Regional S&T planning and green generic technologies: A spatial differences-in-difference analysis

Green Generic Technologies (GGTs) are pivotal for large-scale and sustainable green transitions. Existing literature mainly focuses on policies that induce ordinary green technologies, with little attention given to GGTs, which face unique challenges like technological lock-in and pervasive spillover dilemmas. Therefore, this paper aims to explore whether regional S&T planning (RSTP), as a strategic policy framework, can promote GGTs, examining both direct and spillover effects across geographical and innovation networks. This study constructs a panel dataset of 284 cities in China from 2008 to 2020 and applies a spatial differences-in-difference (SDID) model to estimate the impacts of RSTP on GGTs. This paper uses the generalizability index of patent citations to measure GGTs, exploring the spillover effects across spatial neighbors and innovation-network collaborators. Specifically, this study adopts natural language processing (NLP) methods to extract two distinct RSTP policy goals—anticipatory and obligatory—and investigates the heterogeneous effects resulting from these goals. The results show that RSTP positively impacts local GGTs' development but has negative geographical spillovers on neighboring cities. Additionally, RSTP's anticipatory goals positively influence both GGTs and innovation-network spillovers. In contrast, its obligatory goals yield adverse effects, likely due to policy myopia, their coercive nature, and limited flexibility in fostering dynamic interactions and coordination. This study contributes to the literature on green and generic technologies, particularly regarding the policy mechanisms that drive regional green transitions. It also provides important implications for emerging economies seeking large-scale green transformation and industrial upgrading through strategic innovation governance.