Article Per Year (5 Year)
p-Index From 2020 - 2025
0.702
P-Index
This Author published in this journals
All Journal Annals of Human Resource Management Research Journal of Governance and Accountability Studies
Nwosu, Chibuzo Charles
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Motivation through indirect compensation: Evaluating employee performance in Enugu State Civil Service Commission Udodiugwu, Michael Ikenna; Nwosu, Chibuzo Charles; Obiakor, Ugochukwu Jude; Nwumeh, Uchenna Juliana
Annals of Human Resource Management Research Vol. 4 No. 2 (2024): September
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/ahrmr.v4i2.2320

Abstract

Purpose: This study evaluates the impact of indirect compensation on employee job performance by the Enugu State Civil Service Commission. Research Methodology: This study employed a cross-sectional survey research design with a population of 280 participants, comprising staff from the Administration, Planning and Budgeting, and Research & Statistics Units, spanning grade levels 2-16 within the Enugu State Civil Service Commission. Data were collected using a questionnaire as the primary tool and rigorously analyzed using the Pearson correlation coefficient in the Statistical Package for Social Sciences (SPSS) version 23. Results: The findings revealed a significant positive impact of indirect compensation metrics on employee performance of the Enugu State Civil Service Commission. Limitations: The study specifically targeted personnel within grade levels 2-16 of the Enugu State Civil Service Commission. Contribution: This research significantly advances our understanding of indirect compensation and its impact on employee performance by pioneering new concepts, refining existing theories, and conducting comprehensive empirical studies. Funding: This research did not receive any funding from any Agency or Organization.
Artificial intelligence in public service and governance in Nigeria Nwosu, Chibuzo Charles; Obalum, Dike Chijioke; Ananti, Mathias Ozoemena
Journal of Governance and Accountability Studies Vol. 4 No. 2 (2024): July
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jgas.v4i2.2425

Abstract

Purpose: This study explores the current state of artificial intelligence implementation in Nigeria’s public service and the potential benefits, challenges, and strategic steps needed to harness AI for improved governance and service delivery. Methods: The research design was qualitative. The data were collected using secondary data collection, in which a thorough literature review of academic articles, books, and reports related to AI was consulted. This study applied a thematic research approach to clarify the underlying issues, beliefs, and experiences related to artificial intelligence in governance and public services. The study was also anchored to content analysis. Results: The findings revealed that AI application in Nigeria’s public service is still in its early stages, with promising developments in areas such as e-governance, healthcare, banking sector, real estate business, and law enforcement/security outfits. There is a need for the government in Nigeria to invest significantly in infrastructural advancement and human capital development, which in turn will close the skill gaps, infrastructural deficits, and lapses that crop up from the unawareness of Artificial Intelligence in the technological advancement of Nigeria. Limitations: This study examined the current state of AI in Nigeria's public services and governance by identifying the key barriers that affect the adoption and implementation of AI. The study made progressive recommendations that integrated the application of artificial intelligence in public services and governance in Nigeria. Contributions: This study provides a comprehensive understanding of how AI can be adopted in Nigeria’s unique environment. Findings: This study did not receive any funding from any agency or organization.
Motivation through indirect compensation: Evaluating employee performance in Enugu State Civil Service Commission Udodiugwu, Michael Ikenna; Nwosu, Chibuzo Charles; Obiakor, Ugochukwu Jude; Nwumeh, Uchenna Juliana
Annals of Human Resource Management Research Vol. 4 No. 2 (2024): September
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/ahrmr.v4i2.2320

Abstract

Purpose: This study evaluates the impact of indirect compensation on employee job performance by the Enugu State Civil Service Commission. Research Methodology: This study employed a cross-sectional survey research design with a population of 280 participants, comprising staff from the Administration, Planning and Budgeting, and Research & Statistics Units, spanning grade levels 2-16 within the Enugu State Civil Service Commission. Data were collected using a questionnaire as the primary tool and rigorously analyzed using the Pearson correlation coefficient in the Statistical Package for Social Sciences (SPSS) version 23. Results: The findings revealed a significant positive impact of indirect compensation metrics on employee performance of the Enugu State Civil Service Commission. Limitations: The study specifically targeted personnel within grade levels 2-16 of the Enugu State Civil Service Commission. Contribution: This research significantly advances our understanding of indirect compensation and its impact on employee performance by pioneering new concepts, refining existing theories, and conducting comprehensive empirical studies. Funding: This research did not receive any funding from any Agency or Organization.
Artificial intelligence in public service and governance in Nigeria Nwosu, Chibuzo Charles; Obalum, Dike Chijioke; Ananti, Mathias Ozoemena
Journal of Governance and Accountability Studies Vol. 4 No. 2 (2024): July
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jgas.v4i2.2425

Abstract

Purpose: This study explores the current state of artificial intelligence implementation in Nigeria’s public service and the potential benefits, challenges, and strategic steps needed to harness AI for improved governance and service delivery. Methods: The research design was qualitative. The data were collected using secondary data collection, in which a thorough literature review of academic articles, books, and reports related to AI was consulted. This study applied a thematic research approach to clarify the underlying issues, beliefs, and experiences related to artificial intelligence in governance and public services. The study was also anchored to content analysis. Results: The findings revealed that AI application in Nigeria’s public service is still in its early stages, with promising developments in areas such as e-governance, healthcare, banking sector, real estate business, and law enforcement/security outfits. There is a need for the government in Nigeria to invest significantly in infrastructural advancement and human capital development, which in turn will close the skill gaps, infrastructural deficits, and lapses that crop up from the unawareness of Artificial Intelligence in the technological advancement of Nigeria. Limitations: This study examined the current state of AI in Nigeria's public services and governance by identifying the key barriers that affect the adoption and implementation of AI. The study made progressive recommendations that integrated the application of artificial intelligence in public services and governance in Nigeria. Contributions: This study provides a comprehensive understanding of how AI can be adopted in Nigeria’s unique environment. Findings: This study did not receive any funding from any agency or organization.
Co-Authors Ananti, Mathias Ozoemena Nwumeh, Uchenna Juliana Obalum, Dike Chijioke Obiakor, Ugochukwu Jude Udodiugwu, Michael Ikenna