Search

Although conceptualized in various ways within the project management literature, complexity is usually identified as one of the drivers of uncertainty, which may result in deviations from the expected project performance in the construction industry. Effective strategies to manage risk and complexity can only be formulated by understanding the complexity-uncertainty-performance triad in construction projects and modeling the non-linear interactions between these factors. In this study, a meta-modeling approach was utilized for understanding complex interactions within the triad. Using a database of projects from the seed scenarios developed by experts, a Bayesian Belief Network (BBN) meta-model was constructed for capturing complex interactions across the triad. Shapley value from Game Theory was adapted to assess the output of the BBN meta-model for establishing the relative contribution of complexity and uncertainty factors to project performance while considering the efficacy of potential strategies. The output of the Shapley value analysis was used to develop an Artificial Neural Network (ANN) model for predicting project performance. The application of the proposed methodology was demonstrated through a case study involving experts from an international construction company. The results clearly manifest the merits of integrating these approaches in a unique order in that BBNs are useful for understanding the holistic account of complex interdependencies involved in construction projects, utilization of Shapley value helps in establishing the relative importance of factors across a BBN meta-model and allocating limited resources to manage project complexity and uncertainty, and ANNs exhibit an improved accuracy in predicting the project performance given the relative importance established across complexity and uncertainty factors. The findings from the case study demonstrate that the proposed methodology can be used to understand how performance may change with respect to different combinations of implemented strategies, complexity and uncertainty factors. [ABSTRACT FROM AUTHOR]

In the globalized business world, construction companies start to seek new opportunities to invest on an international basis in order to gain profit. Therefore, construction companies have to conduct not only national projects but also international projects to be competitive. However, although these international projects can be profitable, the construction companies face many challenges in the management of these projects due to the country-specific problems and conditions. This can lead to variation in the management of similar projects conducted in different countries. In particular, cost estimation in different countries is a challenging task for construction companies. Therefore, in order to provide insights about construction cost in different countries, different organizations publish construction cost indices. However, some criticisms related to the reliability and usability of these indices are stated. In this study, a new concept, called a cost map, is proposed by developing a framework based on twelve macro level parameters. The cost map is applied to 37 European countries. The data related to these parameters are collected using different databases. European countries are clustered by using a self-organizing map. As a result of this study, the cost map is determined as a reliable and convenient tool for a cost comparison. [ABSTRACT FROM AUTHOR]

Risk management is deemed as a critical process toward achieving the objectives of any project. A number of tools and techniques have been developed to help project managers reduce the risk involved in complex projects as risk is generally perceived as a negative event. However, uncertainty, which may lead to risk events may well result in opportunities. With the main aim of managing both risk and opportunity within an interdependent setting of interacting project uncertainties, we present a new thinking, called 'uncertainty thinking', a process model, a Bayesian Belief Network and Influence Diagram based modeling approach to implement uncertainty thinking in practice. We demonstrate the implementation of the developed uncertainty modeling approach through an illustrative case. We introduce new loss and opportunity metrics to help project managers prioritize uncertain variables within a network setting taking into account interdependencies and develop an optimization scheme for selecting loss reduction and opportunity exploitation strategies in accordance with the decision maker's loss averse/gain seeking preferences. The results reveal the importance of modeling both risk and opportunity in managing project uncertainties as focusing only on the negative connotation of risk may result in selecting sub-optimal decisions. Furthermore, we also establish that minimization of the expected loss across a risk network does not necessarily maximize the expected gain. [ABSTRACT FROM AUTHOR]

Introduction. Expert witness reports, prepared with the aim of quantifying fault rates among parties, play an important role in a court's final decision. However, conflicting fault rates assigned by different expert witness boards lead to iterative objections raised by the related parties. This unfavorable situation mainly originates due to the subjectivity of expert judgments and unavailability of objective information about the causes of accidents. As a solution to this shortcoming, an expert system based on a rule-based system was developed for the quantification of fault rates in construction fall accidents. The aim of developing DsSafe is decreasing the subjectivity inherent in expert witness reports. Methodology. Eighty-four inspection reports prepared by the official and authorized inspectors were examined and root causes of construction fall accidents in Turkey were identified. Using this information, an evaluation form was designed and submitted to the experts. Experts were asked to evaluate the importance level of the factors that govern fall accidents and determine the fault rates under different scenarios. Based on expert judgments, a rule-based expert system was developed. The accuracy and reliability of DsSafe were tested with real data as obtained from finalized court cases. Result. DsSafe gives satisfactory results. [ABSTRACT FROM AUTHOR]

Literature on international construction is rich in adopting conceptual frameworks to investigate levels of international competitiveness and making inter‐country comparisons about sources of national competitive advantage. However, there are limited studies that result from collaborative work between different country researchers about development of custom frameworks to investigate complexities of international construction business, experience‐based generic libraries applicable to international construction projects and forecasting models. Ranko Bon's contribution to the international construction literature is invaluable as he has dealt with broad trends and dominant patterns of change in the global construction market by referring to judgments of experts from all over the world and helped dissemination of this practical information which may be used by policy makers and construction professionals seeking jobs in the global market. [ABSTRACT FROM AUTHOR]

Copyright of Building Research & Information is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)