Innovation in grassroots government governance is a vital measure for advancing the construction of the national governance system. From the "Technology-Organization-Environment" perspective, this study integrates multiple conditional variables and employs the dynamic QCA method to analyze data from 92 typical regions in China, so as to explore the key factors and driving paths influencing innovation in grassroots government governance. The study reveals that innovation in grassroots government governance is driven by the synergy of multiple factors; there are three types of paths to enhance the effectiveness of such innovation, namely the "Environment-Driven Mobilization Type", "Collaborative Multi-Driven Type" and "Technology-Environment Dual-Driven Type". Meanwhile, incentive mobilization, public demand, horizontal learning and economic development are the four key factors affecting innovation in grassroots government governance. Furthermore, the effective connection between the endogenous driving mechanism composed of incentive mobilization and public demand, and the external resource linkage mechanism formed by horizontal learning and economic development, serves as the key to improving the effectiveness of innovation in grassroots government governance. Therefore, grassroots governments need to consider the key factors of local innovation from a configurational thinking perspective, further explore the synergy among factors, and develop a governance innovation path that conforms to practical realities.