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The purpose of this research was to analyze the level of employee work motivation based on their demographic variables in Amhara National Regional State Bureaus. Correlational and descriptive survey design were applied. Quantitative data was collected from 373 sample respondents through the application of stratified and simple random sampling techniques but out of these, five questionnaires were not valid and the analysis was made for 368 respondents. Reliability and validity of the measurements were checked through the use of factor analysis and pilot test.
Independent sample t-test, one-way ANOVA and multiple linear regression analysis were applied.
The researcher found that the overall role of demographic variables (gender, marital status, educational level, work experience and age) on employee motivation was statistically significant. Separately, from the t-test result, it was revealed that gender and marital status; and from the one-way ANOVA analysis, work experience and age of employees have significant role on employee motivation while educational level has no significant role on employee motivation.
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The strength of the association was also determined by Omega square estimation. On the other hand, from the multiple regression analysis, work experience and age have positive and significant effect on employee motivation whereas educational level was not significant predictor of employee motivation. Thus, the researcher concluded that the employees’ demographic variables (gender, marital status, work experience and age) have played their own role on the level of employee motivation in Amhara National Regional State Bureaus.
Motivation is important to perform an organization’s goal in an appropriate manner.
Employee motivation is the desire, determination and ambition to want perform his/her job willingly to the best of his/her ability to see his/her organization success. Without motivated employees, an organization has full of workers who come in for their pay check that employees doing only what is necessary to keep their job security; and the organization remains where it is now or even begins to fail (Daft and Marcic, 2008; Kinicki and Fugate, 2012). As an organization grows as its assets start to consistently outweigh its liabilities. One of the most vital assets of an organization is its employees that the more willing employees are to perform at their best, the more productive they become (Kreitner and Kinicki, 2007). Therefore, employee motivation plays an important role to meet accomplish organizational goals, personal goals, increase the level of satisfaction, improve the efficiency of employees, to create team harmony in an organization; and for stabilized workforce in an organization. In turn, these lead employees to exert extra effort and energy and go extra miles to meet the goals of their organization (Mitchel, 1997; Dessler, 2008).
Employee motivation can be influenced by a number of factors such as organizational, environmental and individual factors, thus identifying the motivational factor of employees plays vital role for the performance of an organization; and employee motivation is also a psychological process resulting from the reciprocal interaction between an individual and the environment that affects an individual’s choice, effort, and persistence; and they associate it with the accomplishment of goals in an organization (Mitchel, 1982 and 1997; Latham, 2007; Baily and Clegg, 2008; Dessler, 2008). It is clear that employees who are well motivated perform their assigned job in an efficient way than demotivated employees in an organization and motivation is a phenomenon which cannot be seen directly rather it is the means to achieve the visible things through an invisible force and that pushes employees to behave in a certain way (Armstrong, 2007; Pinder, 2008).
One can infer the motivational process and analyze streams of behavior caused either by environmental or inherited factors that can be determined through their effects on abilities, beliefs, knowledge and personality factors of an employee (Mitchel, 1997; Bjorklund, 2011). Even if various research were conducted on the relationship between demographic variables and organizational commitment in different countries mostly in private sectors, as far as the researcher’s understanding, there is no research in topic in Ethiopian public sector context because the working culture of a country in which the research is conducted and organizational culture (private sector is different from public sector organizations) is varied (contextual gap) since most of the research is done in private sectors of other countries in a sense the working culture of Ethiopian public organization is different from other countries.
In Ethiopia, the issue of public employee performance and leadership were the focus of the government and the government launched public sector reform programs since 2003 to improve the quality of services provided; give special attention to leadership capacity development program to make leaders capable; and implement different management techniques like business process reengineering, balanced scorecard, kaizen and development of change army to improve the performance of public organizations (Getachew & Richard, 2006; MOCB, 2008; MOCS, 2013). The reasons for these initiatives were to transform the public service system into modern, effective and efficient that allows government to attain the vision and policy strategies (MOCS, 2013). However, the reform programs did not bring change as it is expected; and the performance of public employees’ and organizations is still backward and poor; it was only structural change in an organization (Getachew and Richard, 2006; MOCS, 2013).
