Nnamdi Azikiwe University Journals
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GLOBAL VALUE CHAIN, ECONOMIC INTEGRATION AND ECONOMIC DEVELOPMENT: IMPLICATION FOR ECOWAS
No full textThis study examined the effect of Global Value Chain and economic integration on economic development in selected ECOWAS countries. This paper used a Linear Panel Autoregressive Distributed Lags/Pooled Mean Group (ARDL/PMG) approach to determine the effect of Global Value Chain and economic integration on economic development among ECOWAS countries between 1995 and 2022. From the panel ARDL/PMG estimation, we found that in the long run, Global Value Chain and Foreign Direct Investment have significant long-run relationship with GDP per capita among selected ECOWAS countries. A 1% increase in Global Value Chain and Foreign Direct Investment will increase the GDP per capita by 31% and 16% respectively among the selected ECOWAS countries. The short run result revealed that Global Value Chain and Domestic Credits to Private sector have contradictory relationship with GDP per capita. While Global Value Chain revealed positive relationship, Domestic Credits to Private sector showed negative relationship. The speed of adjustment of the economic development function to equilibrium in the event of disequilibrium in the short run is 43%. Given the findings, this study recommends a more vibrant participation of ECOWAS member countries in Global Value Chain and economic integration considering its resultant positive effect on economic development. 
JURISDICTION OF UK COURTS TO HEAR AND DETERMINE CLAIMS FOR OIL-RELATED ENVIRONMENTAL DAMAGE OCCURRING IN NIGERIA: REFLECTIONS ON THE CASE OF OKPABI V. ROYAL DUTCH SHELL PLC1*
No full textIn Okpabi v. Royal Dutch Shell PLC, the United Kingdom Supreme Court established that in appropriate cases, a parent company domiciled in the United Kingdom could be held vicariously responsible in a UK Court for the polluting activities of its Nigerian subsidiary occurring wholly within Nigeria. Through an analysis of the Okpabi case, this article examines the jurisdictional challenges that Nigerian litigants are bound to face should they seek redress in English courts for environmental damage caused by the oil operations of Multi-National Oil Companies (MNOCs) in Nigeria. The article finds that the Okpabi series of cases (including the recent English High Court ruling delivered on the 20th day of June 2025, that Royal Dutch Shell PLC and its now former Nigerian subsidiary can be held legally responsible for historic oil pollution in Nigeria) offers potential opportunities for Nigerian victims of oil-related environmental damage desirous of instituting their cases in England. Evidence from the cases indicates that the English courts are ready and willing to exercise jurisdiction to hear and determine claims for damages for the polluting activities of MNOCs in Nigeria, provided that there is an “anchor” defendant domiciled within the United Kingdom.
PENAL RESPONSIBILITY AND SANCTIONS FOR VIOLATION OF INTERNATIONAL HUMANITARIAN LAW RULES: AN APPRAISAL
No full textAs the world continues to urbanize, armed conflicts are also increasing, leading to greater violation of the rules of armed conflict with devastating effect on civilians and infrastructure. Violations of International Humanitarian Law (IHL) often referred to as war crimes, carry significant penal responsibility and sanctions. Individuals and states can be held accountable for violation of rules of IHL, with sanctions ranging from individual criminal prosecutions to state responsibility for reparations. States are obligated to suppress all violations of IHL rules set out in the four Geneva Conventions and Additional Protocols. The Conventions and their additional Protocols require States to enact criminal legislation to punish those responsible for grave breaches. The aim of this research is to analyze the penal responsibility and sanctions for violations of International Humanitarian Law. The research adopted the doctrinal method of legal research. It found that the inadequate legislation during armed conflict undermines individual protection, leading to widespread violation of human right. This research concluded that Under IHL, States are legally required to take concrete measures to ensure the effective implementation of humanitarian law, however, the ineffectiveness of sanctions for serious violations of international humanitarian law (IHL) is evident and often stems from the complex nature of armed conflict. Lastly, it is recommended that international cooperation and strengthening of international criminal courts are crucial for ensuring accountability and effective implementation of sanctions for the violation of IHL rules
MITIGATING GENDER DISCRIMINATION THROUGH GENDER MAINSTREAMING OF ARTIFICIAL INTELLIGENCE POLICIES IN NIGERIA
No full textArtificial Intelligence is a simulation of human intelligence that has become very crucial to human operations. It operates with the same perspective as is prevalent or acceptable to humans. Consequently, AI is prone to errors due to the possible presence of inaccurate or incomplete data. With regards to gender issues, AI has been recognized as manifesting gender bias; for instance, when women use AI-powered systems to diagnose illnesses, they often receive inaccurate answers, because AI is unaware of symptoms that may present differently in women. The aim of this work is to interrogate the reasons behind the manifestations of AI bias and to proffer solutions towards curbing the same.
