In the context of media convergence, it is of great significance to study and discuss the intelligent digital media asset management model and build a digital media asset management ecosystem model to carry out effective digital media asset management for media organizations and promote the value creation of digital media content assets. Based on the business ecosystem, this study adopts a system dynamics approach to construct a system dynamics model through theoretical research and simulation analysis. By studying the positioning of intelligent digital media asset management and service patterns, the basic framework of digital media asset management ecosystems is proposed. To explore the interaction between different factors, the system dynamics model of value creation in digital media asset management ecosystems is built in this paper. This study provides new insights for media organizations on building an intelligent digital media asset management model and promoting the development and utilization of media content resources.

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 principles of the XGBoost algorithm, analysed the historical data of an e-commerce platform, pre-processed the original data and constructed an e-commerce platform consumer purchase prediction model based on the XGBoost algorithm. By using the traditional random forest algorithm for comparative analysis, the K-fold cross-validation method was further used, combined with model performance indicators such as accuracy rate, precision rate, recall rate and F1-score to evaluate the classification accuracy of the model. The characteristics of the importance of the results were found through visual analysis. The results indicated that using the XGBoost algorithm to predict the purchasing behaviours of e-commerce platform consumers can improve the performance of the method and obtain a better prediction effect. This study provides a reference for improving the accuracy of e-commerce platform consumers' purchasing behaviours prediction, and has important practical significance for the efficient operation of e-commerce platforms.

The trading platform of digital media content products has the characteristics of bilateral markets, which could connect the providers and demanders through the platform, so that to provide trading services for them and earn corresponding benefit. The thesis studies the bilateral market structure, characteristic, and pricing-influencing elements of digital media content product trading platform, and on this basis puts forward pricing strategies of bilateral trading platform of digital media content products in user-gathering stage and stable-developing stage.

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.

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