Digitalization not only drives the expansion of energy demand but also profoundly reshapes the patterns of energy supply and consumption, so it is of great significance to explore the impact of industrial digital transformation on electricity dependence. Based on China’s input-output tables from 1993 to 2021 provided by Eora, this paper measures electricity dependence by the share of total inputs from the electricity production and supply sector in industry intermediate inputs, and investigates the impact of industrial digitalization inputs on electricity dependence as well as the mechanism underlying the impact. The findings indicate that industrial digitalization inputs have a significant positive effect on electricity dependence, which remains robust after addressing endogeneity concerns and a series of robustness checks. Specifically, industrial digitalization inputs strengthen internal electricity demand by increasing direct electricity dependence and electrification rates on the one hand, and further amplifies electricity demand by enhancing indirect electricity dependence and generating spillover effects that transmit along upstream and downstream supply chains on the other hand. Moreover, digitalization inputs in the electricity production and supply sector helps optimize its energy consumption structure, and improved access to clean energy also facilitates industrial digital transformation. Furthermore, the promoting effect of industrial digitalization inputs on electricity dependence is stronger in industries with high energy consumption, high electrification rates, and high digitalization intensity, exhibiting heterogeneous effects across industries with different factor intensities. This paper provides empirical evidence for understanding changes in industrial energy use structure amid digital transformation and for formulating differentiated industrial and low-carbon transition policies.

Under mounting pressures of increasingly stringent resource constraints, severe environmental pollution, and ecosystem degradation, ecological overload and sluggish growth caused by resource misallocation have emerged as critical bottlenecks constraining the development of new quality productive force. This paper, focusing on the key issues of empowering the green foundation of new quality productivity forces, constructs an analytical framework for the coupling and coordination of the Energy-Environment-Economy (3E) system under sustainable development goals, and examines the nonlinear impact of China’s 3E system coupling on Green Total Factor Productivity (GTFP) via spatiotemporal dimension. The results indicate that China’s 3E system exhibits a developmental pattern characterized primarily by “intermediate coordination with notable gradient transition”. When the coupling coordination degree surpasses the critical threshold (0.8424) and enters the “well-coordinated” stage, technological progress becomes the primary driver of GTFP growth, with its marginal contribution to GTFP increasing by 42.4%. Furthermore, regional heterogeneity reveals that coastal regions leverage institutional dividends to achieve a manifold increase in GTFP. In contrast, inland regions are constrained by path dependency, limiting their growth potential. The central regions, however, exhibit a “double threshold” effect. These findings provide a basis for policymaking and offer policy implications for building a regional collaborative governance system, addressing resource misallocation, and accelerating the leapfrog development of new quality productive forces.

The rapid advancement of digital technology has fundamentally reshaped the transfer, diffusion, and creation of human know-ledge. Grounded in the classic SECI model, this study examines the intellectualization of knowledge transfer through three dimensions—its trajectory, function, and model—to uncover the underlying mechanisms driven by digital technologies. The findings indicate that: First, the trajectory evolves progressively from digitalization to intelligentization and toward embodiment, transcending spatiotemporal constraints, particularly in tacit knowledge transfer. Embodied intelligence, as an advanced form of AI, leverages body-environment interactions to enable more efficient intelligent behaviors. Second, the functionality intensifies along this trajectory, overcoming limitations of the SECI model and reflecting a shift in cognitive modes from connectivity and sharing to intelligent empowerment and ultimately human-machine integration. Third, The model transforms the classical SECI framework, leveraging technologies such as cloud computing, quantum computing, and large models to converge four stages into a unified “human-machine shared sensing” phase, enabling instant knowledge transfer across heterogeneous spatiotemporal contexts. This study highlights the profound impact of digital technologies on knowledge transfer, offers theoretical insights for knowledge management and intellectualization, and provides practical guidance for knowledge-intensive organizations in fostering knowledge transfer and enhancing innovation capabilities during digital transformation.

