Factors Influencing Performance Appraisal Effectiveness in ODL Institutions

Performance appraisal is essential, unavoidable, and universal, particularly in organisations where individuals tend to evaluate the work performance of others. The purpose of this study is to assess employee’s feedback towards performance appraisal exercises in the ODL institutions, Malaysia. Included in this study are one dependent variable (performance appraisal) and three independent variables (motivation, job satisfaction and engagement). The quantitative approach of analysis using data gathered by questionnaire distribution among samples was used in this study. This study assesses the direct relationship between motivation, job satisfaction, engagement and performance appraisal. In this study, primary data will be employed, and a survey questionnaire that had been adopted and modified from earlier studies is used to gather the data. SPSS 22.0 and Smartpls version 4 software were used for the direct and indirect links and testing of model hypotheses. Structural equation modeling, known for its ability to analyze complex interactions between variables, was used to analyze a comprehensive data set of 241 responses, and convergent and discriminant validity was confirmed. Evaluation of the structural model crucially confirmed the hypotheses and revealed three direct relationships and all these hypotheses were supported. These results highlight the profound importance of these factors in shaping performance appraisal and facilitating the effective appraisal system into ODL institutions. In addition to the empirical findings, this study contains very important theoretical implications, highlighting the central role that motivation, job satisfaction and engagement in influencing performance


Introduction
Performance management (PM) can be referred to as a process for an organisation to ensure the performance of employees based on works assigned to them are conducted in-line with organisational objectives (Al-Jedaia & Mehrez, 2020).In any organisation, employees or human capital is of great importance for an organisation to fully achieve organisational objectives or goals (Bušatlić & Musić-Kilic, 2018).Employees are the only resource of an organisation that has ratios, feelings and intentions that affect organisations' efforts in achieving those goals, due to the role of employees as the driving force of all the resources owned by the organisation.To measure organisational performance, performance appraisal (PA) is a method to understand the situation, because the performance management process requires a meaningful insight on what are the activities and outputs planned by the organisations are achieved or otherwise, and feedback needs to be provided to help employees meet the expectations (Lin & Kellough, 2019).According to Al-Jedaia and Mehrez (2020), PA is a regular and systematic process to evaluate employee's performance.It is a formal procedure to assess or evaluate employees' strengths and weaknesses.The essential purpose of PA is to help managements make right decisions on salaries, promotions, training and to encourage employees through positive feedback (Ameen & Baharom, 2019;Idowu, 2017).One of the most important roles of management is to carefully identify and select the relevant performance criteria that lead to achieve organisational goals and objectives.Rusu et al. (2016) believe that key performance indicators (KPI) which are directly related to a specific job should be applied.In addition, Sanyal et al. (2017) argue that for valid performance criteria, KPI should relate to the organisation environment and goals, be clear, measurable and realistic.
Employee performance and job satisfaction are directly influenced by the performance evaluation method used (Chandhana & Easow, 2015).Less than 6% of employees think their evaluations are effective, which is not enough to boost job satisfaction (Teckchandani & Pichler, 2015).The evaluation system continues to be viewed as unfair, inaccurate, and a yearly ritual by most employees (Sanyal et al., 2017).As a result, studies are needed to investigate how staff view performance evaluations and how that influences their level of job satisfaction.

Research Objectives
This research is conducted to achieve the following objectives: • To determine the relationship between motivation and performance appraisal • To determine the relationship between satisfaction and performance appraisal.
• To determine the relationship between engagement and performance appraisal

Research Questions
Based on the above problem statement below are the research questions are: • What is the relationship between between motivation and performance appraisal?
• What is the relationship between satisfaction and performance appraisal?
• What is the relationship between engagement and performance appraisal

