Jin, X H (2011) Model for efficient risk allocation in privately financed public infrastructure projects using neuro-fuzzy techniques. Journal of Construction Engineering and Management, 137(11), pp. 1003-1014. ISSN 0733-9364
Abstract
Risk allocation plays a critical role in privately financed public infrastructure projects. Project performance is contingent on whether the adopted risk-allocation strategy can lead to efficient risk management. Founded primarily on the transaction cost economics, a theoretical framework was recently developed to model the risk allocation decision-making process in privately financed public infrastructure projects. In this paper, a neuro-fuzzy model adapted from an adaptive neuro-fuzzy inference system was further designed based on the framework by combining fuzzy logic and artificial neural network techniques. Real project data were used to train and validate the neuro-fuzzy models. To evaluate the neuro-fuzzy models, multiple linear regression models and fuzzy inference systems established in previous studies were used for a systematic comparison. The neuro-fuzzy models can serve the purpose of forecasting efficient risk-allocation strategies for privately financed public infrastructure projects at a highly accurate level that multiple linear regression models and fuzzy inference systems could not achieve. This paper presents a significant contribution to the body of knowledge because the established neuro-fuzzy model for efficient risk allocation represents an innovative and successful application of neuro-fuzzy techniques. It is thus possible to accurately predict efficient risk-allocation strategies in an ever-changing business environment, which had not been achieved in previous studies.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial neural networks; fuzzy logic; organizational capability; public-private partnership; risk allocation; transaction cost economics |
| Index terms: | risk management, project performance, risk allocation, partnership, decision-making process, fuzzy logic, forecasting, public infrastructure, regression model, organizational capability, body of knowledge, artificial neural network, strategy, project data, transaction cost, fuzzy inference |
| Subjects: | financial risk, project management theory and practice, management, infrastructure and transport systems, decision-making and optimization, financial analysis, statistical analysis, partnership management, decision analysis, sociology, risk assessment, data collection methods, knowledge management, data science, prediction and forecasting, modelling and simulation |
| Topics: | Cost Management, Business Strategy, Project Management, Research Practice, Engineering Principles, Information Management, Stakeholder Management, Risk Management, Digital Applications, Organizational Design |
| Descriptive scope: | 5 PCTEA |
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