Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

Risk Identification and Assessment in PPP Infrastructure Projects using Fuzzy Analytical Hierarchy Process and Life-Cycle Methodology

To fulfil the increasing demands of the public,Public Private Partnership (PPP) has beenincreasingly used to procure infrastructureprojects, such as motor ways, bridges, tunnelsand railways. However, the risks involved inPPP projects are unique and dynamic due tolarge amount of investment and longconcession period. This paper aims to developa risk identification framework from theperspectives of project life cycle, and anassessment framework for risks associatedwith PPP project using fuzzy analyticalhierarchy process (AHP). First the paperreviews the current literature to identifycommon risks in PPP infrastructure projectsand classification methods used. The risksidentified from the literature were classifiedusing project life cycle perspectives. Followingthat, the paper presents the advantages offuzzy AHP. Furthermore, the paper provides aframework for assessment of risks in PPPprojects followed by an illustrative examplewhere the data was obtained from surveyquestionnaires. The paper concludes that risksassociated in PPP infrastructure projects areunique and therefore it is beneficial to classifythem from project life cycle perspectives, andthe proposed fuzzy AHP method is suitable forthe assessment of these risks

Analysis and Management of the Price Volatility in the Construction Industry

The problem of price volatility as it pertains to material and labor is a major source of risk and financial distress for all the participants in the construction industry. The overarching goal of this dissertation is to address this problem from both viewpoints of risk analysis and risk management. This dissertation offers three independent papers addressing this goal. In the first paper using the Engineering News Record Construction Cost Index (ENR CCI), a predictive model is developed. The model uses General Autoregressive Conditional Heteroscedastic (GARCH) approach which facilitates both forecasting of the future values of the CCI, and capturing and quantifying its volatilities as a separate measure of risk through the passage of time. GARCH (1,1) was recognized as the best model. The maximum volatility was observed in October 2008 and results showed persistent volatility of the CCI in the case of external economic shocks. In the second paper using the same cost index (ENR CCI), the methodology of the first paper is integrated with Value at Risk concept to cautiously estimate the escalation factor in both short and long-term construction projects for avoiding cost overrun due to price volatilities and inflation. Proposed methodology was also applied to two construction projects in which the estimated escalation factors revealed satisfactory performances in terms of accuracy and reliability. Finally, the third paper addresses the price volatility from the view of risk management. It entails two objectives of identifying and ranking of potential management strategies. The former is achieved via in-depth literature review and questionnaire interviews with industry experts. The latter is done using Analytic Hierarchy Process (AHP). Quantitative risk management methods, alike those offered in foregoing papers are considered as one of the candidates in dealing with the price volatility risk. Cost, risk allocation and duration were perceived as the most significant criteria (project indicators) in construction projects. Also, Integrated Project Delivery (IPD) with respect to project duration; quantitative risk management methods with respect to the cost; and Price Adjustment Clauses (PAC) with respect to the risk allocation, were recognized as the top strategies to manage the risk of price volatilities