doi: 10.7763/IJMO.2023.V13.826
A Simulation of the Optimal Personnel Demand for Banking Hall Services
David Oriedi
1,*
,
Kennedy Malanga
2
,
George Musumba
1
,
Gabriel Kamau
1
,
Mosses Ollengo
3
- 1 Department of Computer Science, Dedan Kimathi University of Technology, Nyeri, Kenya
- 2 Department of Information Technology, Kirinyaga University, Nyeri, Kenya
- 3 Department of Chemistry, Dedan Kimathi University of Technology, Nyeri-Kenya
- Manuscript received December 3, 2022
- revised January 9, 2023
- accepted February 25, 2023
- published May 10, 2023
Abstract
The banking industry has seen a revolutionarymoment in adopting mobile banking technology in the last fewyears. The technology has contributed to many customerskeeping off the banking hall for basic and routine transactions.This has largely been attributed to the convenience of mobilebanking, including time management and increased privacy.However, there are still times when a bank conducts large-scaleservice provision for many people. For example, a paymentagency contracted by the government to disburse funds to asection of the citizens may require that money be channeled onlythrough a particular bank. If the period for such a requirementis limited, there is likely to be pressure on both the bank and thewould-be customers because of long queues. For cases like that,there is a need to simulate possible scenarios and plan to avoiddelays and frustrations for both parties. This work proposes aqueue simulation model that can be used to forecast the numberof bank staff that can be deployed for such a scenario vis a visthe expected number of customers seeking service. Results haveshown that the simulation model can help the bank managementmake optimal choices that will avoid waste in the form of humanor financial resources.
Keywords
- Bank
- model
- simulation
- model
- queue
How to Cite
David Oriedi, Kennedy Malanga, George Musumba, Gabriel Kamau, and Mosses Ollengo, "A Simulation of the Optimal Personnel Demand for Banking Hall Services," International Journal of Modeling and Optimization, vol. 13, no. 2, pp. 60-65, 2023. https://doi.org/ 10.7763/IJMO.2023.V13.826
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).