Appraisal System and Employee Performance. Case Study of the International Committee of the Red Cross in Yemen

TABLE OF CONTENTS

ACKNOWLEDGMENT

TABLE OF CONTENTS

LIST OF TABLES

LIST OF FIGURES

ABSTRACT

LIST OF ABBREVIATIONS & ACRONYMS

CHAPTR ONE INTRODUCTION
1.1 Background of the Study
1.2 Overview of ICRC Organization
1.3 Problem Statement
1.4 General Objective
1.5 Research Objectives
1.6 Research Questions
1.7 Significance of the Study
1.8 Scope of the Study

CHAPTER TWO LITERATURE REVIEW
2.1 Introduction
2.2 Theoretical Framework
2.2.1 Justice Theory
2.2.2 Equity Theory
2.2.3 Expectancy Theory
2.3 Empirical Review
2.3.1 Perceived Fairness and Employees’ Performance
2.3.2 Perceived Accuracy and Employee’ Performance
2.3.3 The Quality of Appraisal Feedback and Employees’ Performance
2.3.4 Motivation as Moderator Between Appraisal System and Employees’ Performance
2.4 Research Gap
2.5 Conceptual Framework
2.6 Research Hypotheses
2.7 Operationalization and Measurement of Variables

CHAPTER THREE RESEARCH METHODOLOGY
3.1 Introduction
3.2 Research Onion
3.3 Research Onion of the Current Study
3.3.1 Research Philosophy
3.3.2 Research Approach
3.3.3 Research Design
3.4 Data Collection Method
3.5 Population and Sample
3.5.1 Population
3.5.2 Sampling Technique
3.5.3 Sampling Size
3.6 Validity and Reliability
3.7 Resources Access for Primary and Secondary Data
3.7.1 Primary Data Collection
3.7.2 Secondary Data Collection
3.8 Statistical Techniques
3.8.1 Descriptive Statistics
3.8.2 Spearman’s Rho Correlation
3.8.3 Analyzing Regression Coefficients
3.8.4 Variance (ANOVA) and F-test
3.8.5 Assumptions of Linear Regression Tests
3.8.5.1 Multi-collinearity Test:
3.8.5.2 Test for Normality:
3.8.5.3 Test for Autocorrelation
3.8.6 Moderated Regression Analysis (MRA)
3.9 Ethical Consideration
3.10 Chapter Summary

CHPTER FOUR DATA ANALYSIS AND PRESENTATION
4.1 Introduction
4.2 Response Rate
4.3 Descriptive Statistics of Demographic Profile
4.4 Descriptive Statistics of the Performance Appraisal System
4.4.1 Perceived Fairness of the Performance Appraisal System
4.4.2 Perceived Accuracy of the Appraisal System
4.4.3 Quality of Performance Appraisal Feedback
4.4.4 Motivation as a Moderator Between the PAS and Employees' Performance
4.4.5 Employees’ Performance
4.4.6 Summary of the Descriptive Statistics of the Above Findings
4.5 Spearman’s Rho Correlation Analysis
4.5.1 The Impact of Performance Appraisal System on Employees’ Performance
4.6 Regression Coefficient Analysis
4.6.1 The Impact of Perceived Appraisal Fairness on Employees’ Performance
4.6.2 The Impact of Perceived Accuracy on Employees’ Performance
4.6.3 The Impact of Feedback Quality on Employees’ Performance
4.6.4 The Combined Impact of Performance Appraisal System Variables on Employees’ Performance
4.7 Assumptions of Linear Regression Tests
4.7.1 Test for Autocorrelation
4.7.2 Test for Normality
4.7.3 Multi-collinearity Test
4.8 Moderation Analysis of Motivation as a Moderating Variable
4.8.1 Moderated Regression Analysis
4.8.2 Assumptions of Linear Regression Tests
4.8.2.1 Test for Autocorrelation
4.8.2.2 Multi-collinearity Test
4.8.2.3 Test for Normality
4.9 Output of Hypotheses Testing
4.10 Chapter Summary

CHAPTER FIVE DISCUSSION OF THE FINDINGS
5.1 Introduction
5.2 The Impact of Perceived Fairness of the Performance Appraisal System on Employees’ Performance
5.3 The Impact of Perceived Accuracy of the Performance Appraisal System on Employees’ Performance
5.4 The Impact of Quality on the Performance Appraisal Feedback on Employees’ Performance
5.5 The Overall Impact of Performance Appraisal System Variables on Employees’ Performance
5.6 The Impact of Motivation as a Moderator Between the Performance Appraisal System and Employee’s Performance

CHAPTER SIX CONCLUSION AND RECOMMENDATIONS
6.1 Introduction
6.2 Conclusion
6.3 Recommendations
6.4 Limitations of the Study
6.5 Suggestions for Further Research

REFERENCES

APPENDICES
APPENDIX A: LETTER OF INTRODUCTION
APPENDIX B: QUESTIONNAIRES OF THE STUDY

ACKNOWLEDGMENT

Words are inadequate to convey the best of my gratitude for the numerous ways in which so many people have helped me in this degree journey. Above all, I praise Allah for granting me the strength, courage, and direction to complete this thesis work. I must willingly express my gratitude to my beloved wife, Ibtesam, who took on several domestic and family duties so that I could devote the necessary time to finishing my Master's degree. My love, I am eternally grateful for all your sacrifices you made for me and for our sons, Sabry and Abdullah. I also want to express my great gratitude to my family, who encouraged and supported me with their love and constant prayers.

To my research supervisor, Mr. Prashant Priyadarish, I thank you for your patience and guidance in preparing and completing this dissertation project. I would also like to express my gratitude to Mr. Shiju Philipose, for his help from the beginning of my master's journey. Likewise, I want to extend my love and respect to the exceptional colleagues who inspired and supported me along this journey. My special thanks and appreciation go to all ICRC staff members who took the time to complete my questionnaires. I would also like to express my big thanks to Elissar Aboud, the ICRC HR Manager in Yemen, and the LND (Learning and Development) team, who supported me in conducting this study at the ICRC organization in Yemen.

LIST OF TABLES

Table 2.1: Operationalization and Measurement of Variables

Table 3.1: Cronbach’s Alpha Test

Table 4.1: The Results of the Demographic Characteristics of Respondents

Table 4.2: Mean Scores for Perceived Fairness of the Performance Appraisal System

Table 4.3: Mean Scores for Perceived Accuracy of the Performance Appraisal System

Table 4.4: Mean Scores for Quality of Performance Appraisal Feedback

Table 4.5: Mean Scores for Motivation as a Moderator Between PAS and EP

Table 4.6: Mean Scores for Employees’ Performance

Table 4.7: Summary of Overall Mean Scores of Variables

Table 4.8: Spearman’s Rho Correlation Analysis Results

Table 4.9: Regression Analysis for Perceived Fairness and Employees’ Performance

Table 4.10: Regression Analysis for Perceived Accuracy and Employees’ Performance

Table 4.11: Regression Analysis for Feedback Quality and Employees’ Performance

Table 4.12: Regression Analysis for the Combined Impact of PAS on EP

Table 4.13: Multicollinearity Statistics

Table 4.14: Regression Analysis for Motivation as a Moderator Variable

Table 4.15: Multicollinearity Statistics

Table 4.16: Output of Hypotheses Testing

LIST OF FIGURES

Figure 2.1: Common Errors of Raters

Figure 2.2: Conceptional Framework

Figure 3.1: The Research Onion Model

Figure 3.2: The Research Onion Model of the Current Study

Figure 3.3: Moderation Framework

Figure 3.4: A Statistical Model for Moderating Analysis

Figure 3.5: Demographic Characteristics Dashboard

Figure 4.1: Histogram of Regression Standardized Residuals

Figure 4.2: Regression Standardized Residuals with a Q-Q Plot

Figure 4.3: Histogram of Regression Standardized Residuals

Figure 4.4: Regression Standardized Residuals with a Q-Q Plot

ABSTRACT

International organizations permanently put forth a concerted effort to encourage and motivate employees to provide a high level of performance by using effective performance appraisal systems for competitive advantage and higher productivity. Therefore, performance appraisal is a critical source and the key driver of continuous improvement for both the organization’s and employees’ performance. However, the PAS of HRM in many organizations still encounters challenges in enhancing employees' performance and achieving desired outcomes. In this respect, the first objective of the study was to investigate the impact of the performance appraisal system on employee performance at the ICRC in Yemen. The study depended on three constructs of the performance appraisal system—perceived fairness, perceived accuracy, and quality of appraisal feedback—for examining their impacts on employees’ performance. The second objective of the study was to examine whether motivation moderates the relationship between the performance appraisal system and employees’ performance. This study adopted a descriptive quantitative method for collecting primary data through the questionnaires distributed to 217 employees at the ICRC in Yemen. Correlation analysis and simple and multiple regression were applied to examine the impacts of the independent variables on the dependent variable and to check the relationship between the variables. By analyzing variables individually, the study found a positive influence and a significant relationship between the perceived fairness of performance appraisal and employees’ performance, between the perceived accuracy of performance appraisal and employees' performance, and between the quality of appraisal feedback and employees’ performance. Through the combined measurements of the variables using multiple regression analysis, the results revealed that perceived accuracy has a stronger effect and a positive relationship with employees’ performance than other variables. Though, it showed that perceived fairness and feedback quality don’t have a significant impact on employees’ performance. In addition, the study revealed that motivation plays a positive role as a moderator between the performance appraisal system and employees’ performance. Besides, it found that motivation significantly influences the relationship between them. The study was also limited to three constructs of the performance appraisal system, along with motivation as a moderator variable and employees’ performance in terms of individual objectives and organizational objectives.

Keywords: Performance Appraisal System, Employees’ Performance, ICRC, Yemen

LIST OF ABBREVIATIONS & ACRONYMS

DF - Degrees of Freedom

DW - Durbin-Watson Test

EP - Employees’ Performance

FQ - Feedback Quality

HRM - Human Resources Management

ICRC - International Committee of the Red Cross

M - Motivation

Ӎ - Moderator Variable

MRA - Moderated Regression Analysis

PA - Perceived Accuracy

PAS - Performance Appraisal System

PF - Perceived Fairness

SDs - Standard Deviations

Sig - Significant

SPSS - Statistical Package for Social Sciences

VIF - Variance Inflation Factor

X - Independent Variable

Y - Dépendent Variable

Z - Interaction Variable

CHAPTR ONE INTRODUCTION

1.1 Background of the Study

Any international company in this universe relies on its human resources to accomplish its objectives effectively and compete efficiently among other competitors. Today, organizations work to motivate and boost their employees' productivity through effective and accurate performance appraisal systems. A performance appraisal system (PAS) is the most important tool that plays a central role in human resource management for managing individuals successfully and effectively. The PAS refers to the methods and procedures applied to evaluate the level, quantity, and quality of the employees’ performance by providing ongoing feedback to improve their performance (Dijk, 1915). Based on the Rahahleh et al. (2019) study, the performance appraisal system is considered a tool to manage and measure workers' performance to enhance performance and motivation. While employees’ performance (EP) refers to a set of tasks, the employee should understand and achieve according to the updated job description to meet the organizational expectations (Rotundo & Sackett, 2002). As per Peters and Waterson (2004), "employee performance" means any activity required to be accomplished by the employees to accomplish both job-related goals and organizational goals.

According to Abdulkadir and Isiaka (2012), the PAS helps organizations achieve their strategies and increase effective work performance by focusing on employees’ weaknesses, improvable points of their performance and providing ongoing improvement. The effective performance appraisal system can help organizations motivate their employees. In addition, the PAS helps employees improve their performance by giving feedback about the need for improvement and helping them achieve better performance by receiving positive reinforcement that can motivate them constantly (Tiwari, 2020).

Moreover, the PAS helps the supervisors figure out their workers' strengths and weaknesses, deliver the required training, and give ongoing feedback to achieve the best performance. Therefore, the practical review system has to be fair, accurate, and structured to provide constant feedback to enhance the employees’ performances effectively and efficiently. Accordingly, many multinational organizations, such as the ICRC, made considerable efforts to improve the effectiveness of the performance appraisal system by using effective appraisal methods and adopting electronic performance review systems instead of traditional systems to improve accuracy and fairness (Ugoani, 2020).

However, the human resource management of these organizations still encounters challenges in achieving better employee performance because of the shortcomings of the appraisal system process. Quite a lot of employees claim the issues with the appraisal system are not due to the system but rather the deficiencies of supervisors, even if this is true, the supervisors are still considered a part of the system. Hence, the evaluation system is not a mechanism but a series of processes that engage the people who should implement them accurately and fairly (Levinson, 1976). Therefore, the outcomes of the performance appraisal have not only a positive but also a negative impact on employees, influencing their motivation and, consequently, their performance quality. In this respect, the most significant point of this topic is to define the factors related to performance appraisal that would lead to positive employee reactions to performance appraisal, which, in turn, can motivate employees to improve performance (Selvarajan & Cloninger, 2012). According to many studies, many workers still perceive the appraisal system as inaccurate, unfair, and no more than an annual ritual, as it does not reflect the reality of their level of performance (Sanyal et al., 2017).

Likewise, other studies showed that many employees are dissatisfied with the performance appraisal system because it has failed to meet their expectations (Mercer, 2002; Morgan, 2006). According to Smither & London (2009), about 80–90% of managers revealed that the PAS is ineffective in enhancing employee performance and organizational performance. For example, there are many organizational cases where the appraisal system provokes conflicts between the line managers and workers as they consider the evaluation system biased, inaccurate, and unfair (Al-Habsi & Madbouly, 2021). In such cases, the effectiveness of the employees' performance has decreased because they are concerned about the evaluation issues rather than concentrating on their work commitments (Underwood et al., 2016). Thus, line managers are considered to be most centrally responsible for the success of the performance appraisal —or the opposite (Stone et al., 2008).

