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Public AdministrationArtificial Intelligence and Corruption/Fraud Detection in Nigeria's Public Sector
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About This Research Topic Corruption remains one of the most persistent obstacles to effective public administration in Nigeria. On Transparency International’s 2025 Corruption Perceptions Index, Nigeria scored 26 out of 100 and ranked 142nd of 182 countries, behind 33 other African countries, despite dedicated agencies like the Economic and Financial Crimes Commission (EFCC) and Independent Corrupt Practices Commission (ICPC). Traditional detection—manual audit, whistleblower reports, reactive investigation—cannot match the scale of modern public sector transactions. Artificial Intelligence and machine-learning analytics promise anomaly detection at speed and scale unattainable manually. While Nigerian banking research shows NLP-augmented AI improves fraud detection accuracy, adoption in banking remains slow due to cost and expertise gaps, and application within public anti-corruption institutions themselves remains under-examined. Explore public administration and anti-corruption project topics Main Abstract Corruption remains persistent obstacle to public administration and development in Nigeria. Transparency International 2025 CPI scored Nigeria 26/100, rank 142/182, stagnant for years despite EFCC and ICPC existence. AI and ML analytics have been proposed internationally and within Nigerian finance as tools detecting anomalous patterns indicative of fraud or corruption at scale and speed beyond traditional audit. While AI fraud detection is studied with growing rigour in Nigerian banking sector, its application within public anti-corruption institutions remains under-examined. This study investigates extent of AI-driven fraud/corruption detection capability and perceived effectiveness within selected federal anti-corruption and revenue agencies in Abuja FCT. Anchored on Fraud Triangle Theory, Fraud Diamond framework, and Principal-Agent Theory, study adopts descriptive survey design complemented by document analysis of agency reports and international frameworks including UK International Public Sector Fraud Forum (IPSFF) AI framework. Population comprises investigative, audit, ICT/data-analytics staff of selected agencies, sample via Taro Yamane formula with stratified random sampling. Data collected via structured 5-point Likert questionnaire addressing three constructs: AI/analytics adoption for detection, institutional and data-readiness factors, perceived detection effectiveness. Analysis via descriptives and inferential (Chi-square, linear regression, ANOVA) at 0.05 level. Study expected to establish current AI adoption level across agencies, identify institutional and data factors shaping adoption, and determine statistical relationship between adoption and perceived effectiveness. Concludes with recommendations on data infrastructure, capacity building, inter-agency sharing to strengthen AI-enabled anti-corruption capability.
Public AdministrationCYBERSECURITY GOVERNANCE IN GOVERNMENT INSTITUTIONS IN NIGERIA
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About This Research Topic Digitisation of government services online portals interoperable databases digital identity systems automated back-office processing has expanded attack surface available to malicious actors even as improved efficiency and citizen access. Government institutions attractive targets for cybercriminals state-sponsored actors hacktivists given sensitivity data they hold tax records biometric identity health records and disruptive high-visibility impact successfully compromising public infrastructure. Cybersecurity governance institutional structures policies practices through which organisation identifies protects against detects responds to and recovers from cyber risk has consequently become essential rather than peripheral dimension of public-sector digital transformation. Cybersecurity governance in government institutions in Nigeria Internationally US NIST Cybersecurity Framework first released 2014 organised around five core functions Identify Protect Detect Respond Recover has become most widely referenced government-oriented framework mandated across all US federal agencies and voluntarily referenced worldwide. Comparative research on state-level US government adoption found majority state CIOs rely on NIST standards foundation enterprise-wide security policy adoption persistently constrained by funding governance stakeholder support skilled-personnel shortages illustrating even in jurisdiction with strong central guidance institutional implementation remains uneven. Nigeria cybersecurity governance architecture rests principally on two instruments: Cybercrimes Prohibition Prevention Act 2015 as amended which criminalises range cyber offences and establishes institutional responsibilities including Nigeria Computer Emergency Response Team ngCERT and National Cybersecurity Policy and Strategy NCPS which sets out overarching approach to governance critical infrastructure protection capacity building. Recent scholarship examining instruments however finds remains unclear whether effectively secure Nigeria digital domain in practice notwithstanding existence on paper Falade & Osho 2026. Qualitative doctoral study information security officers across three information-security-certified government institutions in central Nigeria similarly found Nigerian government organisations face significant challenges complying with cybersecurity policies threatening security and efficiency of e-government systems and raising concerns about data breaches service disruption diminished public trust Waldenu doctoral study 2025. This study investigates state of cybersecurity governance institutional structures policy compliance incident-response preparedness within selected federal Ministries Departments and Agencies MDAs Abuja Federal Capital Territory to establish empirical baseline against which Nigeria cybersecurity policy ambition can be assessed at institutional level. Main Abstract As government institutions increasingly digitise service delivery and data management security of underlying digital infrastructure has become precondition for rather than adjunct to effective public administration. Cybersecurity governance institutional structures policies practices through which organisation manages cyber risk has consequently emerged critical dimension of public-sector digital transformation. Nigeria cybersecurity governance architecture rests on two principal instruments: Cybercrimes Prohibition Prevention etc Act and National Cybersecurity Policy and Strategy NCPS yet recent scholarship questions whether these instruments translate effectively into operational institutional practice particularly within government agencies whose e-government systems represent high-value targets for cyberattack. Qualitative doctoral study information security officers in central Nigerian government institutions found persistent compliance challenges threatening security of e-government systems while broader Nigerian cybersecurity scholarship identifies funding constraints weak legal enforcement skills shortages low institutional awareness as recurring barriers. This study examines state of cybersecurity governance institutional structures policy compliance staff preparedness within selected federal MDAs Abuja Federal Capital Territory. Anchored on NIST Cybersecurity Framework Identify Protect Detect Respond Recover Neo-Institutional Theory and Routine Activity Theory study adopts descriptive survey research design complemented by document analysis Cybercrimes Act and NCPS. Population comprises ICT information-security and administrative staff selected MDAs with sample determined using Taro Yamane formula and selected through stratified random sampling. Data collected via structured questionnaire built on five-point Likert scale addressing institutional cybersecurity governance structures policy compliance and awareness and incident-response preparedness and analysed using descriptive statistics and inferential statistics Chi-square simple linear regression and ANOVA at 0.05 significance level. Study expected to establish current maturity cybersecurity governance across sampled MDAs identify organisational factors most strongly shape that maturity and determine statistical relationship between cybersecurity governance maturity and staff-perceived institutional resilience to cyber incidents. Study concludes with recommendations institutionalising NIST-aligned governance structures strengthening compliance monitoring and building incident-response capacity across Nigerian federal public service. Keywords: Cybersecurity Governance, Cyber Risk Management, Policy Compliance, Public Administration, Nigeria, NIST Framework, NCPS, Cybercrimes Act
Public AdministrationClimate Change Governance in Nigeria
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About This Research Topic Climate change governance refers to institutional structures policies and coordination mechanisms through which state formulates implements and monitors action to mitigate greenhouse-gas emissions and adapt to climate impacts. Unlike many policy domains mapping neatly onto single tier or agency climate governance inherently multilevel and multi-actor: international commitments UNFCCC Paris Agreement must be translated into national legislation and institutions which must in turn be operationalised by subnational governments and sector-specific agencies with private-sector and civil-society actors complementary roles — structure Elinor Ostrom termed polycentric governance in recognition that no single-level mechanism can by itself adequately address phenomenon simultaneously global in cause and profoundly local in impact and implementation. At SCHOLARNESTHUB, we transform climate policy research into SEO-optimized academic resources. This study on climate change governance in Nigeria is crafted for students searching for public administration project topics and environmental management project topics . Nigeria climate-governance architecture developed substantially past several years. Climate Change Act 2021 signed 18 Nov 2021 first stand-alone comprehensive climate legislation in West Africa requiring government to establish National Climate Change Action Plan and five-year rolling carbon budget with specific annual targets and creating National Council on Climate Change NCCC inaugurated 2022 chaired by President with control over newly established Climate Change Fund. Nigeria revised NDC commits to unconditional 20% reduction emissions below business-as-usual by 2030 rising to conditional 47% contingent on international support alongside longer-term net-zero target 2050-2070 — with NCCC DG reaffirming at COP30 Belem Nov 2025 national mandate to achieve 32% emissions reduction by 2035. Despite developing national architecture first comprehensive empirical assessment across all 36 states — document and budget review national survey 1,306 respondents validation workshop over 600 participants — found low climate literacy among subnational officials weak public awareness limited policy development only handful states possessing dedicated climate policies or action plans fewer than 20% maintaining climate-related budget lines and weak cross-sectoral collaboration alignment with national frameworks (Okereke et al 2025). In response Federal Ministry of Environment in partnership with Society for Planet and Prosperity launched Subnational Climate Governance Performance Rating and Ranking 2025 explicitly designed to benchmark and drive reform across 36 states through comparative transparency — initiative Minister described Oct 2025 as reflecting climate change status as central to current federal administration policy focus. Main Abstract Climate change governance — institutional structures policies and coordination mechanisms through which state formulates and implements climate mitigation and adaptation action — has assumed growing prominence in Nigerian public administration formalised through Climate Change Act 2021 establishment of National Council on Climate Change (NCCC) in 2022 and Nigeria's Nationally Determined Contributions (NDCs) under Paris Agreement which commit country to 20% unconditional and 47% conditional reduction in emissions below business-as-usual by 2030 alongside longer-term net-zero target for 2050–2070. However recent large-scale empirical research — first comprehensive assessment of climate awareness policy and action across all 36 Nigerian states involving national survey 1,306 respondents and validation workshop over 600 participants — has found persistently low climate literacy among subnational officials weak policy development (only handful states possess climate policies or action plans) and fewer than 20% of states maintaining dedicated climate-related budget lines exposing substantial structural and institutional weaknesses in Nigeria multilevel climate-governance architecture. This study investigates institutional readiness and multilevel coordination for climate governance within selected federal and subnational institutions in Abuja FCT. Anchored on Polycentric Governance Theory Multilevel Governance Theory and Institutional Capacity Theory study adopts descriptive survey research design complemented by document analysis of Climate Change Act 2021 Nigeria NDCs and Subnational Climate Governance Performance Rating. Population comprises staff of NCCC relevant federal MDAs and FCT-level climate-focal-point officials with sample determined using Taro Yamane formula and selected through stratified random sampling. Data collected via structured questionnaire built on five-point Likert scale addressing three constructs: institutional climate-governance capacity (policy budget and personnel) inter-agency and multilevel coordination and perceived climate-action implementation effectiveness. Data analysed using descriptive statistics and inferential statistics (Chi-square simple linear regression and ANOVA) at 0.05 significance level. Study expected to establish current level of institutional climate-governance readiness identify factors shaping multilevel coordination effectiveness and determine statistical relationship between institutional capacity and perceived implementation effectiveness. Study concludes with recommendations for strengthening institutional capacity budgetary commitment and multilevel coordination to support Nigeria climate commitments.
