An organization's strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio's sustainable success and the achievement of those objectives. Moreover, project interdependencies and cause-effect relationships between risks create complexity for portfolio risk analysis. This paper presents a model using Bayesian network (BN) methodology for modeling and analyzing portfolio risks. To develop this model, first, portfolio-level risks and risks caused by project interdependencies are identified. Then, based on their cause-effect relationships all portfolio risks are organized in a BN. Conditional probability distributions for this network are specified and the Bayesian networks method is used to estimate the probability of portfolio risk. This model was applied to a portfolio of a construction company located in Iran and proved effective in analyzing portfolio risk probability. Furthermore, the model provided valuable information for selecting a portfolio's projects and making strategic decisions.
Despite broad improvements in construction management, claims still are an inseparable part of many con-struction projects. Due to huge cases of claim in construction industry, this study argues that claim management is a significant factor in construction projects success. In this study, the most possible causes of these emerging claims are identified and statistically ranked by Probability-Impact Matrix. Subsequently, by classifying claims in different cases, the most important ones are ranked in order to achieve a better understanding of claim management in each project. In this regard, a new index is defined, being able to be applied in a variety of projects with different time and cost values, to calculate the amount of possible claims in each project along with related ratios with respect to the cost and time of each claim. This study introduces a new model to predict the frequency of claims in construction projects. By using the proposed model, the rate of possible claims in each project can be obtained. This model is validated by applying it into fitting case studies in Iran construction industry.
This study addresses the effect of selecting an appropriate risk measure and the impact of this choice on the efficient frontier of the project portfolio of an organisation. The appropriate choice of a firm's project portfolio has a great impact on the organisational success. Each portfolio manager selects the best projects with different criteria and consistent with firm's strategic objectives. We used the Markowitz efficient frontier method to select the best projects of the organisation. The choice of proper measures impacts on this decision and can change the organisation's portfolio. The standard deviation was applied, and the relevant optimisation was made for this purpose. Then, the semi-standard deviation was used to differentiate between favourable and unfavourable opportunities. Afterwards, Value at Risk and Expected Shortfall were applied as appropriate risk measures to make a better estimate of the tail risks. All these risk measures were used to select the best possible projects. Managers should select the appropriate risk measures according to their objectives, estimation of their project distribution, and characteristics of the projects. This research studied the best measures consistent with construction projects and the effect of changes in these measures.
In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.
The present research investigates the role of project management office in project efficiency and thus its success. The statistical population used in this work includes construction corporations active in the Iran construction industry and familiar with the concept of project management office. In such organizations, existence of the project management office and the success of their projects is firstly assessed and the role of the project management office in success of the organization's project as well as comparison of them with each other is then studied. For this purpose, a quantitative research methodology in the form of survey, along with designing a questionnaire with the help of 5-point Likert scale have been used. The results obtained indicate the existence of a highly strong linear relationship between the existence of project management office and the success of project. The results also show that the more highlighted the features of this office such as methods and standards for project management, project history archive, cooperation between employees/human resources office, project management educating and project administrative support, the more the success aspect of the project will be. Finally, the mentioned inferential statistics and qualitative features lead to generation of practical guidelines for organizations which have or are seeking to establish project management office.
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