Consequently, to examine the impact of PAS on employees’ performance, it needs to study the factors that affect the outcomes of the performance appraisal system. Many past studies have indicated the presence of enduring discontentment among both employers and employees because of the outputs of performance appraisal systems in the matter of accuracy, unfairness, and feedback outcomes factors that make PAS ineffective (Abbas, 2014). Based on Selvarajan & Cloninger's (2009) study, effective PAS outcomes help to improve the employees' performance and motivate them effectively. As stated by Lawler (1967), the essential factors that play a central role in the success of a performance appraisal system are the employees' perceptions of fairness and accuracy as they influence their workplace behaviours and attitudes. Employee reactions to appraisals that relate to perceived fairness, perceived accuracy, and employee satisfaction, as well as how they would motivate employees to improve their performance, are the main components of appraisal effectiveness (Roberson & Stewart, 2006; Selvarajan & Cloninger, 2012).

Accordingly, the purpose of this study is to examine and investigate how employees perceive the performance appraisal system and how that affects their level of performance by evaluating the effective indicators that may affect the outcomes of performance appraisal effectiveness that involve perceived fairness, perceived accuracy, and richness of feedback. The current study also aims to investigate whether motivation as a moderator variable can influence the relationship between the performance appraisal system and employees’ performance significantly.

1.2 Overview of ICRC Organization

The case study of this research is the International Committee of the Red Cross (ICRC) organization in Yemen. It is an international humanitarian organization that was established in 1863 in Geneva, Switzerland, by Henry Dunant. The ICRC's root foundation relates to the Geneva Conventions, the Red Crescent Movement, and the International Red Cross. It works in more than 100 countries with 20,000 employees. The goal of the ICRC's founding is to provide aid to the people who are affected by armed violence and conflict in any place in the world by delivering the needed help. In addition to endeavouring to prevent the suffering of people through the promotion of humanitarian laws to protect them from war and other situations of violence. The ICRC got its formal mandate from the Geneva Conventions of 1949. The humanitarian mission of the ICRC organization is to provide a humanitarian response to the needs of the affected people through the humanitarian principles of independence, neutrality, and impartiality, which are related to international humanitarian law (IHL) (ICRC, 2022).

The ICRC is the oldest international humanitarian organization to have entered Yemen. The ICRC organization has been working since 1962, at the time of the civil war between Royalists and Republicans, in response to the humanitarian consequences of that conflict and violent situation. Despite facing many challenges due to the political instability, events, and changed circumstances in Yemen, it tried to remain committed to doing its humanitarian mission for the people's needs (ICRC, 2011). It expanded its activities in the country starting from its delegation in Sana'a in 1990 and then gradually opened eight sub-delegations in big governorates because of the continued armed conflict for more than seven years (ICRC, 2020). Tens of thousands of civilians have died in this conflict, and more than four million people have been displaced (OCHA, 2022).

In these last years, the ICRC has employed more employees to achieve its humanitarian objectives with a large team that has grown to about 500 line managers and subordinates. In this aspect, there is a need for well-managed human resources management to enhance their performance through an effective appraisal system to manage their performance successfully, influence their motivation positively, and create innovation.

1.3 Problem Statement

Performance reviews play a crucial role in HRM because it is widely believed that they increase work efficiency and productivity. However, both managers and employees have negative opinions about the evaluation processes and the fairness they offer, such as the situation of the ICRC in Yemen (Kim & Holzer, 2014). Hence, the performance appraisal system can have a positive and negative impact on the level of employees’ performance. For this respect, the ICRC worked to improve the performance appraisal system by adopting an electronic appraisal system and an effective methodology to communicate feedback to employees to manage and enhance their performance by improving their skills and competencies and providing and funding the needed training (SAP, 2019).

Nevertheless, from my observations in the last few years as one of the employees of this organization, a significant number of employees complained about the outcomes of the performance appraisal system at ICRC. Some employees claimed that the performance appraisal process doesn't serve the purpose for which it was designed. They felt that the results of the performance appraisal didn't reflect the actual level and accuracy of the performance achieved. They are dissatisfied with the outcomes of their appraisal, as it did not match their perception of their work performance. According to Horsoo's (2009) study, although performance appraisal was designed to be a tool for performance improvement, it had been transformed into a discriminatory, punitive, and judgmental process.

Thus, employees' perceptions of PAS can affect the level of performance of both the employees and the organization. In this regard, there has been no previous study on this topic at the ICRC in the context of Yemen until now. Therefore, the current study's goal is to find out how ICRC employees view their performance evaluation system. The study focuses on determining and examining the factors that impact the effectiveness of the performance appraisal system at the ICRC in Yemen and providing recommendations to improve it according to the overall results. Thus, in order to understand how they feel about the current PAS and how it affects performance, a questionnaire survey of ICRC staff members in Yemen has been conducted.

1.4 General Objective

This research aims to analyze the impact of the performance appraisal system on employees' performance at the ICRC organization in Yemen.

1.5 Research Objectives

1. To examine the impact of the existing performance appraisal system on employees’ performance in terms of fairness, accuracy, and feedback at the ICRC in Yemen.
2. To investigate if motivation as a moderator impacts the relationship between the performance appraisal system and employees’ performance at the ICRC in Yemen.

1.6 Research Questions

1) What is the impact of the perceived fairness of the performance appraisal system on the employees’ performance at the ICRC in Yemen?
2) What is the impact of the perceived accuracy of the performance appraisal system on the employees’ performance at the ICRC in Yemen?
3) What is the impact of the quality of performance appraisal feedback on the employees’ performance at the ICRC in Yemen?
4) What are the combined impacts of the perceived fairness, perceived accuracy, and feedback quality of the performance appraisal system on the employees’ performance at the ICRC in Yemen?
5) Does motivation moderate the relationship between the performance appraisal system and employees’ performance at the ICRC in Yemen?

1.7 Significance of the Study

This study is important for the Human Resources department and ICRC Yemen Mission HR Professionals and other humanitarian organizations, as it provided insights into the influence of PAS on their employees' performances along with how they can be supported to enhance their productivity and efficiency. Moreover, this study can figure out how the employees see the performance appraisal system and how that impacts their level of performance by evaluating the effective indicators that may affect the outcomes of performance appraisal effectiveness, including perceived fairness, perceived accuracy, and feedback quality, along with examining the employees’ motivation as a moderator variable between PAS and EP.

Furthermore, this study could show the effectiveness of the performance appraisal system and how to enhance the employees’ performance and lower the negative impacts on the employees’ motivation for better performance and an enjoyable working environment for all the staff. Researchers and intellectuals can also benefit from the findings of this study to explain the performance appraisal systems and employee performance of international humanitarian organizations in Yemen. Further, they can conduct the same study in a different context and compare the results with those of this research.

1.8 Scope of the Study

The study was conducted at the ICRC organization in Yemen. The purpose of this study was to examine the relationship between the performance appraisal system and the employee’s performance. The further aim of this study was to show the influence of the performance appraisal system on employees’ performance through its relation to employees’ motivation as a moderating factor. The study focused on three constructs of the performance appraisal system: perceived fairness, perceived accuracy, and feedback quality as independent variables with one dependent variable, employees’ performance. The study also emphasized the role of motivation as a moderator variable between the performance appraisal system and employees' performance. The study was adopted as there were no prior studies that evaluated the impact of the appraisal system on employees’ performance at the ICRC in the context of Yemen. The research was limited to the organization's employees in order to collect data for this study via questionnaires. The targeted population of the study was 217 employees at the ICRC in Yemen.

CHAPTER TWO LITERATURE REVIEW

2.1 Introduction

This chapter discusses and analyzes the impact of the performance appraisal system on employees’ performance in past studies by various researchers and scholars. It figures out the theories of the performance appraisal system and the empirical review addressed by the study objectives and questions. Furthermore, it presents previous literature as well as numerous academic and journal articles relevant to the chosen topic and study issues. Additionally, a conceptual framework has been designed to demonstrate how the variables in the performance appraisal system affect employees’ performance. A research gap has also been identified.

2.2 Theoretical Framework

The study used the main related theories to investigate the relationship between the performance appraisal system and employees’ performance and their relationship to motivation as a moderator variable. Three common theories from the literature reviews on performance evaluation have thus been adopted into the theoretical framework. These theories, which are crucial for critically examining the study's issues, include the theories of justice, equity, and expectancy.

2.2.1 Justice Theory

According to previous literature from the last three decades, the fairness of the performance appraisal is an important component of the appraisal system's effectiveness. Many types of literature have emphasized the relationship between performance appraisal fairness and organizational justice theory. Based on the organizational justice theory, appraisal fairness was classified into three types: interactional fairness, procedural fairness, and distributive fairness (Greenberg, 1986). Interactional fairness was defined by Bies and Moag (1986) as the extent to which employees receive treatment during the execution of appraisal processes and procedures. This type is concerned with the criteria of fairness in interpersonal communication, which include respect, truthfulness, and justification. Procedural fairness, on the other hand, is concerned with a fair process of evaluating procedures set up by the organization for justice appraisal outcomes (Colquitt et al., 2001). Thus, as argued by Masterson et al. (2000), interactional justice refers to the fairness of the supervisors, whereas procedural justice refers to the fairness of the appraisal system of any organization.

As stated in Erdogan's (2002) study, the criteria of the performance appraisal system can be fair, but if the line manager does not apply these criteria well, the procedures would be invalid and unfair. Therefore, there would be no procedural justice without fair supervisory behavior and appraisal procedures. Accordingly, to cover this gap, it should divide procedural justice into rater procedural justice and system procedural justice, which are related as one construct. In this respect, interactional justice is related to the fairness of interpersonal interaction through communication during the performance appraisal process. Moreover, the definition of distributive justice comes back to the equity theory, which refers to when individuals compare their input and output ratios of appraisal outcomes with others to determine the level of fairness (Adams, 1965). If the employees perceive inequity, they change their efforts or perceptions of inputs or outputs (Erdogan, 2002).

2.2.2 Equity Theory

The first development of the equity theory of motivation was made in 1965 by John Stacey Adams. Equity theory is considered a balance between the inputs achieved by individuals, such as effort and skills, and what they receive as rewards, such as compensation and promotion (Adams, 1965). These people provide their equity judgment by comparing their received reward ratio for similar inputs to that of other people who receive rewards in comparison to them. If the employees feel they receive less than they deserve, that can increase their tension. Thus, this tension is generated as they feel a sense of injustice (Robbins, 1993). According to Carrell and Dittrich (1978), equity theory is related to employees’ performances because the received payment and other rewards influence their motivation to perform better. Accordingly, a positive perception of the received rewards by employees can change their behavior to positively complete their tasks (Kamau, 2012).

Moreover, equity theory relates to the motivation of employees. It depends on the fair treatment they receive in decisions concerning compensation and promotion. If the employees feel they are treated unfairly, they will be less motivated to deliver their maximum (Tahar-Kedem, 2014). In this respect, the equity theory is selected for this study because it refers to employees' expectations that procedures of the appraisal system should be applied fairly, accurately, ethically, amendable, freely, and participatively. Thus, if the employees perceive procedural fairness that would enhance their positive attitude toward the appraisal outcomes, they will be more motivated to improve their performance effectively (Ullah et al., 2021). As a result, this theory is adopted in this study to evaluate the perceived appraisal fairness at the ICRC and its influence on employees’ performance.

2.2.3 Expectancy Theory

Vroom was the scholar who created the expectancy theory in 1964. Through this theory, Vroom suggested that employees will be motivated to perform with a high level of effort when they think that their efforts will lead to a high level of performance (expectancy), which in turn will lead to rewards (instrumentality) such as an increased salary, a bonus, or a promotion. Therefore, this effort will lead to better performance appraisal and a good reward from the organization, such as a salary increment, bonus, or promotion, for satisfying the goals of the employees (Valence) (Vroom, 1964). This theory argues that the decision of an individual to behave in a certain way depends on the expected outcomes and the value a person attached to them (Robbins, 1993).

As stated by Fudge and Schlacter (1999), expectancy theory is a process theory of motivation that focuses on personal opinions of the set objectives and achieving them. It means that the results of the PAS process will lead to the expected outcomes. For example, when the employees accomplish the set objectives, they expect a reward such as promotion, recognition, or a salary increase, which, in turn, leads to a higher level of motivation. Moreover, expectancy theory suggests that employees will modify their behaviour according to the perceived satisfaction they receive from their organization. When they receive good rewards, that will affect their behaviour positively, which leads to achieving goals effectively and efficiently (Salaman et al., 2005).

2.3 Empirical Review

The first objective of this study depends on the effective indicators that affect the outcomes of performance appraisal effectiveness, involving perceived fairness, perceived accuracy, and the quality of appraisal feedback, to examine the impact of performance appraisal on employee performance. The secondary objective is to determine whether motivation moderates the relationship between the performance evaluation system and employees' performance.

2.3.1 Perceived Fairness and Employees’ Performance

According to Jacobs et al. (1980), the fairness perception of performance evaluation is a vital measure in examining the effectiveness and efficiency of the performance of both employees and the organization. While the performance appraisal system is considered a fundamental function of HR, it helps to make critical decisions about employees, promotions, pay, and training needs (Levy & Williams, 2004). Accordingly, the fairness of the appraisal system can have a great influence on employees’ future careers. Based on the Bretz et al. (1992) study, the perceived fairness of the performance review and the performance appraisal system is the most significant performance appraisal problem faced by organizations. The findings of their study indicated that most workers perceive the performance appraisal system as inaccurate and unfair.

On the other hand, past studies have indicated that if the employees perceive the appraisal system fairly, they will be more satisfied, committed, and motivated to increase productivity and provide better performance (Roberson & Stewart, 2006). Thus, organizations need to examine the employees' perception of fairness because it affects all stages of the appraisal process (Levy & Williams, 2004). They should ensure that all PAS processes are applied in a valid and unbiased manner to make all employees believe that they will receive fair performance appraisal outcomes from their managers (Taylor et al., 1995).

Moreover, previous literature has classified appraisal fairness into three parts: interactional fairness, procedural fairness, and distributive fairness, according to the justice theory (Greenberg, 1986). Interactional fairness refers to how employees are treated in the appraisal processes and procedures. And procedural fairness is concerned with the fair processes of carrying out the procedures set up by the organization in order to achieve justice appraisal outcomes. Besides, the distributive context relates to the fair outcomes of performance appraisals attained by employees (Colquitt et al., 2001). Therefore, organizations should consider all three types of appraisal fairness to implement a fair PAS. They need to recognize the negative impact of unfair appraisal systems on employee perception, such as decreased motivation, tardiness, low commitment, idleness, and increased absenteeism (Wright, 2004).

