The Influence of Generational Variables on Job Motivation: Research Proposal

Topic: HR Management
Words: 2011 Pages: 7


Problem Statement

Four diverse and radically different generations are converging for the first time in recorded history. One of the final refuges of legal discrimination in the workplace today is a generational dispute. Each group has its own set of values, expectations, learning preferences, and attitudes. These significantly impact their propensity to adopt new work habits and their overall level of job satisfaction. Job satisfaction relates to how employees feel about different parts of their employment and can have a beneficial impact on a number of job-related factors, including efficiency, absenteeism reduction, labor turnover, and overall well-being (Wang et al., 2019). The discussion of job satisfaction is part of a larger discussion on the age and gender differences in self-reported subjective well-being. Comparatively, women had greater rates of voluntary turnover and worse work satisfaction, but the scientific community has paid little attention to female voluntary turnover and its precursors (Memon & Jena, 2017). Therefore, it is critical to investigate the link between female employees’ ages and their growing impact on workplace satisfaction.

The efficacy of an organization’s operations and financial performance are significantly influenced by employee job satisfaction, one of the most investigated themes in management literature. There is currently little to no evidence in the context of large enterprises to support the influence of generational variables on the levels of job motivation and job satisfaction among female employees. This study’s focus is on the idea of job satisfaction, including how it relates to women in the workforce and if generational disparities have an impact. The main goal of the study is to ascertain how female workers’ job satisfaction is impacted by their age at major organizations, namely Fortune 500 companies.

Research Questions

This study makes use of the problem and context mentioned above to conduct the following research questions: How do generational differences among female workers at Fortune 500 companies affect employee job satisfaction? At what age does job satisfaction peak? Based on the overarching research questions, two hypotheses can be derived. Possible Hypothesis 1: older female employees are more likely to have higher job satisfaction than younger employees. Possible Hypothesis 2: Job satisfaction will peak among female employees ranging in age between 40 and 50 years old. The purpose of the study is to research the company-wise subject differentiation on age diversity and show employers how to evaluate and analyze the comparative satisfaction of their firm in a slick and distinct manner. In addition, the study can provide insight into how age considerations may improve the happiness of female employees and lower turnover. This, in turn, drives corporate performance and might assist organizations in comparing various satisfaction characteristics with competitors within their industrial sector.

Literature Review

Demographical Characteristics and Job Satisfaction

It is a well-accepted axiom in the literature that there are systematic gender and age differences in how the components of employment function as sources of happiness or discontent in the trade-offs between them (Carvajal & Popovici, 2018). One research calculated the satisfaction ratings of American pharmacists with several aspects of their jobs compared them across genders and age groups and looked for gender-age contextual factors. When age groupings were taken into account, the results showed that female pharmacists indicated overall greater levels of work satisfaction than male pharmacists (Carvajal et al., 2019). Additionally, compared to male pharmacists, women exhibited higher levels of workload and stress as well as better satisfaction with a variety of specific aspects of the job. This study has consistently indicated that younger pharmacists are less happy with their jobs or certain aspects of them than older pharmacists (Carvajal et al., 2019). Younger specialists may not be able to appropriately appraise their working circumstances due to their lack of experience in the profession; this mismatch between reality and expectations might be a factor in their discontent.

There are commonalities and distinctions in the perceptions when organizational ideals and demographic factors that affect male and female work satisfaction are examined. When organizational culture characteristics that influence work satisfaction were examined with respect to age, an analogous study produced intriguing findings. Younger employees, in contrast to earlier findings, showed more job satisfaction and comfort with lengthy hours (Sharma, 2017). The findings also showed that possibilities for professional development and job passion had an impact on younger employees’ satisfaction (Sharma, 2017). This may be due to the fierce rivalry that exists in organizations right now, making it difficult to land a rewarding position. On the other hand, older workers have already shown themselves to the company and are less interested in competitiveness and innovations. In a related study, demographic parameters were examined as independent variables to see how they affected work satisfaction. The findings showed a substantial association between employee age and job satisfaction, with workers aged 36 to 45 reporting the highest levels of satisfaction (Tadesse & Muriithi, 2017). These results, once more, significantly deviate from the trend that was previously observed.

