EFFECT OF OPRAS ON EMPLOYEES’ PERFORMANCE IN TANZANIA LOCAL GOVERNMENT AUTHORITIES: THE CASE OF MTWARA MUNICIPAL COUNCIL

ABSTRACT


I. INTRODUCTION
New public management (NPM) reforms have given rise to a global phenomena known as performance measurement systems (PMSs). Despite being widespread and well-established at this point, they have drawn criticism for both their design and their implementation [1]. According to [1], the trend of many, primarily Western, governments undertaking reforms to the administration of their various public sectors occurred between the late 1970s and the mid-1990s. Many of the reform measures that was undertaken under the pretext of new public management (NPM), which was underpinned by a mindset of "managerialism" and placed a heavy emphasis on enhancing public sector performance, integrated management techniques that are typically associated with the private sector.
The performance evaluation process gained popularity in the 1940s. Merit rating was initially used to back up an employee's compensation or earnings during the time of the Second World War [2]. The technique, which relied on material outcomes, paid higher output with higher pay or compensation, and vice versa. However, early researchers found that workers' levels of motivation for their occupations and performance varied even among those with almost comparable skills to work and compensation [3].
According to research conducted in Jordan [4], performance standards have a negative effect on employees' ability to perform their jobs in the banking industry in the south of the country. Employees in this industry prefer to work with more freedom while still adhering to established standards that could boost productivity.
According to [1], these reforms replaced the old collegial public sector management with a more professional style of management, changing how the public sector operates from "administration" to "management". Competition, cost effectiveness, and operational prudence are examples of private sector company values that have evolved into guiding management concepts. The main factors influencing how public resources are allocated have changed from being based on the quest for greater effectiveness in the administration of the public sector to being based on ideals of equity or social justice. This promoted a more competitive climate where management for results was prioritized. An increasing focus on performance or a greater openness of that performance was one of the main effects of NPM reforms. In light of this, measurement systems for performance (PMSs) evolved into a crucial component of management reforms for the public sector and have since remained a crucial tool in managing the larger public sector [1].
Performance measurement has traditionally concentrated solely on financial metrics. Because organizations and the marketplaces in which enterprises compete are becoming more complex, studies conducted in the late 1980s demonstrated that historical financial data is insufficient to satisfy the PM in the modern economy [5]. This is because the correlation between financial reporting and shareholder value has decreased. Instead, non-financial elements such as client loyalty, satisfaction among workers, internal procedures, and an organization's innovations promote sustainable shareholder value [5].
The definition of a performance evaluation is still up for controversy, according to [5], despite the fact that much study has been done on the subject [6]. The definition of [7] that describes performance measurement (PM) as "the process of measuring how efficient and effectiveness of previously implemented actions" is stated by [8]. This definition emphasizes both efficacy and efficiency, but it doesn't say what to measure or why. The justification, with a focus on measuring the value that the company delivers to its consumers, provides greater advice to those involved in performance measurement [1]. "PM is assessing the effectiveness of an organization's management and the value it provides to customers and other stakeholders." Employers, whether in the private or governmental enterprise/office, medium or big firms, typically try to achieve employee production to meet overall operational goals, according to [9]. Employers use a range of techniques and procedures to assess employee work performance in order to realize this. Performance appraisals are the name given to these measurement techniques. Some utilize multiple tools in addition to one, but smaller organizations frequently pick and employ the one tool that suits them the best. Employees must perceive these measuring systems as equitable and fair in order for them to be taken seriously. The tools that offer the greatest degree of impartiality should be chosen by people who use them. It's challenging to eliminate all or most subjectivity, although some methods are more conducive to objectivity than others [9].
The high school instructors of Kirinyaga West Sub County in Kenya agreed, according to [10] findings, that they are motivated if their work contribution is acknowledged; the chance for further education motivates them to put forth more effort; TSC offers teachers the chance for career advancement; TSC bases promotion on work performance; and TSC links work performance with rewards. This suggested that the use of rewards as a method of performance evaluation had a significant impact on how well secondary school teachers performed in Kirinyaga West Sub County.
Since the government opted to give up the confidential appraisal method, Tanzania, and the public service industry in particular, have used the OPRAS to monitor staff performance (President's Office Public Services Management, Dar es Salaam, 2011). This came after the government's announcement of the Public Service Transformation Program (PSRP) in 2000. Employer participation in goal-setting, implementation, monitoring, and review procedures is crucial, according to OPRAS, since it encourages personal responsibility and enhances openness and communication among management and staff. Therefore, introducing and operationalizing OPRAS is required of all Ministries, Autonomous Departments and Agency (MDAs), local governments (LGAs), and Regions. This is supported by laws and policies, which, among other things, enforce OPRAS adoption in the public sector. These include the legislation known as the Public Service Act ( There are various performance measurement systems that have been developed over time during the course of attempting to improve organizations' performance [11]. Therefore, various organizations, including public organizations and agencies in Tanzania measure their employee performance using these performance measurement systems. Studies such as [12] study entitled "Employee's Performance Measurement Practices in Public Sector: A Case Study of Tanzania Electricity Supply Company Headquarter (Dar es Salaam)" and [13] paper "Measuring Performance in Public Sector Organizations: Evidence from Local Government Authorities in Tanzania" provide evidence of performance measurement on employees performance. However, these papers and research focus on measuring performance and not on the effects of these performance measurement systems on employees' performance. Additionally, it has been acknowledged by investigators like [14] in the paper titled Application of open performance assessment and evaluation framework in Tanzania that local government agencies suggested on the scheduling activities to be of both managers and staff members and that it should be carried out continuously. Thus, study is required to determine the impact of OPRAS on employees' performance in Tanzanian local government agencies, specifically in this particular instance of Mtwara Municipal Council.

