Exploring technology opportunities with a deep learning-based clustering approach: the case of pyrolysis technology for recycling plastic wastes

With the rapidly changing business environment, the dynamic capability of an enterprise begins with sensing and grasping technology opportunities. Considering that the knowledge gaps between science and technology hinder the exploration of technology opportunities, previous studies proposed methods to extract technology opportunities by identifying the knowledge gaps between science and technology literature. This study improves upon previous methods for identifying knowledge fields contained in the literature by introducing a deep learning-based clustering approach. This study also proposes a way to reduce experts’ workloads in determining gaps in the field between science and technology literature. The key idea of the proposed method is to include technologies other than the technology in question. Additionally, pyrolysis technology can convert plastic wastes into useful materials and is considered a green technology. Therefore, this study applies our improved method to explore the technology opportunities of pyrolysis technology. The results show that our method can effectively identify technology opportunities. In the case of plastic wastes, the results show that recovering carbon fibers from plastic wastes and recycling metals from e-waste plastics are expected to be prevailing technological fields.