Utilisation and Integration of Operations Research Techniques in Nigerian Commercial Banking Institutions
Utilisation and Integration of Operations Research Techniques in Nigerian Commercial Banking Institutions.
ABSTRACT
The study seeks to determine the extent of utilisation and integration of Operations Research (OR) in Nigerian commercial banking institutions.
Its specific objectives are to ascertain the frequency of use of OR techniques in the investment decisions of Nigerian commercial banks, ascertain the extent of use of OR model in the liquidity management decisions of Nigerian commercial banks.
Determine the ratio of usage of OR techniques in the loans and credit administration decisions of Nigerian commercial banks, determine the level of application of OR in the operations management decisions of Nigerian commercial banks.
Ascertain the determinants of successful OR application in the operations of Nigerian commercial banks; and to determine the level of integration of OR in the commercial banking operations of Nigerian commercial banks.
The research instrument used for data collection is a combination of questionnaire and structured oral interview. The data collected was analysed using simple percentages and relative frequencies; while the hypotheses raised were tested using Z-test statistics at five percent (5%) level of significance.
The investigations revealed a high frequency of use of OR techniques in solving the investment decision problems of Nigerian commercial banks, a high extent of use of OR techniques in handling the liquidity management decision problems of Nigerian commercial banks.
INTRODUCTION
In recent years, there has been considerable interest in describing the practice of Operations Research in business oriented organisations (commercial banks inclusive).
Previous studies have, for the most part, been general in their description of the role of Operations Research in business organisations (Uwah, 2007; Ighomereho, 2006).
All business organisations are set up to achieve certain specified goals and objectives by efficiently utilizing the vast array of resources which they have at their disposal.
These resources often include human resources, machines and money amongst numerous others; and often decisions must be made concerning the most efficient and cost effective means of utilizing every available resource.
One of the modern techniques that can assist managers in this regard is Operations Research which is also referred to as Management Science, Quantitative Analysis or Decision Science.
Operations Research basically refers to the application of quantitative techniques in organisations with the aim of aiding and improving management decision making (Kalavathy, 2008).
It is also concerned with the analysis of complex business problems with the aim of determining the optimal solutions to such problems.
In this regard, it emphasizes throughout the optimization of organizational and system performance using quantitative techniques and modeling to help make better decisions (Ighomereho, 2006).
REFERENCES
Agbadudu, A.B., Ogunrin, F.O. and Ighomereho, O.S. (2004). Strategic Planning with Input-Output Table: A Linear Programming approach. Nigerian Journal of Business Administration, 6(1), 7-16.
Board, J.L.G., Sutcliffe, C.M.S. and Ziemba, W.T. (1999). Portfolio Theory: Mean Variance in Encyclopedia of Operations Research and Management Science edited by Saul I. Gass and Carl M. Harris. Boston: Kluwer Academics Publishing.
Elimam, A.A., Girgis, M. and Kotob, S. (1997). A Solution to Post Crash Dept Entanglements in Kuwaits al-Manakh Stock Market. Interfaces, 27(1), 89-106.
Holmer, M.R. and Zenios, S.A. (1998). “Designing Callable Bonds Using Simulated Annealing. In Operational Tools in Management of Financial Risk, edited by C. Zopounidis, Kluwer Athens: Kluwer Academic Publishers.
Keim, D.B. and Ziemba, W.T. eds (1999). Security Market Imperfections in Worldwide Equity Markets. London: Cambridge University Press.
Klaassen, P. (1998). Financial Asset Pricing Theory and Stochastic Programming Models for Asset/Liability Management: A Synthesis. Management Science, 44(1), 31-48.
CSN Team.
