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National digital identity management systems have gained traction as a critical tool for inclusion of citizens in the increasingly digitised public services. With the help of the World Bank, countries around the world are committing to building and promoting digital identification systems to improve development outcomes as part of the Identity for development initiative (ID4D). One of those countries is Nigeria, which is building a national ID management database for its over 100 million residents. However, there are privacy, security, human rights, ethics and socio-cultural implications associated with the design and scaling of such a system at a national level. Through a mixed method approach, this paper identifies some of these concerns and categorises which ones Nigerians are most worried about. It provides an empirically sound perspective around centralised national electronic identity (eID) management system, public trust and responsible data governance, and offers recommendations on enhancing privacy, security and trustworthiness of the digital infrastructure for identity management in Nigeria.

Organizational performance depends on two key elements, human capital and entrepreneurial leadership style, a combination that has sparked interest among researchers and practitioners. Based on these facts, this study investigates the impact of human capital and entrepreneurial leadership styles on organizational performance. A cross-sectional survey design was adopted for the study and data was elicited through questionnaire. Research objectives and research questions were set and the targeted population comprised of six hundred fifty-eight (658) workers from Table Water Enterprises in Minna, Niger State while the sample size is one hundred and ninety-two (192). IBM SPSS 24.0 was used to analyze data. Regression, reliability analysis, and descriptive statistics were used. Human capital, entrepreneurial leadership style is assumed to account for 39.1% of the variability in other variables (R2 of 0.391), and the independent factors statistically substantially predict the dependent variable, F 60.710, p