







































22 

 

Finance, Accounting and Business Analysis 
Volume 1 Issue 1, 2019 

 

 

 

The Influence of The Performance Evaluation on Salary  

 
Dhiaa Shamki1, Aisha Al Shehemi2  
Department of Accounting, Komar University of Science and Technology, Sulaymaniyah-Kurdistan 

Region-Iraq1 

Ministry of Social Development in The Sultanate of Oman, Muscat2 

 

Info Articles   Abstract 

 
 
History Article: 
Received 30 May 2018 
Accepted  4 December 2018 
Published  29 January 2019 

 Objective: The purpose of the study is to indicate whether salary and the extra 
amount are influenced by performance evaluation linked collectively and 
simultaneously with position, gender, education and experience. It is found that the 
employee’s salary could be significantly and negatively influenced by performance 
evaluation, gender, education and performance evaluation moderated by gender, 
while the position, experience, performance evaluation moderated by position, 
education and experience have no effect on the salary. 

Methodology: The study examines 27,522 observation and 11 variables for 417 
governmental employees in Ministry of Social Developments in the Sultanate of 
Oman within 2011-2016 using descriptive statistics, correlation and regression 
analyses 

Results: It is found that the employee’s salary could be significantly and negatively 
influenced by performance evaluation, gender, education and performance 
evaluation moderated by gender, while the position, experience, performance 
evaluation moderated by position, education and experience have no effect on the 
salary. Significantly, the extra amount has been positively influenced by position, 
gender, and performance evaluation moderated by position and gender and 
negatively by experience and performance evaluation moderated by experience. 
Other variables have insignificant effect on the extra. 

Implication: The study’s results are beneficial indicator in improving the performance 
of employees based on their salaries and designing a guide on how to evaluate this 
performance related to position, gender, education and experience. 

.  

 
Keywords :  
Employee’s Salary, Extra 
Amount, Performance 
Evaluation, The Sultanate of 
Oman.  

 

  

   

 
 
 
 
 
 

 
 Address Correspondence:   

E-mail : dhiaa.shamki@komar.edu.iq1, 
              rafef.alro7@gmail.com2 
 

 

  

mailto:dhiaa.shamki@komar.edu.iq1


Dhiaa and Aisha / Finance, Accounting and Business Analisys 

23 

 

1. Introduction  

Previous studies examined the relationship between employees’ salary and their performance and 

demonstrated that it is influenced by many factors. These factors include position and gender (Ohlott et al., 

1994; Bateman and Snell, 2004; Shrum, 2007; Nazrul, 2009; Mphil et al., 2014; Ufuophu-Biri and Iwu, 

2014) and education (Caruth and John, 2008; Surina et al, 2015). There is a limited research on the 

relationship between the employee’s salary and performance evaluation and to what extent that the salary 

and rewards will be influenced by the performance evaluation in presence of different factors such as 

position, gender, education and experience.   

The current study examines the influence of performance evaluation alone and linked collectively 

and simultaneously with position, gender, education and experience on salaries and extra amounts received 

by employees in Ministry of Social Developments. The study attempts to answer questions of; does 

employees’ performance evaluation influence their salaries and the extra amount? Could this evaluation 

regarding employees’ position, gender, education and experience influence their salaries and the extra 

amount? The objectives of the study are to indicate whether the employees’ salaries and the extra amount in 

public sector are influenced by their performance evaluation linked collectively and simultaneously with 

position, gender, education and experience. 

The study’s results will be useful in examining the influence of performance evaluation on their 

salaries that is not well examined before. This will assist to improve the performance of employees based on 

their salaries. Also, this study provides an empirical evidence on how to increase employees’ salaries in the 

public sector based on their performance evaluation. Consequently, this might be assistant in presenting a 

guide to strengthen the performance evaluation form and its contents to be different according to the position 

and experience of the employee in public sector. 

In addition to this introduction, Prior research reviewing the relationships among study variables 

will be in the second section. The third section presents the hypotheses and methods employed in the study 

while the fourth section reveals the finding. Finally, discussion, contributions and calling for future research 

are stated in the last section.       

