ANALYSIS OF SINGLE AND MULTI-TELLER MODELS OR USING SIMULATION FOR REDUCING WAITING TIME: A CASE STUDY OF FIRST BANK AND ECO BANK, NIG. LTD

ANALYSIS OF SINGLE AND MULTI-TELLER MODELS OR USING SIMULATION FOR REDUCING WAITING TIME: A CASE STUDY OF FIRST BANK AND ECO BANK, NIG. LTD

  • The Complete Research Material is averagely 82 pages long and it is in Ms Word Format, it has 1-5 Chapters.
  • Major Attributes are Abstract, All Chapters, Figures, Appendix, References.
  • Study Level: MTech, MSc or PhD.
  • Full Access Fee: ₦8,000

Get the complete project » Instant Download Active

CHAPTER ONE

GENERAL INTRODUCTION

This chapter discusses the introductory part of the thesis. It includes the background of the study, research motivations and goals, the research questions for which the thesis should provide answers to, the methodology that is used to answer those questions and finally the contribution to knowledge.

1.1 Background of the Study

In every bank, there is banker-customer relationship. The corporate objective of any bank which is maximization of shareholders‟wealth can only be achieved if customers are retained and satisfied. This is according to the Kotler P (1999) perception that the key to successful marketing of financial services is identification and packaging of customers‟ need to their satisfaction.

The competition in Nigerian banking sector of which First Bank Samaru is part of, is getting more intense, partly due to regulatory imperatives of universal banking and also due to customers‟ awareness of their rights. Bank customers have become increasingly demanding, because they require high quality, low priced and immediate service delivery. They want additional improvement of value from their chosen banks (Kasum A. S et al, 2006). Service delivery in banks is personal, customers are either served immediately or join a queue (waiting line) if the system is busy. A queue occurs where facilities are limited and cannot satisfy demand made against them at a particular period. However, most customers are not comfortable with waiting or queuing, (Kasum A. S et al, 2006). The danger of keeping customers in a queue is that customers waiting time may amount to or could become a cost to them. Customers are prepared not to spend more cost of waiting or queuing. The time wasted on the queue would have been judiciously utilized elsewhere (the opportunity cost of time spent in queuing), (Elegalam, 1978).

Waiting is one of the important issues to the service industry because of its impact towards the operations capabilities and customer satisfaction of the organization. The determination of how long a customer should wait for a product or service has long been a major concern for service management specialists who bear the trade-off between minimizing operation costs incurred in optimizing the configuration of a queue system, as well as, minimizing the cost of waiting of the customers.

ATM is the abbreviation ofAutomated Teller Machine which acts as a teller in a bank who takes and gives money over the counter.ATMs are placed not only near or inside the premises of banks, but also in locations such as shopping centers/malls, airports, grocery stores, petrol/gas stations, restaurants, or any place where large numbers of people may gather. ATM services includes function such as cash withdrawal, balance enquiry, bill payment, cash and cheque deposit, saving and credit account on a 24-hour basis. Thus with the introduction of ATMs, some limitation of time and geographic location has been resolved, (Lukwiya, 2011).

14


As the current economies progressively changes into a service dominated one, it is essential to thoroughly understand the know-how to effectively deal with waiting lines so as to improve customer satisfaction of service, (Mandia, 2012). In view of this, there is need to find out inadequacies in queue management, explore the psychological and social aspect of queues, and finally formulate a general framework based on the consumer behavior in queues, which would serve to aid the design of queuing systems.

1.2 Research Motivations and Goals

The major goal or purpose of the dissertation is to analyze single and multi-teller models of a Bank so that management of the Bank or similar service system can take decision on how to improve on waiting in the two case study Banks and achieve increased efficiency.

One of the motivating factors is that, McKinsey consultants write in “Is Simulation Better than Experience?”, “Simulations can be better than experience because they compress time and remove extraneous details. Unlike life, simulations are optimized for learning.” Indeed, the true beauty of simulation is that it provides an immersive learning experience, where skills, process, and knowledge can all be enhanced in a way reality cannot. And the ability to explore, experiment, and repeatedly apply this knowledge to unlimited model situations is what makes simulation the most versatile form of learning available. And now, thanks to the development of new technology, computer simulation is making this type of learning more effective than ever, (Access, 2012).

Customers are prepared not to spend more cost of waiting / queuing. The time wasted on the queue would have been judiciously utilized elsewhere (the opportunity cost of time spent in queuing), (Elegalam, 1978).

As one of the customer of First bank in Samaru who used to join long queue in the bank or in the ATM premises, which lasted for one hour or more especially during the last two weeks of the month, it is always boring and precious time is wasted and this always give rise to most of customers complaining in the queue. The same thing happens in the first Bank in Bida and all the Nigerian queue areas such as petrol stations, and hospitals. Therefore, there is need for reducing the waiting time.

"Statistic was produced during the 1980s by a consulting firm, Priority Management Pittsburgh, which says that averageAmericans spend five years of their lives waiting in lines and six months sitting at traffic lights (compared, incidentally, with four years doing housework). Even if the time spent in queues has been more heavily curtailed in recent years by the prevalence of online retail transactions, the statistic retains a certain force" (Kevin, 2012).

Similarly, Nigerians have not developed like theAmericans but they are already spending a lot of time in queues (such as in banks, filling stations, hospitals, traffic, etc.), and this will worsen when Nigeria become developed, therefore, it is necessary to pay attention to queue management in order to reduce wait time and achieve efficiency.

15


1.3 Problem Statement

Most customers are not comfortable with waiting or queuing (Kasum A. S et al, 2006). The danger of keeping customers in a queue is that customers waiting time may amount to or could become a cost to them. Customers are prepared not to spend more cost of waiting or queuing. The time wasted on the queue would have been judiciously utilized elsewhere (the opportunity cost of time spent in queuing), (Elegalam, 1978). Bank customers have become increasingly demanding, because they require high quality, low priced and immediate service delivery. They want additional improvement of value from their chosen banks (Kasum A. S et al, 2006).

The aim of the research is to analyze Single Server – Single queue and Multi-server – Single queue systems, case studies of First and ECO banks using Simulation which will help to control and reduce waiting problems in the case study Banks and achieve increased efficiency.

1.4Aim and Research Objectives

The aim of the research is to analyze Single Server – Single queue and Multi-server – Single queue systems, case studies of First and ECO banks using Simulation in order to help controlling waiting in the case study Banks and achieve increased efficiency.

The objectives are to:

(i).                                     use direct observation to collect data necessary from the First and ECO Banks for analyzing them using electronic device.

(ii).                                    fit that data in to the Queuing formula for M/M/1 (M means Arrival process which is Markovian or Poisson process or (Random) arrival process, M means Service time distribution which is Exponential, 1 means the number of servers) and M/M/S (M means Arrival pr


You either get what you want or your money back. T&C Apply







You can find more project topics easily, just search

Quick Project Topic Search