Scenario‐Driven Innovation: Identifying Technological Opportunities Within Sustainable Business Models

ABSTRACT With the advancement of the digital revolution, application scenarios are becoming increasingly complex and diverse. Accurately identifying technological opportunities (TOs) driven by user needs within these scenarios remains a significant challenge for enterprises, while existing theories and practices often lag behind. To address this gap, this study proposes a comprehensive framework for identifying and evaluating TOs based on scenario demands. The framework leverages text mining techniques to analyze scenario demands in depth and employs cosine similarity to quantify the extent to which these needs are satisfied. Additionally, generative topographic mapping (GTM) is used to construct patent maps, facilitating the identification of potential technological opportunities (PTOs). To evaluate the viability of transforming PTOs into actionable TOs, system dynamics (SD) simulations are applied to model sustainable business scenarios. The effectiveness of the framework is demonstrated through a case study on insulated gate bipolar transistors (IGBTs). Results indicate that the proposed approach enhances the accuracy of technological opportunity identification (TOI) and provides both theoretical and practical guidance for enterprises seeking to strategically align their technological development with evolving scenario demands.