Rapid and pervasive digitization of innovation processes and outcomes has upended the way that innovative actors jointly creating value, deepened the development of extant theories on innovation ecosystems, and triggered the discussion on building digital innovation ecosystems. Innovation ecosystem studies have underlined the importance of coordinate symbiosis between innovative actors. The ecosystem members jointly create value around a hub actor, which means they work cooperatively and competitively to support new products, new technologies, and coherent customer solutions. Going digital not only introduces data as a new productive factor but also enhances the collaboration among actors, which changes the behavior logic of innovation ecosystems. Therefore, understanding digital innovation ecosystems in a proper way contributes to guiding the innovation practice in a digital era, as well as expanding or reconstructing relative theories on innovation ecosystems. However, most of the existing studies have neglected the new characters, new trends, or new challenges. There is an urgent need for scholars conducting in-depth studies to understand the nature of digital innovation ecosystems. 
   To fill the research gap, this paper put forward two basic manifestations of digital innovation ecosystems, that is, innovation-oriented digital ecosystems (or say, digital innovation ecosystem Ⅰ type) and digital-enabled innovation ecosystems (or say, digital innovation ecosystem Ⅱ type). On the one hand, innovation-oriented digital ecosystems are defined as digital ecosystems that serve for the creation, application, and diffusion of digital innovations. The innovation-oriented digital ecosystems could realize the join value creation among digital actors through innovation, and therefore can be regarded as innovation ecosystems established around digital actors. Such ecosystems also have characters that they inherit from digital ecosystems, that is, convergence, scalability, generativity, and modularity. On the other hand, the digital-enabled innovation ecosystems are the deep integration between the digitalization process and the behavior logic of ecosystem actors. From the perspective of a complex adaptive system (CAS), this paper constructed a theoretical analytical framework on the behavior logic of innovation ecosystems consisting of five dimensions, that is, actors, structures, institutions, functions, and evolution. Going digital enables new characters to innovation ecosystems, which also changes the behavior logic of innovation ecosystems.
    The two types of digital innovation ecosystem permeate each other and push forward each other. Such intertwined relationships change the way of jointly value creation among innovative actors and improve the innovation capability and innovation effectiveness in an all-round way. This paper introduces a conceptual framework for studying digital innovation ecosystems by integrating the above two concepts: innovation-oriented digital ecosystems and digital-enabled innovation ecosystems (i.e., digital innovation ecosystem Ⅰ type and Ⅱ type). This paper clarified the nature of digital innovation ecosystems by describing how the actors, structures, institutions, functions, or evolution perform when convergence, scalability, generativity, and modularity influence the ecosystems profoundly in a digital era. At last, this paper outlines a new research agenda to fill the gap in our understanding of digital innovation ecosystems. It points out that the following scholars could modify or polish the theories on digital innovation ecosystems by conducting convincing empirical analysis like measuring or case study, analyzing the pathway of ecosystem growth or development, or studying the policy on supporting the establishment or development of digital innovation ecosystems.

The breakthrough of key core technologies is a major issue that China encounters at the current stage of its development. The reasons why key core technologies are difficult to conquer, not superficially because of a comprehensive technology blockade from the developed countries, but fundamentally because of some systematic problems, including that the basic research support is insufficient; the collaborations between industry, academia and research departments are not close enough; the early market is difficult to form; and the institutional mechanism of developing key core technologies is not valid enough, and so on. Therefore, to make a breakthrough in key core technologies is not simply a technological issue, but a systemic issue. Accordingly, this study explored the breakthrough mechanism of key core technologies in the context of innovation ecosystem evolution.

As for research methods, this study explored the key core technology breakthrough mechanism by applying the exploratory dual case study method, and taking the high-end scientific instrument industry as the research subject. Two typical cases of Illumina and BGI have been selected as the samples of international leading firm and the domestic catch-up firm for a comparative analysis of the gene sequencer technology breakthroughs. The research steps are as follows: (1) The authors of this paper obtained the first-hand data and second-hand data through interviews and other means, analyzed and summarized the characteristics of research objects, event sequences, influential events, environment, organization and other factors related to time and order with the help of time axis, and divided the innovation ecosystem evolution process from the start-up stage to the prosperity stage; (2) Based on the literature research, we established a theoretical analysis framework by measuring three categories, including system structure, dynamic capabilities and value proposition, to provide guidance for data coding; (3) We also processed the open coding, axial coding and selective coding in the proceduralised grounded analysis, and made the theoretical saturation achieved when there is no new property of category identified;(4) We finally conducted a comparative analysis of two cases by vertical and horizontal comparison.

