Factors Affecting the Loyalty of Public Bank Employees in Bangladesh

Table of contents

1. Introduction

Public bank is one of the largest government sector banks in Bangladesh. In the public banks more employees are being employed compared to private banks of Bangladesh. People feel comfortable to work with these public banks as they do not have much pressure and a threat from their employer banks. Hence, the performances of public sector banks are often poor in Bangladesh. Serious concern has already been developed regarding the loyalty of the public banks of Bangladesh which are instrumental for the poor performance. The reason could be attributed by the reluctance in control and the permanent job arrangement. Therefore, the loyalty of the public bank employees is a serious question among the policy makers in this sector of Bangladesh. The encyclopedic aim of this study is to identify the factors that are concerned with the loyalty of public bank employees in Bangladesh. The specific objectives are as follows.

i. To describe the loyalty issue of public banks in Bangladesh; ii. To identify the factors related to the loyalty of the public banks in Bangladesh; iii. To discern the significant factors concerned with the adherence of the public banks in Bangladesh.

II.

2. Methodology

The reason for this examination was to recognize the factors concerning the loyalty of the public banks in Bangladesh. Both primary and secondary information were utilized to conduct this study. Primary data has been collected from the government bank employees, and the secondary data has been collected from the books, magazines, and journals.

3. a) Details of the Respondents

Table 1 shows that 60% of the respondents were male, and 40% were female employees of the public banks in Bangladesh. The majority of the respondents were at the age of 31-40 years followed by 41-50 years, 21-30 years, and above 50 years (Table 2). Majority of the respondents are married (86.50%), and few were unmarried respondents (Table 3). Table 4 shows that most of the respondent employee's experience was at the of 5-10 years, followed by 10-15 years, more than 15 years and less than 5 years.

4. b) Sample Design and Determination of Sample Size

There are nine public banks in Bangladesh. Among these banks, three are specialized banks that are currently operating their services besides of six public commercial banks. The banks owned by the government are: (i) Uttara Bank Limited (ii) Sonali Bank Limited (iii) Rupali Bank Limited (iv) Rajshahi Krishi Unnayan Bank (v) Pubali Bank Limited (vi) Janata Bank Limited (vii) Bangladesh Krishi Bank (viii) Bangladesh Development Bank Limited and (ix) Agrani Bank Limited. It has been identified from the literature that there are about 77024 employees in nine government banks of Bangladesh (Table 5). The sample size of this study has been determined by using the following formula suggested by Yamane (1967).

?? = ?? 1 + ??(??) 2

Where n is the sample size, N is the population size, and e is the level of precision. For this study, level of precision is presumed as 0.07 and the population size is 77024. Putting these values in the above equation, the required number of sample size becomes approximately 204. This study interviewed 200bank employees of nine banks under study. This figure is well above the critical sample size of 200 for employing multivariate analysis (Hair et al., 1998).

Taking the accessibility and willingness of the employees to respond to this study into account, Convenience Sampling Method was used to draw the sampling units (Malhotra, 2007).

5. c) Questionnaire Design

The structured questionnaire was used in this research to collect information from public bank employees. Responses to all the statements in the questionnaire were measured on a five-point scale ranging from 1 to 5 with 1 indicating strongly disagree and 5 indicating strongly agree. One of the relative advantages of using this scale is its suitability for the applications of multifarious statistical tools used in marketing and social research study (Malhotra, 1999). The collected data were statistically processed subsequently to get useful information. The reliability statistics show that the internal consistency of the questionnaire is under the acceptable limit (Nunnally, 1978). The reliability statistics are at the acceptable level (Table 6). Data were collected from both primary and secondary sources. Primary data were used for the purpose of identifying the factors concerned with the loyalty of the public banks of Bangladesh. The survey was conducted among the 200 employees of nine public banks of Bangladesh. The survey was conducted in 2019. The interviewers were properly trained on the items included in the questionnaire for data collection before commencing the interview. Along with descriptive statistics 1 , inferential statistical 2 techniques such as, Factor Analysis and Multiple Regression Analysis were used to analyze the data. A Principal Component Analysis (PCA) with an Orthogonal Rotation (Varimax) 3 1 Descriptive statistics includes statistical procedures that we use to describe the population we are studying. The data could be collected from either a sample or a population, but the results help us organize and describe data. Descriptive statistics can only be used to describe the group that is being studying. That is, the results cannot be generalized to any larger group. 2 Inferential statistics is concerned with making predictions or inferences about a population from observations and analyses of a sample. That is, we can take the results of an analysis using a sample and can generalize it to the larger population that the sample represents.

