Nnamdi Azikiwe University Journals
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INFRASTRUCTURE CHALLENGES AND ARTIFICIAL INTELLIGENCE INTEGRATION AMONG SMALL AND MEDIUM ENTERPRISES IN ANAMBRA STATE, NIGERIA
No full textThe integration of Artificial Intelligence (AI) into Small and Medium Enterprises (SMEs) holds significant potential for enhancing productivity, innovation, and competitiveness. Hence, this study explored Infrastructure Challenges and Artificial Integration among small and medium enterprises in Anambra state. The objective was to analyse the specific infrastructural Challenges that hinder AI integration in SMEs and to evaluate how these infrastructural limitations affect the adoption and effective use of AI technologies in SMEs within Anambra State. The study applied a qualitative research approach using thematic analysis. A descriptive research design was used to gain an in-depth understanding of the subject matter. Convenient sampling techniques were employed in selecting 10participants for the interviews. All interviews were transcribed verbatim and uploaded into MAXQDA Analytics Pro 2020 (qualitative data analysis software).The coding scheme was systematically applied to all transcripts through multiple close data readings. Both semantic/explicit content and latent content requiring interpretative analysis were captured by the codes. Findings revealed a complex interplay between existing challenges and the transformative potential of artificial intelligence for businesses. It therefore recommended the need for SMEs in Anambra State to embrace smart technology as a catalyst for innovation, competitiveness, and long-term succes
AI-DRIVEN CUSTOMER RELATIONSHIP MANAGEMENT PRACTICES AND SUSTAINABLE GROWTH OF NIGERIAN SMEs
No full textThis study explored the impact of AI-driven customer relationship management (CRM) practices on the sustainable growth of small and medium-sized enterprises (SMEs) in Nigeria. The research focused on the use of AI in customer data management, interaction automation, customer segmentation, predictive analytics, engagement strategies, and sales optimisation. A field survey conducted in 2024 collected data from 450 SMEs across Nigeria, using a random sampling technique. Data were gathered through structured questionnaires and analysed using descriptive and inferential statistics. The results demonstrated that AI-driven CRM practices, particularly in customer data management, interaction automation, customer segmentation, predictive analytics, and sales optimisation, significantly enhance the sustainable growth of Nigerian SMEs. Engagement strategies, while important, showed a weaker correlation. The study recommends that SMEs in Nigeria integrate AI-driven CRM tools to improve operational efficiency, customer satisfaction, and long-term growth. Additionally, investment in AI technology and staff training on its effective utilisation is essential for aligning CRM practices with sustainable growth objectives
The Role of Community-Based Agricultural Extension Approaches in Promoting Sustainable Livelihoods and Environmental Stewardship in Southern Taraba, Nigeria
No full textThis study examined the role of community-based agricultural extension approaches in promoting sustainable livelihoods and environmental stewardship in Southern Taraba, Nigeria. A multistage sampling procedure was employed to select 300 respondents from 15 villages across Donga, Wukari, and Takum Local Government Areas. Data were collected through structured questionnaires and focus group discussions and analyzed using descriptive statistics and Logit regression. Results revealed varying levels of awareness and adoption of extension strategies, with Farmer Groups/Associations (90%) and Peer Learning and Farmer-to-Farmer Extension (80%) demonstrating the highest adoption rates, while Participatory Technology Development and Mobile Advisory Services recorded the lowest (30%). Major factors influencing community participation included social networks and leadership (90%), access to information (80%), government and institutional support (80%), and perceived benefits (75%). Logit regression analysis indicated that access to information (β = 1.25, p < 0.01), education level (β = 0.95, p < 0.01), social networks (β = 1.10, p < 0.01), perceived benefits (β = 1.45, p < 0.01), institutional support (β = 0.80, p < 0.01), and environmental awareness (β = 1.00, p < 0.01) were significant predictors of the adoption of sustainable agricultural practices. The model exhibited a strong explanatory power (Pseudo R² = 0.78), confirming that (78%) of the variation in adoption behavior was accounted for by these variables. The study concludes that community-based agricultural extension approaches enhance the adoption of sustainable agricultural practices, strengthen local institutions, and foster environmental stewardship. It recommends strengthening the capacity of extension workers through participatory training, expanding community-based outreach via mobile and local agents, and instituting participatory monitoring mechanisms to ensure context-specific, adaptive, and sustainable interventions
