Much of the existing research literature on OJ focuses on the relationship of OJ and employees’ performance, work performance, organizational commitment, chances of turnover, attendance, and, above all, job satisfaction of employees ([53]). The direct relationship of OJ’s dimensions with TP has not yet been empirically investigated.

The overall connection between organizational justice (OJ) and team performance (TP) is well established in management literature, especially in the realm of the private sector. There is, however, a huge disparity when we turn our attention to the public sector, and particularly in developing countries such as Pakistan. The issue is that we do not have empirical knowledge of how OJ affects TP in the case of the Pakistani public sector institutions in particular ([3]). Public servants are not unaware of these concepts; their organization is built like the private sector (with work teams, reviews, and bonuses), and these factors may change because of the bureaucratic, hierarchical, and frequently politically based nature of these organizations. As such, generalizing the results of the organizations in the private sector to the population sector is problematic. Whereas previous studies have demonstrated extensive associations between OJ and individualized results like job satisfaction, turnover, and commitment ([14]; [53]), there has been a relative paucity of studies that specifically investigate the effects of distributive justice and procedural justice on team-based performance outcomes in a developing country in the public sector. The parameter to be filled in this study is by undertaking empirical testing on the direct influences of distributive and procedural justice in relation to team performance amongst employees in the federal organizations within the Pakistani public sector. By contextualizing the research in this area, which has not been thoroughly studied, the study will be a part of a deeper understanding of how perceptions of fairness affect team performance in a bureaucratic setting.

1) Does distributive justice affect team performance in public sector organizations?

2) Does procedural justice affect team performance in public sector organizations?

1) To examine the effect of distributive justice on team performance.

2) To examine the effect of procedural justice on team performance.

During a political debate, Aristotle elaborated justice as fairness in the distribution of assets among the general population ([45]). Justice is a basic guideline of collaborative activities in a firm ([7]). Justice is perceived as a decision or activity that is ethically correct based on morals, religion, reasonableness, value, or law ([42]). It is a noteworthy cause of concern for both firms and workers ([49]). Fayol referred to justice as a command and obligation; he expressed that the necessity of sanction has roots in the understanding of fairness ([20]). Fayol additionally referenced that equity shapes the 14 basic standards of management, which involve workers to illuminate clashes in the firm as a direct affirmation of interactional justice in work ([23]). The idea of equity and justice has been a feature of social establishments ([44]), which expresses that equity and justice enable a person to amplify individual profit and gains by bypassing short-term benefits. [50] stated that augmenting an individual’s gain is known as the “self-interest model” or “instrumental model”. Their theory recommended that, by monitoring individual gains, an impression of just procedure emerges, and this perception is appreciated in the sense that it improves the probability of accomplishing the required result.

The field of justice and fairness has turned into a significant area of study, allowing firms to know the conduct and attitude of workers towards equity in an organization ([24]). A person strives to accomplish a firm’s objectives when he or she is valued, regarded, and cherished in a group of people. This idea is known as the relational model. The relational model encourages a person to know their standing and regard in a team. Various models of justice express that it has symbolic value, regards for the dignity of the individual, and confirms the status of a person in a team by helping individuals to know their value and standing. Such an idea offers a progressively psychological clarification of an individual observation ([31]).

Justice is an old concept that is in-built in the human instinct, where [17] show that individuals see justice as a “fair” event. [52], in their examination, express that even a little kid is very much aware of the idea of justice (that something or an act is not regarded by the child as fair), which has attached something of ultimate importance to mankind. In the study of [22], the general population cares about equity since they care about human respect and regard. They also highlight that “if justice is available for the general population, they will remain together; in any case, if justice is not given by any means, that will pull them apart”.

One can refer to the workplace as a social setup where many acts of injustice happen ([39]). The common phrase “a fair day’s pay for a fair day’s work” reflects the prominence of justice in the firms. The concerns regarding being treated fairly and in a just manner are an important aspect of employees’ work-related perception. Thus, it affects the quality of the interactions in social setups related to jobs and task performance. Employees consider fairness as the most desirable quality of a workplace ([43]).

Organizational behaviour and organizational psychology now put a special emphasis on this concept of the perception and reaction of workers to justice and fairness at work, known as organizational justice. Different related concepts and types of organizational justice and the responses of employees to it have been studied in detail by earlier research ([17]). The focus of these studies had been on the effects of OJ on factors like the effectiveness of managerial working: work performance, non-attendance, workers’ commitment to organization ([13]).

