This chapter discusses the methodology of the research. The research questions and objectives mentioned in Chapter 1 will be identified and analyzed via appropriate research instruments to accomplish the main purpose of the research, which is to examine the relationship between emotional intelligence and job satisfaction among individual employees in the workplace. The elements which will be elaborated throughout this chapter are respondents of the study, research instruments, data collection, pilot test, and data analysis.
The respondents of the study are aˆ¦ (still in the progress of confirmation aˆ¦) from the aˆ¦ which will be taken as samples for the study. Their perception and responses towards emotional intelligence and job satisfaction will be further assessed to meet the research purposes of this study.
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3.3 Research Instruments
This research utilized the quantitative research methodology. The instrument used to collect data was questionnaire. A set of questionnaire containing 57 questions divided into 3 sections was developed mainly based on two questionnaires used previously by another study, that are Trait Meta-Mood Scale (Salovey, Mayer, Goldman, Turvey, & Palfai, 1995) and Job Satisfaction Survey (Spector, 1985).
The questionnaire applied to the research was mainly divided into 3 sections, which were: i) demographic information, ii) emotional intelligence assessment, and iii) job satisfaction survey. Different question-types were included in the questionnaire, such as listing, rating, scales, close-ended and open-ended question. Followings are further elaboration of each section in details.
3.3.1 Demographic Information
The demographic information is indispensable within a questionnaire to gain the most fundamental information concerning individual respondents. There are altogether four items adopted in this questionnaire, namely gender, age, races, and length of services. These precious data can be utilized as the extra to infer other factors of job satisfaction if necessary.
3.3.2 Emotional Intelligence Assessment
In order to construct an evaluation of EI, the TMMS measure of three factors (eg. attention to, clarity of, and the mood repair of emotions) was being modified to match the expectation of this research. The original assessment includes 48-items to which participants respond on a Likert 1-to-5 Scale, but for this research will use a shortened 33-item scale. The scale is equally divided to address the three-components of emotional intelligence, and it includes reversed scored items to prevent an acquisition set. For instance, there are 11 items for attention, 11 items for clarity, and 11 items for repair after certain modification. Question like “I pay a lot of attention to how I feel” was labeled attention to feeling; “I am usually very clear about my feelings” was regarding clarity of feelings; and “Although I am sometimes sad, I have a mostly optimistic outlook” was one of the items within category of mood repair. A clearer distribution of these three subscales based on the items is shown in the Table 3.1 as followed.
Table 3.1 Items according to the Emotional Subscales
Subscale
Item numbers
Attention
6, 7, 10, 13, 15, 16, 21, 24, 25, 29, 32
Clarity
1, 4, 8, 14, 18, 19, 20, 23, 26, 30, 33
Repair
2, 3, 5, 9, 11, 12, 17, 22, 27, 28, 31
The TMMS provide insight into individuals’ strategies for dealing with emotion post-appraisal, as well as their abilities to self-regulate their emotions. The level of emotional intelligence as measured by the TMMS is determined through subjects’ responses of their evaluation on each item as whether they agree with it based on the Likert Five Scale as shown in Table 3.2.
Table 3.2 Scoring on Likert Five Scale
Score
Answer Scale
5
Strongly Agree
4
Somewhat Agree
3
Neither Agree nor Disagree
2
Somewhat Disagree
1
Strongly Disagree
3.3.3 Job Satisfaction Survey
The original Job Satisfaction Survey (JSS), copyrighted by Paul E. Spector (1994), consists of nine categories of job aspects to provide responses related to job satisfaction. According to the cultural requirement and certain context of this research, JSS was modified to measure only five dimensions of employee job satisfaction by asking employees to respond to a series of questions describing their job perceptions. The five categories include work on pay, contingent rewards, co-workers, nature of work, and communication. The items and description of the five categories of JSS are shown in Table 3.3 a followed.