Public AdministrationArtificial Intelligence Governance, Transparency and Accountability in Nigeria's Public Sector
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About This Research Projects As artificial intelligence increasingly mediates government decision-making—from benefits screening to fraud detection, resource allocation, and citizen chatbots—questions of governance, transparency, and accountability have moved to the centre of public administration. Unlike earlier ICT, machine learning systems can generate outputs difficult to explain even to developers, raising algorithmic opacity. International bodies responded with governance instruments: OECD AI Principles and NIST AI Risk Management Framework codify transparency, contestability, non-discrimination, human oversight. UK Ethics, Transparency and Accountability Framework and Algorithmic Transparency Recording Standard require public bodies to document and publish information about automated systems deployed. In Nigeria, digital transformation agenda anchored on National Digital Economy Policy and Strategy 2020-2030 and emerging National Artificial Intelligence Strategy articulates ambition to deploy AI across public sector. Nigeria Data Protection Act 2023 and establishment of Nigeria Data Protection Commission represent steps toward data-governance architecture relevant to AI accountability. Yet Nigerian scholarship on governance has focused predominantly on general corruption and corporate-governance-style reforms, with limited attention to AI-specific governance challenges. Explore public administration AI governance topics Main Abstract As AI systems increasingly mediate government decision-making and service delivery, governance, transparency, and accountability have moved from margins to centre of public administration scholarship. In Nigeria, enthusiasm for AI-enabled public services reflected in National Digital Economy Policy and Strategy 2020-2030 and emerging National AI Strategy has not been matched by equally mature regulatory and institutional architecture for governing how AI systems are procured, deployed, monitored, held accountable within MDAs. This study examines state of AI governance, transparency, accountability practice in selected federal MDAs in Abuja FCT. Drawing on Principal-Agent Theory, Public Accountability Theory, and OECD/NIST algorithmic accountability literature, study adopts descriptive survey design complemented by document/policy analysis. Population comprises administrative, ICT, compliance/audit staff of selected MDAs, sample via Taro Yamane formula with stratified random sampling. Data collected via structured 5-point Likert questionnaire addressing four constructs: institutional AI-governance structures, transparency practices, accountability and oversight mechanisms, staff perceptions of AI-related risk (bias, privacy, opacity). Analysis combines descriptives with inferential Chi-square and linear regression at 0.05 level. Study expected to establish extent to which MDAs institutionalized governance structures such as designated oversight officers, algorithmic impact assessments, public disclosure practices; identify gaps between policy commitments and operational practice; determine statistical relationship between strength of governance mechanisms and perceived transparency/accountability outcomes. Concludes with recommendations addressing regulatory clarity, oversight capacity, disclosure standards, citizen-redress mechanisms to guide NITDA, Bureau of Public Service Reforms, individual MDAs in building governance architecture commensurate with AI adoption ambitions.
Public AdministrationASSESSMENT OF LOCAL GOVERNMENT SERVICE DELIVERY IN SELECTED LOCAL GOVERNMENTS IN AKWA IBOM STATE
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About This Research Topic Local government occupies central place in theory and practice of democratic governance worldwide tier closest to people and by constitutional mandate expected to serve as primary vehicle through which grassroots development planned coordinated delivered. In Nigeria 1999 Constitution as amended recognises local government as third tier Section 7(1) guaranteeing democratically elected system and Fourth Schedule enumerates functions provision maintenance of primary healthcare participation in primary adult vocational education construction maintenance roads streets public highways provision markets motor parks public conveniences refuse sewage disposal registration births deaths marriages among others. These functions define local government service delivery process by which councils translate statutory responsibilities into tangible goods services improving welfare. Where local governments perform creditably citizens experience improved access healthcare safer roads better sanitation efficient civil registration. Conversely underperformance consequences felt directly dilapidated health centres uncollected refuse impassable roads non-functional markets. Since return to democracy 1999 Nigeria experimented with reforms including 1976 Local Government Reform most comprehensive attempt standardising structure nationwide despite reforms service delivery continues attracting scholarly policy attention because persistent gap between constitutional promise grassroots development and lived experience. Scholars attribute gap to inadequate funding over-dependence statutory allocation Federation Account weak IGR corruption mismanagement poor infrastructure inadequately motivated personnel weak monitoring limited citizen participation. Akwa Ibom State created 1987 comprises thirty-one LGAs each headed elected chairman and legislative council. Uyo state capital generally benefiting greater administrative attention higher IGR potential proximity state institutions while Ikot Ekpene historically significant commercial cultural centre rely more heavily statutory allocations. This article for SCHOLARNESTHUB presents rewritten assessment empirically comparing Uyo and Ikot Ekpene. For related governance research see public administration project topics on SCHOLARNESTHUB . Main Abstract Local governments occupy strategic position in governance architecture of Nigeria being tier closest to citizenry and primarily responsible for delivery of basic services such as primary healthcare primary education sanitation rural infrastructure civil registration. Despite constitutional recognition as third tier service delivery at this level remained subject of considerable public concern characterised by allegations of inefficiency poor infrastructure weak accountability low citizen satisfaction. Study assessed state of service delivery in local governments in Akwa Ibom State using Uyo Local Government Area and Ikot Ekpene Local Government Area as case studies. Study guided by four specific objectives: examine level of service delivery in selected local governments identify factors influencing service delivery assess level of citizens satisfaction with services rendered and determine relationship between funding/resource allocation and quality of service delivery. Study adopted survey research design and drew sample of 380 respondents from staff and residents of two LGAs using Taro Yamane formula and combination of stratified and simple random sampling. Structured questionnaire built on five-point Likert scale principal instrument complemented by key informant interviews with selected officials. Data analysed using descriptive statistics frequency counts percentages means standard deviation and inferential statistics independent samples t-test Pearson Product Moment Correlation simple linear regression with aid of SPSS version 25. Reliability established using Cronbach Alpha coefficient 0.84 indicating high internal consistency. Findings revealed service delivery in both LGAs rated below average with mean scores 2.41 for Uyo and 2.29 for Ikot Ekpene on four-point interpretation scale and no statistically significant difference existed between two LGAs in overall level of service delivery t 1.47 p greater than 0.05. Study further found strong positive statistically significant relationship between resource allocation/funding and quality of service delivery r 0.68 p less than 0.05 and that inadequate funding poor infrastructure corruption weak monitoring mechanisms low citizen participation were major factors constraining effective service delivery. Study concluded local government service delivery in study area falls short of citizens expectations principally due to fiscal administrative and governance constraints rather than absence of legal framework. Recommended among others full implementation of local government financial autonomy strengthening IGR institutionalisation of citizen participation mechanisms such as town hall meetings public expenditure tracking and periodic capacity building for personnel. Study contributes by providing empirically grounded comparative evidence on service delivery performance across two structurally different LGAs within same state and offers framework policymakers administrators can apply in diagnosing improving service delivery gaps.