For many reasons, OJ is vital for people at work ([16]). The previous studies highlight three very significant justice instigators that are relational, deontic, and instrumental. The facets are inclusive and reflect upon each other; others maintain that workers stress attaining justice through all three aspects.

Whereas the third kind of constructs stresses the fact that a person is always seeking respect, appreciation, and inclusion in a respected group of individuals. The perception of being treated fairly and just practices and decision processes best elaborates the value and worth of an individual in a team or group.

Organizational justice, furthermore, offers a governance apparatus for the resolution of disputes between the institute and employees through focusing on the perceived procedural, interactional, and distributive justice ([11]). The attitude of a worker regarding the institution or firm depends on how a comparison is made of individual efforts and incentives on the contribution a worker exhibits at work; however, a worker would most probably show a positive behaviour about the firm he works in, given inputs and increases are equivalent or superior ([26]). The level of will surely tend to decrease, and workers would exhibit negative work-related attitudes if other workers are rewarded relatively more for equal or less amount of work ([32]).

From the past parts, it has turned out to be obvious that workers’ perception of justice is significant for their work behaviours, work attitudes, prosperity, and well-being ([33]). Both theoretical records and observational examinations were examined to demonstrate that individual workers who feel fairly treated and feel more satisfied at work are increasingly attached to the organization and enjoy a good, healthy life ([34]).

Existing emphasis is not much on solid connections among perception of OJ and individual consequences ([5]) but much upon various procedures through which perception of fairness is identified with tasks and well-being results.

People have various attributes that impact the justice information and the degree to which it influences their behaviors and practices at work. Alongside personal contrasts, context and time-bound variables also fill in the form of limiting conditions or enhancing factors on fairness impacts ([12]). Workers’ job qualities are explicit, employees working in a certain condition in the firm ([41]). The environment’s attributes may impact justice perception. In this manner, one approach to think about procedures can be by researching conditions that can weaken or strengthen the perceived justice, like a mediating factor or moderator ([21]).

An alternate approach to reveal insight into the procedures’ basic perceived OJ observations is through examining the way people respond to similar perceived fairness. The methodology by looking for the role and effect of mediating variables to open the black box containing the instruments connecting perception of justice and related results ([25]).

SETs are frequently used for anticipating, highlighting, and clarifying equity impacts; it seems clear that a study of mediators for the effect of justice would be helpful. It might be that explicit setups should be examined to portray the means among OJ’s perceptions and explicit consequences relating to work ([15]).

Before 1980, the OJ was measured based on a single element. Multiple-item measures emerged with the expansion of the concept of organizational justice ([4]). Earlier researchers believed that organizational justice has only two types, namely distributive and procedural justice ([18]). They claimed that DJ is the impartiality of results in the allocations and allocations of the organization, arguing that procedural justice is the justice in processes concerning distribution and sharing processes of a firm ([51]). Later, another kind is also deliberated upon, named interactional justice. It is an addition to procedural justice, nevertheless, it simply narrates the human element of the firm or institution ([10]). This type is further subdivided into dualistic dimensions, namely informational justice and interpersonal justice. So, there are four factors of organizational justice, i.e., informational justice, distributive justice, interpersonal justice, and procedural justice ([14]). All these kinds of justice are linked; nonetheless, these take diverse and distinctive measurements ([14]; [3]).

Workers are not treated well by the firms; some are given jobs, and others are not. In a firm, some new recruits are promoted on a fast track basis while others may not get such rewards even after working with full devotion. This differential treatment in the work environment is a reason for the unjust distribution of assets ([6]). These issues of unjust distribution and discriminatory attitudes at firms were the real worry for the social researcher for three decades, which spanned from the 1950s to the 1970s.

As Adams’ equity theory and the social exchange theory were the main conceptual frameworks for the research on justice and fairness of decisions and rewards systems of an organization, distributive justice was the only type known before 1970 ([9]).