Table 3.3 Items and Description of the JSS Subscales
Subscale
Item Numbers
Description
Pay
1, 6, 11, 16
Pay and remuneration
Contingent Rewards
2, 7, 12, 17
Appreciation, recognition, and rewards for good work
Co-workers
3, 8, 13, 18
People that respondents work with
Nature of Work
4, 9, 15, 19
Job tasks themselves
Communication
5, 10, 14, 20
Communication within the organization
Since scoring on Likert Five Scale is also applied to measure level of job satisfaction, five choices offered by each item ranging from “strongly disagree” to “strongly agree” are the standard scale for respondents to reflect their perception towards job satisfaction. Responses to the items should be numbered from 1 representing strongest disagreement to 5 representing strongest agreement with each. This assumes that the scale has been modified as violating the original agree-disagree response choices where summated rating scale is used. A comprehensive figure of scoring scale is demonstrated in Table 3.4 as followed.
Table 3.4 Scoring on Likert Five Scale
Score
Answer Scale
5
Strongly Agree
4
Somewhat Agree
3
Neither Agree nor Disagree
2
Somewhat Disagree
1
Strongly Disagree
3.4 Pilot Test
A pilot test is carried out to detect the reliability of an instrument as well as its way of design in order to provide proxy data for selection of a probability sample (Emory & Cooper, 1991). In this study, the questionnaire was piloted to a group of 15 respondents to assess its validity and reliability before it was distributed. The pilot test is essential to assess the internal reliability of items through using Cronbach’s Alpha, which is a tool for verifying the reliability of items in the questionnaires (Nunnallym, 1978). It is the coefficient of the reliability that reflects the positive relation between each item. If the value of I± (alpha) close to 1, it means that the reliability is high, and vice versa. The greatest level of reliability is I± > 0.7 or I± = 0.7.
3.5 Data Collection
All survey materials were distributed and returned by manual distribution to the organization. The data collected through direct distribution to XXX organization included questionnaires with the modified version of the Trait Meta-Mood Scale (TMMS) and Job Satisfaction Survey (JSS). The questionnaires were distributed to the respondents randomly selected employees from the XXX organization.
First of all, a pilot test was conducted in the organization before final distribution of the questionnaires for the respondents. There were 15 respondents being involved in the pilot test to ensure the reliability of the instrument. Later on, researcher distributed the questionnaires to the respondents within period from DD/MM/YY until DD/MM/YY. One week after the initial survey, a phone call reminder was sent to the supervisor of those participants asking for their cooperation and urging them to complete the survey materials. Participants who had not received a survey were then asked to call or email the researcher to have the questionnaire sets sent to them.
As mentioned, the only instrument used in this study was questionnaire, which contributed to the primary data of the study. Secondary data such as those derived from journals, articles, books and thesis, were also adopted to compensate the insufficiency of the primary data in order to attain the objectives of the study.
3.6 Data Analysis
To analyze the data, a total of three dimensions from the independent variable of emotional intelligence were taken into consideration namely, attention to feelings, clarity in discrimination of feelings, and mood repair. The dependent variable, job satisfaction was assessed based on the modified five aspects of job satisfaction which were pay, contingent rewards, co-workers, nature of work, and communication. Correlations between those three dimensions of emotional intelligence with the five aspects of job satisfaction will be analyzed. Data were entered into the computer using Statistical Packages fir Social Science (SPSS) version 16 software. Results were presented through frequency counts, correlations and other descriptive statistics.
3.6.1 Analysis of the First Objective
To analyze the first objective, the level of emotional intelligence among employees based on overall summation of the three factors will be demonstrated through means per subscale and total score; standard deviation per subscale and total score; and coefficient alpha per subscale and total score. For example, the mean score will be divided into three levels, which is low, moderate, and high. The level of emotional intelligence as according to the mean score calculation is shown in Table 3.5.
Table 3.5 Level of Emotional Intelligence according to Mean Score
Ratio
Level
1.00 – 2.33
Low
2.34 – 3.66
Moderate
3.67 – 5.00
High
3.6.2 Analysis of the Second Objective
To analyze the second objective, job satisfaction level will be assessed through the Job Satisfaction Survey. The respondents are required to circle a number from one to six that corresponds with their feelings about each question regarding to the job. The questions are alternately favorable and unfavorable. The scale for scoring the survey is set up as a summated rating scale format as explained before. The summated rating scale is where both positive and negative ended questions are asked, in which adding the number of positive responses and the reverse score of negative responses scores each facet. The resulting score is the total number to be used for each facet and to be added to get the global score. Since there are five facets of job satisfaction modified to match the context of this study, the scores range from 4 to 24 for each subscale, and 20 to 120 for the global score. If the score of subscale has a high number, such as 20, then the subscale shows a high level of job satisfaction. Besides, the negatively worded items should be reversely scored. The rightmost values should be substituted for the leftmost.
