Determinants of the Annual Income of Truck Drivers in the UK - Research Proposal Example

RЕSЕАRСH АND QUАNTITАTIVЕ МЕTHОDS RЕSЕАRСH РRОРОSАL by Student’s name Code+ course name Professor’s name University name City, State Date Determinants of the annual income of truck drivers in the UK ABSTRACT There has been mixed reaction on the determinants of the annual income of truck drivers in the UK. Women lobby groups argue that gender significantly determine wages in the UK trucking industry to support their claims of gender discrimination. On the other hand, trucking companies in the UK have maintained that wages of truck drivers are solely determined by the number of jobs assigned to a truck driver and the number of days spent on travel by the driver. This study sought to examine if gender, the number of jobs assigned to a truck driver and the number of days spent on travel by a truck driver influenced the annual income of truck drivers. Data regarding truck drivers ID, the gender of truck drivers, the number of jobs assigned in a year to truck drivers, number of days spent by a driver in a year and their respective incomes was collected from a sample of 30 truck drivers in the UK. Descriptive statistics, regression analysis and t-test for regression slope were used to analyze the data. The regression output revealed that the three variables only explained 9.2% variations of annual income of truck drivers in the UK. This study revealed that the three variables under investigation were not statistically significant at 5% significance level. Therefore, the study concluded with 95% confidence level, that gender does not influence the annual income of a truck driver and that the claim by women lobby groups that female truck drivers earn less is erroneous. Similarly, the study concluded that the number of jobs assigned to a driver and the number of days a driver spent on travel do not significantly influence the annual income of a driver. The claim by trucking companies, that the annual income of truck drivers is solely influenced by the number of jobs assigned to a truck driver and the number of days a truck driver spent on travel is erroneous. INTRODUCTION Background Although the majority of truck drivers in the UK are men, there are thousands of women truck drivers across the UK. There have been claims of discrimination of female truck drivers by women groups. They have claimed that women truck drivers earn far much less than their male counterparts to support their claims of gender discrimination. Trucking companies have always denied these claims by women lobby groups. Research Problem There has been mixed reaction on the determinants of annual income of truck drivers in the UK. Women lobby groups argue that gender significantly determine the annual income of truck drivers in the UK to support their claims of gender discrimination. On the other hand, trucking companies have maintained that wages of truck drivers are solely determined by the number of jobs and the number of days spent travelling by the driver. The research problem of this study was to examine if gender significantly determines the income earned by a truck driver as claimed by women lobby groups. It further sought to examine if the number of jobs assigned to a truck driver per year and number of days spent on travelling per year are significant determinants as claimed by trucking companies. Research purpose The research problem of this study was to examine if gender significantly determines the income earned by a truck driver as claimed by women lobby groups. It further sought to examine if the number of jobs and days on travel were significant determinants as claimed by trucking companies. Significance of the study There is a need for business to be ethical as part of their corporate social responsibility. Ethical behaviour ensures all stakeholders are treated fairly including; customers, employees, competitors and society at large. There are two potential ethical issues in this case. The first one is gender discrimination by trucking companies and the second one is whether trucking companies are giving objective information regarding the annual income paid to truck drivers. Therefore, the finding of this report will be important to all stakeholders in the trucking in UK to try to evaluate the ethical behaviour of trucking companies. It is equally important to trucking companies themselves in evaluating their ethical standards. Research question The research questions for this study were; i. Is gender a significant determinant of the annual income of truck drivers in the UK? ii. Does the number of jobs assigned in a year to truck drivers significantly determine the annual income earned by truck drivers in the UK? iii. Is the number of days spent by a driver on travel in a year a significant determinant of annual income earned by truck drivers in the UK? Research Hypotheses This study comprised of a null and alternate hypotheses for each of the three research questions For the first research question, the null and alternate hypotheses were; Null hypothesis (H0): Gender is not a significant determinant of the annual income of truck drivers in the UK. Alternate hypothesis (HA) Gender is a significant determinant of the annual income of truck drivers in the UK. For the second research question, the null and alternate hypotheses were; Null hypothesis (H0): The number of jobs assigned in a year to truck drivers is not a significant determinant of annual income earned by truck drivers in the UK. Alternate hypothesis (HA): The number of jobs assigned in a year to truck drivers is a significant determinant of annual income earned by truck drivers in the UK. For the third research question, the null and alternate hypotheses were; Null hypothesis (H0): The number of days spent by a driver on travel in a year is not a significant determinant of annual income earned by truck drivers in the UK. Alternate hypothesis (HA): The number of days spent by a driver on travel in a year is a significant determinant of annual income earned by truck drivers in the UK. RESEARCH METHODOLOGY Introduction This section focuses on the research techniques that were adopted and used for this study with the aim of achieving the research objectives. Research design Quantitative research design was best suited to examine the relationships between the variables under investigation and to answer the research question based on hypothesis testing. Research model Truck drivers’ annual income in the UK is determined by gender, the number of jobs assigned to the driver and the number of days spent travelling by the driver. This can be illustrated with the following model; Yt= αXt+ βAt+ δMt+e