Equity theory usually describes DJ as employees’ perceived match between the outcomes they receive and the efforts they put in. The main aspect focused on by Adams was the perception of individuals about consequences like salary or performance assessment ([40]). Individuals’ perception that there is inequality regarding outcomes, a change in efforts, or else adaptation in their own perception of inputs or outcomes will be a result ([8]). Adam used the SET context for the evaluation of the fairness. Thus, he believed that individuals were more concerned about the fact of how fair the outcomes were. They do not show a sentiment of concern for the absolute level of outcomes ([30]). In order to evaluate the fairness, Adams proposed employee input calculation as the ratios, for example, knowledge, skills, and abilities, to his outcomes, and then linking the ratios of different employees to the ratios of a particular individual. Equity rule, although having an objective nature, is completely subjective. It is the perception of an individual, and it varies from one person to another. Therefore, mainly the term perceived distributive justice is used. Additional distribution guidelines, like need and equality-based, are effective as well ([22]). Equal output for each employee is the equality rule. Whereas, the need rule states that the output should be based on the needs of an individual ([37]). In different settings and situations, organizations can opt for a specific allocation rule ([19]). Given that the main purpose of the adoption of any of the rules of distribution is to attain DJ.

Relationship of distributive justice and an individual’s emotion is highly significant as the is on outcomes, therefore, perceived injustice concerning a particular outcome effects emotions and the person have feelings like guilt, dignity, anger and happiness or thoughts like flawed contributions and products his own or others’ ([2]; [1]) and as a result effect their behaviour. This behaviour effect can be in the form of either leaving the organization or a noticeable decline in commitment and motivational level, and poor performance.

Impartiality in the processes and procedures adopted for achieving the administrative outcomes. It is the impartiality in the organizational processes and procedures outlined. PJ is the result of distribution and allocation made from the perspective of an organization. It is not only the distribution of resources that decides about the fairness or justice, but the processes and procedures of outcomes are also decisive in this regard. Organizational justice thus has procedural justice as a main element that cannot be ignored ([39]; [50]).

Evidence of procedural justice is based on two theories. More basic to the idea of PJ is the theory developed by [50], i.e., control theory. The main axiom of control theory is that employees of an organization would love to gain control over the manner in which organizations deal with them. Equity in processes is an element of utmost value that aids workforces to take control over their results. Another model presented by [38] is the group value model. A Person prefers to be a member of the groups in an organization, these groups perform specific work assignments, and rational processes are vital in this construct as it gives worth to the individuals who accomplish assigned tasks and play an important role in a specific team for the accomplishment of the crucial objective of an institute ([29]). The procedural impartiality in dissemination mockeries has a major consequence on one’s attitudes and assessments. Many studies have shown that when employees are confronted with issues in procedural justice, they will feel demotivated and frustrated, and as a result, put their efforts into correcting the fairness system of the organization. In many cases, employees tend to exhibit negative work-related attitudes and behaviour as well ([24]). In case there exists a perception of PJ among workers, it is almost impossible for them to agree to indulge in dishonest practices. If they are thinking that the organization is exhibiting procedural unfairness, most of them will adopt unproductive reactions ([22]).

Although the organizations acknowledge the importance of fair procedures, there is still a wide gap between the perception of employees regarding fair procedures and the existing practices. Creating the right balance in the procedural justice and the demands of the employees is an uphill task for the organizations, as the employees are always trying to get hold of the procedures that are directly affecting them ([28]). Thus, the importance of procedural justice in deciding the attitudes and behaviour of employees, such as motivation, work-related stress, happiness, and performance, is evident. Workers feel motivated and show positive work-related behaviour when they perceive organizational justice procedures to be fair and impartial. In the opposite case, they feel demotivated, stressed, and show negative attitudes, which results in a decline in performance, commitment, and even may result in rude behaviour, and at times they may look for a better job in another organization ([50]).

The study of the given construct (Figure 1) is the conceptual framework, basically focusing on the question of what the interlink is between organizational justice and team performance.

Figure 1. Conceptual framework.

H1: Distributive justice significantly correlates with team performance.

H2: Procedural justice has a significant impact on team performance.

An actual framework of the inquiry and the direction about the research, useful in the investigation of the data for the scientific study, is known as Research Design ([48]). It is the Research Design that is adopted as the method for finding answers to the main questions asked in the research questions section of the study and to attain the purpose of the study. Information about data, size of sample, and ways and means to collect, analyze, and interpret results from the data are provided by the research design ([46]). The purpose and main motive behind the study were to test the hypotheses and study the impacts. Thus, a new, unique, and non-human-made phenomenon is tested in the research ([47]). A deductive approach is adopted, as the nature of the study is descriptive. Thus, it involves generalizing from the theme assumptions and then drawing conclusions regarding the exact assumptions through the support of relevant data and materials.

