eISSN: 3023-3267 editor@aimjournals.com
All Journals
Submit your article

Critique Open Research & Review

Open Access Peer Review International
Open Access

Financial Feasibility Assessment of Water Supply Infrastructure Development Using Fuzzy Logic Methodologies

DOI https://doi.org/10.55640/corr-v03i04-01
PDF
Dr. Navin Reddy 1 ,
4 Institute of Infrastructure and Environment, University of Edinburgh, Edinburgh, United Kingdom

Abstract

Financial feasibility studies are paramount for the successful development of large-scale infrastructure projects, such as Drinking Water Supply Systems (Sistem Penyediaan Air Minum - SPAM). However, these studies are often plagued by inherent uncertainties and imprecisions in various financial parameters, leading to potential inaccuracies in traditional evaluations. This article explores the application of fuzzy logic methodologies to enhance the robustness and realism of financial feasibility assessments for water supply infrastructure development. Traditional deterministic approaches, which rely on crisp numerical values, are often inadequate for capturing the subjective and imprecise nature of future costs, revenues, and economic conditions. Fuzzy set theory provides a powerful framework to model and incorporate these uncertainties, offering a more nuanced and realistic evaluation. By reviewing the principles of fuzzy finance and outlining a methodological framework for integrating fuzzy logic into key financial metrics like Net Present Value (NPV) and Internal Rate of Return (IRR), this study demonstrates how fuzzy methods can provide more robust decision-making support for project developers and investors, particularly in dynamic and uncertain environments. The approach aims to provide a more comprehensive understanding of financial viability, moving beyond single-point estimates to embrace ranges and degrees of possibility.

Keywords

Financial Feasibility, Water Supply Infrastructure, Decision Support Systems

References

📄 Buckley, J. J. (1987). "The fuzzy mathematics of finance." Fuzzy Sets and Systems, 21(3), 257–273. https://doi.org/10.1016/0165-0114(87)90128-X.
📄 Chiu, C.Y., & Park, C. (1994). "Fuzzy Cash Flow Analysis Using Present Worth Criterion." Fuzzy Cash Flow Analysis Using Present Worth Criterion, 39(2), 113–138. https://doi.org/10.1080/00137919408903117.
📄 Dhillon, A., et al. (2016). "Proteolytic Enzymes." Current Developments in Biotechnology and Bioengineering: Production, Isolation and Purification of Industrial Products, (September), 149–173. https://doi.org/10.1016/B978-0-444-63662-1.00007-5.
📄 Gray, C., Simanjuntak, P., Sabur, L. K., Maspaitella, P. P. L., & V. R. (2002). Pengantar Evaluasi Proyek. 2nd ed. Jakarta: Gramedia Pustaka Utama.
📄 Kasmir, & Jakfar. (2003). Studi Kelayakan Bisnis. Jakarta: Kencana Prenada Media Group.
📄 Liu, J., & Wu, C. (2018). "Fuzzy C-Means and Its Application in Financial Analysis." 19(1), 213–234.
📄 Majlender, P. (2003). "Strategic investment planning by using dynamic decision trees." Proceedings of the 36th Annual Hawaii International Conference on System Sciences, HICSS 2003. https://doi.org/10.1109/HICSS.2003.1174208.
📄 Martini, S., et al. (2010). "Fuzzy Investment Model for Financial Feasibility Analysis of Sugarcane-Based Industrial Diversification." Jurnal Sosial-Ekonomi Pertanian dan Agribisnis, 134–140.
📄 Omitaomu, O. A., & Badiru, A. (2007). "Fuzzy present value analysis model forevaluating information system projects." Engineering Economist, 52(2), 157–178. https://doi.org/10.1080/00137910701328912.
📄 Papulele, W. (2011). Investment Cost Analysis of Housing Projects. Faculty of Engineering, Manado.
📄 RH, L. (1987). Maintenance Engineering Handbook. Consulting Engineer, Old Bridge, New Jersey.

Similar Articles

1-10 of 17

You may also start an advanced similarity search for this article.