The in-depth analysis of job satisfaction is relevant to a larger discussion on the gender differences in self-reported happiness and satisfaction. A British investigation validated both age and cohort impacts. As they accumulate more experience, the older generation of women shows a fall in their relative happiness (Green et al., 2017). The more recent cohorts entered the labor market with significantly smaller satisfaction than the previous cohorts, indicating that there are disparities between cohorts (Green et al., 2017). Therefore, each impact is consistent with the general fall in female working satisfaction. As was stressed, the reduction is due to women’s net evaluations of traits being less favorable. This seems to support the idea that women are beginning to have preconceptions of the labor force that more closely resemble those of males and mirror real experiences.

According to the results of a study done in Serbia, there is some correlation between employee age and level of job satisfaction. The findings indicate that employees in the age range of up to 30 years have the highest rate of job satisfaction (Djordjević et al., 2017). Results regarding gender revealed that women between the ages of 20 and 30 had the highest degree of work satisfaction (Djordjević et al., 2017). It becomes evident that there is a significant amount of variability in these diverse outcomes. Indeed, academics acknowledge and agree that fluctuations in work satisfaction with time. However, over the course of several decades, conflicting results have been obtained about the nature of the link between work satisfaction and time. An important addition to this study is the resolving of the many contradictions in the body of information about the correlations between age and job satisfaction measurements, especially in the context of Fortune 500 companies.


Sampling Strategy

The primary study will be carried out to examine the hypotheses that were previously stated. The research will be conducted by delivering online questionnaires to Fortune 500 companies operating in the US. One section of the survey will ask about the respondents’ general characteristics, such as their gender, age, number of years of employment, degree of education, and place within the organizational hierarchy. The Job Descriptive Index (JDI), which gauges job satisfaction, will be implemented in the questionnaire’s second section. It is required to get informed permission from potential research participants by outlining the study’s main components and the participation obligations. One of the critical elements of the moral conduct of studies involving humans is the procedure of obtaining informed permission. A digital consent document, including the necessary information, will be made available, and prospective participants will be shown it as part of the consent procedure.

Initially, the research will consist of about 100 respondents who work for five to ten running organizations. In the sample’s population breakdown, females will make up all of the individuals. In terms of the age structure, there should be equitable distribution amongst generational groups. Thus, stratified random sampling would be the most appropriate sampling technique for this study. This sampling technique divides the target population into homogeneous, mutually exclusive segments and then randomly selects a sample from each segment (Iliyasu & Etikan, 2021). Consequently, it would be the most convenient method in terms of allocating female participants according to their age group.


This study’s setting will be limited to an online questionnaire, with no face-to-face interaction necessary. Given the employees’ heavy workloads, this environment is the most practical for speedier data collection and the one where the participants are most likely to be cooperative. The sample is drawn from the female workers at the 2022 Fortune 500 businesses. The businesses on the Fortune 500 list are all significant businesses with strong human resources, a deeper appreciation of values, and a more pressing need for the creation of mission statements (Lin et al., 2019). The list combines privately owned businesses with publicly disclosed revenues with publicly listed corporations. In some studies on cross-cultural business and management, the Fortune 500 list is used as a sample group of big businesses.


Across the body of research on job satisfaction, several approaches may be used to collect data on it, including surveys, interviews, rank order studies, sentence completion exams, and critical incident procedures. The age of the respondents—the dependent variable—will be ascertained through a demographic survey question. The Job Satisfaction Index will be used to operationalize the job satisfaction concept, which is the dependent variable. Employee surveys have been the primary approach employed to measure work satisfaction in the great majority of job satisfaction studies. The Job Descriptive Index (JDI), the most often used of these measures, has shown good reliability and validity (Sainju et al., 2021). As a result, the JDI will be the primary survey tool used in this study to gauge work satisfaction. The JDI has five components: colleague satisfaction, job contentment, salary satisfaction, job opportunity satisfaction, and supervisor satisfaction.