II.1 THEORETICAL REVIEW
Through HR, businesses hope to achieve high and consistent performance [15]. One of the key elements in the logical and organized process of HRM is PA (Answers.com). In order to recruit and choose employees, train and develop current employees, and motivate and maintain a quality workforce through adequate and appropriate reward of their performance, information gathered during and at the conclusion of the PA process is necessary [2]. As a result, the HRM system may fail without a solid PAS founded on the principles of objectivity, accuracy, relevance, and feedback. The important human resource could be completely wasted as a result of this.

II.2 PERFORMANCE APPRAISAL
There are numerous ways to define performance appraisal, Performance appraisal is described as the formal rating and description of employees by their supervisors, which is typically done once a year. Additionally, management uses performance evaluation to detect and gauge employee performance in firms.
Additionally, performance evaluation helps workers identify their objectives, outlook, and motivation for completing the duties that have been allocated to them [16]. According to [17], performance refers to what management expect employees to produce in terms of outcomes, efforts, tasks, and quality under a certain period of time and under particular circumstances.

II.3 THE PROCESS OF PERFORMANCE APPRAISAL
In order to help managers and staff members plan, manage, evaluate, and realize enhancements in performance in the company with the purpose of accomplishing the desired organization goals, [18] defines open performance evaluation as an open, formal, and systematic method. This definition holds true for the entire investigation.

II.3.1 Performance Appraisal Importance
Financial success, productivity, quality of goods and services, customer happiness, and employee satisfaction are five key organizational outcomes that are impacted by the performance appraisal process. According to [19], successful performance leadership is defined as accomplishing financial as well as nonfinancial objectives while also enhancing customer service and process quality. Additionally, it is crucial for employees to feel that there is room for improvement in their job and that the assessments are fair in performance reviews [20]. The performance review process, awards, motivations, and growth have a negative influence on employees without fairness [21].

Hypothesis:
HI: There is a positive relationship effect between accuracy and employees performance. H2: There is a positive relationship effect between objectivity and employees performance. H3: There is a positive relationship effect between feedback and employees performance.

