Analysis of Survey on Job Satisfaction Essay

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Job Satisfaction

The main objective of this research is to examine the various factors affecting job satisfaction given that satisfaction is a dynamic phenomenon that includes a person's attitudes and behaviors. The author also seeks to examine organizational injustices and how they affect job satisfaction and organizational commitment. Organizations in the modern business environment consider job satisfaction as a legitimate factor that has strong impacts on organizational commitment. In light of this significance, it's important for organizations to evaluate and identify factors that affect job satisfaction. Therefore, this research primarily seeks to study the various factors affecting job satisfaction.

Data Analysis Methodology

To achieve the aims of this study, the researcher conducted 26 surveys on 26 different employees to determine issues that are affecting the job satisfaction in their different working environments. The researcher developed surveys with open ended questions that act as a framework of understanding what employees want from their managers. Notably, the surveys were not carried out on any specific organization but on a group of participants who provided their personal experience on job satisfaction. The research participants were selected randomly though they were required to meet certain criteria to be included in the study. The use of 26 surveys for this study was geared towards ensuring the researcher conducts a comprehensive study on this dynamic phenomenon.

To analyze the data qualitatively, the researcher utilized multiple regression analysis to examine the relationship between the various factors and job satisfaction. The use of regression analysis for this study is attributable to the fact that it's an advanced technique of data analysis that enables a researcher to scrutinize the relationship between two or more variables. Notably, there are several types of regression analysis, which implies a researcher makes his choices depending on the variables and phenomenon under investigation. Multiple regression analysis is suitable for analyzing data in this study because job satisfaction (the dependent variable) is affected by several factors (independent variables). The existence of numerous factors affecting job satisfaction implies that the data analysis methodology should be one that enables the researcher to study each factor with regards to its impact on job satisfaction.

Since this research is qualitative, the researcher has utilized inductive reasoning to conduct the analysis. Inductive research involves working using a bottom-up approach in which participants' opinions and views are used to generate wider themes and create a theory linking the themes (Soiferman, 2010). The use of inductive analysis for the study is also fueled by the fact that this study is exploratory in nature. Inductive analysis usually involves making observations and identifying patterns, which is used in creating a tentative hypothesis that eventually results in a theory (Research Methods Knowledge Base, 2006). In this case, the researcher makes observations of participants' responses to issues affecting job satisfaction and uses them to identify patterns and develop a theory relating to job satisfaction.

Data Analysis

As previously mentioned, the sample used in this research was 26 individuals who responded to the survey consisting of several questions. The data relating to these participants are as shown in Tables 1, 2 and 3. As shown in these tables, male participants accounted for 61% whereas female respondents were 39%. On the other hand, those under 25 years were 8%, those between 25-34 years were 31%, those between 35-44 years were 46%, and those aged 45 years or more were 15%. Participants with job tenure below 1 year accounted for 4%, those between 1-5 years were 53%, those between 6 -10 years were 12%, and those with 10 years or more were 31%.

Demographic Characteristics

In conducting the analysis, gender, age group and job tenure were used a demographic characteristics to help determine factors that affect job satisfaction. The researcher conducted a series of ordinary least squares (OLS) multiple regressions to examine the link between these demographic attributes and an individual's job satisfaction. The demographic variables in this multiple regression analysis were categorical since the methodology is based on several assumptions including the fact that variables must either be categorical or quantitative (Satterfield, 2015). Similar to other statistical procedures, multiple regression analysis is based on assumptions regarding the population or sample from which study data is obtained.

Using categorical data, the normal characteristic in multiple regression analysis is count, which includes the demographic characteristics of a sample or population. According to the responses in the survey questions, the predictors in this research have some variation in value.

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The researcher divided these three demographic variables into three categories i.e. age group, job tenure, and gender. This was followed by determining the effect of these variables on job satisfaction regardless of the other dimensions of job satisfaction. Furthermore, the researcher also conducted analysis on the effect of these demographic variables and other dimensions on job satisfaction among the population.

Job Satisfaction Dimensions

In addition to the demographic variables, the researcher included other dimensions of job satisfaction in the study based on survey questions and responses from participants. Multiple regression analysis was suitable in examining these dimensions of job satisfaction because the methodology evaluates the impact of an independent variable on a dependent variable. Moreover, this data analysis technique helps in determining the total effect of independent variables on the dependent variable. The reliability of findings in this study is determined by the basic assumptions regarding the sample or population from which data regarding the phenomenon under investigation is obtained.

The other dimensions of job satisfaction included in the analysis are salary and benefits, work schedule, conflict resolution, nature of work, autonomy and personal expression, respect and job promotion, fairness, teamwork, transportation grant, motivation, supervision, motivation, open communication, and recognition/feedback. These dimensions were identified based on the questions in the survey and literature review of information on job satisfaction. They were also identified based on the respondents' personal opinion to open ended questions relating to the phenomenon under investigation. The initial regression analysis was carried out on the summative score of job satisfaction for these dimensions in the survey. The researcher conducted several regressions for each job satisfaction dimension as shown in Figure 1.

Once the regressions for each of these job satisfaction dimensions are conducted, the researcher examined how organizational injustices affect job satisfaction and organizational commitment. In this case, the researcher examined three major aspects i.e. organizational injustices, organizational commitment, and participant's desire to leave their jobs. The researcher primarily focused on determining how job satisfaction and organizational commitment is affected by organizational injustices in light of what employees expect or desire from a manager.

Measuring Instruments

The researcher utilized two measuring instruments to evaluate variables in this study i.e. the Job Satisfaction Survey (JSS) and the Organizational Commitment Scale (OCS). The Job Satisfaction Survey, which was developed by Spector examined nine components of job satisfaction i.e. promotion, pay, contingent rewards, communication, working conditions, fringe benefits, nature of work, and co-workers. The survey questionnaire comprised of various items that were regarded to be of equal value and to which participants responded based on their personal opinions and experience. Notably, the second section of the questionnaire comprised a five-point Likert-type scale, which was a summated rating with which participants would provide responses based on how true the statement was to them. Organizational Commitment Scale (OCS) was originally developed by Allen and Meyer and comprises six items including affective commitment, continuance commitment, and normative commitment (Lumley et al., 2011, p.108). Affective commitment is an employee's emotional and psychological connection to an organization, while continuance commitment is awareness of consequences associated with leaving an organization, and normative commitment is a sense of responsibility to continue working with an organization.

Results of Data Analysis

Since a total of 26 questionnaires were distributed and 26 were returned, the response rate was calculated as follows:

Returned Completed Questionnaires * 100

Total Distributed Questionnaires

Therefore the calculated response rate for this survey was 100%.

Findings based on Demographic Variables

As reflected in the responses, employees aged 25-24 and 35-44 had the highest and second highest mean score of 3.2 and 3.0 respectively and better job tenure of either 1-5-year or 6-10 years as compared to other age groups. These employees reported increased job satisfaction and better working conditions. Employees aged 45 years and above had a lower mean score compared to their counterparts aged 25 years and below. As a result, those aged 45 years or more have less job satisfaction and slightly lower job tenure as compared to those aged 25 years or less.

Male workers were on average more satisfied with their jobs as compared to female workers. However, this statistic may not provide a clear indication of the difference in job satisfaction between male and female workers because the number of men who completed this survey was more than female workers. In essence, since the survey was completed by 16 male participants and 10.....

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