Browsing by Author "Kyei Baffour, Yaw Anokye"

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    Modelling queuing system in the banking industry: Case study Ghana Commercial Bank, Suame, Kumasi Ecobank, Ashtown, Kumasi and Barclays Bank of Ghana, Tanoso Branches
    (2014-09-09) Kyei Baffour, Yaw Anokye
    The issue of queuing is a bother to both management and customers in the delivery of service in the banking industry. The main idea or pivot of the queuing system is a teller who provides some services to a population of customers. This study therefore determined whether the present capacity level in the banking industry strike a balance between waiting and service time using Barclays Bank, Tanoso Branch, Ghana Commercial Bank, Suame Branch and Ecobank, Ashtown Branch as a case of interest. Primary data on five hundred and fifty-eight (558) 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. By using the queuing rule First-come, First-serve as practiced by the case study and M/M/s queuing model, the performance measures were calculated uncovering the applicability and extent of usage of queuing models in achieving customer satisfaction at lowest cost by minimizing waiting times, idle times, capacity utilization and queues at the bank. The study shows 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. It was observed that any time the number of tellers at BBG an Ecobank were reduced to two during a peak day, the queue elongated resulting in high capacity utilization factor and hence a high waiting time. It is therefore recommended that management makes better decisions relating to number of tellers that would be necessary to serve customers during peak and off-peak hours, days and weeks.