Report Structure And Findings: A Study On JCU’s Employee Environment

Body of Report

The purpose of this report draws from the Vice Chancellor’s interest in creating a gender neutral and environmentally sound work place where the Vice Chancellor would like to see equal representation of males and females in the JCU workforce at all levels. The Vice Chancellor would also like to see equality in regards to remuneration (pay), retention (time employed with JCU) and employment level.

Such data and subsequent reports are important to the VC as it will inform planning for and assessment of future and current innovative hiring, training, and promotion policies and programs encouraging staff being proactive around these issues.

The Vice Chancellor is particularly keen to improve the retention rate for women employees across all campuses as historically the retention of women in the organization has been problematic.

To this end, the purpose of this report is to provide some preliminary studies, investigating what the current employee environment is and therefore identifying the priorities in terms of areas that need to be targeted to move towards the Vice Chancellor’s goals.

The report therefore covers the descriptive analysis of the data obtained from three campuses of JCU regarding employee demographics and salary scale. The report ends by concluding on the summaries of the main points or findings of the report.

The first section presented in this section is the variable description. The name, type of the variable and scale of measurement is presented in table 1 below.

Variable name	Variable type	Scale of measurement
Location	Independent	Nominal
Gender	Independent	Nominal
Academic Division	Independent	Nominal
Age	Independent	Scale
Education	Independent	Nominal
Salary	Dependent	Scale
Length of employment	Independent	Ordinal
Employment type	Independent	Nominal
Country of residence	Independent	Nominal
Citizen status	Independent	Nominal
Job role	Independent	Nominal
Mode of transport to work	Independent	Nominal

 

This section provides the descriptive statistics for age and salary grouping the data based on the different campuses. The results are presented in table 2 below;

Location	Cairns	Townsville	Singapore	JCU as a whole
Age	Salary	Age	Salary	Age	Salary	Age	Salary
N	Statistic	65	65	90	90	45	45	200	200
Minimum	Statistic	25.00	44.00	25.00	41.00	26.00	42.00	25.00	41.00
Maximum	Statistic	70.00	170.00	68.00	169.00	70.00	168.00	70.00	170.00
Mean	Statistic	47.42	109.00	47.30	104.78	47.67	108.42	47.42	106.97
Std. Deviation	Statistic	13.84	38.49	12.86	38.75	14.17	39.15	13.42	38.61
Skewness	Statistic	-0.19	-0.06	-0.05	-0.10	0.02	-0.22	-0.08	-0.11
Std. Error	0.30	0.30	0.25	0.25	0.35	0.35	0.17	0.17
Kurtosis	Statistic	-1.22	-1.32	-1.16	-1.32	-1.43	-1.22	-1.24	-1.29
Std. Error	0.59	0.59	0.50	0.50	0.69	0.69	0.34	0.34

The figures below shows the scatter plots for salary and age for the different campuses. There seems to be a negative relationship between age of the employees and the employee salaries for the Cairns campus. However, for the two other campuses, there seems to be a positive relationship between the age of the employees and the employee salaries (Cohen, Cohen , West, & Aiken, 2002). Similarly, the correlation between age of the employees and the employee salaries for the entire JCU is positive as can be seen from figure 4.

The table below presents the correlation between age of the employees and the employee salaries for the three campuses and the overall JCU as a whole (Nikoli?, Muresan, Feng, & Singer, 2012). For all the three campuses and the JCU as a whole, there is no significant correlation between age of the employees and the employee salaries. This means that, it is not significant to claim that at JCU the employee salaries is related with the age of the employees.

Correlations
Location	Age	Salary
Cairns	Age	Pearson Correlation	1	-.077
Sig. (2-tailed)		.544
N	65	65
Salary	Pearson Correlation	-.077	1
Sig. (2-tailed)	.544
N	65	65
Townsville	Age	Pearson Correlation	1	.194
Sig. (2-tailed)		.066
N	90	90
Salary	Pearson Correlation	.194	1
Sig. (2-tailed)	.066
N	90	90
Singapore	Age	Pearson Correlation	1	.271
Sig. (2-tailed)		.072
N	45	45
Salary	Pearson Correlation	.271	1
Sig. (2-tailed)	.072
N	45	45
		Pearson Correlation	1	.123
		Sig. (2-tailed)		.083
JCU		N	200	200
		Pearson Correlation	.123	1
		Sig. (2-tailed)	.083
		N	200	200

The tables below compares the average salary for the male and female employees in all the three campuses as well as JCU as a whole.

Group Statistics
Location	Gender	N	Mean	Std. Deviation	Std. Error Mean
Cairns	Salary	Male	36	105.1944	38.05997	6.34333
Female	29	113.7241	39.16075	7.27197
Townsville	Salary	Male	47	107.3830	37.69301	5.49809
Female	43	101.9302	40.13157	6.12001
Singapore	Salary	Male	29	110.4828	40.36585	7.49575
Female	16	104.6875	37.82366	9.45591
JCU as a whole	Salary	Male	112	107.4821	38.21796	3.61126
		Female	88	106.3182	39.31937	4.19146

Independent Samples Test
Levene’s Test for Equality of Variances	t-test for Equality of Means
F	Sig.	t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
Lower	Upper
Cairns		.202	.654	-.887	63	.379	-8.530	9.620	-27.753	10.694
			-.884	59.4	.380	-8.530	9.650	-27.837	10.777
Townsville		.518	.474	.665	88	.508	5.453	8.204	-10.851	21.756
			.663	86.0	.509	5.453	8.227	-10.902	21.807
Singapore		.554	.461	.471	43	.640	5.795	12.300	-19.011	30.601
			.480	32.83	.634	5.795	12.067	-18.759	30.350
JCU		.229	.633	.211	198	.833	1.164	5.51366	-9.709	12.037
				.210	184.4	.834	1.164	5.533	-9.751	12.079

An independent samples t-test was performed to compare the average salaries for the JCU employees in different campuses and JCU as a whole based on gender (male and female). Results showed that there is no significant difference in the employee salaries for the male and female employee in all the campuses as JCU as a whole, p > 0.05.