Public AdministrationGOVERNANCE AND SERVICE DELIVERY IN LOCAL GOVERNMENTS
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About This Research Topic Local government is constitutionally the tier closest to the people, mandated by Section 7 of the 1999 Constitution of Nigeria to deliver primary healthcare, environmental sanitation, local roads, markets and other grassroots services. The promise is that decentralized governance better identifies local needs. Yet across Nigeria, service delivery remains poor—heaps of uncollected waste, dilapidated roads, under-equipped primary healthcare centres, and low citizen trust. Ikeja Local Government Area of Lagos State, the state capital and one of Nigeria’s most economically vibrant councils hosting Computer Village, Allen Avenue corporate cluster, and Murtala Muhammed Airport, exemplifies this paradox: relatively high internally generated revenue but persistent complaints about waste evacuation, drainage, and weak consultation. Explore public administration project topics This article rewrites the original case study on governance and service delivery in Ikeja LGA, preserving its survey methodology and findings while adding analytical depth for Scholarnesthub readers. Main Abstract This study examined the relationship between governance and service delivery in Nigerian local governments using Ikeja Local Government Area, Lagos State, as case study. Despite constitutional recognition as third tier closest to people, grassroots service delivery remains poor, marked by inadequate waste management, poor roads, weak primary healthcare and limited citizen participation. Guided by four objectives—to assess transparency and accountability, examine citizen participation, evaluate service delivery state, and determine governance-service delivery relationship—the study adopted descriptive survey design. Population 8,500 (staff and residents), sample 350 drawn via Taro Yamane formula using stratified and simple random sampling. Instrument: structured 5-point Likert questionnaire plus key informant interview guide, validated by experts, Cronbach Alpha 0.86. Analysis via SPSS v26 using descriptives (frequencies, percentages, mean, SD) and inferential (Pearson correlation, t-test, ANOVA, multiple regression). Findings: accountability and transparency moderate (grand mean 2.98), citizen participation low (2.63), overall service delivery below average (2.53). Correlation showed positive significant relationship between accountability/transparency and service delivery (r=.612, p<.05) and between citizen participation and service delivery (r=.487, p<.05). Regression revealed governance practices jointly explained 43.3% variance in service delivery (R²=.433, F(3,346)=87.45, p<.05), with accountability strongest predictor (β=.312, p<.05). Study concluded weak governance structures—low accountability, poor transparency, limited participation—significantly undermine service delivery. Recommended institutionalizing participatory budgeting, strengthening internal and external accountability mechanisms, improving fiscal autonomy, and leveraging digital platforms for transparency and engagement.
MathematicsINVENTORY MANAGEMENT OPTIMIZATION USING MATHEMATICAL MODELS
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About This Research Topic Every firm that stocks physical goods whether pharmaceutical distributor retail chain or manufacturing enterprise faces recurring mathematical decision: how much of each item to order at time and when to place that order so as to satisfy customer or downstream demand reliably while minimizing combined costs ordering too frequently incurring repeated fixed ordering or setup costs and holding excess inventory incurring storage capital obsolescence spoilage costs. Trade-off is of particular economic significance in Nigeria where working capital is often constrained and costly to access and where for essential goods such as pharmaceuticals stockouts carry consequences extending well beyond lost sales to genuine public health risk. Mathematical theory inventory management traces to pioneering work Harris 1913 who derived classical Economic Order Quantity EOQ formula by minimizing via elementary calculus sum annual ordering cost inversely proportional order quantity and annual holding cost directly proportional order quantity establishing celebrated square-root relationship between order quantity and underlying demand ordering-cost holding-cost parameters that remains foundational result inventory theory more than century later. The EOQ model was developed by Ford W. Harris in 1913 but R. H. Wilson consultant who applied it extensively and K. Andler are given credit for their in-depth analysis. Goal calculating EBQ is product produced required quantity required quality at lowest cost and classical EOQ model Harris 1913 calculates optimal order quantity annual demand ordering cost per order holding cost per unit per year formula considers demand rate fixed lead times regular holding ordering costs remain static. Subsequent extensions basic model to quantity discounts finite production rates stochastic demand single-period newsvendor settings multi-item budget-constrained optimization collectively constitute rich practically important body applied mathematics directly relevant operational financial performance any goods-holding enterprise. Recent inventory optimization frameworks include supply chain analytics dashboard EOQ reorder points safety stock optimization reorder point triggers replenishment before stock runs out ROP avg daily demand lead time plus safety stock where end-to-end retail demand forecasting system SARIMA Prophet XGBoost LightGBM Ensemble EOQ-based inventory optimization safety stock computation reorder point analysis across 20 SKUs service level target 95% Z 1.645 and safety stock Z times sigma_demand sqrt lead time Z 1.65 for 95% service level and reorder point avg daily demand lead time plus safety stock. For related materials see ScholarNestHub operations research collection . Main Abstract Effective inventory management balancing competing costs ordering too frequently against costs holding excess stock while avoiding stockouts that can be especially consequential for essential goods such as pharmaceuticals is fundamental applied mathematics problem confronting Nigerian distributors and retailers. Study develops comprehensive mathematical treatment inventory optimization spanning classical Economic Order Quantity EOQ model its extension to quantity discounts and finite production rates stochastic safety-stock and reorder-point analysis under demand uncertainty single-period newsvendor model and Lagrangian-multiplier approach to multi-item inventory optimization under binding working-capital budget constraint and applies resulting framework to original case study Nigerian pharmaceutical distributor managing eight stock-keeping units. Classical EOQ model solved analytically via calculus setting derivative total cost to zero and cross-validated numerically via constrained optimization yielded optimal order quantity 1,435 units against representative demand ordering-cost and holding-cost parameters with numerical and analytical solutions agreeing to within 0.000002 percent confirming both correctness derivation and its implementation. Extension to all-units quantity-discount schedule correctly identified lowest-price tier 410 naira per unit at orders 1,000 units or more as cost-minimizing once associated purchase-cost savings incorporated into total cost. Economic Production Quantity EPQ extension accounting for finite production replenishment rate reduced total annual cost by 36.8 percent relative to instantaneous-replenishment EOQ model reflecting smaller effective holding cost achieved when inventory accumulates gradually rather than arriving all at once. Stochastic reorder-point analysis incorporating demand variability during twelve-day lead time and 95 percent target service level computed required safety stock 48.4 units; strikingly naive reorder point set equal to mean lead-time demand alone without any safety stock was shown to imply exact 50 percent stockout probability on every replenishment cycle stark illustration necessity formal safety-stock calculation. Lagrangian multi-item model applied to eight-SKU case study under binding 800,000 naira average-inventory-investment budget constraint correctly proportionally shrank each item order quantity relative to unconstrained optimum increasing total ordering-plus-holding cost by 131,191 naira 20.0 percent relative to unconstrained optimum quantifying precise economic cost capital rationing. ABC analysis classified three of eight items as Class A together accounting for 70.3 percent annual inventory value directing management attention accordingly. Optimized multi-item policy achieved 25.3 percent cost reduction relative to naive uniform fixed-order-quantity baseline. Concludes mathematically rigorous inventory optimization properly extended to address quantity discounts production constraints demand uncertainty and binding capital constraints provides Nigerian distributors with substantial quantifiable cost-reduction opportunities and recommends systematic adoption EOQ-based ordering policies service-level-driven safety stock and Lagrangian budget allocation in place uniform or intuition-based inventory practices.