Against the backdrop of persistent turbulence in the global economic and trade environment and the escalating trend of trade protectionism, trade restrictive policies have emerged as a significant exogenous shock factor affecting the stable operation of global value chains. This paper constructs a global value chain network distinguishing between domestic and foreign-invested enterprises based on OECD-AMNE input-output data. Utilising the GTA Global Trade Alert database to quantify the intensity and scope of trade restrictive measures, it systematically assesses the impact of such policies on the resilience of global value chain networks from a multidimensional perspective of heterogeneity across countries, industries, and domestic versus foreign-invested enterprises. The study finds that: (1) Trade restrictive policies exert a significant dampening effect on the resilience of both domestic and foreign-invested enterprises within global value chain networks. (2) Trade restrictive policies produce heterogeneous impacts on the resilience of domestic and foreign-invested enterprises within global value chain networks, depending on the development level of their home countries or economies, their sectoral affiliation, and the specific type of trade restrictive policy imposed. (3) Trade restrictive policies exert negative impacts on the resilience of both domestic and foreign-invested enterprises within global value chain networks through channels including increased intermediate goods trade costs, suppression of technological spillover effects, and reduced participation in global value chains. (4) Trade restrictive policies exert negative impacts on the network resilience of both domestic and foreign-invested enterprises participating in complex value chain activities, while only adversely affecting the network resilience of foreign-invested enterprises engaged in simple value chain activities. The findings of this study have important practical significance for maintaining a stable global economic and trade pattern and building resilient industrial and supply chains.

Industrial Internet platforms are one of the key domains driving the digital and green twin transition of manufacturing enterprises. This paper first calculates the level of digital and green twin transition of manufacturing enterprises using the entropy method and coupling coordination model. Subsequently, this paper selects data from A-share listed manufacturing companies from 2010 to 2023 and utilizes the Ministry of Industry and Information Technology’s “Industrial Internet Pilot Demonstration Platform Projects” (2018—2023) to construct a quasi-natural experiment. By employing a multi-period differences-in-differences model, the study investigates the actual impact of Industrial Internet platforms on participatory manufacturing enterprises’ digital and green twin transition and the mechanism underlying the impact. This research reveals: The industrial Internet platform can significantly promote the digital and green twin transition of participatory manufacturing enterprises. At the same time, the industrial Internet platform can improve the resource allocation efficiency of manufacturing enterprises, promote multi-initiative collaboration and innovation, and then improve the level of their digital and green twin transition. The conclusion of this study not only enriches the research related to the transformation of enterprises empowered by industrial Internet platforms from the perspective of platform-participating manufacturing enterprises, but also provides a decision-making reference for promoting the digital and green twin transition of manufacturing enterprises.

In green development, it is of great significance to give full play to the leading role of the digital economy, a powerful driving force for high-quality economic development. Based on the data of Chinese Industrial Enterprise Pollution Emission Database and China Customs Database, this paper investigates how a company’s green production is influenced by its digital input and the digital product network it is exposed to. Empirical results show: a company’s digital input does not have a significant influence on its green production, while the digital product network it is exposed to exerts a powerful enabling effect on its green production. Digital technology flowing in the product network improves the green production capacity of enterprises by increasing their innovation and improving their supply-chain management. This cleaning effect can be enhanced by higher allocation efficiency in the export market, especially for small companies that offer products of quite different quality or operate in the zones that are subject to dually environmental control. Key words: digital input, digital product network, green production, innovation, supply-chain management

The report of the 20th National Congress of the Communist Party of China called for efforts to “accelerate the green transformation of development mode, implement the comprehensive conservation strategy, and develop green and low-carbon industries”, which is a clear requirement for enterprises to develop in a green and low-carbon manner. Effectively driving the improvement of carbon emission performance through carbon risk avoidance has become an inevitable choice for enterprises to obtain green competitive advantages and realize low-carbon transformation. Based on signaling theory and organizational learning theory, this paper builds a theoretical model of carbon risk avoidance, green image and green competitive advantage, and empirically tests the research hypothesis and influence path with data from 239 enterprises. The results show that carbon risk aversion has an inverted U-shaped effect on green competitive advantage, and corporate green image plays a partial mediating role in the effect of carbon risk aversion on green competitive advantage. Further research shows that organizational learning ability can significantly enhance the inverted U-shaped relationship between carbon risk avoidance and green competitive advantage, and higher organizational learning ability can enhance the positive effect of carbon risk avoidance on green competitive advantage. The research conclusions of this paper expand the theoretical system of carbon risk, and provide theoretical basis and policy inspiration for Chinese enterprises to carry out low-carbon transformation to improve green competitive advantage from the perspective of “carbon peak”.