Amhara National Regional State is one region among the nine regions in Ethiopia in which almost in all the public sector bureaus of the region, the regional state performance is revealed as below the desired level and the employees’ job performance is considered as average too. The basic reasons for the low performance of employees are manifested by some indicators such as staff turnover, lack of integrity, absenteeism, organizational justice, lack of punctuality, lack of engagement, lack of public service motivation, irresponsiveness and lack of commitment in their present work (Abeje, 2015; Argaw and Gajendran, 2016). In this regard, work motivation has great role on the performance and achievement of objectives in an organization. Currently, Ethiopia has intensively embarked on implementing a comprehensive agenda to achieve its vision to become the middle-income country in the year 2025 through the major anchor of the second growth and transformation plan (ADBG, 2016) with the assumption of transformational leaders that enforce the plan. The plan is comprehensive and intensive which demands motivated employees that create inspired working environment in the public organizations. Therefore, this research is significant for Amhara National Regional State Bureaus, Ethiopia, academicians, and in the literature to fill the gaps.
The objective of this study is to analyze the level of employee work motivation based on their demographic variables in Amhara National Regional State Bureaus.
Motivation refers to the force or forces that arouse enthusiasm, drives, effort and persistence to pursue a certain course of action; and it is the response to an object, people or events (Dessler, 2008; Daft and Marcic, 2008; Kinicki and Fugate, 2012). Literally, motivation, derived from the Latin word meaning “to move” represents those psychological goal directed processes (Kreitner and Kinicki, 2007; Mathibe, 2008). Job motivation has two major dimensions (intrinsic and extrinsic motivation). Intrinsic motivation occurs when an individual does something not because there may be a reward at the end, but because they find satisfaction in the activity itself while extrinsic motivation refers to the behavior or action that an employee display or takes because of an anticipated reward (Park & Rainey, 2012; Armstrong, 2007).
In line to employee motivation and demographic variables; Arooj and Momina (2017) examined the role of gender in their research and found that there is a significant difference in intrinsic motivation between female and male employees in which females are more intrinsically motivated than male employees but no difference in extrinsic motivation. Similarly, Beena and Anjali (2016) evaluated the relationship of employee motivation and demographic variables (age, gender, educational level and marital status) and revealed that there is a difference in employee motivation based on educational level and marital status of employees while because of age and gender, there is no significant difference in employee motivation.
On the same vein, Jackalas et al. (2016) explored the impact of demographic variables on organizational culture and employee motivation; and noted that significant positive relationship was found between employee’s motivation and educational level and work experience while the relationship between age and employee motivation was not significant. Likewise, Triyanto (2016) analyzed the relationship between motivation and certain demographic variables (gender, work tenure and level of education); and stated that there is a significant difference between demographic variables such as gender, work experience and educational level and work motivation. Moreover, Ali et al. (2015) examined the effect of demographic variables on work motivation and organizational commitment; and from the findings of their research, it is confirmed that demographic (age, work experience and marital status) variables and work motivation of employees were significantly correlated.
Hence, based on the above reviewed literature, the researcher formulated the following major and sub- hypothesis.
Hypothesis 1: The level of employee motivation is different based on their demographic characteristics.
The researcher used a correlational and descriptive survey research design. Correlational research design was appropriate design because the study explored the relationship between employee motivation and the demographic variables; and to predict the effects of the demographic variables on the dependent variable whereas descriptive survey is used to describe the phenomenon as it is (Bordens and Abbot, 2008). The researcher used quantitative research approach.
The target population of this study was 5552 permanent public sector employees of Amhara National Regional State Bureau, Ethiopia. Sample respondents were selected from thirty-five bureaus in the region using proportional stratified and simple random sampling techniques. The sample size was 373 and determined by Yamane’s (1967) formula: n= N/1+ (N*e2), where n is sample size, N is total population and e (5%) is the probability error; assumed that the level of confidence is 95%. But out of 373 sample respondents, five questionnaires were incomplete and thus discarded; and then the analysis was done using 368 sample respondents.
Primary data was collected from the sample respondents through the use of self-administered questionnaire. In this regard, a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree) was used; and it is measured by sixteen-item scale developed by (Mottaz, 1985; Ertan, 2008; Nida et al., 2014), and it is defined as the complex of forces, drives, need, or other psychological mechanisms that start and maintain activity towards achieving individual goals.
In this study, the validity and reliability of the measurement was tested.
