A Stochastic Decision-Support Framework for Exploring Strategic Pathways in 3D Concrete Printing
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Date
2024-09-04
Publication Type
Working Paper
ETH Bibliography
yes
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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.
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Publication status
published
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Book title
Journal / series
Volume
Pages / Article No.
Publisher
Social Science Research Network
Event
Edition / version
v1
Methods
Software
Geographic location
Date collected
Date created
Subject
Probability Distribution; Global Sensitivity Analysis; Uncertainty; Industrial Economics
Organisational unit
09624 - Hall, Daniel M. (ehemalig) / Hall, Daniel M. (former)
02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
Notes
Preprint
Funding
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