Impact of Funding Sources on Institutional Performance in Nigerian Higher Education

Impact of Funding Sources on Institutional Performance in Nigerian Higher Education | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of Funding Sources on Institutional Performance in Nigerian Higher Education Olugbenga Olowoye This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7091781/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The assessment of university funding adequacy reveals a critical and multifaceted crisis affecting higher education institutions globally. Based on a comprehensive survey, this paper examined ten key operational areas within selected universities. The analysis presents alarming evidence of systematic underfunding across all measured domains, with particularly severe deficiencies in physical infrastructure maintenance and support services. This paper thus leveraged on Donabedian model and SERVQUAL to assess the funding sources available to the Universities. The findings demonstrate that current funding mechanisms are fundamentally inadequate to support the complex operational requirements of modern universities, with profound implications for educational quality, institutional sustainability, and national development goals. Specifically, five major factors were extracted as capable of influencing institutional performance relative to funding. These include finance, employee competencies, infrastructural development, Quality of Service (QoS), and ethical standards. Together, these factors account for 62.12% of the total variance in institutional performance, indicating that they collectively explain a significant proportion of the variability observed across institutions. The multimodal regression used to consolidate the results shows that federal universities tend to have better physical facilities compared to private universities. However, QoS plays a significant role in shaping perceptions of private universities. Employee competence and responsiveness is a key distinguishing factor specifically for state universities. In terms of funding adequacy, state universities are 49.6% more likely than federal universities to be perceived as adequately funded. Private universities stand out even more in this regard, being 280.1% more likely to be considered financially adequate than federal universities. These findings highlight the varying strengths and challenges across federal, state, and private university systems in key performance areas. These insights call for urgent policy reforms and strategic investments to address the disparities in university funding and performance. Strengthening institutional capacity across all sectors is essential to achieving equitable, high-quality higher education aligned with national and developmental priorities. Finance Analysis Operations Research Leadership and Ethics Figures Figure 1 1. Introduction The relationship between funding sources and institutional performance in Nigerian higher education represents one of the most critical challenges facing the country's educational development trajectory. As universities and other tertiary institutions navigate an increasingly complex landscape of financial constraints and expanding enrolment demands, understanding how different funding mechanisms influence institutional outcomes has become paramount for educational stakeholders and policymakers alike. Nigerian higher education faces significant justifications for re-engineering, including the need to address funding, infrastructural, and management issues (Wike, 2024). This funding crisis has created a multifaceted challenge where poor recruitment practices, inadequate training programs, political interference, and limited funding (Mafindi, 2024) collectively undermine institutional effectiveness. The complexity of this situation is further compounded by the diverse array of funding sources available to Nigerian institutions, each carrying distinct implications for institutional autonomy, academic quality, and long-term sustainability. The Nigerian higher education funding ecosystem comprises multiple stakeholders and mechanisms, including government educational agencies such as the National Universities Commission (NUC); National Board for Technical Education (NBTE); National Commission for Colleges of Education (NCCE) and Tertiary Education Trust Fund (TETFund) (Ngonso, 2022). These agencies play crucial roles in both funding allocation and institutional oversight, creating a complex web of accountability relationships that significantly influence how institutions operate and perform. International research on funding mechanisms provides valuable insights for understanding the Nigerian context. Studies from other developing countries demonstrate that in education finance, the sources of funds and the size of the resources are key determinants of quality education (Mutiso, 2015). Furthermore, evidence suggests that performance funding consistently benefits high-resource institutions and imposes financial burdens on low-resource institutions (Hagood, 2017), raising important questions about equity and access in funding distribution models. The performance implications of different funding sources extend beyond simple resource availability. Research indicates that although competition-based funding is widely applied, traditional factors such as student enrolment and budget history still influence funding decisions (Shin, 2022), suggesting that even innovative funding approaches may perpetuate existing institutional hierarchies and performance patterns. This phenomenon has relevance for Nigerian institutions, where historical underfunding and infrastructural deficits may limit their ability to compete effectively for performance-based resources. The strategic responses of institutions to funding constraints reveal the adaptive capacity of higher education organisations. Rather than choosing between different funding streams, universities are adapting to the conditions of their funding environments (Kohtamki, 2023), often developing mixed funding portfolios that combine government appropriations, student fees, research grants, and private partnerships. However, addressing funding issues is vital for enhancing staff commitment and productivity, ultimately fostering institutional success and academic excellence (Mafindi, 2024). The urgency of addressing funding challenges in Nigerian higher education cannot be overstated. Despite the implementation of entrepreneurship skills development programmes in Nigerian higher education institutions in response to the National Universities Commission (NUC) policy, the sector has failed to equip graduates with the capacity to venture into enterprise activities and the creation of valuable products and services. (Agwu, 2025) Hence the lingering high rate of unemployment and the poor state of development of the Nigerian small business sector. This performance gap underscores the critical need for more effective funding strategies that can support institutional capacity building and educational quality enhancement. Understanding these complex relationships between funding sources and institutional performance is essential for developing evidence-based policies that can transform Nigerian higher education into a more effective, equitable, and globally competitive system. The research problem centers on the limited evidence that performance funding improves student outcomes, despite its widespread adoption and political support. Implementation obstacles, unintended consequences, and variations in program design contribute to the lack of clear impact, highlighting the need for a more nuanced and context-sensitive approach to performance funding. Addressing these challenges requires a comprehensive evaluation and refinement of performance funding policies, considering the diverse missions and goals of higher education institutions. Although evidence suggests that performance funding does stimulate colleges and universities to substantially change their policies and practices, it is yet unclear whether performance funding improves student outcomes. This study is thus set to achieve two objectives, first to assess the extent of available funding to different units and programmes in the University as well as to investigate the factors responsible for institutional performance relative to funding sources. 2. The Impact of Funding Adequacy on Educational Infrastructure and Institutional Performance in Developing and Underfunded Systems. Educational funding adequacy is a cornerstone of institutional effectiveness and educational quality. In both developing and developed contexts, persistent underfunding remains a systemic challenge. This is especially true in settings where public budgets are constrained, governance mechanisms are inflexible, and political priorities shift frequently. Research from developing education systems offers valuable insights into the multifaceted consequences of underfunding and potential policy responses. In Kazakhstan, for example, the higher education sector faces critical barriers to development, including financial constraints, outdated scientific infrastructure, and weak university–industry linkages (Turginbayeva, 2025). These challenges are exacerbated by budgetary inflexibility, which delays infrastructure upgrades and impedes digital transformation. According to expert assessments, perceptions of infrastructure accessibility and predictability of funding overwhelmingly have negative correlation (r= -0.421) with infrastructure accessibility (Turginbayeva, 2025). The study further shows that lack of sustained support for early-career researchers further undermines staff retention and institutional resilience. This pattern of underinvestment is not unique to Central Asia. In the United States, particularly in the state of Pennsylvania, Steinberg (2014) documents a significant adequacy gap (defined as the difference between the resources required for all students to achieve academically and the actual resources allocated). The study noted that for the 2009–10 academic year, the average district-level adequacy gap was $1,559 per pupil, rising to $2,416 per pupil for districts serving the most economically disadvantaged students. These figures highlight the compounding effect of socio-economic disparities on funding equity, with chronic underfunding disproportionately affecting marginalised populations. The concept of funding adequacy is grounded in the broader discourse on equity in educational finance. Odden and Picus (2014) argue that adequacy-based funding frameworks are designed not merely to equalise inputs but to ensure that all learners have access to the level of resources needed to meet educational standards. This shift from equity to adequacy has informed various school finance reforms across North America and parts of sub-Saharan Africa, where funding models increasingly incorporate performance-based and needs-based indicators (UNESCO, 2021). Furthermore, the institutional performance implications of inadequate funding are well-documented. Financial constraints often lead to deteriorating learning environments, loss of qualified personnel, and limited research outputs. Hanushek and Woessmann (2015) demonstrate that investments in educational quality—especially in teacher training, facilities, and curriculum development—are strongly correlated with improved learning outcomes at both primary and higher education levels. Conversely, underfunded systems tend to experience diminished morale, increased dropout rates, and lower labour market returns for graduates. In the African context, Oketch and Rolleston (2007) highlight that while public financing has expanded access to basic education, the quality of education remains uneven due to systemic inefficiencies and underinvestment in secondary and tertiary sectors. Similarly, in Nigeria, Olaniyan and Okemakinde (2008) report that public universities suffer from erratic funding, delayed salary payments, and ageing infrastructure, conditions that inhibit innovation and academic competitiveness. The challenge of maintaining quality while expanding access creates additional funding pressures in higher education systems across Africa, with massification representing one of the most significant transformations over the past four decades (Kipchumba, 2019). The steady rise in student enrollment at higher education institutions worldwide has become a growing concern for students, educators, parents, policymakers, and educational analysts. This concern is especially pronounced in contexts where limited fiscal resources have undermined the quality standards essential for educational development (Akinyemi, 2012). This phenomenon has been borne out of a global trend of massification of higher education as many countries begin to consider the importance of education and skills development in economic growth and social development. On the other hand, it has been triggered by the perceived pattern of commodification of higher education services in which student intake and teaching outputs are intricately linked to the financial sustainability of higher education institutions. The Nigerian higher education system offers a compelling case for examining these challenges, given its central role in driving national development (Akinyemi, 2012). It is important to state that this system faces unprecedented pressures that mirror broader African and global trends while maintaining distinct national characteristics. Taken together, these studies emphasise the critical role of predictable and adequate funding in sustaining institutional performance. The links between financial investment, infrastructure development, and educational outcomes are neither linear nor automatic, but they are deeply interconnected. Institutions that receive consistent and adequate funding are better positioned to attract and retain talent, modernise operations, and improve service delivery for students. 2.1 Historical Development of Educational Institutions in Nigeria and the Global Economic Menace University education in Nigeria began in 1948 with the establishment of University College, Ibadan. After independence in 1960, successive governments expanded the number of universities—a policy driven by the shortage of qualified manpower following the departure of British officials, as well as the need to accommodate a growing number of prospective students (Dumbili, 2014). This expansion marked the early stages of what would later become a significant massification challenge. Today, the demand for higher and tertiary education in Africa is high. As a result, public institutions are enrolling large numbers of students—a phenomenon known as massification, which refers to the rise in student enrollment without a corresponding increase in resources (Mafuhure, 2023). In the Nigerian context, this massification has created unique pressures that extend beyond simple enrolment numbers. The global economic crisis has significantly impacted the education sector, with many higher institutions facing severe challenges. In Nigeria, reduced access due to rising education costs has made it difficult for students to afford tertiary education, resulting in lower enrollment rates and declining educational quality (Ahmad, 2025). Economic pressures have fundamentally reshaped the landscape of Nigerian higher education. In the 1970s, although the number of universities increased, this expansion was accompanied by a decline in infrastructure, inadequate funding, and deteriorating working conditions. These issues triggered frequent strikes and prompted a significant exodus of academics to other countries (Dumbili, 2014). This historical pattern set a precedent for the persistent challenges facing Nigerian universities today. Similarly, Zimbabwean universities have begun enrolling large numbers of students to compensate for dwindling government support (Mafuhure, 2023)—a trend that mirrors Nigeria’s growing dependence on student fees to sustain operations, thereby intensifying the tension between access and financial sustainability. On the government side, repeated cuts to education funding have become common, plunging the system into an unimaginable crisis (Ahmad, 2025). This reduction in public investment has compelled Nigerian higher education institutions to seek alternative revenue sources while still striving to maintain educational quality. Globally, inadequate funding is one of the foremost challenges facing the management of higher education institutions. Limited access to financial resources hinders the deployment of IT infrastructure and services—essential tools for delivering modern educational and administrative services. This shortfall directly impacts the quality of education and administrative efficiency, with broader implications for national economic development (Alo, 2022). In Nigeria, this technological infrastructure gap poses a critical obstacle to efforts aimed at modernizing higher education. The need for robust funding systems has become paramount—not only to ensure quality education but also to minimize educational waste and make effective use of scarce resources (Akinyemi, 2012). In a context defined by persistent resource constraints, innovative funding and delivery approaches are essential. 