identify the most important reasons for charity contributions, a seven scale linkert chart was used in the study. The scale was 1 to 7 (1 being strongly disagree with the statement and 7 being strongly agree with the statement). The reasons that were gauged on this linkert chart were as follows:

  • “I feel uplifted when I help others/support worthy causes”
  • “It is in line with my ethical beliefs or religious beliefs”
  • “I am genuinely concerned about the particular causes that I support”
  • “To help make the world a better place”
  • “I can afford to give money to charity”

A descriptive statistics was carried out to understand how the respondents answered the questions. Table 5 below shows the results of this descriptive analysis. The table is an extract from SPSS software since the analysis was carried in the spss.

Table 5: Descriptive statistics results for reasons for contribution

Reason for charity Uplifted/Worthy course Ethical/religious belief Concerned genuinely Make world better Afford
N Valid 231 231 231 231 231
Missing 0 0 0 0 0
Mean 4.46 3.95 5.41 4.33 3.61
Median 5.00 4.00 6.00 4.00 3.00
Mode 5 1 7 4 1
Std. Deviation 1.771 2.248 1.811 1.988 2.021
Sum 1031 913 1250 1000 833

Interpretation of the results

From the above descriptive statistics results above (table 5) it observed that most of those who contributed to the charity were genuinely concerned. These reason had mode of value 7 (see table 5 above). Being uplifted was second reason as to why some people contributed (it had a mode value of 5). Further from table 5 it is observed that the least reasons as to why people contributed towards charity were because of religious beliefs and because they could afford. These reasons had a mode of value of 1. Meaning that they did not contribute because they could afford nor because of their ethical or religious beliefs.

Place of data collection

In order to understand how data were collected in various places, descriptive statistics was done on the “place data. The result of this analysis is shown in table 6 below.

Table 6: Place of data collection

  Frequency Percent Valid Percent Cumulative Percent
Valid 1 93 40.3 40.3 40.3
2 81 35.1 35.1 75.3
3 57 24.7 24.7 100.0
Total 231 100.0 100.0  

Key:

1 = Coventry, 2 = Warwick, 3 = Wolverhampton

Interpretation of the data

From table 6 above, it can be observed that most of data (40.3%) were collected from Coventry and the least data were collected from Wolvehampton.

Chi-Square Test

Chi-Square test was performed so understand if there is relationship between level of education and amount collected for medical research. Chi-square test was used in this analysis because the two variables are categorical in nature. The following two hypotheses were developed to explore this if indeed a relationship exists between these variables. The two hypotheses are stated below.

  • Null Hypothesis (H0): There is no relationship between amount collected for medical research and level of education.
  • Hypothesis 1 (H1): There is a relationship between amount collected for medical research and level of education. That is, the amount of money collected on medical research depended on level of education.

Note: In order to perform the chi-square test on the variables, it was assumed the each of the correspondents was counted once and the data was randomly collected; and hence all observations were independent. The results of performing this test are shown in table 6 (cross tabulation table) and table 7 (Chi-square test table).

Table 6: Cross tabulation of Medical research fund and Level of Educatin

Fund_MR * Education Cross-tabulation
Count
  Education Total
Secondary College Bachelors MSc/PhD
Medical Research Fund No 25 44 56 32 157
Yes 17 21 22 14 74
Total 42 65 78 46 231

Table 7: Chi-Square Test results

Chi-Square Tests
  Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 1.956a 3 .582
Likelihood Ratio 1.916 3 .590
Linear-by-Linear Association 1.257 1 .262
N of Valid Cases 231    
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 13.45.

Interpretation of the Chi-square test results

The findings of Chi-Square test analysis in table 5 satisfies the chi-square test condition that the expected frequency on any cell should always be equal or greater than 5 (Elliott & Woodward, 2014). The minimum expected count in this condition was 13.45. From the table 7 it is observed that Pearson chi-square value is 1.956 and 3 degrees of freedom, the p value (statistical significance) is 0.582 which is greater than 0.05. Since the value of P is greater than 0.05, there is no significant relationship between level of education and amount of money collected for medical research. This, therefore, means that the null hypothesis (H0) is accepted, while the alternative hypothesis (H1) rejected.