Data for this study were collected through a self-administered questionnaire. The population for this research consists of government employees working in public sector organizations across Pakistan. Due to the vast and geographically dispersed nature of this population, it was not feasible to conduct a census. Therefore, a convenience sampling strategy was employed.

Two public service-oriented government organizations located in the capital city of Islamabad, the Capital Development Authority (CDA) and the Federal Government Employees Housing Foundation (FGEHF), were selected as the sample for this study. The selection of these organizations was driven by several key factors. Both CDA and FGEHF are highly relevant and representative examples of public sector institutions in Pakistan, as they are instrumental in providing essential services (housing and urban development) to a large segment of the population. Furthermore, their location in Islamabad facilitated logistical ease, enabling the researchers to collect data within reasonable time and budget constraints while ensuring a focused and manageable study scope. The researchers secured the necessary access and permissions to conduct the survey within these two organizations, which was a critical consideration given the institutional access challenges often associated with public sector research. This focused approach on two prominent public service organizations in the capital city provides a meaningful and manageable sample from which to draw empirical conclusions.

Considering access, economy, and time constraints, convenience sampling was used as a technique of data collection. In this way, many respondents are reached with ease. When the population is not known, and data collection becomes a challenge, researchers use this technique of data collection. Researchers select members based on proximity and do not consider whether they represent the entire population or not. Through this technique, researchers acquire the desired views in a convenient way. In order to test the relationship of factors in the conceptual framework, 500 questionnaires were distributed among the target population. Time constraints were the main hurdle of the study. Through the usage of the convenience sampling technique, a large number of questionnaires, duly filled in, were collected with a relatively low cost and less effort.

This study had a unit of analysis as individuals working in the public sector organizations. The unit of analysis is the depiction of the level of collection of the collected data, which is further analyzed at a later stage of the study. Primary data was collected from responsible and reliable workers of teams in the government sector, employees of CDA and FGEHF of Pakistan to give their comments and responses about the factors of the developed conceptual framework.

After consulting the relevant literature regarding the selection of an adequate sample size for such studies, a sample was finally selected as mentioned in Table 1, comprising 500 personnel (working in teams) of the two public sector organizations (CDA and FGEHF), both located in the federal capital city of Pakistan, i.e., Islamabad.

Table 1. Breakdown of questionnaire’s statistics.

As already highlighted in the above paragraphs, the questionnaire (instrument used in this study) was basically adapted from earlier research. Organizational justice is measured in its two types, namely procedural justice and distributive justice. As shown in Table 2, the measurement elements of these concepts have been taken from studies such as organizational justice from the studies of [14] and [4], and for measuring the last concept of team performance.

Table 2. Instrument adoption.

In similar quantitative studies, the measures used to test the hypotheses are also quantitative. As highlighted by earlier researchers, the degree of stability is known as reliability, whereas the similarities in the outputs for a given time period are referred to as consistency of data. In order to have accurate results, it is imperative to know the reliability of the data used. For the sake of checking the consistency and reliability of this study, Cronbach’s alpha is used as a tool of measurement and testing. The value ranges from 0.00 to 1.00 for the reliability coefficients. Higher reliability is shown by a higher value of this coefficient. However, the value of 5.0 or higher falls in the acceptable range ([47]).

As per Table 3, Cronbach’s Alpha test was applied to the data, the result was a value of 0.903, which is much higher than the given minimum measure of 0.5, thus showing that the questionnaire was a very reliable one. It can be stated that the instrument, scale, and elements used for data collection in the research are very reliable, and the outcomes of data analysis are also reliable.

Table 3. Cronbach’s Alpha values for DJ, PJ, ItJ, and TP.

Three variables to know the demographic diversity of the respondents were also included in the sample, which allowed us to conduct descriptive analysis. The three variables were age, gender, and educational qualification of the respondents. Table 4 provides a comprehensive picture of the analysis of the demographic elements. It lists the frequencies, percentages, valid percentages, and cumulative percentages of males and females for gender, four different age brackets for age, and five different qualifications for academic qualification.