Scientific and technological innovation talents are the key human resources for a country to become more innovative and own more core technologies. Promoting the agglomeration of scientific and technological innovation talents is essential for advancing China’s ambition to build a globally important talent center and innovation hub. Taking 295 cities in China as cases of configuration research, this paper explores the role of working, natural, and living amenities on the scientific and technological innovation talents aggregation based on the amenities theory. The findings reveal that, firstly, the scientific and technological innovation talents aggregation is influenced by a combination of working, natural, and living amenities provided by cities, rather than being dominated by a single amenity. Secondly, different amenity elements synergistically contribute to three pathways for attracting scientific and technological innovation talents, namely “dominated by scientific and technological innovation” “co-driven by social economy and scientific and technological innovation” and “synergisticly driven by multi-factors” Thirdly, although a single amenity does not constitute a necessary condition for scientific and technological innovation talents aggregation, the working amenity centered around the scientific and technological innovation plays a more universally applicable role. The conclusion enriches the antecedents of the scientific and technological innovation talents aggregation and the related research of amenities theory, and provides policy enlightenment for cities to “build nest to attract phoenix” by building urban amenities for talents.

The growth of SRDI “Little Giant” enterprises, which are an important force in curbing cutthroat competition around key core technologies, has received unprecedented attention and strong support from the Ministry of Industry and Information Technology (MIIT) of the People’s Republic of China. By participating in the development of national and industrial standards, SRDI “Little Giant” enterprises can better orient themselves in their high-quality development and gain support in terms of standards, but the existing research on the impact of their participation in standard development on their growth and the mechanism underlying the impact is not deep enough. This paper constructs a theoretical model based on signal theory and knowledge-based view, collects the data of 752 manufacturing SRDI “Little Giant” enterprises from 2015 to 2022, and empirically examines the impact of their participation in standard-setting on their growth and the boundary conditions. The study finds that SRDI “Little Giant” enterprises’ participation in standard-setting promotes their growth through the intermediary mechanism of increasing customer dispersion, and the scenario diversity attribute of enterprises negatively moderates the relationship between participation in standard setting and customer dispersion, while the technological sophistication attribute positively moderates the relationship between customer dispersion and growth; further analyses show that participation in standard-setting has a stronger effect on the growth of firms that are smaller in size and in more competitive industries. The findings of the study help deepen the understanding of the growth path of SRDI “Little Giant” enterprises, and provide a theoretical basis for “Little Giant” enterprises to break through the growth boundary and better play the role of chain-supplementing and chain-strengthening in a highly dynamic environment.

Enterprise innovation is the fundamental way to lead the construction of a modern industrial system and form new quality productivity. Data elements are new factors of production and the basis for converting old drivers of economic growth to new ones. So can we use data elements to stimulate the innovation vigor of enterprises, give a boost to the efficiency of their innovation, and form new quality productivity? In this paper, based on the heterogeneous innovation theory, we divide enterprise innovation into iterative and radical innovation, construct a theoretical model of data element and enterprise dual innovation, and theoretically clarify the effect of data element on iterative and radical innovation as well as the mechanism underlying the effect. Microscopic data of listed companies from 2011 to 2023 is further used to empirically test theoretical models. The results show that: (1) Data elements significantly promote the iterative innovation and radical innovation of enterprises, and have a greater impact on the iterative innovation. (2) In terms of influence mechanism, the moderating effect of enterprise size on the influence of data elements on enterprise ambassadors innovation is manifested as a dual effect: it not only enhances the polarization effect of data elements on iterative innovation, but also inhibits the equilibrium effect of data elements on radical innovation. (3) The heterogeneity analysis finds that the data elements have a particularly prominent promoting effect on the dual innovation of high-tech intensive enterprises and private enterprises. This study provides useful insights for exploring the innovation-driven path of deep integration of digital and real economies to develop new quality productivity.

Existing research on the relationship between category spanning and firm performance has yielded inconsistent conclusions, with limited empirical studies focusing on technology-based start-ups. Drawing on categorization theory, this paper explores the impact of category spanning across different patent categories on the performance of technology-based start-ups, utilizing patent data from 86 Chinese technology start-ups between 2000 and 2019, comprising a total of 451 patent records. Additionally, based on a population ecology perspective, this study examines the moderating effects of firm age and population density on the relationship between category spanning and firm performance. The findings reveal a U-shaped relationship between the extent of category spanning and firm performance. Moreover, the analysis shows that firm age strengthens the U-shaped relationship between category spanning and performance, while population density weakens this relationship. These results offer new explanations for the inconsistent effects of category spanning and provide valuable contextual insights. The study contributes to the strategic formulation and implementation of category spanning in firms, offering rich managerial implications.

