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

 

Table Of Contents


Chapter ONE

INTRODUCTION

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

Chapter TWO

LITERATURE REVIEW

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

Chapter THREE

RESEARCH METHODOLOGY

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

Chapter FOUR

DATA PRESENTATION AND ANALYSIS

  • 4.1Data Analysis and Interpretation
  • 4.2Customer Arrival Patterns
  • 4.3Service Time Distribution
  • 4.4Queue Length Analysis
  • 4.5Utilization of Service Channels
  • 4.6Customer Satisfaction Levels
  • 4.7Comparison of Queuing Models
  • 4.8Managerial Implications

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • 5.1Summary of Findings
  • 5.2Conclusion
  • 5.3Recommendations for Practitioners
  • 5.4Recommendations for Future Research
  • 5.5Contribution to Knowledge

Project Abstract

<p> 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. <br></p>

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