This result has also been supported by the cross tabulation analysis of level of education data and research fund data in table 6. It is observed that those whose level of education is MSc and PhD contributed the least (only 14 out 46, 30%); those with secondary education only 17 out 42 (40%) contributed; those with bachelors only 22 out of 78 (28%) contributed; and those with college degrees only 21 out of 65 (32%) contributed.

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One Way ANOVA test

One Way ANOVA test was carried on the data to establish if there is any mean difference making world a better place and feeling uplifted, and also if the is mean difference between genuine concern and making world a better place. Since variables that were to be used in test were all continuous were all continuous, One Way ANOVA analysis was selected (Kohli, 2014). As a result the following hypotheses were established and tested.

  • Null hypothesis 1 (H0) = There is mean difference between making world a better place and feeling uplifted when helping others.
  • Alternative hypothesis 1 (H1) = There is no mean difference between making world a better place and feeling uplifted when helping others.
  • Null hypothesis 2 (H0) = There is mean difference between making world a better place and genuine concern.
  • Alternative hypothesis 2 (H0) = There is no mean difference between making world a better place and genuine concern.

The results of One Way ANOVA are shown in tables 8 and 9 below.

Table 8: Testing homogeneity of the variances

Test of Homogeneity of Variances
  Levene Statistic df1 df2 Sig.
Uplifted/Worthy course 2.296 6 224 .036
Concerned genuinely 29.884 6 224 .000

Table 9: One Way ANOVA test results

ANOVA
  Sum of Squares df Mean Square F Sig.
Uplifted/Worthy course Between Groups 215.907 6 35.984 15.945 .000
Within Groups 505.530 224 2.257    
Total 721.437 230      
Concerned genuinely Between Groups 239.888 6 39.981 17.422 .000
Within Groups 514.043 224 2.295    
Total 753.931 230      

Interpretation of ANOVA test

From table 9 above, it is observed that the values of F, degree of freedom and p for feeling uplifted and worthy course are 15.945, 6 and 0.000. Since significance value (p) is less than 0.05, there is a statistically significant mean difference between making world a better place and feeling uplifted when helping others. Since the mean difference between these variables is statistically significant, the null hypothesis is accepted while the alternative hypothesis is rejected. This means that those of contributed for charity because they felt uplifted also contributed so as to make the world a better place to live in.

Also from the table above, it is observed that the values of F, degree of freedom and p for genuine concern are 17.422, 6 and 0.000. Since significance value (p) is less than 0.05, there is a statistically significant mean difference between genuine concern and making the world a better. Since the mean difference between these variables is statistically significant, the null hypothesis is accepted while the alternative hypothesis is rejected. This means that those of contributed for charity because they were genuinely concerned also did so because they wanted to make the world a better place to live in.

Linear Regression

Linear regression was also carried out in this study to determine if making world a better depended on genuine concern. The hypothesis that was tested is stated below.

  • Null hypothesis (H0): Making world a better depends genuine concern of the participants

Table 10: Linear regression result

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 281.572 1 281.572 102.769 .000b
Residual 627.424 229 2.740    
Total 908.996 230      
a. Dependent Variable: Make world better
b. Predictors: (Constant), Concerned genuinely

Interpretation of regression results

From table 10 above, it is observed that F = 102.769, degree of freedom = 1, p = 0.000. Since the value of p is less than 0.05, there is dependence of dependent variable on independent variable is statistically significant, hence the null hypothesis is accepted and alternative hypothesis rejected (Elliott & Woodward, 2014). Therefore, “making world a better place” depends on genuine concern of the participants.

Conclusion

In summary this study found out that of the 231 participants, 74 contributed towards medical research fund, and 83 contributed towards children and young people fund, the rest did not contribute. It was found out that the main reason as to why people contribute towards charity was because they are genuinely concerned and they did so as to make the world a better place. It was also found out that level of education does not affect decision to contribute towards a charity or not.

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  1. Aljandali, A., 2016. Quantitative Analysis and IBM® SPSS® Statistics: A Guide for Business. London: Springer.
  2. Elliott, A. C. & Woodward, W. A., 2014. IBM SPSS by Example: A Practical Guide to Statistical Data Analysis. London: SAGE Publications.
  3. Kohli, S., 2014. The usefulness of the quantitative method of statistical analysis. Germany: GRIN Verlag.
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