Factors influencing preferential treatment on academic performance of private universities in Mogadishu

This study aims to explore how favoritism affects students' grades at private universities in Mogadishu. It uses a quantitative approach involving interviews with 98 faculty members. The research team carefully collected data to ensure the results were reliable. They then analyzed the data using statistical software like SPSS and Smart PLS. The findings show that favoritism, along with nepotism and cronyism, negatively impacts students' academic achievements in these universities. This research adds to what we already know about the negative effects of preferential treatment, especially regarding nepotism, favoritism, and cronyism. It makes a significant contribution to discussions on how favoritism affects education, highlighting its harmful effects. The study also suggests that future research in Somalia could look at this issue in other cities to better understand its wider effects. While this study focused on how favoritism influences students' grades, it points out that future research could examine other factors like trust within the organization, employee commitment, the tendency of employees to remain silent, and staff turnover. These factors could offer further insights into the complex environment of private universities in Mogadishu and similar institutions around the world.


Introduction
*Both developing and developed countries have nepotism and favoritism in their workplaces (Vveinhardt and Sroka, 2020).Family, religion, caste, language, and social status influence loyalty (Iqbal and Ahmad, 2020).Multiple studies have linked an organization's unfairness and dishonesty to favoritism, nepotism, and a hostile work environment.Nepotism and favoritism are inevitable and hard to show (Ombanda, 2018).All industries share this unprofessionalism (Arasli et al., 2006).
Most Middle Eastern, Arab, and Turkish cultures practice tribalism, which fosters nepotism, favoritism, and cronyism based on clan networks, religion, and political allegiance (Caputo, 2018).Somalia has social and cultural connections with these countries, which makes them relevant.Additionally, nepotism and favoritism are common issues in African institutions, so it is important to increase awareness about these problems (Elbaz et al., 2018).Nepotism, favoritism, and cronyism are the most unethical and inequitable organizational practices in Africa, causing workers to leave or be fired from numerous organizations (Hudson et al., 2022).
Countries with significant corruption and low university competitiveness commonly hire and promote professors favoring or promoting relatives (Abramo et al., 2014).One such example was Italian higher education (Osipian, 2020).African research demonstrated political and educational elites exploited favoritism and nepotism to administer institutions (Akuffo and Kivipõld, 2019).Recent university research has found partiality in numerous academic domains (Aydogan, 2012;Hameed et al., 2020).Nepotism, favoritism, and cronyism are understudied locally and globally (Arasli and Tumer, 2008;Ombanda, 2018).Further research is needed to determine how these events relate to these factors at institutions worldwide (Vveinhardt and Sroka, 2020;Vveinhardt and Bendaraviciene, 2022).
Somalia has the highest unemployment rate at 54% and 75% youth unemployment.Favoritism, nepotism, and cronyism in public and private sector employment and selection have a long history of illegal activities and familial ties.A skills mismatch, lack of training and employment, and merit-based recruiting are also evident.Favoritism, nepotism, and cronyism have minimal empirical investigation (Khamis et al., 2020).No study in Somalia has examined the relationship between nepotism, favoritism, and cronyism and academic performance.Preferential treatment's effects on several organizational characteristics have been seldom studied, making this study important.Therefore, the researchers seek to examine the factors influencing preferential treatment on the academic performance of private universities in Mogadishu.
This study investigates factors influencing preferential treatment on the academic performance of private universities in Mogadishu with the following objectives: 1.The study aims to investigate how nepotism impacts the academic performance of private universities in Mogadishu.2. To identify the impact of favoritism on academic performance at private universities in Mogadishu.3. To study how cronyism impacts academic achievement in private universities in Mogadishu.

Preferential treatment
Preferential treatment refers to the practice of granting higher positions to individuals, including family members, close acquaintances, and those who share similar political beliefs, without regard to their qualifications (Kerse and Babadağ, 2018;Khamis et al., 2020).This concept is deeply intertwined with issues of discrimination and inequality.Moreover, it can manifest in various contexts, including employment, education, and government policies, and is often seen as a form of injustice that perpetuates disparities and hampers equal opportunities.Favoritism, nepotism, and cronyism are prevalent types of preferential treatment that are contingent upon the association between the entity and the recipient of the confidential treatment (Iqbal and Ahmad, 2020).
This study investigates the function of preferential treatment from three vantage points: nepotism, favoritism, and cronyism.While preferential treatment is often viewed as a mechanism to address historical injustices, it has sparked ongoing debate and controversy.Some argue that affirmative action policies, a form of preferential treatment, can redress inequalities (Kerse and Babadağ, 2018).However, critics question their effectiveness and raise concerns about reverse discrimination (Iqbal and Ahmad, 2020).

