A Deep Learning-Based Assessment of the Synergy Between New Energy Policies and New Quality Productive Forces: An Integrated Goal-Instrument-Value Framework for Sustainable Development

Abstract

China has shifted from a stage of rapid growth to a stage of high-quality development. This highlights the critical need for policy frameworks that synergistically align technological innovation with sustainable development. To address the research gap in systematically assessing the collaboration between New Energy Industry (NEI) policies and New Quality Productive Forces (NQPF), this study proposes a three-dimensional “Goal-Instrument-Value” framework. Methodologically, we employ a combination of deep learning models (including LDA topic modeling, LSTM networks, and the Soft EDA algorithm) and policy quantification methods, analyzing 135 NQPF policies and nearly 800 NEI policies. The findings reveal a significant and strengthening synergy between the two policy domains. Notably, a misalignment exists in the goal dimension, where the weight of science and technology in NEI policies remains modest at 20%, indicating substantial potential for enhancement. In the instrument dimension, there is a predominant reliance on economically driven instruments, along with a notable underutilization of environmental instruments. Nevertheless, the overall synergy in policy value, as measured by a specialized New-Force Dictionary and the BM25 model, exhibits a consistent upward trend. Based on these findings, we recommend strengthening investment in NEI technology R&D, increasing the deployment of environment-oriented policy instruments, and establishing a cross-departmental policy synergy mechanism. These measures are crucial to fully harness the synergistic potential of NEI and NQPF policies for accelerating China’s green industrial transformation and achieving its sustainable development goals.