 

2. Literature Review  

2.1. Salary and Performance evaluation 

Performance is the implementation of the work in a manner and at a certain level of quality to 

achieve the desired goals. Changes in the public sector require attention to job performance and how 

employees perform the required work. The employee performance is a process of understanding the 

workforce indicating what needs to fulfill the organizational objectives based on measures of employees’ 

skills, competency requests, employees’ enhancement steps and delivering the best outcomes. Therefore, a 

job evaluation process has been developed to improve the performance of employees in the public sector 

(Dart, 2004; Igbojekwe and Ugo-Okoro, 2015; Mollel et al. 2017).  

The most efficient employees are like to be motivated to perform their duties since they will receive 

the rewards and bonus (Mphil et al., 2014). The highly motivated employees obtain advantages for achieving 

their organizations objectives (Rizwan and Ali, 2010). According to Mphil et al., (2014), the job satisfaction 

influences the employee performance level. One of main issues that drives the job satisfaction is the suitable 

and sufficient compensations and incentives of employees which supports the organization objective.  

Since salaries for their expected efforts are allocated to fixed rate, employees’ performance related 

to bounces is to improve the productivity. Many organizations use bounces pay as monetary reward giving 

to employees in addition to their fix compensation as the extra amount (Heneman and warner, 2005). 

Commonly, this pay plan is frequently employed in evaluating employee performance (Mphil et al., 2014). 

The relationship of pay and performance is directly associated since employees receive a constant salary in 

a time period and in addition to bonus as reward for the ideal performance or additional efforts (Bandiera et 

al., 2007). When the employees receive unsuitable salaries, their dissatisfaction will be occurred and 

achieving goals will be minimized and deteriorated (Mphil et al. 2014). 

It is hard to decide that the approach of pay-related-performance is completely assisting the 

enhancement of employees’ performance and their stimulation in the public sector (Cardona, 2006). 

Performance in prior research has been contradictorily affected by paying salary and extra amount for 

performance. They have a positive influence on the performance in study of Lazear (2000), while a negative 

one is found by Frey and Jegen (2001). The marks of the annual reports for performance evaluation will be 

used as proxy for that evaluation in this study. Consistent with previous studies (Rizwan and Ali, 2010; 

Mphil et al., 2014), it is expected for this study that performance evaluation has a positive influence on the 

salary.  

 

 

 



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2.2   Salary, Performance evaluation, Position and Gender 

The employee’s position is the key motivational rewards to influence performance (Mphil et al., 

2014). It is familiar for employees to take higher positions with same organization or with different ones for 

many reasons especially if this position leads to maximized the salaries and benefits (Bateman and Snell, 

2004).  It is found that women are fewer than men in developing job opportunities during their profession. 

This issue is examined by Ohlott et al. (1994) who found that men experience is greater task-related 

developmental challenges than women who have experience greater developmental challenges that stem 

from hurdles appearing in their jobs. This is the cause that indicating why senior management positions are 

promoted for few women. Consistent with previous studies (Bateman and Snell, 2004; Mphil et al., 2014), 

it is expected for this study that employees’ performance evaluation moderated by their position (hereafter 

PERF-POST) influence the salary positively. 

Some jobs look to be more suitable for females, while others for male (Ufuophu-Biri and Iwu, 2014). 

It means that the gender has an important role in employees’ performance and their motivation. Positions 

associated with the gender factor may lead the organization’s outcomes at its different levels. (Ufuophu-Biri 

and Iwu, 2014). In this study, managers forms 38.1 percent of the sample. Managers for department and 

above level will be measured as a position for the purpose of the study.  