Nepotism
Nepotism comes from the Latin word "nepot," meaning nephew or grandchild or favoring one's kin when in a position of power or authority (Abdalla et al., 1998;Arasli and Tumer, 2008;Vveinhardt and Sroka, 2020;Shubayra et al., 2022).It involves granting positions, promotions, or opportunities to family members, often based on kinship rather than merit.Nepotism can have detrimental effects on workplace morale, productivity, and the overall fairness of decision-making processes.Furthermore, since the fourteenth century and until today, nepotism, favoritism, and cronyism have been significant problems (Iqbal and Ahmad, 2020).
The notion of nepotism, which describes the abuse of office to benefit members of one's own family, is regarded as unprofessional in the workplace context (Spranger et al., 2012;Aydogan, 2012;Caputo, 2018).Nepotism is the actual or perceived favor given by one family member over another (Elbaz et al., 2018;Kerse and Babadağ, 2018).Nepotism removes and pressures people to leave an institution (Iqbal and Ahmad, 2020).Moreover, in academics, recruiting and interacting with close relatives is also called nepotism (Allesina, 2011).However, nepotism is a preference for friends, relatives, or political allies (Serfraz et al., 2022).The present study provides a definition of nepotism as the practice of hiring individuals who are related to one another within the same organization or utilizing familial connections to secure employment for them within external organizations.
Nepotism manifests itself in various ways, including relative nepotism, friend nepotism, connection nepotism, contribution nepotism, and referral nepotism, all forms of nepotism (Ombanda, 2018).According to Vveinhardt and Sroka (2020), scholars have categorized nepotism into two different types based on the selection process employed, namely entitled and reciprocal nepotism.
Nepotism is common in developing and developed countries and many private institutions and is considered unprofessional (Arasli and Tumer, 2008;Kerse and Babadağ, 2018).Most studies agree that nepotism is more common in collectivist cultures where social, educational, economic, and political structures inspire individuals to support relatives and friends (Elbaz et al., 2018;Vveinhardt and Sroka, 2020).
Nepotism can directly affect the motivation of employees and may influence their behaviors and intentions.This includes their likelihood of wanting to leave their job and spreading negative opinions about their workplace (Arasli et al., 2006).Nepotism lowers employee morale and causes family disputes and sibling rivalries (Abdalla et al., 1998).Shubayra et al. (2022) indicated that the presence of nepotism in an organization could result in lower productivity, reduced trust among employees towards the organization, a decrease in professionalism, and could ultimately contribute to the risk of institutional failure.Ombanda (2018) discovered four crucial adverse influences of nepotism in companies in his studies on institutional commitment: Employee dissatisfaction, excessive staff turnover, team distrust, and employee disputes.Nepotism is prohibited in specific workplaces as a matter of ethics because it is too disruptive and bothersome (Ombanda, 2018).Finally, nepotism is a disease that has spread throughout society, including academics.It may be a severe problem in systems where career promotion is based on seniority rather than achievements (Allesina, 2011).Additionally, most previous nepotism studies have been undertaken at the macro level (Abdalla et al., 1998;Arasli and Tumer, 2008).Hence, this study aims to explore the issue at the micro level.Based on a thorough review of pertinent theoretical literature, this paper proposes the following research hypothesis: H1: Nepotism is negatively related to the significant academic performance of private universities in Mogadishu.