Table 4. Demographic descriptive with respect to gender.

Table 4 shows the gender of the public sector employees of CDA and FGEHF, of which 458 respondents were identified, 71.2% (326) were male and 28.8% (132) were female.

Table 5 shows the age of the public sector employees of CDA and FGEHF and represented that there were 458 respondents and from them25.8% (118) were between the age of 18 - 30 years, 41.9% (192) were between the age of 31 - 40 years, 18.3% (84) were between 41 - 50 years and 14% (64) were of the age between 51 - 60 years, which means that major chunk of the respondents belonged to the age bracket of 31 - 40 years.

Table 5. Demographic descriptive with respect to age.

Table 6. Demographic descriptive with respect to education.

Table 6 shows the educational qualification of the public sector employees of CDA and FGEHF and represented that there were 458 respondents and from them 18.1% (83) were matriculate, 17.5% (80) had completed intermediate, 25.3% (116) were graduates and 28.6% (131) were master’s degree holders and only 10.5% (48) had an M.Phil. or Ph.D. educational qualification level. This shows that most of the respondents had university-level education.

The current work model of linear regression was used to indicate the interrelationship between independent and dependent variables. The effect of IV on DV is observed via this model. The ideal model equation of linear regression should consist of the criterion known as BLUE (Best Linear Unbiased Estimator).

Table 8. Descriptive statistics of normality for OJ and TP.

The results of the analysis presented in Table 8 confirm the normality of the data distribution and allow us to confirm the assumption of normality of data, and hence, further processing of data for next-level analysis is recommended.

In linear data, the likelihood of committing big mistakes is less. Normally distributed residuals shown in Figure 2 confirm that the linearity assumption is achieved for the current research work. Thus, we can proceed further to the next level of analysis.

The next significant supposition of regression analysis is autocorrelation. The value of the Durbin-Watson test of the best fitted model with no autocorrelation must be below +2, and the R-squared value must preferably be within the range of 0 to 1 ([47]). Table 9 shows that the Durbin-Watson value is 1.813, which is less than +2. On the other side, R-squared and adjusted R-squared values are 0.66 and 0.058, which fall between 0 and 1. Thus, there exists no issue of autocorrelation in this study.

Figure 2. Normal P-P plot of regression standardized residual dependent variable: team performance.

Table 9. Model summary of DJ, PJ, ItJ, and IfJ with TP.

a. Predictors: (Constant), Distributive Justice, Procedural Justice; b. Dependent Variable: Team Performance.

The last but not least supposition of regression is multicollinearity. The interrelationship among the predictors is shown via Multicollinearity ([36]). Multicollinearity exists when two or more variables highly and assertively correlate with one another. Multicollinearity among the predictors gives birth to many issues during multiple regressions, thus making it almost impossible to ascertain the absolute importance of each factor of the study. Multicollinearity can be tested via two basic tests, one of which is the Variance Inflation Factor (VIF), while Tolerance is the other one. Tolerance is the other name given to the test of VIF. If the standard values of VIF are above 10, then the issue of multicollinearity exists in the data set. And if the value of Tolerance is less than 10, it is an illustration of a major problematic multicollinearity. As shown in Table 10, multicollinearity does not exist.

Table 10. Multicollinearity statistics for OJ and TP.

a. Dependent Variable: Team Performance.

Convergent Validity is constructed when an extraordinary correspondence is found between two different persons giving their views on the same thing. In the clarification of convergent validity, factor loadings are an important aspect. If the factor loads high, there are also higher odds of the convergence on the collective fact and on the same realities. The tool of convergent validity tells the number of elements that are loading in factor analysis. It represents the elements’ convergence, and it also denotes the collection of similar elements below one heading that have matching potentials and aptitudes. Moreover, it also displays the reply of selected components and furthermore stipulates acknowledgement of these elements, which are used again from the earlier research in this different setting. When there is a similar kind of answer and feedback of the designated sample to a particular measure and having an extraordinary link, the Convergent validity is established. To ascertain convergent validity, a factor analysis Questionnaire (Tool) is used.

Table 11. Construct validity.

In order to test the factors for correlation among them, Bartlett’s test of sphericity is a common statistical tool. Via this test, different matrices of correlation among the factors show a high link or no link is known. A significant value of 0.001 of Bartlett’s test indicates that a link or connection among the factors exists, and further analysis can be done.