Indicating whether that employee’s gender associated to his/her performance in the public sector 

could enhance employees’ performance and productivity that will help organization’s staff to attain 

satisfaction in the workplace (Ufuophu-Biri and Iwu, 2014). It is found in previous research that that 

employee’s gender has a significant influence on employees’ performance in some professions (Shrum, 2007; 

Nazrul, 2009). Burleson and Samter (1992) found that this factor is a significant determinant for employee’s 

performance in their organization. They concluded that a specific gender could be the best for a performance 

in particular professions than the other gender. Aremu and Adeyoju (2003) found that gender has a 

significant effect on employee’s performance in Nigeria, while it is found that there is insignificant 

relationship between employees’ performance and their gender in that country (Ufuophu-Biri and Iwu, 

2014). 

Determining whether that employee’s performance evaluation moderated by gender (hereafter 

PERF-GNDR) influences their salaries and extra in the public sector in Oman will be examined in this 

study. The women in this study form 29.3 percent of the sample, while the rest percentage is for men. This 

study examines the employee’s gender as the state of being male or female. Consistent with previous studies 

(Burleson and Samter, 1992; Aremu and Adeyoju, 2003; Shrum, 2007; Nazrul, 2009), it is expected that the 

employee’s gender linked with performance evaluation has a positive significant influence on the employees’ 

salary and the extra amounts. 

 

2.2. Salary, Performance evaluation and education. 

There is a certain need to improve evaluation process of employee performance based on their 

education levels in an organization. Performance evaluation has influence on the job satisfaction and the 

trend of employees’ performance based on education level (Caruth, and John, 2008). Different benefits and 

compensation packages are designed to attract employees with higher education as possible. It is right that 

most employees with higher education believe that when they perform best abilities, their salaries can be 

maximized (Surina et al, 2015).  

Examining the education level in this study is determined based on the education degree of an employee. 

The study sample is divided into different education levels. Those levels are middle school, high school, 

general education diploma, bachelor, higher diploma, master’s and doctorate certificate forming 2.6%, 

69.9%, 2.9%, 12.9%, 0.5%, 9.1%, and 2.2% of the study sample respectively. Consistent with previous 

studies (Caruth, and John, 2008; Surina et al, 2015), the study expects that the performance evaluation 

moderated by education (hereafter PERF-EDCT) has a positive significant influence on the salary and extra 

amounts. 

 

2.3. Salary, Performance and Experience 

Changes in the abilities of employees are possible with continued work within similar conditions 

and lead to use different criteria to determine their salaries (Schuldes, 2006). Indeed, in the public sector, 

experiences and salary as pay-related-performance schemes are differently researched. Certainly, results of 

examining the relationship between experiences and salary are not proved. This pay approach can effectively 

assisted in improving motivation and performance evaluation based on experience in the public sector 

(Cardona, 2006).  

Paying for performance could significantly support employee’s works and tasks that request minimal 

investments for experts (Milkovich and Wigdor, 1991). In public sector, employees with low experience 



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have greater opportunities in getting job less interesting than managers and consequently might be good 

candidates for pay-related-performance. The cause for this situation is that those tasks are not well rewarded 

(Buelens and Van den Broeck (2007). The results of these tasks are not difficult to be gauged than composite 

tasks that have less important role (Weibel et al., 2009).  

In accordance with Wright, 1990), the employee’s experience will be measured for this study as 

employment length (in years). The study sample is divided into different ranges for employees’ experience 

in years. The experience ranges in years are 1 – 5, 6 – 10, 11 – 15, 16 – 20, 21 – 25 and 26 years and above 

forming 25.1%, 6.7%, 14.1%, 20.1%, 13.2 and 20.89% of the study sample respectively. Although pay for 

performance is the key determination, experience rewards still are more complex and difficult to be 

measured (Mphil et al., 2014). Therefore, the study has no expectation for the influence of employee’s 

performance evaluation moderated by experience (hereafter PERF-EXPR) on the salary and the extra 

amounts.  

 

2.5. Theoretical framework 

Stewardship theory is developed in line with agency theory. It presents a different view that the 

managers are motivated rather than employees since managers interests are with the owners of organization 

(Davis et al., 1997). Ouchi (1980) proposes that organization can proactively manage their selection and 

socialization practices so that employee interests are aligned with the firms not been based on the assumption 

that the goals of employer and employee diverge as in agency theory.  