III. RESEARCH METHODS
The positivist research philosophy served as the basis for this investigation. Positivism, according to [22], supports the idea that derived knowledge can be utilized to demonstrate real comprehension (certitude or truth). Empiricism, which refers to confirmed positive facts or evidence gained by the senses, serves as the basis for positivism. Introspection and intuitive knowledge are not valued by the positivist philosophy.
This study used a quantitative research approach throughout the examination. Quantitative research is the process of acquiring and analyzing numerical data. It could be used to uncover patterns and averages, create theories, investigate causes, and extrapolate results to bigger groups. According to [23], precise measurements while mathematical, numerical in nature, and statistical analysis of the data gathered by means of surveys, questionnaires, and polls, as well as manipulating of previously gathered statistical information using computational approaches, are key components of quantitative research techniques.
A research approach based on case studies was used for this investigation. [24] asserts that case study research entails a thorough and in-depth consideration of a specific event, circumstance, the company, or social unit. A case is typically "an occurrence of some kind in a bounded context" with a defined time and space period. A case inquiry is a thorough analysis of a current issue in the light of practical knowledge. The case review is relevant, especially if the phenomenon's background is significant.

III.1 POPULATION
The entirety of the objects under inquiry constitutes the study population. Population is defined by [25] as any subject or subjects in all areas of study. Population refers to the total set of individuals, businesses, plants, or other objects who possess one or more traits that the study is interested in. The Mtwara District Council employs 1094 people. The following categories apply to these workers. There are 124 workers in the health sector, 788 teachers in elementary and secondary schools, 36 workers in agriculture and livestock, 11 workers in the workplace, 81 village executive officers, and 54 workers in administration. As a result, the participant population of the research be made up of all Mtwara district Council employees. The researcher, however, is not able to conduct the study on the entire population that is specified. An employee sample was instead chosen and used for the purpose of inquiry.

III.2 SAMPLE AND SAMPLING TECHNIQUES
A "sample" is the overall number of participants who are chosen to participate in a study. Sampling is the method used to get the sample. According to [25], sampling is the process of choosing a portion of a total or aggregate on the basis upon which a decision or conclusion is formed about the aggregation or totality. In simple terms, it is the method of learning details about a whole population by looking at a small portion of them. For the purposes of the relevant investigations, researchers often frequently choose just a few objects from the universe.
The ten per cent (10%) of the population that was accessible made up the 109 participants in the study's sample, which was drawn from an estimated population of 1,094 people. According to Krishnaswami (2003), the sample size was thought to be sufficient and therefore representative. The author claims that a sample size of between 5% and 10% of the total accessible population is sufficient for data collection for a total population of between 1000 and 5000. Additionally, the formula below was applied to draw a sample from the population of 1094 employees.
Where N= population of employees, 1094 C= coefficient of variation (assumed), 10% n = sample 109 e= sample error (assumed), 1% The population of the case region under investigation in this study ranges from 1000 to 5000. In order to reflect the entire population, 10% will be used. A basic form of random sampling involves selecting a part of a population at random. Using this method of sampling, each participant of the general population have a precisely equal possibility of being chosen. This sampling technique for probability requires only a small amount of prior population knowledge and is the simple to understand of all the ones available. It also only requires one random pick. Due to the randomization used, any research done with this sample ought to demonstrate a high level of validity internally as well as externally [25]. Simple random sampling is suggested because each employee will have an equal chance if being selected as a sample. The 100 respondents who did not hold managerial roles will be chosen at random to make up the sample.

III.2.1 Data Collection
According to [26], this is a strategy for gathering data that entails giving the subject a set of planned and structured questions to answer in writing. Data for this study will be gathered via a selfadministered questionnaire. Respondents chose their responses from a sheet of closed-ended questions in this survey. The purpose was to facilitate the collection and processing of data. The researcher chose to employ this strategy to complete data collection quickly since this study takes a quantitative approach and because of the time allocated for data collection.

