Amid increasingly intense global technological competition, the importance of breakthrough technological innovation for China’s long-term competitive advantage and industrial transformation has been emphasized. How to promote such innovation through artificial intelligence (AI) in the digital era has become a key strategic issue for enterprises. Based on socio-technical system theory and dynamic capability theory, a theoretical model of “AI capability-knowledge dynamic capability-breakthrough technological innovation” was developed to examine the internal mechanisms. Questionnaire data were collected from 312 enterprises to conduct empirical analysis. The findings indicate that AI capability significantly promotes breakthrough technological innovation. Knowledge dynamic capability plays a mediating role, especially in the dimensions of knowledge creation and knowledge integration, where strong positive effects were observed. Furthermore, a data-driven culture serves as a moderating factor, strengthening the influence of AI capability on breakthrough innovation. These results contribute to a deeper understanding of how breakthrough technological innovation can be achieved in the digital era through AI.

With the rise of the post-Schumpeterian innovation paradigm, manufacturer-user (MU) collaborative innovation has become a crucial means of promoting technological innovation and achievement transformation. A theoretical framework for MU collaborative innovation was constructed by reviewing the theoretical underpinnings of MU collaborative innovation and clarifying the distinctions between MU collaborative innovation and single-subject innovation. A theoretical framework encompassing roles, modes, processes, mechanisms, and commercialization of MU collaborative innovation was proposed. MU collaborative roles and modes are identified as drivers of the MU collaborative innovation process, with manufacturers and users taking on different roles and utilizing distinct modes in the collaborative innovation process. A MU collaborative mechanism was constructed from the four perspectives of strategy, knowledge, organization, and digital technology. MU collaborative commercialization was explored in terms of heterogeneous commercialization needs, opportunities for use and verification, and the initial adoption and diffusion of innovative achievements. Three future research directions are proposed: user-led MU collaborative innovation, AI-empowered MU collaborative innovation, and MU collaborative innovation in ecosystem contexts. New perspectives and insights are provided for academia and industry through the construction of the theoretical framework of MU collaborative innovation and the proposal of future research directions.

In the dynamic environment, top managers comprehensively scan, capture, and evaluate the internal and external environment to stimulate cross-boundary innovation. In this process, how executive alertness towards resources and opportunities plays a role deserves exploration. Based on the “awareness-motivation-capability (AMC)” framework of dynamic competition theory, the relationship between executive alertness and cross-boundary innovation was examined, as well as the moderating effect of performance shortfalls and dynamic capability. Using the data of listed companies from 2012 to 2023 in Shanghai and Shenzhen Stock Exchanges, the results indicate that both resource alertness and opportunity alertness have a positive effect on cross-boundary innovation. Furthermore, performance shortfalls and dynamic capability strengthen the relationship between executive alertness and cross-boundary innovation. The heterogeneity test result shows that there are systematic differences in the driving effect of executive alertness on cross-boundary innovation among enterprises of different technological attributes and property rights. The research results expand the research on the antecedents of cross-boundary innovation, and provide practical inspiration for cross-boundary innovation.

Collaborative innovation platform is an effective carrier for gathering and integrating innovation resources, and knowledge flow has an important impact on the orderly operation of collaborative innovation platform. Therefore, it is necessary to carry out effective governance of the platform to guarantee the smooth flow of knowledge, so as to promote the sustainable development of the collaborative innovation platform. Based on this, the system dynamics model was used to analyze the impact of collaborative innovation platform governance mechanism on knowledge flow. First, the knowledge flow process of collaborative innovation platform was analyzed and the connotation of governance mechanism of collaborative innovation platform was clarified. Secondly, the impact of the governance mechanism of collaborative innovation platform on knowledge flow was analyzed, and then a theoretical model was constructed. Finally, system dynamics was applied to construct a system dynamics model of the influence of collaborative innovation platform governance mechanism on knowledge flow, and the model was simulated with by Vensim PLE to reveal the role of collaborative innovation platform governance mechanism on knowledge flow. The results show that both contract and relationship governance mechanisms have a positive impact on the knowledge flow of collaborative platforms, with the relational governance mechanism playing a stronger role, and the simultaneous use of both types of governance mechanisms is more conducive to the promotion of the knowledge flow of collaborative platforms. The results further show that the combination of strong contract and strong relationship governance mechanism can better promote the knowledge flow of collaborative platform under different degrees of knowledge failure and initial knowledge potential difference. It can provide references for the policy formulation and improvement of collaborative innovation platforms in China.

The industrial intelligence manifested by replacing labor with machines is an important means for manufacturing enterprises to improve quality and efficiency. However, it also brings undeniable social consequences, such as layoffs and labor disputes. Under such pressure, whether enterprises are able to continue promoting industrial intelligence has become a central research topic. From the perspective of corporate social responsibility and through the configurational analysis of 101 manufacturing enterprises, it is found that six factors, including government subsidies, profitability, customer type, enterprise type, enterprise age and competition intensity, interact with each other to form paths to expand the use of machines, namely: goverment subsidy-driven paths, competition-driven paths, and profit-driven paths. At the same time, it also identified paths where firms reduces the use of machines, including efficiency-loss path, legitimacy-loss path, dual-loss path, and legitimacy-protection path. These findings not only unravel the heterogeneous impacts of different stakeholders (such as governments, managers, customers, etc.) on enterprises, but also provide strategic guidance and decision-making framework for enterprises to continue the automation process and to find a balance between operational efficiency and social responsibility when facing labor disputes.