using the SPSS (Statistical Package for Social Sciences) was performed on the survey data. Multiple Regression 3 Varimax rotation is an orthogonal rotation of the factor axes to maximize the variance of the squared loadings of a factor (column) on all the variables (rows) in a factor matrix, which has the effect of differentiating the original variables by extracted factor. Each factor will tend to have either large or small loadings of any particular variable. A varimax solution yields results which make it as easy as possible to identify each variable with a single factor. This is the most common rotation option.

6. Analysis 4

III.

7. Literature Review

Such Multiple Regression was conducted by using SPSS to identify the relationships between the dependent and independent variables and the significant factors. 7). 4

8. In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'Criterion

Variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed.

9. Analysis and Interpretations

In the analysis part of this paper, multivariate analysis like factor analysis and multiple regression analysis have been performed.

10. a) Results of Exploratory Factor Analysis (EFA)

The results of factor analysis show that the communalities of all variables concerning the loyalty of the public bank employees in Bangladesh are significantly high indicating the variables are fundamental in this study (Table 8). Table 9 shows the factors related to the loyalty of the public bank employees in Bangladesh. It shows that prompt service, well dressed and politeness of the bank employees are concerned with the loyalty of the public bank employees in Bangladesh. The variance of factor named prompt service is the highest (46.83%) followed by well dress and politeness (10.01%). The total variance of the data set is 56.86% indicates that a major portion of the data set has been included in the analysis. Table 10 shows the factor loadings of the variables constituted the factors are very high. It shows that the factor loadings of all the variables are high, indicating that the variables constituted the factor(s) have a higher level of relationships with them.

11. b) Results of Multiple Regression Analysis

Model summary also shows that the adjusted R square is 0.598, that indicates a higher level of relationships of the factors with the overall loyalty of the public bank employees in Bangladesh (Table 11). a. Rotation converged in 3 iterations.

Analysis of variance (ANOVA) shows that the two factors concerning the loyalty of the public bank employees in Bangladesh are significantly related to the overall loyalty of the employees of Bangladesh (Table 12). Table 13 shows that the factors such as prompt service and well dress and politeness are significantly related to the overall loyalty of the public bank employees in Bangladesh. a. Dependent Variable: Considering above factors, I am satisfied with the services of the bank to its stakeholders

12. V. Conclusions and Recommendations

The factor analysis results show that the variables used in the analysis have a higher level of relationship in the data set. The factors related to the loyalty of the public bank employees in Bangladesh identified in this study are prompt service, well dressed and politeness of the bank employees. The factor loadings of the variables constituted the factors are very high. It shows that the factor loadings of all the variables are high,specifying that the variables constituted the factor(s) have a higher level of relationships with them. The model summary also shows that the adjusted R square is 0.598, that interprets a significant correlation of the factors with the overall loyalty of the public bank employees in Bangladesh. Results also show that the factors such as prompt service and well dress and politeness are significantly related to the overall loyalty of the public bank employees in Bangladesh. This study recommends that the policymakers of the public banks of Bangladesh should focus on the prompt service and well dress and politeness of the employees for increasing the loyalty of their employees in the future. However, there is an ample scope to improve the results of this study by taking more samples into consideration in the future.