The research results are as following: (1)The innovation ecosystem is the carrier for the breakthrough of key core technology, and the innovation ecosystem promotes the key core technology breakthroughs through the evolution process of “individual reproduction, population shaping and community integration”; (2)International leading firms tend to choose the maintenance breakthrough path of “product-service-ecology”, while the domestic firms tend to choose the reverse breakthrough path of “service-product-ecology”;(3)The implementation of the key core technology breakthroughs by domestic firms usually goes through three main stages. The first stage is to develop their own innovation ecosystem within the innovation ecosystem of international leading firms. The second stage is to withdraw from the constraints of the innovation ecosystem of international leading firms and implement reverse breakthroughs upstream of the industrial chain after a critical event occurs. The third stage is to purposefully carry out ecological innovation around key core technologies, forming confrontation with international leading firms; and (4) The key core technology breakthrough process of domestic firms is often affected by four important factors, including value proposition, innovation environment, dynamic capability, and critical events.This study revealed the interactional relationships between the evolution of innovation ecosystem and the breakthroughs of key core technologies, which brings enlightenment to government policy-making and enterprise innovation practice.

This study have put forward the following suggestions: (1) The government should focus on optimizing the policy system, providing comprehensive policy supports to enterprises with the potential to make breakthroughs in key core technologies, and establish a suitable policy environment for cultivating an innovation ecosystem conducive to key core technology breakthroughs, such as promoting the first set of policies, implementing application benchmarks, industrial demonstration, and scenario development projects. (2) For the catch-up firms, it is important to recognize that the key core technology breakthrough process of the latecomers is different from the one of international leading firms. Domestic catch-up firms may follow the reverse breakthrough path of “service-product-ecology” to develop the key core technologies. In this process, domestic firms should attach importance to establishing correct value propositions, improving dynamic capabilities, and keenly paying attention to the impact of critical events.

    Artificial intelligence (AI) is reshaping the structural form of the innovation ecosystems and cooperation modes between innovation subjects, bringing disruptive changes to enterprise innovation, and posing new challenges to the innovation ecosystem theory. However, current research lacks insight into how AI participates in building the innovation ecosystem. This paper focused on the theories related to innovation ecosystems, and analyzed the structure and construction process of the innovation ecosystems with AI participation based on the exploratory case study of Huawei′s HarmonyOS. The research found that: (1) AI, as the innovation subject, plays such multiple identities as enabler, supporter, connector and driver, and the innovation ecosystem with AI participation presents the characteristics of coexistence of human and AI dual innovation subjects; (2) AI, as the innovative technology, promotes multi-level and all-round interaction among innovation subjects, and promotes the diversification and decentralization of innovation ecosystems; (3) AI co-evolved and co-existed with the innovation ecosystem it participated in, and in different stages of the construction of the innovation ecosystem, the innovation mechanism evolve from being expert-led, to partnerships and collaborations, and finally to collaborative sharing. This study has further enriched and developed the theory of innovation ecosystems, and it will provide guidance for enterprises to build innovation ecosystem under the new situation to enhance innovation vitality and sustainable development ability. 

    With the release of Chat GPT and the advent of New Bing, especially the emergence of new war modes in the Russia-Ukraine Conflict, AI technology has played an important role in the future development of competitions. How to break through the bottleneck of artificial intelligence technology, effectively enhance the competitiveness of the artificial intelligence industry is currently an unavoidable problem. This article focused on improving the competitiveness of the artificial intelligence industry, with the main focus on solving the problem of industrial innovation efficiency. In this paper, through literature analysis and system analysis methods, relevant analysis was conducted on the innovation ecosystem of the artificial intelligence industry, the following main conclusions was made: (1) the overall trend of artificial intelligence has become the core hub of industrial development, social change, and international competition has been clarified, and the viewpoint that the development of artificial intelligence is the development of the future has been formed; (2) we constructed a scientific and efficient artificial intelligence industry innovation ecosystem model, which will provide an effective analytical tool for effectively solving the problem of innovation environment barriers and innovation subject opposition, and for the macro regulatory layout and micro precise policy implementation of the artificial intelligence industry; (3) we established a multi-disciplinary, multi industry talent cultivation and output mechanism with intelligent education as the core, thus providing strategic support for the long-term development of the artificial intelligence industry.