The table below compares the length of employment for the males and females in the different campuses. Results shows that for Cairns campus, majority of the male employees (44.4%) have worked for between 3 and 6 years while majority of female employees (37.9%) have worked for more than 10 years.

For Townsville, majority of the female employees (53.5%) have worked for between 3 and 6 years while majority of male employees (36.2%) have worked for more than 10 years.

For Singapore campus, majority of the male employees (48.3%) have worked for between 3 and 6 years, similarly, majority of female employees (50.0%) have also worked for between 3 and 6 years.

For JCU as a whole, majority of the male employees (40.2%) have worked for between 3 and 6 years, similarly, majority of female employees (46.6%) have also worked for between 3 and 6 years.

Length of employment * Gender Cross tabulation
% within Gender
		Gender	Total
Campus	Length	Male	Female
Cairns	≤3	5.60%	3.40%	4.60%
3<x≤6	44.40%	34.50%	40.00%
6<x≤10	16.70%	24.10%	20.00%
≥10	33.30%	37.90%	35.40%
Total	100.00%	100.00%	100.00%
Townsville	≤3	0.00%	2.30%	1.10%
3<x≤6	31.90%	53.50%	42.20%
6<x≤10	31.90%	23.30%	27.80%
≥10	36.20%	20.90%	28.90%
Total	100.00%	100.00%	100.00%
Singapore	3<x≤6	48.30%	50.00%	48.90%
6<x≤10	17.20%	6.30%	13.30%
≥10	34.50%	43.80%	37.80%
Total	100.00%	100.00%	100.00%
JCU	≤3	1.80%	2.30%	2.00%
3<x≤6	40.20%	46.60%	43.00%
6<x≤10	23.20%	20.50%	22.00%
≥10	34.80%	30.70%	33.00%
Total	100.00%	100.00%	100.00%

The table below compares the education level for the males and females in the different campuses. Results shows that for Cairns campus, majority of the male employees (44.4%) have master’s equivalent level while majority of female employees (37.9%) have doctoral equivalent level.

Education * Gender Cross tabulation
% within Gender
Campus	Education	Male	Female	Total
Cairns	Bachelor’s or equivalent level	19.40%	13.80%	16.90%
Doctoral or equivalent level	27.80%	37.90%	32.30%
Master’s or equivalent level	44.40%	31.00%	38.50%
Post-secondary level	8.30%	17.20%	12.30%
Total	100.00%	100.00%	100.00%
Townsville	Bachelor’s or equivalent level	14.90%	7.00%	11.10%
Doctoral or equivalent level	40.40%	32.60%	36.70%
Master’s or equivalent level	34.00%	46.50%	40.00%
Post-secondary level	10.60%	14.00%	12.20%
Total	100.00%	100.00%	100.00%
Singapore	Bachelor’s or equivalent level	24.10%	12.50%	20.00%
Doctoral or equivalent level	31.00%	31.30%	31.10%
Master’s or equivalent level	34.50%	25.00%	31.10%
Post-secondary level	10.30%	31.30%	17.80%
Total	100.00%	100.00%	100.00%
JCU	Bachelor’s or equivalent level	18.80%	10.20%	15.00%
Doctoral or equivalent level	33.90%	34.10%	34.00%
Master’s or equivalent level	37.50%	37.50%	37.50%
Post-secondary level	9.80%	18.20%	13.50%
Total	100.00%	100.00%	100.00%

As can be seen in the figure below, the average salary is slightly higher for the female employees as compared to that of the male employees at Cairns campus. However, the average was higher in the two other campuses as well as for the JCU as a whole.

The figure below shows that majority of employees have worked for between 3 and 6 years while minority have worked for 3 or less years.

The figure below shows that majority of employees have either master’s equivalent level of doctoral equivalent level with minority having either bachelor’s equivalent level or post-secondary level.

Conclusion

The main purpose of this report was to provide some preliminary studies, investigating what the current employee environment is. Results showed that majority of employees have worked for between 3 and 6 years while minority have worked for 3 or less years. In terms of education level, it was established that majority of employees have either master’s equivalent level of doctoral equivalent level with minority having either bachelor’s equivalent level or post-secondary level.

In overall, results showed that there was no significant difference in terms of the employee salaries across the three campuses. However, female employees at Cairns campus earned slightly more than male employees which could be attributed to the fact that majority of female employees at Cairns campus had doctoral level against the male employees who majority had master’s level.

References

Cohen, J., Cohen , P., West, S. G., & Aiken, L. S. (2002). Applied multiple regression/correlation analysis for the behavioral sciences. Journal of Statistics, 34-49.

Nikoli?, D., Muresan, R. C., Feng, W., & Singer, W. (2012). Scaled correlation analysis: a better way to compute a cross-correlogram. European Journal of Neuroscience, 1-21.

Székely, G. J., & Rizzo, B. N. (2007). Measuring and testing independence by correlation of distances. Annals of Statistics, 35(6), 2769–2794.