2.2 Higher education and Resource Constraint Despite the rapid expansion of university access to meet growing social demand, limited public funding for higher education has hindered the development of public universities. As a result, massification has led to a decline in per-student expenditure, undermining efforts to maintain acceptable standards of educational quality (Jacob, 2018). While this observation specifically references Haiti, similar trends are evident in Nigeria’s higher education system. Graduate education across Sub-Saharan Africa has also suffered from declining donor support, prolonged economic crises, explosive growth in undergraduate enrollment, and a shortage of faculty with doctoral qualifications (Hayward, 2014). Nigeria, as part of this regional landscape, faces comparable challenges in sustaining the quality of graduate programs while working to expand access. Higher education institutions in developing countries—especially in Africa—face growing challenges related to the massification of classes, as rapid increases in student enrollment have led to extremely large class sizes, with some courses enrolling over 3,000 students. This surge raises serious concerns about the quality of education and equitable access to learning (Tepe, 2025). Nigerian universities face persistent challenges related to overcrowded classrooms and overstretched resources. Key issues include limited resource availability, poor study conditions, and restricted access to digital learning solutions. Delivering quality education—particularly in courses requiring practical application—demands specialized training environments and infrastructure that are often lacking in developing countries (Tepe, 2025). These infrastructure deficits pose serious obstacles to effective teaching and learning in Nigeria. A high lecturer-to-student ratio further compounds the problem, especially in practice-based disciplines. Poor classroom management and limited student engagement in large lecture halls often result in surface-level learning, where students rely on rote memorization rather than developing critical thinking skills (Mafuhure, 2023). This pedagogical challenge underscores deeper systemic weaknesses within Nigeria’s higher education system. Rather than addressing the root challenges in higher education, the Nigerian federal government shifted responsibilities by approving private university ownership in 1999 and establishing the National Open University (NOUN) in 2001. These moves reflect deeper issues such as faculty overload, erosion of academic autonomy, an emphasis on publication quantity over quality, and the rise of a consumerist attitude among students (Dumbili, 2014). Such governance reforms align with broader neoliberal trends shaping higher education globally. Across Africa, the massification of higher education has largely resulted from progress at the primary and secondary levels, producing a growing pool of graduates seeking post-secondary opportunities. This surge in demand has led to rapid increases in enrollment across public and private institutions. However, it has also introduced significant challenges—including inadequate funding, limited institutional capacity, management inefficiencies, and strained infrastructure—particularly as universities expand to meet rising expectations (Kipchumba, 2019). Opportunities for meaningful interaction among academics in Nigerian institutions have diminished significantly as harsh economic realities take hold. Yet such interactions are essential, as they foster collaboration and knowledge-sharing within the academic community (Ahmad, 2025). The growing isolation of scholars poses a serious challenge to knowledge production and institutional development. Despite financial constraints in the higher education sector, it remains crucial for academic staff to share research findings and engage in collaborative efforts with other experts. Strengthening such partnerships could play a vital role in addressing Nigeria’s educational, research, and institutional challenges (Ahmad, 2025). 2.3 Regional Patterns and Trends In recent years, Africa’s higher education sector has undergone remarkable transformation. This includes rapid expansion in the number and diversity of institutions and academic programs, significant growth in student enrolment, the development of quality assurance frameworks, and improvements in institutional governance. These changes have been driven by various developments that have helped reposition higher education as a key contributor to national development (Kipchumba, 2019). The growth of private higher education in Africa has been propelled by rising demand that public institutions alone could not meet, as well as policy influences from Structural Adjustment Programmes, which promoted privatization beginning in the 1980s. Over the past three decades, private institutions across the continent have followed diverse growth trajectories (Tamrat, 2018). Empirical studies consistently show that while student enrollment in higher education institutions continues to rise, stakeholders increasingly question the quality of graduates. Findings often reveal moderate to high satisfaction among students and faculty regarding certain aspects of quality assurance; however, significant challenges persist—particularly resource limitations and institutional resistance to change. The Nigerian higher education system illustrates the complex challenges faced by developing countries in balancing massification with quality assurance. Universities must prioritize their core responsibilities: generating relevant knowledge, preparing students to be active citizens equipped for the labor market, contributing to community development, and fostering critical thinking (Zeelen, 2012). To address these issues, studies recommend that governments support colleges selectively—focusing on institutions capable of delivering programs in critical fields such as technology, economics, and the sciences (Kipchumba, 2019). This selective approach to expansion offers valuable insights for Nigerian policymakers aiming to optimize resource allocation while maintaining educational quality. The model of virtually free higher education funded by taxpayers has reached its limits. At the same time, institutional mechanisms to regulate massification have become essential—not only to protect educational consumers but also to counter the decline in quality. Achieving this will require greater public investment to enhance Nigeria’s global academic standing and harness the positive externalities of higher education (Jacob, 2018). The Nigerian case underscores the need for comprehensive policy frameworks that address the key dimensions of massification, including sustainable funding, infrastructure development, robust quality assurance systems, and innovative pedagogical strategies. Research findings on these challenges can be applied across other African universities facing similar pressures. Solutions such as intelligent classrooms for face-to-face learning (Tepe, 2025) suggest that collaborative and adaptive approaches may be the most effective path forward for the region’s higher education development. 2.4 Donabedian’s Structure–Process–Outcome (SPO) Model The Nigerian higher education landscape is plagued by systemic challenges, chief among them being inadequate and inconsistent funding, which significantly hampers institutional performance. Chronic underfunding by the government—combined with limited engagement from private funding sources—has led to the deterioration of physical infrastructure, weakened research capacity, and declining teaching quality. In response to this precarious funding environment, there is a growing need for structured evaluative frameworks, such as the SPO (Structure–Process–Outcome) model. This model enables institutions to assess their overall health by aligning resource inputs with administrative and academic processes, and by measuring the outcomes achieved. Originally developed for the healthcare sector, the SPO (Structure–Process–Outcome) model has proven valuable beyond its initial domain and is now widely applied in education and organizational performance evaluation. In higher education, the model is increasingly used to assess institutional effectiveness by examining how structural factors—such as funding, faculty competence, and infrastructure—influence educational processes and, ultimately, student and institutional outcomes. Within this context, structure includes elements like funding sources, physical facilities, academic staff qualifications, and institutional policies. Process refers to teaching methodologies, research activities, administrative procedures, and stakeholder interactions. Outcome encompasses measurable indicators such as graduation rates, research output, graduate employability, and the institution’s overall reputation. The rationale for applying the SPO (Structure–Process–Outcome) model to funding impact studies in educational institutions lies in the need for a systematic understanding of how financial inputs affect the quality and efficiency of educational delivery—and, ultimately, institutional effectiveness. This structured approach helps clarify complex causal relationships and pinpoint bottlenecks where funding either supports or falls short in sustaining institutional processes. In higher education, applications of the SPO model include evaluating how resource availability influences curriculum delivery, research capacity, and student performance—factors that are critical to institutional accreditation and global rankings. The SPO (Structure–Process–Outcome) model offers a transparent framework that enhances accountability and supports strategic planning in academic institutions (Tossaint-Schoenmakers, 2021). Its adaptability is further demonstrated through integration with evaluation tools like Health Impact Assessment (HIA), showcasing its capacity to incorporate broader economic and social perspectives into institutional performance analysis beyond its original healthcare context. Notably, the model’s application in evaluating chronic disease management services has yielded methodological insights that are transferable to the education sector. These insights are particularly valuable for assessing complex academic systems marked by multi-level interactions, resource limitations, and the need for coordinated institutional processes (Ameh, 2017). 2.5 Conceptual framework The conceptual framework for this study illustrates the influence of various funding sources on institutional performance in Nigerian higher education. It begins by identifying the primary sources of funding - namely, the Federal Government, State Governments, and private institutions—which serve as the foundational inputs into the higher education system. These funding sources directly influence a set of latent institutional performance factors—identified through factor analysis—that represent core service and operational dimensions within higher education institutions. Specifically, these factors include financial adequacy, workplace environment and resources, service reliability, responsiveness and competence, as well as institutional empathy and student-centered practices. Together, these dimensions reflect how stakeholders perceive institutional performance and highlight the internal capacity of institutions to deliver quality education and support services. The relationship between funding sources and the latent performance dimensions suggests that the nature and adequacy of financial inputs significantly shape both the institutional environment and the quality of service delivery. These performance factors, in turn, contribute to the classification of institutions as federal, state, or private—representing a high-level organizational outcome. In this study, institutional classification is treated as the dependent variable and analyzed using multinomial regression. This approach allows for the examination of variations in performance indicators across different funding contexts. This framework draws its conceptual foundation from the Input–Process–Output (IPO) model, a well-established approach in educational and organizational research. In this context, funding sources represent the input, latent performance factors form the process, and institutional classification serves as the output. The framework also parallels Donabedian’s Structure–Process–Outcome model, widely applied in assessing service quality in both health and education sectors. Moreover, the latent dimensions of institutional performance align closely with the SERVQUAL model (Parasuraman, Zeithaml, & Berry, 1988), which has been extensively used to evaluate service quality in higher education. This conceptual alignment reinforces the theoretical basis of the study, providing a robust foundation for empirically examining how different funding structures influence institutional performance across Nigerian higher education institutions. 