Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/2637
Title: Selection of funding schemes by a borrowing decision model: A Hong Kong case study
Author(s): Leung, Andrew Yee Tak 
Author(s): Tang, C. M.
Wong, C. W. Y.
Lam, K. C.
Issue Date: 2006
Publisher: Routledge
Journal: Construction Management and Economics 
Volume: 24
Issue: 4
Start page: 349
End page: 365
Abstract: 
In financial decision‐making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi‐structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium‐size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision‐maker to analyse the financial options.
URI: https://repository.cihe.edu.hk/jspui/handle/cihe/2637
DOI: 10.1080/01446190500434906
CIHE Affiliated Publication: No
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