Machine learning and technological mediation in cost estimation practice Online publication date: Tue, 25-Jan-2022
by Hans Voordijk; Faridaddin Vahdatikhaki; Erik Matel
International Journal of Management Concepts and Philosophy (IJMCP), Vol. 15, No. 1, 2022
Abstract: Due to their complex architecture, methods based on machine learning (ML) lack transparency on how inputs are transformed into outputs. With the growing influence of ML in construction cost estimation, analysing this transformation that is in a great part unperceivable by humans becomes increasingly important. The ways in which technology transforms inputs into outputs are also the focus of the philosophy of technological mediation. The purpose of this study is to understand the mediating role that ML plays in construction cost estimation. An existing method for developing a ML cost estimation model for the tendering phase in construction engineering services was chosen as the subject of an exploratory case study. By applying concepts of technological intentionality, case-based reasoning and digital materials, the kind of technological mediation that ML technology provides between users of this technology and cost estimation in construction practice is discussed.
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