Favoritism
Favoritism has existed throughout history, including among the Sumerians, Romans, Greeks, Archaic Chinese, Indians, and Greeks, as well as in the Middle Ages, and it is still present in the globe today (Çarikiçi et al., 2009).Favoritism derives from the Latin word for giving a nephew or grandchild various jobs based on relationships rather than qualifications (Khamis et al., 2020;Vveinhardt and Sroka, 2020).
"Favoritism" refers to giving preferential treatment to certain officials or employees over others (Safina, 2015).Favoritism is giving friends and acquaintances preferential treatment in career, job, and personnel decisions (Iqbal and Ahmad, 2020;Vveinhardt and Sroka, 2020).In addition, the definition of favoritism is that a person is given preference because of a privilege, not because they are the most qualified in their profession (Çarikiçi et al., 2009).This study adopts the definition from Çarikiçi et al. (2009).
Favoritism is a more comprehensive phrase than nepotism, even though the two terms are commonly interchanged within the context of scientific literature (Vveinhardt and Sroka, 2020).Favoritism is a broad idea discussed in many ways, such as nepotism, cronyism, partisanship, clientelism, and patronage (Dagli and Akyol, 2019).Nepotism, cronyism, and patronage are the three subcategories that fall under the broader category of favoritism (Aydogan, 2012;Karakose, 2014;Elbaz et al., 2018).Favoritism can be divided into political and relative favoritism (Çarikiçi et al., 2009).There are three types of favoritism: Nepotism, in which family members are given preference; cronyism, in which friends are given priority; and patronage, in which political parties exert effect to select their friends or relatives (Karakose, 2014;Hameed et al., 2020).In addition to these three points of view, favoritism may also be seen regarding a person's socioeconomic level or when people in similar social and economic standings favor one another (Aydogan, 2012).
Someone's race or ethnicity can also cause favoritism because they went to the same college or are in the same group (Khamis et al., 2020).Another similar problem is favoritism, which is giving special treatment to close friends instead of giving everyone the same treatment (Abdalla et al., 1998;Arasli et al., 2006;Abubakar et al., 2017).
Favoritism harms managerial transparency and renders the organization a closed or partially closed system (Aydogan, 2012).It is suggested here that bias at work could cause job stress and raise staff dissatisfaction (Arasli and Tumer, 2008;Shubayra et al., 2022).The opinions of academic members regarding the existence of favoritism at institutions of higher education were presented in both written and visual forms.Also, it was noted that there have only been a handful of research projects on favoritism in the educational system (Aydogan, 2012).The present study proposes the following research hypothesis based on a thorough evaluation of the relevant theoretical literature: H2: Favoritism is negatively associated with the substantial academic performance of private universities in Mogadishu.

Cronyism
Cronyism is a general term for preferential treatment (Aydogan, 2012;Shubayra et al., 2022).Cronyism means giving politicians an advantage over others (Arasli and Tumer, 2008).Cronyism also refers to the preferential treatment of people with similar political views (Iqbal and Ahmad, 2020).Cronyism is defined as one friend's actual or perceived preference for another (Elbaz et al., 2018).This study adopts the definitions by Iqbal and Ahmad (2020) and Elbaz et al. (2018).
According to Khatri and Tsang (2016), cronyism is a form of favoritism in which an employer attempts to build a team of persons that can be simply managed and influenced in decision-making.Depending on the context, different academics use terms to describe cronyism, such as nepotism, favoritism, and patronage (Yu et al., 2023).
Cronyism increased stress within the institution and, as a result, led to lower job satisfaction, reduced institutional performance, and decreased employee morale (Arasli and Tumer, 2008;Pearce, 2015;Shubayra et al., 2022).Numerous studies show that cronyism negatively impacts institutional performance (Pearce, 2015).After an extensive literature study, it was demonstrated that cronyism affects worker satisfaction and turnover intentions in the banking, family business, and hotel industries.
However, no research has been done on higher education organizations in needy nations like Somalia (Iqbal and Ahmad, 2020).Based on an indepth analysis of the relevant theoretical literature, the current study proposes the following research hypothesis: H3: Cronyism causes a negative sign in the academic performance of private universities in Mogadishu.

Academic performance
Performance can be defined as the productive exertion of an employee towards the attainment of a specific objective through the successful execution and completion of a task to a satisfactory level (Ombanda, 2018).Academic performance has defined the capacity of institutions to fulfill their aims and objectives (Abubakar et al., 2018).According to the purpose of this study, performance is defined as the consequence of a person's results and outputs; consequently, an employee's job is contingent on achieving the organization's objectives.
The notion of performance is essential and crucial to organizations as a whole.It is universal and necessary for various institutions to focus on their existence (Abubakar et al., 2018).Quantitative and qualitative scores about the goals for a particular activity measure the performance of an individual, group, and institution (Ombanda, 2018).The findings of various scholarly researchers show that the performance of an individual is closely linked with the characteristics of their job and the effective administration of the multiple procedures involved in accomplishing the desired outcome.Research indicates that the efficacy of an organization is closely linked to the productivity of its workforce, and suboptimal outcomes may ensue from workplace deficiencies such as the recruitment and retention of unsuitable personnel (Ombanda, 2018).