In the increasingly digitalized business environment, entrepreneurial resilience, which is the ability of entrepreneurs to effectively adapt to, recover from, and transcend difficulties, plays a crucial role in enhancing the quality of strategic decision-making through learning. Grounded in Upper Echelons Theory, this study elucidates the mechanism through which entrepreneurial resilience influences strategic decision quality in digital environment. The analysis of 313 survey questionnaires reveals that the stronger the recovery resilience and growth resilience of entrepreneurs, the higher the quality of their strategic decision-making. Entrepreneurial resilience exerts a positive influence on strategic decision-making quality through two learning pathways: exploratory learning and exploitative learning. However, when the level of enterprise digitalization is high, the positive impact of recovery resilience on strategic decision-making quality is attenuated. This finding enriches the understanding of the proactive role of entrepreneurial resilience, offers a new perspective for strategic decision-making research, and provides practical guidance for entrepreneurs to leverage entrepreneurial resilience in enhancing strategic decision-making quality in digital environment.

Under the strategic framework of promoting high-quality economic and social development, collaborative innovation stands as a critical pathway, playing a significant role in optimizing resource allocation, facilitating industrial upgrading, and driving regional deve-lopment. Leveraging data from the Xinjiang Science and Technology Progress Award, this study constructs a collaborative innovation network for the Xinjiang region and investigates the influence of its structural characteristics on innovation performance. The findings indicate that over time, the level of collaborative innovation in Xinjiang’s development trial zone has progressively strengthened, demonstrating a distinct phased development pattern. Further analysis reveals that network features such as centrality and structural holes have a significant impact on innovation performance, with this impact exhibiting heterogeneity between core and non-core innovation regions. This research provides empirical support and policy recommendations for advancing the optimization and development of Xinjiang’s innovation ecosystem.

This study focuses on designer brands rooted in cultural and aesthetic values, exploring how they construct brand identity in online retail and stabilize it in customers’ minds by consistently integrating a sense of “human presence” into their digital storefronts, thereby aligning the brand image with the company’s original vision. Through a qualitative study of the independent designer brand DW, this paper reveals that in e-servicecapes where face-to-face interactions are absent, brands can interweave dual narratives centered on products and designers, cultivating a unique brand aura that serves as a differentiating marker of brand identity. This study proposes a theoretical framework that explains the mechanisms of shaping designer brands with a unique aura in online retail, highlighting the critical role of designer’s creative control in maintaining this aura and resonating with customers. The findings of this study provide valuable insights into overcoming key challenges in online retail, such as conveying complex brand messages and fostering deep connections with like-minded customers.

Online health communities (OHCs) are an important platform for internet-based medical services and knowledge dissemination in health education in China. However, previous studies often treat online consultation and health promotion as two separate research questions, with limited research on their potential associations. Given this research gap, this study constructs a research model by integrating the signaling perspective within the framework of social capital theory and employs text mining and statistical modeling methods to explore the multidimensional effects of physicians’ social capital in the context of health knowledge popularization in OHCs, and examine how it affects physicians’ online service performance. For sample selection, this study takes China’s most representative online health community platform (HaoDF Online) as the research context and obtains abundant research data from it. The researchers first train text classification models using machine learning methods to automatically identify the topics of doctors’ popular science articles, which greatly improves the accuracy and coverage of sample selection. Next, this study employs word vector techniques to compare the similarity between doctors’ health popular science articles and patients’ consultation text, and quantitatively extracts the “doctor-patient shared language” variable that reflects the readability of physicians’ health popular science articles. Based on the above work, this study constructs an empirical dataset with accurate mapping relationships between popular science article topics and online consultation diseases, which lays the data foundation for subsequent fine-grained causal relationship verification. Finally, this study adopts multi-level regression models to simultaneously examine the interaction effects among independent, mediating and moderating variables. The results show that doctors’ use of doctor-patient shared language in health popular science writing has a positive impact on their online consultation volume, and doctor-patient reciprocal feedback mediates this process. Furthermore, doctors’ professional qualifications can significantly moderate the effect of doctor-patient reciprocal feedback on online consultation volume. These findings extend the theoretical connotation and interpretation of social capital theory. They also provide important references for doctors to provide high-quality popular science knowledge and promote efficient OHCs operation.