Taylor’s theory has supported transform hourly jobs into positions where employees are received the suitable 

compensations for their skill or their performance (Schuldes, 2006). In opposite of pay for performance 

scheme, its opponents proved that agency and stewardship theories as self-interest approaches have no 

sufficient explanation for the employees motivation especially for who work in the public sector (Moynihan 

and Pandey, 2007).  

Whether pay-for-performance theory is built on controlling employees’ behavior related to their 

outputs, the purpose of this approach is to motivate those employees to maximize their individual 

performance (Deckop et al., 1999). Referring to Perry et al. (2006) who identify type of task as a moderator 

of the pay and performance link, this study associates the salary and the extra amount with their performance 

evaluation linked with position, gender, education and experience in the public sector. As theoretical 

framework, the links among employee’s salary, extra as depending variables (hereafter DVs), performance 

evaluation, position, gender, education and experience as independent variables (hereafter IVs) and 

performance evaluation linked with position, gender, education and experience as moderator variables 

(hereafter MVs) are illustrated in Figure 1. 

 

3. Hypotheses development and research methods 

According to the mentioned theoretical and conceptual framework and based on the study’s 

problem, questions and objectives, our hypotheses are placed as follows: 

Hypotheses (1): The influence of employees’ performance evaluation on salaries is moderated by employees’ 

position, gender, education and experience such that the increase in salaries is greater for; 

performance evaluation with administrative position more than this without one; male more 

than this for female; high education more than this with low ones; and long experience 

period more than this with short ones. 

 

Hypotheses (2): The influence of employees’ performance evaluation on extra amounts is moderated by 

employees’ position, gender, education and experience such that this extra is greater for; 

performance evaluation with administrative position more than this without one; male more 

than this for female; high education more than this with low ones; and long experience 

period more than this with short ones. 

 
  
 
 
 
 
 
 
 
 
 
 
 



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Independent Variables                                   Moderator Variables                             Dependent Variables 

 

Figure 1.  

Conceptual framework  

Note:  
Extra is the additional amount received by the employees for ideal performance and distinguished efforts.  

PERF-POST, PERF-GNDR, PERF-EDCT and PERF-EXPR are MVs reflecting the correlated performance evaluation with position, gender, 

education and experience respectively. 

 

 

The study examines the influence of performance evaluation, position, gender, education and 

experience as IVs, performance evaluation linked collectively and simultaneously with position, gender, 

education and experience as MV on the employee’s salary and the extra amounts as DV. The strategy of the 

study is collecting archival data for period 2011-2016 from the systems and records of the Ministry of Social 

Developments (MOSD) in the Sultanate of Oman.  

To conduct the results, this study employed observations about 417 persons (managers and 

employees), 11 variables for each person (2 DVs, 5 IVs, and 4 MVs). The number of observations for a year 

is 4,587 and 27,522 observations for the period 2011 – 2016 as illustrated in Table (1). 

 

Table 1 

Size for study’s sample, variables and Observations within 2011-2016 

# Term No. 

1 Sample size  417 persons 

2 DVs per person 2 Variables 

3 IVs per person  5 variables 

4 MVs per person  4 variables 

5 Total variables (2 + 3 + 4) 11 variables 

6 Observations per year (1* 5) 4,587 observations 

7 Observations within research’s period (6* 6 years)  27,522 observations 

8 Pooled observations 27,522 observations 

 

Via SPSS outputs, ANOVA presents values for sum of squares, F, and significance. The significance 

with F indicate the significant values of study’s model (Pallant, 2010). From the regression analysis of the 

study, the betas values show the power of each IVs (and MVs) to explain the DV variance. The t-test and p-

values indicate whether a resulted coefficient is significantly different from zero. They will be used to accept 

or reject our hypotheses.  

 

  



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4. Findings 

The examining for the assumptions of regression analysis is required to indicate the suitability of 

this analysis. These assumptions are correlation, linearity, multicollinearity, and homoscedasticity (Pallant, 

2010). It is found that salary, extra and performance evaluation have non-normal distribution. Therefore, 

they are transformed to new variables by adopting Square root, inverse and logarithm processes respectively.   