This index seeks to gauge an employee’s level of job satisfaction by utilizing words, primarily adjectives, to convey how the individual feels about his work. JDI implies a questionnaire that could measure the variables that impact work satisfaction after conducting several surveys and statistical analyses, such as factor analysis. The JDI has 72 questions that evaluate five aspects, making it the most reliable tool for measuring work satisfaction. The correlation between the JDI components is shown in Table 1, which shows strong internal consistency.

Table 1

Procedures and Design

An association claim will serve as the foundation for this investigation. When doing correlational research, the researcher is given a chance to explain the connection between two observed variables or if they are associated. It is important to note that the two variables being discussed cannot be altered. As a result, a numerical correlation coefficient between age and work satisfaction may be calculated. Making predictions from one variable to another would also be possible as a result. It would be feasible to accurately predict one variable from the other if this investigation discovers that the two variables are connected. In correlational research, prediction design models are frequently utilized. The capacity to forecast is the primary goal of research in predictive design. In order to investigate the predictive validity of age on work satisfaction, this study will use a predictive correlational design.

The development of an online questionnaire and an informed consent form would be the first stage in carrying out the research. A stratified random sample technique will be used to choose the respondents, who will represent 5–10 Fortune 500 businesses from each generation within each organization. Following the recruitment of respondents and receipt of their agreement, the data-collecting procedure would be carried out, and the pertinent variables would be coded. The analysis of the data will be done in stages. The right descriptive measurements should be utilized first. Performing a predictive multiple regression will allow the validity of the hypothesis as well as the predictive validity of the variables to be examined. Following data analysis, conclusions are to be drawn based on the findings, and they should be discussed in relation to the body of current research. The research’s implications and limitations at this stage will be noted and explored as well.


Carvajal, M. J., & Popovici, I. (2018). Gender, age, and pharmacists’ job satisfaction. Pharmacy Practice, 16(4), 1396.

Carvajal, M. J., Popovici, I., & Hardigan, P. C. (2019). Gender and Age Variations in Pharmacists’ Job Satisfaction in the United States. Pharmacy, 7(2), 46.

Djordjević, B., Ivanović-Djukić, M., & Lepojević, V. (2017). Relationship of Ages and Gender of the Employees in Organisations in the Republic of Serbia and Their Job Satisfaction. Economic Themes, 55(2), 263–280.

Green, C. P., Heywood, J. S., Kler, P., & Leeves, G. (2017). Paradox Lost: The Disappearing Female Job Satisfaction Premium. British Journal of Industrial Relations, 56(3), 484–502.

Iliyasu, R., & Etikan, I. (2021). Comparison of quota sampling and stratified random sampling. Biometrics &Amp; Biostatistics International Journal, 10(1), 24–27.

Lin, Q., Huang, Y., Zhu, R., & Zhang, Y. (2019). Comparative Analysis of Mission Statements of Chinese and American Fortune 500 Companies: A Study from the Perspective of Linguistics. Sustainability, 11(18), 4905.

Memon, N. Z., & Jena, L. K. (2017). Gender Inequality, Job Satisfaction and Job Motivation: Evidence from Indian Female Employees. Management and Labour Studies, 42(3), 253–274.

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Sharma, P. (2017). Organizational culture as a predictor of job satisfaction: The role of age and gender. Management: Journal of Contemporary Management Issues, 22(1), 35–48.

Tadesse, B., & Muriithi, G. (2017). The influence of employee demographic factors on job satisfaction: A case study of Segen Construction Company, Eritrea. African Journal of Business Management, 11(21), 608–618.

Wang, M., Hu, C., Huang, M., Xie, Y., & Zhu, W. (2019). The effect of emotional clarity and attention to emotion on job satisfaction: A mediating role of emotion regulation among Chinese medical staff. Asian Journal of Social Psychology, 22(3), 316–324. Web.

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