Modelling and assessment of critical risks in BOT road projects

Abstract

Over the years, many private sector participation (PSP) models have been evolved for infrastructure procurement and the Build-Operate-Transfer (BOT) model is one of the most common approaches used for the same. Private infrastructure projects under BOT arrangement have a complex risk profile and to a considerable extent, the success of any BOT project is influenced by the degree to which various project risks are managed. The major steps involved in risk management of a project are risk identification, risk assessment and the processes of prioritization and response to the risks. The conventional risk assessment approaches may not be effective in privatized infrastructure projects because of the fact that, they have very long project lifecycle with many country and sector specific risk factors. The assessment of complex risks is often a difficult task when past data on similar risks are not available. In this research, a risk probability and impact assessment framework based on fuzzy-fault tree and the Delphi method is proposed. The framework includes extensive scenario modelling of critical risks in projects and systematic processing of professional judgement (subjective knowledge) of experts and is developed and demonstrated in the context of critical risks in Indian BOT road projects. Detailed scenario modelling of most critical risks such as traffic revenue risk, delay in land acquisition, demand risk and delay in financial closure are also presented. The proposed risk assessment framework is generic and can be applied with appropriate modifications to suit any complex developmental project where past data is inadequate for risk assessment.BOT projects, risk modelling, risk assessment, fuzzy sets, possibility distribution,

Design and Pilot Run of Fuzzy Synthetic Model (Fsm) for Risk Evaluation in Civil Engineering

“…In addition, Thomas et al (2006) generated a fuzzy fault tree to enhance risk assessments by considering the opinions of different experts. A fuzzy decision-making model was designed by Wang and Elhag (2007) for a bridge construction project.…”

“…As an attempt to produce reliable final priority weighs, researchers adopted different types of Fuzzy prioritization approaches, for instance, the earliest attempt in prioritizing fuzzy weighs was accomplished by van Laarhoven and Pedrycz (1983) in which triangular fuzzy numbers were compared according to their membership functions. Likewise, Buckley (1985) used trapezoidal fuzzy numbers to integrate the fuzzy priorities of comparison ratios.…”

Impacts of Construction Events on the Project Equity Value of the Channel Tunnel Project

“…The most crucial element to successful project finance, then, is the effective management of various project risks; the main elements of project risk management include the identification, the measurement/assessment, and the process of prioritizing and responding to various project risks (Thomas et al, 2006). Among these elements, risk measurement/assessment is the most difficult task, which involves evaluation of the probability of occurrence of risk events and their impact on the project (Thomas et al, 2006).…”

“…Among these elements, risk measurement/assessment is the most difficult task, which involves evaluation of the probability of occurrence of risk events and their impact on the project (Thomas et al, 2006). For international construction projects, past research studies have proposed various approaches for project risk assessment/measurement, including: decision analysis (Jeljeli and Russell, 1995;Mulholland and Christian, 1999;Han and Diekmann, 2001), fuzzy set analysis (Jablonowski, 1994;Tah and Carr, 2000), simulation and sensitivity analysis (Woodward, 1995;Songer, et al, 1997;Ye and Tiong, 2000), and analytical hierarchy process analysis (Mustafa and Al-Bahar, 1991;Hastak and Shaked, 2000).…”

“…For international construction projects, past research studies have proposed various approaches for project risk assessment/measurement, including: decision analysis (Jeljeli and Russell, 1995;Mulholland and Christian, 1999;Han and Diekmann, 2001), fuzzy set analysis (Jablonowski, 1994;Tah and Carr, 2000), simulation and sensitivity analysis (Woodward, 1995;Songer, et al, 1997;Ye and Tiong, 2000), and analytical hierarchy process analysis (Mustafa and Al-Bahar, 1991;Hastak and Shaked, 2000). In most of the infrastructure BOT projects, simulation and sensitivity analysis are used for technical and financial risk assessment; however, risk measurement is often constrained by the nonavailability of past information on impact of important risk factors, including events which affect the risk profile of BOT projects (Thomas et al, 2006). Although at least nine empirical studies on PPP risks have been written to date, all of these studies are based on surveys and case studies (Li et al, 2005a;Shen et al, 2006;Akintoye et al, 1998;Li and Tiong, 1999;Schaufelberger and Wipadapisut, 2003;Yeo and Tiong, 2000;Zayed and Chang, 2002;Lam and Chow, 1999;Abednego and Ogunlana, 2006).…”