Designing a Framework to Estimate Project Duration with Respect to Weather Risk and Creating a Navigational Support System in Benchmark Space: Applied in Construction Projects

Abstract

Construction projects often do not meet their targets, and usually face time and cost overruns (Agyakwah-Baah & Fugar, 2010; Memon, Abdul, & Abdul, 2012). Due to the complexity and dynamic nature of these projects, it is difficult for project managers to meet project objectives (Collyer & Warren, 2009). A substantial amount of work has been done to overcome this problem by developing different tools and methods, yet often projects still cannot meet their targets (Acebes, Pajares, Galán, & López-Paredes, 2014; Y. Chen, Zhang, Liu, & Mo, 2012). In the construction industry, a rich body of research has emerged to develop frameworks and tools for project management. The majority of current tools do not consider the dynamic nature of projects (Franceschini, Maurizio, & Domenico, 2007). Therefore, in this research, a decision support framework has been developed for the planning phase of a project lifecycle. In addition, a navigational support system has been created for the execution phase of the project lifecycle to monitor and control project performance. This thesis focuses on creating two artefacts: [1] a decision support framework for planning construction projects under uncertainty, in particular, severe weather conditions, and [2] a decision support system as a generic engine for controlling and monitoring key performance indicators at project level. For validation, we applied both artefacts to the construction industry and selected construction projects as cases. It is important to estimate a project’s duration properly in the initial phase to avoid cost and time overruns. Thus, the developed decision support framework in this thesis fills the gap in the phase of project planning by estimating project duration and taking into account the effect of weather on project performance and construction activities. Initial project planning is essential, but it is important to monitor and control the project to bring the project back on track if it veers off from the desired performance. Hence, project managers are keen to know the position of project performance with respect to the agreed criteria and what action to take to bring the project back on track. Thus, a decision support system called Navigational Support System (NSS) has been created to monitor and control project performance among multiple key performance indicators. This research consists of three original papers. Paper I provides a comprehensive review of the literature on the possible causes of delays, the problems with current methods and tools in construction projects in estimating project duration. This paper fills a gap in the literature by proposing a decision support framework to estimate project performance and duration with respect to weather, and presents a model developed through the proposed framework and validated in a real-case construction project. Paper II provides a comprehensive review of literature on the problems of existing performance measurement tools. A conceptual framework of the Navigational Support System (NSS) (Marzoughi & Arthanari, 2016a) based on the idea of navigating in benchmark space, introduced by Arthanari (2010), and the architecture of NSS is proposed. In addition, this paper illustrates the NSS using a case from interior design projects. Finally, Paper III illustrates the implementation of the generic engine proposed in Paper II for further validation in a real-life construction project. In this research, different methodologies have been used to validate both the decision support framework and NSS. In Paper I, multiple methodologies are used to integrate five modules (expert knowledge module, filtration module, multicriteria decision-making module, forecasting module and estimation module) to estimate the duration of construction project activities. Moreover, the techniques applied to integrate weather related variables in the process of estimating the duration of activities affected by weather, such as multivariate data analysis methods including principal component analysis, time series model building approaches, multi-criteria decision-making tools, non-linear multiple regression, and qualitative and quantitative data collection methods are introduced. In Paper II, a Navigational Support System (NSS) is created as a generic engine using design science research methodology. Multivariate statistical techniques and dynamic decision-making techniques were integrated to create the NSS. In Paper III, the NSS has been implemented in construction projects for validating created artefacts. Finally, the efficacy, validity and ease of use of the NSS are evaluated through applying the NSS in a real-life construction project.