III.2.2 Data Processing and Analysis
Multiple linear regressions were employed in the investigation. The data was analyzed using several linear regression modes to demonstrate the relationship that currently exists between the independent and dependent variables. Each independent variable was expressed by a number of different factors; hence an average was calculated for each category of variables in order to represent the variable [27]. The relationship between OPRAS targets, on the one side as one of the independent characteristics; accuracy, objectivity, and feedback; and employee performance, on the other side as a variable that is dependent, was then expressed in the model. The generated data from the variables with a Likert scale were entered in SPSS and analyzed to create regression results demonstrating the connection between performance assessment systems and their influence on employee performance.

III.2.4 Regression Model
The model of the current study is of the form: Where; 1 , 2 , 3, 4 … represent slopes, 1 Accuracy -AC 2 Represents Objectivity -OB 3 Represents Feedback -FB Y represents employee's performance, and Represents the error term.
The regression model was built using the same core presumptions of the model for linear regression, including linearity, independence of errors, equal variation of errors, and homogeneity of errors [28]. Linearity was checked by plotting each independent variable against the dependent variable while independence of errors was checked by using the scatter plot of residuals. Normality of errors was checked by looking at QQ-plots of sample quintiles as well as using histograms while the constant variance was checked using the residual box plots.

IV.1 PARTICIPANTS SAMPLE PROFILE
Gender, age, education level, and employee performance were the four demographic factors that were taken into consideration ( Table 2). Female constituted the majority of all respondents. They constitute 2/3 of all participants leaving men trailing behind almost 30%. Respondent's age between 21-30, and 31 -40 and those aged 60 were the majority of all participants' age groups; both have more than 40% of all participants. These were followed by 41-50 age groups who constituted 1/3rd of all participants. The lowest score age group was 60 and above who clocked just 1% of all participants.
The employee education was observed, where by majority were bachelor graduates who command just above 1/3 of all participants, they are closely followed by diploma holder who scored 32.4. Master's degree holder was third scoring almost 1/5 of all participants. Training last were PhD holders who are just above 1 % Experience shows that those employees who have been to work between 11-15 years are the majority who have almost 1/3rd of all participants, followed by 6-10 group who constitute 26 % of all participants. Last age groups are 20 and above who are just above 10 %.

IV.2 DESCRIPTIVE STATISTICS RESULTS
Four distinct variables for the mean, the standard deviation, the lowest and max; accuracy in target setting; objectivity of the targets; and feedback, descriptive statistics were generated. Employee performance was the dependent variable.

IV.2.1 Effect of Accuracy
Descriptive statistics (mean, standard deviation, minimum, and maximum scores) were computed for the effect of setting accuracy targets on employee's performance scale ( Table 3

IV.2.2 Effect of Objectivity
Descriptive statistics (mean, standard deviation, minimum, and maximum scores) were computed for the effect of effect of Objectivity of targets on employee's performance scale ( Table 4

IV.2.3 Effects of Feedback
Descriptive statistics (mean, standard deviation, minimum, and maximum scores) were computed for the effects of feedback on employee's performance scale (Table:5

IV.2.4 Employee's performance
Descriptive statistics (mean, standard deviation, minimum, and maximum scores) were computed for the dependent variable employee's performance scale (Table 4.2). The results show that Promotions are rewards of exceptional performance scored highest (M = 4.37, S.D. = .824) followed by Employees are fairly compensated for their performance (M = 4.22, SD = .583). The least way through which employee's performance was explained is There is a low staff turnover at Mtwara District Council (M = 3.92, SD = 1.098) followed by Employees career growth is determined by performance system (M = 3.94, SD = 1.12).

IV.2.5 Multiple Regression Analysis
Multiple regression analysis was used as the dependent variable to determine the impact of OPRAS (independent factors) on employee performance. The results are presented in Table 7.
The model is summarized with a focus on the revised R2 statistics (.189). This indicates that OPRAS is responsible for 18.9% of the variation in employee performance.

IV.2.6 Anova
The results of an analysis of variance (ANOVA), also known as model fit outcomes, are displayed in Table 8 below. In this table, the F-statistics and their associated sig. value are of particular interest. The results show that the F-statistics is 1.281 percent (p< 0.001). The results confirm the model's assertion that "the approach" possesses power to predict job performance using OPRAS scores." On the basis of OPRAS scores, it seems that the model may be able to forecast employee performance with accuracy.

