The performance evaluation of global expansion strategies of Chinese law firms based on the improved back propagation prediction model

This study aims to enhance the scientific nature of performance management and the efficiency of strategic execution for Chinese law firms in global expansion.The study employs the balanced scorecard to establish a performance indicator system spanning seven dimensions.These dimensions include finance, customers, internal processes, learning and growth, industry scale and influence, local development foundation, and market potential, enabling systematic and diversified performance evaluation.Second, by combining trend decomposition and fluctuation modeling, the trend-seasonal (TS)-Back Propagation (BP) performance prediction model is implemented to enhance the predictive ability of the performance of law firms' global expansion strategies.Experimental results show that compared with the traditional BP model and other six mainstream prediction models, the TS-BP model exhibits higher prediction accuracy and stability in six evaluation indicators.The TS-BP model demonstrates excellent generalization ability and stability across different city levels.Especially in first-tier cities, the mean squared error of the TS-BP model is below 0.01, far superior to other models.Meanwhile, the error in third-tier cities is still controlled at a low level, verifying the model's practical value and adaptability.This study integrates strategic management with artificial intelligence technology to enhance law firms' performance prediction capabilities.The study seeks to provide crucial data support and decision-making references for law firms to formulate precise international development strategies, optimize resource allocation, and adjust business approaches.