Preferential treatment and academic performance
Nepotism can benefit small and family-owned businesses by providing an efficient way to recognize loyal employees and organizational effectiveness and enhance job satisfaction.Working with a relative can assist small businesses in establishing a robust communication network and fostering a family-friendly environment (Abdalla et al., 1998).There is evidence that nepotism among family businesses can have beneficial and harmful consequences (Serfraz et al., 2022).
In opposition to these beneficial impacts, nepotism may result in non-family employees losing faith in and commitment to their bosses (Serfraz et al., 2022).This behavior is a significant barrier to the advancement of the organization, and it encourages employees to look for other employment opportunities (Abubakar et al., 2017).
Favoritism occurs in organizations based on social and familial ties, and these connections inspire staff members to show partiality (Iqbal and Ahmad, 2020).Favoritism can also lead to low productivity, team mistrust, and employee conflicts if the leader overlooks a skilled worker and fails to use their talents for the job and the business's success (Ombanda, 2018).From the perspective of promotion, favoritism offended work satisfaction and turnover intention (Arasli et al., 2006).In conclusion, several research studies show signals favoring these conversations or arguments.Research by Arasli and Tumer (2008) found that favoritism hurts work satisfaction in both public and private institutions.
The management of cronyism can be a difficult task, particularly in societies that prioritize personal connections, particularly with cronies, who are defined as close friends of long-standing.This is evidenced by the appointment of political associates to positions of authority without consideration for their credentials, as noted by Arasli and Tumer (2008).According to Arasli et al. (2006), research has shown that cronyism has an undesirable connection with work satisfaction.
Numerous studies have addressed the topics of nepotism, favoritism, and cronyism from various perspectives, concentrating on multiple aspects.However, most academics emphasize the negative aspects of nepotism, cronyism, and favoritism (Vveinhardt and Sroka, 2020).Favoritism, nepotism, and cronyism involve preferential treatment, cause unfair competition, lower job satisfaction, and increase turnover intentions, family disputes, organizational commitment, and work stress (Elbaz et al., 2018;Kerse and Babadağ, 2018).Also on the rise are instances of favoritism, nepotism, and cronyism in private institutions, as well as the attendant conflicts and staff demoralization that result from these phenomena (Caputo, 2018).Furthermore, the researchers also find an inverse association between work satisfaction and turnover intention (Arasli and Tumer, 2008).Finally, nepotism, favoritism, and cronyism are immoral actions leaders utilize to fulfill their self-interest against the institution's general interest (Iqbal and Ahmad, 2020).

Theoretical framework
This research is based on the stewardship theory.According to Davis et al. (1997), the theory posits that managers prioritize the best interests of principals due to the belief that by acting in the best interest of the organization, they can enhance their prospects for accomplishments and fulfill their selfactualization needs.According to this theory, there is a strong and positive correlation between an organization's performance and a manager's success (Shattock, 2008).This study employs the stewardship theory as it is deemed more suitable for non-profit organizations, particularly in the context of higher education (Lokuwaduge and Armstrong, 2015).

Research model
Practices of nepotism, favoritism, and cronyism are also big issues in the academic sector, particularly at private universities; this is the case in any industry that is based on human interaction.This study aimed to examine the impact of nepotism, favoritism, and cronyism on the academic performance of private universities.To achieve this objective, a comprehensive literature analysis was done, and a research model was then developed.The developed model included factors such as nepotism, favoritism, and cronyism in the domains of literature, teaching, and research performance, which were added to the variable of academic performance.These variables were then combined with the variable of academic performance, which was hypothesized to be related, but no evidence of this association was found in the existing literature.The picture presents a model that has been designed to examine the impact of nepotism, favoritism, and cronyism practices on the academic performance of private universities.
According to empirical research, there is a linkage between nepotism, favoritism, and Cronyism and academic performance.The question of whether the connection is positive or negative emerges.Fig. 1 displays this connection and attempts to demonstrate whether it is positive or negative.It shows a direct solid association between preferential treatment and academic performance.The conceptual research model of this study is shown in Fig. 1.