Furthermore, equity theory is another theory used to determine employee perceptions about fairness issues, as discussed above. According to this theory, the motivation and enthusiasm of employees at environmental work depend on the fair treatment they get in decisions concerning compensation and promotion. In this context, if the employees perceived they were treated unfairly, they would be demotivated (Tahar-Kedem, 2014). On the other hand, employees will be more motivated if they have the perception that they are being rewarded satisfactorily, increasing their productivity and performance (Mariti, 2019).

2.3.2 Perceived Accuracy and Employee’ Performance

In line with Wood and Marshall (2008), perceived accuracy is an essential aspect of examining the effectiveness of the PAS by evaluating the employee's motivation and satisfaction with the performance appraisal as it would impact their performance. Prior literature indicates that when employees perceive the accuracy of the PAS outcomes, they are more satisfied to accept the results and work on them to produce better performance. In this regard, the perceived accuracy of employees relates to the expectancy theory by Porter and Lawler (1968), which refers to employee motivation outcomes when they believe the extra efforts will lead to expected performance and greater rewards like promotion, salary increase, or bonus (Mariti, 2019).

Moreover, the accuracy rating of the PAS is considered the primary factor of appraisal effectiveness as it helps to make a range of administrative decisions that include development, training, promotion, and compensation for enhancing employee performance effectively (Ilgen & Feldman, 1983). As stated in the Murphy & Cleveland (1991) study, the past researchers of the PAS focused on the shortcomings of data processing rather than understanding how the appraisers evaluate their employees. The competency of appraisers depends on their having the capabilities and skills to motivate their subordinates effectively.

In the general context, the performance appraisal system is exposed to a variety of possible sources of error that the rater should be aware of to prevent and eliminate them. These common errors include varying standards of recency, primacy effects, rater bias, central tendency, leniency, and strictness errors; halo and horns effects; similar-to-me/different-from-me errors; sampling errors; and strictness errors (Mathis & Jackson, 2010), as demonstrated in Figure 2.1. below.

Figure 2.1: Common Errors of Raters

Abbildung in dieser Leseprobe nicht enthalten

Source: (Mathis & Jackson, 2010)

However, even if there is a well-structured appraisal system and a competent appraiser, this is insufficient to achieve an accurate PA because there are other various effect factors. These factors involve unclear communication of expectations and standards between the line manager and subordinate, understandable and agreed-upon indicators to accomplish the set objectives, and employees’ reactions to the appraisal results. In addition to being worried about biased views and the possibility of challenging evaluation results (Murphy & Cleveland, 1995; Ullah et al., 2021). Therefore, using these criteria is the proper way to assess employees' perceived accuracy toward PAS. Consistent with Hulland's (1999) research, a good evaluation of the PAS' accuracy depends on the employees' views because they know well how they performed their duties. If they have a negative attitude and doubt about the PAS' accuracy, that can impact the whole system. In this regard, the effectiveness and neutrality of PAS don't only depend on their technical validity and reliability but also on the workers' reactions (Henseler et al., 2015). Thus, HR leaders must ensure that all employees accept the method of implementing the PAS process.

2.3.3 The Quality of Appraisal Feedback and Employees’ Performance

Supervisors can build a trustworthy relationship with their subordinates through communication to understand their wishes, goals, and motivations; communication can affect the employee's performance directly and indirectly (Karen K. Myers & Sadaghiani, 2010). In recent years, many researchers have focused particularly on one form of communication, namely feedback. Based on Aguinis's (2009) study, the quality of appraisal feedback is an effective indicator that can lead to positive outcomes in performance appraisal when it is timely, specific, and derived from a reasonable conception. Efficient appraisal feedback can promote good relationships between line managers and employees and identify the needed areas of improvement for better performance. It can also increase employee motivation, engagement, and job satisfaction. Effective communication helps to direct employee behavior positively and increase productivity.

Furthermore, appraisal feedback can increase employee motivation and performance to a high level. Besides, appraisal feedback can let employees with poor performance know how their efforts are valued. Additionally, it lets these employees know that their performance is unsatisfactory and requires improvement (Jones & George, 2009). Feedback quality should be provided with a positive attitude and direct communication between the line manager and the subordinator about performance and the needed improvement (Roberson & Stewart, 2006). Thus, appraisal feedback is a critical part of an effective appraisal system for all parties in the appraisal process; if there is no quality feedback, it will cause inaccurate evaluations, stress, and a way of hunting for mistakes and providing notes negatively (Brown & John, 2005).

To encourage workers to improve and lessen the negative aspects of their performance, line managers should give even negative feedback in an effective and transparent manner (Roberson & Stewart, 2006). In this aspect, past studies showed that international companies do not provide their employees with the chance to communicate the relevant matters to their careers, including feelings, strengths, weaknesses, and the accomplishment of individual objectives (Nathan et al., 1991). In other words, employees in international companies are not given enough time for appraisal feedback. As a result, they have a negative perception of the appraisal system, believing it is unfair and inaccurate. Consequently, it reveals that appraisal feedback has a significant impact on employee performance, which remains an ongoing issue in many international companies.

2.3.4 Motivation as Moderator Between Appraisal System and Employees’ Performance

Based on the Iqbal et al. (2013) study, motivation is a driving force that impacts and leads a person to change behaviour toward achieving organizational goals. It means that an employee needs to be motivated to work well; otherwise, he won't be more productive and active in achieving organizational objectives effectively and efficiently. Moreover, motivation is defined as the employee's desire to enhance his performance according to the received feedback, which results in future improvements (Ilgen et al., 2014). Therefore, the motivation that is analyzed herein is the employees' motivation after the performance appraisal process. According to Selvarajan & Cloninger (2009), higher levels of perceived fairness and accuracy among employees can generate higher levels of appraisal motivation and satisfaction and enhance future performance. Thus, the main factors that motivate employees are appraisal fairness, appraisal accuracy, and effective appraisal feedback.

According to many organizational researchers, perceived fairness is the core source of motivation for employees (Weiss & Suckow, 1999; Cropanzano et al., 2003). In other words, if the employees perceive that the PAS is unfair and inaccurate, they will not care about the feedback they receive for improvement (Levy & Williams, 2004). Obviously, the impact of fairness perceptions on the employee's motivation goes back to the self-determination theory, which states that when the fundamental needs of employees are met, they will be motivated to improve their performance in the future (Bies, 2001). Besides, justice theory, which includes interactional fairness, procedural fairness, and distributive fairness, is positively related to motivation to improve performance, as discussed above.

Moreover, appraisal accuracy plays a central role in motivating employees for effective outcomes and accurate performance (Murphy & Cleveland, 1991; Mayer & Davis, 1999). As a result, it can determine the accuracy of the PAS using the expectancy theory, which refers to the expectations and standards toward a specific goal that help motivate employees to exert significant effort in order to achieve better performance (Vroom, 1964). This theory supposes that employees are motivated to behave in a particular way due to a combination of three perceptions that involve expectancy, instrumentality, and valence (Robbins, 1993). Further, the reactions of the employees to the last evaluation and their confidence in the appraisers influence their perception of the accuracy of PAS, which can impact the level of employee motivation (Sudin, 2011). If employees have faith in their appraiser's assessment, the perceived accuracy of the PAS-positive lead to better performance (Clarke et al., 2019).

Furthermore, there is a significant relationship between the feedback accuracy of PA and motivation that depends on the perceived feedback quality (Taylor et al., 1995). According to Brett & Atwater (2001), employees who thought performance feedback was less accurate viewed it as less helpful for future development and were less motivated to alter their behaviour and perform better. Therefore, appraisal feedback affects employees' motivation and performance, whether positive or negative, according to its accuracy, valence, and kind. Ilies & Judge (2005) claim that receiving bad feedback has a negative impact on perceptions of the accuracy of the feedback given. Therefore, line managers who provide accurate and positive feedback can enhance employees' motivation and performance, while managers who provide negative feedback can cause a decrease in the motivation and performance levels of employees (Castille, 2018). Positive feedback produces a positive effect that leads to increased perceptions of feedback accuracy and enhances the employee's motivation and performance.

2.4 Research Gap

The most important of human resource function within organizations is performance appraisal, in which raters or supervisors analyze and evaluate the performance of their subordinates (Selvarajan & Cloninger, 2009). There have been many studies conducted on the effectiveness of the performance appraisal system on employees’ performance. Despite the fact that the performance appraisal system has many beneficial aspects for employers and employees, including pay rates, promotions, motivating factors, development needs, and training requirements, it appears that both employees and managers continue to have a negative attitude and are generally unhappy with the results (Khoury & Analoui, 2004). Past studies have focused on performance appraisal within organizational psychology to examine employee performance. However, these studies revealed that both employers and employees are still not satisfied with the outcomes of performance appraisal systems in terms of fairness, accuracy, and feedback (DeNisi & Pritchard, 2006; Selvarajan & Cloninger, 2009).

However, most of these studies were conducted in Western countries. Because of unstable politics, continuous conflicts, and socio-cultural and economic differences, this finding cannot be generalized in a third-world country like Yemen. Moreover, this particular issue has not been clearly researched in the Middle East context, specifically from the perspective of Yemen. Therefore, this demonstrates the presence of a gap concerning the influence of performance appraisal systems on employee performance. No previous research has investigated the impact of the appraisal system on employees’ performance in humanitarian organizations in Yemen like the ICRC. To close this gap, it is required to assess how the ICRC's performance evaluation system has affected its employees in Yemen.

2.5 Conceptual Framework

As illustrated in the following conceptual framework in Figure 2.2, it determines the relationship between variables in accordance with what has been critically discussed above. That shows the impact of performance appraisal systems on employee performance by evaluating the effective indicators that can affect the outcomes of performance appraisal effectiveness involving fairness, accuracy, and feedback. It also shows the impact of motivation as a moderator between the performance appraisal system and employees' performance.

Figure 2.2: Conceptional Framework

Abbildung in dieser Leseprobe nicht enthalten

Source: Author (2023)

2.6 Research Hypotheses

The researcher determined to discover the relationship between the performance appraisal system and the employees’ performance by examining the following hypotheses:

i. H1: Perceived fairness in the performance appraisal system has a significant impact on employees’ performance.
ii. H2: Perceived accuracy in the performance appraisal system has a significant impact on employees’ performance.
iii. H3: The quality of performance appraisal feedback has a significant impact on employees’ performance.
iv. H4: Motivation moderates the relationship between the performance appraisal system and employees' performance.

2.7 Operationalization and Measurement of Variables

Table 2.1: Operationalization and Measurement of Variables

Abbildung in dieser Leseprobe nicht enthalten

Source: Author (2023)

CHAPTER THREE RESEARCH METHODOLOGY

3.1 Introduction

The study built an academic design by connecting theories, methods, and techniques as a comprehensive and coherent unit to make sure of the accuracy of the collected data. The methodology of the study depends on the research onion model. It started with determining the philosophy of the study, which was positivism with a deductive approach and descriptive design for collecting the data of the research. In general, the study is quantitative, and the time horizon is cross-sectional. To test the study hypotheses, the study relied heavily on primary data collected through the questionnaire survey. For the statistical techniques, the study has used descriptive statistics, correlation analysis, and simple and multiple regression to examine the impacts of the independent variable on the dependent variable and to check the relationship between the variables.

3.2 Research Onion

There are many past studies about the research process. Today, many researchers adopt the research onion model for their research processes. This model was developed by Saunders, Lewis, and Thornhill (2007). The onion model provided a clear series of stages with different methods of data that can be used in a variety of contexts, which helped to design the research methodology effectively (Bryman, 2012). This model points to the research process going from the outer layer to the inner layer (Aguinis, 2009). It includes six main layers: research philosophies, approaches, strategies, choices, time horizons, techniques, and procedures, as seen in Figure 3.1) below.

Figure 3.1: The Research Onion Model

Abbildung in dieser Leseprobe nicht enthalten

Source: (Saunders, et al., 2009)

3.3 Research Onion of the Current Study

According to the onion model, the research process of the current study has been determined, particularly as shown in Figure 3.2. The philosophy of this study was positivism, and the nature of the research was quantitative. The current study adopted the deductive approach to examine causal relationships between variables. The strategy of this research was a case study that depends on using a questionnaire survey for collecting data from the respondents. The study design was cross-sectional and descriptive, describing specific factors or causes related to the research topic at a particular time.

Figure 3.2: The Research Onion Model of the Current Study

Abbildung in dieser Leseprobe nicht enthalten

Source: Author (2023)

3.3.1 Research Philosophy

This research used positivism philosophy, which it considers to be the most effective method of studying human and social behavior. This philosophy was created as a reaction to the metaphysical view (Aiken, 1965). The central idea of positivism holds that social context should be evaluated objectively rather than assumed. It can be conducted subjectively based on reflection, sensation, or intuition (Easterby-Smith et al., 2008).

Therefore, the researcher has used this philosophy to measure the impact of the performance appraisal system on the employee’s performance and its relation to motivation at the ICRC organization in Yemen. Based on Saunders et al.'s (2009) view, researchers should investigate human and social behavior independently, neutrally, and with an objective viewpoint. Hence, the researcher depended on the method of examining related theories, hypotheses, and variables independently and neutrally. In addition to using the numbers in an objective form and conducting statistical methods in quantitative research for analysis.

3.3.2 Research Approach

This study selected the deductive approach because it uses it to examine causal relationships between variables. It also relates more to the positivist philosophy. This approach starts with one or more objectives that generate one or more research questions required to answer them. This method depends on the quantitative method to collect data through the questionnaire to examine the relationship between variables. According to Saunders et al. (2009), there are two types of research approaches: deductive and inductive. While the inductive approach uses the collected data to develop theories, the deductive approach uses it to test existing theories and hypotheses.

The variables of this study were the performance appraisal system as an independent variable and the employees’ performance as the dependent variable. The main independent variable (PAS) was classified and divided into three constructs as independent variables that affect its effectiveness: fairness perception, perception of accuracy, and quality of appraisal feedback. The study also contained the motivation variable as a moderator variable between the performance appraisal system and employees’ performance. In this respect, the study examined if motivation has a significant impact on the relationship between PAS and EP (King, 2013). Through this approach, the study tested the hypotheses and answered the study questions.

