This paper investigates how technology influences banks’ efficient service delivery and reduces customers’ average waiting time in obtaining services in a commercial bank at Obafemi Awolowo University. The Direct non-participatory observation was adopted to record time measurements and primary data. The time measurements were based on customers’ arrival times to the banking hall and the service times of the customers who arrived at the bank between the hour of 12.00pm and 1.00pm which have been previously observed to be the bank’s peak period. Data were fitted into the model and the results computed and analyzed. The findings of the study show that both arrival of customers and service time rate of servers follow a poisson exponential probability distribution, respectively. The results reveal that the mean service rate, the mean time spent in the queue by a customer, and aggregate service rate in the system by a customer are substantially reduced and the waiting line is short in a technology driven bank. The study concluded that only technology driven services can reduce customers’ waiting time and improves efficient service delivery systems in Nigerian modern banking.
| Published in | International Journal of Finance and Banking Research (Volume 2, Issue 6) |
| DOI | 10.11648/j.ijfbr.20160206.11 |
| Page(s) | 185-192 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Waiting Lines, Technology, Banks’ Services, Poisson Distribution
| [1] | Samuelson, Douglas A. (1999) “Predictive Dialing for Outbound Telephone Call Centres”. Interfaces 29(5), pp. 66–81. |
| [2] | ErlangAgnerKrarue (1909) “The Theory of Probabilities and Telephone Conversations”. |
| [3] | Winston, W. L. (1991) “Operations Research: Applications and Algorithms”, Boston: PWS – Kent Publishing. |
| [4] | Dasgupta, Ani and Ghosh, Madhubani (2000) “Including Performance in a Queue Via Prices: The Case of a Riverine Port”, Management Science, 46(11), pp. 1466–1484. |
| [5] | Markov, A. A. (1906) “Extension of the Law of Large numbers to Dependent Quantities”, IzvestilaFiz-Matem, Vol. 2, pp. 135–156. |
| [6] | Cooper, R. B. (1981) “Introduction to Queuing Theory”; 2ndedn. Elesevier North Holland, New York. |
| [7] | Gross, D. and Harris, C. M. (1985) “Fundamental of Queuing Theory”, 2ndedn. John Wiley, New York. |
| [8] | Ullah, A. (2014) “Sub-Optimization of Bank Queuing System by Qualitative and Quantitative Analysis”, Vol. 2(2), pp. 978–1047. |
| [9] | Azmat, W. (2007) “Queuing Theory and Its Application: Analysis of the Sales Checkout Operations in Ica Supermarket, Dalana: University of Dalarna”, Department of Economics and Society. |
| [10] | Zhang, J. (1998) “Simulation for a Hospital Clinic Queue System”, System Engineering Theory and Practice, Vol. 3, pp. 140–144. |
| [11] | Bhathawala, B. P. (2012) “Case Study for Bank ATM Queuing Model”. International Journal of Engineering Research and Applications (IJERA), 2(5), pp. 1278–1284. |
| [12] | Famule, F. D. (2010) “Analysis of M/M/I Queuing Model with Applications to Waiting Time of Customers in Banks” Global Journal of Computer Science and Technology. |
| [13] | Vasumaths, A. D. (2010) “Application of Simulation Techniques in Queuing Model for ATM Facility”. International Journal of Applied Engineering Research, Dindiga. |
| [14] | Chen, H; Whitt, W. [2007] “Diffusion approximations for open queuing network with service interruptions”. Queuing system, vol. 13[4]; pp. 335-347. |
| [15] | Calving Yeung [2015] “Asymptotic analysis of real time queues”, paper presented at Shreve conference. |
| [16] | Jackson, J. R. (1957) “Networks of Waiting Lines Operation Research”, 5(4); pp. 518–521. |
| [17] | Abdul-Wahab, N. Y. and Ussiph, N. (2014) “An Application of Queuing Theory to ATM Service Optimization: A Case Study”, Mathematical Theory and Modeling, Vol. 4(6): 11–23. |
| [18] | TodYang (2000) “Theory and Methodology of Queues with a Variable Number of Servers”. European Journal of Operational Research, 124, pp. 615–628. |
| [19] | Kelly, F. P. (1975) “Networks of Queues with Customers of Different Types”. Journal of Applied Probability, 12(3), pp. 542–554. |
| [20] | Kendall, D. G. (1953) “Stochastic Processes Occurring in the Theory of Queues and their Analysis by the Method of the Imbedded Markov Chain”. The Annals of Mathematical Statistics, 24(3), pp. 338–340. |
| [21] | Lee A. M. [1996] “Applying queuing theory”, St. Marints press, New York. |
| [22] | Adekanye, F. A. (2003) “Innovations Technology and the Nigerian Financial Sector”. Papers and Proceedings of the Directors’ Seminar, Financial Institution Training Centre, Lagos. |
