Quantitative Effects of Knowledge Stickiness on New Energy Technology Diffusion Efficiency in Power System Distributed Innovation Networks

Against the backdrop of continuously increasing renewable energy penetration, enterprises within the power system have formed highly distributed collaborative innovation networks in wind power, photovoltaics, and energy storage. However, knowledge stickiness resulting from complex knowledge structures and dispersed organizational boundaries significantly impedes technology diffusion efficiency.To quantify this impact, this study constructs a distributed innovation network comprising 96 nodes and 1,243 collaborative links based on joint patent, cooperative R&D, and technology licensing data from 96 power equipment and new energy enterprises between 2010 and 2023. Knowledge distance between enterprises is calculated using technology classification codes and patent citation information, thereby constructing a knowledge stickiness index.By measuring diffusion trajectories across 14 specialized new energy technology domains, diffusion efficiency is characterized using weighted shortest paths, average diffusion strides, and diffusion coverage rates. A panel regression model and spatial lag model are established, incorporating knowledge stickiness indices, network centrality, structural hole constraints, and firm absorption capacity.Empirical results indicate that a 0.1-unit increase in the knowledge stickiness index raises the average diffusion stringency of new energy technologies by approximately 7.4% and reduces the three-year diffusion coverage rate by about 5.8%, with the model's overall explanatory power ranging between 0.42 and 0.57.Leading power enterprises with high network intermediary centrality partially offset the adverse effects of knowledge stickiness, achieving diffusion efficiency approximately 12–15% higher than peripheral firms within their technological sub-networks. This study quantifies the impact of knowledge stickiness within distributed innovation networks in power systems, providing empirical foundations for designing collaborative promotion strategies for new energy technologies and cultivating critical nodes.