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This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

Building on the theory of resource-based view (RBV), this paper is determined to explore the key drivers that drive platform ecosystem adoption by small businesses and mediation mechanisms that facilitate the translation of these drivers into improved firm financial and nonfinancial performance.

In this study, structural equation modeling is used to analyze the data. A survey questionnaire was taken from 430 small businesses operating their businesses on various digital platform ecosystems in China to investigate the links between parameters by testing hypotheses. Digital startups operating their businesses on popular Chinese platform ecosystems, including Alibaba, Taobao, Jingdong, Maituan and HelloChe, were chosen.

The finding deciphers a nuanced interplay of the adoption drivers, with innovation capability emerging as a mediation mechanism translating these drivers into improved financial and non-financial performance.

The acknowledgment of potential drawbacks, such as the focus on specific drivers of platform ecosystem adoption, highlights the need for future research to explore additional factors that may influence adoption decisions. By examining institutional factors, market conditions or external shocks like the COVID-19 pandemic, researchers can provide a more comprehensive understanding of the complexities surrounding platform ecosystem dynamics and offer insights into adaptive strategies for businesses facing uncertainty.

The outcome benefits policymakers and ecosystem designers by creating and overseeing platform ecosystems that support the highlighted drivers. This study further serves as a roadmap for both platform owners and prospective small enterprises as they map their path toward the digital frontier.

The findings from the research indicate that small enterprises that embrace platform ecosystems can experience improved financial and non-financial performance, which in turn promotes economic development and the generation of jobs. By utilizing innovative strategies and maximizing their strategic advantages, these enterprises can not only prosper but also make significant contributions to community development and help alleviate joblessness. This highlights the significance of assisting with the incorporation of digital technology in small businesses to achieve wider societal advantages.

Research originality lies in bridging the gap between strategic inputs and measurable outcomes, stressing the vital function of a firm’s innovation in turning ecosystem-driven opportunities into enhanced performance. This means the pivotal role of this study lies in exploring platform ecosystem adoption drivers based on the theory of RBV and the way innovation capability of platform ecosystems facilitates the translation of these drivers into improved financial and nonfinancial performance.

The link between theory and practice in innovation studies still has some gaps, despite scholars’ efforts to illustrate and identify them in real-world situations. To fully understand the dynamics of the innovation ecosystem, it is crucial to consider key actors and their roles and recognize their impact on ecosystem outcomes. Therefore, this paper seeks to discuss how analytical structures of innovation ecosystems address the dynamics of actors and their contribution to the ecosystem outcomes.

A research protocol was developed to query the Web of Science database to identify analytical structures of innovation ecosystems based on pre-established criteria.

The dynamics of actors interfere with their contribution to value creation. That is, the actor changes his contribution. Therefore, depending on the ecosystem's value proposition, the activities and dynamics of the actors change over time.

It contributes to advancing the discussion of innovation ecosystems, addressing insights into the dynamics of actors in different analytical structures. The essay proposal considers innovation ecosystems' evolutionary aspects, value propositions and exchange. In addition, the importance of orchestration in the various stages of the ecosystem is highlighted.

The objective of this article is to analyze the mediating role of innovation capability—both radical and incremental—between technological turbulence and digital innovation ecosystem performance, considering the impact of cross-organizational knowledge sabotage. Despite the enthusiasm surrounding digitization, the high failure rate (80%) of digital transformation projects has received limited attention. This alarming statistic indicates a potential rise in opportunistic behaviors within organizations. We hypothesize that employees seeking to reduce the risk of being displaced by digital technologies, may not only hide knowledge, as previously observed, but also engage in knowledge sabotage by disseminating inaccurate information during the co-creation of digital innovations within the digital innovation ecosystem.

The study employed structural equation modeling to examine moderated mediation using survey data collected from 148 firms, mainly from sectors of high to medium levels of digital intensity.

The most significant finding indicates that cross-organizational knowledge sabotage considerably reduces the only mediating effect, namely that of incremental innovation capability.

