I. INTRODUCTION AND REVIEW CONTEXT

Human Resource Management (HRM) is regarded as the significant department for talent management. The talented employees compulsorily considered as assets in the organization which can be effective through acquisition, development, motivation and maintenance integrated from all units of the bank. HRD selects the right kind of personnel for the committed posts. In addition to this, HRD maintains talent human resources for the bank by applying various motivational techniques and HRs considered as soft assets (www.ventureline.com). Since bank is a service industry, this is why, its sustainability and competitive opportunities depends on how HR Department utilize their potentialities and competencies. The need of talent employees is well recognized in all events of global financial crisis (2007-2008) that was mostly connected with ambitious and ineffectual investment decision by the banks (Islam et al, 2017). Bangladesh Bank (BB) and Ministry of Finance (MoF) emphasized to ensure better HRM in the banking sector of Bangladesh through circulars (BB & MoF, 2015). The circulars are associated with rules and regulations, maintaining banking hours, salaries and incentives, leave and performance appraisal of female employees.

Motivation means inspiring people to work continuation. Motivated employees do have best quality of performance. Employees' motivation is affected by various factors. The total environment of the banking industry has become changed due to face the competitive sustainability. Basic pay, gross pay, designation, promotion, scoring of banking diploma for promotion, experiences, location or posting, types of bank etc. are the issues of demographic factors. Designation and gross pay are highly correlated for motivation.

Different emerging theories of motivation support that age, experience, pay, designation etc. affect the motivation. Work experience relates the holding position through up gradation in the organization. Maslow's need hierarchy theory proves the said issues of demographic (Maslow, 1954). On the other supportive part of the Two-Factor Model namely Hygiene and Motivating factors. Employees can enjoy these factors related to opportunities over a long-term service the organization (Herzberg, 1959, 1987). The Two Factor Theory states that human needs are ordered in a series of levels of the hierarchy accordance to importance which creates motivation. Alderfer's (1969) ERG theory chains Need-Hierarchy and Two-Factor Theory of motivation. Existence (E) chains the basic need and job security, relatedness (R) actually related to social needs and growth (G) is supportive with status and highest level achievement. If a higher order need constants or unfulfilled, an individual can degenerate to lower order needs which cause satisfy easily. McClellend's Three Needs Model (1961) is also supportive to Needs Theory of Maslow whereas it can be seen that need for affiliation (social need), need for power related to ego/status and remaining one that is need for achievement connected to challenging achievement. An employer does have the ability to understand the needs so as to meet these needs having a better chance of involving and retaining talent employees. A survey conducted by Watson Wyatt Worldwide showed that $71\mathrm{\%}$ people deliberate money as the main reason to stay as followed by promotion prospect $(33\mathrm{\%})$ (Endress, 2007). Abraham Harold Maslow suggested a theory that delineated five hierarchical needs which could also be functional to an organization and its employees' performance (Gordon, 1965). Without one of the lower ones the second need could be achieved or satisfied. Maslow's needs theory is static imperative and applicable in today's business organizations, for every organization that seek to obtain success and excellence reflects positively the organizational culture, HRM and the employee's productivity, to attain organizational excellence and create good environment, better and enjoyable work environment and achieve goal at the right time then a effort and application of the theory is supreme (Jerome, 2013). When an organization tries to know what drives personnel to work more, it is in a better position to influence them to perform well (Kovach, 1987). Again it clarifies that employees performance can be examined by three indicators namely ability, workplace environment, and motivation (Griffin, 1990). It is critical job for the managers in terms of motivating subordinates since it is noticed that there globally changes in demographic factors, as well as highly advanced technology (Wiley, 1997). This only emphasized the need to explore what motivates employees in order to get better performance. The author highlighted the most and less important factors of motivation in workplace from the earlier management. The most important factors in 1946 (appreciation), 1980 (interesting work), 1986 (interesting work) and 1992 (good wages) and less important factors were in 1946 (discipline), 1980 (discipline), 1986 (personal problems), and 1992 (personal problems). The study received the most striking findings that money and job security are the clear indicators of motivation. The effective pay program, a primary motivating factor is critical due to individuals and psychological possessions. It is does have immaterial value of the reward, but the increase in self-regard that public recognition accompanying with monetary compensation affords (Dawson and Dawson, 1990). In the past, huge numbers of research studies on employee motivation in the different perspectives already conducted. Very few of them were conducted relating to demographic composition with motivation. The present paper stressed to observe the influential factors of motivation with the sources variables of demographic issues among the employees in the sampled banks. The study also designed to explore the most effective factors in motivation.