| [23] | Cane, A. (1992) “Information Technology and Communication Advantage: Lessons from the Developed Countries”. World Development 20(12). |
| [24] | Whitt, W. (1999) “Predicting Queuing Delays”. Management Science, 45(6), pp. 870–888. |
| [25] | Pepperd, J. (2001) “IT Strategy for Business”. Pitman Publishing. |
| [26] | Musara, M. and Fatoki, O. (2010) “Has Technological Innovations Resulted in Increased Efficiency and Cost Savings for Banks’ Customers?” African Journal of Business Management, Vol. 4(9), pp. 1813–1821. |
| [27] | Gordon, W. J., Newell, G. F. (1967) “Closed Queuing Systems with Exponential Servers”, Operation Research, 15(2), pp. 254–270. |
APA Style
Philip Olawale Odewole. (2016). Waiting Lines, Banks’ Effective Delivery Systems and Technology Driven Services in Nigeria: A Case Study. International Journal of Finance and Banking Research, 2(6), 185-192. https://doi.org/10.11648/j.ijfbr.20160206.11
ACS Style
Philip Olawale Odewole. Waiting Lines, Banks’ Effective Delivery Systems and Technology Driven Services in Nigeria: A Case Study. Int. J. Finance Bank. Res. 2016, 2(6), 185-192. doi: 10.11648/j.ijfbr.20160206.11
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Download@article{10.11648/j.ijfbr.20160206.11,
author = {Philip Olawale Odewole},
title = {Waiting Lines, Banks’ Effective Delivery Systems and Technology Driven Services in Nigeria: A Case Study},
journal = {International Journal of Finance and Banking Research},
volume = {2},
number = {6},
pages = {185-192},
doi = {10.11648/j.ijfbr.20160206.11},
url = {https://doi.org/10.11648/j.ijfbr.20160206.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijfbr.20160206.11},
abstract = {This paper investigates how technology influences banks’ efficient service delivery and reduces customers’ average waiting time in obtaining services in a commercial bank at Obafemi Awolowo University. The Direct non-participatory observation was adopted to record time measurements and primary data. The time measurements were based on customers’ arrival times to the banking hall and the service times of the customers who arrived at the bank between the hour of 12.00pm and 1.00pm which have been previously observed to be the bank’s peak period. Data were fitted into the model and the results computed and analyzed. The findings of the study show that both arrival of customers and service time rate of servers follow a poisson exponential probability distribution, respectively. The results reveal that the mean service rate, the mean time spent in the queue by a customer, and aggregate service rate in the system by a customer are substantially reduced and the waiting line is short in a technology driven bank. The study concluded that only technology driven services can reduce customers’ waiting time and improves efficient service delivery systems in Nigerian modern banking.},
year = {2016}
}
TY - JOUR T1 - Waiting Lines, Banks’ Effective Delivery Systems and Technology Driven Services in Nigeria: A Case Study AU - Philip Olawale Odewole Y1 - 2016/12/10 PY - 2016 N1 - https://doi.org/10.11648/j.ijfbr.20160206.11 DO - 10.11648/j.ijfbr.20160206.11 T2 - International Journal of Finance and Banking Research JF - International Journal of Finance and Banking Research JO - International Journal of Finance and Banking Research SP - 185 EP - 192 PB - Science Publishing Group SN - 2472-2278 UR - https://doi.org/10.11648/j.ijfbr.20160206.11 AB - This paper investigates how technology influences banks’ efficient service delivery and reduces customers’ average waiting time in obtaining services in a commercial bank at Obafemi Awolowo University. The Direct non-participatory observation was adopted to record time measurements and primary data. The time measurements were based on customers’ arrival times to the banking hall and the service times of the customers who arrived at the bank between the hour of 12.00pm and 1.00pm which have been previously observed to be the bank’s peak period. Data were fitted into the model and the results computed and analyzed. The findings of the study show that both arrival of customers and service time rate of servers follow a poisson exponential probability distribution, respectively. The results reveal that the mean service rate, the mean time spent in the queue by a customer, and aggregate service rate in the system by a customer are substantially reduced and the waiting line is short in a technology driven bank. The study concluded that only technology driven services can reduce customers’ waiting time and improves efficient service delivery systems in Nigerian modern banking. VL - 2 IS - 6 ER -
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