A digital Technology–Cultural resource strategy to drive innovation in cultural industries: A dynamic analysis based on machine learning

Abstract

With the gradual maturing of digital technology, the innovation strategy of ‘technology + culture’ is becoming increasingly significant for the sustainable development of cultural industries. This paper takes cultural industries in China's 31 provinces and municipalities in 2019 as a research sample and seeks to explore the multi-dimensional and periodical evolution relationship between digital technology, cultural resources, and innovation in cultural industries by drawing on machine learning algorithms and ergodic theory. The following conclusions are obtained. Firstly, the relationship between digital technology and cultural resources and their impact on the innovation of cultural industries is found to be nonlinear, which is a dynamic evolution process. Secondly, the impact of cultural resources on cultural industry innovation is not completely positively correlated, and the impact on technological innovation is more like an inverted U-shaped curve with a rising, peak, and declining period; the impact on content innovation, meanwhile, is similar to the ferment and take-off stages in the S-curve of innovation. And digital technology plays a significant role in promoting innovation, and is, especially in technological innovation, more like an ascending step from quantitative changes to qualitative change. Thirdly, digital technology and cultural resources are found to play different roles in the different stages of innovative development. Cultural resources are the basic factor and digital technology is the incentive factor.