1. Introduction
Importance of IWP in Education
Individual Work Performance (IWP) is an essential element in a performance management system in the education sector, as it strengthens accountability and aligns with institutional goals (Newspaper, 2019). In Bhutan, the Royal Civil Service Commission (RCSC) introduced the Managing for Excellence (MAX) system in 2017 to enhance teacher performance, while the Royal University of Bhutan (RUB) adopted the Performance Management System (PMS) the same year to promote professionalism, evidence-based management, and improved teaching, research, and service outcomes (Phuntsho, 2018).
While IWP is a mandatory requirement for teachers and academics, serving as an essential tool for performance evaluation, its implementation and execution among faculty members still face considerable issues (Rinzin, 2018).
Challenges in Assessment and Execution of IWP
Despite the intended benefits, several issues have emerged in the assessment and implementation of IWP, especially in the education sector. Rinzin (2019) identified lack of clarity and consistency in the evaluation of IWP as a major challenge faced by employees. On the other hand, supervisors are seeking additional information for appraisal purposes (Lamsang, 2018; Rinzin, 2018; Tshomo, 2019; Kuensel1, 2019).
The Bhutanese government issued an executive order to review the IWP system due to repeated teacher grievances, leading to a mandated review and the formation of a task force to study related issues in schools (Rinzin, 2018; MoE & RCSC, 2019; Lamsang, 2024). This institutional challenge aligns with broader academic findings that many faculty dislike and view performance appraisal evaluations as inaccurate (Larsen, 2009; Chun et al., 2018). Despite these challenges, addressing performance appraisal remains essential as long as these systems are in place (Sherman, 2020).
Interviews with staff across RUB colleges also indicate several challenges with the IWP system. Some staff reported a lack of clarity and interpretation of IWP items (J. Nair, personal communication, 2024). A related issue is the inconsistent interpretation of specific items by supervisors (Y. Pelden, personal communication, 2024). This lack of communication meant that many staff were unaware of the particular items and activities being evaluated, which led to widespread dissatisfaction with their ratings and a perceived lack of transparency (J. Nair, personal communication, 2024; S. Dema, personal communication, 2024).
However, some colleges reported having a clear format and consistency in the evaluation of IWP (W. Wangmo, personal communication, August 15, 2024) (JNEC). D. Dema (personal communication, August 20, 2024) highlighted that the universities under RUB started with IWP much later than the schools. IWP assessments and evaluations have always been a challenge for evaluators. Most of the items were not communicated to staff; therefore, staff were unaware of which items and activities were taken into consideration. Many staff expressed unhappiness with the ratings and the lack of clarity of items.
Given these challenges, there is a need to understand the specific issues faced by immediate supervisors in assessing faculty performance within RUB. Although systems such as MAX and PMS aim to improve accountability and productivity, gaps remain in clarity, communication, interpretation, and consistency in IWP assessment (Thusi, 2023). Against this backdrop, this study investigates the challenges faced by supervisors and academics in assessing IWP within the Royal University of Bhutan.
Research Questions
The study is guided by the following research questions: What are the challenges and issues related to IWP faced by academic staff? What are the issues faced by immediate supervisors in assessing faculty IWP?
2. Literature Review
Performance Evaluation
Performance evaluation is one of the most important parts of human resource practices and organizational management. It assesses employee performance and provides mechanisms for feedback, motivation, and improved performance in line with organizational goals (Daoanis, 2012). A sound performance evaluation system is expected to generate accurate, fair, and useful information about employee performance (Obisi, 2011; Samwel, 2018).
Several factors influence performance appraisal systems, including the purpose of appraisal, performance criteria, fairness, rater capability, communication, and the organizational environment. The present study adapts relevant factors from prior studies and focuses on objectivity in performance appraisal, familiarity with faculty, conflict with organizational goals, fairness of assessment, and time-consuming aspects of performance evaluation.
Challenges Associated with Performance Appraisal
Prior literature identifies multiple challenges associated with performance appraisal systems. First, lack of objectivity can produce biased ratings and inconsistent judgements. Second, familiarity between supervisors and employees may affect ratings either positively or negatively. Third, organizational goals and individual goals may be insufficiently aligned, which may weaken the validity of evaluation. Fourth, perceived unfairness in appraisal can reduce motivation and commitment. Fifth, the time required for evaluation can place a heavy burden on both supervisors and employees.
In higher education, these challenges are especially important because academic work includes teaching, research, service, student engagement, and institutional responsibilities that may not be easy to measure through a single appraisal framework.
3. Research Methodology
Research Design
This study applied a quantitative approach to examine challenges associated with the IWP system. The study developed a structured questionnaire based on variables identified in the literature and adapted from Sherman (2020). The framework included lack of objectivity in performance appraisal, familiarity with faculty, clashing with organizational goals, partiality towards faculty, and performance appraisal consuming supervisors’ time.