Relationship between motivation, satisfaction, engagement & performance appraisal
According to Amirullah (2015) motivation means giving it, the emergence of motivations or things that cause impetus or circumstances that cause impetus.In addition, she pointed out that motivation can also be said as energy to generate impulses within (drive arousal).
Motivation is considered as a condition or energy that drives employees who are directed or directed to achieve the objectives of the company's organisation.Another study conducted by Salbiyah et al (2019) on the effect of work motivation on the performance of female lecturers at University of Muhammadiyah Surabaya (UMSurabaya) showed that work motivation significantly affected the performance of female lecturers at UMSurabaya.Job satisfaction is defined as the degree to which an employee likes their job or dislikes it (Mahmoud et al., 2020).Based on a study conducted by Mahmoud et al (2020), job satisfaction significantly and fully mediates the relationship between employees' attitudes towards performance appraisal system and trust.
Based on research conducted by Ajibola et al (2019), the results showed a positive and significant relationship between performance appraisal and employee engagement among employees of oil and gas, wire industries, and tertiary institutions in South-West Nigeria.This is further supported by the findings of Jani and Balyan (2016) who found out that there was a positive significant relationship between performance appraisal and employee engagement.
Therefore, the following hypotheses were proposed H1: There is a relationship between motivation and performance appraisal H2: There is a relationship between satisfaction and performance appraisal H3: There is a relationship between engagement and performance appraisal

Methodology
This study sought to assess academics and non-academics in ODL institutions.To achieve this objective, researchers conducted a survey to collect primary data, meticulously examining previous research to select reliable and valid measurements.The survey questionnaires were then emailed to selected participants, utilizing purposive sampling due to the unavailability of a comprehensive population list.A total of 26 variables were scrutinized, including exogenous variables such as motivation, gauged using a 4-item scale (Hair et al., 2019); satisfaction, assessed with 4 items (Lin et al., 2020); engagement evaluated through 4 items from Jasielska et al ( 2021); while the dependent variable was performance appraisal, appraised via 4 items (De Cannière et al., 2009).A Likert scale featuring four response choices, ranging from strongly disagree to strongly agree, was employed to gauge elements within each construct.Out of 350 surveys disseminated, 266 were collected, resulting in a response rate of 76%, considered satisfactory for employing structural equation modeling (SEM) in data analysis.Of the collected surveys, 241 were identified as clean and suitable for analysis.For data analysis and hypothesis testing, researchers selected the Smartpls4 software, known for its use of structural equation modeling (SEM) techniques.This choice was driven by the software's robust assessment capabilities and proficiency in handling multivariate data analysis, aligning seamlessly with the study's objectives and adhering to the guidelines outlined by (Ringle et al., 2022).Smartpls4 proved indispensable in effectively scrutinizing proposed hypotheses and conducting comprehensive multivariate data analysis, facilitating a thorough examination of both measurement and structural models.

Respondents' Profile
The gender distribution among respondents indicates a notable majority of females, constituting 56% of the sample, while males account for 44%.This gender representation reflects potential disparities in the participation of male and female respondents, prompting further exploration into gender dynamics within the study.The highest percentage falls within the 36 to 45-year-old category (47%), suggesting a substantial representation of mid-career professionals.The inclusion of participants across various age brackets, including those under 36 and over 46 years old, contributes to a comprehensive participant across different career stages.
The data on years of service illustrate a varied level of experience among respondents.A substantial portion, 63%, has served between more than 10 years, indicating a cohort with vast experience.
The majority of respondents hold the position of executive (44%) with a minimal representation of Associate Professor & Professor of 3.3%.This distribution highlights the seniority and diversity in the hierarchy among the participants.
The categorization based on the job category reveals a high participation from non-academics constitute 78%, while those from academics represent 22%.
The respondents overwhelmingly express a positive stance toward recommending technology adoption, with 95.9% endorsing it, while 4.1% indicate otherwise.This high recommendation rate suggests a general positive disposition among the surveyed academicians toward adopting technological advancements in their academic practices.