  Innovation ecosystems are characterized by the coordination mechanisms among diverse organizations around shared value propositions. This topic has become a significant academic issue in business management recently. This study reviewed the innovation ecosystems based on the quantitative analysis, and analyzed 1856 pertinent journal papers through bibliometric and content analysis techniques. The main findings include: Firstly, quantitative research on innovation ecosystems has identified three literature clusters related to corporate affiliation, technology connections and interaction mechanisms, with emerging related themes. Secondly, regarding quantitative measurements, both corporate affiliation and technology connections concentrate on analyzing the composition and relationship dimensions, developing distinct quantitative methods in terms of nodes, indicators, and modeling techniques; and despite their differences, they converge in research methods at the interaction mechanisms level. Thirdly, this study proposed an integrated framework combining “corporate affiliation-technology connections-interaction mechanisms” within the innovation ecosystem′s quantitative analysis. It highlights the importance of adapting between corporates and technologies during innovation, coordinating supply and demand to facilitate value creation and value capture through interactions. Reviewing the innovation ecosystem literature based on the quantitative analysis is an attempt to fill the current gap dominated by qualitative rather than quantitative research and lack of quantitative reviews. This will suggest directions for future quantitative empirical studies on innovation ecosystems and offer insights for integrating theory into academic, commercial, and policy-making practices.

   Innovation ecosystem has the characteristics of complexity, openness, self-organization and habitat. It is an important organizational form for a country or region to carry out innovation. The successful practice of Silicon Valley showed that constructing an innovation ecosystem was a great significance to stimulate the innovation vitality and build competitiveness of a country or region. Under the background of the new round of scientific and technological revolution and industrial reform, group innovation characterized by intelligence, green and ubiquitous has triggered a major adjustment of the international industrial division and disruptive technologies. It is reshaping the world competition pattern and changing the power balance between countries or regions. Implementing innovation driven development has become the general trend of world competition and the core strategy for countries or regions to seek competitive advantage. Focusing on constructing innovation ecosystem has become an important way of implementing innovation driven development.
   China′s economic development has entered the new normal.The important feature is that economic development has changed from factor and investment driven to innovation driven. Innovation has become the fundamental driving force to promote China′s high-quality economic development. In recent years, with the implementation of innovation driven development strategy, China′s innovation driven development has made remarkable achievements. However, there are still some problems, such as weak ability of original innovation, insufficient diversity of innovation subjects, low efficiency of the use of scientific and technological resources, imperfect mechanism of industry-university-research collaborative innovation and transformation of scientific and technological achievements. As a high-level organizational form for carrying out innovation activities, the connotation of innovation ecosystem meets the requirements of innovation driven development and construction a powerful country in scientific and technological innovation. 
    Therefore, following the logic and paradigm of innovation ecosystem, improving the original innovation ability, building a diversified innovation subject and deepening the collaborative innovation of industry-university-research are undoubtedly the key to China′s adhering to innovation driven development and accelerating the construction of a powerful country in scientific and technological innovation.
    The development and application of new generation digital technologies such as big data,AI and IOT have accelerated the transformation of economic and social activities to digitization and profoundly changed all aspects of economic and social development. The embedding of digital technology is profoundly changing the value co-creation mode of innovation ecosystem and the relationship between innovation subjects, and expanding the theory of innovation ecosystem. Therefore, with the advent of the digital economy era, the mechanism of innovation ecosystem evolution under the digital transformation has aroused the attention and thinking of the academia. However, throughout the existing research literature, there are still few research literatures to carry out in-depth discussion on this topic. Basing on this, the paper deeply discusses the reconstruction of innovation ecosystem by digital transformation from the aspects of space-time boundary, species composition and innovation methodology, then the paper focuses on the driving mechanism of innovation ecosystem evolution under digital transformation from the two levels of digital technology and data resources. Specifically, digital technology stimulates high-frequency innovation by reducing the uncertainty of innovation activities; Enhances the integration and generation of innovation ecosystem, improves the integration ability of innovation resources and the accumulation and diffusion speed of innovation knowledge; Strengthens the communication and coordination, deepens the system communication and coordination mechanism etc to drive the sustainable evolution of innovation ecosystem. Data resources stimulate innovation vitality by improving the innovation ecosystem value co-creation model; Promote innovation accelerating iteration, maintains efficient innovation etc to drive the continuous evolution of innovation ecosystem.