3. Methodology This study employed a quantitative research design, collecting primary data through a structured questionnaire and supplementing it with secondary sources and online resources. The questionnaire was designed to gather information on the extent of funding allocated to various university units and programmes, as well as the factors influencing institutional performance in relation to different funding sources. A multistage sampling technique was used to select a total of 420 respondents, based on Cochran’s formula for an unknown population size with a 5% margin of error. In the first stage, the Southwest geopolitical zone of Nigeria was purposively selected from the country’s six zones due to its unique characteristics. This region is home to two of Nigeria’s first-generation federal universities—University of Ibadan (UI) and Obafemi Awolowo University (OAU)—both established over six decades ago. Additionally, the Southwest hosts the headquarters of major financial institutions and is in close proximity to Nigeria’s primary seaport (Apapa Wharf) and international airport (Murtala Muhammed Airport). In the second stage, four leading states—Oyo, Osun, Ogun, and Lagos—were selected based on their relatively high population sizes. Notably, Oyo and Osun host the highest concentration of universities in the region, while Lagos serves as Nigeria’s commercial capital. The third stage involved the purposive selection of two universities from each of the three ownership categories: federal, state, and private. The selected institutions included the University of Ibadan (UI) and Obafemi Awolowo University (OAU) for federal universities; Lagos State University (LASU) and Olabisi Onabanjo University (OOU) for state universities; and Babcock University and Covenant University for private universities. In the final stage, 70 academic and administrative staff members were purposively selected from each of the six universities. All selected participants had a minimum of one year of work experience at their respective institutions. The study utilized Donabedian’s model and the SERVQUAL framework to assess the funding sources available to universities. To evaluate funding adequacy and effectiveness, a range of relevant variables and indicators were considered. These included items related to the maintenance of physical infrastructure and equipment, timely payment of staff salaries, provision of allowances for departments and programmes, funding for IT services, health, safety and security measures, curriculum development, staff training, staff and student welfare, and the adequacy of learning resources. Respondents’ levels of agreement with each item were measured using a five-point Likert scale: 1 = Strongly Disagree , 2 = Disagree, 3 = Neutral , 4 = Agree , and 5 = Strongly Agree . Data analysis was conducted using frequency counts, percentages, means, and standard deviations. An exploratory factor analysis (EFA) was conducted to identify the underlying dimensions influencing institutional performance in relation to funding sources. The analysis was based on 27 observed items, rated by respondents using a five-point Likert scale ranging from Strongly Disagree to Strongly Agree (Appendix I). Preliminary tests confirmed that the data were suitable for factor analysis. The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy was 0.92, well above the recommended threshold of 0.80, indicating excellent sampling adequacy. Additionally, Bartlett’s Test of Sphericity was statistically significant (χ² = 4132.973, p < .001), suggesting sufficient intercorrelation among the items (Shrestha, 2021). Using principal component extraction and varimax rotation, five distinct latent factors were retained based on the eigenvalue-greater-than-0.5 rule, further supported by a visual inspection of the scree plot (Appendix III). Collectively, these five factors explained 62.12% of the total variance (Appendix II), indicating a strong representation of the underlying constructs. Each factor consisted of a coherent grouping of items with high loadings, suggesting meaningful and interpretable dimensions of institutional performance shaped by funding sources. The five latent factors were further examined through confirmatory analysis using multinomial regression (Appendix IV), which revealed statistically significant results for three out of the five variables. The analysis was conducted on 309 completed responses, representing a 73.6% response rate from the total number of questionnaires distributed. This is considered highly encouraging, especially given that data collection was conducted via email—a method typically associated with lower response rates. For context, Johnston et al. (2021) reported response rates ranging from 57.4% to 66.3% in primary care studies across North America, underscoring the strong participant engagement and data reliability achieved in the current study. 4.1 The spread of the selected Institutions The institutional ownership data presented in Table 1 show a clear tripartite distribution among the 309 staff respondents. Federal government-owned institutions constitute the largest group, representing 36.6% (113 staff), followed closely by state government institutions at 33.7% (104 staff), and private institutions at 29.8% (92 staff). This distribution offers valuable insights into the higher education landscape in Nigeria and raises important considerations regarding governance, institutional efficiency, and public policy implications. Table 1: Types of selected Institutions Institution type Frequency (staff) Percent Federal government 113 36.6 State government 104 33.7 Private ownership 92 29.8 Total 309 100 Combined public sector ownership—encompassing both federal and state institutions—accounts for 70.3% of the personnel in the dataset, highlighting the significant role of government in institutional control. This distribution reflects broader ownership trends observed in other sectors. For example, Butler (2012) notes that “the eastern United States is dominated by private ownership, while the western United States is dominated by public ownership,” and that “federal and state lands tend to be in more rural areas, while private forest ownerships tend to be in closer proximity to urban areas.” The substantial level of governmental ownership in Nigerian higher education may reflect strategic public interest considerations or historical development patterns that have favored public sector dominance. The slight predominance of federal ownership (36.6%) over state ownership (33.7%) suggests a relatively balanced distribution of responsibilities between the two levels of government. However, this fragmented ownership pattern reflects broader challenges in institutional management. As Ruple (2014) observes, “often no single owner—whether states, private entities, or the federal government—controls enough contiguous land to allow effective management,” and such fragmentation frequently leads to disputes over access and related issues. Similarly, this distribution may mirror the complex governance structures found in many institutional contexts. According to Xu (2011), “the central government has control over personnel, whereas subnational governments run the bulk of the economy; initiate, negotiate, implement, divert, resist reforms, policies, rules, laws" and "reform trajectories been shaped by regional decentralization.” Although private ownership represents the smallest category at 29.8%, it maintains a substantial presence, reflecting a mixed economic approach to institutional governance. Research suggests that “state ownership is an important institutional dimension in emerging markets, and strong ties with the government can influence the performance of State-Owned Enterprises (SOEs) through various market and non-market channels,” while also noting that “there is very little existing research on cross-country comparisons of the performance of SOEs vis-à-vis private firms” (Le, 2021). 4.2 Extent of available funding to units and programmes among selected Institutions As shown in Table 2, the survey data indicate that the maintenance of physical facilities received the lowest adequacy rating (mean = 2.49 ± 1.31), with an overwhelming 63% of respondents describing funding in this area as extremely insufficient. This finding is particularly troubling given the critical role that physical infrastructure plays in the effective functioning of university operations. According to Ofor-Douglas (2022), the poor maintenance of physical resources in Nigerian universities will inevitably lead to a decline in institutional productivity. Table 2: The extent of available funding to different units and programmes in the University EI (%) I (%) N (%) SS (%) VS (%) MEAN (SD) Total (%) Maintenance of physical facilities 78 (25.3) 116 (37.7) 20 (6.5) 70 (22.7) 24 (7.8) 2.49 ± 1.31 308 (100) Maintenance of equipment 64 (20.8) 117 (38.0) 22 (7.1) 83 (26.9) 22 (7.1) 2.62 ± 1.28 308 (100) Timely payment of employees’ salaries 30 (9.8) 90 (29.5) 29 (9.5) 116 (38.0) 40 (13.1) 3.15 ± 1.26 305 (100) Allowances for programmes and units 41 (13.3) 114 (37.0) 46 (14.9) 82 (26.6) 25 (8.1) 2.79 ± 1.21 308 (100) Property funding for IT services 36 (11.9) 115 (38.0) 25 (8.3) 95 (31.4) 32 (10.6) 2.91 ± 1.26 303 (100) Health, safety and security services 47 (15.4) 116 (37.9) 35 (11.4) 84 (27.5) 24 (7.8) 2.75 ± 1.23 306 (100) Curriculum development and teaching 19 (6.1) 112 (36.2) 39 (12.6) 110 (35.6) 29 (9.4) 3.06 ± 1.16 309 (100) Continuous employees training 64 (20.7) 90 (28.1) 46 (14.9) 84 (27.2) 25 (8.1) 2.73 ± 1.28 309 (100) Staff and student welfare 48 (15.5) 122 (39.5) 45 (14.6) 76 (24.6) 18 (5.8) 2.66 ± 1.18 309 (100) Learning resources 43 (13.9) 108 (35.0) 37 (12.0) 85 (27.5) 36 (11.7) 2.88 ± 1.28 309 (100) EI=Extremely Insufficient, I= Insufficient, N=Neutral, SS=Somewhat Sufficient, VS=Very sufficient The data show that 78 respondents (25.3%) rated funding as extremely insufficient, while 116 respondents (37.7%) considered it insufficient—resulting in a combined perception of funding inadequacy from 194 respondents (63.0%) out of a total of 308. This aligns with the findings of Ofor-Douglas (2022), who identified several challenges hindering the effective management and maintenance of physical resources in Nigerian universities, including inadequate funding, insufficient facilities, and the misuse of existing infrastructure, among other factors. Similarly, the equipment maintenance category received an adequacy score of 2.62 ± 1.28, with 181 respondents (59%) rating funding as either extremely insufficient or insufficient—highlighting another critical area of concern. As Ndiyamba et al. (2024) note, enhancing practical skills training in universities depends on the availability, adequacy, relevance, and proper maintenance of essential equipment and facilities. The data also reveal significant challenges in human resource management. Timely payment of employee salaries received the highest adequacy score among all categories, at 3.15 ± 1.26. However, this remains below the threshold for adequacy, with 120 respondents (39.3%) still rating salary payment as extremely insufficient or insufficient. This is particularly troubling, as staff compensation is a fundamental obligation of any functional institution. In addition, staff and student welfare recorded an adequacy score of 2.66 ± 1.18, with 170 respondents (55%) perceiving funding as extremely insufficient or insufficient. According to Ikogho (2025), while lecturers generally recognize the importance of health and safety facilities, major concerns persist around inadequate funding, lack of modern equipment, and a poor maintenance culture. In the area of professional development and training, continuous employee training received an adequacy rating of 2.73 ± 1.28, with 154 respondents (49.8%) considering funding to be extremely insufficient. This underfunding has cascading effects on both institutional capacity and the overall quality of education. While many colleges provide basic facilities and some support, staff training and funding for improvements and equipment remain limited (Wheater, 1988). The consequences of this extend beyond individual professional growth to the broader institutional system. Ikogho (2025) highlights that lack of policy implementation and inadequate staff training are major barriers to effective health and safety management in academic institutions. Despite these challenges, lecturers identified several promising strategies for improvement, including increased funding, technological advancement, public-private partnerships, and enhanced staff training. Curriculum development and teaching received a relatively higher adequacy score of 3.06 ± 1.16 compared to infrastructure categories. However, this still falls short of adequate levels, with 131 respondents (42.4%) rating funding as extremely insufficient. Similarly, learning resources scored 2.88 ± 1.28, with 151 respondents (48.9%) perceiving funding as inadequate. The underfunding of educational resources poses direct risks to teaching quality and student learning outcomes. Funding for IT services received an adequacy score of 2.91 ± 1.26, with 151 respondents (49.9%) rating it as extremely insufficient or insufficient. In an era of growing digitalization and technological dependence in higher education, such underfunding represents a critical vulnerability. As Venable (2010) notes, several key considerations must be addressed, including the characteristics and needs of modern students, the availability of technologies, funding requirements, and confidentiality concerns. The continuous advancement of technology has made it increasingly feasible to deliver a wide range of online student services. However, the technological gap becomes especially problematic when measured against the evolving expectations of today’s students. These students are often multitaskers with what Venable (2010) describes as “zero tolerance for delays.” Their high level of digital fluency creates an expectation for on-demand access to services and information—anytime and anywhere. 4.3 Factors A multinomial logistic regression analysis was conducted to examine how five latent institutional factors influence the likelihood of a university being funded by either a State Government or through Private Ownership, using Federal Government funding as the reference category. The latent factors analyzed were: Financial Adequacy and Institutional Funding, Employee Competence and Responsiveness, Physical Environment and Facilities, Service Reliability and Trust, and Institutional Care and Ethical Standards. Notably, three of these factors emerged as statistically significant predictors, indicating meaningful associations with the type of institutional ownership. 4.3.1 State Government vs Federal Government The results revealed that Financial Adequacy and Institutional Funding significantly increased the likelihood of a university being state funded rather than federally funded ( B = 0.403, p = 0.014, Exp( B ) = 1.496). This means that a one-unit increase in the perception of financial adequacy corresponds to a 49.6% higher probability of an institution being classified as state-funded. This finding suggests that respondents perceive state universities as having relatively stronger institutional funding compared to their federal counterparts. Similarly, Employee Competence and Responsiveness emerged as a significant predictor ( B = 0.356, p = 0.016, Exp( B ) = 1.427). A one-unit increase in this factor increases the odds of a university being state-funded by 42.7%, indicating that state universities are perceived to perform better in terms of staff responsiveness and competence than federal institutions. However, the remaining three factors - Physical Environment and Facilities, Service Reliability and Trust, and Institutional Care and Ethical Standards - did not exhibit statistically significant effects in predicting whether an institution is state- or federally funded ( p > 0.05). This indicates that perceptions of infrastructure quality, service reliability, and ethical standards do not differ substantially between state and federal universities. 4.3.2 Private Ownership vs Federal Government In contrast, the factor Financial Adequacy and Institutional Funding had a stronger and highly significant effect in distinguishing privately owned universities from federally funded ones (B = 1.335, p < 0.001, Exp(B) = 3.801). This indicates that a one-unit increase in the perception of financial adequacy increases the likelihood of a university being privately owned—rather than federally funded—by 280.1%. This finding underscores the perception that private universities are more financially stable and better resourced than their federal counterparts. The factor Physical Environment and Facilities also showed a significant effect, though it was negatively associated (B = -0.614, p = 0.001, Exp(B) = 0.541). This means private universities are 45.9% less likely to be associated with better physical environments compared to federal institutions, suggesting that federal universities may be perceived as having superior infrastructure, facilities, or environmental upkeep. The factor Service Reliability and Trust approached statistical significance (B = 0.343, p = 0.053, Exp(B) = 1.409), implying that private universities may be viewed as somewhat more reliable in service delivery than federal ones, although the result is only marginally significant. The remaining two factors - Employee Competence and Responsiveness and Institutional Care and Ethical Standards - did not significantly differentiate private universities from federal institutions ( p > 0.05), indicating no meaningful perceived differences in these areas. 