This study determined whether the present capacity level in the banking industry strike a balance between waiting and service time using Barclays Bank, Tafo Branch and Agricultural Development Bank, Kumasi Adum Branch as a case of interest. Primary data on Six Hundred and Thirteen (613) customers arriving at the case of study throughout the selected hours and days were collected, taken into consideration; the arrival, processing and departure times of each customer.
The study then showed how the data collected at the respective dates possesses the Markovian properties, that is, Poisson and Exponential Distributions, hence the use of two “M’s” in the M/M/s queuing model. It determined the probabilistic analysis that the teller(s) is idle and also determined the probability of certain number of arrivals occurring at a given time.
Inhaltsverzeichnis (Table of Contents)
- Chapter One: Introduction
- 1.0 Background of the Study
- 1.1 Statement of the Problem
- 1.2 Objectives of the Study
- 1.3 Methodology
- 1.4 Justification
- 1.5 Limitation
- 1.6 Organization of the Thesis
- Chapter Two: Literature Review
- 2.0 Introduction
- 2.1 Queuing Researches In The Banking Industry
- 2.2 Historical Perspective of Queuing Theory
- Chapter Three: Methodology of the Study
- 3.0 Introduction
- 3.1 Primary Data Collection
- 3.2 Description of Queuing System
- 3.2.1 Queuing Systems in the Case of Study
- 3.3 Fundamental Queuing Relations
- 3.4 Customer Arrival and Inter Arrival Distribution
- 3.4.1 Probability Distribution
- 3.4.2 Exponential Distribution
- 3.4.3 Poisson Distribution
- 3.5 Teller Utilization Factor (p)
- 3.6 Little's Law
- 3.7 Queuing Model Description
- 3.7.1 M/M/1 Model
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This study aims to analyze the queuing system in the banking industry, specifically at Barclays Bank, Tafo Branch, and Agricultural Development Bank, Kumasi Adum Branch. The research investigates whether the current capacity levels in these banks strike a balance between customer waiting time and service time. The study utilizes queuing theory to model and analyze the collected data.
- Analysis of queuing systems in the banking industry.
- Evaluation of current capacity levels in relation to waiting and service times.
- Application of queuing models (M/M/s) to analyze customer arrival and service patterns.
- Determination of the impact of the number of tellers on queue length and waiting time.
- Recommendations for optimizing teller staffing to improve customer satisfaction and minimize costs.
Zusammenfassung der Kapitel (Chapter Summaries)
Chapter One: Introduction: This chapter introduces the study, highlighting the problem of long customer queues in the banking industry. It states the objectives of the research, which are to determine whether existing bank capacity balances waiting and service times, using two Ghanaian bank branches as case studies. The methodology, justification, limitations, and thesis organization are also outlined. The chapter sets the stage by emphasizing the negative impact of excessive wait times on both customer satisfaction and bank efficiency.
Chapter Two: Literature Review: This chapter reviews existing literature on queuing systems within the banking industry and provides a historical perspective on queuing theory itself. It likely examines previous studies that have applied queuing models to analyze similar scenarios and explores different queuing models and methodologies. This chapter lays the theoretical groundwork for the study, contextualizing the chosen approach within the broader field of operations research and queuing theory.
Chapter Three: Methodology of the Study: This chapter details the research methodology employed. It describes the primary data collection process, which involved observing and recording the arrival, processing, and departure times of 613 customers at the selected bank branches over specific days and hours. The chapter explains how the data is analyzed to determine whether it fits Markovian properties (Poisson and Exponential Distributions), justifying the use of the M/M/s queuing model. Key concepts such as teller utilization factor and Little's Law are explained, and the specific queuing model used (M/M/s) is described in detail, laying out the framework for the quantitative analysis of the data.
Schlüsselwörter (Keywords)
Queuing theory, M/M/s queuing model, banking industry, customer service, waiting time, service time, capacity utilization, teller staffing, customer satisfaction, Poisson distribution, Exponential distribution, Markovian properties, performance measures, peak hours, off-peak hours.
Frequently Asked Questions: Analysis of Queuing Systems in the Banking Industry
What is the main topic of this study?
This study analyzes queuing systems in the banking industry, focusing on customer waiting and service times. It uses queuing theory, specifically the M/M/s model, to examine the relationship between bank capacity and customer experience at two Ghanaian bank branches (Barclays Bank, Tafo Branch, and Agricultural Development Bank, Kumasi Adum Branch).
What are the key objectives of this research?
The research aims to determine if current bank capacity balances customer waiting and service times. It seeks to apply queuing models to analyze customer arrival and service patterns, understand the impact of the number of tellers on queue length and waiting time, and provide recommendations for optimizing teller staffing to improve customer satisfaction and minimize costs.
What methodology is used in this study?
The study employs primary data collection through observation of customer arrival, processing, and departure times at the selected bank branches (613 customers observed). Data analysis determines if the data fits Markovian properties (Poisson and Exponential Distributions) to justify the use of the M/M/s queuing model. Key concepts such as teller utilization factor and Little's Law are applied.
What are the key themes explored in this research?
Key themes include the analysis of queuing systems in the banking industry, evaluation of current capacity levels in relation to waiting and service times, application of queuing models (M/M/s), determination of the impact of the number of tellers on queue length and waiting time, and recommendations for optimizing teller staffing.
What are the chapter summaries?
Chapter One (Introduction): Introduces the study, its objectives, methodology, justification, limitations, and organization. It highlights the problem of long queues in banking and sets the context. Chapter Two (Literature Review): Reviews existing literature on queuing systems in banking and provides a historical perspective on queuing theory. Chapter Three (Methodology): Details the data collection process (observing 613 customers), data analysis, and the application of the M/M/s queuing model. It explains concepts like teller utilization factor and Little's Law.
What are the keywords associated with this research?
Queuing theory, M/M/s queuing model, banking industry, customer service, waiting time, service time, capacity utilization, teller staffing, customer satisfaction, Poisson distribution, Exponential distribution, Markovian properties, performance measures, peak hours, off-peak hours.
What specific queuing model is used?
The study utilizes the M/M/s queuing model to analyze the data.
What data was collected?
Primary data was collected by observing and recording the arrival, processing, and departure times of 613 customers at the selected bank branches.
Where was the research conducted?
The research was conducted at Barclays Bank, Tafo Branch, and Agricultural Development Bank, Kumasi Adum Branch in Ghana.
- Quote paper
- Emmanuel Oppong-Gyebi (Author), 2010, Modeling Queuing System in the Banking Industry, Munich, GRIN Verlag, https://www.grin.com/document/1349674
