Questionnaire. (3) (3) Bachelor s degree (3) Clerk (3) Third. (6) Other (specify) (6) Other (specify)

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1 Questionnaire 1. Age (years) 2. Education 3. Job Level 4.Sex 5. Work Shift (1) Under 25 (1) High school (1) Manager (1) M (1) First (2) (2) Some college (2) Supervisor (2) F (2) Second (3) (3) Bachelor s degree (3) Clerk (3) Third (4) (4) Master s degree (4) Secretary (5) Over 55 (5) Doctoral degree (5) Technician 5a. Employment Status (1) Part Time (2) Full Time (6) Other (specify) (6) Other (specify) Here are some questions that ask you to tell us how you experience your work life in general. Please circle the appropriate number on the scales below. To what extend would you agree with the following statements on a scale of 1 to 7, 1 denoting very low agreement and 7 denoting very high agreement

2 Questionnaire 6 The major happiness of my life comes from my job Time at work files by quickly I live, eat, and breathe my job My work is facinating My work gives me a sense of accomplishment My supervisor praises good work The oppertunies for advancement are very good here My co workers are very simulating People can live comfortaly with their pay in this organization I get a lot of cooperation at the workplace My supervisor is not very capable Most things in life are more important than work Working here is a drag The promotion policies here are very unfair My pay is barely adequate to take care of my expenses My work is not the most important part of my life

3 Analysis Proper 360 employees Work three shifts Experience high staff turnover Keen to understand intensions stay/leave 50 in-depths was conducted Developed Independent and Dependent Variables Job caractristics Perceived inequities Burnout Job satisfaction

4 Analysis Proper 174 employee survey was conducted Used disproportionate stratified sampling Tested following hypothesis: 1 Men will perceive less equity than women (or women will perceive more equity than men). 2 The job satisfaction of individuals will vary depending on the shift they work. 3 The employees intensions to leave (ITL) will vary according to their job title. In other words there will be significant differences in the ITL of top managers, middle level managers, supervisors, and the clerical and blue collar workers. 4 There will be relationship between the shifts that people work (first, second and third) and the part-time and full-time status of employees. In other words these two factors will not be independent. 5 The four independent variables of the job characteristics, distributive justice, burnout and job satisfaction will significantly explain the variance in intention to leave ITL.

5 Analysis Proper Steps 1 Establishment of Cronbach s alpha for the measures 2 The frequency distribution of the variables 3 Descriptive statistics such as mean and standard deviations 4The Pearson correlation matrix 5 The results of hypothesis testing

6 Reliability of Measures Cronbach s Alpha SPSS Reliability Analysis Menu Analyze Scale Reliability analysis Select variables Choose model Alpha Reliability Output Reliability Coefficients 5 items Alpha = < Poor, 6 7 ok, >7 Good

7 Obtaining Descriptive Statistics Frequency Distributions SPSS Frequencies Analyze Descriptive Statistics Frequencies Select variables Choose Statistics, Charts Frequencies Output

8 Frequency Distributions Output 12.2 Frequencies Output Respondent's Department Cumulative Percent Frequency Percent Valid Percent Marketing Production Sales Finance Servicing Maintenance Personnel Public Relations Accounting Total

9 Frequency Distributions Item % Men 86% Women 14% 1 st Shift 68% 2 nd Shift 19% 3 rd Shift 13% Full-Time 84% Part-Time 16% Item % 1 Year < 21% 1 3 years 20% 4 6 Years 20% >6 Years 39% Elementary 8% A/L 28% Degree 23% Masters 30% PhD 11%

10 Descriptive Statistics Measures of Central Tendency and Dispersion SPSS Frequencies Analyze Descriptive Statistics Frequencies Select variables Choose Statistics, Charts Descriptive Output.

11 Output 12.3 Descriptive Output Descriptive Statistics N Minimum Maximum Mean Std Deviation Variance Dist Justice* Burnout Job Sat Job Char ITL** *5 Point Scale **4Point Scale

12 Inferential Statistics Pearson Correlation SPSS Pearson Correlations Matrix Analyze Correlate Bivariate Select variables Option select e.g. Pearson, Test for significance two tailed Correlation Output.

13 Output 12.4 Pearson Correlations Matrix Correlations Dist Justice Burnout Job Sat Job Char ITL Pearson Correlations Significance (2-tailed) N Correlation at.01(2 tailed) **Correlation at.0001 (2-tailed) Dist Justice Bunout Job Sat Job Char ITL Dist Justice Bunout Job Sat Job Char ITL Dist Justice Bunout Job Sat Job Char ITL

14 Hypothesis 1 Use of t Test H10 : There will be no difference between men and women in their perceived inequities H10 is μw = μm H1A: women will perceive more equity than men (or men will perceive less equity than women) H1A is μw > μm SPSS: t Test for Differences between Two Groups (Independent teat samples) Analyze Compare Means Independent sample t-test Select variables and define groups Option select Specify Confidence level required t-test Output.