Introduction
This section describes the methodologies and procedures used to perform this study.The research design, study population, and sample methods cover.The data types and sources are explained, as well as data gathering techniques and how reliability is ensured.It also outlines how the variables in the research are measured.The data were analyzed utilizing SPSS and Smart PLS.The findings have been organized and presented in tabular format, encompassing various aspects, including demographic information, as well as measurement and structural outcomes.

Paradigms
The primary aim of this study is to elucidate the causal relationship between preferential treatment and academic performance.In this regard, the positivism paradigm approach is deemed most appropriate.Through the lens of the positivist approach, it can be asserted that this study adopts a quantitative methodology, employing a deductive approach to formulate its testable hypotheses.The findings of this study are intended to be generalized to the entire population.The theory of stewardship serves as a guide for analyzing the relationships between variables.

Research design
The purpose of this study is to present a comprehensive picture of the effects of preferential treatment on academic performance.The survey uses an explanatory research technique whereby preferential treatment and academic performance may be assessed as they occur naturally.Descriptive research aims to explain why events occur and generate, expand, refine, or test hypotheses.Also, offer actual data to support or reject (Neuman, 2020).This study uses an explanatory research methodology to determine the strength of the relationship between preferential treatment and academic performance.However, descriptive research examines a situation or problem to explain the correlations between variables (Saunders et al., 2009).

Target population
The present research focuses on preferential treatment and academic performance at Mogadishu's private universities.Somalia's central government disintegrated in 1991, triggering a civil conflict that harmed higher education and other institutions.In 1999, the local community, diasporas, religious groups, and international nongovernmental organizations worked together to reestablish the higher education system (HIPS, 2013).The higher education sector is growing in Somalia's central city of Mogadishu, where 20 private universities coexist with one state-owned university (HIPS, 2013).Mogadishu has 40 private universities.Another statistics study states that Mogadishu has one state-owned and 62 private universities.The researcher's selection process involved choosing two universities out of 62, based on their notable student and faculty populations and student with lecturer ratio.Additionally, these universities were among the earliest establishments in Mogadishu, as reported by HIPS (2013) and GPE (2017).All Somali institutions had 2,501 lecturers, and although there are varied numbers of lecturers at universities, the chosen universities had 342 lecturers (HIPS, 2013; GPE, 2017).

Sample size
Due to the needed costs and time, covering the targeted population may not be possible; a sample is taken from various universities.The survey's private university representation was calculated, providing a target population of 342 employees.Krejcie and Morgan's (1970) table for choosing the sample size of research activities suggested a sample size of 181 for a population of 342.

Method of data collection
The researchers utilized a combination of secondary and primary data for the purposes of this study.The primary instrument employed for data collection was questionnaires.A questionnaire is a method of gathering data in which a specific group of individuals is chosen to answer a standardized set of questions in a predetermined sequence (Saunders et al., 2009).The study employed structured questionnaires utilizing a five-point Likert scale.The researchers distributed a structured questionnaire to the members of the senate and faculty of private universities in Mogadishu.A collective sum of 181 individuals was engaged within the context of private universities in Mogadishu.However, the data from a total of 98 individuals who completed the required information accurately were subjected to analysis.Secondary data is derived from scholarly sources such as journals, books, and reports originating from various institutions of higher education.

Measurement instrument and questionnaire design
The research instrument utilized in this study consisted of a survey questionnaire that demonstrated both validity and reliability.The current study utilized all primary constructs that were validated in prior research.In accordance with this, questionnaire forms have been produced.The questions utilized in this study were derived from previous research and were selected based on their high levels of validity and reliability.
The measurement scales for this study are based on previous research.The nepotism scale includes 16 items, adapted from studies by Abdalla et al. (1998), Ombanda (2018), Kerse and Babadağ (2018), and Bekesiene et al. (2021).To assess favoritism, 16 items were taken from research conducted by Abubakar et al. (2017), Ombanda (2018), andElbaz et al. (2018).The cronyism scale comprises four items derived from Arasli and Tumer (2008) and Serfraz et al. (2022).For measuring academic performance, nine items were utilized from a study by Abubakar et al. (2018).Responses for all items were collected using a five-point Likert scale, which ranges from "strongly disagree" to "strongly agree."The total number of items used in the study was 45.