Figure 1. Research framework.
Source: Modified and adapted from Sherman (2020).
Click here to view Figure 1 image
Direct image file: https://bjbm.gcbs.edu.bt/public/journals/1/figures/fig1_research_framework.png
Study Area and Respondents
The study covered eight constituent colleges of the Royal University of Bhutan. These were Gedu College of Business Studies (GCBS), College of Language and Culture Studies (CLCS), College of Natural Resources (CNR), College of Science and Technology (CST), Jigme Namgyel Engineering College (JNEC), Gyalpozhing College of Information Technology (GCIT), Samtse College (SC), and Samtse College of Education (SCE).
For supervisors, the researcher conducted a census study. For academic respondents, the sample size was calculated using Taro Yamane’s sample size formula. Although the calculated sample size was 212, the researcher received 85 responses. Sample selection was carried out using a simple random sampling technique.
| College | Supervisor | Academics | Academic Sample Size (%) | Sample Size |
|---|---|---|---|---|
| GCBS | 4 | 65 | 14 | 30 |
| CLCS | 5 | 45 | 10 | 21 |
| CNR | 7 | 60 | 13 | 28 |
| CST | 6 | 61 | 13 | 29 |
| JNEC | 7 | 55 | 12 | 26 |
| GCIT | 3 | 21 | 5 | 10 |
| SC | 6 | 101 | 22 | 47 |
| SCE | 6 | 45 | 10 | 21 |
| Total | 44 | 453 | 100 | 212 |
Data Collection and Instrument
Primary data were collected with the help of a structured questionnaire. A closed-ended questionnaire was circulated among target respondents. The questionnaire consisted of questions based on the indicators and variables mentioned in the report of Sherman (2020). Respondents were asked to respond using a five-point Likert-type response set: 1 = strongly disagree, 2 = disagree, 3 = undecided or neutral, 4 = agree, and 5 = strongly agree. The measurement scale for the data was ordinal, but the variables were treated as continuous.
Questionnaire Reliability and Validity
Content validity was already proven because the survey instrument was modified from Sherman (2020). Cronbach’s alpha was computed for dependability. Cronbach’s alpha was calculated for reliability, with 0.812 for the 29 items, which was acceptable.
4. Result and Discussion
Analysis of the Survey Data from the Perspective of Academics
Most respondents were lecturers, followed by associate lecturers and assistant lecturers. Most respondents were male and had work experience ranging from 0 to 25 years. Eighty-five percent of respondents agreed that IWP is conducted every year, while 15% reported that IWP is not done yearly in their respective colleges.
| Items | Yes (%) | No (%) |
|---|---|---|
| Supervisor and employee discuss together for IWP preparation | 68 | 32 |
| Mid-review of IWP takes place every year | 72 | 28 |
| IWP appraisal is a challenging task | 62 | 38 |
Table 2 indicates that 68% of respondents agreed that supervisors and employees jointly discuss the preparation of IWP, whereas 32% stated the opposite view. Seventy-two percent of respondents indicated that the mid-year IWP review does not take place every year, while 28% agreed. Further, 62% stated that IWP appraisal is a challenging task, and 38% believed it is not.
Figure 2. Level of IWP implementation.
Source: Primary data.
Click here to view Figure 2 image
Direct image file: https://bjbm.gcbs.edu.bt/public/journals/1/figures/fig2_iwp_implementation.png
Figure 2 shows the level of IWP implementation. Fifty-five percent of academic staff agreed that IWP is fully implemented in their respective colleges. Forty-three percent of academic staff reported that IWP is partially implemented, and only 2% reported that IWP is not implemented.
| Statistic | Value |
|---|---|
| Multiple R | 0.512 |
| R Square | 0.262 |
| Adjusted R Square | 0.194 |
| Standard Error | 0.604 |
| Observations | 60 |
Table 3 presents a regression analysis, which indicates a moderate correlation between the dependent variable and independent variables, with a Multiple R value of 0.512. The R Square value of 0.262 indicates that the predictors explain 26.2% of the variability in IWP implementation. The adjusted R Square of 0.19 indicates that 19% of variations in Y values (IWP system) were explained by the independent variables under the study. The standard error value of 0.60 indicates that the average error in the proposed model is moderate.
| Source | df | SS | MS | F | Significance F |
|---|---|---|---|---|---|
| Regression | 5 | 6.988 | 1.398 | 3.831 | 0.005 |
| Residual | 54 | 19.699 | 0.365 | ||
| Total | 59 | 26.687 |
Table 4 indicates the overall significance of the regression model. The ANOVA results indicate that the F value is 3.831 and the P value is 0.005, which implies that the model is statistically significant.
