Purpose: In the digital economy era, digital platforms are vital infrastructure for innovation subjects to perform digital innovation activities. Achieving efficient and smooth knowledge transfer between innovation subjects through digital platforms has become a novel research subject. This study aims to examine the knowledge transfer mechanism of digital platforms in the digital innovation ecosystem through modeling and simulation to offer a theoretical basis for digital innovation subjects to acquire digital value through knowledge-sharing and thus augment their competitive advantage.Design/methodology/approach: This study explores the optimal symbiotic interaction rate between different users based on the classic susceptible-infected-removed (SIR) model. Additionally, it constructs a knowledge transfer mechanism model for digital platforms in the digital innovation ecosystem by combining the theories of communication dynamics and symbiosis. Finally, Matrix Laboratory (MATLAB) software is used for the model and numerical simulation.Findings: The results demonstrate that (1) the evolutionary path of the symbiotic model is key to digital platforms' knowledge transfer in the digital innovation ecosystem. In the symbiotic model, the knowledge transfer path of digital platforms is “independent symbiosis—biased symbiosis (user benefit)—reciprocal symbiosis,” aligning with the overall interests of the digital innovation ecosystem. (2) Digital platforms' knowledge transfer effects within the digital innovation ecosystem show significant differences. The most effective knowledge transfer model for digital platforms is reciprocal symbiosis, whereas the least effective is parochial symbiosis (platform benefit). (3) The symbiotic rate has a significant positive impact on the evolutionary dynamics of knowledge transfer on digital platforms, especially in the reciprocal symbiosis model.Originality/value: This study's results aid digital innovators in achieving efficient knowledge transfer through digital platforms and identify how symbiotic relationships affect the knowledge transfer process across the ecosystem. Accordingly, the authors propose targeted recommendations to promote the efficiency of knowledge transfer on digital platforms.

Purpose: In the era of the digital economy, the digital innovation ecosystem is an important vehicle to alleviate enterprises' resource and capability constraints and thus improve their digital innovation performance. Embedding digital innovation ecosystems for survival and development opportunities has become a new strategic choice for enterprises. However, how digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises has not yet been fully revealed. This study examines whether digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises through ambidextrous capabilities (exploration and exploitation) and the moderating role of strategic flexibility. Design/methodology/approach: A field survey was conducted in China, collecting survey data from 578 complementary enterprises in advanced manufacturing industries embedded in digital innovation ecosystems. This study applies multiple regression analysis to verify the relevant hypotheses. Findings: The results confirmed that (1) digital innovation ecosystem embeddedness has a significant positive effect on complementary enterprises' digital innovation performance; (2) Ambidextrous capabilities play a partial mediating role in the relationship between digital innovation ecosystem embeddedness and complementary enterprises' digital innovation performance. (3) Strategic flexibility positively moderates the effect of digital innovation ecosystem embeddedness on ambidextrous capabilities and digital innovation performance. Practical implications: The findings, intended to guide enterprises that complement the digital innovation ecosystem to achieve digital innovation and performance improvement, highlight the importance of eco-embedded strategies, ambidextrous capabilities and strategic flexibility. Originality/value: The finding enriches antecedent research on digital innovation performance and provides practical insights for firms to embed themselves in digital innovation ecosystems to improve performance.

To foster the sustainable development of culture, particularly focusing on the preservation of cultural heritage, encompassing relics, intangible cultural heritage, and historical sites, China has launched a strategy for the digitalization of culture, with the goal of establishing a holistic national big data framework for cultural resources. To improve the efficiency of collaborative supply of cultural resource big data among various parties and to further advance the sustainable development of culture, this research has created a cooperative model that includes cultural institutions, a cultural resource big data service platform, and government participation. Our research findings, based on prospect theory and evolutionary game theory combined with Chinese practice, are presented below. (1) Various factors, including the coefficient of digital infrastructure empowerment, access charges for digital infrastructure, government penalties, and the probability of data leakage, have varying effects on the system in different states. (2) Once the industry has developed, the government can increase the impact of digital infrastructure empowerment to create stronger incentives, rather than relying solely on rewards or penalties. (3) When the value level of cultural resource big data is high, the benefit distribution coefficient does not affect the system evolution results. Finally, we offer practical insights for the government, cultural organizations, and cultural resource big data service platforms based on our research results. Our research offers Chinese insights for global cultural sustainable development.