The milestones a CEO has reached along his or her career path contribute to the formation of his or her cognitive framework, social resources, and managerial vision, which in turn affects the implementation of corporate innovation. However, the typical career patterns of CEOs in Chinese enterprises and their specific impacts on corporate innovation remain unclear. Using a sample of Chinese A-share listed companies from 2007 to 2023, this study manually collects CEO career data and identifies typical CEO career patterns from the dimensions of employer, status, and function based on sequence analysis. The research indicates that CEO career patterns exert differentiated impacts on corporate innovation. From the employer background perspective, compared to CEOs with most experience in private sector, CEOs with most experience in a single traditional sector simultaneously promote both breakthrough and incremental innovation, whereas CEOs with diverse cross-sector experience tend to inhibit incremental innovation. From the status evolution perspective, compared to stepwise promoted CEOs, founding CEOs exert a significant positive effect on both types of innovation. From the functional expertise perspective, compared to management-oriented CEOs, technical expert CEOs demonstrate clear advantages in driving both breakthrough and incremental innovation, while diversely functional CEOs are more likely to foster breakthrough innovation. Notably, the tenure of production expert CEOs is significantly associated with declines in both breakthrough and incremental innovation. The findings of this study extend the literature on the determinants of corporate innovation and the economic consequences of CEO careers. It provides new empirical evidence for improving the development and selection mechanisms for CEOs of listed companies and for further enhancing corporate innovation levels.

This study introduces the concept of AI use hiding and, grounded in the two-component model of impression management theory, examines the underlying motives driving employees’ AI use hiding behaviors through the dual-process lens of impression motivation and impression construction. Based on data from a three-wave survey of 475 employees at a large internet company in Southwest China, the findings reveal that: (1) employees’ perceived AI utility, along with their perceptions of leader’s AI trust or AI doubt, jointly stimulate assertive and defensive impression management motives (the impression motivation process); (2) these impression management motives, combined with employee’ perceived AI accessibility, influence their decision to hide AI use as a specific impression construction strategy (the impression construction process); (3) both assertive and defensive impression management motives mediate the relationship between perceived AI utility and AI use hiding; (4) the higher perceived leader’s AI trust or AI doubt and the lower perceived AI accessibility, the stronger the mediating effect of perceived AI utility on AI use hiding through impression management motives. These results not only illustrate that AI use hiding represents a balancing strategy between technological empowerment and impression management, but also highlight the crucial role of leadership attitudes and technological context in shaping employees’ impression management motivation and construction.

Through conducting three rounds of questionnaires to 171 employees of a state-owned enterprise in southwest China, this study examines the impact of unethical pro-organizational behavior on workplace deviance, and investigates the mediating psychological mechanisms of moral disengagement and the boundary conditions of guilt and ethical leadership. The results show that employees’ unethical pro-organizational behavior positively influences their workplace deviant behavior via moral disengagement. Moreover, employees’ guilt positively moderates the relationship between unethical pro-organizational behavior and moral disengagement while ethical leadership negatively moderates the relationship between employee moral disengagement and deviant behavior. For the indirect relationship between unethical pro-organizational behavior and deviant behavior through moral disengagement, guilt positively moderates this relationship, but ethical leadership negatively moderates it. This study explains the impact of unethical pro-organizational behavior on employees’ moral cognition and other unethical behavior, enriching the theoretical study on the consequences of unethical pro-organizational behavior as well as the boundary conditions.

In the face of growing risks and uncertainties, firms are in urgent need of enhancing the resilience of their supply chains. However, existing literature offers limited understanding of the mechanisms underlying supply chain resilience, particularly regarding the differentiated effects and boundary conditions of internal versus external supply chain integration. Based on the dynamic capabilities theory, this study uses valid survey data from 622 firms collected in the Alliance of Industrial Internet and related organizations to investigate the impact of supply chain integration on supply chain resilience. The findings reveal that supply chain integration has a significant positive effect on supply chain resilience, with internal integration exerting a stronger impact than external integration. Moreover, the level of information sharing plays a partial mediating role in this relationship, while a firm’s digital capability strengthens the mediating effect of information sharing. Further analysis indicates that manufacturing firms exhibit higher dependence on supply chain integration, whereas the resilience-enhancing effect of integration is weaker for medium-sized firms. Based on these findings, this study proposes an innovative strategy of “inside-out” integration to enhance supply chain resilience, offering insights for firms to manage supply chain in complex and uncertain environments.

