This thesis studies the integration of sustainability selection criteria into construction procurement. Using an Agent-Based Model (ABM), the study simulates single stage sealed tender processes also called first-price sealed bid auctions to analyze how different sustainability scoring rules influence bid pricing, contractor participation, and market competitiveness. The research examines the current state of the art of modelling in construction procurement and studies current practices for integrating environmental sustainability into public and private procurement processes.

The resulting model is grounded in utility theory and incorporates empirical data from construction management literature to model contractor decision-making under various sustainability-driven auction scenarios. The study evaluates the most common current sustainability scoring rules in practice—minimum requirements, flat discounts, and scaling discounts—and compares their effectiveness in promoting sustainability while maintaining market competitiveness.

Applying the model, the study simulates policy scenarios for implementing sustainability criteria and scoring rules over multiple tenders. These scenarios are designed to optimize for maximum sustainability investment from contractors while ensuring equitable access to sustainable construction opportunities. The findings suggest that an adaptive approach, combining minimum requirements and scaling discounts over time, is optimal for achieving sustainability goals in the construction sector.

The model is validated through pattern-oriented modeling (POM), and the findings are further scrutinized by expert interviews for alignment and use in real-world practices. This research serves as a proof of concept for applying auction theory, which has seen use in other sectors, to improve the impact of sustainability criteria in construction procurement. The study hopes to provides a step toward designing more effective procurement strategies that align market behavior with environmental goals.