Data analysis
In this study, both descriptive and inferential statistical methods were employed.Descriptive statistics were initially utilized to analyze the demographic characteristics of the study participants using the Statistical Package for the Social Sciences (SPSS).The SPSS version 23 was employed to conduct the preliminary data screening, which involved checking for missing values and ensuring the integrity of the data prior to analysis.In addition, Smart PLS version 4 was utilized to validate the study's model, and the researchers employed measurement modeling and structural modeling techniques to analyze the data.In addition, the measurement modeling approach was utilized in order to evaluate the reliability and validity of the instrument.Following this, a study was conducted using structural modeling to analyze the interconnections between the variables employed in the research model.

Demographic information
Before reviewing the data and identifying missing values, researchers conducted a data screening.As a result of using the Google form and requiring respondents to answer all questions, the researchers eliminated all missing data values.In addition, seven respondents with identical responses indicating disengagement were eliminated from the analysis.
Table 1 provides the study's demographic information.The study examined seven demographic variables to gather background information on the participants.The first variable, gender, showed a majority of men, with 84 out of 98 participants being male, reflecting a workforce demographic skewed towards men due to cultural norms in the country.
Age was the second variable, with the participants distributed across three age groups: 35 were under 30 years, 35 were aged 31 to 35 years, and 28 were over 36 years.This suggests a young workforce, primarily between 25 and 35 years old.
Marital status was the third variable, indicating a majority of married individuals (70 out of 98) aligned with the cultural practice of marrying early, typically in the early thirties.
The fourth variable, job title, revealed a composition of 46 senior academics, 32 in management or administration, and 20 as junior lecturers, indicating a low proportion of junior faculty members.
For the fifth variable, education level, the majority of the 98 respondents (74) held a master's degree, with a smaller number having a bachelor's degree (13) or a Ph.D. ( 11).This highlights a significant concentration of master's degrees among respondents and a notable scarcity of Ph.D. holders in Mogadishu's private universities.
The sixth variable, job experience, was categorized into three groups: 36 participants had less than six years of experience, another 36 had between six to ten years, and 26 had more than eleven years, showing a range of experience levels among the staff.
Lastly, the seventh variable, employment status, showed that the majority (76 out of 98) were permanent employees, with 18 part-time employees and four special contractors, indicating a predominance of permanent positions and limited use of special contractors in these universities.

The measurement model
The Measurement Model comprises the examination of the constructs' quality, encompassing the evaluation of both reliability and validity.The evaluation of the reliability and validity of the measurement model encompassed the analysis of multiple indicators, such as factor loadings, composite reliability (CR), average variance extract (AVE), discriminant validity, and VIF for detecting multicollinearity.The results of the study are presented in Tables 2 and 3.

Constructs loadings, CR, AVE, and VIF for multicollinearity
Prior to analyzing the data, the measurement model underwent validation.The researchers assessed the construct validity and internal consistency of the model.Following Chin's (1998) guidance, factor loadings between 0.5 and 0.7 were deemed acceptable.According to Hair et al. (2019), indicators should only be considered for removal if their factor loadings range between 0.40 and 0.70, and their elimination would enhance the model's internal consistency or convergent validity.The analysis showed that 16 indicators met the required threshold, with factor loadings from 0.591 to 0.852, which is within the acceptable limits.Additionally, Hair et al. (2019) suggested that the average variance extracted (AVE) should be no less than 0.5 to confirm convergent validity.The AVE values across all constructs varied from 0.518 to 0.625, indicating satisfactory results.The study found that all values surpassed the minimum acceptable threshold.For reliability testing, CR was preferred over Cronbach's alpha due to its more accurate approximation.The evaluation of construct reliability demonstrated that all constructs had values above the .70threshold required, with CR values ranging from 0.755 to 0.871, which is acceptable.Two methods were applied to assess discriminant validity, as detailed in Table 3.

