Coupling of Traditional Handicraft Skills Intangible Cultural Heritage and Cultural Industry Agglomeration under the Background of Big Data

Abstract

The transmission of traditional folk craft skills and educational innovation are key to achieving the living transmission of cultural heritage. This paper takes China’s 31 provinces as its research subjects and constructs an evaluation index for the competitiveness of China’s cultural heritage. It comprehensively employs the Analytic Hierarchy Process (AHP) and the Entropy Weighting Method to determine the weights of the indicators. This approach effectively integrates subjective expert experience with objective data, thereby avoiding the biases associated with single-weight determination methods. A BP neural network-based evaluation model for China’s cultural heritage competitiveness was established. The model was trained using 2014 data on China’s cultural heritage competitiveness, generating evaluation results for each province and overcoming the limitations of traditional linear evaluation methods. Empirical results indicate that the model exhibits good fit, with a maximum error of only 0.0006 in the test sample. Between 2014 and 2019, the overall level of cultural heritage competitiveness across Chinese provinces improved, with the mean rising from 0.1744 to 0.2393; however, the disparity in development levels of cultural heritage competitiveness among provinces remains significant. Therefore, this paper proposes specific strategies in areas such as digital technology capabilities, distinctive development advantages, and educational innovation, providing methodological support and practical strategies for the transmission of traditional folk craft skills and educational innovation.