Discovery of Potential Technological Opportunities in the Green Building Field from a Technology Convergence Perspective: A Two-Stage Prediction Approach Using Interpretable Machine Learning

As one of the world's largest energy consumers and carbon emitters, the construction industry plays a pivotal role in advancing global sustainability. Promoting technological innovation is essential for the industry's green transformation while maintaining development goals. However, current research reveals a significant gap in identifying and assessing potential technological innovation opportunities within the green construction sector, resulting in a lack of decision-making guidance for governments and innovators during the research and development phase. Recognizing this, the study proposes a two stage technology opportunity prediction approach based on interpretable machine learning from the perspective of technology convergence. Unlike traditional methods, this approach estimates the likelihood of emerging technological opportunities and anticipates the impact of convergence events. By examining 600,442 patent documents related to green technologies and construction, the study forecasts potential technology convergence innovations and investigates the factors driving these trends. The findings provide critical decision support for policymakers and organizations to develop strategies for green technology innovation.