As mentioned in Table 11, the squared partial correlation between the factors and the squared correlation between the variables is verified and confirmed by applying the Kaiser-Meyer-Olkin (KMO) test. Values range from 0 to 1. Zero value means the estimated total complete partial correlation is greater than the aggregate of total correlation, which verifies that the factor analysis is probably insufficient. 1 and the values approaching 1 display conservativeness, which is shown in the patterns of correlation. This shows that factors are loading effectively, and factor analysis provides reliable variables. [27] suggest that KMO values falling in the range of 0.7 and 0.8 are adequate. The KMO test was applied and is shown in the above table, which shows that all the loaded factors of this research are consistent.

An Exploratory Factor Analysis (EFA) was conducted to examine the construct validity of the measurement items for distributive justice (DJ) and procedural justice (PJ). Principal Component Analysis with Varimax rotation was applied.

The Kaiser-Meyer-Olkin (KMO) values were 0.855 for distributive justice and 0.726 for procedural justice, both exceeding the minimum acceptable threshold of 0.60 ([27]). Bartlett’s Test of Sphericity was significant (p < 0.001), confirming the suitability of the data for factor analysis.

As mentioned in Table 12, two factors emerged with eigenvalues greater than 1. The first factor explained 27.65% of the variance, while the second explained 17.95%, for a cumulative variance of 45.6%. While this percentage is somewhat lower than the recommended 50% - 60%, it still demonstrates moderate construct validity and is comparable to earlier studies using justice dimensions ([14]).

Table 12. Factor loading (OJ).

These results confirm that the measurement items clustered into two factors corresponding to distributive justice and procedural justice. Each factor exhibited strong internal consistency, as reflected in Cronbach’s alpha values of 0.889 (DJ) and 0.725 (PJ), supporting the reliability of the construct.

Table 13 shows the figures of R-square = 0.10, 0.16, 0.18, and 0.24 in that order, and displays F-value = 0.558, 29.095, 20.585, and 20.702 significant at 99% confidence level (p < 0.000). Thus, it indicates model fitness, and we can proceed with our analysis to the next level.

Table 13. Regression results for organizational justice predicting team performance.

Model Fit Statistics: R² = 0.066; Adjusted R² = 0.058; F(2, 455) = 16.14, p < 0.001; Durbin-Watson = 1.813. ns = not significant; *p < 0.01.

The regression analysis tested whether distributive justice and procedural justice predict team performance. Results showed that the overall model was statistically significant (F(2, 455) = 16.14, p < 0.001), explaining about 6.6% of the variance in team performance (R² = 0.066). Among the predictors, procedural justice had a significant positive effect on team performance (β = 0.258, p < 0.001). In contrast, distributive justice was not a significant predictor (β = 0.035, p = 0.41). These results provide partial support for the hypotheses: H2 (procedural justice → team performance) was supported, while H1 (distributive justice → team performance) was not supported.

To examine the impact of dimensions of organizational justice (distributive justice, procedural justice) on team performance. Results show that procedural justice has a significant relationship with team performance. However, distributive justice does not have a significant effect, indicating that employees place more emphasis on fair procedures than on outcome fairness in Pakistan’s public sector.

As mentioned in Table 14, the findings of this study reveal a significant relationship between procedural justice (PJ) and team performance (TP), while distributive justice (DJ) appears to have an insignificant effect on TP. This outcome is particularly insightful when viewed through the lens of Pakistan’s public sector.

Table 14. Table of results.

The significant positive relationship between PJ and TP suggests that in a bureaucratic environment, the fairness of the processes used to determine outcomes is more critical to team performance than the fairness of the outcomes themselves. This aligns with existing justice theory, which posits that in organizations with rigid hierarchies and fixed pay scales, employees are highly sensitive to how decisions are made. In the public sector of Pakistan, where promotions, resource allocation, and job assignments are often governed by established, formal procedures, employees may prioritize transparency and consistency. When they perceive the rules and decision-making processes as just—regardless of the final outcome—they are more likely to exhibit positive behaviors such as increased effort, trust, and commitment, which collectively enhance team performance. This is because a fair process signals that the organization values its employees and operates on principles of equity, fostering a stable and predictable work environment.