4.1 Descriptive statistics 

As appeared in Table (2) and after transformation process, salary is the highest value (150) and 

performance evaluation is the lowest one (0) among salary, extra and performance evaluation. The means 

of position, gender, education and experience are 38%, 71%, 24% and 54% indicate that 38% of study’s 

sample is managers, 71% male, 24% graduates and 54% experience with more than 16 years. 

 

Table 2 

Descriptive statistics 

 N Minimum Maximum Mean Std. Deviation Skewness Kurtosis 

Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error 

Salary 2502 59 150 104.06 18.976 .197 .049 -.660 .098 
Extra 1041 1 3 2.07 .386 -.065 .076 -.473 .151 
Performance 
evaluation 

2502 0 2 .97 .240 -.079 .049 .418 .098 

Position 2502 0 1 .38 .486 -.489 .049 -1.762 .098 
Gender 2502 0 1 .71 .455 .912 .049 -1.168 .098 
Education 2501 0 1 .24 .430 -1.188 .049 -.588 .098 
Experience 2502 0 1 .54 .489 .427 .049 -1.819 .098 
Valid N (listwise) 1041         

 

In descriptive statistics, standard deviation is used to measure the deviation of a data values from its mean. Its 

values have to be not more than 3 to guarantee that the data has no outliers which could significantly 

influence the regression analysis and its results. As it shown in Table (2), standards deviation values are less 

than 3 except salary after transformation process. Skewness and kurtosis scores have to be between ±2. It 

means that it is acceptable for normal distribution of study’s data. Values above or below the majority of 

other observations are outliers and extremes. The skewness and kurtosis scores for our study data are 

between ±2, then they are acceptable since this data has the normal distribution and the regression analysis 

can be operated.  

4.2. Correlation analysis 

The correlation test after transformation process indicates that the type and sign of the relationships 

among the study variables. According to Table (3), there are significant positive and negative relationships 

at .01, .05 and .10 levels among the study’s variables except education with extra. 

 
Table 3 

Correlation analysis results 

Salary 
Pearson Correlation 1       
Sig. (2-tailed)        
N 2502       

Extra 

Pearson Correlation -.131** 1      

Sig. (2-tailed) .000       
N 1041 1041      

Performance 
evaluation 

Pearson Correlation -.142** -.067* 1     
Sig. (2-tailed) .000 .030      
N 2502 1041 2502     

Position 
Pearson Correlation -.475** .110** .229** 1    
Sig. (2-tailed) .000 .000 .000     
N 2502 1041 2502 2502    

Gender 
Pearson Correlation -.160** -.100** .074** .201** 1   
Sig. (2-tailed) .000 .001 .000 .000    
N 2502 1041 2502 2502 2502   

Education 
Pearson Correlation -.338** .018 .113** .254** .035 1  
Sig. (2-tailed) .000 .554 .000 .000 .084   
N 2501 1041 2501 2501 2501 2501  

Experience 
Pearson Correlation -.605** .115** .110** .430** .229** .042* 1 
Sig. (2-tailed) .000 .000 .000 .000 .000 .036  
N 2502 1041 2502 2502 2502 2501 2502 

 

 

 

 

 



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4.3. Empirical results 

Based on what our first hypothesis stated, Table (4) shows that salary, performance evaluation, 

position, PERF-POST, gender, PERF-GNDR, education, PERF-EDCT, experience and PERF-EXPR 

variables entered the regression analysis and no variable has been removed. The total variation in salary has 

been accounted via the model summary. The information from Table (4) is about the ability of regression 

line. The R2 value is 0.535 meaning that 53.5 percent of the total variance in the salary can been explained. 

The significant F statistic in ANOVA results indicate that the model is significant as a whole for our study.   

