An Approach Based on Bayesian Network for Improving Project Management Maturity: An Application to Reduce Cost Overrun Risks in Engineering Projects

Organizational Aspects and Practices for Enhancing Organizational Project Management Maturity

An organization’s performance in a project is determined by its ability to implement project management knowledge and practices. This ability reflects the organization’s level of project management maturity (PMM). PMM is premised on the belief that the higher the PMM level, the higher the ability to successfully deliver a project. With this in mind, the current paper aims to determine the type of organizational aspects and practices that could influence the success of PMM implementation in organizations. For this purpose, a systematic literature review (SLR) was performed on 23 articles published between 2011 and 2021 that studied PMM. The findings showed that most articles stressed organizational culture and integration with strategic organizational initiatives. Among all the studied industries, the information technology industry stood out. Content analysis was used for analyzing data, which were thematized using ATLAS.ti. Ten sub-themes emerged, with six sub-themes under organizational aspects and four sub-themes under organizational practices. These sub-themes, which were intertwined with the implementation and growth of PMM in organizations, positively impact project delivery performance. Based on this, several future research opportunities were proposed.

Risk assessment of R&D projects: a new approach based on IVIF AHP and fuzzy axiomatic design

Both national and international encouragements for research and development (R&D) projects have been growing worldwide. Since R&D projects include various uncertainties related to time, technology, finance, and knowledge, risk management studies are highly significant for the success of these projects. In risk management, all of the potential actions that might have negative impacts on the processes or outputs of a project should be determined, and if it is possible, their negative impacts should be reduced before the project starts. In this study, after risks in R&D projects are determined, the alternative projects are prioritized with respect to these risks by using an approach based on interval-valued intuitionistic fuzzy AHP and fuzzy information axiom. Interval-valued Intuitionistic Fuzzy Analytic Hierarchy Process (IVIF AHP) is used to determine the importance degrees of the determined risk factors while fuzzy information axiom is used to evaluate R&D projects considering these risk factors. It is revealed that the most important risk is “Abnormal changes in cost” while the least important one is “Deficiencies in contract articles”.

Adaptation of a Cost Overrun Risk Prediction Model to the Type of Construction Facility

To assess the risk of project cost overrun, it is necessary to consider large amounts of symmetric and asymmetric data. This paper proposes a cost overrun risk prediction model, the structure of which is based on the fuzzy inference model of Mamdani. The model consists of numerous inputs and one output (multi-input-single-output (MISO)), based on processes running consecutively in three blocks (the fuzzy block, the interference block, and the block of sharpening the representative output value). The input variables of the model include the share of element costs in the building costs (SE), predicted changes in the number of works (WC), and expected changes in the unit price (PC). For the input variable SE, it is proposed to adjust the fuzzy set shapes to the type of building object. Single-family residential buildings, multi-family residential buildings, office buildings, highways, expressways, and sports fields were analyzed. The initial variable is the value of the risk of exceeding the costs of a given element of a construction investment project (R). In all, 27 rules were assumed in the interference block. Considering the possibility of applying sharpening methods in the cost overrun risk prediction model, the following defuzzification methods were investigated: the first of maxima, middle of maxima, and last of maxima method, the center of gravity method, and the bisector area method. Considering the advantages and disadvantages, the authors assumed that the correct and basic defuzzification method in the cost overrun risk prediction model was the center of gravity method. In order to check the correctness of the assumption made at the stage of designing the rule database, result diagrams were generated for the relationships between the variable (R) and the input variables of individual types of buildings. The results obtained confirm the correctness of the assumed assumptions and allow to consider the input variable (SE), adjusted individually to the model for each type of construction object, as crucial in the context of the impact on the output value of the output variable (R).