Comparison of Alberta Industrial and Pipeline Projects and US Projects Performance

Purpose The purpose of this paper is to understand the underlying logics applied by different project evaluation approaches and to propose an alternative research agenda. Design/methodology/approach This paper explores the project evaluation literature via conducting a qualitative research applying systematic literature review and thematic analysis. Findings The project evaluation literature has mainly concentrated on the objective aspects of project evaluation and overlooked the subjective aspects that reflect the temporal, dynamic, complex and subjective nature of today’s projects. The authors propose a meta-framework that helps project practitioners to select an appropriate project evaluation criterion for their projects by considering the strengths and limitations of their preferred project evaluation model as well as making project evaluators aware of the underlying logics associated to diverse project evaluation approaches. Research limitations/implications This study suggests that new conceptual approaches to deal with some of the major challenges in the project evaluation field. Practice-based views, narrative analysis and actor-network theory are likely to be useful tools to better understand and cope with the projects’ uncertainty and complexity. Practical implications The findings of this research assist project management practitioners and particularly project evaluators to enhance their understanding of the subjectivity, complexity and dynamics of current projects. To increase the reflexivity and resilience of project evaluation practice, this study also proposes new directions to apply different criteria, sub-criteria and indicators to the evaluation practice. Originality/value The originality of this study relies on transcending the conventional objective and rational approaches prevailing in current project evaluation practices. It proposes a research agenda that pave the way to address the shortcomings of conventional project evaluation practice.

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Implementation of the Neural Networks for Improving the Projects’ Performance of Steel Structure Projects

Elhegazy

Badra

Haggag

et al. 2021

J. Ind. Intg. Mgmt.

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This paper aims at developing a model to measure and evaluate the performance and productivity of the construction of steel structure projects (SSPs). Practitioners and experts comprising a statistically representative sample were invited to participate in a structured questionnaire survey to achieve the objective. The questionnaire consisted of 17 factors that were classified under the following four primary categories, with terms such as feasibility study stage, planning stage, design, and engineering stage, and construction stage. Artificial neural networks (ANNs) were used for designing a model on MATLAB for measuring and evaluating the projects’ performance of the Construction of SSP based on the 14 factors that affect the steel structure process. The results suggest that the proposed ANN model for SSP can produce measures and evaluate the projects’ performance quickly and accurately when actual data is available for model training. The user can enter the values of main factors that affect their projects’ performance to produce an accurate output of the evaluation for the projects’ performance and productivity. The construction industry can use the findings of this paper as a basis for improving the projects’ performance of the construction for SSP.

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Comparison of Alberta Industrial and Pipeline Projects and US Projects Performance

Cited by 3 publications

References 5 publications

Feasibility Assessment and Enhancement of TOF-Based UWB RTLS for Non-Line-of-Sight Conditions on Construction Sites

Feasibility Assessment and Enhancement of TOF-Based UWB RTLS for Non-Line-of-Sight Conditions on Construction Sites

Understanding project evaluation – a review and reconceptualization

Implementation of the Neural Networks for Improving the Projects’ Performance of Steel Structure Projects

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