Validity Test: It is the degree used to ensure the accuracy and ability of the measurement items which are intended to the concept (Sekaran, 2003; Creswell, 2014; Hair, et al., 2010; Anol, 2012). Specifically, the researcher checked content, nomological, convergent and discriminant validity using expertise, prior research and factor analysis.
Reliability Test: The researcher also applied the reliability test for this research measurement. Score reliability is a requirement for construct validity. Reliability can be defined as the degree to which measurements are free from error and, yield consistent results. Reliability, also called internal consistency and reproducibility, or used to evaluate the degree of consistency of the items to measure the research variables (Hair, et al., 2010). Internal reliability of a measurement is checked using composite reliability (CR) (Fornell and Larcker, 1981) and Cronbach’s alpha value (Nunnally, 1978; Nunnally and Bernstein, 1994; George and Mallery, 2003; Ghauri and Gronhaug, 2005). According to these scholars, when the reliability of the variables is greater than 0.70, it is considered as more appropriate but 0.60 and above is also acceptable. Pilot test was also conducted through the use of 30% (112 employees) of the total sample employees in order to check the Cronbach’s alpha value of the scales. Thus, the composite reliability (CR), AVE and Cronbach’s alpha values of all the constructs are presented in the following table.
As it is observed in the above table, almost all composite reliability and Cronbach’s alpha values of the constructs have a value greater than the benchmark of 0.70; and the composite reliability of employee motivation is above the acceptable threshold (0.60) which indicated that there is adequate internal consistency.
The t-test, one-way ANOVA and multiple regression analysis result of this study is presented and discussed in the following manner.
Independent t-test analysis was conducted to analyze the role of demographic variables such as gender and marital status on employees’ work motivation. The analysis is based on the descriptive statistics such as mean and standard deviation; and t-value, and significant (p) value.
Independent sample t-test was applied to determine that employee work motivation is different based on their gender. The test was used to check the hypothesis that employees work motivation is significantly different based on their gender (H1a).
In this table it is observed that the mean of male and female score for participants in this research regard to their work motivation is 50.30 and 28.31 respectively. In addition, it is shown that the standard deviations which means the variation in the data (spread of scores) is a little wider for male (SD=15.44) respondents than female respondents (SD= 7.00). Therefore, one can understand that, on average, male participants of the study in relation to their level of motivation were more motivated than those of female respondents. Correspondingly, the t-test result showed that there is significance difference in employee motivation based on their gender difference (t (317.51) = 18.52, p = 0.000. As shown above in the table, the results from the independent sample t-test revealed that there is statistical difference in employee work motivation based on their gender difference in which male were more motivated than female employees. Thus, the specific hypothesis one-one (H1a) was accepted.
The analysis was conducted to investigate the association of employees’ marital status and their work motivation in an organization. It was used to test the hypothesis that employees work motivation is significantly different based on their marital status (H1b).
The descriptive statistics showed the relationship between employee motivation and marital status which indicated the mean value and standard deviation for married respondents (M=47.24, SD=16.68) and unmarried respondents (M=38.82, SD=15.18) respectively. Thus, one could understand that, on average, married participants of the study in relation to their level of motivation were more motivated than those unmarried respondents. Likewise, the t-test result showed that there is significance difference in employee motivation based on their marital status difference (t (178.68) = 4.53, p = 0.000. As shown above in the table, the results from the independent sample t-test revealed that there is statistical difference in employee work motivation based on their marital status in which married employees were more motivated than unmarried employees. Thus, the specific hypothesis one-two (H1b) was accepted.
Analysis of variance (ANOVA) is used to compare the mean results of independent variables to what extent the factors have an influence on the dependent variable (Gaur and Gaur, 2009) since the researcher is interested to determine the contribution of each demographic factors (educational level, work experience and age) of the respondents, one-way ANOVA was conducted; omnibus test in generalized linear models was used in this study to test the overall role of demographic variables (gender, marital status, educational level, work experience, and age) on employees’ motivation. The analysis is done based on Welch’s statistics, F-value and significant (p) value; and Omega squared estimation(Olejnik and Algina,2003) was also used to determine the strength of the association of the significant role of demographic variables on employee motivation.