The methodology used in this study is doctrinal, constituting the use and analysis of already existing literature. This work found that AI manifestation of gender bias is a direct result of already existing gender inequality and discrimination in the society and that gender mainstreaming into AI is crucial to mitigating gender inequality and discrimination against women. The work recommends solutions inclusive of a change in the mentality that approves of male domination and gender profiling; positive policies towards gender inclusivity in AI development, aimed at feeding the machine with data possessive of the feminine perspective and improved mechanism for enforcement.
CONSUMER TRUST AND ATTITUDES TOWARD NIVEA TELEVISION ADVERTISEMENTS: THE ROLE OF PERCEIVED CREDIBILITY, APPEAL, AND PURCHASING BEHAVIOR
No full textThis study investigates consumer attitude and trust toward NIVEA’s television advertisement campaigns, focusing on how emotional appeal, message clarity, and perceived authenticity influence brand perception and purchasing behavior. Despite NIVEA’s global brand recognition, uncertainties persist regarding the effectiveness of its TV campaigns in fostering consumer trust and driving purchase intent. The research explores Consumer Attitudes and Trust toward Television Advertisement Campaigns, testing hypotheses through a quantitative approach. Data were collected from 900 respondents via an online survey, examining demographic factors, trust levels, and advertisement perceptions. Statistical methods such as correlation, regression, and descriptive analysis were applied to identify relationships between variables and to predict and explain how independent variables affect the dependent variable. The findings reveal minimal associations between demographic characteristics and consumer responses, with most correlation coefficients near zero and p-values exceeding 0.05 for key variables like age (p = 0.113), gender (p = 0.551), and trust in ads (p = 0.217). An adjusted R-squared value of 0.039 indicates that only 3.9% of the variance in consumer trust can be attributed to perceived ad credibility. The results suggest that demographic targeting alone is insufficient for shaping consumer attitudes toward NIVEA’s TV campaigns. Instead, enhancing ad content through emotional appeal, trust-building narratives, and authentic storytelling is crucial. The study highlights the importance of broader advertising strategies aimed at fostering trust and boosting consumer engagement beyond demographic considerations
EFFECT OF LIQUEFIED PETROLEUM GAS PRICE ON THE LEVEL OF PATRONAGE AMONG HIGHER EDUCATION STUDENTS
No full textThis paper examined the effect of prices of LPG fuel, LPG cylinders, and LPG accessories on the patronage and use of LPG for cooking by students of higher education institutions (HEIs) in Lagos State. The paper is necessary because of the benefits of switching to a clean cooking fuel like LPG by students of HEIs in Nigeria and the important role of price in achieving this. The target population was the students of the Faculty of Science, University of Lagos. The research used a cross-sectional design and convenience sampling technique. A structured questionnaire was used to collect data from a valid sample of 250 respondents from University of Lagos, Akoka. A multiple regression statistical method was used to test the hypotheses. Results from the analysis suggested that prices of LPG fuel and cylinders did not significantly affect the patronage and use of LPG for cooking by the students of HEIs. On the contrary, the findings indicated that prices of LPG accessories significantly affected LPG patronage and use. It was concluded that prices of LPG fuel, LPG cylinders, and LPG accessories affected LPG patronage differently. The research also made recommendations. Finally, the research limitations and suggestions for future studies were provided
Analysing the Causes and Effects of Farmer-Herder Conflict in Benue State, Nigeria
No full textOver the years, Benue State has witnessed prolonged conflict between farmers and herders. This conflict has affected the coexistence of the two groups. It is therefore necessary to understand the trend and its effects in Benue\u27s state. Detailed information on the spatial distribution and trend of the conflict was provided. The period considered for this study was from 2011–2022. The causes and implications of this phenomenon in the Benue state were examined. Conflict data were sourced from the Armed Conflict Location and Events Data (ACLED) 2022 version to generate the frequencies of conflicts in the study area, and field observations using a questionnaire were used to ascertain the authenticity of the location. Farmers and herders were selected from the three senatorial zones that formed the study population. Two hundred and seventy-nine copies of the questionnaire were administered purposely in vulnerable communities. Contamination of water bodies by cattle, destruction of crops by cattle, grazing of fallow land, and indiscriminate bush burning were the leading causes of these conflicts. At the same time, the displacement of farmers and herders, loss of agricultural products in storage, degradation of farm products, and increased poverty were among the implications of the conflict in the study area. This study highlights the importance of assessing the spatiotemporal distribution of farmers’ herders conflicts in Benue state
