Artificial Intelligence Enabled Recruitment and Human Intellectual Development in Small and Medium Enterprises in Lagos, Nigeria (Published)
The growing adoption of Artificial Intelligence (AI) in human resource management is transforming recruitment practices, yet empirical evidence on its implications for human intellectual development and firm performance among small and medium enterprises (SMEs) in developing African economies remains limited. This study examined AI-enabled recruitment on hiring efficiency, hiring quality and human intellectual development among SMEs in Lagos, Nigeria, while assessing the mediating role of intellectual capital and the moderating effects of adoption barriers. Anchored in the Resource-Based View, the study adopted a quantitative cross-sectional survey design. The population comprised 121,239 registered SMEs in Lagos State, from which a sample of 439 respondents was determined using Yamane’s formula at a 5% margin of error. Data were collected from SMEs owners and human resource managers using a structured questionnaire and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with 5,000 bootstrap subsamples. The findings revealed that AI-enabled recruitment significantly improved hiring efficiency (β = 0.482, p < 0.001), hiring quality (β = 0.415, p < 0.001), and human intellectual development (β = 0.367, p < 0.001). Intellectual capital partially mediated the relationship between AI-enabled recruitment and SMEs performance, accounting for 38.8% of the total effect. However, infrastructure constraints (β = −0.214, p < 0.001) and cost and skills constraints (β = −0.187, p < 0.001) significantly weakened the positive effects of AI-enabled recruitment. The study concludes that the strategic value of AI in SMEs recruitment extends beyond hiring efficiency to the development of human and organisational intellectual capabilities. It recommends affordable and scalable AI solutions, targeted digital-skills development, improved digital infrastructure, and responsible AI governance to enable SMEs to translate AI adoption into sustainable performance.
Keywords: AI-enabled recruitment, Artificial Intelligence, SMEs performance, human intellectual development; intellectual capital
Impact of Entrepreneurial Traits on the Performance of Small and Medium Enterprises (SMEs) In North Central, Nigeria (Published)
This study examined the impact of entrepreneurial traits on the performance of Small; and Medium Enterprises (SMEs) in North Central Nigeria. The specific entrepreneurial traits considered in the study include entrepreneurial need for achievement, entrepreneurial passion, and self-efficacy. A sample size of 400 SME owners and managers was selected for the study. Data collected through a structured questionnaire were analyzed using Structural Equation Modeling (SEM) to test the hypothesized relationships among the variables. The findings of the study revealed that entrepreneurial need for achievement has a positive and significant effect on SME performance. Similarly, entrepreneurial passion was found to have a positive and significant influence on SME performance, indicating that emotional attachment and enthusiasm for business activities contribute to improved outcomes. The results further showed that self-efficacy has the strongest and most significant effect on SME performance among the variables examined, suggesting that entrepreneurs’ confidence in their abilities plays a critical role in determining business success. Based on these findings, the study concludes that entrepreneurial traits significantly influence the performance of SMEs in North Central Nigeria, with self-efficacy emerging as the most important predictor. The study recommends that entrepreneurship development programs should focus on strengthening entrepreneurs’ psychological attributes such as achievement motivation, passion, and self-confidence through training, mentoring, and capacity-building initiatives. These efforts are essential for improving SME performance and enhancing sustainable economic development in the region.
Keywords: SMEs performance, entrepreneurial traits, structural equation modeling (SEM)