Where; Yt represents the dependent variable for a truck driver’s annual income in the UKA during the year t. Xt is dummy variable for gender. The gender dummy variable will be equals to zero if a selected individual is male and equals to one if the selected individual is a woman. At represents the independent variable for the number of jobs assigned to a driver in a given year of income. Mt represents the independent variable for the number of days a truck driver spent on the road in a given year of income. e is the error term. α,β and δ represents the coefficients of the respective independent variables. Definition and measurement of variables The dependent variable for this study was a truck driver’s annual income in the UK. There were three independent variables; gender, the number of jobs assigned to a driver and the number of days spent by a driver on the road in a given year of income. A truck driver’s income was measured in UK pounds. Men were represented by the code 0 while women were represented by the code 1 in the data table. The number of jobs assigned to a truck driver was measured using ordinary numbers. The numbers of days spent by a driver was measured using ordinary calendar days. Study area and target population The theoretical population of the study consists of all truck drivers in the UKA. However, the study was restricted to drivers of North American Van Lines Company due financial and time constraints. Data type and source This study relied on secondary data to obtain the data required for the analysis. Data regarding truck drivers ID, the gender of truck drivers, the number of jobs assigned in a year to truck drivers, number of days spent by a driver in a year and their respective incomes. This data was obtained from the management accountant’s records. Data relating to the year 2011 was used. This was the most recent and complete data that could be obtained. The collected data is in appendix A. Sampling technique and sample size To constitute a sample size out of the population of the study, simple random sampling technique was used to select 30 truck drivers in the UK. Simple random sampling was appropriate because it allowed unbiased sampling and it accorded the research work more scientific feature, thereby concretizing the validity of the research findings. The sampling frame was restricted to truck drivers of North American Van Lines Company due to financial and time constraints. North American Van Lines Company is a UK based trucking company. North American Van Lines Company has its corporate office in New York with more than 70 local offices in both the UK and Canada. The company has approximately 850 drivers. Data analysis Multiple linear regressions were used in analyzing the data collected. Multiple regression analysis is a statistics analysis tool that is commonly used to determine the relationship between dependent variable and independent variables using historical data[Chr11]. Normally, multiple linear regression analysis is used to evaluate the nature of the correlation between the variables under examination[Hea11]. In this study, multiple linear regressions will be used to evaluate the nature of the relationship between annual income of truck drivers, which is the dependent variable, and gender, number of jobs assigned to a driver and the number of days spent travelling. T-tests for the regression slope were used to evaluate whether the three coefficients of the independent variables are statistically significant. The p-value obtained from the t-test for regression was compared to the p-critical at 5% significance level which is 0.05. Normally, if the p-value obtained is higher than the 0.05 then the independent variable is statistically significant[Klu09]. However, if the p-value is lower than the 0.05 then the independent variable is not statistically significant. Descriptive statistics was also used to analyze the data collected. The mean of the various variables were obtained, frequencies of men and women were obtained. Graphs were also used in the study. This study used SPSS to analyze the data collected. Ethical consideration Data was collected after obtaining permission from North American Van Lines Company. The data collected from North American Van Lines Company was used for this research only. During data analysis, care will be taken to avoid misrepresentation of the data collected. RESEARCH FINDINGS The research findings discussed below are in the SPSS output which is in appendix B under appendices. Descriptive statistics results The descriptive statistics comprised of median, mode frequency tables with percentages and bar graph. The sampled number of truck drivers was 30 of which 20 were male and 10 were female. The male drivers were 66.7% of the sampled truck drivers while female truck drivers were only 33.3% of the sampled truck drivers. This implies that men drivers form a higher proportion of truck drivers in the UK. This information is represented graphically by a bar graph in appendix B under appendices. The mean annual income of all sampled truck drivers was $ 59,104 with a standard deviation of $ 5428.48. The highest paid truck earned $ 69,603 while the lowest paid truck driver earned $ 50,128. The mean number of jobs assigned to the sampled truck drivers was 181.83 with a standard deviation of 33.43. The truck driver who was assigned the highest number of jobs had 232 assigned jobs while the one who was assigned the least number of jobs was assigned 98 jobs. The mean number of days spent on travel by the sampled truck drivers was 192.77 days with a standard deviation of 39.94 days. The truck driver who spent the highest number of days on the road spent 280 days while the truck driver who spent the least number of days spent 110 days on the road. Regression results In the regression model, the annual income earned by a truck driver in the UK was being explained by gender, number of jobs assigned to the driver and the number of days the driver spent on the road in a given year of income. The adjusted R square is 0.092. Adjusted R square gives the explanatory power of the model. This implies that the model of this study only explains 9.2% of variations of the annual income a truck driver earns. 90.8% of variations in the annual income of drivers cannot be explained by the model. This model has a low explanatory power because it only explains 9.2% of variations in the annual income of truck drivers in the UK whereas 90.8% of the variations in the annual income of truck drivers in the UK are explained by factors outside this study. T-test for the regression slope results The t-calculated from the regression output of gender is 1.313. The p-value, P (t Read More