Data Analysis Measurement Model
This study employed the measurement evaluation technique proposed by Hair et al. (2017) to assess both first-order and second-order measurements.The primary objective was to identify items with loadings below the 0.7 threshold.
The examination of construct reliability and validity indicated that all constructs exhibited Average Variance Extracted (AVE) values exceeding 0.5, ranging from 0.705 to 0.797 (refer to Table 1), demonstrating the establishment of convergent validity (Hair et al., 2017).Additionally, composite reliability for all constructs surpassed 0.7, ranging from 0.905 to 0.959, and Cronbach's alpha values were greater than 0.7, ranging from 0.865 to 0.950 (see Table 1).To ascertain discriminant validity, the researchers initially evaluated cross-loadings to ensure the effective representation and measurement of each construct by its respective items (Table 2).Subsequently, the Heterotrait-Monotrait (HTMT) ratio, a recommended criterion for assessing discriminant validity in Variance-Based Structural Equation Modeling (VB-SEM) (Henseler & Ray, 2016), was employed.The HTMT ratios for the constructs, alongside the original sample, are presented in Table 3.Most of these values were below the 0.85 threshold, and the bias-corrected and accelerated bootstrap confidence intervals remained below 1, affirming adherence to discriminant validity.This analysis further strengthened confidence in the distinctiveness of the constructs and their ability to effectively measure various aspects of the phenomenon under investigation.The goodness of fit (GoF) assessment may be viewed as a method for estimating the model fit (Ramayah et al., 2018).According to Dijkstra and Henseler (2015), SmartPLS can assist the researcher with estimating the model fit.The tests include standardised root mean square residual (SRMR), exact model fit test, normed fir index (NFI) or Bentler and Bonett index, chi-square and degree of freedom (DoF), and root mean square (RMS)_theta.Table 4 shows the model fit for this study with SRMR value for both the saturated model (0.044) and the estimated model (0.044) are below 0.08.while the d_ULS and d_G for both models are higher than 0.05.Thus, the SRMR model fit criterion is met and the model fit is established.

Structural Model
Within this study, the assessment of the structural model involved a concurrent examination of pathway coefficients (β) and coefficients of determination (R 2 ) using the methodology outlined by (Hair et al., 2017).The Partial Least Squares (PLS) technique was employed, utilizing 5000 subsamples to establish the significance level of path coefficients.
The results of hypothesis tests, encompassing confidence intervals, path coefficients (beta), associated t-statistics, and p-values, are presented in Table 5.This thorough analysis provides valuable insights into the significance and robustness of relationships among the variables integrated into the structural model.
H1 proposed that engagement has a relationship with performance appraisal.The beta coefficient for engagement (E) influencing performance appraisal (PA) is 0.054, with a tstatistic of 4.170 and a p-value of 0.000.The positive beta suggests a positive relationship between engagement and performance appraisal.The t-statistic indicates that the relationship is significant (p < 0.05), supporting rejecting the null hypothesis.This implies that respondents' engagement significantly influences their performance appraisal system.Therefore, H1 was supported.
For H2, it was proposed that a relationship between motivation and performance appraisal exists.The statistical result showed the relationship between motivation (M) and performance appraisal (PA) and the beta is 0.098, the t-statistic is 1.710, and the p-value is 0.044.The positive beta and significant t-statistic suggest that motivation has a significant and positive impact on performance appraisal system.Therefore, H2 was supported.
H3 suggested that there was a relationship between job satisfaction and performance appraisal.The statistical analysis result showed a beta of 0.101, a t-statistic of 5.477, and a pvalue of 0.000.The positive beta and significant t-statistic indicate a strong and significant relationship.Therefore, H3 was supported.
The conducted analysis in this research provided robust evidence supporting all of the hypotheses, confirming the established connections among the inspected variables.
To ensure the reliability of the structural model, we assessed the inherent Value Inflation Factor (VIF) values, all of which were found to be below the generous threshold of 5, with the all value recorded at 1.000 (Table 6).This minimal level of collinearity facilitates meaningful comparisons of magnitudes and the interpretation of coefficients within the model.
Importance Performance Analysis (IPMA), proposed by Ringle and Sarstedt (2016) and Hair et al (2019), was employed to assess the significance and effectiveness of latent variables in elucidating acceptance.The outcomes presented in Table 7 reveal that concerning the overall impact on performance appraisal, job satisfaction exhibits the most substantial influence (0.555), followed by engagement (0.227), and motivation (0.168).These figures signify the relative importance of each latent variable within the performance appraisal context.Regarding performance, engagement achieved the highest score (59.142) on a scale spanning 0 to 100, indicating relatively robust performance.In contrast, satisfaction saved the lowest score (56.260), signifying a lower level of accomplishment.
Notably, despite its pivotal role of performance appraisal, satisfaction displayed the weakest performance.In light of these findings, top management in ODL institutions should prioritize and emphasize efforts aimed at enhancing employee's performance management system intentions, as enriching the system can consequently enhance overall performance.