    A resilient innovation ecosystem can provide greater room for high-quality development. Therefore, it is of great significance to investigate how to improve the resilience of the regional innovation ecosystem. Based on the 2010-2019 Chinese co-application inventions and geographic information data, this study used the complex network methods and panel models to investigate how community dynamics affect the resilience of the regional innovation ecosystem. The results of this study showed that, under the impact of knowledge source risks, community evolution has an inverted U-shaped impact on the resilience of regional ecosystems. With the evolution of the community structure of “tight inside and loose outside” (close connection within the community and sparse connection between communities), the resilience of the regional ecosystem first increased and then decreased. It showed that when the “tight inside and loose outside” of communities increases from a low level to a moderate level, it is beneficial to reduce information transmission costs and transaction costs, increase social capital within the community, and thus have a positive impact on the resilience of the regional innovation ecosystem; but when the community structure dynamics is changed from a moderate level to a higher level, it will lead to “lock-in dilemma”, which will have a negative effect on the resilience of the regional innovation ecosystem. Therefore, the moderate level of community structure is more conducive to the improvement of the resilience of regional innovation ecosystems. Knowledge diversity positively mediates the relationship between community evolution and regional ecosystem resilience. The evolution of community structure further affects the resilience of regional ecosystems by directly affecting the knowledge diversity within the community. As the degree of “tight inside and loose outside” of the community increases, the knowledge diversity within the community will first increase and then decrease. We explain this phenomenon by investigating the learning mechanism within communities. Innovation community theory points out that the learning mechanism of the community has undergone a transition from “learning by localization” to “learning by specialization”. After entering the stage of specialized learning, innovation entities in the community will pay more attention to specific fields with strong technical similarities, which limits the development of knowledge diversification. Knowledge diversity is the guarantee that the innovation ecosystem has more alternative technological paths in the face of external shocks. Therefore, the change in the level of knowledge diversity from high to low will have an inverted U-shaped impact on the resilience of regional innovation systems. On the basis of existing research, this paper has investigated the mechanism by which community evolution affects the resilience of regional innovation ecosystems, and will further complement the research on the evolution mechanism of innovation ecosystems.The community structure of regions with higher levels of innovation performance or acting as knowledge fountains has a stronger marginal effect on regional innovation ecosystem resilience. Regional innovation ecosystems have different characteristics. The results of heterogeneity analysis showed that within the scope of the positive marginal effect of the inverted U-shaped in baseline regression, regions with a higher level of innovation performance or acting as knowledge fountains demonstrate higher marginal effects. This result explained the role of innovation capability and knowledge base in enhancing the resilience of innovation ecosystems and responded to existing research on the operating efficiency of regional innovation ecosystems. For policymakers, we propose that in the context of Chinese innovation ecosystem management, they should focus on how to get close to the “best balance point” in the evolution of the innovation community structure. Possible actions should be taken to monitor and manage the moderate turnover rate of community members in the regional innovation ecosystem.