MathematicsTRANSPORTATION PROBLEM OPTIMIZATION FOR SUPPLY CHAIN LOGISTICS
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About This Research Topic Efficient distribution of goods from multiple production or storage locations to multiple demand locations among most economically consequential logistical problems confronting modern manufacturing and supply chain operations and of particular significance in Nigeria whose large land area geographically dispersed population centres variable road infrastructure quality combine to make transportation cost substantial component of delivered price of manufactured goods such as cement fertilizer refined petroleum products. Firm operating several plants each with fixed monthly output capacity and serving several regional markets each with specified demand faces mathematical problem determining how much to ship from each plant to each market minimising total transportation cost while fully satisfying demand and respecting capacity limits. This problem known as transportation problem special structure of linear program in which constraint matrix has distinctive network form permitting solution methods considerably more efficient than general-purpose simplex and admitting elegant duality theory expressed directly in terms of per-origin and per-destination shadow prices. First formalised by Hitchcock 1941 and Koopmans 1949 solution methods Northwest Corner Least Cost Vogel Approximation Method for initial basic feasible solution and MODI modified distribution or stepping-stone for iteratively improving to optimality remain foundational techniques in operations research worldwide. Despite availability of general-purpose LP software capable of solving as special case specialised methods retain value exploit network structure for efficiency yield dual shadow prices u_i v_j directly as by-product rather than requiring separately formulated dual and provide transparent hand-auditable window into how efficient distribution plan constructed transparency of value where non-specialist decision-makers must understand and trust plan. This article for SCHOLARNESTHUB implements and rigorously validates three initial methods and MODI optimality-improvement method addressing degeneracy and imbalance and applies validated framework to original case study Nigerian cement network four plants Ibese Gboko Obajana Calabar six markets Lagos Abuja Kano Port Harcourt Enugu Kaduna extracting shadow prices and comparing against naive baseline. For related optimisation studies see operations research project topics on SCHOLARNESTHUB . Main Abstract Efficient distribution of manufactured goods from multiple production sites to geographically dispersed markets central logistical challenge for Nigerian manufacturing firms whose profitability depends critically on minimizing substantial transportation costs arising from large land area and variable road infrastructure quality. Study develops comprehensive treatment of classical transportation problem special structure of linear program modelling minimum-cost distribution of homogeneous commodity from multiple supply origins to multiple demand destinations and applies it to original case study Nigerian cement manufacturing distribution network. Three initial-basic-feasible-solution construction methods Northwest Corner method Least Cost method and Vogel Approximation Method VAM implemented from scratch and compared on didactic three-origin four-destination problem with VAM found to reach true optimal solution directly 0.0 percent gap while Northwest Corner and Least Cost produced initial solutions 18.7 percent and 7.9 percent above optimal respectively. MODI modified distribution method implemented with explicit u-v dual-variable computation and stepping-stone loop-based pivoting shown to improve Least Cost initial solution to true optimum in two pivot iterations with result cross-validated exactly against independent general-purpose linear programming solver. Deliberately constructed degenerate problem in which Northwest Corner method produced fewer than required m+n-1 positive basic allocations correctly resolved using epsilon-perturbation technique preserving spanning-tree structure required for valid dual-variable computation. Unbalanced problem in which total supply exceeded total demand correctly solved through introduction of zero-cost dummy destination absorbing surplus capacity. Validated framework then applied to original case study four-plant six-market Nigerian cement distribution network plants at Ibese Gboko Obajana Calabar markets at Lagos Abuja Kano Port Harcourt Enugu Kaduna for which MODI-optimal distribution plan achieved total monthly transportation cost 90,000,000 naira in thousand-bag units 42.5 percent reduction relative to naive capacity-proportional allocation baseline costing 156,553,571 naira. Shadow prices dual variables extracted from optimal MODI tableau used to predict marginal cost impact of reallocating 10,000 bags monthly capacity from Calabar to Ibese plant shadow-price prediction 600,000 naira cost reduction matched actual cost change obtained by fully re-solving perturbed problem exactly providing striking numerical confirmation of transportation-problem duality theory. Study concludes transportation problem solved through properly validated combination of initial-solution heuristics and MODI optimality refinement provides Nigerian logistics planners with both computationally efficient and economically interpretable tool for minimum-cost distribution network design and recommends adoption of Vogel Approximation Method given demonstrated ability to reach or closely approach optimality without requiring further MODI refinement as preferred initial-solution heuristic for practical deployment.
MathematicsHEAT TRANSFER MODELING USING FINITE DIFFERENCE METHODS
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About This Research Topic Accurate heat conduction modeling is central to mathematical physics and practical engineering, from materials science to passive cooling design in tropical climates. The governing parabolic partial differential equation—the heat equation—was first derived by Fourier in 1822. While analytical solutions via separation of variables exist for simple geometries, most engineering problems require numerical solution. The finite difference method replaces continuous derivatives with discrete approximations on a grid, dating to Richardson (1911) and Crank and Nicolson (1947). Explore mathematics and physics project topics This article rewrites the original project on heat transfer modeling, preserving its three-scheme validation and Nigerian building wall application while adding depth for Scholarnesthub readers. Main Abstract Accurate modeling of transient heat conduction is essential to classical mathematical physics and to thermal design of buildings in tropical climates. This study develops and numerically solves the one-dimensional transient heat conduction equation using three finite difference schemes: explicit forward-time central-space (FTCS), fully implicit backward-time central-space (BTCS), and Crank-Nicolson, each implemented directly in Python without black-box solvers. All three were validated against exact analytical separation-of-variables solution for a rod with fixed ends and single-mode initial condition, achieving maximum absolute errors of 1.17×10⁻⁴, 2.83×10⁻⁴, and 8.32×10⁻⁵ respectively under matched discretization, confirming correct implementation. Von Neumann stability analysis established classical criterion r = α dt/dx² ≤0.5 for explicit scheme, demonstrated computationally using point-disturbance initial condition: explicit remained smoothly diffusive at r=0.45 but produced exponentially growing sign-alternating oscillation at r=0.55, exactly as amplification-factor theory predicts. Combined spatial-temporal convergence study confirmed second-order accuracy (empirical orders 2.00, 1.99, 2.00) for all three when mesh ratio held fixed during refinement, while pure-temporal study on fine spatial grid isolated first-order temporal accuracy of implicit scheme (order 0.94) and showed Crank-Nicolson temporal error falls below spatial truncation floor, consistent with its second-order temporal accuracy. Validated Crank-Nicolson was applied to original tropical building physics problem: periodic conduction through 200 mm walls of solid concrete, clay brick, and insulated composite under diurnal ambient cycle representative of Nigerian coastal climate (mean 27°C, amplitude 8°C). Insulated composite transmitted smallest fraction of outdoor swing to indoor surface (decrement factor 0.031 vs 0.046 for concrete) and longest thermal lag (6.16 h vs 2.56 h for concrete), demonstrating quantifiable comfort advantage. Study concludes validated finite difference methods provide rigorous actionable tool for tropical building design and recommends incorporation of decrement factor and time lag into Nigerian building guidance.
MathematicsMATHEMATICAL MODELING OF DRUG DOSAGE AND CONCENTRATION IN THE BLOODSTREAM
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About This Research Topic Safe drug therapy hinges on maintaining plasma concentration within a therapeutic window—above the minimum effective concentration but below the toxic threshold. Pharmacokinetics quantifies how absorption, distribution, metabolism and excretion shape this time course. For orally administered drugs, concentration rises as drug is absorbed from gut to blood, then falls as elimination clears it. Understanding this rise-and-fall profile mathematically enables rational dosing design rather than trial-and-error prescribing. Browse mathematics and pharmacology project topics This article rewrites the original undergraduate project on compartmental modeling of drug dosage, preserving its analytical Bateman solution, RK4 validation, and renal impairment analysis while adding explanatory depth for Scholarnesthub readers. Main Abstract Effective pharmacotherapy requires plasma concentration to remain within a therapeutic window defined by minimum effective and maximum safe concentrations. This study develops a compartmental model of drug dosage and concentration dynamics as a one-compartment open model with first-order absorption and elimination, extended to a two-compartment model with peripheral tissue. The governing ODEs were solved analytically via the classical Bateman function and numerically via fourth-order Runge-Kutta (RK4) in Python. Numerical accuracy was confirmed: RK4 matched the analytical solution within 5.45×10⁻⁷ mg/L and an independent LSODA solver within 1.86×10⁻⁵ mg/L. Under baseline parameters for a moderately hydrophilic renally cleared drug (500 mg dose, F=0.85, ka=1.2 h⁻¹, V=38 L, CL=6.5 L/h), single-dose predictions were Cmax 8.09 mg/L at Tmax 1.9 h, AUC 65.38 mg·h/L, half-life 4.05 h. Convergence study yielded empirical orders 1.04 for Euler and 4.22 for RK4, matching theory. Multiple dosing every 8 h showed accumulation to periodic steady state with ratio 1.34. Nonlinear least-squares fitting of one-compartment model to simulated two-compartment data gave R²=0.910, quantifying approximation error. Normalized sensitivity analysis identified dose and bioavailability as unit-elastic for Cmax and AUC, clearance dominant for AUC (sensitivity -0.923). Optimization derived maintenance dose 611.8 mg q8h to sustain average steady-state 10 mg/L within window 4–18 mg/L, giving steady-state peak 13.94 and trough 5.45 mg/L. Renal impairment scenario showed this regimen exceeds toxicity under any impairment degree, with severe impairment (20% normal CL) producing peak 50.12 mg/L, nearly 3× toxic threshold. The study demonstrates that rigorous, validated pharmacokinetic modeling is essential for individualized dosing, especially with impaired clearance, and recommends dose adjustment linked to quantitative clearance estimates.
