The era of the digital economy has ushered in a new development opportunity for the energy industry, and the role of digitalization in the green and low-carbon transformation process of the energy industry has received increasing attention. Based on the panel data of 55 energy enterprises in China, this study explores the mechanism by which energy enterprises’ digital transformation impacts enterprise green innovation from the perspective of dynamic capability and adopts the double-fixed-effects regression model to empirically analyze the impact of energy enterprises’ digital transformation on enterprise green innovation. The study explores the mediating role of dynamic capability between energy enterprise digital transformation and enterprise green innovation and conducts heterogeneity analysis. The empirical results show that there is a significant positive correlation between the digital transformation level and the green innovation level of energy enterprises. The mechanism test shows that the digital transformation of energy enterprises can promote their green innovation ability by improving their dynamic capability. Heterogeneity analysis shows that the digital transformation of energy enterprises has a significant promotional effect on the green innovation of state-owned enterprises but has no significant effect on non-state-owned enterprises. The results of this study provide a reference for promoting the green development of enterprises, enhancing the green and low-carbon transformation of the energy industry and realizing the sustainable development of enterprises.

To improve and enhance the predictive ability of consumer purchasing behaviours on e-commerce platforms, a new method of predicting purchasing behaviour on e-commerce platforms is created in this paper. This study introduced the basic...

With the rapid development of video websites, copyright management and the protection of online movies are facing severe challenges. With the strengthening of intellectual property protection, copyright value management has become necessary for the transformation of copyright value, which is of great significance for the healthy development of the industry. Based on the current development status of China’s online movie offerings, online movies were collected from China’s three major video platforms between 2016 and 2018 as research objects, and a set of scientific and effective online movie copyright value assessment methods and systems are proposed through the fuzzy comprehensive evaluation method, analytic hierarchy process, Delphi method, and empirical research. In this study, using data collected through a questionnaire survey, a fuzzy evaluation method is applied to establish the evaluation index of the copyright value of online movies. Moreover, according to the Delphi method, expert suggestions are collected, the indexes are scientifically corrected in the market, and the weights of the copyright value evaluation index of online movies both before and after broadcasting are calculated using the analytic hierarchy process. On this basis, by applying big data analysis, the communication effect index, prebroadcast value score evaluation index, and postbroadcast value evaluation index are deeply analyzed, and the copyright value evaluation model of online movies both before and after broadcasting is established. Finally, based on market feedback data, the evaluation models are revised and empirically tested to verify the scientificity and rationality of the copyright evaluation method proposed in this study. The results show that the proposed methods and systems for evaluating the copyright value of online movies are scientific and effective. This study provides new insights for all types of movie and television production organizations and video playback platforms on how to design effective copyright value evaluation models and practice methods for online movies.

In the era of artificial intelligence (AI), cultural industries have introduced new development opportunities, and their global value chain (GVC) position is receiving more attention. This study uses panel data from global cross‐borders from 56 countries (regions) as the research sample to empirically analyze the impact of AI on improving the GVC position of cultural industries using the double fixed effects regression model and examines the heterogeneity effect. The results confirm that there is a significant positive correlation between AI and the GVC position of cultural industries. The mechanism test shows that AI impacts the division of labor position in the GVC of cultural industries mainly through technological innovation and the industrial structure. Heterogeneity analysis shows that AI has a significant effect on promoting the cultural industry’s GVC position in high‐income countries (regions) but it has no significant effect on low‐ and middle‐income countries (regions). The results of this study can provide a useful reference for improving the division of labor positions in the GVC and better promoting the development of cultural industries.

From the perspective of firm capability, this study explores the impact of digital intelligence transformation and management innovation on the performance and sustainable development of Chinese firms. On the basis of constructing an evaluation index system of firm digital intelligence transformation and management innovation, a comprehensive evaluation model of firm digital intelligence transformation and management innovation is constructed via the analytic network process (ANP) and fuzzy comprehensive evaluation method. Taking Chinese film and television firms as an example, this study selects 160 data samples from 85 firms and constructs a structural equation model to empirically analyze the impact of digital intelligence transformation and management innovation on the performance of firms. The study results show that, in the context of digitalization and intelligence, firm digital intelligence capability and dynamic capability have a significant positive effect on firm performance. Firm digital intelligence transformation and management innovation directly impact performance and can play a role through firm digital intelligence capability and dynamic capability as intermediaries, and the chain intermediary effect of digital intelligence capability and dynamic capability is significant. The research results show that firm digital intelligence and dynamic capabilities provide a functional path for firm digital intelligence transformation and management innovation to improve performance. Moreover, the innovative application of digital intelligence technology has an important impact on the sustainable development of firms. Digital transformation and management innovation can help firms enhance their ability to manage environmental uncertainties, improve firm performance and foster the achievement of sustainable development goals.

The aim of this study was to study the impact of artificial intelligence (AI) on enterprises in terms of strategy, technology, business operations, and organizational management. This study used grounded theory analysis to identify the influencing factors of AI technology application maturity in Chinese enterprises. Taking Chinese film and television enterprises as an example, this study constructed an AI technology application maturity evaluation index system for enterprises based on the analytic network process (ANP) and evaluated the application maturity of AI technology in enterprises in terms of enterprise strategy, technology, business operations, and organizational management. To comprehensively evaluate and empirically analyze the application maturity of enterprise AI technology, this study calculated the index weight based on the ANP, and combined it with the fuzzy comprehensive evaluation method to construct a comprehensive evaluation model. The research results showed that intelligence strategy was the element that was believed to be most affected by the maturity of enterprise AI technology. For technology, intelligence technology and equipment were the elements that were believed to be affected the most. For business operations, smart shooting was the element that was believed to be affected the most. With respect to organizational management, corporate culture was the element that was believed to be most affected. The results showed that the proposed methods for evaluating the application maturity of enterprise AI technology are scientific and effective. The results of this study provide a reference for promoting the application of AI, implementing the intelligence transformation, and enhancing the core competitiveness of enterprises.