Research questions: Does demographic composition affect employee motivation in the banking sector?

Objective of the study: The main objective of the study was to scan effective factors in demographic and motivating focuses among the employees of the banking sector in Bangladesh.

II. RESEARCH FRAMEWORK

Hypotheses

Alternative hypotheses ( $H_a$ )

$H_{a1}$ Employee motivation is related to work experience in the sampled banks.

$H_{a2}$ There is a positive relationship between employee motivation and present basic salary

$H_{a3}$ Present gross salary affects employee motivation in the banking sector.

$H_{a4}$ Initial basic salary motivates employees positively. $H_{a5}$ Initial gross salary motivates employee positively.

III. METHODOLOGY

The study has been designed based on empirical and quantitative materials. The employees who were in the service full time in the banks considered as participants. The primary data were collected during

March-June 2019 from 400 employees (320 employees of four public and remaining 80 employees of six private banks operated in the Northern three districts of Rangpur Division Bangladesh through sample random sampling (SRS). Data have been analyzed by SPSS IBM Version 22.0. Secondary data were collected from different research articles, published and unpublished books, dailies and websites.

IV. RESULTS AND DISCUSSION

Demographic issues		Percent	Mean	SD	CV
Sex	Male	83.5	1.165	0.372	31.93%
	Female	16.5
Age group	<30-40 years	59.5	2.633	0.922	35%
	41-50 years	13.8
	>50 years	26.8
Marital status	Married	99.0	1.010	0.100	9.86%
	Single	1.0
Religion	Islam	89.3	1.110	0.321	18.94%
	Hindu	10.75
Type of bank	Public	80.0	1.200	0.401	33.38%
	Private	20.0
Location (District)	Rangpur	41.5	1.743	0.712	40.88%
	Dinajpur	42.8
	Nilphamari	15.8
Educational Qualification	Bachelor	17	2.660	0.749	28.15%
	Master	83
Discipline/ Group	Science	31.8	1.865	0.695	37.26%
	Humanities	50
	Business	18.3
Bank Diploma	Nil	62.3	0.543	0.761	140.34%
	Part-1	21.3
	Part-2	16.5
Job Experience (Year)	1-5	11.3	2.985	1.483	49.70%
	6-10 Years	45.5
	11-15 Years	8.0
	16-20 Years	4.0
	20 Years (more)	31.3
Present Designation/ Post	Entry Level Officer	77.4	5.505	1.319	23.96%
	Executive Level Officer	22.9
Present Basic Pay (Tk.)	<10000- 300000/-	49.0	35512	14246	40.12%
	30000/- (more)	511.0
Present Gross Pay (Tk.)	<20000-40000/-	19.0	60945	26809	44%
	>40000-60000/-	38.0
	60000/- (more)	43.0
First Joining Designation	Entry Level Officer	99.5	4.110	1.925	46.85%
	Executive Level Officer	0.5
Initial Basic Pay (Tk.)	<10000-20000/-	96.6	35512	14246	40.12%
	>20000-30000/-	3.5
Initial Gross Pay (Tk.)	<20000-40000/-	98.8	13401	16433	122.63%
	40000-60000/- (more)	1.2

Table 2: Regression: Model Summary

${}^b$

Model	R	R Square	Adjusted R Square	Std. Err. of Estimates	Change Statistics
					$R^2$ Change	F	df1	df2	Sig. F
1	${0.971}^a$	0.942	0.940	2.741	0.94	483.94	13	386	0.000
a. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla).
b. Dependent Variable: Working experience (year).

Remarks: The fitted linear regression model for working experience (year) and other independent variables listed. The model is good fit for this dataset and the coefficient of multiple determinations $R^2$ is 0.942 (Table

2). Since the $R^2\sim 0.94$ then the dependent variable work experience 94% explained by the independent variables/predictors.

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	47261.760	13	3635.520	483.944	${0.000}^b$
	Residual	2899.737	386	7.512
	Total	50161.498	399
a. Dependent Variable: Working experience (year)
b. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla).

Remarks: From the Table 3 ANOVA table the fitted regression model F-test statistic value is 483.944 and the significance value (p value) 0.000 which is less than 0.05 (p value< $\alpha$ ). Then all the regression coefficients were statistically highly significant at 5% level of significance. That is the null hypothesis is rejected and alternative hypothesis is accepted. Therefore, all the regression coefficients were not zero (0).