Under the background of the strategy of cultural power, China actively encourages the construction of digital cultural industry innovation ecosystem to realize the value co-creation of all parties. However, the research on value co-creation in the innovation ecosystem of the digital culture industry lacks a unified analytical framework, and it is mostly based on qualitative methods. Based on this, this paper constructed a value co-creation mechanism model using the exploratory single-case analysis method in accordance with the research logic of "driving factors - behavioral patterns - co-creation results". Then, this paper adopted the fuzzy set qualitative comparative analysis method to explore the group path of realizing value co-creation. The results showed that the value co-creation of the innovation ecosystem of the digital culture industry is driven by six factors: market economy, value demand, cultural consensus, industrial policy, IP resources and digital technology. There are six behavioral modes of content creation, including channel docking, IP ecology, intermediary cooperation, technology empowerment and government-enterprise collaboration, so as to realize value acquisition, transmission, creation, value-addition, and cyclic iteration. The three factors that drive value co-creation are digital market-driven, new demand-driven and "content + technology" dual-wheel-driven under the strategy of cultural power. The three behavioral modes of realizing value co-creation are channel-connected content ecosystem mode, intermediary-supported content ecosystem mode and technology-enabled content ecosystem mode. This paper has not only expanded the analytical framework and research methods for this issue, but also will provide policy insights for the high-quality development of China's digital culture industry.

Improving the level of knowledge governance can effectively solve the problem of "stranglehold" and stimulate the innovation ecosystem to evolve to a higher stage. Based on the theory of collaborative governance and the "B-L" reaction model, this study established a four-dimensional co-evolution model composed of knowledge governance mechanism, knowledge governance willingness, knowledge governance configuration and knowledge governance performance, and used fsQCA to explore the configuration path of improving knowledge governance performance in innovation ecosystem. The results showed that (1) the technological advantages of high niche players can effectively promote the evolution of knowledge governance of innovation ecosystem to a higher level; (2) considering the technology potential difference to match the configuration results, it can accelerate the formation of the knowledge governance path of the innovation ecosystem with Chinese characteristics; and (3) balancing the effectiveness of core elements of knowledge governance can effectively promote the improvement of knowledge governance performance in the innovation ecosystem. This study has revealed the internal influence of different technology potential differences on the collaborative evolution of the knowledge governance of innovation ecosystem, and explored the internal mechanism of the configuration of various factors under different scenarios to improve the performance of the knowledge governance of innovation ecosystem, and it will provide theoretical basis and practical inspiration for the government to introduce relevant governance policies.

    With the development of the Internet and the emergence of platform firms, "platform economy" and "platform ecosystem" frequently appear in the public. To promote the development of the platform ecosystem, platforms are committed to innovation and therefore have made remarkable achievements. For example, Alibaba′s innovative businesses in the e-commerce business, cloud computing, and digital media have facilitated transactions and social interactions among lots of platform participants. Xiaomi′s IoT developer platform has cooperated with partners to build an innovative ecosystem and provided smart products and services to 68 million households worldwide. Apple′s iOS and Google′s Android platform ecosystems have attracted numerous developers and end users. Existing relevant researches focus on the definition, characteristics, opening strategy, competition strategy, and governance strategy, but lack of overview research on the topic of platform ecosystem innovation. It is difficult to fully understand the platform strategy to promote ecosystem innovation, which brings trouble to the practice and theory. It is necessary to comprehensively review and analyze the literature on platform ecosystem innovation to promote the flourishing of the innovative practice and theory of the platform ecosystem. 
    In this paper, the measurement and statistics of literature clarify the research situation in this field. From the descriptive statistics of the number of publications and published journals in the past years, it is concluded that this topic has a broad research prospect. The results of keyword co-occurrence and emergence detection by CiteSpace 6.1.R6 in 1964 literature show that: First, the keywords with the highest co-occurrence frequency at home and abroad are "ecosystem" and "innovation" respectively. Second, the highest intensity of keywords at home and abroad are "platform enterprise" and "business ecosystem" respectively, which are frontier topics. Furthermore, it sorted out some opinions of key literature and got such meaningful conclusions: First, platform ecosystem in the digital economy refers to a collection of innovative organizations that platform firms as the core connects lots of complementors and end users with digital technologies and standards. Second, from the perspective of the value creation mechanism, the platform ecosystem can be divided into transaction-driven and innovation-driven. Third, transaction-driven value creation follows the service-dominant logic. Platform participants interact in the integration of resources and design of matching rules, which drives the value co-creation of all parties. Innovation-driven value creation follows the value-adding logic, which refers to the platform sponsors providing boundary resources, including software toolkits, application program interfaces, rules, etc., to support the innovation of complements, so that they can create diversified products or services, and realize the value co-creation with the platform. Fourth, this paper summarizes strategies of ecosystem innovation promoted by these two platforms, that is, platform ecosystem innovation is driven by openness, competition, cooperation, and governance strategies. Alibaba′s retail and Xiaomi′s IoT developer platform ecosystems exemplify these strategies.
    Future research on platform ecosystem innovation can focus on the following three directions: First, research on platform ecosystem innovation can enrich the Chinese local context. From the view of the number of publications and journals, domestic research is falling behind foreign studies, while the platform economy in China has been developing rapidly in recent years. Given the inconsistency between theory and practice, it is a valuable direction for scholars to explore the unique source of value creation and the platform-enabled innovation strategies, and form the platform ecosystem innovation theory with Chinese characteristics. Second, some exploration is made to the mechanism of the relationship among openness, competition, cooperation, and governance strategies and their influence on innovation. For example, the interrelated policies, such as how platforms implement governance policies by determining the degree of openness, affect ecosystem innovation, is very worthy of discussion. The existing literature on platform strategies only discussed the direct influence on the platform ecosystem innovation but has not explored its impact path. Solving the mystery of the black box would clarify the mechanism of each strategy′s impact on innovation. Third, from the perspective of government scientific supervision, the strategies for maintaining orderly competition among various platform organizations and promoting the high-quality innovative development of the platform market are meaningful research topics. It makes sense to find methods to scientifically regulate the platform market, which are helpful to guide the high-quality development of the platform ecosystem under the new pattern from the macro level.