MathematicsEPIDEMIC FORECASTING MODELS APPLIED TO MALARIA TRANSMISSION DYNAMICS
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About This Research Topic Malaria continues to rank among most significant public health challenges confronting sub-Saharan Africa and Nigeria bears disproportionate share of global burden according to successive World Malaria Reports Nigeria alone accounts for over quarter of global cases and comparable proportion of deaths majority among children under five and pregnant women. Disease caused by Plasmodium transmitted through bite of infected female Anopheles mosquitoes persistence governed by complex interplay biological environmental socioeconomic factors difficult to capture through observational epidemiology alone. Mathematical modelling since pioneering work of Sir Ronald Ross early twentieth century provided indispensable quantitative framework for transmission dynamics vector-borne diseases Ross original mosquito-human model later extended by Macdonald and generalised into compartmental SEIR framework established disease persistence and elimination characterised through single threshold quantity basic reproduction number R0 when exceeds unity sustained transmission when falls below unity dies out. Contemporary malaria models extend classical Ross-Macdonald by incorporating latency in host and vector populations giving rise to coupled SEIR human and SEI mosquito systems nonlinear no closed-form analytical solution necessitating numerical methods fourth-order Runge-Kutta finite difference adaptive-step LSODA standard tools while next-generation matrix methods provide rigorous analytical route to deriving R0. Beyond mechanistic modelling statistical regression forecasting combined with compartmental models produce short-term incidence forecasts supporting resource allocation drug procurement timing of vector-control campaigns seasonal regression well suited to malaria incidence in Nigeria fluctuating with rainy dry seasons influencing mosquito breeding habitat. This article for SCHOLARNESTHUB develops coupled SEIR-SEI model derives R0 analytically solves numerically using RK4 with independent cross-validation conducts stability and sensitivity analyses and combines mechanistic model with seasonal regression forecasting component. For similar epidemiological modelling see epidemiology project topics on SCHOLARNESTHUB . Main Abstract Malaria remains one of most persistent vector-borne diseases in sub-Saharan Africa with Nigeria accounting for disproportionately large share of global cases and mortality. Study develops and analyses compartmental epidemic forecasting model for malaria transmission dynamics formulated as coupled Susceptible-Exposed-Infectious-Recovered SEIR system for human host population and Susceptible-Exposed-Infectious SEI system for Anopheles mosquito vector population. Basic reproduction number R0 derived analytically using next-generation matrix method and evaluated numerically at R0 1.788 under baseline parameter assumptions representative of holoendemic transmission settings indicating sustained disease persistence. Seven-dimensional nonlinear system of ordinary differential equations solved using fourth-order Runge-Kutta RK4 scheme implemented in Python and validated against independent adaptive-step LSODA solver yielding maximum absolute discrepancy 8.88 x 10^-4 confirming numerical accuracy. Comparative convergence study between Euler method and RK4 established empirical convergence orders 0.99 and 4.06 respectively consistent with theoretical expectations. Local stability analysis of disease-free equilibrium conducted via Jacobian eigenvalue criterion confirmed instability of disease-free state under baseline parameters one eigenvalue with positive real part 0.0299 consistent with R0 greater than 1 while endemic equilibrium approximately 43.3 infectious humans and 76.8 infectious mosquitoes per reference cohort located using Newton-Krylov-based fsolve routine. Normalized forward sensitivity analysis identified mosquito biting rate sensitivity index 1.000 and mosquito natural death rate sensitivity index -0.708 as parameters exerting greatest proportional influence on R0 providing quantitative justification for vector-control interventions. Intervention scenario simulations demonstrated insecticide-treated net ITN coverage 60 percent reduces R0 below unity R0 0.983 while combined ITN and indoor residual spraying IRS coverage 80 percent reduces R0 to 0.536 effectively eliminating sustained transmission in model. Seasonal regression model fitted to simulated 24-month incidence series constructed to reflect patterns reported in Nigeria Malaria Elimination Programme NMEP surveillance data achieved coefficient determination R2 0.985 and used to forecast incidence over six-month horizon. Study concludes combined vector-control strategies offer most mathematically robust route to malaria elimination within study area and recommends intervention planning be informed by sensitivity-ranked parameters rather than uniform resource allocation. Model methodology and forecasting framework contribute reproducible data-validated tool for public health decision support in malaria-endemic regions of Nigeria.
MathematicsLinear Programming Approach to Optimal Resource Allocation in Agriculture
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About This Research Topic Agriculture remains largest employer of labour and principal contributor to GDP in Nigeria yet farm-level productivity and profitability persistently constrained by scarcity of key productive resources: arable land, irrigation water, seasonal labour and working capital. Farm managers whether individual smallholders or cooperative enterprises routinely face decision of how to allocate scarce resources among competing crop enterprises each with differing input requirements yields market prices production costs in order to maximise profitability or another objective such as food-security provision subject to hard limits imposed by available resources. At SCHOLARNESTHUB, we transform operations research projects into SEO-optimized academic resources. This study on linear programming approach to optimal resource allocation in agriculture is crafted for students searching for mathematics project topics and agricultural economics project topics . Resource allocation problem is in mathematical essence linear programming problem: decision variables are areas planted to each crop objective function linear combination of per-hectare profits and resource constraints linear inequalities bounding total land water labour capital use. Linear programming formalised by Dantzig 1947 with simplex algorithm provides efficient computational method for solving such problems even at scale of dozens or hundreds variables constraints and rich analytical theory duality theory yielding not merely optimal allocation but economically interpretable shadow prices quantifying marginal value of each scarce resource information of direct value to resource investment and expansion decisions. Application to agricultural planning dates to earliest years with Heady and Candler 1958 among first to systematically apply LP to farm planning establishing now-standard practice representing farm cropping decision as LP with land labour capital constraints. Despite more than six decades subsequent development including extensions to integer stochastic multi-objective basic LP crop-allocation model remains workhorse tool in agricultural economics and operations research valued for computational tractability rich duality-based economic interpretation and capacity to incorporate policy-relevant constraints such as food-security area floors and market-absorption ceilings alongside physical resource constraints. Main Abstract Efficient allocation of scarce agricultural resources land water labour and capital among competing crop enterprises fundamental economic and mathematical problem confronting Nigerian farm cooperatives and smallholder farmers whose profitability and food-security contribution depend critically on how limited resources deployed. This study develops linear programming model for optimal crop-mix resource allocation grounded in simplex method and duality theory and applies it to representative Nigerian farm cooperative cultivating five staple and cash crops maize lowland rice cassava sorghum and cowpea under constraints on available land irrigation water seasonal labour and working capital together with food-security and market-absorption bounds on individual crop areas. Small didactic two-crop problem first solved by hand-implemented tableau simplex converging to optimum (4,3) hectares in two pivot iterations and cross-validated exactly against HiGHS solver. Full-scale five-crop model solved via HiGHS dual-simplex algorithm identified optimal cropping plan zero hectares maize and rice 35 hectares cassava 33.33 hectares sorghum and 30 hectares cowpea yielding seasonal profit 34,813,333 naira with working capital as sole binding resource constraint (shadow price 1.933 naira of profit per naira of capital). Strong duality verified numerically to gap 7.5 x 10^-9 naira and complementary slackness confirmed exactly across all constraints and bound-constrained variables. Reduced-cost analysis showed maize and rice held at zero lower bounds to be marginally unprofitable under binding capital scarcity with shadow costs 3,000 and 79,667 naira per hectare respectively while cassava and cowpea held at upper market-capacity bounds exhibited positive shadow values 154,667 and 13,333 naira per hectare indicating relaxing market absorption limits would materially increase profit. Resource-availability sensitivity sweep and six-scenario parametric analysis (drought land expansion capital shortfall rice price shock and labour shortage) demonstrated optimal cropping plan highly sensitive to capital availability and to relative crop prices and comparatively insensitive to moderate variation in land or water availability given binding capital constraint. LP-optimal plan achieved 15.0 percent higher profit than naive equal-hectare allocation baseline. Integer-programming (whole-hectare) extension solved via branch-and-bound yielded solution within 0.153 percent of continuous LP relaxation confirming fractional-hectare LP solutions provide excellent and computationally efficient approximation to practically required integer allocation. Study concludes linear programming rigorously grounded in simplex and duality theory provides Nigerian agricultural planners with mathematically robust and economically interpretable tool for resource-constrained crop-mix optimization and recommends its adoption alongside routine shadow-price-based sensitivity reporting in cooperative and extension-service farm planning practice.
