Dynamic evaluation framework shows positive correlation between human capital development and regional growth in Northeast China, suggesting effective policy interventions.
This study develops a dynamic evaluation framework to analyze the interaction between digital and traditional industries in Northeast China from temporal and regional perspectives. Using a 24-year dataset (2000-2024) across five major Chinese economic regions, the framework integrates coupling coordination modeling, system dynamics, and time-series forecasting with SARIMA and LSTM models. Results indicate that digital investment and human capital development significantly enhance industrial performance, with strong positive correlations between coordination and regional growth (r = 0.89, p < 0.01). The LSTM model demonstrates superior adaptability to nonlinear fluctuations compared with SARIMA, achieving a 25% reduction in forecast error. Evidence from Liaoning Province validates that targeted policy interventions - particularly demonstration zone strategies - can accelerate coordination between digital and traditional sectors. The framework provides methodological and empirical foundations for regional development strategies in transitional economies.
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Chen et al. (2026) studied this question.
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