    Megaproject innovation has become an effective model of independent innovation in Chinese industry. This paper adopts the case study method, based on the general analysis framework of innovation ecosystem theory, and takes Shenhua Coal-To-Oil Indirect Liquefaction Demonstration Project of Four Million Tons Per Year as the case, to investigate the process of user enterprises leading the relevant parties under the common vision to participate in and cooperate in the realization of megaproject innovation in the way of innovation ecosystem. 
    The conclusion of this paper is that in the user-driven megaproject innovation ecosystem, the experience accumulation and participation ability of users enable them to promote the value creation activities as the orchestrator, collaborator and complementor. In the definition stage, as an ecological organizer, Shenhua defines requirements from the common vision of independent localization of major equipment and materials of coal-to-oil key technologies, so as to clarify the value creation content of each participant in the ecosystem. In this stage, the national leading mechanism is mainly in the design stage. As the ecological leader, Shenhua demonstrates the technology through pre-research and feasibility report. First, in the user-led innovation ecosystem of major projects, market approved conditional procurement and bidding, joint activities and coordination institutions established based on common interests are indispensable operating mechanisms. Second, user enterprises in megaprojects have dual identities: it not only bears the national strategic mission, but also represents the market foresight demand. Third, the experience accumulation and participation ability of users enable them to promote the value creation activities as the arranger leader, collaborator and complementor.
    In this stage, the market mechanism is mainly in the construction stage. As an ecological synergist, Shenhua integrates the advantages of the participants in the ecosystem to realize the project-oriented resource integration. This stage is mainly the ecological mechanism. In the commissioning stage, as an ecological complementor, Shenhua solves the challenges in the commissioning process through the technological innovation activities of complementary suppliers and complementors. In this stage, the ecological mechanism mainly needs to be explained. Due to the large scale and complex process of the project and the difficulty of collaboration, the mechanisms used in the life cycle of the project are often overlapping and repeated. In general, different phases of the construction mechanism have different focus.
     In terms of theoretical contributions, this paper puts forward the theoretical framework of user-driven innovation ecosystem, and analyzes the case of megaprojects. Based on this theoretical framework, two findings are drawn: First, in the innovation of complex product systems such as megaprojects, the unique application scenarios and process requirements of end users are conducive to the demonstration of megaproject design, organize and implement, and accelerate the innovation process of system participants, especially supplier groups. This is reflected in the ability of leading users to be the first to obtain market access qualifications and lead core technology suppliers with their accumulated experience and capabilities in open innovation cooperation. The joint actions of complementary technology providers based on a common vision not only increase the possibility of users adopting domestic technologies and products, but also provide market opportunities for domestic suppliers to develop and apply new products. It is a value creation activity based on symbiotic relationship, and then drives the co-evolution of relevant participants in the domestic industrial innovation chain with systematic value creation. Second, in the innovation ecosystem of megaprojects, end users bear dual missions. In megaprojects, end user enterprises are often central or state-owned enterprises, which shoulder both the public mission of the government and the market interests of enterprise users. End-user enterprises play the role of system integrator, and the government has a strong guiding role in ecological formation and joint cooperation. Its measures to promote scientific and financial support in the localization of market access conditions directly affect whether end-user enterprises can form an ecosystem around megaprojects and create value. 
     This paper has promoting significance for the practice and theoretical research of the organization of megaproject innovation. As a megaproject bearing public mission, it has increasingly become an important way to make breakthroughs in industrial technology. How can megaproject technologies and products built by users spread quickly and achieve market benefits? In the early stage, demand incentive measures such as government procurement targeted subsidies given by the government will help the diffusion and application of industrial technology.

