An impartial financial decision support system (e-FDSS) for construction SMEs in Hong Kong

Abstract

Comparing to the other industries in Hong Kong, the construction industry generally experiences an unreasonably greater number of bankruptcies since the financial crisis in 1997. The main reasons are that the financial resources are insufficient and the contractors fail to persuade creditors. Small and Medium Enterprises (SMEs) contribute 98% of the economy in Hong Kong. However, in a capital budgeting evaluation survey conducted in 1999, less than 30% of construction SMEs claimed that their firms used financial decision support tools for managing their projects. In a recent survey with 30.7% responses has also been conducted in 2004 using modified Pike’s study (1988) to study the financial behaviour in local Group A-C contractors, less than 56.5% of construction SMEs reported to use any financial decision support tools. The study in this thesis therefore investigates an impartial financial decision support system (FDSS) called e-FDSS for the solution of multi-criterion financial risk and decision analysis in the projects of a construction SME. In the construction industry, tangible and intangible criteria always co-exist and their weights have significant impact on the final financial decision outcome. Individual cognitive judgment could not be simply modelled and quantified by rational rules in conventional multi-criterion decision aid (MCDA) methods. None of the conventional MCDA methods provided a way to solve complex decision-making problems reasonably well, due to the imprecise information and unquantifiable uncertainties available to the decision-makers. The method of entropy has been useful in quantifying uncertainty in decision-making. The e-FDSS is entropy-based. A two-dimensional (2-D) plane is first formulated as the inclusion of four principal decision vectors including (1) the relative weights between construction activities (unbiased first principal vectors), (2) between potential projects (second principal vectors), (3) between financial risk incurred (third principal vectors), and (4) the weights of risk for each activity arising on each project (fourth principal vectors). As there should be no bias between the construction activities themselves, the first principal vectors are different from the other vectors that they are unbiased. Risk adjusted discount rate (RADR) of each vector is then incorporated with the weights derived by the 2-D plane to obtain the final three-dimensional (3-D) decision weights. The e-FDSS also incorporates a Funding Strategy Model (FSM) to maximize or minimize the loan and to minimize the interest payments for all projects. Two adaptive genetic algorithms (AGA) are then employed to find the best projects and loan decision problems in e-FDSS to improve the performance of the canonical GA which is characterized by static crossover and mutation probability. Multiple projects being undertaken by a construction SME in Hong Kong was assessed to evaluate the system. The results indicated that uncertainties in each vector have been quantified to provide an upper, average and lower bound financial risks on projects with inconsistency 0.009, 0.032 and 0.036 respectively. Finally, a benchmarked overall cash flow was achieved in the selected projects. The original forecasted ratio to the total contract sum of selected projects was 62.87%. The risk adjusted discount overall profit at the end was 0.97 millions more than that of the original forecasted profit and its ratio to the total contract sum of selected projects was 65.79%. SME Loan Guarantee Scheme (SGS) that was launched by the Hong Kong Special Administration Region (HKSAR) was first identified as the source of external financing. An accurate, objective, realistic and reliable decision on financial risk analysis could be provided to the decision-makers to evaluate, select, and control the projects by rating impartially and discounting the cash flow in terms of risk rate with the most suitable source of findings. In addition, resource allocation could be optimized and the best time to start a new project can be identified in the progress curve. The cash flow profiles of projects were predicted accurately with the most adverse financial condition shown to the construction SME. Thus the contractor could adopt suitable management strategies to mitigate the risk to an acceptance level so that the corporate cash flow is improved to reduce the chance of insolvency or bankruptcy. It was noted that the weightings obtained here were restricted to the multiple projects of a construction SME in Hong Kong. For small or international construction companies or for other special projects, different ratings on the criteria will result and more or less input criteria should be considered. Nevertheless, the merit of e-FDSS actually provides a method to tackle the quantitative and qualitative problem in complex decision-making problems. As many businesses have grown significantly and the environment becomes more unpredictable, a novel, reliable, impartial and user-friendly (FDSS is required to provide information for use by potential investors and the financial management of the company.

Date of Award	15 Feb 2006
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Yee Tak Andrew LEUNG (Supervisor) & Ka Chi LAM (Supervisor)