Determinants of Soil Additive Application by Farmers in Delta State: An Economic and Extension Perspective
No full textDespite numerous efforts by the Nigerian government to revitalize the production of groundnut through research, crop improvement practices and vast resources of land, there seems to be inadequate supply of groundnuts to meet both the local and international market demand. The study examined the allocative efficiency of groundnut-based cropping systems in Taraba State, Nigeria. Primary data were collected from 354 groundnut-based farmers using purposive and random sampling techniques using questionnaires which were administered to groundnut producers in the study area. The data collected were analysed using stochastic cost function. The Maximum Likelihood Estimates (MLE) of the stochastic cost function for groundnut-based cropping systems, namely; sole groundnut, groundnut/maize, groundnut/cowpea, groundnut/sorghum/cowpea,groundnut/sorghum, groundnut/millet and groundnut/cassava show mean allocative efficiencies of 77%, 89%, 83%, 91%, 92%, 91% and 94% respectively. The elasticity of output with respect to cost of labour, cost of groundnut seed, cost of fertilizer, cost of land, cost of transportation and cost of agro-chemicals were positive and statistically significant at both 1% and 5% levels in most of the enterprises. The estimated coefficient of the cost inefficiency model revealed that membership of association, age, household size, educational level, extension visit and farming experience were the dominant sources of allocative inefficiency among the groundnut-based farmers in most of the enterprises. The study recommends that farmers should form co-operative groups in order to address high cost of labour, inadequate access to credit facilities and high cost of agro-chemical. This will help to mobilize savings and improve farmers’ efficiencies
The Global Cultivation of Climate-Resilient Crops: Addressing Contemporary Agricultural Challenges in Greenfield Development
No full textThis study examines the global cultivation of climate-resilient crops as a strategic response to contemporary agricultural challenges in Greenfield development contexts. Using a mixed-methods approach, the research analyzed data from 156 Greenfield agricultural projects across 42 countries over a 10-year period (2014-2024). Results indicate that Greenfield sites utilizing climate-resilient crops achieved 34.7% higher yields compared to conventional varieties (p<0.001), with drought-tolerant maize showing the highest improvement at 41.2%. Economic analysis revealed that climate-resilient crops generated 28.5% higher net income per hectare, with benefit-cost ratios ranging from 2.31 to 3.84. Adoption rates varied significantly by region, with Sub-Saharan Africa leading at 67.3%, followed by South Asia at 52.8%. Policy support emerged as the strongest predictor of adoption success (β=0.742, p<0.001), while technical assistance and farmer training showed moderate positive correlations (r=0.634, p<0.05). The study confirms that climate-resilient crops significantly enhance agricultural productivity and economic sustainability in Greenfield developments, with policy frameworks and institutional support being critical success factors
Macroeconomic Analysis of Climate Change Impacts on Yam productivity in Nigeria
No full textAn analysis of the effects of climate change (CC) on yam productivity was carried out. The years\u27 analysis covered from 1991 to 2022. The work assessed the influence of variables-rainfall, temperature, carbon dioxide emissions, sunshine duration, and relative humidity influenced yam productivity. Secondary data was analysed by using econometric models such as Autoregressive Distributed Lag (ARDL) and the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests. The findings showed the R2 value of 0.993, accompanied by an adjusted R2 of 0.96, indicate that the explanatory variables influence and sum up to account for 99.3% of the variation in Yam productivity in the period under study. This high R2 and adjusted R2 demonstrated that the model expressed the dynamics of Yam productivity. The lag of average relative humidity (LN (ARELH (-1))) shows a negative and significant effect on yam productivity with a coefficient of -0.487757 (p = 0.0343). of average annual(AN) rainfall (LN(ARF (-1))), average annual temperature (LN(ATEMP (-1))), average annual Co2 emissions (LN(ACDE (-1))), and AN relative humidity (LN(ARELH(-1))) exhibit significant impacts on yam productivity. The second lag of the inflation rate (LN(INFR(-2))) is significant and positive. The coefficient is 0.084980 (p = 0.0054), suggesting that positive inflation rates in the past positively influence yam productivity