Under the uncertain environment, excellent groups try to achieve sustainable development through innovation ecology optimization and upgrading. However, faced with the risks that may be brought by the dynamic environment, we have not yet found an effective solution to how to build a matching innovation ecology and maintain the dynamic balance of innovation ecology. This paper conducted an exploratory singlecase study on the innovation ecology evolution of parent company as designers of the innovation ecosystem, and refined the construction process and evolution logic model of the innovation ecosystem at different development stages. Our findings revealed that: The construction and evolution of the groups′ innovation ecosystem is influenced by the relationship tension caused by changes in the institutional environment and resource endowment. At different development stages, parent company constructs a matching innovation ecosystem by adopting various specific mechanisms to cope with the relationship tension between the parent company and its subsidiaries, and between the parent company and other subjects. Ecological niche change is the evolutionary logic of the group innovation ecosystem. At different stages, the parent company respectively promotes the continuous upgrading of the innovation ecosystem through the evolutionary logic of niche translation, niche translation and shift, and niche shift. The conclusions of the study will provide a reference for group companies to think about the development path based on the construction of the innovation ecosystem and enhance the resilience of the organizational structure to cope with uncertain environment.

   How to use digital innovation ecological organizations to empower non-core enterprises in marginal ecological niches to reverse their marginal status and achieve cross-industry innovation development is an important theoretical and practical issue for widely gathering enterprise strength and developing new quality productivity. However, existing research mostly focused on the impact of digital technology on cross-border innovation, lacking attention to the affordance of digital innovation ecosystem organizations formed on digital technology. Based on the classic framework of affordance theory and the "architecture, strategy, environment" organizational theory, this study used the fs/QCA analysis method to explore the multiple paths through which the affordance of digital innovation ecology empowers non-core enterprises to achieve cross-industry innovation. The research found that digital innovation ecosystem organizations can provide action potential for the realization of corporate strategic visions, but non-core enterprises on the edge of the ecosystem cannot achieve cross-industry innovation solely through a single dimension of affordance. It is necessary to combine the availability of digital technology architecture, the availability of the digital innovation ecosystem environment, and the multidimensional strategy of digital innovation strategy to support non-core enterprises in exploring the potential of cross-industry technology grafting and transforming it into effective actions to achieve cross-industry innovation goals, including two dominant logics and four sub-paths: digital distribution availability (discrete knowledge type, dynamic alliance type) and digital recombination availability (dislocation recombination type, fission recombination type). The research conclusion will contribute to the theoretical integration of the affordance of digital innovation ecology and cross-industry innovation research, and provide practical inspiration for non-core enterprises to achieve cross-industry innovation leap.