Since the JSS assesses job satisfaction on a continuum from low (dissatisfied) to high (satisfied), there are no specific cut scores that determine whether an individual is satisfied or dissatisfied. Hence, the absolute approach is adopted to interpret satisfaction scores. Provided the JSS uses 6-point agree-disagree response choices, agreement with positively-worded items and disagreement with negatively-worded items would represent satisfaction, whereas disagreement with positive-worded items, and agreement with negative-worded items represents dissatisfaction. For the 4-item subscales, as well as the 36-item total score, this means that scores with a mean item response (after reverse scoring the negatively-worded items) of 4 or more represents satisfaction, whereas mean responses of 3 or less represents dissatisfaction. Mean scores between 3 and 4 are ambivalence. Translated into the summed scores, for the 4-item subscales with a range from 4 to 24, scores of 4 to 12 are dissatisfied, 16 to 24 are satisfied, and between 12 and 16 are ambivalent. For the 20-item total where possible scores range from 20 to 120, the ranges are 20 to 60 for dissatisfaction, 80 to 120 for satisfaction, and between 60 and 80 for ambivalent.
3.6.3 Analysis of the Third Objective
To analyze the third objective, Pearson’s Correlation Coefficient is applied to show the correlation between the two variables, emotional intelligence (independent variable) and job satisfaction (dependent variable). The strength of the association between the two variables or significant relationship is measured. Pearson’s correlation coefficient (r) for continuous interval data ranges from -1 to +1:
Figure 3.1 Pearson’s correlation coefficient (r) for continuous interval data ranges
r = 0
r = -1 r = +1
Positive correlation indicates that both variables increase or decrease together, whereas negative correlation indicates that as one variable increases, so the other decreases, and vice versa. It measures the strength of the linear relationship between two variables. Correlation coefficients range from -1.00 to +1.00. The value of -1.00 represents a perfect negative correlation while a value of +1.00 represents a perfect positive correlation. However, a value of 0.00 represents a lack of correlation. Table 3.6 shows the degree of significance between two variables based on the correlation scale (r).
Table 3.6 Degree of Significance
Pearson’s Correlation Coefficient (r)
Degree of Significance
0.00 – 0.20
Extremely Low
0.20 – 0.40
Low
0.40 – 0.60
Moderate
0.60 – 0.80
High
0.80 – 1.00
Extremely High
3.6.4 Analysis of the Fourth Objective
And lastly, to analyze the fourth objective, R-Squared is utilized to measure the influence of emotional intelligence towards job satisfaction level. It is a statistical term saying how good one term is at predicting another.A When R-Squared is equal to 1.0, it means given the value of one variable, the value of another variable can be perfectly predicted.A When R-Squared is equal to 0.0, then knowing one variable does not help to know the other variable at all.A More generally, a higher value of R-Squared means can better predict one variable from another. Customarily, the degree to which two or more predictors (independent or X variables) are related to the dependent (Y) variable is expressed in the correlation coefficient R, which is the square root of R-square. In multiple regression, R can assume values between 0 and 1.
As mentioned earlier, the correlation coefficient (r) represents the linear relationship between two variables. However, if the correlation coefficient is squared, then the resulting value (r2, the coefficient of determination) will represent the proportion of common variation in the two variables, which shows the strength or magnitude of the relationship. It is important to know the magnitude or strength as well as the significance of the correlation in order to evaluate the correlation between emotional intelligence and job satisfaction.
3.7 Summary
In brief, methodology of this study was designed cautiously and systematically to analyze the data in order to ensure that the objectives of the study are accomplished as well as the research questions were answered reasonably. The Trait Meta-Mood Scale (TMMS) was used to measure the level of emotional intelligence possessed by the respondents. And yet, Job Satisfaction Survey (JSS) was adopted and modified to measure the degree of job satisfaction among the respondents. The relationship between emotional intelligence and job satisfaction was assessed through Pearson correlation to determine whether there is a significant relationship exists. Furthermore, the influence of emotional intelligence towards job satisfaction was measured through Regression Squared as well. The results derived from the questionnaire after going through all those steps of data collection and data analysis will be demonstrated in subsequent chapters behind this.