3.3.3 Research Design

There are two main categories of research designs, depending on the questions: exploratory and descriptive. While the descriptive design uses it to describe specific factors or causes connected to the research topic, the exploratory design uses it to explore the main aspects of the research and create a view of the topic under study.

This study used the descriptive method because it is suitable for a survey method to examine the impact of appraisal systems on employee performance by examining associative relationships between variables. This method is designed for conducting such a study (Saunders et al., 2009). Besides, this study used a cross-sectional design that focuses on phenomena at a particular time to examine associative relationships between variables.

Moreover, this study used a survey methodology through a standardized questionnaire with a large enough sample size of employees at the ICRC organization to generalize statistically about regularities in human social behavior. A descriptive study, also called case study research, collects data to answer questions concerning the specific issues of this study subject (Borg & Gall, 1989). Five questions in this study need to have answers, as mentioned in the 1.6 section.

In a nutshell, the natural design of this study was a descriptive quantitative method for data collection and analysis via a questionnaire survey strategy. As stated by Goundar (2012), quantitative research can provide a broad understanding of issues under investigation in terms of evaluating the performance, behaviors, and attitudes of the employees toward the PAS at the ICRC in Yemen. The descriptive design also relates to the deductive approach and research objectives for testing the mentioned hypotheses.

3.4 Data Collection Method

The main method of collecting data for this research was primary data collection.

The primary data collection strategy depended on the survey strategy to collect quantitative data by using structured questionnaires for the employees at the ICRC organization. Structured questionnaires relied on a 5-point Likert scale rating (1–5), where 1 meant strongly disagreeing and 5 implied strongly agreeing. The study adopted the survey strategy because it is appropriate to find answers to who, how, and what questions and to show the relationships between variables in this study (Saunders et al., 2009). The time horizon of this study was cross-sectional. As per Easterby-Smith et al. (2008), the questionnaire survey strategy is appropriate for cross-sectional studies.

Moreover, the study depended on the secondary data collected from relevant and appropriate sources to find answers to the research questions and test the study hypotheses (Dudovskiy, 2018). The secondary data collection method involves all the published books, magazines, journals, reports and newspapers related to the study topic and the chosen organization. The researcher followed the set criteria for selecting this data, which contains publication date, author credentials, source reliability, and discussion quality. He also focused on the contribution of the data to the development of the study area to make sure of the validity and reliability of the research. Then, the researcher used this data to make arguments and deep discussions of all the associated factors of the study (Dudovskiy, 2018).

3.5 Population and Sample

3.5.1 Population

The term "population" refers to the whole group of people or entities, and the researcher collects the data for the study from them (Schindler & Cooper, 2006). The population of this research included all the staff members working at the ICRC in Yemen. There is no official report that determines the total number of employees. Therefore, the researcher asked the HR team directly, as he works there. According to that, 500 employees were working at the ICRC in Yemen.

3.5.2 Sampling Technique

The probability sampling method was the sampling technique employed in this study. This method was used mainly for the quantitative research method, as the probability sampling method is used mainly for the quantitative research method as each member of the population has an equal chance of being selected randomly (Casteel & Bridier, 2021). The used type for this study was a simple random sampling method.

Based on Denscombe's (2002) study, probability sampling is the best technique for a survey strategy study as the sample can represent a cross-section of the whole. This method also helps the researchers increase the accuracy and validity of the survey by measuring the error or bias degree using understandable statistical methods. In accordance with Saunders et al. (2009), probability sampling is not only increasing the accuracy of the results but also decreasing the time and money required for collecting, checking, and analyzing the data.

3.5.3 Sampling Size

Based on Saunders et al.'s (2009) study, the sample size of the probability sampling method should be large enough to increase the accuracy and validity of the data. A sufficient sample size must be used to apply survey methodology through a standardized questionnaire in order to statistically generalize patterns in human social behavior. When the sample is larger, the error and bias are much lower. The whole population of employees at the ICRC in Yemen is 500.

Thus, this study relied on Morgan & Krejcie's (1970) method of sampling for calculating the required sample size because it considers the population size, a specific margin of error, and the desired confidence interval. The table sample size of this method states that for a total population of 500, the minimum number of samples required to represent the whole population is 217. Accordingly, the appropriate sample size for this study was to collect 217 samples.

3.6 Validity and Reliability

Pilot testing and Cronbach's alpha were conducted to assess the validity and reliability of this study. According to Saunders et al. (2009), the validity and reliability of the collected data and the response rate depend on the design of the questions, the structure of the questionnaire, and the rigor of the pilot testing. Probability sampling is considered the superior method for increasing the accuracy of the collected data. According to Cronbach (1951), for collecting accurate and objective data on the Likert scale, one needs to test the reliability by using Cronbach's alpha to measure the internal consistency, which is the close relationship between a set of items or sub-group of the questions in the questionnaire, expressed as a number between 0 and 1. Specifically, the measurement rules of the Cronbach Alpha as determined by George and Mallery (2003) are the following:

Abbildung in dieser Leseprobe nicht enthalten

Table 3.1: Cronbach’s Alpha Test for the Current Study Reliability Statistics

Abbildung in dieser Leseprobe nicht enthalten

Source: Data Survey, (2023)

3.7 Resources Access for Primary and Secondary Data

3.7.1 Primary Data Collection

The study used questionnaires within the survey strategy for collecting data from the employees at the ICRC in Yemen (the target population). Employees are a central source of data collection because they are the primary stakeholders in performance appraisal system practices. The questionnaires were selected for this study because they provide an efficient method of collecting responses from a large sample before quantitative analysis since each person will get the same series of standardized questions to answer (Robson, 2002). Thus, the questionnaire is the primary data collection instrument used in this study because of its validity and reliability (Saunders et al., 2009). The questionnaire included a series of closed-ended questions graded on five Likert scales, along with an additional comment box. This question is considered a free-open question for each class of questions to provide the chance for the respondents to add any other information they view as important for the study. In terms of access to the ICRC employees, the researcher works at the ICRC company; however, he asked the ICRC head of HR to give him permission to access the ICRC employees through sending an official email that contains the link to the questionnaire. After that, he had obtained permission to distribute the survey to the target population.

The researcher used self-administered questionnaires, which the respondents answered. Questionnaires are administered electronically using the Internet (Internet-mediated questionnaires). It used an online software tool, SurveyMonkey.com, for creating a web-based questionnaire page. Then, the researcher sent an email containing the link to the questionnaire page to all respondents and collected them after one month. The researcher designed questionnaires according to the research objectives and questions based on a five-point Likert scale, where (1) means strongly disagree, (2) means disagree, (3) means undecided, (4) means agree, and (5) means strongly agree. Accordingly, there were five sections of the five variables to the questionnaire that contain 35 items. In addition to the demographic profile section at the beginning that contains 6 items. The types of variables were opinion variables for the independent variables, behavioral variables for the dependent variables, and attribute variables for the respondents’ characteristics.

3.7.2 Secondary Data Collection

As discussed above, it used external sources such as reports and journal articles, books, or collecting the related data for this study. Secondary data was used to support arguments and have in-depth discussions about all aspects of the research (Dudovskiy, 2018). The secondary data of this study was used to investigate theories, identify and definite key words, conduct an empirical review, conduct a deep discussion and critical argument of the topic issues, and select appropriate methodologies and statistics techniques. The arrangements for data access, the researcher works at the ICRC, and while he can access and collect internal data, he has relied on collecting that data that is relevant to operations and the history of the company from sources in the public domain, such as websites and annual reports.

3.8 Statistical Techniques

Based on the Lewis-Beck (1995) study, the statistical techniques for data include analyzing, inspecting, cleaning, coding in a systematic way, and drawing meaningful interpretations to provide a clear academic picture of the research findings. Therefore, before analyzing the obtained data, the data had been checked, coded, and handled. Further, the data were tested for integrity and errors. All collected data were analyzed by using SPSS (Statistical Packages for Social Sciences) version 25 step by step, as discussed in the following points.

3.8.1 Descriptive Statistics

Descriptive statistics was applied to analyze and present the data according to the characteristics of the respondents, including gender, age, education level, years of experience, and contract type. Also, descriptive statistics were used to determine the minimum and maximum scores, means, and standard deviations (SDs) of each question in each variable. According to Saunders et al. (2009), it is very significant to assess the distribution of the numerical data values for a variable around its mean by using the standard deviation. If the data values are close to the mean score, this is more typical than being more different.

3.8.2 Spearman’s Rho Correlation

Spearman’s rho correlation was conducted to measure the strength of the relationship between two variables. This analysis determined whether there is a positive or negative relationship, or whether there is no relationship at all, using the correlation coefficient value, and that the correlation always falls between +1 and -1 (Saunders et al., 2009). The value of the coefficient, expressed like this:

-A perfect negative correlation is shown by the symbol (-1).
-A perfect positive correlation is represented by (+1).
-The value (0) represents perfectly independent relationships or no correlations.
-Between +1 and -1 are weaker positive and negative correlations.

3.8.3 Analyzing Regression Coefficients

The regression coefficient helps to assess the strength of the relationship between a numerical dependent variable and one or more numerical independent variables, represented by R2 (Schindler & Cooper, 2006). It is used to assess the fit in the variation between a dependent variable (EP) and independent variables (PF, PA, and FQ) one by one. In cases where R2 is high, the model is more reliable and closer to its predictions, and vice versa (Saunders et al., 2009). In this study, the regression coefficient was calculated using simple linear regression, as follows: Y = 0 + 1X +. R2 ranges from 0 to 1. 0 and 1 refer to the parameters, and it refers to the probabilistic error term of the linear regression model that explained any variability in the dependent variable that could not be explained by X (Wagschal & Mooi, 2014). In addition, the t-test results with the corresponding p-value were used to test whether the individual independent variable has a significant relationship with the dependent variable.

On the other hand, a multiple regression was conducted to assess the overall and connected relationship between performance appraisal system constructs and employee performance that included PF, PA, and FQ as independent variables regressed against employee performance as the dependent variable. And for determining the stronger variable. This regression was applied to determine the dependent variable (EP) based on the multiple independent variables (PF, PA, and FQ). In this respect, the multiple linear regression model has the following form (Wagschal & Mooi, 2014): Y = 0 + 1X + 2X + 3X.

Consequently, the equations of the regression models are as follows:

-Y = β0 + β1 (PF)+ ε.
-Y = β0 + β1 (PA) + ε.
-Y = β0 + β1 (FQ) + ε.
-Y = β0 + β1 (PF) + β2 (PA) + β3 (FQ)+ ε.

3.8.4 Variance (ANOVA) and F-test

The analysis of variance (ANOVA) was applied to test the differences between the means of variables for statistical significance. ANOVA uses the F-test to evaluate the causal relationship between the dependent variable EP and the three independent variables, PF, PA, and FQ, along with performing moderation analysis for the motivation variable (M) as a moderator. The F-test uses F values to examine data; if the statistic values were less than 0.05, the model had a significant effect; otherwise, it had an insignificant effect (Vaus, 2002).

3.8.5 Assumptions of Linear Regression Tests

3.8.5.1 Multi-collinearity Test:

A variance inflation factor (VIF) was used to determine whether or not there is multicollinearity. VIF was used to figure out the amount of variance that was inflated (Saunders et al., 2009). Hair et al. (2006) showed that a large VIF value of 10 or above refers to high collinearity, while less than that refers to low collinearity between variables.

3.8.5.2 Test for Normality:

This test was conducted to determine whether the dependent variable and the independent variables have normal distributions or not (Hair et al., 2006).

3.8.5.3 Test for Autocorrelation

The autocorrelation test applies to discover the presence or absence of a correlation between the time of observation between period t and period t–1 by using the Durbin-Watson (DW) test (Saunders et al., 2009).

This test uses the following hypotheses:

H0 (null hypothesis): There is no correlation among the residuals.

HA (alternative hypothesis): The residuals are autocorrelated.

The value of the DW statistic ranges from 0 to 4. A DW value of 2 or near 2 indicates no autocorrelation; less than 2 indicates positive autocorrelation; and more than 2 indicates negative autocorrelation. Therefore, a value between 1.5 and 2.5 is relatively normal and acceptable.

3.8.6 Moderated Regression Analysis (MRA)

An analysis of moderation was used in the study to determine whether employee motivation affects the relationship between the performance evaluation system as an independent variable and employees’ performance as a dependent variable. In this section, the three independent variables (PF, PA, and FQ) are merged into one variable, the performance appraisal system (PAS), as an independent variable (X).

Abbildung in dieser Leseprobe nicht enthalten

The aim of moderation analysis is to examine the impact of the moderating variable, which is motivation (M), between the performance appraisal system as an independent variable (X) and employees’ performance as a dependent variable (Y), as displayed in Figure 3.3 below.

Figure 3.3: Moderation Framework

Abbildung in dieser Leseprobe nicht enthalten

Source: Author (2023)

Therefore, the moderating analysis was conducted by assessing the interaction effect of moderating. The interaction term is depicted as X* Ӎ (Z) (Memon, et al., 2019). As a result, the statistical model for moderation analysis includes an interaction term (Z) that points to the dependent variable, as reflected in Figure 3.4 below.

Figure 3.4: A Statistical Model for Moderating Analysis

Abbildung in dieser Leseprobe nicht enthalten

Source: Author (2023)

Then, the moderation effect was assessed by creating a moderated regression model that figures out whether a moderator (motivation) impacts the strength and/or direction of the relationship between an independent variable (performance appraisal system) and dependent variable (employees’ performance), along with conducting the assumptions of linear regression tests that were discussed above (Andersson et al., 2014). The regression equation model of the moderating variable is Y = 0 + 1X + 2M + 3XM +. Thus, the equation of the motivation variable is as follows:

-Y = β0 + β1 PAS + β2 M + β3 X*M+ ε.

3.9 Ethical Consideration

The ethical considerations of this study were more concerned with ethical issues related to the use of individuals as the main subjects of the study. The main goal of this study is to protect all the participants and show the research in ways that can serve their interests in the workplace. The researcher would ensure this research doesn’t cause any physical harm, discomfort, pain, or embarrassment to any respondent. Moreover, the researcher checked the ethical viability by making strategies that consider issues that relate to risk management, protecting confidentiality, and the process of informed approval (Saunders et al., 2009).