4.4 Effective policy frameworks must address multiple dimensions. Class Size and Resource Allocation: To improve quality teaching and learning amid increasing class sizes, it is essential for government funding to higher education institutions to be increased. This should be accompanied by the adoption of policies aimed at reducing large class sizes and ensuring the equitable allocation of resources to faculties and academic departments. Universities should rigorously assess staff–student ratios and available infrastructure before launching new academic programmes. In addition, monitoring adherence to approved yearly enrolment targets is critical. Academic staff should adopt collaborative teaching methods that encourage and support students’ self-directed learning styles. Furthermore, optimal use of educational technologies should be promoted through the systematic integration of digital tools into teaching and learning environments. Providing enhanced administrative and psychosocial support for both students and lecturers is also vital. These macro-, meso-, and micro-level strategies are necessary to maintain and improve academic quality in the face of massification pressures (Mbanga, 2023). Performance-Based Funding: The implementation of transparent, outcome-oriented funding mechanisms is recommended. Such systems should reward institutional efficiency and effectiveness while also ensuring adequate baseline funding to support all essential academic and administrative operations. 4.5 Future research should focus on the longitudinal assessment of funding adequacy and its impact on educational outcomes, institutional sustainability, and broader societal benefits. In addition, studies should aim to develop adaptive financing models and explore international best practices in university–industry collaboration to strengthen the innovation ecosystem. Conclusion The comprehensive analysis of university funding adequacy reveals a crisis of systemic proportions, affecting all operational domains of higher education institutions. With mean adequacy scores falling well below acceptable thresholds across all ten measured categories, the data highlight a consistent pattern of institutional underfunding—one that threatens educational quality, research capacity, and long-term sustainability. The implications extend beyond the individual institution to impact national competitiveness, innovation potential, and the achievement of broader social development goals. Particularly severe deficiencies in physical infrastructure maintenance, equipment upkeep, and support services form a fragile foundation that undermines the effectiveness of all other institutional functions. Nevertheless, the analysis also points to actionable pathways for improvement through strategic interventions, targeted policy reforms, and innovative funding mechanisms. Success will require coordinated efforts at multiple levels—from institutional leadership to national governance—backed by international collaboration and the exchange of best practices. The urgency of addressing these funding challenges cannot be overstated. The future of higher education—and its ability to meet societal needs in an increasingly complex global environment—depends on immediate and sustained investment. Only through a comprehensive and unified commitment to adequate resource provision can universities effectively fulfill their essential roles in education, research, and social progress. In summary, Financial Adequacy and Institutional Funding emerged as a consistently significant factor in both comparisons, strongly influencing the likelihood of an institution being either state-funded or privately owned, relative to federal universities. Employee Competence and Responsiveness significantly distinguished state universities from federal ones, while Physical Environment and Facilities notably differentiated private universities from their federal counterparts. These findings highlight the critical role of financial resources, staff quality, and infrastructure in shaping institutional identity and stakeholder perceptions across different university types in Nigeria. References Agwu, C. O., & Nziadam, L. (2025). Implementing Service Learning for Creativity and Entrepreneurial Skill Development in Nigerian Higher Education: A Disciplinary-Based Approach. African Journal of Humanities and Contemporary Education Research , 18 (1), 111-124. https://doi.org/10.62154/ajhcer.2025.018.010632 Ameh, S., Gómez-Olivé, F. X., Kahn, K., Tollman, S. M., & Klipstein-Grobusch, K. (2017). Relationships between structure, process and outcome to assess quality of integrated chronic disease management in a rural South African setting: applying a structural equation model. BMC health services research , 17 , 1-15. Donabedian, A. (1988). The quality of care: How can it be assessed? Journal of the American Medical Association, 260 (12), 1743–1748. https://doi.org/10.1001/jama.1988.03410120089033 Donabedian, A. (2005). Evaluating the quality of medical care. The Milbank Quarterly , 83 (4), 691. Ghofrani, M., Valizadeh, L., Zamanzadeh, V., Ghahramanian, A., Janati, A., & Taleghani, F. (2024). Adapting the Donabedian model in undergraduate nursing education: a modified Delphi study. BMC Medical Education , 24 (1), 202. Hagood, L. P. (2019). The financial benefits and burdens of performance funding in higher education. Educational Evaluation and Policy Analysis , 41 (2), 189-213. https://doi.org/10.3102/0162373719837318 Ikogho, D. E., Onoharigho, D. F., & Samuel, R. (2025). Perceptions and Expectations of Safety Gadgets: Insights from Health and Safety Education Lecturers in Some Selected Universities in Niger Delta Region. International Research Journal of Multidisciplinary Scope , 6 (2), 106-114. Johnston, S., Hogg, W., Wong, S. T., Burge, F., & Peterson, S. (2021). Differences in mode preferences, response rates, and mode effect between automated email and phone survey systems for patients of primary care practices: cross-sectional study. Journal of Medical Internet Research , 23 (1), e21240. Kobayashi, H., Takemura, Y., & Kanda, K. (2011). Patient perception of nursing service quality; an applied model of Donabedian’s structure‐process‐outcome approach theory. Scandinavian journal of caring sciences , 25 (3), 419-425. Kohtamäki, V. (2023). Strategic dependence on external funding in Finnish higher education. Cogent Education , 10 (2), 2282816. Mafindi, K. A. (2024). Evolution and Impact of Personnel Management Practices in Higher Education Institutions. Solo Universal Journal of Islamic Education and Multiculturalism , 2 (03), 279-292. Mutiso, J. M., Onyango, M., & Nyagol, M. O. (2015). Effects of funding sources on access to quality higher education in public universities in Kenya: A case study. Ndiyamba, D., Murena, E., Zendera, W., Mafuratidze, F., and Madzudzo, E. (2024). Enhancing Mechanical Engineering Education in Zimbabwe through Identifying Critical Equipment, Facilities, and Maintenance Strategies for Effective Training at Universities. i-manager’s Journal on Mechanical Engineering , 14(3), 1-18. https://doi.org/10.26634/jme.14.3.21225 Ngonso, B. F. (2022). Ethical Lapses in the Nigerian Higher Education System. Journal of Ethnics in Higher Education , 1 . https://doi.org/10.26034/fr.jehe.2022.3376 Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64 (1), 12–40. Pekarcikova, J. (2023). HIA as a standard tool for effective decision-making on NCD policies. European Journal of Public Health , 33 (Supplement_2), ckad160-1300. Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American journal of Applied Mathematics and statistics, 9(1), 4-11. Shin, J. C., Ho, S. S. H., Chen, R. J. C., & Lee, J. K. (2023). Does institutional performance matter under competition-based funding for higher education in East Asia? A comparative study in Korea and Taiwan. Studies in Higher Education , 48 (3), 383-398. Tossaint-Schoenmakers, R., Versluis, A., Chavannes, N., Talboom-Kamp, E., & Kasteleyn, M. (2021). The challenge of integrating eHealth into health care: systematic literature review of the Donabedian model of structure, process, and outcome. Journal of medical Internet research , 23 (5), e27180. Tuan, N. M. (2012). Effects of service quality and price fairness on student satisfaction. International Journal of Business and Social Science, 3 (19), 132–150. https://ijbssnet.com/journals/Vol_3_No_19_October_2012/15.pdf Wike, R. E. (2024). Re-Engineering Nigerian Higher Education for Sustainable Development and Global Competitiveness. European Journal of Arts, Humanities and Social Sciences , 1 (2), 33-46. Zhang, L., Gowan, M., & Treviño, L. K. (2011). The influence of academic discipline and student characteristics on perceptions of service quality in higher education. The Review of Higher Education, 34 (4), 501–528. https://doi.org/10.1353/rhe.2011.0015 Additional Declarations The authors declare no competing interests. Supplementary Files Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7091781","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483446081,"identity":"1fbbd447-5fe1-4ea8-aae9-016b4e878ee6","order_by":0,"name":"Olugbenga Olowoye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYDACCSjNB6FsgJix8QBRWtggVBpISwNJWg6DSbxa5KObjz38UsMgx8beY/iYp+K83dr2w0BbamyicWkxvHMs3VjmGIMxG88ZY2OeM7eTt51JBGo5lpbbgEvLjBwzaQk2hsQ2idxt0rxtt5PNDgC1MDYcxqMl/5u0xD+Yln/nks3OP8SvRV4ih03yYxtMS8MBO7MbBGwxkDlmJs3YJwH0y/nPhnOOJSeY3QDakoDHL/Kzm59J/vhmI8fP3pb44E2Nnb3Z+fSHDz7U2OC25QADAzMPNHaYeBgYEsEqE3AoB9sCVMH4A8oBMezxKB4Fo2AUjIIRCgDCMl60Kz/+HAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0009-1698-4001","institution":"Wilmington University","correspondingAuthor":true,"prefix":"","firstName":"Olugbenga","middleName":"","lastName":"Olowoye","suffix":""}],"badges":[],"createdAt":"2025-07-10 10:10:54","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7091781/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7091781/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86633037,"identity":"9b13c6f1-1494-4d48-b6c2-cfa1111bcbb2","added_by":"auto","created_at":"2025-07-14 06:43:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138175,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConceptual framework of Institutional funding system in Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource: Adapted from Donabedian Model (Donabedian, 2005; Kobayashi, 2011)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7091781/v1/389912516e797c142b43335c.png"},{"id":86633914,"identity":"bb5cbb5e-be2b-40e1-bb12-0b9441360f65","added_by":"auto","created_at":"2025-07-14 06:59:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":921302,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7091781/v1/ee793b68-a9e2-400a-a0cd-b65df54ee3e2.pdf"},{"id":86632237,"identity":"1516f410-cefb-450a-b7c0-31dbc1afb29a","added_by":"auto","created_at":"2025-07-14 06:35:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":46283,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7091781/v1/6d1cf51ff6fdd267f3026944.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cem\u003eImpact of Funding Sources on Institutional Performance in Nigerian Higher Education\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe relationship between funding sources and institutional performance in Nigerian higher education represents one of the most critical challenges facing the country\u0026apos;s educational development trajectory. As universities and other tertiary institutions navigate an increasingly complex landscape of financial constraints and expanding enrolment demands, understanding how different funding mechanisms influence institutional outcomes has become paramount for educational stakeholders and policymakers alike. Nigerian higher education faces significant justifications for re-engineering, including the need to address funding, infrastructural, and management issues (Wike, 2024). This funding crisis has created a multifaceted challenge where poor recruitment practices, inadequate training programs, political interference, and limited funding (Mafindi, 2024) collectively undermine institutional effectiveness. The complexity of this situation is further compounded by the diverse array of funding sources available to Nigerian institutions, each carrying distinct implications for institutional autonomy, academic quality, and long-term sustainability.\u003c/p\u003e\n\u003cp\u003eThe Nigerian higher education funding ecosystem comprises multiple stakeholders and mechanisms, including government educational agencies such as the National Universities Commission (NUC); National Board for Technical Education (NBTE); National Commission for Colleges of Education (NCCE) and Tertiary Education Trust Fund (TETFund) (Ngonso, 2022). These agencies play crucial roles in both funding allocation and institutional oversight, creating a complex web of accountability relationships that significantly influence how institutions operate and perform. International research on funding mechanisms provides valuable insights for understanding the Nigerian context. Studies from other developing countries demonstrate that in education finance, the sources of funds and the size of the resources are key determinants of quality education (Mutiso, 2015). Furthermore, evidence suggests that performance funding consistently benefits high-resource institutions and imposes financial burdens on low-resource institutions (Hagood, 2017), raising important questions about equity and access in funding distribution models.\u003c/p\u003e\n\u003cp\u003eThe performance implications of different funding sources extend beyond simple resource availability. Research indicates that although competition-based funding is widely applied, traditional factors such as student enrolment and budget history still influence funding decisions (Shin, 2022), suggesting that even innovative funding approaches may perpetuate existing institutional hierarchies and performance patterns. This phenomenon has relevance for Nigerian institutions, where historical underfunding and infrastructural deficits may limit their ability to compete effectively for performance-based resources. The strategic responses of institutions to funding constraints reveal the adaptive capacity of higher education organisations. Rather than choosing between different funding streams, universities are adapting to the conditions of their funding environments (Kohtamki, 2023), often developing mixed funding portfolios that combine government appropriations, student fees, research grants, and private partnerships. However, addressing funding issues is vital for enhancing staff commitment and productivity, ultimately fostering institutional success and academic excellence (Mafindi, 2024).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe urgency of addressing funding challenges in Nigerian higher education cannot be overstated. Despite the implementation of entrepreneurship skills development programmes in Nigerian higher education institutions in response to the National Universities Commission (NUC) policy, the sector has failed to equip graduates with the capacity to venture into enterprise activities and the creation of valuable products and services. (Agwu, 2025) Hence the lingering high rate of unemployment and the poor state of development of the Nigerian small business sector. This performance gap underscores the critical need for more effective funding strategies that can support institutional capacity building and educational quality enhancement. Understanding these complex relationships between funding sources and institutional performance is essential for developing evidence-based policies that can transform Nigerian higher education into a more effective, equitable, and globally competitive system. The research problem centers on the limited evidence that performance funding improves student outcomes, despite its widespread adoption and political support. Implementation obstacles, unintended consequences, and variations in program design contribute to the lack of clear impact, highlighting the need for a more nuanced and context-sensitive approach to performance funding. Addressing these challenges requires a comprehensive evaluation and refinement of performance funding policies, considering the diverse missions and goals of higher education institutions. Although evidence suggests that performance funding does stimulate colleges and universities to substantially change their policies and practices, it is yet unclear whether performance funding improves student outcomes. This study is thus set to achieve two objectives, first to assess the extent of available funding to different units and programmes in the University as well as to investigate the factors responsible for institutional performance relative to funding sources.