A study on the impact of entrepreneurial bricolage on enterprise performance management using the BPNN-DEMATEL method and social network analysis

With the advancement of artificial intelligence (AI), intelligent methods have become increasingly important for optimizing enterprise development strategies. This study applies the Back Propagation Neural Network-Decision Making Trial and Evaluation Laboratory (BPNN-DEMATEL) method and social network analysis to improve strategic decision-making for emerging enterprises. First, the BPNN-DEMATEL method is developed based on Back Propagation Neural Network (BPNN) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL). Then, it is refined using insights from social network analysis. Finally, the model is evaluated to assess its effectiveness in analyzing performance management strategies. Results indicate that the BPNN-DEMATEL model improves calculation accuracy by approximately 23 %–47 % and reduces reaction time by 20 %–50 % compared to existing models. After optimization, integrating social network analysis further enhances accuracy, increasing it by 38 %–70 %. Additionally, the model effectively examines the impact of entrepreneurial bricolage on performance management, providing insights that support new venture development. These findings contribute to the optimization and practical application of AI in enterprise strategy, offering both technical and theoretical foundations for business growth in the digital era.