This study relied on a questionnaire to collect the primary data from the target population. Questionnaires were electronically distributed with a polite introductory note and a clear and specific purpose for the research. Then, provided assurances about confidentiality and how data collected during and after the study was managed. The questionnaire didn’t contain individual names, mobile numbers, and addresses to maintain privacy. After that, the researcher got permission to use the official email of the ICRC organization to distribute the questionnaires to the target population.

Moreover, the researcher explained the goal of the research to the targeted respondents and the benefits they would gain from it without exaggeration. The researcher got permission to do this study from the head HR manager of the organization in Yemen, as this study may help the organization develop the performance of its employees. The researcher also used secondary data that can be taken from the republic's records, such as reports and online references.

3.10 Chapter Summary

The study shaped an academic design by tying together ideas, methods, and approaches as one block and coherent context to ensure the accuracy of the data gathered. The research onion model adopts the study's methodology. The first step was deciding on the study's philosophy, which was positivism with a logical methodology and descriptive design for gathering the research's data. The study is quantitative in nature and has a cross-sectional time frame. The study made extensive use of primary data gathered from the survey to evaluate its hypotheses. Descriptive statistics, correlation analysis, simple and multiple regression, and statistical testing have all been employed in the study to analyze the effects of the independent variables on the dependent variable and to ensure the relationship between the variables.

CHPTER FOUR DATA ANALYSIS AND PRESENTATION

4.1 Introduction

This chapter presents and discusses the descriptive statistics results of the survey data. Firstly, the study undertook descriptive statistics to analyze preliminary information on the demographic profiles. Descriptive statistics was also used to determine the mean score values and standard deviation scores of the variables in this study. Secondly, correlation analysis was used to examine the effect of the relationship between the performance appraisal system and employees' performance. Then, regression analysis was conducted to determine the nature of the relationship between the independent variables and the dependent variable. Besides, it used the assumptions of linear regression tests to model the relationship between a response and a predictor. The linear regression tests included tests for multicollinearity, autocorrelation, and normality. As such, moderation analyzes were similarly applied in the current study to examine if motivation moderates the relationship between the performance appraisal system and employee performance.

4.2 Response Rate

The questionnaire survey for this research was conducted among 217 employees working at the ICRC in Yemen. The employees were selected because they are the main stakeholders in the performance appraisal system and have the highest potential for influencing an organization’s performance through their performance appraisal. One hundred forty-three employees out of 217 employees completed the responses to the questionnaire for this study, which represents a response rate of 65.90%. According to Kothari (2004), if the survey got a 50% response rate, that is acceptable, 60% is good, and 70% is very good. Therefore, the response rate is considered a good representative sample, representing the whole population of the study.

4.3 Descriptive Statistics of Demographic Profile

Table 4.1: The Results of the Demographic Characteristics of Respondents

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data, (2023)

Figure 3.5: Demographic Characteristics Dashboard

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data, (2023)

The above (Table 4.1) determines the demographic characteristics of the respondents, which include gender, age, education level, years of experience, staff position and contract type. The demographic variables were collected and analyzed for this study, which targeted employees at the ICRC in Yemen.

The results of the study of the demographic characteristics are detailed in Table 4.1 above. It reveals the majority of the respondents, 79% (113), were male, and the remaining 21% (30) were female. The age category ranged from 18 to over 50 years, with more than half of the respondents (employees) in the 31-to-40-year group (62.2%), the next higher group whose ages were between 41 and 50 years (18.9%), and those between 26 and 30 years (14.7%).

The category of educational qualification of respondents reveals that most of them have bachelor’s degrees, 57.3% (82), followed by those who have master’s degrees, 34.3% (49). The majority of the respondents have between 1 and 5 years of experience (53.1%), while the next group has between 6 and 10 years of experience (23.1%). For the staff category, it shows most of the respondents were subordinates, 67.1% (96), followed by the group who were both line managers and subordinates, 23.8% (34). Finally, it shows that the line managers of most respondents were expatriate (mobile), 60.1% (86), while the line managers of the remaining respondents were resident staff, 39.9% (57).

4.4 Descriptive Statistics of the Performance Appraisal System

This study focused on examining the impact of the performance appraisal system on employees' performance by evaluating the effective indicators of performance appraisal effectiveness, which include perceived fairness, perceived accuracy, and feedback quality. Therefore, descriptive statistics was used to determine the mean score values and standard deviation scores.

4.4.1 Perceived Fairness of the Performance Appraisal System

According to the overall response to the fairness of the performance appraisal questionnaire in Table 4.2 below, the overall mean score was 3.44 with a standard deviation of 0.77.

Table 4.2: Mean Scores for Perceived Fairness of the Performance Appraisal System

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

Moreover, the results showed the highest mean score was 3.92 and the lowest mean score was 2.99. That indicated that most respondents were more inclined toward "undecided" and "agree," which implied that they somewhat agreed with the statements, which are related to the fairness of the performance appraisal system.

4.4.2 Perceived Accuracy of the Appraisal System

Table 4.3: Mean Scores for Perceived Accuracy of the Performance Appraisal System

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

The total mean score was 3.46 with a standard deviation of 0.61 based on the overall responses to the accuracy of the performance appraisal questionnaire in Table 4.3 above. The mean score ranged from 2.75 to 3.73 with the highest mean score. This showed that the majority of respondents had a tendency to select "undecided" and "agree," which suggested that they only slightly disagreed with the claims relating to the accuracy of the performance rating system.

4.4.3 Quality of Performance Appraisal Feedback

Table 4.4: Mean Scores for Quality of Performance Appraisal Feedback

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

The total mean score was 3.55 with a standard deviation of 0.68 based on the overall replies to the quality of the performance appraisal feedback questionnaire in Table 4.4 above. It revealed the highest mean score was 3.59, while the lowest mean score was 3.41 That indicated that most respondents were more inclined toward "undecided" and "agree," which implied that they somewhat agreed with the statements, which are related to the quality of performance appraisal feedback.

4.4.4 Motivation as a Moderator Between the PAS and Employees' Performance

The average motivation score across all responses was 3.50, with a standard deviation of 0.82, as shown in Table 4.5 below. The results showed that 3.82 was the highest mean score and 3.16 was the lowest mean score. That indicated that most respondents were more inclined to be "undecided" or "agree." That implied that they are somewhat satisfied with the statements, which are related to motivation as a moderator variable (M) between PAS and EP.

Table 4.5: Mean Scores for Motivation as a Moderator Between PAS and EP

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

4.4.5 Employees’ Performance

The overall mean score for the employees' performance survey was 4.23, with a standard deviation of 0.45, according to the overall responses in Table 4.6 below. It also revealed that 4.32 was the highest mean score and 4.19 was the lowest. This suggested that the majority of respondents were more likely to "agree" and "strongly agree," which signified that they in some way strongly agreed with the assertions that were made regarding the performance of the employees.

Table 4.6: Mean Scores for Employees’ Performance

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

4.4.6 Summary of the Descriptive Statistics of the Above Findings

Table 4.7: Summary of Overall Mean Scores of Variables

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

4.5 Spearman’s Rho Correlation Analysis

4.5.1 The Impact of Performance Appraisal System on Employees’ Performance

Spearman’s rho correlation was conducted to measure the strength of the relationship between each independent variable and dependent variable. That helped figure out whether those variables have a positive or negative relationship if present, or if there is no relationship at all.

According to the result in Table 4.8 below, the correlation coefficient between perceived fairness and employees' performance was 0.288, with a p-value of 0.0004. The result of R indicates there was a weak positive correlation between these variables with very high statistical significance. In the same context, the correlation coefficient between perceived accuracy and employees' performance was 0.314, with a p-value of 0.0001. The result of R indicates there is a weak to moderate positive correlation between these variables with very high statistical significance. The correlation coefficient between feedback quality and employees' performance was 0.292, with a p-value of 0.0003. This R indicated a weak correlation with the same high statistical significance of other variables.

Table 4.8: Spearman’s Rho Correlation Analysis Results

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

Consequently, there was a positive relationship between variables, but it was weak. While the P-value was highly significant, which refers to the existing impact between all the independent variables (perceived fairness, perceived accuracy, and feedback quality) and dependent variables (EP), Thus, the null hypothesis is rejected, and we accept the alternative hypothesis.

4.6 Regression Coefficient Analysis

4.6.1 The Impact of Perceived Appraisal Fairness on Employees’ Performance

Table 4.9: Regression Analysis for Perceived Fairness and Employees’ Performance

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

The above (Table 4.9) shows an analysis of regression between the independent variable, perceived fairness, and employees’ performance as the dependent variable.

Since the R-value is 0.309, there is a positive correlation between the dependent variable and the independent variable. Further, this section shows the R square value, which represents how the total variation for the dependent variable is explained by the independent variable. In this respect, the value of R2 is 0.096, which means that 9.6% of the independent variable (perceived fairness of the performance appraisal) explained the dependent variable (employees’ performance). Besides, the adjusted R2 value of 0.089 reveals that 8.9% of the total variability in employees’ performance is explained by the fairness of the performance appraisal. Therefore, this is good, because 9.6% is not far off from 8.9%.

The second branch of the table below presents the F-test statistic and the regression significance estimate to test whether the overall regression model is a good fit for the data. Accordingly, the results show that the independent variable statistically significantly predicts the dependent variable, F (1, 141) = 14.924, p (0.0001) < .05, which indicates that the model fits the data well. That implies a statistically significant impact of the perceived fairness of performance appraisal on employee performance.

The third branch of the table represents the unstandardized Beta coefficient of perceived fairness of the performance appraisal, which shows how much the dependent variable (employees’ performance) changes when the appraisal fairness increases by one unit. Therefore, the change is 0.182, which means that the average value of employees’ performance increases by a value of 0.182 when appraisal fairness increases by one unit. While the value of employee performance is 3.606, the perceived fairness value is zero. Consequently, the estimated model coefficient is the regression equation: Y = 3.606 + 0.182 EP. Moreover, this section shows the t-test results associated with the p-value to test whether the individual independent variable has a significant relationship with the dependent variable. The t-test result was 3.863 for the independent variable (PF), with a p-value of 0.000. That reveals a significant positive relationship between the perceived fairness of appraisal and employees’ performance since the p-value is less than the critical value of 0.05. Hence, the null hypothesis is rejected, while the alternative hypothesis is accepted.

4.6.2 The Impact of Perceived Accuracy on Employees’ Performance

Table 4.10: Regression Analysis for Perceived Accuracy and Employees’ Performance

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

The above (Table 4.10) shows the analysis of regression between the independent variable, perceived accuracy, and employees’ performance as the dependent variable.

The first section of the table is the model summary, which shows the R-value, which refers to the Pearson correlation coefficient. As the R-value is 0.384, there is a positive correlation between the dependent variable and the independent variable. The section also shows the R square value, which represents how the total variation for the dependent variable is explained by the independent variable. In this respect, the value of R2 is 0.147, which means that 14.7% of the independent variable (perceived accuracy) explained the dependent variable (employees’ performance). Besides, the adjusted R2 value of 0.141 reveals that 14.1% of the total variability in employees’ performance is explained by the accuracy of the performance appraisal. Therefore, this is good, since 14.7% is not far off from 14.1%.

The second branch of the table below presents the F-test statistic and the regression significance estimate to test whether the overall regression model is a good fit for the data. Accordingly, the results show that the independent variable statistically significantly predicts the dependent variable, F (1, 141) = 24.355; p (0.0001) < .05. That implies a statistically significant impact of the perceived accuracy of performance appraisal on employee performance.

The third branch of the table represents the unstandardized Beta coefficient of the perceived accuracy of the performance appraisal, which shows how much the dependent variable (employees’ performance) changes when the appraisal accuracy increases by one unit. Therefore, the change is 0.284, which means that the average value of employees’ performance increases by a value of 0.284 when appraisal fairness increases by one unit. While the value of employees’ performance is 3.249, the perceived fairness value is zero. Consequently, the estimated model coefficient is the regression equation, Y = 3.249 + 0.284 EP.

Moreover, this section shows the t-test results associated with the p-value to test whether the individual independent variable has a significant relationship with the dependent variable. The t-test result was 4.935 for the independent variable (PA), with a p-value of 0.000. That reveals a significant positive relationship between the perceived accuracy of the appraisal system and employees’ performance since the p-value is less than the critical value of 0.05. Hence, the null hypothesis is rejected, while the alternative hypothesis is accepted.

4.6.3 The Impact of Feedback Quality on Employees’ Performance

Table 4.11: Regression Analysis for Feedback Quality and Employees’ Performance

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

The above (Table 4.11) shows the analysis of regression between the independent variable, feedback quality, and employees’ performance as the dependent variable.

The first section of the table is the model summary, which shows the R-value, which refers to the Pearson correlation coefficient. As the R-value is 0.313, there is a positive correlation between the dependent variable and independent variable. The section also shows the R square value, which represents how the total variation for the dependent variable is explained by the independent variable. In this respect, the value of R2 is 0.098, which means that 9.8% of the independent variable (quality of performance appraisal feedback) explained the dependent variable (employee performance). In addition, the adjusted R2 value of 0.092 reveals that 9.2% of the total variability in employees’ performance is explained by the feedback quality of the performance appraisal system. Therefore, this is good, because 9.8% is not far off from 9.2%.

The second branch of the table below presents the F-test statistic and the regression significance estimate to test whether the overall regression model is a good fit for the data. Accordingly, the results show that the independent variable statistically significantly predicts the dependent variable, F (1, 141) = 15.330, p (0.0001) < .05, which indicates that the model fits the data well. This indicates a statistically significant impact of the quality of performance appraisal feedback on employee performance.

The third branch of the table represents the unstandardized beta coefficient quality of performance appraisal feedback, which shows how much the dependent variable (employees’ performance) changes when the appraisal feedback increases by one unit. Therefore, the change is 0.208, which means that the average value of employees’ performance increases by a value of 0.208 when feedback quality increases by one unit, while the value of employee performance is 3.493 when the feedback quality value is zero. Consequently, the estimated model coefficient is the regression equation, Y = 3.493 + 0.208 EP.

Moreover, this section shows the t-test results associated with the p-value to test whether the individual independent variable has a significant relationship with the dependent variable. The t-test result was 3.915 for the independent variable (FQ), with a p-value of 0.000. That reveals a significant positive relationship between the quality of the appraisal feedback and employees’ performance since the p-value is less than the critical value of 0.05. Hence, the null hypothesis is rejected, while the alternative hypothesis is accepted.