\u003c/p\u003e"},{"header":"2. The Impact of Funding Adequacy on Educational Infrastructure and Institutional Performance in Developing and Underfunded Systems.","content":"\u003cp\u003eEducational funding adequacy is a cornerstone of institutional effectiveness and educational quality. In both developing and developed contexts, persistent underfunding remains a systemic challenge. This is especially true in settings where public budgets are constrained, governance mechanisms are inflexible, and political priorities shift frequently. Research from developing education systems offers valuable insights into the multifaceted consequences of underfunding and potential policy responses. In Kazakhstan, for example, the higher education sector faces critical barriers to development, including financial constraints, outdated scientific infrastructure, and weak university\u0026ndash;industry linkages (Turginbayeva, 2025). These challenges are exacerbated by budgetary inflexibility, which delays infrastructure upgrades and impedes digital transformation. According to expert assessments, perceptions of infrastructure accessibility and predictability of funding overwhelmingly have negative correlation (r= -0.421) with infrastructure accessibility (Turginbayeva, 2025). The study further shows that lack of sustained support for early-career researchers further undermines staff retention and institutional resilience. This pattern of underinvestment is not unique to Central Asia. In the United States, particularly in the state of Pennsylvania, Steinberg (2014) documents a significant adequacy gap (defined as the difference between the resources required for all students to achieve academically and the actual resources allocated). The study noted that for the 2009\u0026ndash;10 academic year, the average district-level adequacy gap was $1,559 per pupil, rising to $2,416 per pupil for districts serving the most economically disadvantaged students. These figures highlight the compounding effect of socio-economic disparities on funding equity, with chronic underfunding disproportionately affecting marginalised populations.\u003c/p\u003e\n\u003cp\u003eThe concept of funding adequacy is grounded in the broader discourse on equity in educational finance. Odden and Picus (2014) argue that adequacy-based funding frameworks are designed not merely to equalise inputs but to ensure that all learners have access to the level of resources needed to meet educational standards. This shift from equity to adequacy has informed various school finance reforms across North America and parts of sub-Saharan Africa, where funding models increasingly incorporate performance-based and needs-based indicators (UNESCO, 2021). Furthermore, the institutional performance implications of inadequate funding are well-documented. Financial constraints often lead to deteriorating learning environments, loss of qualified personnel, and limited research outputs. Hanushek and Woessmann (2015) demonstrate that investments in educational quality\u0026mdash;especially in teacher training, facilities, and curriculum development\u0026mdash;are strongly correlated with improved learning outcomes at both primary and higher education levels. Conversely, underfunded systems tend to experience diminished morale, increased dropout rates, and lower labour market returns for graduates.\u003c/p\u003e\n\u003cp\u003eIn the African context, Oketch and Rolleston (2007) highlight that while public financing has expanded access to basic education, the quality of education remains uneven due to systemic inefficiencies and underinvestment in secondary and tertiary sectors. Similarly, in Nigeria, Olaniyan and Okemakinde (2008) report that public universities suffer from erratic funding, delayed salary payments, and ageing infrastructure, conditions that inhibit innovation and academic competitiveness. The challenge of maintaining quality while expanding access creates additional funding pressures in higher education systems across Africa, with massification representing one of the most significant transformations over the past four decades (Kipchumba, 2019). The steady rise in student enrollment at higher education institutions worldwide has become a growing concern for students, educators, parents, policymakers, and educational analysts. This concern is especially pronounced in contexts where limited fiscal resources have undermined the quality standards essential for educational development (Akinyemi, 2012). This phenomenon has been borne out of a global trend of massification of higher education as many countries begin to consider the importance of education and skills development in economic growth and social development. On the other hand, it has been triggered by the perceived pattern of commodification of higher education services in which student intake and teaching outputs are intricately linked to the financial sustainability of higher education institutions. The Nigerian higher education system offers a compelling case for examining these challenges, given its central role in driving national development (Akinyemi, 2012). It is important to state that this system faces unprecedented pressures that mirror broader African and global trends while maintaining distinct national characteristics.\u003c/p\u003e\n\u003cp\u003eTaken together, these studies emphasise the critical role of predictable and adequate funding in sustaining institutional performance. The links between financial investment, infrastructure development, and educational outcomes are neither linear nor automatic, but they are deeply interconnected. Institutions that receive consistent and adequate funding are better positioned to attract and retain talent, modernise operations, and improve service delivery for students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1 Historical Development of Educational Institutions in Nigeria and the Global Economic Menace \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUniversity education in Nigeria began in 1948 with the establishment of University College, Ibadan. After independence in 1960, successive governments expanded the number of universities\u0026mdash;a policy driven by the shortage of qualified manpower following the departure of British officials, as well as the need to accommodate a growing number of prospective students (Dumbili, 2014). This expansion marked the early stages of what would later become a significant massification challenge. Today, the demand for higher and tertiary education in Africa is high. As a result, public institutions are enrolling large numbers of students\u0026mdash;a phenomenon known as massification, which refers to the rise in student enrollment without a corresponding increase in resources (Mafuhure, 2023). In the Nigerian context, this massification has created unique pressures that extend beyond simple enrolment numbers.\u003c/p\u003e\n\u003cp\u003eThe global economic crisis has significantly impacted the education sector, with many higher institutions facing severe challenges. In Nigeria, reduced access due to rising education costs has made it difficult for students to afford tertiary education, resulting in lower enrollment rates and declining educational quality (Ahmad, 2025). Economic pressures have fundamentally reshaped the landscape of Nigerian higher education. In the 1970s, although the number of universities increased, this expansion was accompanied by a decline in infrastructure, inadequate funding, and deteriorating working conditions. These issues triggered frequent strikes and prompted a significant exodus of academics to other countries (Dumbili, 2014). This historical pattern set a precedent for the persistent challenges facing Nigerian universities today. Similarly, Zimbabwean universities have begun enrolling large numbers of students to compensate for dwindling government support (Mafuhure, 2023)\u0026mdash;a trend that mirrors Nigeria\u0026rsquo;s growing dependence on student fees to sustain operations, thereby intensifying the tension between access and financial sustainability. \u003c/p\u003e\n\u003cp\u003eOn the government side, repeated cuts to education funding have become common, plunging the system into an unimaginable crisis (Ahmad, 2025). This reduction in public investment has compelled Nigerian higher education institutions to seek alternative revenue sources while still striving to maintain educational quality.\u003c/p\u003e\n\u003cp\u003eGlobally, inadequate funding is one of the foremost challenges facing the management of higher education institutions. Limited access to financial resources hinders the deployment of IT infrastructure and services\u0026mdash;essential tools for delivering modern educational and administrative services. This shortfall directly impacts the quality of education and administrative efficiency, with broader implications for national economic development (Alo, 2022).\u003c/p\u003e\n\u003cp\u003eIn Nigeria, this technological infrastructure gap poses a critical obstacle to efforts aimed at modernizing higher education. The need for robust funding systems has become paramount\u0026mdash;not only to ensure quality education but also to minimize educational waste and make effective use of scarce resources (Akinyemi, 2012). In a context defined by persistent resource constraints, innovative funding and delivery approaches are essential.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Higher education and Resource Constraint\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite the rapid expansion of university access to meet growing social demand, limited public funding for higher education has hindered the development of public universities. As a result, massification has led to a decline in per-student expenditure, undermining efforts to maintain acceptable standards of educational quality (Jacob, 2018). While this observation specifically references Haiti, similar trends are evident in Nigeria\u0026rsquo;s higher education system.\u003c/p\u003e\n\u003cp\u003eGraduate education across Sub-Saharan Africa has also suffered from declining donor support, prolonged economic crises, explosive growth in undergraduate enrollment, and a shortage of faculty with doctoral qualifications (Hayward, 2014). Nigeria, as part of this regional landscape, faces comparable challenges in sustaining the quality of graduate programs while working to expand access.\u003c/p\u003e\n\u003cp\u003eHigher education institutions in developing countries\u0026mdash;especially in Africa\u0026mdash;face growing challenges related to the massification of classes, as rapid increases in student enrollment have led to extremely large class sizes, with some courses enrolling over 3,000 students. This surge raises serious concerns about the quality of education and equitable access to learning (Tepe, 2025). Nigerian universities face persistent challenges related to overcrowded classrooms and overstretched resources. Key issues include limited resource availability, poor study conditions, and restricted access to digital learning solutions. Delivering quality education\u0026mdash;particularly in courses requiring practical application\u0026mdash;demands specialized training environments and infrastructure that are often lacking in developing countries (Tepe, 2025). These infrastructure deficits pose serious obstacles to effective teaching and learning in Nigeria.\u003c/p\u003e\n\u003cp\u003eA high lecturer-to-student ratio further compounds the problem, especially in practice-based disciplines. Poor classroom management and limited student engagement in large lecture halls often result in surface-level learning, where students rely on rote memorization rather than developing critical thinking skills (Mafuhure, 2023). This pedagogical challenge underscores deeper systemic weaknesses within Nigeria\u0026rsquo;s higher education system.\u003c/p\u003e\n\u003cp\u003eRather than addressing the root challenges in higher education, the Nigerian federal government shifted responsibilities by approving private university ownership in 1999 and establishing the National Open University (NOUN) in 2001. These moves reflect deeper issues such as faculty overload, erosion of academic autonomy, an emphasis on publication quantity over quality, and the rise of a consumerist attitude among students (Dumbili, 2014). Such governance reforms align with broader neoliberal trends shaping higher education globally.\u003c/p\u003e\n\u003cp\u003eAcross Africa, the massification of higher education has largely resulted from progress at the primary and secondary levels, producing a growing pool of graduates seeking post-secondary opportunities. This surge in demand has led to rapid increases in enrollment across public and private institutions. However, it has also introduced significant challenges\u0026mdash;including inadequate funding, limited institutional capacity, management inefficiencies, and strained infrastructure\u0026mdash;particularly as universities expand to meet rising expectations (Kipchumba, 2019).\u003c/p\u003e\n\u003cp\u003eOpportunities for meaningful interaction among academics in Nigerian institutions have diminished significantly as harsh economic realities take hold. Yet such interactions are essential, as they foster collaboration and knowledge-sharing within the academic community (Ahmad, 2025). The growing isolation of scholars poses a serious challenge to knowledge production and institutional development.\u003c/p\u003e\n\u003cp\u003eDespite financial constraints in the higher education sector, it remains crucial for academic staff to share research findings and engage in collaborative efforts with other experts. Strengthening such partnerships could play a vital role in addressing Nigeria\u0026rsquo;s educational, research, and institutional challenges (Ahmad, 2025).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Regional Patterns and Trends\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn recent years, Africa\u0026rsquo;s higher education sector has undergone remarkable transformation. This includes rapid expansion in the number and diversity of institutions and academic programs, significant growth in student enrolment, the development of quality assurance frameworks, and improvements in institutional governance. These changes have been driven by various developments that have helped reposition higher education as a key contributor to national development (Kipchumba, 2019).\u003c/p\u003e\n\u003cp\u003eThe growth of private higher education in Africa has been propelled by rising demand that public institutions alone could not meet, as well as policy influences from Structural Adjustment Programmes, which promoted privatization beginning in the 1980s. Over the past three decades, private institutions across the continent have followed diverse growth trajectories (Tamrat, 2018).\u003c/p\u003e\n\u003cp\u003eEmpirical studies consistently show that while student enrollment in higher education institutions continues to rise, stakeholders increasingly question the quality of graduates. Findings often reveal moderate to high satisfaction among students and faculty regarding certain aspects of quality assurance; however, significant challenges persist\u0026mdash;particularly resource limitations and institutional resistance to change.\u003c/p\u003e\n\u003cp\u003eThe Nigerian higher education system illustrates the complex challenges faced by developing countries in balancing massification with quality assurance. Universities must prioritize their core responsibilities: generating relevant knowledge, preparing students to be active citizens equipped for the labor market, contributing to community development, and fostering critical thinking (Zeelen, 2012).