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant: Experience)	-16.110 (B0)	2.519		-6.395	0.000
	Gender	0.664 (B1)	0.402	0.022	1.652	0.099
	Age	0.800 (B2)	0.034	0.663	23.649	0.000
	Marital status	0.697 (B3)	1.417	0.006	0.492	0.623
	Religion	-0.535 (B4)	0.439	-0.015	-1.220	0.223
	Present designation	1.294 (B5)	0.181	0.152	7.150	0.000
	First joining post	-1.663 (B6)	0.147	-0.286	-11.334	0.000
	Type of Bank	-0.567 (B7)	0.636	-0.020	-0.891	0.374
	Name of the Bank	-0.192 (B8)	0.113	-0.039	-1.697	0.091
	Location (District)	0.341 (B9)	0.665	0.020	0.512	0.609
	Location (Upazilla)	-0.055 (B10)	0.098	-0.023	-0.555	0.579
	Educational qualif.	-0.860 (B11)	0.257	-0.057	-3.343	0.001
	Group/ Subject	0.001 (B12)	0.206	0.000	0.005	0.996
	Banking Diploma	0.013 (B13)	0.223	0.001	0.059	0.953
a. Dependent Variable: Working experience (year).

• Religion + 1.294 * Presentdesignation - 1.663 * Firstjoiningdesignation - 0.567

• TypeofBank - 0.192 * NameoftheBank + 0.341 * Location(Disrtict) - 0.055

• Location(Upazilla) - 0.860 * Educationalqualification + 0.001 * GrouponSubject + 0.013

• BankingDiploma

Remarks: From the fitted (Table 4) the age, present designation, first joining designation, educational qualification were statistically significance at 5% level of significance. Therefore, employees' motivation is exaggerated by the control variable namely age, designation, and educational qualification. The subject or major discipline does not directly affect motivation $({\beta }_{12})=0.001$ and p value is 0.996. Among the significant independent predictors age (0.800) and present designation (1.294) were positive contribution on the dependent variable working experience (year).

Figure 1 & 2: Histogram and P-P Plot of Regression Standardized Residual (Experience)

Remarks: The Figure 1 & 2 depict that the fitted histogram showed the bell shape curve and Q-Q (quantile-quantile) plot the fitted residual line passing through the origin. Therefore, the dependent variable working experience (year) is normally distributed and the linear regression model best fit for this dataset.

Model	R	$R^2$	Adjusted $R^2$	Std. Err. of the Estimates	Change Statistics
					$R^2$	F change	df1	df2	Sig. F
1	${0.877}^a$	0.769	0.762	6987.86	0.769	99.1	13	386	0.000
a. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla).
a. Dependent Variable: Present Basic Salary.

Remarks: The above fitted linear regression model (Table 5) for present basic salary and other independent variables listed. The model is good fit for this dataset and the coefficient of multiple determinations $R^2$ is

0.769. Since the $R^2\sim 0.769$ then the dependent variable present basic salary 76.9% or about 77% explained by the independent variables/predictors mentioned above.

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	62872948092.258	13	4836380622.481	99.045	${0.000}^b$
	Residual	18848472031.68	386	48830238.424
	Total	81721420123.94	399
a. Dependent Variable: Present Basic Salary
b. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla).

Remarks: From the (Table 6) ANOVA (Analysis of Variance) table the fitted regression model F-test statistic value is 99.045 and the significance value (p value) 0.000. Then all the regression coefficients were statistically strongly significant at 5% level of significance. That is alternative hypothesis is accepted. Therefore, all the regression coefficients were not zero (0).

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Cons: Present basic pay)	-38670.051 ( $B_0$ )	6422.814		-6.021	0.000
	Gender	554.461 ( $B_1$ )	1024.262	0.014	0.541	0.589
	Age	709.891 ( $B_2$ )	86.209	0.461	8.235	0.000
	Marital Status	-5124.611( $B_3$ )	3613.823	-0.036	-1.418	0.157
	Religion	1360.314 ( $B_4$ )	1118.681	0.031	1.216	0.225
	Present designation	6201.641( $B_5$ )	461.322	0.571	13.443	0.000
	First joining post	1902.867 ( $B_6$ )	374.125	0.256	5.086	0.000
	Type of Bank	1834.212 ( $B_7$ )	1621.950	0.051	1.131	0.259
	Name of the Bank	282.551 ( $B_8$ )	289.017	0.045	0.978	0.329
	Location (District)	-1672.287 ( $B_9$ )	1695.606	-0.078	-0.986	0.325
	Location (Upazilla)	74.986 ( $B_{10}$ )	250.856	0.024	0.299	0.765
	Educational qualifi.	1623.504 ( $B_{11}$ )	656.077	0.085	2.475	0.014
	Group/ Subject	-323.377 ( $B_{12}$ )	525.967	-0.016	-0.615	0.539
	Banking Diploma	878.569 ( $B_{13}$ )	569.666	0.047	1.542	0.124
a. Dependent Variable: Present Basic Salary ( $B_0$ )

