The Cost Drivers of Infrastructure Projects: Definition, Classification, and Conceptualization

Abstract

Reducing cost is a critical objective for project teams. However, unlike the research on topics such as cost overruns, cost reduction literature is limited. Previous studies have primarily examined cost estimation/reduction models or high-level cost reduction strategies. Therefore, it is necessary to identify specific actions that project teams can take to reduce cost. By focusing on the "cost drivers" of infrastructure projects, researchers have a practically relevant lens through which cost reduction can be promoted and studied. Thus, this integrative literature review establishes a foundation for infrastructure project cost drivers knowledge, addressing three research questions revolving around deriving a definition, classification scheme, and conceptual framework of cost drivers. This paper first produces a definition of cost drivers by critically analysing cost drivers concepts/perspectives and existing definitions. Second, cost drivers were drawn from relevant articles and classified to produce a taxonomy of 14 key cost drivers. Third, a conceptual framework (two-by-two matrix) of cost driver types was developed to acknowledge the influence project teams can have. Finally, a research agenda proposes further investigation in cost drivers/reduction research regarding each cost driver, apt research methods, and necessary project contexts. This paper's theoretical contribution is a deepening of infrastructure project cost drivers knowledge using a definition, taxonomy, and conceptual framework. The practical contribution is a deepened awareness of the key opportunities forand threats tocost reduction for project teams, as well as a knowledge of those cost drivers that they actually have an influence over, i.e., to reduce their project's cost.Popular topics in the realm of cost reduction in project/construction management literature tend to be primarily focused on reducing cost overruns or cost estimation inaccuracy, through analysing either the human-based determinants (e.g.