| Variable | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
|---|---|---|---|---|---|---|
| Intercept | 2.264 | 0.642 | 3.526 | 0.001 | 0.977 | 3.551 |
| OPA (Mean) | -0.347 | 0.157 | -2.206 | 0.032 | -0.662 | -0.032 |
| FA (Mean) | 0.091 | 0.095 | 0.951 | 0.346 | -0.101 | 0.282 |
| COG (Mean) | -0.045 | 0.145 | -0.309 | 0.758 | -0.337 | 0.247 |
| FOA (Mean) | 0.374 | 0.179 | 2.092 | 0.041 | 0.016 | 0.733 |
| TC (Mean) | 0.313 | 0.112 | 2.791 | 0.007 | 0.088 | 0.537 |
Table 5 shows the regression results where objectivity in performance appraisal (OPA), fairness of assessment (FOA), and time-consuming (TC) factors have a significant influence on IWPS. Specifically, the p-values for OPA (0.032), FOA (0.041), and TC (0.007) are all below 0.05, confirming that these variables significantly predict IWPS. The final regression equation is IWPS = 2.264 − 0.347 OPA + 0.374 FOA + 0.313 TC + Error.
| Hypothesis | P Value | S/NS |
|---|---|---|
| Hypothesis 1: Objectivity in performance evaluation has a positive impact on individual work performance (IWPS). (OPE) | 0.032 | Significant |
| Hypothesis 2: Familiarity with academics impacts IWPS (FA) | 0.346 | Non-Significant |
| Hypothesis 3: Conflict with organizational goals influences IWPS (COG) | 0.758 | Non-Significant |
| Hypothesis 4: Assessment fairness influences IWP (FOA) | 0.041 | Significant |
| Hypothesis 5: Time factors play a significant role in IWP assessment (TC) | 0.007 | Significant |
Component Analysis
A principal component analysis was performed to identify the items that have a significant impact on the Individual Work Performance system. Findings reveal that TC1 (IWP evaluation is time-consuming), OPA4 (IWP process is comprehensive to accommodate all aspects of performance), and OPA5 (fairness of IWP system) are the main challenges behind individual work performance evaluation.
| Item | Component 1 |
|---|---|
| TC1 | .785 |
| OPA4 | .725 |
| OPA5 | .722 |
| COG3 | .697 |
| FOA1 | .685 |
| FA1 | .661 |
| COG4 | .653 |
| COG2 | .640 |
| FOA5 | .639 |
| OPA3 | .578 |
| FOA4 | .544 |
| OPA1 | .523 |
| FOA3 | -.428 |
| FA3 | -.430 |
| Dimension | Mean |
|---|---|
| TC | 3.86 |
| OPA | 3.38 |
| FOA | 3.20 |
| COG | 3.18 |
| FA | 2.83 |
Table 8 shows the mean value of the different dimensions influencing the IWP system implementation. Findings indicate that TC and OPA have a stronger influence on the IWP compared to other independent variables. The mean values of TC and OPA are 3.86 and 3.38, respectively. Next to TC and OPA, another dimension that influences the IWP is FOA, with a mean value of 3.20.
Analysis of the Survey Data from the Perspective of Supervisors
Most respondents from the supervisors were male, consisting of 70% males and 30% females, with experience ranging from 6 to 20 years. Forty-two percent of supervisor respondents were DAA, twenty-six percent were HoD, and 32% were Program Leaders.
| Item | Component 1 |
|---|---|
| OPA6 | .828 |
| FA2 | .787 |
| FOA2 | .778 |
| FA3 | .768 |
| COG3 | .720 |
| COG1 | .703 |
| FOA1 | .694 |
| OPA3 | .685 |
| COG2 | .650 |
| FA1 | .635 |
| OPA5 | .522 |
Table 9 shows the component matrix generated after principal component analysis. Results indicate that OPA6, FA2, FOA2, and FA3 are the four items that have a significant influence on the IWP system. Findings indicate that a personal relationship with academics and familiarity with academics significantly influence the IWP evaluation.