Validity
The concept of validity pertains to the assessment of whether a scale accurately and reliably captures and measures the intended construct.Construct validity is evaluated by determining both convergent and discriminant validity (Henseler et al., 2015;Sarstedt et al., 2022;Hair et al., 2019).Convergent validity pertains to the degree to which a latent construct adequately explains the variability observed in its indicators (Hair et al., 2019).Convergent validity is established by employing two distinct methodologies, namely factor loading and average AVE, as demonstrated in Table 2.
Discriminant validity pertains to the extent to which a given construct is empirically distinguishable from other constructs (Hair et al., 2019).Hence, the confirmation of discriminant validity indicates that a construct exhibits unique attributes and encompasses phenomena that are not explained by other constructs within the model (Hair et al., 2019).Chin (1998) and Fornell and Larcker (1981) have introduced two approaches for assessing discriminant validity in Partial Least Squares (PLS) analysis.To establish discriminant validity in SMART-PLS, three specific methods are used: the Fornell-Larcker Criterion, Cross Loadings, and the Heterotrait-Monotrait (HTMT) Ratios (Henseler et al., 2015).The application of the Fornell-Larcker criteria is illustrated in Table 3.
The Fornell-Larcker criteria is a widely recognized approach utilized to assess the discriminant validity of a model.The AVE square root of all variables is calculated using the Fornell-Larcker criterion, which states that the correlation between variables should be higher (Hair et al., 2019).The independence of all constructs is demonstrated, thereby providing confirmation of the presence of discriminant validity.The findings of the study indicate that the model exhibits a significant level of discriminant validity, as depicted in Table 3.The research utilized the heterograft HTMT as a tool to evaluate the discriminant validity, as demonstrated in Table 4.
The HTMT correlation ratio, as discussed by Hair et al. ( 2019), shows that the values obtained from the HTMT ratio test are below 0.90.This outcome suggests that discriminant validity is achieved, confirming that all constructs within the study are distinct and independent from each other.Consequently, the findings of the study demonstrate that the model possesses a strong level of discriminant validity.

Structural model analysis
The assessment of the structural model is a pivotal phase that involves ascertaining the significance and relevance of the proposed structural relationships.In order to assess the efficacy of the model, a range of metrics were utilized, as recommended by Hair et al. (2019).The measures employed in this study encompassed the evaluation of collinearity among the constructs, calculation of the coefficient of determination (R2), and examination of the significance and relevance of path coefficients.Detailed information regarding each step is presented in the subsequent sections.

Collinearity
Prior to conducting hypothesis testing, a comprehensive collinearity diagnostic was employed to assess the presence of common method bias.This was necessary as the data was obtained from a single source utilizing an identical instrument.The results presented in Table 2 indicate that all variables have Variance Inflation Factor (VIF) values that are below 5, in accordance with Vinzi et al. (2010) explanation that VIF values should be less than 5. Hence, the present study does not exhibit any concerns regarding common method bias.Table 2 presents a summary of the collinearity diagnostics.

The coefficient of determination (R2)
The coefficient of determination (R2) is the most commonly employed metric for assessing the explanatory power of a structural model (Hair et al., 2019).The coefficient of determination (R2) evaluates how effectively a statistical model predicts an outcome.The model's dependent variable represents the result.The study's findings are presented in Table 5. Falk and Miller (1992) suggested that R2 values should be equal to or higher than 0.10 in order to be considered acceptable.In social science research, an R-square between 0.10 and 0.50 is acceptable only when some or the majority of the explanatory variables are statistically significant (Ozili, 2023).As presented in Table 5, the magnitude of the R2 value for the academic performance variable is .124.This would indicate that 12.4% of academic performance variations are influenced by preferential treatment dimensions such as nepotism, favoritism, and cronyism.

The significance and relevance of path coefficients
The bootstrapping method, employing 5000 resamples, was utilized to evaluate the significance levels (p values) of the study.The analysis revealed that the relationship between nepotism and academic performance is negative but not statistically significant (p-value = 0.087; p > 0.05), thus supporting Hypothesis 1 (H1).Similarly, the association between favoritism and academic performance is negative and not statistically significant (p = 0.057; p > 0.05), thereby supporting Hypothesis 2 (H2).The findings also show that the link between cronyism and academic performance is negative and statistically insignificant (p = 0.398; p > 0.05), supporting Hypothesis 3 (H3).These outcomes indicate that the dimensions of preferential treatment do not significantly impact academic performance, as presented in Table 3 and further detailed in Table 6 of the study.