15 Output 12.5 t-test for Differences between Two groups Group Statistics N Mean Std Deviation Std Error Mean Dist Justice Treatment Male Female Hypothesis 1 is not Substantiated Perceive differences are not significantly different

16 Independent Samples Test Levene's Test for Equality of Variance t-test for Equality of means 95% confidence interval of the mean F Significance t df Significance (2-tailed) Mean Difference Std.Error Difference Lower Upper Dist Justice Equal Variance assumed Equal Variance not assumed

17 Hypothesis 2 Use of ANOVA H20 : There job satisfaction of individual will be the same irrespective of shift they work (1,2, or 3) H20 is μ1 = μ2 = μ3 Means of the job satisfaction H2A: There job satisfaction of individual will not be the same depending on which shift they work H2A is μ1 = / μ2 = / μ3 SPSS: ANOVA Analyze Compare Means One way ANOVA Select the dependent variable/s and one independent factor variable One-way ANOVA output.

18 Output 12.6 USA One way ANOVA output ANOVA Job Sat Sums of Squares df Mean Squres F Sig F = MS explained =.831 = MS residual.249 Between Groups Within Groups Total Hypothesis 2 is Substantiated There are significant differences in the mean satisfaction levels of workers in the three shifts

19 Hypothesis 3 Use of ANOVA H30 : There will be no difference in the intention to leave of employees at the five different job level H30 is μ1 = μ2 = μ3 = μ4 = μ5 Means of ITL at five different level H3A: There will be difference in the intention to leave of employees at the five different job level H3A is μ1 = / μ2 = / μ3 = / μ4 = / μ5 SPSS: ANOVA Analyze Compare Means One way ANOVA Select the dependent variable/s and one independent factor variable One-way ANOVA output.

20 Output 12.7 One way ANOVA Output ANOVA ITL Sums of Squares df Mean Squres F Sig Between Groups Within Groups F = MS explained =.578 = MS residual.461 Total Hypothesis 3 is not been Substantiated No significance of ITL by groups

21 Hypothesis 4 Use of Chi-Square Test H40 : The shifts worked and employment status (part-time and full-time) will be independent (i.e. will not be related) H4A: There will be a relationship between the shifts worked and employment status (part-time and full-time) SPSS: ANOVA Analyze Descriptive Statistics Crosstabs. (enter the variables in the rows and columns boxes) Select Chi Square Chi Square output.

22 Employment Status Output 12.8 Crosstabs Output Employment Status*Shift Cross-tabulation Shift First Second Third Total Full Time Part Time Total Chi-Square Tests Asymp.Sig (2- Value df sided) Pearson Chi-squre Likehood ratio Linear-by-linera Association N of valid cases 174 Hypothesis 4 is not been Substantiated Part-time and full-time not related

23 Hypothesis 5 Use of Multiple Regression Analysis H50 : The four independent variables will not significantly explain the variance in intention to leave H5A: The four independent variables will significantly explain the variance in intention to leave SPSS: Multiple regression analysis Analyze regression Linear. (enter dependent and independent variables) Regression output.

24 Output 12.9 Regression Output Model Summary 3,4 Variables Entered Model 1 Job Char Dist Just Burnout Job Sat 1,2 Removed R R Squre Adjusted R Squre Std. Eror of the Estimate INDEP.VARS(CONSTANT)JOB CHAR,DIST JUST,BURNOUT,JOB SAT 2 ALL REQUESTED VARIABLES ENTERED 3 DEPENDENT VARIABLE:ITL 4 METHOD: ENTER

25 ANOVA 2 Sum of square df Mean Squre F Significance Model 1 Regression Residual Total INDEP.VARS(CONSTANT)JOB CHAR,DIST JUST,BURNOUT,JOB SAT 2. DEPENDENT VARIABLE: ITL Hypothesis 5 is Substantiated

26 Coefficiets 1 Unstandardized Coefficients Stadardized Coefficients Model B Std.Error Beta t Sig 1 (Constant) Job Char Dist Justice Burnout Job Sat

27 Analysis Proper Tested following hypothesis: 1 Men will perceive less equity than men (or women will perceive more equity than men). Not Substantiated 2 The job satisfaction of individuals will vary depending on the shift they work. Substantiated 3 The employees intensions to leave (ITL) will vary according to their job title. In other words there will be significant differences in the ITL of top managers, middle level managers, supervisors, and the clerical and blue collar workers. Not Substantiated 4 There will be relationship between the shifts that people work (first, second and third) and the part-time and full-time status of employees. In other words these two factors will not be independent. Not Substantiated 5 The four independent variables of the job characteristics, distributive justice, burnout and job satisfaction will significantly explain the variance in intention to leave ITL. Substantiated USA

28 Summary It is clear the job satisfaction is the most influential factor in explaining employees ITL/S ITL does not differ with job level Need to address all levels Job satisfaction is lowest among the evening shift Need to do Qual With low output in inequity of men and women even though not significant need to address gender inequality 4 variables are explaining only 30% of ITL. 70% Unexplained. There could be other variables that are important in explaining.