Bank Service Performance Improvements using Multi-Sever Queue System (original) (raw)
Related papers
2015
This research study is analysis of single queue – single server and single queue multi server systems using simulation in Banks in Zaria and Minna which are cities in Nigeria. The data collected was analyzed and simulation was performed to reveal the problems associated with the case study Banks. The result revealed that the Banks can reduce customer waiting time as a tradeoff or an opportunity cSSost. Economic analysis of these costs will help the management to make a trade-off between the increased costs of providing better service and the decreased waiting time costs of customers derived from providing that service.
Modeling and simulation of queuing system to improve service quality at commercial bank of Ethiopia
Cogent Engineering, 2023
This study aims to develop a queuing model at the Commercial Bank of Ethiopia to improve the service quality perceived by customers using a simulation tool. Performance variables that were considered when developing this model are the average waiting time for a client to get service, customer arrival rates, and service time. After the identification of the problem, the service quality of the bank is assessed using a questionnaire that was prepared in SERVQUAL format. The filled-out and returned questionnaires were analyzed using SPSS, and the results show that the service quality of the bank was deemed very low. The recorded data was then ultimately used as a basis for the determination of arrival, service rates, and the distribution function in the simulation input analyzer. The distribution function determined was used as an input for the development of the existing queue model, and based on that, scientific scenarios are adopted from scientific research and further observations at the bank are added to show enhancement of the existing model. The study used four scenarios to test the response group, and one scenario was selected as the best. This has been identified by adding a server to the counters where there is less utilization, that is, servers four and five. As a result, the waiting time has been minimized by 20 minutes under server four and by 83.4 minutes under server five. Also, the number of customers served per day can be increased from 1048 to 1168, which is 11.45% improvement.
— In this paper, the problem of maximizing customer satisfaction and minimizing cost of providing service were examined with the view of establishing optimal service level that will cater for the tradeoff between the cost of providing banking service to customers and waiting cost. To achieve this, multichannel, single stage queuing (M/M/S) model was adopted and applied. The operating characteristics were calculated with the help of Microsoft Excel package and graph of total expected cost, expected service cost and expected waiting cost were plotted against service level. The data for this study were collected from Diamond bank Plc, Eziukwu Aba through observations and personal interview. The paper suggested an optimal service level of 7tellers for the case study used. The result of this study will be a guide to other operation managers of banks as the factors to be considered when deciding the number of service levels to use for optimal service to be achieved have been x-rayed.
A Case Study of Bank Queueing Model
2013
This paper deals with the Queueing theory and the analysis of queueing system by using probability curves. Starting with the basis of the distributions and important concepts of queueing theory, probability curves of Gamma distribution are used to analyse the banking service.
On Application of Queuing Models to Customers Management in Banking System
Queue is a 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 paper 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.We used the Markovian birth and death process to analyze the queuing model , which is the Multiple servers, single queue, (M/M/S) queuing model to analyze the data collected by observation from a bank and from the results obtained, the arrival rate is 0.1207 and the service rate is 0.156, the probability that the servers are idle is 0.44 which shows that the servers will be 44% idle and 56% busy, the expected number in the waiting line is 0.1361, the expected number in the system is 0.9098. The expected waiting time in the queue is 1.276 and the expected total time lost waiting in one day is 3.2664 hours, the average cost per day for waiting is ₦65.328 and from the calculation of the comparing solutions, the average cost per day from waiting is ₦7.966 which means that there had been a saving in the expected cost of ₦65.328-₦7.966 = ₦57.362. This means that with three servers, the average cost from waiting is reduced. Hence we concluded that the aim and objectives of this paper was achieved.
