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Application of queuing models to customers management in the banking system.

 

Table Of Contents


Chapter ONE

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms

Chapter TWO

2.1 Overview of Queuing Models
2.2 History of Queuing Theory
2.3 Types of Queuing Models
2.4 Applications of Queuing Models
2.5 Queuing Models in Customer Management
2.6 Benefits of Using Queuing Models
2.7 Challenges of Implementing Queuing Models
2.8 Case Studies on Queuing Models
2.9 Future Trends in Queuing Models
2.10 Summary of Literature Review

Chapter THREE

3.1 Research Methodology Overview
3.2 Research Design
3.3 Data Collection Methods
3.4 Sampling Techniques
3.5 Data Analysis Procedures
3.6 Ethical Considerations
3.7 Validity and Reliability
3.8 Limitations of the Methodology

Chapter FOUR

4.1 Data Analysis and Interpretation
4.2 Presentation of Findings
4.3 Comparison with Existing Literature
4.4 Discussion of Results
4.5 Implications of Findings
4.6 Recommendations for Practice
4.7 Recommendations for Future Research
4.8 Conclusion of Findings

Chapter FIVE

5.1 Summary of Findings
5.2 Conclusions Drawn from the Study
5.3 Contributions to Knowledge
5.4 Practical Implications
5.5 Limitations of the Study
5.6 Recommendations for Further Research
5.7 Conclusion and Final Remarks

Thesis Abstract

Queues are common sight in banks these days especially on Mondays and on Fridays. Hence queuing theory which is the mathematical study of waiting lines or queue is suitable to be applied in the banking sector since it is associated with queue and waiting line where customers who cannot be served immediately have to queue(wait) for service. The aim of this project is to determine the average time customers spend on queue and the actual time of service delivery, thereby examining the impact of time wasting and cost associated with it. The primary data were collected from the UBA branch at Okpara Avenue, Enugu, the data were collected based on the arrival pattern and service pattern of customers. The methodology employed followed the birth and death Markovian process. We further used the chi-square test to test the arrival pattern to determine if it follows a Poisson distribution and also tested the service pattern to determine if it follows an exponential distribution. The results obtained from the chi-square test showed that the arrival pattern follows a Poisson distribution and that the service pattern follows an exponential distribution, hence it can be analyzed using Markovianbirth and death process. The results obtained showed that service rate is 0.1521 and arrival rate is 0.2157, the probability that servers are idle is 0.2786 and the cost incurred from waiting is N938.597. We were now forced to recommend based on the analysis, that the Bank management should increase the number of servers to three so as to help reduce the time customers spend on queue and also reduce cost incurred from waiting. We now concluded that the objective of this project was achieved.

Thesis Overview

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