Designing Optimal Government–Contractor Subsidy Policy for Promoting Modular Construction: Bilevel Stochastic Program

Modular construction (MC) is an advanced construction method that offers great economic, social, and environmental advantages over the cast-in-situ method, but the adoption rate of MC is low in practice. Government promotional policies are recognized as effective strategies to incentivize the use of MC modules (MCMs) by contractors. However, current studies devoted to the government subsidy problem are designed based on deterministic parameters. In real-life scenarios, the selling price of MCMs, the cost of cast-in-situ construction, the maximum quantity of MCMs supplied, and the construction work of future projects have many uncertainties. Neglecting these factors can result in suboptimal subsidy plans for governments and further influence the supply chain related decisions made by contractors. This study contributes to the literature by designing an optimal government subsidy allocation strategy to promote the adoption of MC technique. An innovative bilevel stochastic program was formulated that incorporates price and quantity uncertainty, and an exact solution method was developed for problem-solving. The proposed optimal subsidy allocation policy was validated using a Hong Kong case study. The results show that our plan is expected to increase the adoption rate of MC in Hong Kong to 52.3%, thereby justifying the practical contributions of our well-designed subsidy policy. Furthermore, results show that the consideration of real-life uncertainties can result in a noteworthy 38% improvement in the adoption of MC compared with the traditional deterministic method, thereby justifying the methodological contributions of this study. Through sensitivity analysis, useful managerial insights related to subsidy budget are provided for policymakers.