\u003c/p\u003e\n\u003cp\u003eTo address these issues, studies recommend that governments support colleges selectively\u0026mdash;focusing on institutions capable of delivering programs in critical fields such as technology, economics, and the sciences (Kipchumba, 2019).\u003c/p\u003e\n\u003cp\u003eThis selective approach to expansion offers valuable insights for Nigerian policymakers aiming to optimize resource allocation while maintaining educational quality. The model of virtually free higher education funded by taxpayers has reached its limits. At the same time, institutional mechanisms to regulate massification have become essential\u0026mdash;not only to protect educational consumers but also to counter the decline in quality. Achieving this will require greater public investment to enhance Nigeria\u0026rsquo;s global academic standing and harness the positive externalities of higher education (Jacob, 2018).\u003c/p\u003e\n\u003cp\u003eThe Nigerian case underscores the need for comprehensive policy frameworks that address the key dimensions of massification, including sustainable funding, infrastructure development, robust quality assurance systems, and innovative pedagogical strategies. Research findings on these challenges can be applied across other African universities facing similar pressures. Solutions such as intelligent classrooms for face-to-face learning (Tepe, 2025) suggest that collaborative and adaptive approaches may be the most effective path forward for the region\u0026rsquo;s higher education development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Donabedian\u0026rsquo;s Structure\u0026ndash;Process\u0026ndash;Outcome (SPO) Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Nigerian higher education landscape is plagued by systemic challenges, chief among them being inadequate and inconsistent funding, which significantly hampers institutional performance. Chronic underfunding by the government\u0026mdash;combined with limited engagement from private funding sources\u0026mdash;has led to the deterioration of physical infrastructure, weakened research capacity, and declining teaching quality.\u003c/p\u003e\n\u003cp\u003eIn response to this precarious funding environment, there is a growing need for structured evaluative frameworks, such as the SPO (Structure\u0026ndash;Process\u0026ndash;Outcome) model. This model enables institutions to assess their overall health by aligning resource inputs with administrative and academic processes, and by measuring the outcomes achieved.\u003c/p\u003e\n\u003cp\u003eOriginally developed for the healthcare sector, the SPO (Structure\u0026ndash;Process\u0026ndash;Outcome) model has proven valuable beyond its initial domain and is now widely applied in education and organizational performance evaluation. In higher education, the model is increasingly used to assess institutional effectiveness by examining how structural factors\u0026mdash;such as funding, faculty competence, and infrastructure\u0026mdash;influence educational processes and, ultimately, student and institutional outcomes.\u003c/p\u003e\n\u003cp\u003eWithin this context, \u003cem\u003estructure\u003c/em\u003e includes elements like funding sources, physical facilities, academic staff qualifications, and institutional policies. \u003cem\u003eProcess\u003c/em\u003e refers to teaching methodologies, research activities, administrative procedures, and stakeholder interactions. \u003cem\u003eOutcome\u003c/em\u003e encompasses measurable indicators such as graduation rates, research output, graduate employability, and the institution\u0026rsquo;s overall reputation.\u003c/p\u003e\n\u003cp\u003eThe rationale for applying the SPO (Structure\u0026ndash;Process\u0026ndash;Outcome) model to funding impact studies in educational institutions lies in the need for a systematic understanding of how financial inputs affect the quality and efficiency of educational delivery\u0026mdash;and, ultimately, institutional effectiveness. This structured approach helps clarify complex causal relationships and pinpoint bottlenecks where funding either supports or falls short in sustaining institutional processes. In higher education, applications of the SPO model include evaluating how resource availability influences curriculum delivery, research capacity, and student performance\u0026mdash;factors that are critical to institutional accreditation and global rankings.\u003c/p\u003e\n\u003cp\u003eThe SPO (Structure\u0026ndash;Process\u0026ndash;Outcome) model offers a transparent framework that enhances accountability and supports strategic planning in academic institutions (Tossaint-Schoenmakers, 2021). Its adaptability is further demonstrated through integration with evaluation tools like Health Impact Assessment (HIA), showcasing its capacity to incorporate broader economic and social perspectives into institutional performance analysis beyond its original healthcare context. Notably, the model\u0026rsquo;s application in evaluating chronic disease management services has yielded methodological insights that are transferable to the education sector. These insights are particularly valuable for assessing complex academic systems marked by multi-level interactions, resource limitations, and the need for coordinated institutional processes (Ameh, 2017).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Conceptual framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe conceptual framework for this study illustrates the influence of various funding sources on institutional performance in Nigerian higher education. It begins by identifying the primary sources of funding - namely, the Federal Government, State Governments, and private institutions\u0026mdash;which serve as the foundational inputs into the higher education system.\u003c/p\u003e\n\u003cp\u003eThese funding sources directly influence a set of latent institutional performance factors\u0026mdash;identified through factor analysis\u0026mdash;that represent core service and operational dimensions within higher education institutions. Specifically, these factors include financial adequacy, workplace environment and resources, service reliability, responsiveness and competence, as well as institutional empathy and student-centered practices. Together, these dimensions reflect how stakeholders perceive institutional performance and highlight the internal capacity of institutions to deliver quality education and support services.\u003c/p\u003e\n\u003cp\u003eThe relationship between funding sources and the latent performance dimensions suggests that the nature and adequacy of financial inputs significantly shape both the institutional environment and the quality of service delivery. These performance factors, in turn, contribute to the classification of institutions as federal, state, or private\u0026mdash;representing a high-level organizational outcome. In this study, institutional classification is treated as the dependent variable and analyzed using multinomial regression. This approach allows for the examination of variations in performance indicators across different funding contexts.\u003c/p\u003e\n\u003cp\u003eThis framework draws its conceptual foundation from the Input\u0026ndash;Process\u0026ndash;Output (IPO) model, a well-established approach in educational and organizational research. In this context, funding sources represent the input, latent performance factors form the process, and institutional classification serves as the output. The framework also parallels Donabedian\u0026rsquo;s Structure\u0026ndash;Process\u0026ndash;Outcome model, widely applied in assessing service quality in both health and education sectors.\u003c/p\u003e\n\u003cp\u003eMoreover, the latent dimensions of institutional performance align closely with the SERVQUAL model (Parasuraman, Zeithaml, \u0026amp; Berry, 1988), which has been extensively used to evaluate service quality in higher education. This conceptual alignment reinforces the theoretical basis of the study, providing a robust foundation for empirically examining how different funding structures influence institutional performance across Nigerian higher education institutions.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThis study employed a quantitative research design, collecting primary data through a structured questionnaire and supplementing it with secondary sources and online resources. The questionnaire was designed to gather information on the extent of funding allocated to various university units and programmes, as well as the factors influencing institutional performance in relation to different funding sources.\u003c/p\u003e\n\u003cp\u003eA multistage sampling technique was used to select a total of 420 respondents, based on Cochran\u0026rsquo;s formula for an unknown population size with a 5% margin of error. In the first stage, the Southwest geopolitical zone of Nigeria was purposively selected from the country\u0026rsquo;s six zones due to its unique characteristics. This region is home to two of Nigeria\u0026rsquo;s first-generation federal universities\u0026mdash;University of Ibadan (UI) and Obafemi Awolowo University (OAU)\u0026mdash;both established over six decades ago. Additionally, the Southwest hosts the headquarters of major financial institutions and is in close proximity to Nigeria\u0026rsquo;s primary seaport (Apapa Wharf) and international airport (Murtala Muhammed Airport).\u003c/p\u003e\n\u003cp\u003eIn the second stage, four leading states\u0026mdash;Oyo, Osun, Ogun, and Lagos\u0026mdash;were selected based on their relatively high population sizes. Notably, Oyo and Osun host the highest concentration of universities in the region, while Lagos serves as Nigeria\u0026rsquo;s commercial capital.\u003c/p\u003e\n\u003cp\u003eThe third stage involved the purposive selection of two universities from each of the three ownership categories: federal, state, and private. The selected institutions included the University of Ibadan (UI) and Obafemi Awolowo University (OAU) for federal universities; Lagos State University (LASU) and Olabisi Onabanjo University (OOU) for state universities; and Babcock University and Covenant University for private universities.\u003c/p\u003e\n\u003cp\u003eIn the final stage, 70 academic and administrative staff members were purposively selected from each of the six universities. All selected participants had a minimum of one year of work experience at their respective institutions.\u003c/p\u003e\n\u003cp\u003eThe study utilized Donabedian\u0026rsquo;s model and the SERVQUAL framework to assess the funding sources available to universities. To evaluate funding adequacy and effectiveness, a range of relevant variables and indicators were considered. These included items related to the maintenance of physical infrastructure and equipment, timely payment of staff salaries, provision of allowances for departments and programmes, funding for IT services, health, safety and security measures, curriculum development, staff training, staff and student welfare, and the adequacy of learning resources.\u003c/p\u003e\n\u003cp\u003eRespondents\u0026rsquo; levels of agreement with each item were measured using a five-point Likert scale: 1 = \u003cem\u003eStrongly Disagree\u003c/em\u003e, 2 = \u003cem\u003eDisagree,\u003c/em\u003e 3 = \u003cem\u003eNeutral\u003c/em\u003e, 4 = \u003cem\u003eAgree\u003c/em\u003e, and 5 = \u003cem\u003eStrongly Agree\u003c/em\u003e. Data analysis was conducted using frequency counts, percentages, means, and standard deviations.\u003c/p\u003e\n\u003cp\u003eAn exploratory factor analysis (EFA) was conducted to identify the underlying dimensions influencing institutional performance in relation to funding sources. The analysis was based on 27 observed items, rated by respondents using a five-point Likert scale ranging from \u003cem\u003eStrongly Disagree\u003c/em\u003e to \u003cem\u003eStrongly Agree\u003c/em\u003e (Appendix I).\u003c/p\u003e\n\u003cp\u003ePreliminary tests confirmed that the data were suitable for factor analysis. The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy was 0.92, well above the recommended threshold of 0.80, indicating excellent sampling adequacy. Additionally, Bartlett\u0026rsquo;s Test of Sphericity was statistically significant (\u0026chi;\u0026sup2; = 4132.973, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), suggesting sufficient intercorrelation among the items (Shrestha, 2021).\u003c/p\u003e\n\u003cp\u003eUsing principal component extraction and varimax rotation, five distinct latent factors were retained based on the eigenvalue-greater-than-0.5 rule, further supported by a visual inspection of the scree plot (Appendix III). Collectively, these five factors explained 62.12% of the total variance (Appendix II), indicating a strong representation of the underlying constructs. Each factor consisted of a coherent grouping of items with high loadings, suggesting meaningful and interpretable dimensions of institutional performance shaped by funding sources.\u003c/p\u003e\n\u003cp\u003eThe five latent factors were further examined through confirmatory analysis using multinomial regression (Appendix IV), which revealed statistically significant results for three out of the five variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe analysis was conducted on 309 completed responses, representing a 73.6% response rate from the total number of questionnaires distributed. This is considered highly encouraging, especially given that data collection was conducted via email\u0026mdash;a method typically associated with lower response rates. For context, Johnston et al. (2021) reported response rates ranging from 57.4% to 66.3% in primary care studies across North America, underscoring the strong participant engagement and data reliability achieved in the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1 \u0026nbsp; \u0026nbsp; \u0026nbsp; The spread of the selected Institutions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe institutional ownership data presented in Table 1 show a clear tripartite distribution among the 309 staff respondents. Federal government-owned institutions constitute the largest group, representing 36.6% (113 staff), followed closely by state government institutions at 33.7% (104 staff), and private institutions at 29.8% (92 staff). This distribution offers valuable insights into the higher education landscape in Nigeria and raises important considerations regarding governance, institutional efficiency, and public policy implications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Types of selected Institutions\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"379\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitution type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (staff)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eFederal government\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e36.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eState government\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e33.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePrivate ownership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e309\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCombined public sector ownership\u0026mdash;encompassing both federal and state institutions\u0026mdash;accounts for 70.3% of the personnel in the dataset, highlighting the significant role of government in institutional control. This distribution reflects broader ownership trends observed in other sectors. For example, Butler (2012) notes that \u0026ldquo;the eastern United States is dominated by private ownership, while the western United States is dominated by public ownership,\u0026rdquo; and that \u0026ldquo;federal and state lands tend to be in more rural areas, while private forest ownerships tend to be in closer proximity to urban areas.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eThe substantial level of governmental ownership in Nigerian higher education may reflect strategic public interest considerations or historical development patterns that have favored public sector dominance.