Abstract

Abstract From the sectoral systems of innovation perspective, the windows of opportunity (hereafter referred to as WoOs) for industrial latecomers to catch-up could be opened up through abrupt changes in the technological, market, and institutional dimensions. Existing literature discusses different dimensional changes in isolation. Nevertheless, for green industries, the systemic interplay of these dimensions is of key importance; yet few studies have probed into this. These limitations in the literature are largely rooted in the lack of novel methods to detect and specify these abrupt changes, especially in a quantitative way. This paper, therefore, proposes a framework combining natural language processing methods with experts’ knowledge to detect these abrupt changes—named turbulences—by using multi-source heterogeneous data, in order to better identify the co-occurrences and interactions of turbulences across the technological, market, and institutional dimensions that have a high probability to open up WoOs. We apply this framework to analyze China’s hydropower sector as a case study. The hydropower sector is considered a “green” energy sector, in which China, as this study finds, has recently gained technological leadership. By analyzing the interactions between these multiple dimensions of WoOs, we discover that institutional turbulences proactively intertwine with other turbulences, and collectively form Green WoOs for the successful catch-up of China’s hydropower sector.

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