Impact of e-management on human resource development in the central bank of nigeria, 1999-2009
Table Of Contents
Project Abstract
The Central Bank of Nigeria in its strategy towards improving the human resource management and the general performance of the banks adopted electronic management which is also referred to as Information Communication Technology (ICT). Prior to the introduction of e-management, the bank management and administrative work were done by staff through manual method. Since the introduction of e-management in the Central Bank of Nigeria, no study of this magnitude has been carried out to ascertain its impact of the bank. This study therefore intends to fill this lacuna in knowledge. The broad objective of this study is to explore the impact of e-management on human resource development in the Central Bank of Nigeria. Specifically, this study intends to achieve the following objectives namely to (i) ascertain the extent to which e-management has contributed to human resource development in the Central Bank of Nigeria. (ii) determine the extent emanagement has enhanced staff productivity in the Central Bank of Nigeria and (iii) ascertain whether or not the introduction of e-management increased unemployment in the Central Bank of Nigeria. The field force theory ,propounded by Lewin was used in the analysis of this study. Field force is a theory of change. It believes that the organization is propelled by competition economic, political etc. to change their actions and operations. The study adopted a descriptive cross sectional survey research design and self reporting techniques for data analysis. This study revealed that the use of e-management system in the central bank of Nigeria has improved staff development. Secondly the study also revealed that the implementation of e-management in the central bank of Nigeria has enhanced staff productivity. Thirdly, the study discovered that the introduction of emanagement system in the central bank of Nigeria did not increase unemployment in the Bank.
Project Overview
Title Page – – – – – – – – – – – – i Certification – – – – – – – – – – – -ii Dedication – – – – – – – – – – – -iii Acknowledgement – – – – – – – – – -iv Abstract – – – – – – – – – – – -vi Table of Contents – – – – – – – – – -vii List of Diagrams; Graphs and Tables – — – – – – -viii CHAPTER ONE: INTRODUCTION – – – – – – -1 1.1 Background of the Study – – – – – – – -1 1.2 Statement of the Problem – – – – – – – -4 1.3 Objectives of the Study – – – – – – – -6 1.4 Significance of the Study – – – – – – – -7 1.5 Literature Review – – – – – – – – -7 1.6 Theoretical Framework — – – – – — – -37 1.7 Hypotheses – – – – – – – – – -41 1.8 Method of Data Collection – — – – – – – -41 1.9 Logical Data Framework – – – – – – – -46 CHAPTER TWO: CENTRAL BANK OF NIGERIA AND THE USE OF E- MANAGEMENT SYSTEM – – – – – – – – -49 2.1 Introduction – – – — – — – – – -49 2.2: Brief history of the Central Bank of Nigeria Administrative System – -50 2.3: Components of E-management – – – – – – -52 2.4: The Use of Internet/Intranet Applications – – – – -55 2.5: Central Bank of Nigeria E-management Web Based page – – – -57 2.5.1 Application of the CBN E-management Web Based Page – — – -58 CHAPTER THREE:E-MANAGEMENT AND HUMAN RESOURCE DEVELOPMENT- — – – – – – – – – -60 3:1: Introduction———————————————————60 3.2: Computer Literacy Level and use of Internet/Intranet Technology in the Central Bank of Nigeria – – – – – – -64 3.3: E-management and Staff Development Strategies – – – -75 CHAPTER FOUR: THE IMPACT OF E-MANAGEMENT ON STAFF PRODUCTIVITY – – – – –……87 4.1: Introduction……………………………………………………………… 87 4.2: E-management and Effective Banking Operations – – – -88 4.3: E-management Services Delivery – – – – – – -99 CHAPTER FIVE: E-MANAGEMENT AND EMPLOYEMENT OPPORTUNITIES – – – – – – – – 102 5.1: Introduction- – – – – – – – – – —– – – ——– – – — – – – – – – – – – – – – – – – – – 102 5.2: Effect of E-management on Staff Strength – — – – -104 CHAPTER SIX: SUMMARY AND CONCLUSION – – – – -122 6:1 Summary of Findings – – – – – – – -122 6:2 Conclusions- – – – – – – – – -123 6.3 Recommendations – – – – – – -125 BIBLIOGRAPY – – – – – – – – – – -128 APPENDIX – – – – – – – – – – – -135
Blazingprojects Mobile App
📚 Over 50,000 Project Materials
📱 100% Offline: No internet needed
📝 Over 98 Departments
🔍 Software coding and Machine construction
🎓 Postgraduate/Undergraduate Research works
📥 Instant Whatsapp/Email Delivery
Related Research
Predicting Disease Outbreaks Using Machine Learning and Data Analysis...
The project topic, "Predicting Disease Outbreaks Using Machine Learning and Data Analysis," focuses on utilizing advanced computational techniques to ...
Implementation of a Real-Time Facial Recognition System using Deep Learning Techniqu...
The project on "Implementation of a Real-Time Facial Recognition System using Deep Learning Techniques" aims to develop a sophisticated system that ca...
Applying Machine Learning for Network Intrusion Detection...
The project topic "Applying Machine Learning for Network Intrusion Detection" focuses on utilizing machine learning algorithms to enhance the detectio...
Analyzing and Improving Machine Learning Model Performance Using Explainable AI Tech...
The project topic "Analyzing and Improving Machine Learning Model Performance Using Explainable AI Techniques" focuses on enhancing the effectiveness ...
Applying Machine Learning Algorithms for Predicting Stock Market Trends...
The project topic "Applying Machine Learning Algorithms for Predicting Stock Market Trends" revolves around the application of cutting-edge machine le...
Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems...
The project topic, "Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems," focuses on the integration of machine learn...
Anomaly Detection in Internet of Things (IoT) Networks using Machine Learning Algori...
Anomaly detection in Internet of Things (IoT) networks using machine learning algorithms is a critical research area that aims to enhance the security and effic...
Anomaly Detection in Network Traffic Using Machine Learning Algorithms...
Anomaly detection in network traffic using machine learning algorithms is a crucial aspect of cybersecurity that aims to identify unusual patterns or behaviors ...
Predictive maintenance using machine learning algorithms...
Predictive maintenance is a proactive maintenance strategy that aims to predict equipment failures before they occur, thereby reducing downtime and maintenance ...