\u003c/p\u003e\n\u003cp\u003eThe slight predominance of federal ownership (36.6%) over state ownership (33.7%) suggests a relatively balanced distribution of responsibilities between the two levels of government. However, this fragmented ownership pattern reflects broader challenges in institutional management. As Ruple (2014) observes, \u0026ldquo;often no single owner\u0026mdash;whether states, private entities, or the federal government\u0026mdash;controls enough contiguous land to allow effective management,\u0026rdquo; and such fragmentation frequently leads to disputes over access and related issues.\u003c/p\u003e\n\u003cp\u003eSimilarly, this distribution may mirror the complex governance structures found in many institutional contexts. According to Xu (2011), \u0026ldquo;the central government has control over personnel, whereas subnational governments run the bulk of the economy; initiate, negotiate, implement, divert, resist reforms, policies, rules, laws\u0026quot; and \u0026quot;reform trajectories been shaped by regional decentralization.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eAlthough private ownership represents the smallest category at 29.8%, it maintains a substantial presence, reflecting a mixed economic approach to institutional governance. Research suggests that \u0026ldquo;state ownership is an important institutional dimension in emerging markets, and strong ties with the government can influence the performance of State-Owned Enterprises (SOEs) through various market and non-market channels,\u0026rdquo; while also noting that \u0026ldquo;there is very little existing research on cross-country comparisons of the performance of SOEs vis-\u0026agrave;-vis private firms\u0026rdquo; (Le, 2021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 \u0026nbsp; \u0026nbsp; \u0026nbsp; Extent of available funding to units and programmes among selected Institutions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2, the survey data indicate that the maintenance of physical facilities received the lowest adequacy rating (mean = 2.49 \u0026plusmn; 1.31), with an overwhelming 63% of respondents describing funding in this area as extremely insufficient. This finding is particularly troubling given the critical role that physical infrastructure plays in the effective functioning of university operations. According to Ofor-Douglas (2022), the poor maintenance of physical resources in Nigerian universities will inevitably lead to a decline in institutional productivity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: The extent of available funding to different units and programmes in the University\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"973\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEI (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eI\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSS\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVS\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eMEAN (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eMaintenance of physical facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e78 (25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e116 (37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e20 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e70 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e24 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.49 \u0026plusmn; 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e308 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eMaintenance of equipment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e64 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e117 (38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e22 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e83 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e22 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.62 \u0026plusmn;\u0026nbsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e308 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eTimely payment of employees\u0026rsquo; salaries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e30 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e90 (29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e29 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e116 (38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e40 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3.15 \u0026plusmn; 1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e305 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eAllowances for programmes and units\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e41 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e114 (37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e46 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e82 (26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e25 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.79 \u0026plusmn;\u0026nbsp;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e308 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eProperty funding for IT services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e36 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e115 (38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e25 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e95 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e32 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.91 \u0026plusmn; 1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e303 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eHealth, safety and security services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e47 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e116 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e35 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e84 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e24 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.75 \u0026plusmn; 1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e306 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eCurriculum development and teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e19 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e112 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e39 (12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e110 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e29 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3.06 \u0026plusmn; 1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e309 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eContinuous employees training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e64 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e90 (28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e46 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e84 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e25 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.73 \u0026plusmn; 1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e309 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eStaff and student welfare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e48 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e122 (39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e45 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e76 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e18 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.66 \u0026plusmn; 1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e309 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 283px;\"\u003e\n \u003cp\u003eLearning resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e43 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e108 (35.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e37 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e85 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e36 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.88 \u0026plusmn; 1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e309 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eEI=Extremely Insufficient, I= Insufficient, N=Neutral, SS=Somewhat Sufficient, VS=Very sufficient\u003c/p\u003e\n\u003cp\u003eThe data show that 78 respondents (25.3%) rated funding as extremely insufficient, while 116 respondents (37.7%) considered it insufficient\u0026mdash;resulting in a combined perception of funding inadequacy from 194 respondents (63.0%) out of a total of 308. This aligns with the findings of Ofor-Douglas (2022), who identified several challenges hindering the effective management and maintenance of physical resources in Nigerian universities, including inadequate funding, insufficient facilities, and the misuse of existing infrastructure, among other factors.\u003c/p\u003e\n\u003cp\u003eSimilarly, the equipment maintenance category received an adequacy score of 2.62 \u0026plusmn; 1.28, with 181 respondents (59%) rating funding as either extremely insufficient or insufficient\u0026mdash;highlighting another critical area of concern. As Ndiyamba et al. (2024) note, enhancing practical skills training in universities depends on the availability, adequacy, relevance, and proper maintenance of essential equipment and facilities.\u003c/p\u003e\n\u003cp\u003eThe data also reveal significant challenges in human resource management. Timely payment of employee salaries received the highest adequacy score among all categories, at 3.15 \u0026plusmn; 1.26. However, this remains below the threshold for adequacy, with 120 respondents (39.3%) still rating salary payment as extremely insufficient or insufficient. This is particularly troubling, as staff compensation is a fundamental obligation of any functional institution.\u003c/p\u003e\n\u003cp\u003eIn addition, staff and student welfare recorded an adequacy score of 2.66 \u0026plusmn; 1.18, with 170 respondents (55%) perceiving funding as extremely insufficient or insufficient. According to Ikogho (2025), while lecturers generally recognize the importance of health and safety facilities, major concerns persist around inadequate funding, lack of modern equipment, and a poor maintenance culture.\u003c/p\u003e\n\u003cp\u003eIn the area of professional development and training, continuous employee training received an adequacy rating of 2.73 \u0026plusmn; 1.28, with 154 respondents (49.8%) considering funding to be extremely insufficient. This underfunding has cascading effects on both institutional capacity and the overall quality of education. While many colleges provide basic facilities and some support, staff training and funding for improvements and equipment remain limited (Wheater, 1988). The consequences of this extend beyond individual professional growth to the broader institutional system. Ikogho (2025) highlights that lack of policy implementation and inadequate staff training are major barriers to effective health and safety management in academic institutions.\u003c/p\u003e\n\u003cp\u003eDespite these challenges, lecturers identified several promising strategies for improvement, including increased funding, technological advancement, public-private partnerships, and enhanced staff training. Curriculum development and teaching received a relatively higher adequacy score of 3.06 \u0026plusmn; 1.16 compared to infrastructure categories. However, this still falls short of adequate levels, with 131 respondents (42.4%) rating funding as extremely insufficient. Similarly, learning resources scored 2.88 \u0026plusmn; 1.28, with 151 respondents (48.9%) perceiving funding as inadequate. The underfunding of educational resources poses direct risks to teaching quality and student learning outcomes.\u003c/p\u003e\n\u003cp\u003eFunding for IT services received an adequacy score of 2.91 \u0026plusmn; 1.26, with 151 respondents (49.9%) rating it as extremely insufficient or insufficient. In an era of growing digitalization and technological dependence in higher education, such underfunding represents a critical vulnerability. As Venable (2010) notes, several key considerations must be addressed, including the characteristics and needs of modern students, the availability of technologies, funding requirements, and confidentiality concerns.\u003c/p\u003e\n\u003cp\u003eThe continuous advancement of technology has made it increasingly feasible to deliver a wide range of online student services. However, the technological gap becomes especially problematic when measured against the evolving expectations of today\u0026rsquo;s students. These students are often multitaskers with what Venable (2010) describes as \u0026ldquo;zero tolerance for delays.\u0026rdquo; Their high level of digital fluency creates an expectation for on-demand access to services and information\u0026mdash;anytime and anywhere.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 \u0026nbsp; \u0026nbsp; \u0026nbsp; Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA multinomial logistic regression analysis was conducted to examine how five latent institutional factors influence the likelihood of a university being funded by either a State Government or through Private Ownership, using Federal Government funding as the reference category. The latent factors analyzed were: Financial Adequacy and Institutional Funding, Employee Competence and Responsiveness, Physical Environment and Facilities, Service Reliability and Trust, and Institutional Care and Ethical Standards.\u003c/p\u003e\n\u003cp\u003eNotably, three of these factors emerged as statistically significant predictors, indicating meaningful associations with the type of institutional ownership.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.3.1 \u0026nbsp; \u0026nbsp;State Government vs Federal Government\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe results revealed that Financial Adequacy and Institutional Funding significantly increased the likelihood of a university being state funded rather than federally funded (\u003cem\u003eB\u003c/em\u003e = 0.403, \u003cem\u003ep\u003c/em\u003e = 0.014, Exp(\u003cem\u003eB\u003c/em\u003e) = 1.496). This means that a one-unit increase in the perception of financial adequacy corresponds to a 49.6% higher probability of an institution being classified as state-funded. This finding suggests that respondents perceive state universities as having relatively stronger institutional funding compared to their federal counterparts.\u003c/p\u003e\n\u003cp\u003eSimilarly, Employee Competence and Responsiveness emerged as a significant predictor (\u003cem\u003eB\u003c/em\u003e = 0.356, \u003cem\u003ep\u003c/em\u003e = 0.016, Exp(\u003cem\u003eB\u003c/em\u003e) = 1.427). A one-unit increase in this factor increases the odds of a university being state-funded by 42.7%, indicating that state universities are perceived to perform better in terms of staff responsiveness and competence than federal institutions.\u003c/p\u003e\n\u003cp\u003eHowever, the remaining three factors - Physical Environment and Facilities, Service Reliability and Trust, and Institutional Care and Ethical Standards - did not exhibit statistically significant effects in predicting whether an institution is state- or federally funded (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). This indicates that perceptions of infrastructure quality, service reliability, and ethical standards do not differ substantially between state and federal universities.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.3.2 \u0026nbsp; \u0026nbsp;Private Ownership vs Federal Government\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn contrast, the factor Financial Adequacy and Institutional Funding had a stronger and highly significant effect in distinguishing privately owned universities from federally funded ones (B = 1.335, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, Exp(B) = 3.801). This indicates that a one-unit increase in the perception of financial adequacy increases the likelihood of a university being privately owned\u0026mdash;rather than federally funded\u0026mdash;by 280.1%. This finding underscores the perception that private universities are more financially stable and better resourced than their federal counterparts.