Determination of the Deflection of the Vertical Using a Gravimetric Approach within the Federal University of Technology Akure, Nigeria
No full textDeflection of the vertical is the angle between the true vertical (the direction of gravity) at a point on the Earth\u27s surface and the normal to the reference ellipsoid (the idealized mathematical model of the Earth\u27s shape). It arises due to the Earth\u27s irregular mass distribution, which causes local variations in the direction of gravity. This research investigates the deflection of the vertical at the Federal University of Technology Akure using a gravimetric approach to determine geoidal undulation. Gravity data from 44 geodetic control stations were observed. The geoidal height and deflection of the vertical were calculated through the discrete wavelet decomposition method in MATLAB, with comparisons to ICGEM data. Geoidal heights at each station were also computed using the gravimetric (Stokes integral) approach, with results compared between methods. The study further evaluated high-resolution global geoid models, including EGM 2008, GECO, SGG-UGM-1, SGG-UGM-2, and XGM 2019e_2156. The result reveals that EGM 2008 has the lowest standard deviation of 0.3197m and SGG-UGM-2 with the lowest root mean square error (RMSE) of 0.4787m. For lower-resolution models (GOCO06S, GOSG01S, IGGT_R1, GGM05G, EIGEN 5C), the standard deviation and RMSE differences were also minimal, with EIGEN5C at 0.3180m and IGGT_R1 at 0.3137m. A z-test indicated significant differences between geoidal heights derived from the gravimetric and wavelet methods, leading to the rejection of the null hypothesis. Therefore, discrete wavelet decomposition should be adopted as an alternative method for computing the deflection of the vertical and geoidal heights when using a gravimetric approach
Application of Convolutional Neural Network (CNN) in Identification and Mapping of Urban Road Network in Parts of Benin City, Nigeria Using Remotely Sensed Imagery
No full textAccurate mapping of urban road networks is critical for sustainable urban planning, efficient transportation management, and disaster response. This study presents an automated approach for urban road network extraction using Convolutional Neural Networks (CNNs) applied to high-resolution unmanned aerial vehicle (UAV) imagery of Benin City, Nigeria. UAV data were captured using the DJI Matrice 100 platform equipped with a Zen muse X5 camera, providing imagery at a spatial resolution of 10–15 cm. Following comprehensive preprocessing steps—comprising noise reduction, calibration, image enhancement, georeferencing, orthorectification, and mosaicking—training datasets were generated through manual labeling and feature extraction using ArcGIS. The U-Net based CNN model was trained using 80% of the labeled data with the remaining 20% reserved for testing. Data augmentation techniques were employed to enhance model generalization and mitigate over fitting. Model evaluation demonstrated robust performance, achieving a validation accuracy of 91.3%, mean Intersection over Union (IoU) of 0.834, precision of 0.89, recall of 0.85, and F1-score of 0.87. The trained model exhibited computational efficiency, processing images at an average of 127 ms per image using 2.84 GB of GPU memory. Beyond road extraction, the model successfully classified additional urban land cover classes, including buildings, bare ground, vegetation, and water bodies, yielding an overall dataset quality rating of 8.8/10. The study highlights the potential of deep learning models in providing scalable, accurate, and efficient solutions for urban infrastructure mapping
Urban Flood Mapping using Sentinel-1 SAR Data and Machine Learning: A Case of Maiduguri, Nigeria
No full textFlooding is one of the most devastating hydrological hazards, resulting in significant human and economic losses, particularly in rapidly urbanizing areas with poor urban planning. Recently, Maiduguri, Nigeria, faces recurrent floods, and traditional flood mapping methods relying on optical remote sensed data are often hindered by cloud cover. This study leverages Sentinel-1 Synthetic Aperture Radar (SAR) data and machine learning to overcome these limitations. The research employs threshold-based classification and change detection techniques to analyze pre-flood (January–August 2024) and post-flood (September–October 2024) SAR imagery. The methodology includes radiometric calibration, speckle filtering, and terrain correction to enhance flood detection accuracy. Flood extents were validated using ground reference points, achieving an overall accuracy of 88.6% and a Kappa coefficient of 0.82, confirming the reliability of SAR-derived flood maps. Findings reveal a 524.6 km² of inundated area, with severity concentrated along River Ngadda and low-lying areas. Zonal analysis highlights significant disparities, with the Maiduguri-Monguru Road experiencing 27.98% flooding, while elevated areas like Bornu Industrial Park (0.017%) remained minimally affected. The study also reveals that critical infrastructure are at risk. The research recommends improved urban drainage system, stricter land-use regulations and early warning systems to mitigate flood vulnerability