Conversely, the lack of a significant relationship between DJ and TP in this context is a key finding. Distributive justice refers to the perceived fairness of the outcomes or resource distribution (e.g., pay, promotions, bonuses). In the public sector, many of these outcomes are determined by standardized pay grades and strict seniority-based promotion policies, leaving little room for subjective or performance-based rewards ([11]). Therefore, employees may accept the predetermined nature of these rewards, making the perceived fairness of their distribution less of a motivational factor for team performance. The insignificance of this relationship suggests that for public sector employees in Pakistan, the fairness of “what they get” is less impactful on their work than the fairness of “how they get it” (the processes).

In summary, the results demonstrate that within Pakistan’s public sector, the procedural dimension of organizational justice is a stronger driver of team performance than the distributive dimension. This underscores the need for public sector managers to focus on enhancing procedural fairness by ensuring transparency, consistency, and equity in all decision-making processes.

Team performance has been the focus of numerous previous studies. Based on the statistical analysis presented, the study’s conclusions are limited to the findings regarding the direct relationship between organizational justice dimensions and team performance. The results indicate that procedural justice has a significant positive impact on team performance, while distributive justice does not. This suggests that within the specific context of Pakistan’s public sector, the perceived fairness of processes is more critical to team performance than the perceived fairness of outcomes.

Future research should specifically collect and analyze data that can examine these mechanisms, perhaps using hierarchical regression or mediation/moderation models (e.g., PROCESS macro). Such work would provide a more complete picture of how fair perceptions, leadership, and team dynamics collectively influence performance in public sector organizations.

The findings of this study offer several specific, actionable recommendations for managers and policymakers within Pakistan’s public sector.

Since the research found a significant link between procedural justice and team performance, managers should focus their efforts on enhancing the fairness of processes rather than on the outcomes alone. This involves ensuring transparency, consistency, and providing employees with a voice. For example, managers should make the criteria for promotions, task assignments, and resource allocation clear to everyone, which can help eliminate perceptions of favoritism. They should also apply rules and policies uniformly across all teams to build trust. Allowing employees to provide feedback on organizational procedures, perhaps through regular team meetings, can further enhance their sense of procedural justice.

Given the study’s focus on humility, leaders should actively model these behaviors. A humble leader who is open to feedback and acknowledges their mistakes can make employees feel more respected, which can strengthen their commitment and boost team performance. This creates a safe environment where team members feel comfortable collaborating and taking risks. By focusing on these practical steps, public sector managers should focus their efforts on enhancing the fairness of processes, since distributive justice was not found to significantly influence team performance in this study.

The current study explains the interrelationship among organizational justice (distributive justice and procedural justice). Moreover, this study was conducted on selected employees of only two public sector organizations, i.e., FGEHF and CDA, leaving behind many more public sector organizations with thousands of employees. Thus, this research does not explain the additional causes that might have a far more solid effect on team performance, apart from the organizational justice. The variable not taken into consideration may have a significant effect on team performance. The questionnaire was also a bit short to keep the interest of the respondents alive, as a long questionnaire does not get much welcome response. Some respondents had difficulties understanding the questions. For all these factors and the reasons stated, it is likely that similar research done in a more controlled setting may yield better results.

The study acknowledged as a limitation that the regression model’s R-squared value is 0.066, indicating that the justice dimensions explain only 6.6% of the variance in team performance. The study also acknowledged that the Exploratory Factor Analysis (EFA) resulted in a cumulative variance explained of 45.6%, which is noted to be below the conventional 50% - 60% threshold.

Public sector Organizations must adopt procedures and policies that can enable the employees to stay motivated. The organizations should promote such HRM policies through which fair and equitable distribution of resources is ensured. These organizations should opt for regular training and seminars regarding the positive role of leaders in creating a whole sense of “we” and not “only me”. Leaders must be trained to express a behavior that is in line with the contours of humility, which will create a sense of collective humility to enhance the performance of the teams.

Employees with such positive behavior should be encouraged and given preferential awards and rewards. Also, for future research, collective humility and leadership humility as mediators and moderators should be included in this model.

The framework of this research is important and will be helpful in the coming years to study the effect of organizational justice on team performance. For further study, other predictors can also be added to the independent variable role. More moderators can also be introduced in the same model to test the possible effect on the present construct. The current study was done only in Islamabad. Future researchers can collect data from all over the country to have better generalized results.