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Reseach Article

Multicriteria Decision Approach to Budgetary Analysis in Taraba State, North East Nigeria

by H. B. Habu, A. Okolo
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 21
Year of Publication: 2013
Authors: H. B. Habu, A. Okolo
10.5120/13047-0296

H. B. Habu, A. Okolo . Multicriteria Decision Approach to Budgetary Analysis in Taraba State, North East Nigeria. International Journal of Computer Applications. 74, 21 ( July 2013), 55-59. DOI=10.5120/13047-0296

@article{ 10.5120/13047-0296,
author = { H. B. Habu, A. Okolo },
title = { Multicriteria Decision Approach to Budgetary Analysis in Taraba State, North East Nigeria },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 21 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 55-59 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number21/13047-0296/ },
doi = { 10.5120/13047-0296 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:42:58.316432+05:30
%A H. B. Habu
%A A. Okolo
%T Multicriteria Decision Approach to Budgetary Analysis in Taraba State, North East Nigeria
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 21
%P 55-59
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This study proposes a two-stage process of multi-criteria decision making approach to budgeting for efficient sectoral allocation. The two approaches of Multi-Criteria Decision Analysis (MCDA) used are Analytical Hierarchy Process (AHP) and Goal Programming (GP). The former takes care of an important aspect known as participatory budgeting while the latter handles the optimization aspect which outlines the areas of differences (also known as deviation) when compromise between the two parties is needed. Findings based on analyzing model outcomes, showed that the priorities of stake holders and that of government vary in terms of budget allocation. In other to reach a compromise, the study revealed that Education sector needed the greatest attention, closely followed by General Administration, Health and lastly Forestry.

References
  1. Charnes, A. and Cooper, W. (1961). Management models and industrial applications of linear programming, John Wiley and Sons.
  2. Chen, F. F. and Everett, E. A. Jr. (1991). The impact of flexible manufacturing systems on productivity and quality. IEEE Transactions on Engineering Management, Vol. 38, No. 1, 33-45.
  3. Chun-Chin, W., Chen-Fu C., Mao-Jiun, J. W. (2006). An AHP-based approach to ERP system selection. Int. J. Production Economics, Vol. 96, 47 – 62.
  4. Getachew, N. (2005). Analysis of medium term expenditure planning and budget allocation in Ethiopia (Unpublished thesis submitted to the graduate studies of Addis Ababa University).
  5. Habeeb, Y. A. (1991). Adapting Multicriteria Planning to Nigerian Economy. Journal of Operational Research Society. Vol. 42. No.10, 885-888
  6. Hou, Y. (2006). Planning and budgeting — the case for integrating planning and budgeting. Draft paper for international symposium on public budgeting and governance capacity Guangzhou, China.
  7. Iris, L. (1999). Getting Started on Budget Work, Notes submitted to the Second International Budget Conference entitled “Transparency and Participa-tion in the Budget Process,” Cape Town, South Africa, February 21 to 25, 1999.
  8. Khorramshahgol, R., Hussein, A. and Yvan, G. (1988). An integrated approach to project evaluation and selection. IEEE Transactions on Engineering Management, Vol. 35, No. 4, 265-270.
  9. Korhonen, P. and Wallenius, J. (1990). Using qualitative data in multiple objective linear programming. European Journal of Operational Research, Vol. 48, 81- 87.
  10. Kvanli, A. H. (1980). Financial Planning using goal programming. Omega; Vol. 8, 207 -18.
  11. Lin, W. T. (1989). A survey of goal programming applications. Omega; Vol. 8: 115-17.
  12. Myint, S. and Tabucanon, M. T. (1994). A multi-criteria approach to machine selection for flexile manufacturing systems. International Journal of Production Economics, Vol. 33, Nos 1 – 3, 121 – 131.
  13. OECD Observer (2008). Performance budgeting: a users’ guide. March 2008 OECD policy briefs. Publications of Organisation for Economic Co-Operation and Development. Also available on www.oecd.org/ publications/policy briefs.
  14. Rama, M. R., Naidu, M. M. and Govindarajulu, P. (2007). An Integrated approach of Analytical Hierarchy Process Model and Goal Model (AHP-GP Model) for Selection of Software Architecture IJCSNS. International Journal of Computer Science and Network Security, Vol. 7, No. 10, 108.
  15. Ramanathan, R. and Genesh, L. S. (1995). Energy resource allocation incorporating qualitative and quanti-tative criteria: An Integrated model using goal programming AHP. Socio-Economic Planning Sciences, Vol. 29, No.3, 197-218.
  16. Saaty, T. L. (1977). Scaling Method for Priorities in Hierarchical Structures. Journal of Mathematical Psychology, Vol. 15, 234-281.
  17. Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw- Hill, New York.
  18. Saaty, T. L. (1990). Eigenvector and Logarithmic Least Squares. European Journal of Operational Research, Vol. 48, 156 – 160.
  19. Sarkis, J. and Sundarraj, R. P. (2005). Evaluation of Enterprise Information Technologies: A Decision Model for High-Level Consideration of Strategic and Operational Issues, IEEE Transac-tions on Systems, Man., and Cybernetics -Part C: Applications and Reviews, 1-14.
  20. Schick, A. (1969). The road to PPB: The stages of budget reform, in James W. Davis, Jr. (ed). Politics, Programs and Budgets. Cliffs, New Jersey: Prentice-Hall Inc.
  21. Schniederjans, M. J. and Wilson, R. L. (1991). Using the analytic hierarchy process and goal programming for information system project selection. Information & Management, Vol. 20, 333 – 342.
  22. Suresh, T., Nallan, C. and Kaparthi, S. (1992). Flexible automation invest-ments: A synthesis of two multi-objective modeling approaches. Com-puter and Industrial Engineering, Vol. 22, No. 3, 257 – 272.
  23. Taylor III, B. W., Moore, L. T., and Clayton, E. R. (1982). R & D Project selection and man power allocation with integer non-linear goal program-ing. Management Science. Vol. 28, 1149 – 58.
  24. USAID (2005). Final report: Nigeria budget process support. Submitted to US Agency for International Development/ Nigeria. USAID/n/ program office, Metro plaza Abuja, Nigeria.
Index Terms

Computer Science
Information Sciences

Keywords

Analytical Hierarchy Process Budget Goal Programming