Discussion & Conclusion
In the context of effective performance appraisal, the statistical results of the current study indicate that motivation, engagement and job satisfaction are the factors affecting the performance appraisal system in the ODL institutions.The statistical findings from this study shed light on the crucial roles that motivation, engagement, and job satisfaction play in the area of effective performance evaluation.These variables are observable and interconnected, and they have a significant impact on the efficacy and functionality of the performance evaluation system in ODL establishments.
The research claims that while engagement is the glue that creates a sense of community and commitment to organisational goals, motivation drives educators and staff to higher performance levels.Job satisfaction, on the other hand is one of the main tenets of the ODL framework, which depicts people's overall well-being.These components work together to produce a win-win situation that has a big impact on how successful and efficient performance evaluation systems are.Consequently, the results show not only how these variables relate to one another but also how they work together to help overcome the unique difficulties that come with evaluating and improving performance in the dynamic environment of the ODL.

Theoretical Implications
The study mentioned above has numerous theoretical implications and constitutes a significant addition to the existing literature on performance evaluation, particularly in the context of higher education.
Firstly, the study advances our understanding of the factors influencing the performance appraisal among employees in ODL institutions, strengthening the theoretical basis for efficient evaluation procedures in the distinct environment of higher education.
Secondly, management will use these factors as a basis to focus on the factors studied in organisational management so that the organisation becomes more robust and impressive in its management, especially when evaluating performance in higher education institutions.
On the basis of this theory, management can finally consider how best to evaluate the performance of its employees without making them dissatisfied in the future.

Practical Implications
The study mentioned above has significant practical consequences for higher education institutions who want to deliberately incorporate performance assessment (PA) into their environments.The study is important because they provide organisations and educational institutions with actionable strategies for enhancing employee performance through the development of a work environment that values and promotes high levels of motivation, job satisfaction, and engagement.The study sheds light on the relationship between motivation, job satisfaction, and engagement and performance evaluation.This facilitates the process of streamlining performance evaluation processes to comply with the identified influential factors.
The study's conclusions offer specific actions that businesses and educational institutions may do to raise employee engagement, job satisfaction, and motivation.These are workable strategies.These actions include putting recognition programmes into place, offering chances for professional growth, and cultivating a positive work environment.The ultimate goal is to improve the performance evaluation results overall through proactive action that considers the identified relevant elements.

Suggestions for Future Studies
Future studies could assess the acceptability of particular performance criteria to academic and non-academic staff in ODLs and also highlight the importance of staff involvement in appraisal system design and adjustment for the efficiency of performance appraisal.Future studies also could study other factors that affect the performance appraisal system such as which would help to understand more fully the factors contributing to the effectiveness of performance appraisal in the ODL education sector in Malaysia.Furthermore, it is possible to employ a qualitative research methodology and thereafter compare its outcomes with the findings of the quantitative investigation.Conducting interviews with high-level executives in the ODL institutions would provide the management with an opportunity to thoroughly investigate the aspects that contribute to the effectiveness of a performance evaluation system.

Conclusion
This study concludes by exploring the crucial aspects of performance appraisal in Malaysian Open Distance Learning institutions.Examining employee input on the performance appraisal system, specifically in relation to motivation, job satisfaction, and engagement as separate factors, provides valuable insights into the current knowledge base.Overall, the findings of this study offer a nuanced knowledge as well as practical consequences for the purpose of enhancing the performance evaluation process within the context of the distinctive environment consisting of ODL institutions in Malaysia.
This study on research of the effectiveness of performance appraisal in Open and Distance Learning (ODL) institutions theoretically contributes to knowledge by investigating viewpoints based on the research area.Furthermore, this study focused in Malaysia adds context by considering the distinct socio-cultural dynamics, legal frameworks, educational policies, and organizational structures that are particular to the country.This helps to provide insights that are suited to the requirements that Malaysian educational institutions face.

Figure 1 :
Figure 1: Research Model Notes: E=Engagement M=Motivation S=Satisfaction PA=Performance appraisal