A Stochastic Decision-Support Framework for Exploring Strategic Pathways in 3D Concrete Printing

Abstract

3D Concrete Printing (3DCP) promises significant gains through faster construction and reduced waste, yet its adoption is limited. Addressing economic uncertainty in new technologies, this study presents a three-stage stochastic framework using a case study company, focusing on software, hardware, and material innovation. Stage one quantifies unit cost uncertainties; stage two explores development options for strategic planning; stage three integrates investment costs for a cost-benefit analysis. Using the Resource-Based View (RBV), we show how firms can leverage technological, financial, and human resources to identify and evaluate opportunities. By combining RBV with Monte Carlo simulations and Simulation Decomposition (SimDec), we offer a decision-support toolkit for multivariate cost-benefit analyses essential for adopting new technologies. The findings are relevant to academics, researchers, and industry stakeholders and guide future research in sustainable construction.