Remarks: From the fitted (Table 7) the age, present designation, first joins designation, educational qualification were statistically significance at 5% level of significance. Among the significant independent predictors age (709.891), present designation (6201.641) and first joining designation/post (1902.867) were positive contribution to the dependent variable present basic salary.

Figure 3 & 4: Histogram and P-P Plot of Regression Standardized Residual (Present basic salary)

Remarks: From the fitted histogram (Figure 3 & 4) showed the bell shape curve and Q-Q (quantile-quantile) plot the fitted residual line passing through the origin. Therefore, the dependent variable Present Basic Salary is normally distributed and the linear regression model best fit for this dataset.

Model	R	$R^2$	Adjusted $R^2$	Std. Err. of the Estimates	Change Statistics
					$R^2$	F change	df1	df2	Sig. F
1	${0.826}^a$	0.682	0.672	15365.25	0.682	63.742	13	386	0.000
a. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla)
b. Dependent Variable: Present gross salary

Remarks: The fitted linear regression model (Table 8) for Present Gross Salary and other independent variables listed above. The model is good fit for this dataset and the coefficient of multiple determinations $R^2$ is 0.682.

Since the $R^2\sim 0.682$ then the dependent variable present gross salary 68.2% explained by the independent variables/predictors.

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	195635872639.298	13	15048913279.950	63.742	${0.000}^b$
	Residual	91131097360.703	386	236090925.805
	Total	286766970000.000	399
a. Dependent Variable: Present gross salary
b. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla)

The alternative hypothesis, H1: $B_0=B_1=B_2=\dots \dots =B_{13}\ne 0$

Remarks: From the (Table 9) ANOVA (Analysis of Variance) table the fitted regression model F-test statistic value is 63.742 and the significance value (p value) 0.000. Then all the regression coefficients were statistically highly significant at 5% level of significance. That is, alternative hypothesis is accepted. Therefore, all the regression coefficients were not zero (0).

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant: Present gross)	-76402.124	14122.791		-5.410	0.000
	Gender	1172.807	2252.196	0.016	0.521	0.603
	Age	1244.412	189.561	0.432	6.565	0.000
	Marital Status	-9286.091	7946.247	-0.035	-1.169	0.243
	Religion	1028.259	2459.809	0.012	0.418	0.676
	Present designation	10226.033	1014.378	0.503	10.081	0.000
	First joining design.	3129.422	822.645	0.225	3.804	0.000
	Type of Bank	15523.420	3566.423	0.232	4.353	0.000
	Name of the Bank	420.502	635.505	0.036	0.662	0.509
	Location (District)	-4565.112	3728.379	-0.113	-1.224	0.222
	Location (Upazilla)	326.900	551.594	0.057	0.593	0.554
	Educational qualification	2791.159	1442.615	0.078	1.935	0.054
	Group/ Subject	-282.423	1156.521	-0.007	-0.244	0.807
	Banking Diploma	1700.733	1252.610	0.048	1.358	0.175
a. Dependent Variable: Present gross salary

Present Gross Salary

Remarks: From the (Table 10) fitted the age, present designation, first joins designation, educational qualification were statistically significance at 5% level of significance. Among the significant independent predictors age (1244.412), present designation (10226.033), first joining designation/post (3129.422) and type of bank (15523.420) were positive contribution to the dependent variable Present Gross Salary. Therefore, there is a strong association among age, present designation, joining post and type of bank that affect employee satisfaction.

Figure 5 & 6: Histogram and P-P Plot of Regression Standardized Residual (Present gross salary)

Remarks: From the fitted histogram (Figure 5 & 6) showed the bell shape curve and Q-Q (quantile-quantile) plot the fitted residual line passing through the origin. Therefore, the dependent variable Present Gross Salary is normally distributed and the linear regression model best fit for this dataset.