The relationship between salary, performance evaluation, position and PERF-POST can be noticed 

from Table (4). The coefficients on performance evaluation (β1 = -.114 and t-test = -4.193), gender (β4 = -.864 

and t-test = -4.550), PERF-GNDR (β5 = -.862 and t-test = -4.488) and education (β6 = -.505 and t-test = -2.437) 

are negative and significant at .05 level, while the coefficients on position, PERF-POST, PERF-EDCT, 

experience and PERF-EXPR are insignificant. The coefficients β1, β4, β5, and β6 demonstrate that performance 

evaluation, gender, PERF-GNDR and education could significantly and negatively influenced their salary. 

Other variables have insignificant effect on the salary. 

 

Table 4 

Regression analysis results for salary 

Model / variable Regression outputs Values 

Model R  .731 

R Square .535 
Adjusted R Square .532 
F  

Sig. 
219.857 

.000 

Variables Beta t-test Sig. 

(Constant)  11.946 .000 

Performance β1 = -.114 -4.193 .000 

Position β2 = .092 .379 .705 

PERF-POST β3 = .263 1.074 .283 

Gender β4 = -.864 -4.550 .000 

PERF-GNDR β5 = -.862 -4.488 .000 

Education β6 = -.505 -2.437 .015 

PERF-EDCT β7 = -.240 -1.156 .248 

Experience β10 = -.147 -.419 .675 

PERF-EXPR β11 = .147 .418 .676 
Note: DV: Salary 
IVs: Performance evaluation, position, PERF-POST, Gender, PERF-GNDR, Education, PERF-EDCT, Experience, PERF-EXPR. 
PERF-POST: The influence of employees’ performance evaluation moderated by position on salaries. 
PERF-GNDR: The influence of employees’ performance evaluation moderated by gender on salaries. 
PERF-EDCT: The influence of employees’ performance evaluation moderated by education on salaries.  

PERF-EXPR: The influence of employees’ performance evaluation moderated by experience on salaries.  

 

Based on what the second hypothesis stated, Table (5) shows that extra, performance evaluation, 

position, PERF-POST, gender, PERF-GNDR, education, PERF-EDCT, experience and PERF-EXPR 

variables entered the regression analysis and no variable has been removed. The total variation in extra has 

been accounted via the model summary. 

The information from Table (5) is about the ability of regression line. The R2 value is .090 indicating 

that 9.0 percent of the total variance in the extra can been explained. The significant F statistic in ANOVA 

results indicate that the model is significant as a whole for our study.  

 

  



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Table 5 

Regression analysis results for extra amount 
Model / variable Regression outputs Values 

Model R  .246 

R Square .090 

Adjusted R Square .049 

F  
Sig. 

5.079 
.000 

Variables Beta t-test Sig. 

(Constant)  1.297 .195 

Performance γ1 = .010 .168 .866 

Position γ2 = 1.460 2.227 .026 

PERF-POST γ3 = 1.382 2.085 .037 

Gender γ4 = .781 1.657 .098 

PERF-GNDR γ5 = .938 1.969 .049 

Education γ6 = -.711 -1.180 .238 

PERF-EDCT γ7 = -.725 -1.202 .230 

Experience γ8 = -2.186 -2.817 .005 

PERF-EXPR γ9 = -2.314 -2.964 .003 

Note: DV: Extra 
Other variables are defined before. 

 

The relationship between extra, performance evaluation, position, PERF-POST, gender, PERF-GNDR, 

education, PERF-EDCT, experience and PERF-EXPR can be noticed from Table (5). The coefficients on 

position (γ2 = 1.460 and t-test = 2.227), PERF-POST (γ3 = 1.382 and t-test = 2.058), gender (γ4 =.781 and t-

test =1,657), PERF-GNDR (γ5 = .938 and t-test = 1.969) are positive and significant at .05 level except on 

gender at .1 level, while the coefficients on experience (γ8 = -2.186 and t-test = -2.817) and PERF-EXPR (γ9 

= -2.314 and t-test = -2.964) are negative and significant at .05 level. The coefficients γ2, γ3, γ4 and γ5 demonstrate 

that position, PERF-POST, gender and PERF-GNDR could significantly and positively influenced their 

extra, while experience and PERF-EXPR could significantly and negatively influenced their extra. Other 

variables have insignificant effect on the extra.  