Against the backdrop of increasingly strict global carbon emission reduction requirements and the popularization of the concept of sustainable development, national policy guidance and the innovative application of blockchain technology continue to drive supply chain enterprises to attach growing importance to carbon emission reduction practices. Under the carbon trading mechanism, this paper constructs a low-carbon supply chain model empowered by blockchain technology in which manufacturers and retailers jointly invest in carbon emission reduction, considering the incentive policy of government subsidies for blockchain construction. The independent emission reduction and cooperative emission reduction strategies of the low-carbon supply chain are analyzed. The study shows that regardless of whether blockchain technology is applied or not, cooperative strategy is more helpful than independent strategy for reducing carbon emission and expanding production. And the cooperative strategy is more conducive to realizing an agile low-carbon supply chain. Blockchain technology can empower enterprises to reduce carbon emissions and expand production under the compensatory effect of cooperative strategy, but it depends on the empowerment level of blockchain and the cost of blockchain usage. Moreover, the application of blockchain technology requires the product market to be more responsive than the carbon trading market to avoid the Prisoner’s Dilemma. The government’s incentive policy of subsidizing retailers that apply blockchain technology is conducive to easing the cost pressure on retailers, but it cannot directly reduce carbon emission. The government should design a diversified blockchain support policy, expand the scope of subsidy targets, and diversify the subsidy means.

Airworthiness standards, forged through blood and lives, govern the entire civil aircraft development process and define the safety baseline for civil aviation. Airworthiness standards impose extremely stringent safety requirements on technical standards, with a minimum safety threshold of 10-9 —any failure in a standard clause may lead to catastrophic consequences including aircraft destruction and loss of life. Moreover, since airspace functions as a globally unified market without regional protectionism or graduated entry mechanisms, latecomer countries must meet, from the outset, the same rigorous safety standards as those long-established nations. These extreme constraints create a fundamental dilemma: latecomers must simultaneously conform to existing international standards for market acceptance while breaking through established frameworks to meet unique domestic needs. How to resolve this dilemma has become an urgent question for management research. This study selects AC313 helicopter—the world’s first to achieve full-domain plateau-plain airworthiness and obtain both domestic and international certification—as a representative case. Using a longitudinal case study method, we investigate the mechanisms underlying airworthiness standards innovation in latecomer countries. Key findings include: (1) To overcome the barrier nature of airworthiness standards, latecomers must build an adaptive innovation pathway driven by conventional scenarios, achieving proactive internalization of existing standards through “deconstructing standard principles-integrating resources across platforms-compliance verification,” thus laying the foundation for original breakthroughs. (2) To meet the scientific rigor of airworthiness standards, latecomers must build a breakthrough innovation pathway driven by special scenarios, constructing original standards through “forward design-integrating industry-university-research resources-feasibility verification,” thus providing technological support and expanded application domains. (3) An ambidexterity mechanism emerges between these two pathways: adaptation provides the scientific basis for breakthroughs, while breakthroughs expand the capability boundaries for adaptation. The two are organically unified, jointly enabling standards innovation in latecomer countries. This study offers theoretical guidance and practical insights for latecomers pursuing innovation in high-technology standards domains.

The emergence of digital windows of opportunity not only provides international new ventures (INVs) with opportunities to catch up rapidly in the global market, but also generates brand-new opportunities for them to overtake competitors and “take the lead”. However, existing research has not yet explored in depth the issue of strategic rhythm selection for such enterprises to develop digital windows of opportunity. This paper selects four INVs that have successfully seized digital windows of opportunity as research objects, and constructs a theoretical model matching digital windows of opportunity with strategic rhythms on the basis of analyzing the characteristics of windows of opportunity. The research findings are as follows: (1) From the perspective of opportunity transformation, based on the two dimensions of “innovation type” and “core resource”, the digital windows of opportunity faced by INVs are divided into four types, namely “internal-exploitative”, “external-exploitative”, “internal-exploratory” and “external-exploratory”; (2) For different types of digital windows of opportunity, INVs adopt four strategic rhythms, namely “gradual breakthrough”, “synchronous adaptation”, “flexible orchestration” and “high-frequency shaping”, to carry out opportunity transformation, and smoothly promote the implementation of strategic rhythms by virtue of the organic combination of two strategic actions: digital connection and resource integration; (3) In the process of the coordinated combination of digital connection and resource integration, INVs mainly release the effectiveness of the action combination through two mechanisms: “enhanced complementarity” and “collaborative integration”. The theoretical framework finally formed in this paper is of great theoretical significance for understanding the unique international expansion behaviors of INVs in the context of digital globalization, and responds to the call of scholars in the field of international business to expand the research on the internationalization behaviors of new ventures in the digital era.