Research Journal of Commerce & Behavioural Science - RJCBS
Research Journal of Commerce & Behavioural Science - RJCBS
Research Journal of Commerce & Behavioural Science - RJCBS
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<strong>Research</strong> Methodology<br />
Questionnaire and its Construct Validity<br />
Based on the above literature review, an elevenitem<br />
questionnaire is prepared following 5–point Likart<br />
scale (1 = Strongly Disagree, 5 = Strongly Agree and 3 =<br />
Neutral). Conceptually ‘3’ represents neither satisfied nor<br />
dissatisfied with the variable. Thus, recording ‘4’ and ‘5’<br />
represent satisfaction, the higher the number, the greater the<br />
satisfaction level. Similarly, recording ‘1’ and ‘2’ represent<br />
dissatisfaction, the lower the number, the greater the level <strong>of</strong><br />
dissatisfaction.<br />
For this study, 600 questionnaires were distributed<br />
among the employees <strong>of</strong> 18 different private companies in<br />
Dhaka, Bangladesh out <strong>of</strong> which 467 questionnaires were<br />
received. Each <strong>of</strong> the response received systematically<br />
screened for errors, incomplete and missing responses.<br />
However, those responses that still contained questions in<br />
the survey questionnaire that had been remained unanswered<br />
or left incorrectly answered finally discarded from data<br />
analysis in order to establish a rationality <strong>of</strong> analysis through<br />
proper representation. After having the screening process<br />
completed, 437 responses found valid for data analysis. This<br />
represents a rate <strong>of</strong> 72.8%, which is considered extremely<br />
well in view <strong>of</strong> time, cost, certainty and geographical<br />
constraints (Sandelowski, 1995).<br />
The results obtained from 437 respondents have been<br />
thoroughly analyzed and the outputs <strong>of</strong> the results have been<br />
clearly explained in this section. Applying SPSS, the<br />
principal component analysis (PCA) was carried out to<br />
explore the underlying factors associated with 11 items. The<br />
constructs validity was tested applying Bartlett’s Test <strong>of</strong><br />
Sphericity and The KMO measure <strong>of</strong> sampling adequacy<br />
analyzing the strength <strong>of</strong> association among variables. The<br />
KMO measure <strong>of</strong> sampling adequacy (KMO) was first<br />
computed to determine the suitability <strong>of</strong> using factor<br />
analysis. It helps to predict whether data are suitable to<br />
perform factor analysis. KMO is used to assess which<br />
variables to drop from the model due to multicollinearity<br />
problem. The value <strong>of</strong> KMO varies from 0 to 1, and KMO<br />
overall should be 0.60 or higher to perform factor analysis.<br />
If this does not have achieved, then it is necessary to drop<br />
the variables with lowest anti image value until KMO<br />
overall rises above .60.<br />
The analysis began with an examination <strong>of</strong> the<br />
measurement in terms <strong>of</strong> its reliability and its construct<br />
validity. The composite reliability coefficients <strong>of</strong> the<br />
measurements scale satisfied Nunally’s (1978) guidelines<br />
(Cornbatch Alpha = 0.87). The scale items <strong>of</strong> job, pay,<br />
promotion, supervision, colleague and working environment<br />
are shown in the following Table 1 along with the<br />
corresponding descriptive statistics and reliability. Result for<br />
the Bartlett’s Test <strong>of</strong> Sphericity and the KMO reveal that<br />
both were highly significant and eventually concluded that<br />
this variable was suitable for the factor analysis. According<br />
to the Sekeran (2000) Cronbach alpha is reliability<br />
coefficient that indicates how well the items are positively<br />
correlated to one another. Reliability coefficient tested by<br />
using Cronbach’s alpha (α) analysis. In order to measure the<br />
reliability for a set <strong>of</strong> two or more constructs, Cronbach<br />
alpha is a commonly used method where alpha coefficient<br />
values range between 0 and 1 with higher values indicating<br />
higher reliability among the indicators (Hair, et al., 2010).<br />
After the re-allocation <strong>of</strong> the eleven items, the Reliability<br />
test was conducted to ensure that, the extracted three factors<br />
are appropriate for this grouping. In accordance with the<br />
Cronbach alpha test, the total scale <strong>of</strong> reliability for this<br />
study varies from 0.72 to 0.81, indicating an overall higher<br />
reliability factors. The reliability <strong>of</strong> this study is substantial<br />
in every perspective, as the highest reliability value that can<br />
be achieved is 1.0.<br />
Results and Discussion<br />
Results from the primary data focused on the descriptive<br />
analysis based on the frequency Table 1. Regarding the<br />
length <strong>of</strong> employment as shown in (Table 1), with three<br />
categories: firstly, those below 10 years are 32.7 %.<br />
Secondly, between 10 to 20 years is 42.3 % where as those<br />
above 20 years, which is 25 %. It showed that, 75 % <strong>of</strong> the<br />
respondents have the opportunity to serve for the next 10 to<br />
20 years.<br />
Respondent’s demographic pr<strong>of</strong>ile is shown in<br />
Table 3, out <strong>of</strong> the total participation <strong>of</strong> 437, 80.6 % were<br />
males and 19.4 % were females. As for the education level,<br />
22.6 % were degree holders while 77.4 % were those with<br />
diploma, secondary and primary schools qualifications.<br />
Types <strong>of</strong> employee indicated that, 27.7 % were executives<br />
and 72.3 % were nonexecutive. Out <strong>of</strong> this 27.7 %<br />
executives, 5.8 % are managers and above.<br />
Further, regression analysis was conducted in order<br />
to find out respective strength <strong>of</strong> the determinants <strong>of</strong> job<br />
satisfaction. The dependent variable Job satisfaction has<br />
been regressed by job, pay, promotion, supervision,<br />
colleagues, and environment. The regression results are<br />
shown in Table 4.<br />
Table 4 shows that H1, H2, H3, H4 are accepted (p<br />
< 0.05) while H5 and H6 are rejected. The factors <strong>of</strong> interest<br />
<strong>of</strong> this study (i.e. the independent variables) claim 70% <strong>of</strong><br />
the variance explained by the dependent variable Job<br />
Satisfaction. Out <strong>of</strong> the six determinants, four factors (Job,<br />
Pay, Promotion, and Supervision) are found to have<br />
significant positive impact on job satisfaction. The rest two<br />
factors – colleagues and environment are not found to have<br />
significant impact on job satisfaction. Out <strong>of</strong> the four<br />
significant factors, job has the strongest impact on job<br />
satisfaction with beta value 0.462 followed by promotion,<br />
pay and supervision.<br />
Therefore, employees <strong>of</strong> Bangladesh consider their<br />
job, pay promotion and supervision as the key factors <strong>of</strong><br />
perceiving their job as satisfied. Among these factors, they<br />
consider the job itself as the most important factor followed<br />
by the scope for promotion, pay and supervision. On the<br />
other hand, they do not consider colleagues and environment<br />
as influencing factors to be satisfied with their jobs.<br />
www.theinternationaljournal.org > <strong>RJCBS</strong>: Volume: 01, Number: 08, June-2012 Page 31