MathematicsMATHEMATICAL MODELING OF FLOOD PROPAGATION IN RIVER BASINS
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About This Research Topic Flooding is among most destructive and recurrent natural hazards affecting Nigeria with Niger-Benue river system principal drainage producing severe seasonal flooding displacing millions and causing extensive damage most notably 2012 and 2022 flood events. Propagation of flood wave along channel from point peak rainfall-generated runoff through successive downstream reaches to vulnerable settlements fundamentally mathematical problem in theory hyperbolic and parabolic partial differential equations and effective early warning depends critically on ability to forecast with adequate lead time how upstream hydrograph transforms downstream. Mathematical modeling of flood propagation in river basins Mathematical description unsteady open-channel flow originates with Saint-Venant equations coupled system nonlinear PDEs expressing conservation mass and momentum for one-dimensional shallow water flow first derived 1871. While full Saint-Venant captures complete dynamics including backwater effects and downstream boundary influences computationally demanding and for many practical applications can be simplified without significant loss to kinematic wave approximation in which momentum equation reduced to balance between gravitational and frictional forces yielding single first-order hyperbolic PDE relating discharge directly to channel rating curve. Kinematic wave equation while elegant and efficient has well-known limitation: because purely advective predicts flood wave propagates downstream without any reduction in peak discharge prediction inconsistent with attenuation and dispersion observed in genuine river floods which arises physically from diffusive effects longitudinal pressure gradients and channel storage not captured. Muskingum-Cunge method diffusion-wave routing technique developed by Cunge 1969 reformulating classical Muskingum hydrological routing with physically based channel-derived parameters addresses limitation by incorporating numerical diffusion term calibrated to match physical diffusivity of full dynamic wave equation and remains among most widely used flood routing methods worldwide. Both kinematic and Muskingum-Cunge require numerical solution for all but simplest cases and reliable application depends on understanding numerical stability and convergence properties of finite difference schemes governing hyperbolic kinematic wave by Courant-Friedrichs-Lewy CFL condition first identified 1928 foundational analysis hyperbolic PDEs. This study situated within this tradition formulates linear and nonlinear kinematic wave equations derives validates exact analytical method-of-characteristics solution for linear case implements validates explicit upwind and Lax-Wendroff schemes formally derives computationally demonstrates CFL criterion investigates characteristic downstream steepening and eventual shock formation predicted by nonlinear theory implements Muskingum-Cunge and directly compares physically realistic peak attenuation against non-attenuating kinematic prediction and applies validated framework to original applied case study 120km reach representative of Nigerian river basin. Main Abstract Flooding along Nigeria major river systems particularly Niger-Benue basin recurs seasonally and imposes severe human economic infrastructural costs underscoring need for mathematically rigorous flood propagation models capable supporting early warning and flood management decisions. This study develops and numerically solves kinematic wave equation for flood routing in river channels together with widely used Muskingum-Cunge diffusion routing method and applies resulting validated framework to original case study of flood propagation along stylized reach representative of Nigerian river basin. Linear kinematic wave equation solved analytically via method of characteristics yielding exact travelling-wave solution against which explicit upwind finite difference scheme and second-order Lax-Wendroff scheme validated achieving maximum absolute errors 2.32 and 0.011 cubic metres per second respectively at Courant number 0.144. Von Neumann-type Courant-Friedrichs-Lewy CFL stability analysis established criterion Cr = c dt/dx <=1 for upwind scheme and threshold demonstrated computationally using localized discharge pulse: scheme remained stable and diffusive at Cr 0.80 but produced unbounded oscillatory growth reaching magnitude more than twenty thousand times initial disturbance within three hours at Cr 1.15. Convergence study conducted using full spatial-profile comparison at fixed evaluation time to avoid single-point tracking artifacts confirmed empirical convergence orders 0.79 and 1.26 for upwind and Lax-Wendroff respectively both consistent in ranking with though moderately below theoretical first- and second-order accuracy discrepancy attributed to finite rather than infinite smoothness of realistic flood hydrograph shape functions. Nonlinear kinematic wave equation formulated using Manning's-equation rating curve then applied to 20-kilometre validation reach and shown to reproduce characteristic downstream steepening of rising limb predicted by theory of converging characteristics with rising-limb duration compressing from 29.9 minutes at upstream boundary to 6.0 minutes after 20 kilometres propagation consistent with analytically estimated kinematic shock formation time 1.12 hours. Because kinematic wave equation purely advective and predicts no reduction in peak discharge its output compared against Muskingum-Cunge diffusion routing method which incorporates physically realistic peak attenuation: over same 20-kilometre reach Muskingum-Cunge routing produced 45.4 percent peak attenuation compared with 10.4 percent attributable to numerical diffusion for kinematic wave scheme demonstrating physical necessity of diffusion rather than pure advection term for realistic flood peak forecasting. Sensitivity analysis found peak outlet discharge to respond with comparable magnitude and opposite sign to channel roughness sensitivity index -0.47 and bed slope sensitivity index 0.50. Finally validated Muskingum-Cunge framework applied to original applied case study routing design flood hydrograph over 120-kilometre reach representative of Niger-Benue river system predicting 7.75-hour peak travel time and 0.53 percent peak attenuation across reach results directly relevant to design upstream-to-downstream flood early warning lead times. Study concludes finite difference and diffusion routing methods when rigorously validated against analytical solutions and formal stability theory provide mathematically defensible tools for flood forecasting in Nigerian river basins and recommends incorporation into operational early warning systems. Keywords: kinematic wave equation, flood routing, Muskingum-Cunge method, CFL stability condition, finite difference method, Niger-Benue river basin, Lax-Wendroff
MathematicsOPTIMIZATION OF SCHOOL BUS AND STAFF TRANSPORTATION ROUTING USING GRAPH THEORY
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About This Research Topic Daily pupil and staff transportation is a major cost and safety challenge for Nigerian schools. Determining which bus picks which pupils, in what order, to minimize distance while respecting seating capacity is a classic combinatorial optimization problem. With rising fuel costs, efficient routing directly impacts budgets, punctuality, and safety. Explore mathematics project topics on optimization This article rewrites the original undergraduate project on school bus routing, preserving its exact Held-Karp benchmark and 16-stop Nigerian case study while adding explanatory depth for Scholarnesthub readers. Main Abstract Efficient school bus and staff transport routing to collect all pupils at minimum travel distance under vehicle capacity is a daily operational problem for Nigerian schools. This study develops a graph-theoretic treatment grounded in shortest-path theory, the travelling salesman problem (TSP), and the capacitated vehicle routing problem (CVRP), applied to an original Nigerian school district case study. Dijkstra shortest-path and Kruskal minimum-spanning-tree algorithms were implemented on a seven-node illustrative network to establish foundations. A nine-node (one depot, eight stops) single-vehicle problem was solved exactly via Held-Karp dynamic programming and compared to Nearest-Neighbor heuristic and 2-opt local search; Nearest-Neighbor alone was 8.2% above optimum, while 2-opt refinement reached the exact optimum, visually confirmed by elimination of crossing edge. The framework was extended to CVRP and applied to a 16-stop district with heterogeneous pupil counts and 45-seat capacity, solved via Clarke-Wright Savings algorithm followed by 2-opt refinement, yielding four-bus solution covering 128.4 km total daily distance. This achieved 56.4% reduction versus naive one-bus-per-stop baseline and 11.4% reduction versus Nearest-Neighbor capacity-splitting baseline. Capacity sensitivity analysis showed monotonically diminishing returns between seating capacity and both total distance and buses required, with marginal benefit declining sharply beyond ~50 seats for this demand pattern. The study concludes graph-theoretic optimization combining exact verification for small instances with efficient heuristics for realistic scale provides Nigerian administrators a rigorous actionable tool, recommending Clarke-Wright with 2-opt as practical standard.
EconomicsTHE ECONOMICS OF SKILLS MISMATCH IN GRADUATE UNEMPLOYMENT
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About This Research Topic Nigeria higher-education system produces hundreds of thousands of graduates annually yet graduate labour market characterised by persistently high unemployment and more strikingly widespread underemployment many graduates who secure work find themselves in jobs that neither require nor make use of qualifications they hold. Study of skills mismatch among Nigerian university graduates finds empirically graduate skills demand exceeds supply in some dimensions even as broader survey evidence documents substantial educational mismatch across graduate labour market echoing earlier findings by Dabalen and colleagues. At continental level African Development Bank working paper using school-to-work transition survey data across ten African countries finds skill and educational mismatches prevalent among employed African youth 17.5 percent overskilled 28.9 percent underskilled 8.3 percent overeducated 56.9 percent undereducated relative to current job with overskilling and overeducation associated with wage penalty and undereducation wage premium Morsy & Mukasa 2019. Economics literature has developed specific well-established econometric framework for quantifying wage consequences of vertical qualification-level mismatch: Overeducation-Required-Undereducation ORU earnings model introduced by Duncan and Hoffman 1981 and extended by Verdugo and Verdugo 1989 surveyed by Leuven and Oosterbeek 2011. Rather than estimating single undifferentiated return to years schooling as in conventional Mincer 1974 earnings function ORU decomposes attained schooling into three components years actually required by current job any surplus years overeducation and any deficit years undereducation allowing separately estimate return to each. This study for SCHOLARNESTHUB applies ORU framework to Nigerian graduate labour-market data providing econometrically grounded decomposed picture how vertical mismatch specifically affects graduate earnings complementing descriptive incidence-focused existing Nigerian literature. For similar labour economics studies see economics project topics on SCHOLARNESTHUB . Main Abstract Study examines economics of skills mismatch in Nigerian graduate employment using Duncan-Hoffman 1981 Overeducation-Required-Undereducation ORU earnings-decomposition framework. Nigerian graduate labour-market commentary documented substantial educational mismatch and African Development Bank study finds across ten African countries 8.3 percent of employed youth are overeducated and 56.9 percent are undereducated relative to jobs with overeducation associated with wage penalty and undereducation with wage premium. Study extends framework specifically to Nigerian graduates surveying 400 employed OND/HND Bachelor's Master's PhD holders constructing ORU decomposition using self-reported job-requirement measure. Results show 22.5 percent of sampled graduates are adequately matched 38.2 percent are overeducated averaging 1.99 surplus years and 39.2 percent are undereducated averaging 1.77 deficit years. Duncan-Hoffman ORU wage model finds significant positive returns to required education 9.2 percent per year p<0.001 and overeducation years 6.7 percent per year p<0.001 and significant wage penalty for undereducation years −3.7 percent per year p 0.009. Wald test confirms return to required education significantly larger than return to overeducation years p 0.047 replicating classic Duncan-Hoffman wage-ranking pattern. ORU model explains meaningfully more wage variation R2 0.435 than conventional Mincer benchmark that ignores mismatch R2 0.389 demonstrating practical value of fuller decomposition. Study concludes vertical skills mismatch carries real asymmetric wage cost in Nigerian graduate labour market and recommends curriculum reform career-guidance programming to support mismatched graduates transition into better-matched roles and routine incorporation of job-requirement measures into national graduate-tracer surveys.