Emerging innovation ecosystems, such as those based on artificial intelligence foundation models, are rapidly taking shape. Unlike traditional industry innovation ecosystems, architects in these new ecosystems must navigate both positive and negative impacts of technological innovation during the experimental and exploratory phases of ecological construction. Further investigation is required to understand the formation mechanisms and governance strategies of these emerging industry innovation ecosystems. This paper employed a longitudinal case study approach, focusing on OpenAI, a leading research and development organization, to distill general patterns in the formation of emerging industry innovation ecosystems from the architect's perspective. It also delved into the varied governance mechanisms employed by architects within industry innovation ecosystems. The study revealed that: first, in the initial exploration phase, architects clarify technical objectives through open architecture and extensive testing of various technology pathways; second, during the development breakthrough phase, architects achieve a comprehensive technology layout by leveraging collaborative architecture, making focused investments in selected technology routes, integrating internal technology governance, and embracing public oversight; and third, in the continuous growth phase, architects enhance joint industry governance and engage in governmental governance activities by integrating architecture and accelerating the construction of innovation ecosystems, thereby reinforcing the legitimacy of ecological development. This paper constructed a "structure-conduct-governance-performance" (SCGP) process model, identified multiple governance mechanisms, including technology governance, public supervision, industry governance, and participation in government governance, and advanced research on the formation mechanisms of emerging industry innovation ecosystems. It will hold significant implications for research and development organizations aiming to achieve breakthroughs in emerging technologies and expedite the development of emerging industry innovation ecosystems.

     Knowledge fusion is critical for increasing firm productivity and its innovation competitiveness, and an innovation ecosystem is a critical organizational environment for achieving knowledge fusion. The value propositions in the innovation ecosystem with different value goals are heterogeneous, resulting in significant differences in knowledge fusion paths. Regrettably, however, previous literature has rarely investigated it, leading to a misunderstanding of knowledge fusion, which leads to idle knowledge, invalid fusion and reverse fusion of knowledge. As a result, to reverse the current low level of knowledge fusion in an innovation ecosystem, it is critical to investigate the knowledge fusion paths in an innovation ecosystem.
    Based on the Organizational Symbiosis Theory and the perspective of value proposition heterogeneity, this paper followed the "subject-network-environment" logic and investigates the configuration of knowledge fusion in the technology-dominant and the market-dominant innovation ecosystems. This study employed the survey data from firm-level innovation ecosystems in China, including information technology, intelligent manufacturing, electronic communication, college and technology incubator. A sample of 272 valid questionnaires was drawn from the above organizations, all of which have experiences with knowledge fusion within two types of innovation ecosystems. The configuration relationship was tested using the fuzzy set qualitative analysis (fsQCA) method. 
    The results show that the technology-dominant innovation ecosystem has two knowledge fusion configurations and the market-dominant innovation ecosystem has three knowledge fusion configurations. There are general and special configurations, and further comparative analysis revealed that the two types of innovation ecosystems′ core conditions for high-level knowledge fusion differ, as do the matching and substitution relationships between the conditions. The "focal firm-led" and "actors-network-environment linkage" characteristics of the technology-dominant innovation ecosystem can be summarized. The two paths have different conditions, but they both emphasize high-level knowledge integration. The integration is primarily dependent on the focal firms′ breakthrough improvement in their independent innovation capability. The driving paths of market-led innovation ecosystem driving high-level knowledge fusion can be summarized as "environment-driven", "complementary depending on actors′ ability", and "main actors′ ability-network-environment linkage-type". Although the conditions of the three paths are different, they all emphasize that a high degree of knowledge fusion is primarily driven by complementary actors, innovation networks and exogenous driving forces from the external environment. The general configurations of knowledge fusion of technology-dominant and market-dominant innovation ecosystem are "subject-network-environment linkage-type", but the core conditions differ from the marginal conditions, indicating that knowledge fusion is affected by cross-level multi-factors, but the importance of antecedents to produce a high degree of knowledge fusion differs due to the different value orientations of the innovation ecosystem.
    The findings enrich and strengthen related research on the antecedents and conditions of knowledge fusion in the innovation ecosystem from the perspective of heterogeneity value goals, allowing enterprises and governments to develop targeted innovation strategies, deepen cross-domain knowledge integration, and achieve high-quality innovation development. This paper reminds managers that when some of the conditions are missing or immature, they can compensate and balance by strengthening other conditions as much as possible, thus they must pay close attention to scientific matching and adjustment.