4.6.4 The Combined Impact of Performance Appraisal System Variables on Employees’ Performance

The below (Table 4.12) shows the analysis of the multiple regression model between one dependent variable (EP) and three independent variables (PF, PA, FQ).

The first section of the table is the model summary, which shows the R-value, which refers to the Pearson correlation coefficient. As the R-value is 0.386, there is a positive correlation between the dependent variable and the independent variable.

Table 4.12: Regression Analysis for the Combined Impact of Performance Appraisal System Variables on Employees’ Performance

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

Moreover, the first section shows the R-squared value, which represents how the total variation for the dependent variable is explained by the independent variables. In this respect, the value of R2 is 0.149, which means that 14.9% of the independent variables (PF, PA, and FQ) explained the dependent variable (EP). Besides, the adjusted R2 value of 0.130 reveals that 13% of the total variability in employees’ performance is explained by the three variables (PF, PA, and FQ) of the performance appraisal system. Therefore, this variation is good, since 14.9% is not far off from 13%.

The second branch of the table below presents the F-test statistic and the regression significance estimate to test whether the overall regression model is a good fit for the data. Accordingly, the results show that the independent variables statistically significantly predict the dependent variable, F (3, 139) =8.102, p (0.0000) < .05, which indicates that the model fits the data well. That implies a statistically significant impact of the performance appraisal system variables on employees’ performance.

The third branch of the table represents the unstandardized Beta coefficient for perceived fairness, perceived accuracy, and perceived feedback quality of the performance appraisal, which shows how much the dependent variable (employees’ performance) changes when the performance appraisal variables increase by one unit. Accordingly, the value of employee performance when the performance appraisal system (PAS) is at zero is 3.235. The coefficient of perceived fairness is 0.30, which means that the average value of employees’ performance increases by a value of 0.30 when perceived fairness increases by one unit. Concerning the coefficient of perceived accuracy, it is 0.243, which means that the average value of employees’ performance increases by a value of 0.243 when perceived accuracy increases by one unit. The coefficient of feedback quality is 0.014, which means that the average value of employees’ performance increases by a value of 0.014 when feedback quality increases by one unit. Consequently, the estimated model coefficient is the regression equation: Y = 3.235 + 0.30 PF + 0.243 PA + 0.014.

Moreover, this section shows the t-test results associated with the p-value to test whether the individual independent variables have a significant relationship with the dependent variable. According to the results, perceived fairness and feedback quality have a non-significant relationship with the employees’ performance because their p-values are larger than 0.05. Thus, we fail to reject the null hypothesis. While perceived accuracy has a significant relationship with employees’ performance. The t-test result was 2.290 for the independent variable (PA), at the p-value of 0.024, since the p-value is less than the critical value of 0.05, (at the 98% confidence level). Hence, the alternative hypothesis is accepted.

4.7 Assumptions of Linear Regression Tests

4.7.1 Test for Autocorrelation

As shown in Table 4.11, the value of DW statistics is 1.805, which is between 1.5 and 2.5. Therefore, the value of DW is relatively normal and acceptable.

4.7.2 Test for Normality

For checking the normality assumptions of multiple regression models, it used a histogram to check the normality. If the histogram's bars are too high in the middle and pierce through the normal curve, the histogram is well covered by data and normally distributed. Thus, the residuals are normally distributed, as depicted in Figure 4.1 below.

Figure 4.1: Histogram of Regression Standardized Residuals

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

Figure 4.2: Regression Standardized Residuals with a Q-Q Plot

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

Further, it was conducted to test the normality of residuals with a Q-Q plot. The residuals follow a normal distribution if the Q-Q plot forms a diagonal line around the zero. Thus, the data have a normal distribution, as demonstrated in Figure 4.2 above .

4.7.3 Multi-collinearity Test

As shown in Table 4.13 below, there is no multicollinearity between all the variables: perceived fairness, perceived accuracy, and feedback quality, because the VIF values are less than 10. Thus, multicollinearity would not be a problem in the regression model or its reliability.

Table 4.13: Multicollinearity Statistics Coefficientsa

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

4.8 Moderation Analysis of Motivation as a Moderating Variable

4.8.1 Moderated Regression Analysis

The study used a regression analysis of the moderating variable (motivation) between the independent variables (performance appraisal system variables) and the dependent variable (employees’ performance). The interaction effects of the performance appraisal system and motivation were tested using this regression. Thus, according to Cohen et al.'s (2003) suggestions, the regression analysis of the moderation analysis was conducted in three steps. The first step was to standardize independent variables (Zscore: PAS and Zscore: M), then compute them to generate the interaction variable, X* Ӎ = (Z). The second step was to perform regression analysis by entering the dependent variable (EP) on the independent variable (PAS), which was followed by the moderator variable, as demonstrated in Model 1 in Table 4.14.

Table 4.14: Regression Analysis for Motivation as a Moderator Variable

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

The last step was to regress the dependent variable (EP) on the interaction variable (Z) as an independent variable, as illustrated above in Model 2 in Table 4.14, to assess the effect of motivation and its role as a moderator in the relationship between the performance appraisal system and employees' performance.

Based on the result of the regression model shown in Table 4.14 in the first part, it is revealed that the R-value has increased from 0.380 to 0.411. Thus, there are stronger positive correlations between the dependent variable and overall independent variables with the moderating variable than without the moderating variable. The model summary also shows R2 has increased from 0.144 to 0.169, which indicates that 16.9% of the variation is explained by the addition of the interaction term (Z). In addition, the adjusted R2 value has increased from 0.132 to 0.151, which means that 15.1% of the total variability in employees’ performance is explained by the interaction term between the performance appraisal system and motivation as a moderator. Thus, this variation is good as 16.9% is not far off from 15.1%.

The second part of the table in Model 2 presents the F-test statistic and the regression significance estimate to test whether the overall regression model is a good fit for the data. Accordingly, the results show that the interaction variable statistically significantly predicts the dependent variable, F (3, 139) = 9.396, p (0.0000) < .05, which shows that the model fits the data well. That indicates a statistically significant impact of motivation as a moderator between the performance appraisal system and employees' performance.

Moreover, the third branch of the table in Model 2 represents the unstandardized Beta coefficient of the performance appraisal system and motivation as a moderator, which shows how much the dependent variable (employees’ performance) changes when the interaction term between PAS and M increases by one unit. Accordingly, the value of employee performance when the performance appraisal system is set to zero for the motivation variable is 3.177. The coefficient of PAS is 0.179, which means that the average value of employees’ performance increases by a value of 0.179 when PAS for motivation increases by one unit. The coefficient of motivation is 0.108, which means that the average value of employees’ performance increases by a value of 0.108 when motivation increases by one unit. But the most important here is the regression coefficient of the interaction effect between PAS and M is 0.067, which means that the average value of employees’ performance increases by a value of 0.067 when the interaction effect between PAS and M increases by one unit. Consequently, the estimated model coefficient is the regression equation,

Y = 3.177 + 0.179 PAS + 0.108 M + 0.67 M*PAS.

Furthermore, this section shows the t-test results associated with the p-value to test whether the individual independent variables have a significant relationship with the dependent variable. According to the results, motivation moderated a positive relationship between the performance appraisal system and employees’ performance. The t-test result was 2.014 for the independent variable (PAS), at the p-value of 0.046, which is less than 0.05 (at 96% significance level). Thus, the null hypothesis is rejected, and the alternative hypothesis is accepted. Besides, the moderation effect of the motivation as moderator occurs completely, as there are no significant values in β1 (0.067) and β2 (0.146), which were higher than the 0.05 alpha value.

4.8.2 Assumptions of Linear Regression Tests

4.8.2.1 Test for Autocorrelation

As evidenced in Table 4.14, the value of DW statistics is 1.771, which is between 1.5 and 2.5. Therefore, the value of DW is relatively normal and acceptable.

4.8.2.2 Multi-collinearity Test

Table 4.15: Multicollinearity Statistics Coefficientsa

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

As seen in the Table 4.15 above, there is no multicollinearity between all the variables: PAS, M, and INT, because the VIF values are less than 10. Thus, multicollinearity would not be a problem in the regression model or its reliability.

4.8.2.3 Test for Normality

For checking the normality assumptions of multiple regression models, it used a histogram to check the normality. If the histogram's bars are too high in the middle and pierce through the normal curve, the histogram is well covered by data and normally distributed. Thus, the residuals are normally distributed, as illustrated in Figure 4.3 below.

Figure 4.3: Histogram of Regression Standardized Residuals

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

Further, the normality test of residuals is conducted with a Q-Q plot. The residuals follow a normal distribution if the Q-Q plot forms a diagonal line around the zero. Thus, the data have a normal distribution, as illustrated in Figure 4.4 below.

Figure 4.4: Regression Standardized Residuals with a Q-Q Plot

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

4.9 Output of Hypotheses Testing

According to the overall results above, the output of hypotheses testing is shown in the table 4.16 below.

Table 4.16: Output of Hypotheses Testing

Abbildung in dieser Leseprobe nicht enthalten

Source: Survey Data (2023)

4.10 Chapter Summary

This chapter involved the analysis of the collected data from the survey to answer the five questions of the study objectives as mentioned above. The results of the correlation analysis showed a significant correlation between the independent variables—perceived fairness, perceived accuracy, and feedback quality—and the dependent variable, employee performance.

Moreover, a simple linear regression was conducted to examine variables and clarify the study questions. The first objective was to investigate the influence of the performance appraisal system on the employees' performance at the ICRC in Yemen through four questions. The first question was to examine the impact of the perceived fairness of the performance appraisal system on the employees’ performance. The result revealed that perceived fairness has a significant influence on employees' performance. The second question was to analyze the impact of the perceived accuracy of the performance appraisal system on the employees’ performance. The study found that perceived accuracy has a significant influence on employees' performance. The third question was to analyze the effect of the feedback quality of the performance appraisal system on the employees’ performance. The result also indicated that feedback quality has a significant influence on employees' performance.

The fourth question was to analyze the combined influence of the variables in the performance appraisal system on employees’ performance. Through the combined measurements of the variables using multiple regression analysis, the result revealed that perceived fairness and feedback quality don't have a significant impact on employees’ performance, whereas the perceived accuracy has a significant influence on employees' performance. The second objective of this study was to evaluate the influence of the performance appraisal system on employees’ performance through its relation to motivation as a moderating factor at the ICRC in Yemen. By conducting multiple regression analyzes, the findings revealed that motivation moderates the relationship between the performance appraisal system and employees’ performance.

CHAPTER FIVE DISCUSSION OF THE FINDINGS

5.1 Introduction

This chapter summarizes the findings of the study narratively. It responds to the five research questions to examine the impact of the appraisal system on employees' performance at the ICRC organization in Yemen. These results are presented according to the statistical analysis of the collected data presented and interpreted in the previous chapter.

5.2 The Impact of Perceived Fairness of the Performance Appraisal System on Employees’ Performance

The study found a significant relationship between the perceived fairness of performance appraisal and employee performance. The study also established that the perceived fairness of the appraisal system has a positive impact on the employees’ performance. The findings are in line with a study by Selvarajan and Cloninger (2012), which stated that perceived appraisal fairness is significantly related to the employees’ performance. Based on Tsai and Wang (2013), the perceived fairness of appraisal affects employees’ performance, behavior, and job satisfaction. Moreover, the findings are similar to the results of a study conducted by Warokka et al. (2012), which showed a significant relationship between the perceived fairness of performance appraisal and employees’ performance.

5.3 The Impact of Perceived Accuracy of the Performance Appraisal System on Employees’ Performance

According to the findings of the study, the perceived accuracy of performance appraisals has not only a significant relationship but also a positive impact on employee performance. These findings are parallel to the study conducted by Landy et al. (1987) that revealed a significant relationship between perceived accuracy and employees’ performance because the results of appraisal affect the attitude of the employees, which can lead to an increase or decrease in the performance of employees. They emphasized the role of the supervisor and his competency to implement the appraisal process carefully by devoting enough time to set clear goals and agree beforehand with subordinates on how to achieve these objectives successfully. Moreover, the findings are in line with the study conducted by Shaukat Malik and Aslam (2013), which pointed to the perceived accuracy of performance appraisal having a positive impact on the employees’ motivation to enhance their performance.

5.4 The Impact of Quality on the Performance Appraisal Feedback on Employees’ Performance

The study found a significant positive relationship between the quality of performance appraisal feedback and employees’ performance. The study also discovered that the quality of performance appraisal feedback has a positive effect on employee performance. These findings are supported by Girma et al. (2016), whose study revealed a positive and significant impact between the quality of appraisal feedback and employees’ performance. They showed that discussing the appraisal result and giving feedback can lead to effectively improving the employees’ performance. Moreover, these findings are in line with the findings of Mishra (2017), who found that appraisal feedback has a positive impact on employees' performance. Their study emphasized the significance of feedback that leads to positive behavioral changes in employee work performance, self-awareness, interpersonal skills, and leadership skills.

5.5 The Overall Impact of Performance Appraisal System Variables on Employees’ Performance

The study found a statistically significant impact of the variables in the performance appraisal system on employee performance when combining the other variables as one group. The results of the regression model showed a statistically significant impact of the performance appraisal system constructs on employee performance. However, the study established that the perceived fairness of the appraisal system and the appraisal feedback have a non-significant relationship with employee performance. While the perceived accuracy of the performance appraisal system has a positive impact and a significant relationship with employee performance. This implies that accuracy is the more powerful variable, having a greater impact and a positive relationship with employee performance than the other variables (perceived appraisal fairness and quality of appraisal feedback). As a result, the findings revealed that perceived fairness and feedback quality have no significant effects on employee performance. However, perceived accuracy has a stronger effect and a positive relationship with employee performance than other variables. According to the findings of the current support by Ullah et al. (2021), the perceived accuracy of the performance appraisal system has a significant impact on the employees' productivity. Their result showed that the accuracy of the performance appraisal system is affected by the rater's competence and the possibility of challenging performance appraisal results as inaccurate. They stated that clear communication of standards and the reaction to the last assessment results affect the employees’ perception of the accuracy of the performance appraisal, whether positively or negatively.