EconomicsINFORMAL SECTOR TAXATION AND REVENUE MOBILIZATION IN DEVELOPING ECONOMIES
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About This Research Topic The informal sector dominates employment and output across Sub-Saharan Africa, accounting for 40-60% of GDP in countries like Nigeria, yet contributes disproportionately little tax revenue. This revenue paradox makes informal taxation central to domestic resource mobilization. Kano metropolis, anchored by historic markets like Kurmi and Kantin Kwari, exemplifies both the scale and complexity of the challenge. While early policy treated the informal sector as an untapped base for presumptive taxes, recent scholarship emphasizes governance gains, equity, and tax morale spillovers. See our economics research project topics This article rewrites the original project on informal sector taxation in developing economies, preserving its Tobit methodology and Kano evidence while adding analytical depth and SEO structure for Scholarnesthub readers. Main Abstract This study examines determinants of informal-sector tax and levy payment and estimates revenue-mobilization potential in Kano metropolis using a Type I Tobit censored regression. The informal sector is large in Sub-Saharan Africa but contributes little tax, with many operators paying zero—a feature OLS handles poorly. Grounded in Allingham and Sandmo’s economic deterrence model, Ability-to-Pay Theory, and tax morale/institutional theory, the study surveyed 350 traders, artisans, and service providers in Kano, where 37.7% reported paying no formal tax or levy in the prior twelve months. Tobit results show business income (β=3,534.13, p<0.001), business size, and years operating significantly affect payment as ability-to-pay factors; tax morale (β=2,431.97, p<0.001), perceived enforcement (β=2,249.19, p<0.001), and trust in government (β=1,461.91, p<0.001) are independently significant; trade association membership is the strongest binary determinant (β=5,147.96, p<0.001). McDonald and Moffitt marginal effects decomposition confirms association membership, income, and size as largest unconditional contributors to expected revenue. Observed average payment was ₦4,379.60 versus model-implied average if all paid according to latent capacity-willingness of ₦6,403.13, implying 31.6% revenue potential from closing compliance gaps rather than sector growth. The study recommends community-taxation partnerships with market associations combined with trust-building and credible enforcement communication as most promising levers for Kano State and comparable jurisdictions
EconomicsMICROFINANCE EFFECTIVENESS IN REDUCING RURAL POVERTY
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About This Research Topic Poverty remains disproportionately concentrated in rural Nigeria where limited access to formal credit thin labour markets and dependence on rain-fed smallholder agriculture combine to constrain household income-generating capacity. Nigeria National Bureau of Statistics estimated national poverty line at approximately ₦137,430 per person per year based on 2018/19 Nigeria Living Standards Survey with poverty incidence markedly higher in rural than urban areas NBS 2020. In Nigeria 40.1 per cent total population classified as poor in other words on average four out of 10 individuals Nigeria have real per capita expenditures below N137,430 per year this translates to over 82.9 million Nigerians considered poor by national standards. NBS report is based on data from latest round Nigerian Living Standards Survey conducted 2018-2019 with support from World Bank Poverty Global Practice and technical assistance from LSMS program. Microfinance institutions MFIs have been positioned both by Nigerian policymakers and broader international development community as central instrument for addressing this rural poverty gap on theoretical premise that rural poor not inherently uncreditworthy but excluded from formal finance by collateral requirements and high transaction costs conventional banks unwilling to bear for small high-frequency rural loans Yunus 1999 as foundational to Grameen model subsequently adapted across Nigeria Sub-Saharan Africa grounded in Stiglitz and Weiss 1981 credit-rationing theory and Grameen group-lending model social-collateral logic. Nigeria microfinance sector expanded substantially since Central Bank Nigeria 2005 Microfinance Policy Regulatory Supervisory Framework formalised licensing microfinance banks MFBs alongside informal semi-formal cooperative community-based lending structures. Despite expansion empirical evidence whether microfinance participation translates into measurable poverty reduction rural Nigerian households remains mixed. A propensity-score-matching study southwest Nigeria finds microfinance loans make favourable contributions poverty alleviation though same study cautions continued government support remains necessary Kasali 2020. Separate southwest Nigeria study spanning Ogun Osun Oyo states using sample 1,134 microfinance beneficiaries and non-beneficiaries finds microfinance has only marginal effects rural poor. By contrast logit-based southwest Nigeria study using AMJU Unique Microfinance Bank Ltd clients finds positive statistically significant relationship between microfinance operational strategy poverty alleviation. Existing evidence includes assessing impact adoption agroforestry technology food production poverty reduction farming households Oyo State Nigeria propensity score matching PSM and Foster Greer Thorbecke FGT analysis and Foster-Greer-Thorbecke 1988 used measure poverty index poverty measurement before after collection loan microfinance bank standard living where propensity score distribution common support propensity score estimation shows results from covariate balancing tests both before after matching and Foster-Greer-Thorbecke formula used measure poverty index. For related materials see ScholarNestHub development economics collection . Main Abstract Study examines effectiveness microfinance participation in reducing rural poverty in Oyo State Nigeria using propensity score matching PSM to address selection bias inherent comparing self-selected microfinance participants and non-participants. Nigeria National Bureau of Statistics estimates national poverty line at approximately ₦137,430 per person per year with poverty incidence markedly higher in rural areas and existing southwest Nigerian evidence on microfinance poverty-reduction effectiveness genuinely mixed with some PSM-based studies finding favourable effects and others finding only marginal effects. Grounded in Stiglitz and Weiss 1981 credit-rationing theory and Grameen group-lending model social-collateral logic study surveys 360 rural households 176 microfinance participants 184 non-participants across four Local Government Areas Oyo State estimating logit propensity-score model microfinance participation nearest-neighbour matching with covariate-balance diagnostics and Foster-Greer-Thorbecke FGT poverty-index decomposition both before and after matching. Results show poverty headcount ratio 6.8% among microfinance participants versus 32.6% among non-participants in unmatched sample. Household head education farm size farming as primary occupation and proximity to MFI branch significantly predict participation. After matching 136 treated households to comparable controls achieving adequate covariate balance with post-matching standardised bias below 10% for all covariates estimated average treatment effect on treated is ₦4,267.21 per month increase in per capita expenditure p<0.001 and 25.7-percentage-point reduction in probability being poor p<0.001. Matched-sample FGT decomposition confirms lower poverty incidence depth and severity among participants. Study concludes microfinance participation delivers statistically significant and economically meaningful poverty-reduction effect in study area that survives correction for observable selection bias and recommends continued expansion rural microfinance access particularly through branch-network or agent-based delivery models that address significant distance barrier identified in propensity-score model.
