With the increasing demand for digital innovation scenarios, it is important to complement and improve the policy system for the governance of digital innovation activities. Combining the previous research results on the analysis of antecedent variables, basic effects and potential mechanisms of digital innovation, and based on the citation analysis of digital innovation topics based on the Citespace method, we find that in the past two decades, the topic of digital innovation policy research has gradually shifted from focusing on “constraining policies to control negative impacts” to focusing on “constructive policies to expand positive impacts”. The digital transformation has brought about multidimensional and profound impacts on the governance of innovation activities, and it is necessary to accelerate the theoretical research on policy frameworks for the new areas of technology socialization effects. Summarizing some of the important progresses, we propose a policy framework covering three aspects: policy needs for sustainable transformation of digital innovation, policy orientation and policy dimensions for sustainable transformation of digital innovation, creating R&D opportunities, optimizing R&D organization, building ecological advantages, improving R&D governance, knowledge creation, enabling applications, collaborative promotion, standardizing management, national digital innovation system, digital innovation foundation, data governance capacity, digital security and other aspects of the conceptual framework of the basic policies for sustainable transformation of digital innovation. The research viewpoints and conclusions are of theoretical reference value for further research on key policy conditions for digital innovation, major policy impact effects and digital innovation governance mechanisms.

The fusion of large group decision-making preferences is generally based on hard constraints, and the general low-consensus heterogeneous preference interaction situation of weak relationship decision-making under soft constraints has not been investigated. This study puts forward the preference connotation structure and preference attributes of the intertemporal decision-making of weak relationships groups, objective preference comparison standards between individuals, preference interaction neighborhoods between individuals, preference learning adjustment rules, and preference cycle interaction result evaluation connotations. On this basis, this research constructs a multistage and multiple-round intertemporal decision-making preference dynamic fusion theory and a method for weak relationship large groups. The simulation results verify and support the constructed preference fusion theory and method, indicating that a relatively rational interactive learning and adjustment process can improve the group decision-making performance of the key digital technology R&D team for offshore wind power project construction, operation, and maintenance and effectively improve the convergence level, convergence time, comprehensive decision-making benefits, and decision-making cognition. In the increasingly open large group intertemporal decision-making situation, these research viewpoints and conclusions will help to expand the strong relationship hypotheses of preference fusion in previous group decision-making research. The research opinions and conclusions supplement the theory and method of preference interaction fusion under soft constraints in large group decision-making.