Investigating the Application of Queue Theory in the Nigerian Banking System
SSRN Electronic Journal
This study examined the application of queue theory in the banking system in Nigeria, with particular reference to GTBank and Ecobank Idumota branch, Lagos, Lagos state. The queuing characteristics of the banks were analyzed using a Multi-Server Queuing Model. The performance measures analysis including the waiting and operation costs for the banks were computed with a view to determining the optimal service level. Findings revealed that the traffic intensity was higher in GTbank with p =0.98 than in Ecobank with p= 0.78. Also, the potential utilization showed that Ecobank was far below efficiency compared to GTBank. Looking at the waiting time of customers in line and the time spent in the system, that is (Wq + Ws), we discovered that customers in Ecobank spent more time before being served both on queue and in the system than that of GTBank bank. The study concluded by emphasizing the relevance of queuing theory to the effective service delivery of the banking sector in Nigeria and strongly recommends that for efficiency and quality of service delivery to customers, the management of GTBank and Ecobank should adopt a 13-server model and 10-server model respectively to reduce total expected costs and increase customer satisfaction.
Modeling and Simulation of a Bank Queuing System
One of the major factors influencing the success of organizations in today's competitive world is to increase customer satisfaction through the improvement of service quality. In any service organization, managers are mostly concerned about the time that customers are required to wait for receiving their service. Banks in particular pay special attention to service quality as the most significant core competence. The queue length and waiting time are two significant factors which play important roles in customer perception about the quality of service in banks. Therefore, banks' managers are concerned about providing the optimal service configuration that can satisfy both customers and service providers. Among different approaches which are useful to evaluate different alternatives, simulation has proven its high capability in modeling and evaluating such situations. This study attempts to investigate and suggest the best possible configuration for a bank in Malaysia through constructing computer-based simulation models. As the result of this study, the final suggested configuration shows improvement in terms of average utilization rate of counters and average waiting time that customers have to spend in the queue.
ORIGINAL ARTICLES A Regression Analysis Approach to Queueing System Modelling: a Case of Banks
2011
This paper seeks to establish queuing models that can help banks to improve on their customer service within and outside their place of business. Regression analysis was employed to model the banks' queue system. It was found that The Coefficient of determination, R 2 value was close to unity for multiple linear regression and unity for non-linear regression. Also, the Degree of Correlation obtained was found to be 92% and 100% for the multiple linear regression and non-linear regression which explains that the original uncertainty has been explained by the models thus developed. Therefore, the models clearly indicate that Regression Analysis can be used to model the queuing system of any bank for improved customer service efficiency. Nomenclature: s = Number of servers in the queuing system l = Arrival rate. m = Service rate ρ = Utilization factor L = Expected number of customers in the queuing system L q = Expected queue length (excluding customers being served) W = Waiting ti...
A Regression Analysis Approach to Queueing System Modelling: a Case of Banks
2011
This paper seeks to establish queuing models that can help banks to improve on their customer service within and outside their place of business. Regression analysis was employed to model the banks' queue system. It was found that The Coefficient of determination, R 2 value was close to unity for multiple linear regression and unity for non-linear regression. Also, the Degree of Correlation obtained was found to be 92% and 100% for the multiple linear regression and non-linear regression which explains that the original uncertainty has been explained by the models thus developed. Therefore, the models clearly indicate that Regression Analysis can be used to model the queuing system of any bank for improved customer service efficiency.
Application of Multi-server Queue Model (m/m/c) for Waiting Lines Management in Banking System
Asian Journal of Mathematical Sciences (AJMS), 2022
Queues or waiting lines arise when the demand for service exceeds the capacity of a service facility. One of the major challenges bank customers encounter in banks is the waiting lines in automated teller machines (ATMs). This study formulated a Multi-Server Queue Model (M/M/C) for Queue Management in Banking ATM. The performance level of a typical bank ATM has been effectively investigated using the M/M/S queuing model. It was observed that the busy time of the machine is 2.6 h while the idle time is 7.4 h in the 10 h of banking time which is attributed to the availability of many servers in the system. The utilization factor is 0.26 or 26.0% shows that the service delivery of the machine is very efficient and there is no urgent need for an additional server. The researcher thereby recommended that banks should consider the use of the queue model to test the performance of waiting lines in the ATMs.