Model	R	$R^2$	Adjusted $R^2$	Std. Err. of the Estimates	Change Statistics
					$R^2$	F change	df1	df2	Sig. F
1	${0.689}^a$	0.475	0.457	5713.00316	0.475	26.857	13	386	0.000
a. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla).
b. Dependent Variable: Initial basic salary

Remarks: The fitted linear regression model (Table 11) for Initial Basic Salary and other independent variables listed above. The model is fit for this dataset and the coefficient of multiple determinations $R^2$ is 0.475. Since the $R^2\sim 0.475$ then the dependent variable initial basic salary 47.5% explained by the independent estimators.

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	11395615319.173	13	876585793.783	26.857	${0.000}^b$
	Residual	12598424380.577	386	32638405.131
	Total	23994039699.750	399
a. Dependent Variable: Initial basic salaryb. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla)

Remarks: From the ANOVA Table, the fitted regression model F-test statistic value is 26.857 and the significance value (p-value) is 0.000. Then, all the regression coefficients were statistically significant at a 5% level of significance. That is, the null hypothesis is rejected and the alternative hypothesis is accepted. Therefore, all the regression coefficients were not zero(0).

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant: Initial Basic Pay)	6234.435	5244.365		1.189	0.235
	Gender	-350.697	838.100	-0.017	-0.418	0.676
	Age	-121.912	71.022	-0.146	-1.717	0.087
	Marital Status	1247.972	2977.753	0.016	0.419	0.675
	Religion	-21.884	918.839	-0.001	-0.024	0.981
	Present Designation	-671.561	378.451	-0.114	-1.775	0.077
	First joining designation/post	2220.853	308.118	0.551	7.208	0.000
	Type of Bank	-1285.682	1402.737	-0.066	-0.917	0.360
	Name of the Bank	1064.391	236.772	0.326	4.495	0.000
	Location (District)	1761.002	1401.011	0.162	1.257	0.210
	Location (Upazilla)	-280.441	206.022	-0.178	-1.361	0.174
	Educational Qualification	-879.276	538.907	-0.085	-1.632	0.104
	Group/ Subject	-306.230	431.933	-0.027	-0.709	0.479
	Banking Diploma	-199.290	462.560	-0.020	-0.431	0.667
a. Dependent Variable: Initial basic salary

From the fitted coefficients (Table 13) the first name of the bank were statistically significant at 5% level of significance. Among the significant independent predictors first joining designation/post (2220.853) and name of bank (1064.391) were positive contribution to the dependent variable Initial Basic Salary.

Comment: From the fitted coefficients (Table 13) the, first name of the bank were statistically significance at 5% level of significance. Among the significant independent predictors first joining designation/post (2220.853) and name of bank (1064.391) were positive contribution to the dependent variable Initial Basic Salary.

Figure 7 & 8: Histogram and P-P Plot of Regression Standardized Residual (Initial basic salary)

Remarks: From the Figure 7 & 8 depict that the fitted histogram showed the bell shape curve and Q-Q (quantile-quantile) plot the fitted residual line passing through the origin. Therefore, the dependent variable initial basic salary is normally distributed and the linear regression model best fit for this dataset.

Model	R	$R^2$	Adjusted $R^2$	Std. Err. of the Estimates	Change Statistics
					$R^2$	F change	df1	df2	Sig. F
1	${0.592}^a$	0.351	0.329	13459.34450	0.351	16.058	13	386	0.000
a. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla)
b. Dependent Variable: Initial gross salary

Table 15: ANOVA

${}^a$

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	37815785084.065	13	2908906544.928	16.058	${0.000}^b$
	Residual	69925426394.726	386	181153954.390
	Total	107741211478.791	399
a. Dependent Variable: Initial gross salaryb. Predictors: (Constant), Banking Diploma, Group/ Subject, Gender, Religion, Educational Qualification, Marital Status, Location (District), Type of Bank, Present Designation, First joining designation/post, Name of the Bank, Age, Location (Upazilla)

Remarks: From the Table 15 (ANOVA) the fitted regression model F-test statistic value is 16.058 and the significance value (p value) 0.000. Then all the regression coefficients were statistically significant at 5% level of significance. That is the null hypothesis is rejected. Therefore, all the regression coefficients were not zero (0).