Figure 1. Table 1 :
1
Frequency Percent Valid Percent Cumulative Percent
Male 120 60.0 60.0 60.0
Female 80 40.0 40.0 100.0
Total 200 100.0 100.0
Figure 2. Table 2 :
2
Years Frequency Percent Valid Percent Cumulative Percent
21-30 42 21.0 21.0 21.0
31-40 67 33.5 33.5 54.5
41-50 58 29.0 29.0 83.5
Above 50 33 16.5 16.5 100.0
Total 200 100.0 100.0
Figure 3. Table 3 :
3
Frequency Percent Valid Percent Cumulative Percent
Married 173 86.5 86.5 86.5
Unmarried 27 13.5 13.5 100.0
Total 200 100.0 100.0
Figure 4. Table 4 :
4
Frequency Percent Valid Percent Cumulative Percent
Less than 5 Years 40 20.0 20.0 20.0
5-10 Years 62 31.0 31.0 51.0
10-15 Years 53 26.5 26.5 77.5
More than 15 Years 45 22.5 22.5 100.0
Total 200 100.0 100.0
Figure 5. Table 5 :
5
Sl. No. Name of the Bank Number of Branches Total Employees Year of Established
1. Janata Bank 912 12391 1971
2. Uttara Bank 235 3569 1965
3. Sonali Bank 1215 21839 1972
4. Rupali Bank 665 5150 1972
5. RajshahiKrishiUnnayan Bank 153 3,661 1987
6. Pubali Bank Limited 465 7204 1959
7. Bangladesh Krishi Bank 973 9166 1973
8. Bangladesh Development Bank Limited 32 775 2010
9. Agrani Bank Limited 953 13269 1972
Total Branches & Employees in Public Banks 5603 77024
Figure 6. Table 6 :
6
Cronbach's Alpha No. of Items
0.890 18
d) Data Collection & Analysis
Figure 7. Table 7 :
7
Compe nsation & benefits Work -life balance Organiz ation growth & reputation Superior subord inate relatio nship Level of satisf action Team work Work Envir onment Training & Develop ment Work flexi bility Skill recog nition Job Security Perfor mance appraisal Promotion Career Growth Welfare measures
? ? ? ?
(O. Adedeji, ? ? ?
Abosede
& C.
Ugwumad
u,
Obianuju.
2018)
(Shabnaz,
Figure 8. Table 8 :
8
Variables Extraction
1. The bank's corporal services are seeing attractive 0.731
2. Personnel are well dressed and appear neat in the bank 0.777
3. Personnel are polite in the bank 0.680
4. The personnel provide services timely 0.507
5. The personnel perform services accurately 0.554
6. The personnel provide prompt services to customer 0.550
7. Personnel have the required knowledge and skill to perform the services 0.403
8. The personnel's willingness to help customers is high 0.509
9. The personnel realize the exact desires of their clients 0.546
10. The Bank offers a complete range of services 0.610
11. The personnel are caring and provides individual attention to customer 0.502
Figure 9. Table 9 :
9
Factors Total Initial Eigenvalues % of Variance Cumulative %
1. Prompt Service 5.619 46.827 46.827
2. Well Dress and Politeness 1.202 10.018 56.845
Extraction Method: Principal Component Analysis.
Figure 10. Table 10 :
10
Figure 11. Table 11 :
11
Factors
Variables Prompt Service Well Dressed and Polite
The personnel provide prompt services to customer 0.728
The personnel realize the exact desires of their clients 0.698
The personnel perform services accurately 0.696
The personnel provide services timely 0.686
The personnel's willingness to help customers is high 0.631
Personnel have the required knowledge and skill to perform the services 0.604
The personnel are caring and provides individual attention to customer 0.537
Note: a. Predictors: (Constant), REGR factor score 2 for analysis 1, REGR factor score 1 for analysis 1
Figure 12. Table 12 :
12
Model Sum of Squares df Mean Square F Sig.
Regression 132.430 2 66.215 146.360 .000 a
Residual 89.125 197 0.452
Total 221.555 199
a. Predictors: (Constant), REGR factor score 2 for analysis 1, REGR factor score 1 for analysis 1
b. Dependent Variable: Considering above factors, I am satisfied with the services of the bank to its
stakeholders
Figure 13. Table 13 :
13
Model Unstandardized Coefficients Standardized Coefficients
B Std. Error Beta t Sig.
(Constant) 4.165 0.048 87.572 .000
Prompt Service 0.496 0.048 0.470 10.402 .000
Well Dressed and Polite 0.648 0.048 0.614 13.584 .000

Appendix A

Appendix A.1

Appendix B

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Date: 2019-01-15