Optimisation Framework for Enhancing Construction Productivity of Medium-Level Construction Projects (Kenyan Counties Perspective)
Abstract
Extensive studies have been conducted on optimisation frameworks for construction projects to determine project productivity, albeit biased towards the BIM Principle, Architectural, Engineering, and Construction (AEC) Models, and those that focus on large and complex projects. The objective of this study was, therefore, to develop an integrated (Preconstruction & construction factors) optimisation framework for medium-level projects. Key parameters considered as independent variables were the cost of construction, Project management techniques, Pre-project planning and Lean technology. Project completion time, quality, and costs were listed as aspects of the dependent variable (Project productivity). Structured questionnaires were administered to six professional subgroups and one subgroup of key stakeholders as the study participants. These comprised landlords/homeowners, architects, structural engineers, quantity surveyors, building contractors, construction project managers and Ministry of Housing and Infrastructure officials. Descriptive and diagnostic research methods were used to analyse data. The results on the performance of the framework based on multivariate regression analysis show that there is a strong relationship between performance (Y) and variable factors X1(Cost of construction), X2(Project management techniques), X3(Pre-project planning), and X4(Lean technology). On the importance of the independent variables, Project management techniques took the lead, followed by cost, pre-project planning & lean technology. The results on the performance of the framework based on case studies show the capacity of the framework to optimise by as much as 23.3% & 24.9% on Case studies 1 &2, respectively; however, the percentages should be unique for each specific project. The model was overwhelmingly endorsed by key stakeholders through a validation process over its Key Performance Indicators, adequacy in measuring &scoring indicators and its ability to determine project productivity with a mean rating of 8.63± 0.890 on a scale out of 10. Further research is recommended on the models’ applicability to small-level construction & civil engineering projects & new/unique projects.
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