Other Findings
Additional findings from the supervisor and academic responses are summarized in Tables 10 to 13.
| Row Labels | Strongly Disagree (SD) | Disagree (D) | Neutral (N) | Agree (A) | Strongly Agree (SA) | Grand Total |
|---|---|---|---|---|---|---|
| DAA | 0.00% | 0.00% | 50.00% | 50.00% | 0.00% | 100.00% |
| HoD | 33.33% | 16.67% | 33.33% | 16.67% | 0.00% | 100.00% |
| PL | 0.00% | 11.11% | 66.67% | 0.00% | 22.22% | 100.00% |
| Grand Total | 9.52% | 9.52% | 52.38% | 19.05% | 9.52% | 100.00% |
Table 10 analysis indicates that 50% of the DAA, approximately 16% of the HoD, and 22% of the PL believe that acquaintance with academics influences the IWP evaluation process.
| Row Labels | SD | D | N | A | SA | Grand Total |
|---|---|---|---|---|---|---|
| DAA | 0.00% | 9.52% | 0.00% | 9.52% | 9.52% | 28.57% |
| HoD | 9.52% | 0.00% | 4.76% | 9.52% | 4.76% | 28.57% |
| PL | 0.00% | 9.52% | 4.76% | 14.29% | 14.29% | 42.86% |
| Grand Total | 9.52% | 19.05% | 9.52% | 33.33% | 28.57% | 100.00% |
Table 11 shows that around 18% of the DAA have opinions that checking the documentary evidence for IWP evaluation is a complex process. Likewise, 15% HoD and 29% PL also have the opinion that IWP evaluation is a complex process.
| Designation | Familiarity with Academics Impacts IWP Process | Percentage |
|---|---|---|
| Associate Prof | 5 | 8.12% |
| Assistant Prof. | 5 | 7.61% |
| Lecturer | 24 | 42.13% |
| Associate Lecturer | 15 | 26.90% |
| Assistant Lecturer | 11 | 15.23% |
| Grand Total | 60 | 100.00% |
Table 12 shows that about 8% of associate professors perceive that familiarity with academics impacts the IWP process. Likewise, around 8% of assistant professors, forty-two percent of lecturers, about 27% of associate lecturers, and 15% of assistant lecturers have the opinion that familiarity with academics impacts the IWP evaluation process.
| Designation | SD | D | N | A | SA | Grand Total |
|---|---|---|---|---|---|---|
| Associate Prof. | 0.48% | 1.91% | 0.00% | 3.83% | 0.00% | 6.22% |
| Assistant Prof. | 0.00% | 1.91% | 2.87% | 0.00% | 2.39% | 7.18% |
| Lecturer | 0.96% | 0.96% | 11.48% | 7.66% | 21.53% | 42.58% |
| Associate Lecturer | 0.48% | 0.00% | 5.74% | 11.48% | 9.57% | 27.27% |
| Assistant Lecturer | 0.96% | 1.91% | 1.44% | 7.66% | 4.78% | 16.75% |
| Grand Total | 2.87% | 6.70% | 21.53% | 30.62% | 38.28% | 100.00% |
Table 13 shows that around 68% of the academics have the perception that the IWP process consumes lots of their time. Findings reveal that 6% of associate professors, around 7% of assistant professors, forty-three percent of lecturers, and 27% of associate lecturers feel that the IWP process consumes their time.
5. Conclusion and Suggestions
This research provides insight into the challenges faced by supervisors and academics in the IWP evaluation. Further, the research work tries to identify the key challenges from the perspective of supervisors and academicians in relation to the IWP evaluation. Past studies have established the roles of IWP in evaluating the performance of employees. Results of the study indicate that objectivity in performance appraisal (OPA), fairness of assessment (FOA), and time-consuming (TC) factors significantly influence IWP evaluation. The OPA p-value is 0.032, the FOA p-value is 0.041, and the TC p-value is 0.007, respectively.
From the perspective of supervisors, the main challenge is the personal relationship with faculty members. The second prominent challenge is familiarity with faculty members. Because of excessive familiarity, supervisors may not be able to maintain fairness and unbiasedness in the performance evaluation process. Similarly, Huckman et al. (2009) show that familiarity between supervisors and employees influences the performance evaluation of an individual. Future studies could focus on how the IWP system can be linked with employee motivation because, if these practices do not contribute to improving teacher performance and motivation, then there is no reason to continue with the same.
- For proper implementation of the IWP system, it is advisable to make the entire process of evaluation objective. Any subjectivity in the evaluation process brings bias and unfairness. The IWP process must be comprehensive enough to cover all aspects of employee performance evaluation.
- Supervisors must be trained to maintain fairness in the assessment process. Bias towards the opposite gender should be addressed.
- The IWP process consumes a huge amount of supervisors’ and academics’ time. Therefore, it is advisable to reorganize the entire IWP system and allocate extra time to supervisors and academics.
- While it is challenging to eliminate subjectivity from both supervisors and academics, performance evaluation systems should incorporate mechanisms designed to minimize subjective bias.
- An effective performance evaluation system requires periodic review by key stakeholders to integrate user feedback, address emerging challenges, and align mutual expectations within educational institutions.
- IWP should be developed for each college context or at least adjusted to the specific needs of each college. A common evaluation may not adequately evaluate the IWP.