Innovation-driven development needs to vigorously cultivate and carry forward the craftsmanship. Vigorously promoting the craftsmanship in all walks of life is conducive to building an innovative country, and it is also necessary to build a country with manufacturer of quality products and a country with a strong socialist culture. However, the path mechanism and boundary conditions of how craftsmanship affects employee’ innovation behavior are still unclear. Therefore, data from 454 paired survey questionnaires between employees and their supervisors collected at three time points was used to analyze this research question. Based on model of proactive motivation process and antecedents, the process and boundary conditions of craftsmanship in promoting employee innovation behavior through affecting psychological availability were discussed and analyzed. It reveals that craftsmanship positively affects employees’ innovation behavior. Psychological availability plays a mediating role between craftsmanship and employee innovation behavior. Promotive ethical leadership positively moderates the relationship between craftsmanship and psychological availability, when the level of promotive ethical leadership is higher, this moderating effect is more obvious, at the same time, promotive ethical leadership positively moderates the mediating effect of psychological availability between craftsmanship and employee innovation behavior. Prohibitive ethical leadership cannot play a significant boundary role in the relationship between craftsmanship and psychological availability. The conclusion reveals the important role of promoting craftsmanship in improving employees’ innovation ability, and shows that appropriate leadership style can further strengthen the positive impact of craftsmanship on employees’ work performance.

What are the conditions and scope of application for the hold-up problem? Academic views are not unified. A theoretical model based on outsourcing situation was constructed and deduces the conditions of the hold up problem: when the factors cannot obtain all marginal returns and the contract is incomplete at the same time, the hold up problem arises. When this condition is met, intermediate product manufacturers will reduce the investment in production activities not specified in the contract. Final product manufacturers will require over investment in the contracted parts to avoid output decline due to underinvestment, resulting in investment distortion. Subsequently, the article further explores the economic laws behind the hold up problem, creatively introduces broad externality to explain the general laws that arise when it affects decision-making on variable factor input or output levels, and explains the relationship between broad externality and Pareto optimality. Finally, the paper reveals the setting rules of hold up problem related to broad externality in the model, emphasizing that the judgment of theoretical models should not be limited to conclusions, but should also focus on whether the mechanism corresponding to assumptions and conclusions match reality.

Public acceptance has an important impact on the development of face recognition technology, but there is still a lack of research on the public acceptance of face recognition. A cognitive process model was constructed based on social exchange theory and responsible innovation evaluation criteria. The model examines the behavioral decision-making balance between perceived benefits and perceived risks to determine usage intention for face recognition technology. The structural equation model was used for empirical testing. The results indicate that perceived benefits and moral ethics significantly affect the public’s usage intention. However, in the face of the perceived risks, a phenomenon of “knowingly violate” rather than “timely stop” is observed. Previous privacy invasion experience, information sensitivity and negative news are found to increase perceived risks, though they do not outweigh the benefits of face recognition. Face recognition convenience is shown to enhance perceived benefits, yet it does not lead to the disregard of privacy leakage risks. Knowledge and security related to face recognition is positively and negatively correlated with perceived benefit and perceived risk, respectively. The findings contributes to a deeper understanding of the public concerns and needs for facial recognition technology, providing guidance for optimizing technology development and market promotion strategies.

The cross-border flow restriction indices of 10 exporting and 48 importing countries and the export data of six emerging digital service industries from 2014 to 2021 were matched using the OECD-DSTRI database. The impact of bilateral data cross-border flow restrictions on digital service exports was empirically examined, and a mechanism test and heterogeneity analysis were developed from multiple perspectives. It is shown that bilateral data cross-border flow restrictions inhibit digital service exports, and that data cross-border flow restrictions in exporting countries have a greater inhibitory effect on digital service exports than in importing countries. Heterogeneity analysis reveals that data cross-border flow restrictions between developed countries and EU countries hinder digital services exports to a lesser extent, and that the specific impact of these measures varies according to the type of digital services industry. Mechanism tests show that cross-border data flow restrictions hinder digital services exports by increasing trade cost. Further extension of the analysis finds that digital infrastructure level enhancement and RTA digital trade agreement signing can reduce the extent to which data cross-border flow restrictions impede digital services exports. Further analysis finds that increased levels of digital infrastructure and the signing of RTA digital trade agreements can reduce the extent to which restrictions on the cross-border flow of data impede the export of digital services. The conclusions provide important empirical support for reducing cross-border data flow restrictions and thus empowering the opening up of digital services trade to the outside world to promote China's services foreign trade growth.

Under the increasingly urgent background of global economic transformation, upgrading, and innovation-driven high-quality development, exploring how innovation-driven policies facilitate the optimization and upgrading of urban industrial structures has become crucial for realizing Chinese-style modernization and advancing the development of new productive forces tailored to local conditions. The pilot policy of innovative cities in China was treated as a quasi-natural experiment. Panel data from 281 prefecture-level cities between 2006 and 2019 were utilized, and a multi-period difference-in-differences (DID) model was employed to evaluate the policy's impact on urban industrial restructuring. The results indicate that the innovative city pilot policy significantly promotes the sophistication of urban industrial structures, while its effect on industrial structure rationalization remains statistically insignificant. These findings are validated through a series of robustness tests. Heterogeneity analysis reveals more pronounced policy effects in cities with higher administrative levels, greater proportions of tertiary industry employment, development models not fully reliant on resource endowments, and those located within urban agglomeration economic belts. Mechanism analysis further demonstrates that the policy positively affects industrial structure sophistication through three channels: expanding the digital economy scale, optimizing resource allocation efficiency, and enhancing human capital supply. It empirically reveals the pathway through which innovation policies promote industrial structure optimization, providing both theoretical foundations and practical references for enhancing policy effectiveness and advancing high-quality regional economic development.