EconomicsREMITTANCES AND HOUSEHOLD WELFARE IN MIGRANT-SENDING ECONOMIES
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About This Research Topic International migration and remittances it generates have become one of most significant sources of external finance for developing economies in many cases exceeding both foreign direct investment and official development assistance. Nigeria is Africa largest recipient of remittances in absolute terms and Edo State in South-South geopolitical zone has been repeatedly documented as country single largest migrant-sending state with particularly well-established migration corridor to Europe dating back several decades (Obisie-Nmehielle & Ike, 2017). Remittances sent home by migrants used variously for household consumption, education, healthcare, housing, occasionally productive investment represent potentially significant household-level channel through which international migration affects welfare and development outcomes. Remittances and household welfare in migrant-sending economies Empirical literature on remittances and household welfare in Nigeria while growing consistently faced methodological challenge: household decisions to send migrant abroad and resulting remittance flows not randomly distributed. Households successfully sending migrant and receiving substantial remittances plausibly differ in unobserved ways in underlying wealth, social networks, risk tolerance, or earning potential differences that could independently explain why remittance-receiving households appear better off regardless of genuine causal effect. Chukwuone et al. 2008 explicitly address concern for Nigeria using IV estimation to assess whether remittances have effect on poverty while Fonta et al. 2011 use poverty and Gini decomposition to document poverty falls substantially across all six geopolitical zones as result of inflows. Obisie-Nmehielle and Ike 2017 using 2009 World Bank Migration Survey find having international migrant and receiving remittances significantly increases welfare using consumer and durable-asset indices analysed through OLS and probit though without explicit IV correction. This study builds directly on literature by applying IV 2SLS strategy specifically designed to isolate causal effect of remittances on welfare from confounding influence of unobserved characteristics using historical community migration-network density and distance to Lagos as instruments following broader international literature McKenzie and Rapoport 2007 Woodruff and Zenteno 2007 and migration-cost proxies. Main Abstract This study estimates causal effect of remittances on household welfare in Edo State Nigeria - country's leading migrant-sending state - using instrumental variables two-stage least squares strategy to address endogeneity of household remittance receipt. Existing Nigerian evidence generally finds positive association between remittances and household welfare but much literature does not formally correct for possibility that unobserved household characteristics jointly determine both migration/remittance behaviour and welfare outcomes. Grounded in New Economics of Labour Migration framework this study surveys 340 households 71.2% report remittance receipt instrumenting per capita household remittances with community migration-network density share households in community with international migrant as of 2010 baseline and household distance to Lagos proxy for migration logistics cost following migration-network instrument design established by McKenzie and Rapoport 2007. Naive OLS benchmark finds coefficient 0.757 p<0.001 on per capita remittances in per capita expenditure equation. First-stage regression confirms both instruments strong and correctly signed joint F-statistic 83.49 p<0.001. 2SLS estimate 0.679 p<0.001 somewhat below OLS estimate in theoretically expected direction though Wu-Hausman test statistic 0.922 p0.338 does not provide statistically decisive evidence of endogeneity in this sample and Sargan overidentification test statistic 0.308 p0.579 does not reject instrument validity. Study concludes remittances make statistically and economically significant robust contribution to household welfare in Edo State with estimated marginal propensity to consume out of remittances approximately 0.68-0.76 and recommends continued investment in formal low-cost remittance-transfer infrastructure and diaspora-engagement programming recognising substantial welfare contribution. Keywords: remittances, household welfare, instrumental variables, migration network, two-stage least squares, Edo State Nigeria, McKenzie Rapoport
EconomicsDigital Lending Platforms and Access to Credit for Small and Medium Enterprises
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About This Research Topic Access to credit remains one of most persistent constraints facing SMEs in Nigeria and across Sub-Saharan Africa. SMEs widely regarded as engine room of Nigerian economy accounting for estimated 48% of national GDP and roughly 84% of total employment according to SMEDAN 2023. Despite outsized contribution sector continues to operate under severe financing constraints: limited collateral thin or absent credit histories high transaction costs of small-ticket lending and reluctance of deposit money banks to extend working-capital facilities to informal or semi-formal enterprises. At SCHOLARNESTHUB, we transform fintech and SME financing research into SEO-optimized academic resources. This study on digital lending platforms and access to credit for SMEs in Lagos State is crafted for students searching for business administration project topics and finance project topics . Traditional lending institutions historically relied on collateral-based underwriting audited financial statements lengthy processing cycles poorly matched to operating realities of most SMEs majority micro-enterprises minimal documentation. Mismatch produced what theoretical literature describes as credit rationing: persistent excess demand at prevailing interest rate not resolved by price adjustment because lenders fear adverse selection moral hazard among unobservably risky borrowers (Stiglitz & Weiss 1981). Emergence of digital lending platforms — mobile-app-based algorithm-driven lenders such as FairMoney Carbon Branch Palmcredit and similar fintech ventures — advanced as potential structural response. These platforms depart from collateral-centred model by leveraging alternative data: mobile-money transaction histories airtime top-up patterns digital-payment records behavioural data from smartphone usage to construct real-time creditworthiness scores. By substituting data-driven risk assessment for physical collateral digital lenders can in principle extend credit to previously unbanked SMEs within minutes to hours rather than weeks required by conventional bank appraisal. Nigeria fintech sector expanded rapidly: SME fintech usage reported risen from approximately 6% in 2014 to 42% in 2024 even though digital loan penetration remains low around 12% with rural northern markets lagging behind urban southern centres. Fintech investment reached roughly $1.26bn in 2022 and CBN introduced regulatory framework in 2023 targeting operational conduct of digital lending platforms followed by expanded open banking framework intended to widen access to alternative data. Yet promise not unambiguous: Bjorkegren et al 2022 finds approval raises subjective well-being but does not translate into statistically significant increase in income or measurable long-run business expansion. Same features that make digital lending fast also generate consumer-protection risks including opaque pricing aggressive debt-recovery data-privacy concerns. Main Abstract This study examines effect of digital lending platform usage on access to credit among SMEs in Lagos State Nigeria. Despite over decade of financial-inclusion policy efforts Nigerian SMEs — contributing estimated 48% GDP and 84% employment — continue to face significant credit constraints rooted in collateral requirements thin credit histories and high fixed costs of small-ticket loan appraisal borne by conventional banks. Rapid rise of fintech-based digital lending platforms which substitute alternative behavioural and transactional data for collateral-based underwriting advanced as potential remedy yet rigorous firm-level quantitative evidence from Nigeria remains limited. Grounded in credit-rationing theory of Stiglitz and Weiss (1981) and delegated-monitoring theory of Diamond (1984) study estimates maximum-likelihood probit model of realised SME credit access as function of digital lending platform usage and set of firm- and owner-level covariates using structured questionnaire administered to 320 SMEs across four LGAs in Lagos State. Results show 55.3% sampled SMEs used digital lending platform in preceding twelve months and 72.2% obtained credit over same period. Digital lending platform usage positive and statistically significant at 1% level (probit coefficient = 0.816; average marginal effect = 23.1 percentage points) indicating platform users substantially more likely to access credit than otherwise comparable non-users net of financial literacy collateral credit history education firm size firm age banking relationship and urban location. Financial literacy and medium firm size also independently significant determinants of credit access. Diagnostic tests indicate model well-specified with no material multicollinearity (all VIF <10) and satisfactory calibration. Study concludes digital lending platforms make economically meaningful contribution to closing Nigeria SME financing gap while cautioning that access to credit does not automatically guarantee improved business performance. Policy recommendations include continued regulatory support for alternative-data-based underwriting infrastructure alongside strengthened consumer-protection safeguards and integration of financial-literacy training into SME development programmes.
EconomicsURBANIZATION AND ITS IMPACT ON INCOME INEQUALITY IN NIGERIA
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About This Research Topic Nigeria like much of Sub-Saharan Africa is undergoing rapid urbanization share of national population residing in urban areas risen substantially over recent decades with states such as Lagos Federal Capital Territory Rivers now majority-urban while several northern and middle-belt states remain predominantly rural. This uneven urbanization landscape provides fertile ground for empirically examining question with long theoretical lineage: does urbanization widen or narrow income inequality? Kuznets 1955 foundational hypothesis proposed inverted-U relationship between economic development of which urbanization both driver and consequence and inequality inequality first rising as population shifts from relatively equal low-productivity rural/agricultural economy into more unequal higher-productivity but initially dualistic urban/industrial economy before eventually falling as urbanization matures and gains diffuse more broadly. Recent empirical work refined hypothesis using distributional rather than purely mean-based methods. Ali Attiaoui Khalfaoui and Tiwari 2021 applying Method of Moments Quantile Regression across low middle high-income country panels 1990-2014 find urbanization effect on inequality itself heterogeneous across income distribution: in high-income countries urbanization increases inequality specifically from third quantile upward while in upper-middle-income countries no significant effect in low and middle quantiles but significant increase in higher quantiles. This distributional heterogeneity invisible to model estimating only single average effect motivates use of quantile regression alongside classical Kuznets-curve test to examine urbanization-inequality relationship in Nigerian context. This article for SCHOLARNESTHUB presents rewritten SEO-optimized study combining state-level test across 36 states plus FCT and household-level quantile regression of 420 households. For similar inequality analyses see development economics project topics on SCHOLARNESTHUB . Main Abstract Study examines impact of urbanization on income inequality in Nigeria combining state-level test of classic Kuznets inverted-U hypothesis with household-level quantile-regression analysis of urban income premium distributional heterogeneity. Kuznets 1955 proposed inequality first rises then falls as economy urbanizes and develops while recent cross-country evidence using Method of Moments Quantile Regression finds urbanization inequality effects frequently concentrated in upper quantiles specifically. Grounded in Kuznets hypothesis dual-economy/migration theory and distributional extension study estimates quadratic Kuznets-curve regression of Gini coefficient on urbanization rate across all 36 Nigerian states and Federal Capital Territory 37 units and household-level quantile regression of log per capita income on urban residence across 420 surveyed households. State-level model confirms statistically significant inverted-U relationship R2 0.806 F 38.04 p<0.001 with urbanization rate entering positively p<0.001 and its square negatively p<0.001 implying Kuznets-curve turning point at approximately 55.6 percent urbanization. Governance quality significantly negatively associated with inequality independent of urbanization. At household level urban households exhibit substantially higher Gini 0.429 than rural households 0.346 and while OLS finds average urban income premium 11.5 percent p 0.045 quantile regression reveals premium heavily concentrated at top of distribution rising from statistically insignificant even negatively signed coefficients at 10th-25th percentiles to highly significant 34.9 percent premium at 90th percentile. Study concludes Nigerian urbanization aggregate Kuznets-curve-consistent inequality-increasing phase plausibly driven by urban income advantage concentrated among higher-income households and recommends urban-development policy prioritise broadening lower-income urban residents access to formal-sector opportunity rather than relying on general infrastructure investment alone.
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