5.6 The Impact of Motivation as a Moderator Between the Performance Appraisal System and Employee’s Performance

The study established that motivation moderated a positive relationship between the performance appraisal system and employees’ performance. The study also discovered that motivation has a significant and positive relationship with the performance appraisal system and employee performance. These findings have been supported by Kuvaas (2006), who found a significant impact of motivation as a moderator between performance appraisal satisfaction and employee productivity. His results revealed that moderation has a positive relationship with those with high intrinsic motivation and a negative relationship with employees with low intrinsic motivation. Moreover, the findings are consistent with the study conducted by Iqbal, N. et al. (2013), who found that motivation moderates a significant relationship between performance appraisal and employees’ performance. According to a study conducted by Surajiyo et al. (2021), motivation moderates a significant relationship between work discipline and employees’ performance. Their study stated that the high motivation of employees for work discipline has a significant impact on employees' performance in a positive way.

CHAPTER SIX CONCLUSION AND RECOMMENDATIONS

6.1 Introduction

This final chapter summarizes the overall findings in response to the research questions and highlights the gained insights. It also provides recommendations based on the overall finding of the study. Further, this chapter has outlined suggestions for further research and limitations.

6.2 Conclusion

The study aimed to examine the impact of the appraisal system on employees' performance at the ICRC organization in Yemen. According to the overall findings, it was revealed that there is a correlation between the performance appraisal system and employees' performances at the ICRC in Yemen.

Based on the results of the first question, the study found a positive impact and a significant relationship between the perceived fairness of performance appraisal and employee performance. It also showed that respondents agreed with the statements, which are relevant to the perceived fairness of the performance appraisal system. However, most of them did not agree that managers consider work stresses and strains during the evaluation. According to the results of the second question, the study established that the perceived accuracy of performance appraisal had not only a significant positive relationship with employee performance but also a positive impact on employee performance. It also revealed that respondents somewhat agreed with the statements related to the accuracy of the performance appraisal system. Nevertheless, most of them showed that the change of line manager during the year would affect the accuracy of the performance appraisal.

Moreover, the results of the third question revealed a positive relationship between employee performance and the quality of appraisal feedback. Additionally, it revealed that respondents somewhat agreed with all the statements related to the quality of performance appraisal feedback. The majority of them, however, somewhat agreed that performance appraisal results differ from year to year depending on their level of performance. Furthermore, in the multiple regression, the study found a significant positive relationship between performance appraisal system variables and employees' performance when combined with the other variables as one group. The study established that the perceived fairness and the appraisal feedback did not significantly influence the employees’ performance. However, perceived accuracy had a significant impact on employee performance when combined with two other variables: perceived appraisal fairness and the quality of appraisal feedback.

Regarding the moderated variable of the last question, the results found that motivation moderated the relationship between the performance appraisal system and employees’ performance positively. Further, the study revealed that motivation significantly influenced the relationship between the performance appraisal system and employees' performance. On the other hand, the study revealed that most were somewhat satisfied with the statements related to motivation as a moderator variable (M) between the appraisal system and employees’ performance. They are slightly content with the statement, "the performance appraisal identifies the needed training for improving my performance through appraisal feedback ". Thus, all these results should take into account to make the performance appraisal system more effective for enhancing the level of employees' performance.

6.3 Recommendations

Based on the overall results, the study recommends that ICRC Yemen Mission HR Professionals and line managers in all humanitarian organizations enhance their employees' motivation to increase their productivity and efficiency through the professional application of a well-defined performance appraisal system. Considering the effects of such performance appraisal systems on the employees, promoting interactive communication with the employees, providing needed training, and enhancing the leadership skills of line managers are recommended.

Firstly, ICRC HR Professionals need to develop a well-defined performance appraisal system which clearly identifies the three core constructs: (fairness perception, perception of accuracy, and quality of appraisal feedback) that ensure the effectiveness of the system and will in turn motivate employees for performance improvement and seeking to achieve the organization overall goals.

Secondly, the findings revealed that the performance appraisal system had a significant effect on employees’ performance. It also showed that the performance appraisal system is a central factor in employees' motivation for effective performance. Thus, HR Professionals should conduct more studies and use better techniques for improving their performance appraisal system, as it can help both employees and managers achieve the best-desired outcomes. Further, HR Professionals should provide more training, seminars or workshops for the members of the HR department, especially on how to support, monitor, and direct both employees and line managers to make all the procedures and processes of the performance appraisal system apply efficiently and effectively.

Thirdly, HR Professionals should pay more attention to enhancing and maintaining the fairness and accuracy of the performance appraisal system, encouraging effective feedback, and promoting more communication between employees and line managers to increase employee motivation and the potential for employee professional growth.

Moreover, supporting and inspiring the line managers to use a performance appraisal system for promoting and motivating their employees for better performance. The line manager can improve their employees through effective communication, reasonable and timely feedback, and providing needed training according to their skill shortages and weaknesses. Line managers should also consider all the work stresses, strains, difficulties, and challenges of their subordinates during the evaluation process.

Furthermore, HR Professionals should provide much concentrating on the fairness and accuracy of the performance appraisal approach, which mainly depends on the supervisor's leadership abilities, maturity, and experience. Line managers can learn about the psychology of human behaviour by studying people's reactions.

Besides, line managers should have skills and talents such as care, listening, directing, empathy, and influencing, having self-awareness skills, as they need to be able to identify what motivates each member of the team, how to guide and develop them, and how to calm down team disagreements. Thus, it is very essential to provide training, seminars or workshops for line managers to increase their common understanding of the appraisal system and to motivate and maintain a good relationship with their subordinates.

Finally, HR Professionals should reconsider how to solve the evaluation issues the employees face in the case of changing their line managers during the year, especially the employees under the supervision of expatriates with short missions. Likewise, HR Professionals should focus more on the appeals process and make employees aware of it when they are dissatisfied with the performance evaluation. Additionally, allowing employees to communicate freely about their feelings and achievements in their evaluation issues, as well as giving them a chance to express their opinions of the performance appraisal system within the organization through providing annual related surveys.

6.4 Limitations of the Study

The study has several limitations. Firstly, the study aims to examine the impact of the performance appraisal system as an independent variable under three performance appraisal constructs along with one moderated variable, as mentioned above. The study was also limited to one dependent variable, employees' performances, which are related to individual objectives and organizational goals. Thus, these variables cannot be generalized to all variables of the performance appraisal system and employees’ performance at the ICRC in Yemen. Secondly, the research was carried out at the ICRC in Yemen among 217 employees working at the ICRC in Yemen. As this study was conducted in Yemen, it cannot be generalized to other countries as each country has its own context. Finally, the study was limited to a quantitatively designed questionnaire that contains closed-ended questions on five Likert scales.

6.5 Suggestions for Further Research

This study has examined the perceptions of employees toward the performance appraisal system at the ICRC in Yemen. Therefore, the same research should be carried out within other humanitarian organizations in the context of Yemen to find out if the same findings would be obtained.

REFERENCES

Abbas, M. Z. (2014). Effectiveness of performance appraisal on performance of employees. IOSR Journal of Business and Management, 16(6), pp. 173-178.

Abdulkadir, D. S. & Isiaka , B. S. (2012). Effects of Strategic Performance Appraisal, Career Planning and Employee Participation on Organizational Commitment: An Empirical study. Department of Business Administration, University of Ilorin, Ilorin, Nigeria. DOI:10.5539/ibr.v5n4p124.

Adams, J. (1965). Inequity in Social Exchange. Advances in Experimental Social Psychology, 12(4), pp. 267-299.

Aguinis, H., (2009). Performance Management. Prentice Hall/Pearson Education. 2th ed. Upper Saddle River, London.

Aiken, H. D., 1965. The Age of Ideology the Nineteenth Century Philosophers. 2th ed. New York: New American Library.

Al-Habsi, N. & Madbouly, A., (2021). The Effect of Performance Appraisal Systems on Employees and Organizations in Omani Private and Governmental Institutions. Journal of Finance, Business and Management Studies, 1(1), pp. 31-42.

Andersson, U., Cuervo-Cazurra, A. & Nielsen, B., ( 2014). From the Editors: Explaining Explaining interaction effects within and across levels of analysis. Journal of International Business Studies, 45(9), pp. 1063-1071.

Bies, R., (2001). International (in)justice: The sacred and the profane. In: J. G. &. R. Cropanzano, (Eds.). Advances in organization justice. Stanford: Stanford University Press, p. 89–118.

Bies, R. J. & Moag, J. S., (1986). Interactional justice: communication criteria of fairness. Research on Nego- tiation in Organizations, Volume 1, p. 43–55.

Borg, W. R. & Gall, M. D., (1989). Educational research: an introduction. 5th ed. New York : Longman.

Brett, J. F. & Atwater, . L. E., (2001). 360-degree feedback: Accuracy, reactions, and perceptions of usefulness. Journal of Applied Psychology, Volume 86, p. 930–942.

Bretz, R., Milkovich, G. T. & Read, W., (1992). The Current State of Performance Appraisal Research and Practice: Concerns, Directions, and Implications. Journal Of Management, 18(2), pp. 321-352.

Brown, M. & John , S., (2005). Performance appraisal systems: determinants and change. British Journal of Industrial Relations, 43(4), pp. 659-679.

Bryman, A., (2012). Social Research Methods. 5th ed. Oxford: Oxford University Press.

Carrell, M. R. & Dittrich, J. E., (1978). Equity theory: The recent literature, methodological considerations, and new directions. Academy of Management Review, 3(2), p. 202–210.

Casteel, A. & Bridier, N. L., (2021). Describing populations and samples in doctoral student research. International Journal of Doctoral Studies, Volume 16, pp. 339-362. https://doi.org/10.28945/4766.

Castille, A.-m. R., (2018). A Model of the Relationship Between Performance Feedback and Goal Setting : A Consideration of , Affective Cognitive , and Psychological State Effects. Doctoral Dissertations by an authorized administrator of Louisiana Tech Digital Commons, p. https://digitalcommons.latech.edu/dissertations/32.

Clarke, N., Alshenalf, N. & Garavan, T., (2019). Upward influence tactics and their effects on job performance ratings and flexible working arrangements: The mediating roles of mutual recognition respect and mutual appraisal respect. Human Resource Managemen. Doi : 10.1002/hrm.21967.

Cohen, J., Cohen, . P., West, S. G. & Aiken, . L. S., (2003). Applied multiple regression/correlation analysis for the behavioral sciences. 3th ed. Washington: Lawrence Erlbaum Associates Publishers.

Colquitt, a. A., Conlon, D. E., Wesson, M. J. & Porter, C., (2001). Justice at the Millennium: A Meta-Analytic Review of 25 Years of Organizational Justice Research. Journal of Applied Psychology, 86(3), pp. 425-45. DOI:10.1037//0021-9010.86.3.425.

Cronbach, L. J., (1951). Coefficient alpha and the internal structure of tests. Psychometrika, Volume 16, p. 297–334.

Cropanzano, R., Rupp, E. D. & Byrne, Z. S., (2003). The relationship of emotional exhaustion to work attitudes, job performance, and organizational citizenship behaviors. Journal of Applied Psychology, 88(1), p. 160–169.

DeNisi, A. S. & Pritchard, R. D., (2006). Performance appraisal, performance management and improving individual performance: A motivational framework. Management. Management and Organization Review, 2(2), pp. 253-277.

Denscombe, M., (2002). Ground Rules for Good Research: A 10 Point Guide for Social Researchers. Buckingham [England], Open University: Open University Press.

Dijk, D. V., (1915). Performance Appraisal and Evaluation. International Encyclopedia of the Social & Behavioral, 17(2), p. 716–721.

Dudovskiy, J., (2018). The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance.

Easterby-Smith, M., Thorpe , R., Jackson, P. & Lowe , A., (2008). Management Research. 3th ed. London: Sage Publications.

Erdogan, B., (2002). Antecedents and consequences of justice perceptions in performance appraisals. Human Resource Management Review, 12(4), pp. 555-578.

Fudge, R. S. & Schlacter, J. L., (1999). Motivating employees to act ethically: An expectancy theory approach. Journal of Business Ethics, 18(3), p. 295–304.

George, D. & Mallery, P., (2003). SPSS for Windows step by step: A simple guide and reference. 4th ed. Bosten: Allyn & Bacon.

Girma, T., Lodesso, S. L. & Sorsa , G., (2016). The effect of performance appraisal on employee performance: a survey on administrative staff of Hawassa Univesity. IOSR journal of business and management, 18(3), pp. 36-44.

Goundar, S., (2012). Chapter 3: Research Methodology and Research Method. Research Gate Publications. pp. 1-47.

Greenberg, J., (1986). Determinants of Perceived Fairness of Performance Evaluations. Journal of Applied Psychology, 71(2), pp. 340-342.

Grunkemeier, G. L., Wu, Y. & Furnary, A. P., (2009). The Statistician ’ s Page What is the Value of a p Value ?. The Society of Thoracic Surgeons, 87(5), pp. 1337-1343.

Hair, J. F. et al., (2006). Multivariate Data Analysis. 6th ed. Harlow: Pearson Education.

Henseler, J., Ringle, C. M. & Sarstedt, M., (2015). A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43(1), pp. 115-135. DOI:10.1007/s11747-014-0403-8.

Horsoo, S. K., (2009). Employee performance appraisal, rewards & recognitions – a case study of Barclays Bank of Ghana Limited.

Hulland, J., (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies. Strategic Management Journal, 20(2), pp. 195-204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7.

ICRC, (2011). ICRC: The ICRC in Yemen: historical overview, 1962-2010. [Online] Available at: https://www.icrc.org/en/doc/resources/documents/feature/2011/yemen-history-2011-08-10.htm [Accessed 15 June 2022].

ICRC, (2020). ICRC Yemen Annual Activity Report 2020. [Online] Available at: https://www.icrc.org/en/document/icrc-yemen-annual-activity-report-2020 [Accessed 02 June 2022].

ICRC, (2022). ICRC: Who we are?. [Online] Availableat: https://www.icrc.org/en/who-we-are [Accessed 14 June 2022].

Ilgen, D. & Feldman, J., (1983). Performance appraisal: a process focus’. Research in Organizational Behavior, Volume 55, p. 141–197.