One-way ANOVA was applied to examine the associations of demographic variables of employees such as educational level, work experience and age and their work motivation. The researcher also used omnibus test in generalized linear models to examine the overall roles of demographic variables gender, educational level, work experience, age and marital status of respondents on employee motivation; and then to test the major hypothesis (H1) that the level of employee motivation is significantly different based on the demographic factors of respondents. The result of omnibus test is presented in the following table.
As it is observed in the table above, the omnibus test gives likelihood ratio test statistic and p-value for testing the major hypothesis (H1) that employee motivation is significantly different based on the demographic variables (gender, marital status, educational level, work experience, and age of respondents). Thus, all slope parameters are 0, which indicated that major hypothesis (H1) is accepted p (0.001) < 0.05.
First one-way ANOVA was used to test if there is any significant difference in employees' work motivation based on their educational level. This analysis was used to check the hypothesis that the motivation of employees in an organization is significantly different based on their educational level (H1c). In this regard, the Welch’s test of equality of means and one-way ANOVA result are presented in the following tables accordingly.
The Welch’s test of equality of means for employee work motivation based on their educational level is significant (p>0.05), hence it can be concluded that the population means for each group are approximately the same.
In the table above revealed, the mean results of employee motivation based on their work experience in which employees who have work experience from 1-5 years (M=45.19), 6-10 years (48.88), 11-15 years (M=42.86), and employees who have work experience of above 15 (M=59.79). Similarly, the variation of the data (dispersion score) measured by standard deviation for employees with work experience from 1-5 years (SD=16.44), 6-10 years work experience (SD=15.96), 11-15 years work experience (SD=16.75) and employees with their work experience above 15 years (SD=8.46). Thus, from the result, there is wider deviation in the variation of the data and mean results, particularly; employees who have a work experience of above 15 years were more motivated than the others. On the same vein, the above table showed the comparisons result of employee motivation based on their work experience. From the result, it is indicated that employees with work experience above 15 years with a mean value (M=59.79, p=0.001) had better work motivation followed by employees with work experience from 6-10 (M=48.88, p=0.021). Therefore, employees with more work experience had better work motivation than the others.
Third, one-way ANOVA was applied to test if there is any significant difference in work motivation of employees across different age groups. Thus, based on the analysis, the Welch’s test of equality of means and ANOVA result of the analysis is demonstrated in the following tables respectively.
The descriptive statistics showed that the mean results and the variation of data (dispersion score) of employee motivation based on their age were: age groups from 20-29 (M=36.94, SD=13.42), 30-39 years old (M=44.60, SD=15.86), 40-49 years old (M=45.63, SD=17.38), and employees who were above 49 years old (M=59.80, SD=8.50). It is clear that the mean values in each age group of respondents were different and there is little wider variation of the data. Hence, the level of employee motivation is different based on their age. On the other hand, it is evidenced that a Tukey Post –Hoc test results of one- way ANOVA for employee motivation based on their age were significant that there were significant differences in employee motivation among different age groups. When the age group of 20-29 compared with 30-39 years, 40-49 years and above 49 years age old groups; those who have 30-39 age range (M=44.60, p=0.006); those who were in the age ranges between 40-49 years (M=45,63, p=0.010) and above 49 years old (M= 59.80, p=0.001) employee were more motivated than the age group of 20-29 years old (M=36.94, p=0.028). Thus, employees with the age intervals above forty- nine years old have more work motivation than the other age groups.
Multiple linear regression was used examine the relationship between demographic variables and work motivation of employees. The linear regression model assumed that there is a linear or a straight-line relationship between the dependent variable and each predictor. The total score obtained from the sample employees (368) on their motivation to work is tested against five demographic variables namely age, education, gender, marital status and work experience. The dependent variable work motivation of employees was configured as the total score obtained across the sixteen items. The demographic variables: education, work experience, and age were measured in continuous scales, where specifically speaking education was measured in terms of the number years that one has secured ranging from a minimum of less than twelve years to greater than nineteen years. Gender and marital status were not considered in this test since these are not possible to be measured on continuous scales. From the multiple regression analysis, only key statistics such as standardized beta coefficient, R-square, adjusted R-square, F-value, and significant level (p-value) were used to determine the significant role of demographic variables on employee motivation. The following table depicted the three demographic variables of education, work experience, and age.
Employee Work Motivation and Demographic Variables. (2022, May 22). Retrieved from https://studymoose.com/employee-work-motivation-and-demographic-variables-essay
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