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant: Initial Gross Pay)	181.712	12371.000		0.015	0.988
	Gender	25.992	1972.834	0.001	0.013	0.989
	Age	-90.130	166.047	-0.051	-0.543	0.588
	Marital Status	5525.183	6960.595	0.033	0.794	0.428
	Religion	-251.863	2154.695	-0.005	-0.117	0.907
	Present designation	-1829.536	888.554	-0.147	-2.059	0.040
	First joining designation	4425.217	720.604	0.519	6.141	0.000
	Type of Bank	-1458.181	3124.043	-0.036	-0.467	0.641
	Name of the Bank	2449.083	556.677	0.337	4.399	0.000
	Location (District)	2369.895	3265.911	0.096	0.726	0.468
	Location (Upazilla)	-360.575	483.174	-0.102	-0.746	0.456
	Educational qualification	-1895.923	1263.673	-0.086	-1.500	0.134
	Group/ Subject	164.586	1013.066	0.007	0.162	0.871
	Banking Diploma	321.652	1097.236	0.015	0.293	0.770
a. Dependent Variable: Initial Gross Salary

Figure 9 & 10: Histogram and P-P Plot of Regression Standardized Residual (Initial gross pay)

Remarks: From the fitted histogram (Figure 9 & 10) showed the bell shape curve and Q-Q (quantile-quantile) plot the fitted residual line passing through the origin. Therefore, the dependent variable initial gross salary is normally distributed and the linear regression model best fit for this dataset.

$H_a$	Results	Remarks	Relationship/ effect on employee motivation
$H_{a1}$	p<0.05	Sustained	Employee motivation is related to work experience.
$H_{a2}$	p<0.05	Sustained	There is a relationship between motivation present basic pay.
$H_{a2}$	p<0.05	Sustained	Present gross salary affects employee motivation.
$H_{a1}$	p<0.05	Sustained	Initial gross salary motivates employee positively.
$H_{a1}$	p<0.05	Sustained	Initial basic salary motivates employees positively.
Therefore, employee motivations affected by all the factors of demographic issues in the banks were accordingly observed.

Overall it can be explained that employees are in the service of the banking sector influenced by the age, experience, present designation, joining post, type of bank, present and initial gross. There were strong relationships among these control or sources variables in the study. Gender did not affect the satisfaction of the bank employees. Among these factors the most effective factors were age and present designation (standardized Beta coefficient value 0.663 and 0.571). On the other hand, banking diploma mostly affects the promotion in case of public bank.

Dependent variable	$R^2$	Standardized coefficient	Effective factors	Motivation
Work experience	94%	Age ( $\beta =0.663$ ), present designation ( $\beta =0.152$ )	Age	Therefore, motivation is highly associated and modified by demographic effective factors already explored in column 4.
Present basic pay	77%	Present designation ( $\beta =0.571$ ), age ( $\beta =0.461$ ), and first joining designation ( $\beta =0.256$ )	Present designation
Present gross pay	68.2%	Present designation ( $\beta =0.503$ ), age ( $\beta =0.432$ ), type of bank ( $\beta =0.232$ )and first joining designation ( $\beta =0.225$ )	Present designation
Initial basic pay	47.5%	First joining designation ( $\beta =0.551$ ), and Name of the bank ( $\beta =0.326$ )	First joining designation
Initial gross pay	35.1%	First joining designation ( $\beta =0.519$ ), and Name of the bank ( $\beta =0.337$ )	First joining designation

It is evident from the Table 18 work experience is 94% explained by variance whereas age is strongly associated with job experience. Present basic salary 77% is explained by total predictors and it is highly affected by present designation of the existing employees. Present gross salary 68.2% is varied by the estimators and it is mostly influenced by present position of an employee. Initial basic salary is 47.5% ~48% explained by variance and is prejudiced by first joining designation. Initial gross salary 35.1% is explained by total variance and it is strongly affected by employees' first joining designation. Therefore, employees' motivation of the banking sector of Bangladesh is highly associated with work experience, present and initial salaries which are mostly modified by age, present and initial designation. Finally, equation may be Employee Motivation = f (Age + Present designation + Initial designation).

V. CONCLUDING REMARKS

Motivation is a complex to determine its level. The study found from the empirical analysis based on demographic outlined that the most effective factors age, present designation, first joining designation were explored and strongly associated with employee motivation in the banking sector of Bangladesh. Sample area, job experience and pay were considered only which may confine the scope of the study. Lack of huge context of the research is another limitation in the paper. Further study should emphasize in a larger scale of employee perception concentrating on job security and money or pay intrinsically as well as extrinsically.

ACKNOWLEDGEMENT

The author of this article is grateful to the honorable Professor Dr. Md. Omar Faruk Sarker (PhD Supervisor of the author), Marketing Department, & Dr. Md. Kamruzzaman (PhD Co-Supervisor of the author), Associate Professor (Statistics), IBS, University of Rajshahi, Bangladesh.