Assessment of Science and Technology Innovation Capability of Digital Creative Industries Based on Empirical Analysis of Inputs and Outputs

Starting from the perspective of input and output, this paper builds up the assessment index system of scientific and technological innovation capacity of digital creative industry, covering 11 indicators, such as R&D cost input, R&D personnel equivalent for the whole year, etc. The correlation matrix is constructed using the factor analysis method. The factor analysis method is used to construct the correlation matrix, extract the common factor of each influencing factor indicator of scientific and technological innovation ability, and determine the number and specific content of the common factor. Using the common factors as input data and output data, a three-stage DEA model is proposed to measure the efficiency of the digital creative industry using the EBM model in the first stage, while in the second stage, the SFA regression is used to regress the slack variables in the first stage, and finally in the third stage, the influence of the environmental factors and stochastic factors is eliminated, and the efficiency of the decision-making units is measured again. Through the factor analysis method, this paper identifies four public factors, which are F1 capital structure, F2 industry competition, F3 investment heat, and F4 innovation strength. Through the three-stage DEA analysis, it can be learned that the main reason for the ineffective DEA of the digital cultural and creative content production industry, the lower comprehensive efficiency of the design service industry, the ineffective technical efficiency of the digital creativity and fusion service industry, and the lower value of the comprehensive efficiency of the digital content processing industry is the scale factor.