Ilgen, D. R., Fisher, C. D. & Susan, M., (2014). Consequences of individual feedback on behavior in organizations. Journal of Applied Psychology, 2(2), pp. 21-28.

Ilies, R. & Judge, T. A., (2005). Goal regulation across time: The effects of feedback and affect. Journal of Applied Psychology, 90(3), pp. 453-467.

Iqbal, N. et al., (2013). Impact of performance appraisal on employee ’ s performance involvingthe Moderating Role of Motivation. Arabian Journal of Business and Management Review (OMAN Chapter), 3(1), pp. 37-56.

Jacobs, R., Kafry, D. & Zedecj, S., (1980). Expectations of behaviorally anchored scales. Personnel Psychology, 33(3), p. 595–640.

Jones, G. & George, J., (2009). Contemporary Management. 6th ed. New York, NY: McGraw-Hill International .

Kamau, J. G., (2012). Implementation of quality management strategies in HIV/AIDS cd4 testing laboratories in Nairobi, Kenya. Doctoral dissertation, School of Business, University of Nairobi.

Karen K. Myers, K. & Sadaghiani, . K., (2010). Millennials in the Workplace: A Communication Perspective on Millennials’ Organizational Relationships and Performance. Journal of Business and Psychology, 25(2), p. 225–238.

Khoury, G. & Analoui, F., (2004). Innovative management model for performance appraisal: The case of Palestinian public universities. Management Research News, 27(2), pp. 56-73.

Kim, T. & Holzer, M., (2014). Public Employees and Performance Appraisal: A Study of Antecedents to Employees’ Perception of the Process. Review of Public Personnel Administration. Sage Journals, 36(1), pp. 31-56.

King, P. S., (2013). Moderators/Moderating Factors. New York, NY: Springer. DOI: https://doi.org/10.1007/978-1-4419-1005-9_971

Kothari, C., (2004). Research Methodology: Methods and Techniques. 2th ed. New Delhi: New Age International Pvt Publishers.

Kuvaas, B., (2006). Performance appraisal satisfaction and employee outcomes: Mediating and moderating roles of work motivation. International Journal of Human Resource Management, 17(3), pp. 504-522.

Landy, F. J., Barnes, J. L. & Murphy, K. R., (1987). Correlates of perceived fairness and accuracy of performance evaluation. Journal of Applied Psychology, 63(6), pp. 751-754.

Lawler, E. E., (1967). The multitrait-multirater approach to measuring managerial job performance. Journal of Applied Psychology, Volume 51, p. 369–381.

Levinson, H., (1976). Appraisal of What Performance? Employee Performance Management : Harvard Business Review Magazine. [Online] Available at: https://hbr.org/1976/07/appraisal-of-what-performance [Accessed 13 June 2022].

Levy, P. E. & Williams, J. R., (2004). The social context of performance appraisal: A review and framework for the future. Journal of Management, 30(6), pp. 881-905.

Lewis-Beck, M. S., (1995). Data Analysis : An Introduction Sage University. New York: Sage Publications, Inc.

Mariti, E. W., (2019). Effects of performance appraisal systems on employee performance of multinational companies in Nairobi County. Master Thesis, Strathmore University. [Online] Availableat:https://su-plus.strathmore.edu/handle/11071/6611 [Accessed 27 June 2022].

Masterson, S. S., Lewis, K., Goldman, B. M. & Taylor , M. S., (2000). Integrating justice and social exchange: The differing effects of fair procedures and treatment on work relationships. Academy of Management Journal, 34(4), p. 738–748.

Mathis, R. & Jackson, J., (2010). Human Resource Management. 13th ed. Ohio: South-Western College Publishing.

Mayer, R. C. & Davis, J. H., (1999). The effect of the performance appraisal system on trust for management: A field quasi-experiment.. Journal of Applied Psychology, 84(1), pp. 123-136.

Memon, M. A., Hwa, C. J., Ramayah, T. & Ting, H., (2019). Moderation Analysis: Issues and Guidelines. Journal of Applied Structural Equation Modeling, 3(1), pp. i-xi.

Mercer, (2002). Effective Performance Management Practices. Mercer Human Resource Consulting, p. New York.

Mishra, G., (2017). Role of Perceived Accuracy and Organisation Support on the Perceptions of Behavior Change of Indian it Professionals in Context of Multi-Source Feedback. International Journal of Applied Business and Economic Research, Volume 15, pp. 1-14.

Morgan, D. W. & Krejcie, V. R., (1970). Table for determining sample size from a given population. Educational and Psychological Measurement. Educational and Psychological Measurement, 30(3), pp. 607-610.

Morgan, R., (2006). Making the Most of Performance Management Systems,‟ Compensation and Benefits Review. Volume 38, p. 22–27. Doi: 10.1177/0886368706290001.

Murphy, K. R. & Cleveland, J., (1991). Performance appraisal: An organizational perspective, MA: Allyn & Bacon.

Murphy, K. R. & Cleveland, J., (1995). Understanding performance appraisal : social, organizational, and goal-based perspectives. Thousand Oaks, Calif: SAGE Publications, Inc.

Nathan, B. R., Mohrman, A. M., Jr. & Milliman, J., (1991). Interpersonal relations as a context for the effects of appraisal interviews on performance and satisfaction: A longitudinal study. Academy of Management Journal, 34(2), pp. 352-369.

Neuman, W., (2005). Social Research Methods. 6th ed. London: Peason.

OCHA, (2022). OCHA: Yemen Humanitarian Needs Overview (2022). [Online] Available at: https://reliefweb.int/report/yemen/yemen-humanitarian-needs-overview-2022-april-2022 [Accessed 04 June 2022].

Peters, T. J. & Waterman, R. H., 2004. In Search of Excellence: Lessons From America's Best-Run Companies. London: Harper and Row.

Porter, L. W. & Lawler, E. E., (1968). What Job Attitudes Tell about Motivation. United States: Harvard Business Re view Reprint Service.

Rahahleh, A. H., Alabaddi, A. Z. & Moflih, M. A., (2019). The Impact of Performance Appraisal on Employee Performance in Banks Operating in the South of Jordan. International Journal of Human Resource Studies, 9(4), pp. 77-94.

Robbins, S. P., (1993). Organizational Behavior: Concepts, Controversies, and Applications. 6th ed. Capital Cities: ABC Video Enterprises,.

Roberson, Q. M. & Stewart, M. M., (2006). Understanding the Motivational Effects of Procedural and Informational Justice in Feedback Processes. British Journal of Psychology, Volume 97, pp. 281-98. Doi: 10.1348/000712605X80146.

Robson, C., (2002). Real World Research: A Resource for Social Scientists and Practitioner-Researchers. 2th ed. Oxford: Blackwell Publishers Ltd.

Roscoe, J. T., (1975). Fundamental research statistics for the behavioral sciences. 2th ed. New York: Holt, Rinehart and Winston.

Rotundo, M. & Sackett, P. R., (2002). While the employee performance refers to a set of tasks the employee should understand and achieve them according to the updated job description to meet the organizational expectations.. The Journal of applied psychology, 87(1), pp. 66-80.

Salaman, G., Storey, J. & Billsberry, J., (2005). Strategic human resource management: Theory and practice. 2th ed. SAGE Publications Ltd.

Sanyal, M. K., Biswas, S. B. & Ghosh , R., (2017). Implication of Performance Appraisal process on Employee Engagement Mediated Through the Development and Innovation Oriented Culture. A Study on the Software Professionals of IT Companies in West Bengal. In Proceedings of the First International Conference on Intelligent Computing and Communication, Volume 458, pp. 277-294. Springer, Singapore.

SAP, (2019). SAP News: International Committee of the Red Cross Adopts SAP SuccessFactors Solutions to Support Humanitarian Efforts. [Online] Available at: https://news.sap.com/2019/08/icrc-adopts-sap-successfactors/ [Accessed 10 June 2022].

Saunders, M., Lewis , P. & Thornhill, A., (2009). Research methods for business students. 5th ed. Essex, England: Pearson Education Limited.

Schindler, P. S. & Cooper, D. R., (2006). usiness Research Methods. 9th ed. Pennsylvania State University: McGraw-Hill Irwin.

Selvarajan, R. & Cloninger, P. A., (2009). The influence of job performance outcomes on ethical assessments. Personnel Review, 4(38), pp. 398-412.

Selvarajan, T. T. & Cloninger, P. A., (2012). Can performance appraisals motivate employees to improve performance? A Mexican study. International Journal of Human Resource Management, 23(15), pp. 3063-3084.

Shaukat Malik, M. & Aslam, S., (2013). Performance Appraisal and Employee's Motivation: A Comparative Analysis of Telecom Industry of Pakistan. Pakistan Journal of Social Sciences (PJSS), 33(1), pp. 179-189.

Smither, J. W. & London, M., (2009). Performance Management. Putting Research into Action (Eds.). San Francisco : Jossey-Bass.

Stone, R., Cox, A. & Gavin, M., (2008). Human Resource Management. 10th ed. London: Wiley.

Sudin, S., 2011. Fairness of and satisfaction with performance appraisal process. Journal of Global Management, Volume 2, pp. 66-83.

Surajiyo, Suwarno, Kesuma, I. M. & Gustiherawati, T., (2021). The Effect of Work Discipline on Employees Performance with Motivation as a Moderating Variables in the Inspectorate Office of Musi Rawas District. International Journal of Community Service & Engagement, 2(1), pp. 1-12.

Tahar-Kedem, E., (2014). Is motivation essential for creating new lifestyles: Management intervention model for female immigrants from developing countries. Review of International Comparative Management, 15(1), pp. 16-30.

Taylor, M. S. et al., (1995). Due Process in Performance Appraisal: A Quasi-Experiment in Procedural Justice. Administrative Science Quarterly, 40(3), p. 495–523.

Tiwari, R., (2020). Relationship between Performance Appraisal and Employee Performance : A Study. IOSR Journal of Business and Management (IOSR-JBM), 22(12), pp. 57-61.

Tsai, C.-J. & Wang, W.-L., (2013). Exploring the factors associated with employees' perceived appraisal accuracy: A study of Chinese state-owned enterprises. International Journal of Human Resource Management, 24(11), pp. 2197-2220.

Ugoani, J. N. N., (2020). Performance Appraisal and its Effect on Employees ’ Productivity in Charitable Organizations. Academic Research Publishing Group, 6(12), pp. 166-175. DOI: doi.org/10.32861/bmer.612.166.175.

Ullah, Z. et al., (2021). Perceived accuracy of electronic performance appraisal systems: The case of a non‐for‐profit organization from an emerging economy. Sustainability (Switzerland), 13(4), pp. 1-16.

Underwood, R., Kumari, V. & Peters, E., (2016). Cognitive and neural models of threat appraisal in psychosis: A theoretical integration. Psychiatry Research, Volume 239, pp. 131-138. DOI: 10.1016/j.psychres.2016.03.016.

Vaus, D. d., (2002). Surveys in Social Research. 5th ed. Australia :Allen & Unwin.

Vroom, V. H., (1964). Work and motivation. Newyork: Wiley, NY.

Wagschal, U. & Mooi, . E., (2014). Chapter 7: Regression analysis. In: A Concise Guide to Market Research. The Process, Data, and Methods Using IBM SPSS Statistics -. Verlag Berlin Heidelberg: Springer Texts in Business and Economics,, pp. 139-233.

Warokka, A., Gallato, . C. G. & Moorthy, T., (2012). Does organizational justice in performance appraisal system affect work performance? Evidence from an emerging market. Journal of Human Resources Management Research, Volume 4, pp. 2292-2308.

Weiss, H. M. & Suckow, K., (1999). Effects of justice conditions on discrete emotions. Journal of Applied Psychology, 84(5), p. 786–794.

Wood, R. E. & Marshall, V., (2008). Accuracy and effectiveness in appraisal outcomes: The influence of self- efficacy, personal factors and organisational variables. Human Resource Management Journal ·, 18(3), pp. 295-313.

Wright, R., (2004). Mapping cognitions to better understand attitudinal and behavioral responses in appraisal research. Journal of Organizational Behavior, 25(3), pp. 339-374.

APPENDICES

APPENDIX A: LETTER OF INTRODUCTION

Welcome to My Survey

Dear Colleagues,

I am your fellow colleague Ali Al Ghail, and I am a master’s degree student at Uniathena and GMU - Guglielmo Marconi University, Italy.

I am humbly requesting your valuable support with this questionnaire, which is part of a research project for my master’s degree in International Business Administration (IMBA). The research study is entitled ‘‘ The Impact of Appraisal System on Employees’ Performance: The Case Study of The International Committee of the Red Cross (ICRC) in Yemen”. The title of this research was chosen to study and examine how employees view the appraisal system and its impact on their performances.

Therefore, I am writing to you seeking your kind support in filling out the below questionnaire to the best of your knowledge and experience, bearing in mind that all questionnaires would be anonymous.

The questionnaire contains six sections and would only take ten minutes to complete. Any information obtained for this purpose will be kept confidential and only be used for academic purposes. Thank you in advance for your precious time and looking forward to your feedback.

Yours Faithfully,

Ali Al Ghail

APPENDIX B: QUESTIONNAIRES OF THE STUDY

Section One: Demographic Profile

Kindly indicate to the below questions:

Abbildung in dieser Leseprobe nicht enthalten

Section Two: The Fairness of the Performance Appraisal System

Please indicate your opinion on the following statements on performance appraisal fairness at ICRC Organization.

Abbildung in dieser Leseprobe nicht enthalten

Section Three: The Accuracy of the Performance Appraisal System

Please indicate your opinion on the following statements on performance appraisal accuracy at ICRC Organization.

Abbildung in dieser Leseprobe nicht enthalten

Section Four: The Performance Appraisal Feedback

Please indicate your opinion on the following statements on the performance appraisal feedback quality at ICRC Organization.

Abbildung in dieser Leseprobe nicht enthalten

Section Five: Motivation as a Moderator Between Performance Appraisal System and Employees' Performance

Please indicate your opinion on the following statements on the motivation as a moderator between performance appraisal system and employees' performance at ICRC Organization.

Abbildung in dieser Leseprobe nicht enthalten

Section Six: The Employee Performance

Please indicate your opinion on the following statements on the employee performance at ICRC Organization.

Abbildung in dieser Leseprobe nicht enthalten

Thank you for completing this survey!

[...]