IV.2.7 Coefficients
The regression model's coefficients are shown in (Table 8). The coefficients show, with a normalized B =.092 (p< 0.001) value, that the precision setting of OPRAS objectives positively predicts employee performance. These results showed that the performance of workers whose direct supervisor showed accuracy in defining goals increased by 89.9%. The findings also suggest that objectivity of the targets B .093, (p < 0.001) significantly and positively predicts employee performance. Feedback likewise significantly and positively predicts employee performance B = 138 (p < 0.001).

IV.2.8 Discussion of the Finding
The purpose of the study was to evaluate how OPRAS affected Mtwara Municipal Council employees' productivity in Tanzania. Three independent variables made up the effect of OPRAS: accurately set targets, objectively established targets, and feedback as goals. The performance of the employee was hypothesized to be predicted by these three variables. All theories were confirmed. Employee performance was found to be favorably and considerably impacted by setting accurate targets.
It was discovered that setting objective targets has a favorable and significant impact on employees' performance. This result lends credence to the earlier theory. [29] claim that goalsetting involvement has an impact on employees' pro-active behavior in support of this finding. When the objectives are clear, unambiguous, simple to understand, and impalement employees are easy to implement them.
Accurately setting OPRAS targets was proven to be beneficial and significantly related to employee performance. The conceptual model includes a relationship between target flexibility and firm performance as an intermediary of the impact of target difficulty, although this relationship has only been studied once before and has to be confirmed through replication. A study [2]. looks at how flexible targets affect a firm's success. They define "Target Flexibility" in their paper as "The extent whereby firms potentially modify targets over over the course of a period" when they first propose it. The [30] study is the only one to look at how intra-year adjustments to targets affect performance. [30] make the claim and provide evidence in support of it in their study that the relationship among target difficulty and business performance is moderated by the degree of target flexibility. Target setting needed objectivity for validation the particular goal.
Feedback from managers to employees was discovered to have a favorable and significant relationship influence on employee performance following the final assessment and scoring of OPRAS. The claim is that both positive and negative comments have a favorable impact on an employee's performance. Employees can actively offer job ideas and input in order to overcome challenges and improve their performance, according to research that previously showed a favorable impact of proactive behavior on the business [31] Feedback from managers to employees was discovered to have a favorable and significant relationship influence on employee performance following the final assessment and scoring of OPRAS. The claim is that both positive and negative comments have a favorable impact on an employee's performance. Employees can actively offer job ideas and input in order to overcome challenges and improve their performance, according to research that previously showed a favorable impact of proactive behavior on the business [31].

V. CONCLUSIONS
From the findings it may be concluded that OPRAS at Mtwara Municipal council is acceptable. Accuracy, Objectivity and feedback of OPRAS seem to be very important in order to make OPRAS work. These can be achieved only if supervisors and managers have quality nd skills in OPRAS management.

VI. CONTRIBUTION
This study has contributed in OPRAS management in local government authorities and also the public service working organizations. Theoretically, the study has brought in new perception of how well to management OPRAS so that it can be functionable by adding on the essence of new perception that OPRAS is not for promotion and discipline action oriented but improving performance of employees and the entire organization. Practically the study has contributed on how well OPRAS targets should be treated based on accuracy, objectivity and also importantly sending feedback to employees whether positive and negative.

VII. RECOMMENDATIONS
From the findings, this study recommends that supervisors and managers when setting OPRAS targets as cascaded from organizational objectives, they should make sure and improve on accurately setting targets, objectively setting targets without ambiguity and attainable and time frame shortly known as (SMART) Moreover, it is recommended that further studies to be undertaken focusing on OPRAS. This study used cross-sectional and quantitative approach. However a longitudinal study in qualitative approach may be used so as to trace if there is real behaviourial change for increasing performance after properly managed OPRAS target setting.

IX. ACKNOWLEDGMENTS
Authors would like to acknowledge the effort, help and resourceful from Mtwara municipal council managers and all employees for their courtesy.