The effect of nepotism on academic performance
According to the study's findings, nepotism had an insignificant impact on academic performance.The p-value in this research is 0.087, indicating that a high level of nepotism would reduce academic performance in Mogadishu's private universities.In academics, the practice of recruiting and cooperating with close relatives is sometimes referred to as nepotism (Allesina, 2011;Keles et al., 2011).Recruitment in terms of nepotism stated that nepotism affects not only current workers but also professional managers, who are frequently deterred from entering a business because of measures that favor employees with relatives in top management (Akuffo and Kivipõld, 2019).This demonstrates that nepotism may have effects on academic performance.Similarities exist between this study's findings and those of prior studies (Arasli and Tumer, 2008;Ombanda, 2018;Serfraz et al., 2022).

The effect of favoritism on academic performance
The study revealed that favoritism negatively affected academic performance.In this study, the pvalue is 0.057, showing that a high prevalence of nepotism lowers academic performance at Mogadishu's private institutions.Favoritism is giving special treatment to friends, colleagues, and acquaintances in employment, career, and personnel decisions (Arasli and Tumer, 2008;Iqbal and Ahmad, 2020;Vveinhardt and Sroka, 2020).Furthermore, favoritism has several adverse effects on employees, including employee resentment, indifference, loss of self-confidence, loss of abilities, sense of social alienation, constant fear and pessimism, termination of competent workers, ineffective solutions for human resources planning, weak competition among workers, a lack of teamwork, weakness of creativity, innovation, and organizational culture, as well as a detrimental effect on the decision-making process (Elbaz et al., 2018).This implies that favoritism will have a damaging impact on academic performance.The findings of this study are comparable to those of earlier studies by Arasli and Tumer (2008) and Ombanda (2018).

The effect of cronyism on academic performance
Based on the findings of the study, it was determined that cronyism had a negative and significant impact on academic performance.The pvalue of this study is 0.398, indicating that cronyism has a negative effect on academic performance at private universities in Mogadishu.Cronyism diminishes people's efficiency and effectiveness since they are not rewarded based on their aptitude or expertise (Iqbal and Ahmad, 2020).Furthermore, Cronyism undermines employee confidence and motivation and increases the desire to resign.This indicates that cronyism influences academic performance.This means that if cronyism happens, it will hurt academic performance.The findings of this study are consistent with those of earlier studies (Arasli and Tumer, 2008;Pearce, 2015;Iqbal and Ahmad. 2020).

Conclusions and suggestions
This study identifies a negative relationship between nepotism and academic performance, demonstrating a statistically significant correlation that suggests nepotistic practices in private universities in Mogadishu adversely affect their academic outcomes.Similarly, favoritism is found to have a significantly negative impact on academic performance, indicating that preferential treatment in these institutions likely leads to poorer academic results.Additionally, cronyism is significantly linked to decreased academic performance, highlighting that the more prevalent such practices are in Mogadishu's private universities, the more likely academic performance is to suffer.Based on these findings, the study advises that private universities should promote equal treatment for all and actively work to eliminate nepotism, favoritism, and cronyism within the educational system.Managers should be aware of the perceptions of nepotism, favoritism, and cronyism and ensure fair treatment in career advancement, compensation, and performance evaluations.
The research focuses on the impact of preferential treatment on academic performance, specifically within the context of Mogadishu's private universities.Thus, generalizing these results globally may be challenging.Future research could extend to other cities in Somalia to broaden the understanding of these dynamics.This study emphasizes the need to explore additional factors such as organizational trust and commitment, employee silence, and staff turnover in further research.While this study relied solely on quantitative methods, future research could benefit from a mixed-methods approach to gain a more comprehensive insight into the effects of preferential treatment on academic performance.

Ethical considerations
Important ethical issues were considered before and during the study.Confidentiality was maintained throughout data collection, management, and analysis.To make participants feel comfortable giving their ideas, they were notified of anonymity and confidentiality.Participant confidentiality was maintained during data analysis.Participants were informed of the study's goal, objectives, importance, and other relevant information before consenting.This approach was taken to ensure that all participants received enough information and could independently select whether to participate without researcher interference.After completing the questionnaire, researchers thanked the responders.

Table 1 :
Demographic information

Table 5 :
The coefficient of determination (R2) The model's dependent variable represents the result

Table 6 :
Structural model results (Direct relationships)