Impact of Taro Leaf Blight on Rural Livelihoods in Anambra State, Nigeria: A Gendered Perspective
No full textTaro Leaf Blight (TLB), caused by Phytophthora colocasiae, poses a major threat to cocoyam production and rural livelihoods in Nigeria. This study examined farmers’ awareness, perceptions, and gendered adaptation strategies to TLB in Anambra State. Using multistage purposive sampling, 64 cocoyam farmers (52% female, 48% male) were selected from two Local Government Areas. Data were collected through semi-structured questionnaires and analyzed using descriptive statistics and mean scores. Results showed high awareness of TLB among farmers, who identified symptoms such as brown patches, leaf drying, and plant death. Female and youth farmers perceived the disease as more severe than males, reflecting their closer involvement in crop care. All respondents reported negative effects of TLB on productivity, income, and living standards. Common indigenous management practices included intercropping, early planting, and the use of wood ash and crop rotation. However, limited extension contact and poor access to resistant varieties hinder effective control. The study recommends strengthening gender-responsive extension services, promoting resistant varieties, and enhancing farmer education on disease transmission and climate-smart practices to build resilient and inclusive cocoyam systems
ECONOMIC GLOBALIZATION AND MANUFACTURING OUTPUT IN NIGERIA
No full textThe United Nations, in 2015 had emphasized through its Sustainable Development Goals (SDG), that adequate manufacturing output will reduce poverty, hunger and promote economic growth. However, Nigeria’s manufacturing output has failed to meet this target, with evidences of hunger, poverty and poor economic growth. This study examined the impact of economic globalization and the extent to which it contributed to variance on Nigeria’s manufacturing output. This study utilized manufacturing sector output and economic globalization index data from KOF globalization index. The auto regressive distributed lag was used for estimation of variables in this study. The findings of the study revealed that economic globalization index had long run relationship with manufacturing output. Economic globalization had positive and insignificant coefficient value in the short-run but turned negative and insignificant in the longrun. In addition to these results, the variance decomposition test revealed that globalization accounted for less than 20% variations in manufacturing output for the first five periods. The study concludes that economic globalization was not strong enough to drive manufacturing output in Nigeria and recommends that Nigeria should introduce import substitution strategy to enable her improve the contribution of globalization to her manufacturing output
MACROECONOMIC DETERMINANTS OF POVERTY IN NIGERIA: APPLICATION OF NONLINEAR ARDL
No full textPoverty in Nigeria remains a persistent issue despite the nation\u27s abundant natural resources and growing economy. This study explores the macroeconomic determinants of poverty in Nigeria for the period 1970 to 2023, focusing on variables such as inflation, foreign direct investment (FDI), trade openness, exchange rates, and economic growth. Using a Nonlinear Autoregressive Distributed Lag (NARDL) model, the study investigates the asymmetric short- and long-term effects of these factors on poverty, recognizing that poverty dynamics often do not follow linear patterns. The findings reveal that FDI, trade openness, and economic growth significantly reduce poverty in the short run, while sustained economic growth (measured by real GDP per capita) emerges as a key long-term factor in poverty alleviation. Conversely, exchange rate depreciation and inflation have mixed effects, sometimes exacerbating poverty, especially in the long run. The study highlights the need for stable exchange rates, controlled inflation, and policies that attract quality, long-term FDI. Recommendations emphasize sustaining economic growth, fostering an investment-friendly environment, and maintaining trade openness. These findings underscore the importance of nuanced, stability-focused policies to address the complex and multidimensional nature of poverty in Nigeria