 

5.  Discussion and conclusions 

5.1. Salary and performance evaluation 

According to Hypothesis (1), the study result is consistent with the previous studies of (Frey and 

Jegen, 2001), while it is inconsistent with others that found positive relationship between performance 

evaluation and salary (Lazear, 2000). The result is not completely supported by Mphil et al. (2014) who 

concluded that pay plan is commonly employed to evaluate employee performance. The insignificant results 

of position and PERF-POST are inconsistent with previous studies (Bateman and Snell, 2004; Mphil et al., 

2014). This means that determining salary is not influenced by the position. Despite the gender and PERF-

GNDR have significant influence on the salary, the results are inconsistent with Burleson and Samter (1992), 

Shrum (2007) and Nazrul (2009) because of the negative sign and others who concluded that this influence 

is insignificant (Ufuophu-Biri and Iwu, 2014). Accordingly, the PERF-GNDR is not indicator for his/her 

salary. This might be explained by the small percentage of women in our sample.  

Despite that the influence of education and PERF-EDCT is significant results, it is inconsistent with 

previous studies (Caruth, and John, 2008; Surina et al, 2015) because of the negative sign. The insignificant 

results of those variables are not conformed by previous studies (Buelens and Van den Broeck, 2007). This 

might be explained by lacking of conclusive empirical evidence for effect of performance evaluation based 

on experience in the public sector (Cardona, 2006). Based on the study’s results, Hypotheses (1) has been 

rejected for all factor except the experience. 

 

5.2. Extra and performance evaluation 

From testing Hypothesis (2), the result of the study is conformed to Cardona (2006) who resulted 

that no conclusive empirical evidence that proved the influence of performance pay approach on the 

performance evaluation. This is occurred in line of lacking the employee dissatisfaction with the 

compensation leads to achieving lower objectives of the organization (Mphil et al. 2014). Since the position 



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and PERF-POST have positive influence on extra, they are consistent with previous studies (Bateman and 

Snell, 2004; Mphil et al., 2014). Also, the result of the study regarding the gender and PERF-GNDR are 

consistent with previous studies (Burleson and Samter, 1992; Shrum, 2007; Nazrul (2009), while it is 

inconsistent with Ufuophu-Biri and Iwu (2014). 

The insignificant results of education and PERF-GNDR are not conformed by previous studies 

(Caruth, and John, 2008; Surina et al, 2015). Despite the experience and PERF-EXPR have significant 

influence on the extra, the results is inconsistent with Buelens and Van den Broeck (2007) because of the 

negative sign. This might be explained by lacking of conclusive empirical evidence for effect of performance 

evaluation based on experience in the public sector (Cardona, 2006). Based on the study’s results, 

Hypotheses (2) has been accepted for the influence of position, gender, experience and performance 

evaluation moderated by those factors, while it is rejected for performance evaluation, education and PERF-

EDCT. 

 

 

6.  Contributions and future studies 

The contributions of the study can be noticed in different ways. Firstly, in indicating the influence 

of employees’ performance evaluation on their salaries that is not well researched before. Secondly, in 

improving the performance evaluation of employees by linking it with salaries. Thirdly, in providing new 

evidence on how to improve the employees’ performance by increasing salaries in the public sector. 

Fourthly, in presenting a guide for public sector on how to strengthen the evaluation form to be different 

according to the position and experience of the employee. Consistently with previous studies that examined 

data from other countries, our results will be strengthened and generalized. Accordingly, these results can 

be added to the materials of performance and performance evaluation courses theoretically and practically. 

We suggest that next studies may extend this study by employing different factors such as employee’s age 

and sectors in addition to our study’s factors. Future studies are called to use larger sample size or long 

periods to exam same variables or different ones. Future studies are encouraged to compare our findings 

with other for organizations in the sultanate of Oman, or those from Gulf Cooperation Council, Middle East 

or different regions.  

 

  



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