\u003c/p\u003e\n\u003cp\u003eThe factor Physical Environment and Facilities also showed a significant effect, though it was negatively associated (B = -0.614, \u003cem\u003ep\u003c/em\u003e = 0.001, Exp(B) = 0.541). This means private universities are 45.9% less likely to be associated with better physical environments compared to federal institutions, suggesting that federal universities may be perceived as having superior infrastructure, facilities, or environmental upkeep.\u003c/p\u003e\n\u003cp\u003eThe factor Service Reliability and Trust approached statistical significance (B = 0.343, \u003cem\u003ep\u003c/em\u003e = 0.053, Exp(B) = 1.409), implying that private universities may be viewed as somewhat more reliable in service delivery than federal ones, although the result is only marginally significant.\u003c/p\u003e\n\u003cp\u003eThe remaining two factors - Employee Competence and Responsiveness and Institutional Care and Ethical Standards - did not significantly differentiate private universities from federal institutions (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05), indicating no meaningful perceived differences in these areas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 \u0026nbsp; \u0026nbsp; \u0026nbsp; Effective policy frameworks must address multiple dimensions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClass Size and Resource Allocation:\u0026nbsp;To improve quality teaching and learning amid increasing class sizes, it is essential for government funding to higher education institutions to be increased. This should be accompanied by the adoption of policies aimed at reducing large class sizes and ensuring the equitable allocation of resources to faculties and academic departments. Universities should rigorously assess staff\u0026ndash;student ratios and available infrastructure before launching new academic programmes. In addition, monitoring adherence to approved yearly enrolment targets is critical.\u003c/p\u003e\n\u003cp\u003eAcademic staff should adopt collaborative teaching methods that encourage and support students\u0026rsquo; self-directed learning styles. Furthermore, optimal use of educational technologies should be promoted through the systematic integration of digital tools into teaching and learning environments. Providing enhanced administrative and psychosocial support for both students and lecturers is also vital. These macro-, meso-, and micro-level strategies are necessary to maintain and improve academic quality in the face of massification pressures (Mbanga, 2023).\u003c/p\u003e\n\u003cp\u003ePerformance-Based Funding: The implementation of transparent, outcome-oriented funding mechanisms is recommended. Such systems should reward institutional efficiency and effectiveness while also ensuring adequate baseline funding to support all essential academic and administrative operations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 \u0026nbsp; \u0026nbsp; \u0026nbsp; Future research\u003c/strong\u003e should focus on the longitudinal assessment of funding adequacy and its impact on educational outcomes, institutional sustainability, and broader societal benefits. In addition, studies should aim to develop adaptive financing models and explore international best practices in university\u0026ndash;industry collaboration to strengthen the innovation ecosystem.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe comprehensive analysis of university funding adequacy reveals a crisis of systemic proportions, affecting all operational domains of higher education institutions. With mean adequacy scores falling well below acceptable thresholds across all ten measured categories, the data highlight a consistent pattern of institutional underfunding\u0026mdash;one that threatens educational quality, research capacity, and long-term sustainability.\u003c/p\u003e\u003cp\u003eThe implications extend beyond the individual institution to impact national competitiveness, innovation potential, and the achievement of broader social development goals. Particularly severe deficiencies in physical infrastructure maintenance, equipment upkeep, and support services form a fragile foundation that undermines the effectiveness of all other institutional functions.\u003c/p\u003e\u003cp\u003eNevertheless, the analysis also points to actionable pathways for improvement through strategic interventions, targeted policy reforms, and innovative funding mechanisms. Success will require coordinated efforts at multiple levels\u0026mdash;from institutional leadership to national governance\u0026mdash;backed by international collaboration and the exchange of best practices.\u003c/p\u003e\u003cp\u003eThe urgency of addressing these funding challenges cannot be overstated. The future of higher education\u0026mdash;and its ability to meet societal needs in an increasingly complex global environment\u0026mdash;depends on immediate and sustained investment. Only through a comprehensive and unified commitment to adequate resource provision can universities effectively fulfill their essential roles in education, research, and social progress.\u003c/p\u003e\u003cp\u003eIn summary, Financial Adequacy and Institutional Funding emerged as a consistently significant factor in both comparisons, strongly influencing the likelihood of an institution being either state-funded or privately owned, relative to federal universities. Employee Competence and Responsiveness significantly distinguished state universities from federal ones, while Physical Environment and Facilities notably differentiated private universities from their federal counterparts.\u003c/p\u003e\u003cp\u003eThese findings highlight the critical role of financial resources, staff quality, and infrastructure in shaping institutional identity and stakeholder perceptions across different university types in Nigeria.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAgwu, C. O., \u0026amp; Nziadam, L. (2025). Implementing Service Learning for Creativity and Entrepreneurial Skill Development in Nigerian Higher Education: A Disciplinary-Based Approach. \u003cem\u003eAfrican Journal of Humanities and Contemporary Education Research\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), 111-124. https://doi.org/10.62154/ajhcer.2025.018.010632\u003c/li\u003e\n \u003cli\u003eAmeh, S., G\u0026oacute;mez-Oliv\u0026eacute;, F. X., Kahn, K., Tollman, S. M., \u0026amp; Klipstein-Grobusch, K. (2017). Relationships between structure, process and outcome to assess quality of integrated chronic disease management in a rural South African setting: applying a structural equation model. \u003cem\u003eBMC health services research\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e, 1-15.\u003c/li\u003e\n \u003cli\u003eDonabedian, A. (1988). The quality of care: How can it be assessed? \u003cem\u003eJournal of the American Medical Association, 260\u003c/em\u003e(12), 1743\u0026ndash;1748. https://doi.org/10.1001/jama.1988.03410120089033\u003c/li\u003e\n \u003cli\u003eDonabedian, A. (2005). Evaluating the quality of medical care. \u003cem\u003eThe Milbank Quarterly\u003c/em\u003e, \u003cem\u003e83\u003c/em\u003e(4), 691.\u003c/li\u003e\n \u003cli\u003eGhofrani, M., Valizadeh, L., Zamanzadeh, V., Ghahramanian, A., Janati, A., \u0026amp; Taleghani, F. (2024). Adapting the Donabedian model in undergraduate nursing education: a modified Delphi study. \u003cem\u003eBMC Medical Education\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(1), 202.\u003c/li\u003e\n \u003cli\u003eHagood, L. P. (2019). The financial benefits and burdens of performance funding in higher education. \u003cem\u003eEducational Evaluation and Policy Analysis\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(2), 189-213. https://doi.org/10.3102/0162373719837318\u003c/li\u003e\n \u003cli\u003eIkogho, D. E., Onoharigho, D. F., \u0026amp; Samuel, R. (2025). Perceptions and Expectations of Safety Gadgets: Insights from Health and Safety Education Lecturers in Some Selected Universities in Niger Delta Region. \u003cem\u003eInternational Research Journal of Multidisciplinary Scope\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(2), 106-114.\u003c/li\u003e\n \u003cli\u003eJohnston, S., Hogg, W., Wong, S. T., Burge, F., \u0026amp; Peterson, S. (2021). Differences in mode preferences, response rates, and mode effect between automated email and phone survey systems for patients of primary care practices: cross-sectional study. \u003cem\u003eJournal of Medical Internet Research\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(1), e21240.\u003c/li\u003e\n \u003cli\u003eKobayashi, H., Takemura, Y., \u0026amp; Kanda, K. (2011). Patient perception of nursing service quality; an applied model of Donabedian\u0026rsquo;s structure‐process‐outcome approach theory. \u003cem\u003eScandinavian journal of caring sciences\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(3), 419-425.\u003c/li\u003e\n \u003cli\u003eKohtam\u0026auml;ki, V. (2023). Strategic dependence on external funding in Finnish higher education. \u003cem\u003eCogent Education\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(2), 2282816.\u003c/li\u003e\n \u003cli\u003eMafindi, K. A. (2024). Evolution and Impact of Personnel Management Practices in Higher Education Institutions. \u003cem\u003eSolo Universal Journal of Islamic Education and Multiculturalism\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(03), 279-292.\u003c/li\u003e\n \u003cli\u003eMutiso, J. M., Onyango, M., \u0026amp; Nyagol, M. O. (2015). Effects of funding sources on access to quality higher education in public universities in Kenya: A case study.\u003c/li\u003e\n \u003cli\u003eNdiyamba, D., Murena, E., Zendera, W., Mafuratidze, F., and Madzudzo, E. (2024). Enhancing Mechanical Engineering Education in Zimbabwe through Identifying Critical Equipment, Facilities, and Maintenance Strategies for Effective Training at Universities. \u003cem\u003ei-manager\u0026rsquo;s Journal on Mechanical Engineering\u003c/em\u003e, 14(3), 1-18. https://doi.org/10.26634/jme.14.3.21225\u003c/li\u003e\n \u003cli\u003eNgonso, B. F. (2022). Ethical Lapses in the Nigerian Higher Education System. \u003cem\u003eJournal of Ethnics in Higher Education\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e. https://doi.org/10.26034/fr.jehe.2022.3376\u003c/li\u003e\n \u003cli\u003eParasuraman, A., Zeithaml, V. A., \u0026amp; Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. \u003cem\u003eJournal of Retailing, 64\u003c/em\u003e(1), 12\u0026ndash;40.\u003c/li\u003e\n \u003cli\u003ePekarcikova, J. (2023). HIA as a standard tool for effective decision-making on NCD policies. \u003cem\u003eEuropean Journal of Public Health\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(Supplement_2), ckad160-1300.\u003c/li\u003e\n \u003cli\u003eShrestha, N. (2021). Factor analysis as a tool for survey analysis. American journal of Applied Mathematics and statistics, 9(1), 4-11.\u003c/li\u003e\n \u003cli\u003eShin, J. C., Ho, S. S. H., Chen, R. J. C., \u0026amp; Lee, J. K. (2023). Does institutional performance matter under competition-based funding for higher education in East Asia? A comparative study in Korea and Taiwan. \u003cem\u003eStudies in Higher Education\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(3), 383-398.\u003c/li\u003e\n \u003cli\u003eTossaint-Schoenmakers, R., Versluis, A., Chavannes, N., Talboom-Kamp, E., \u0026amp; Kasteleyn, M. (2021). The challenge of integrating eHealth into health care: systematic literature review of the Donabedian model of structure, process, and outcome. \u003cem\u003eJournal of medical Internet research\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(5), e27180.\u003c/li\u003e\n \u003cli\u003eTuan, N. M. (2012). Effects of service quality and price fairness on student satisfaction. \u003cem\u003eInternational Journal of Business and Social Science, 3\u003c/em\u003e(19), 132\u0026ndash;150. https://ijbssnet.com/journals/Vol_3_No_19_October_2012/15.pdf\u003c/li\u003e\n \u003cli\u003eWike, R. E. (2024). Re-Engineering Nigerian Higher Education for Sustainable Development and Global Competitiveness. \u003cem\u003eEuropean Journal of Arts, Humanities and Social Sciences\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(2), 33-46.\u003c/li\u003e\n \u003cli\u003eZhang, L., Gowan, M., \u0026amp; Trevi\u0026ntilde;o, L. K. (2011). The influence of academic discipline and student characteristics on perceptions of service quality in higher education. \u003cem\u003eThe Review of Higher Education, 34\u003c/em\u003e(4), 501\u0026ndash;528. https://doi.org/10.1353/rhe.2011.0015\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Wilmington University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7091781/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7091781/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe assessment of university funding adequacy reveals a critical and multifaceted crisis affecting higher education institutions globally. Based on a comprehensive survey, this paper examined ten key operational areas within selected universities. The analysis presents alarming evidence of systematic underfunding across all measured domains, with particularly severe deficiencies in physical infrastructure maintenance and support services. This paper thus leveraged on Donabedian model and SERVQUAL to assess the funding sources available to the Universities. The findings demonstrate that current funding mechanisms are fundamentally inadequate to support the complex operational requirements of modern universities, with profound implications for educational quality, institutional sustainability, and national development goals. Specifically, five major factors were extracted as capable of influencing institutional performance relative to funding. These include finance, employee competencies, infrastructural development, Quality of Service (QoS), and ethical standards. Together, these factors account for 62.12% of the total variance in institutional performance, indicating that they collectively explain a significant proportion of the variability observed across institutions. The multimodal regression used to consolidate the results shows that federal universities tend to have better physical facilities compared to private universities. However, QoS plays a significant role in shaping perceptions of private universities. Employee competence and responsiveness is a key distinguishing factor specifically for state universities. In terms of funding adequacy, state universities are 49.6% more likely than federal universities to be perceived as adequately funded. Private universities stand out even more in this regard, being 280.1% more likely to be considered financially adequate than federal universities. These findings highlight the varying strengths and challenges across federal, state, and private university systems in key performance areas. These insights call for urgent policy reforms and strategic investments to address the disparities in university funding and performance. Strengthening institutional capacity across all sectors is essential to achieving equitable, high-quality higher education aligned with national and developmental priorities.\u003c/p\u003e","manuscriptTitle":"Impact of Funding Sources on Institutional Performance in Nigerian Higher Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 06:35:18","doi":"10.21203/rs.3.rs-7091781/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"df0a559c-a308-434c-b2bb-d9f74024e9f8","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51332753,"name":"Finance"},{"id":51332754,"name":"Analysis"},{"id":51332755,"name":"Operations Research"},{"id":51332756,"name":"Leadership and Ethics"}],"tags":[],"updatedAt":"2025-07-14T06:35:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 06:35:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7091781","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7091781","identity":"rs-7091781","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}