Our study presents a novel perspective by investigating the phenomenon of cross-organizational knowledge sabotage. Unlike prior research, which primarily identified the existence of knowledge hiding, our findings suggest that employees are not only willing to withhold information but also to disseminate inaccurate information to external partners. Consequently, our research extends the boundaries of the existing knowledge field by demonstrating that cross-organizational knowledge sabotage has repercussions that extend beyond intra-organizational impacts, as previously recognized. It also adversely affects the outcomes of collaborative work within the digital innovation ecosystem.

This research intends to analyze the innovation ecosystem factors that play a vital role in firm performance. As a result, large-scale empirical studies on the innovation ecosystem are rare, and fewer efforts have been made to determine if and how different factors affect the ecosystem models of firms. There has yet to be a substantial empirical study on the innovation ecosystem.

Data were acquired from Pakistani IT companies. The results show that factors of the innovation ecosystem significantly contribute to business performance. The essential assumption is that resource endowment, organizational culture, knowledge and competence, and technology capability are allied to the innovation ecosystem.

The findings are crucial from a managerial view because firms must focus on changing their innovation ecosystem factors model to achieve greater performance. Radical changes in the firms will only be worthwhile if they value their resource endowments. To attain superior firm performance via influential factors of the innovation ecosystem, IT administrators need to build organizational cultural capacities to adapt to changes brought on by digitization quickly and effectively. However, this must be supplemented by improving organizational knowledge, competencies and technological capabilities to enable organizations to modify their ecosystems.

Eventually, firms can better respond to changes in their settings if they combine these variables by implementing an effective innovation ecosystem model, which leads to greater sector and superior financial performance.

With the widespread penetration of digital technologies, disruptive innovation is not developed by a single firm but is increasingly achieved by an ecosystem. However, limited research has examined the mechanisms involved in achieving disruptive innovation in the context of digitalization and ecosystems. To address this gap, we explore the impact of three dimensions of specialized complementary assets (SCAs) within the innovation ecosystem, human capital SCA (HCSCA), production SCA (PSCA) and marketing SCA (MSCA), on disruptive innovation in core firms through the mediation of digital capability, comprising digital operation capability (DOC) and digital resource collaborative capability (DRCC). Furthermore, innovation ecosystem embeddedness is examined as a moderator between digital capability and disruptive innovation.

Survey data were collected from 234 core firms in China’s high-tech industry. Hierarchical regression, AMOS, and PROCESS tools were used to examine the data.

The results reveal the following: (1) HCSCA and PSCA positively affect disruptive innovation, while MSCA is negatively correlated with disruptive innovation. (2) Digital capability mediates the relationship between HCSCA and disruptive innovation, as well as PSCA and disruptive innovation. However, it suppresses the negative impact of MSCA on disruptive innovation. (3) Innovation ecosystem embeddedness strengthens the influence of DOC on disruptive innovation, but weakens the influence of DRCC on disruptive innovation.

The findings advance the knowledge of disruptive innovation, SCAs within the innovation ecosystem, digital capability and innovation ecosystem embeddedness. They also provide practical insights into the effective implementation of disruptive innovation.

This study aims to map and assess the conceptual development of the innovation ecosystem literature.

A bibliometric analysis was performed using the VOSviewer, RStudio software, Bibliometrix and Biblioshiny packages. To accomplish this, 367 publications published between 2006 and 2020 and indexed in the Web of Science and Scopus databases were assessed.

The results demonstrate a rise in research during 2016, with almost 30% of publications concentrated in only six journals. The co-citation analysis presented four clusters: case studies, business and innovation ecosystems (platform approach), open innovation and national and regional innovation systems (territorial approach). We proposed a theoretical framework based on two approaches in the innovation ecosystem literature based on co-citation analysis: platform, which has its roots in the literature on strategy, and territory, grounded in research on economic geography literature.

One of the limitations of the study is that only articles published in journals were analyzed, leaving out of the sample those published in congresses, books and other sources.

This paper contributes to the literature by presenting and clarifying the different conceptual trajectories of research in innovation ecosystems. We also proposed an analytical framework based on the two main approaches to innovation ecosystems – platform and territory. This framework presents the critical elements of managing innovation ecosystems from both perspectives.

Breakthrough technological innovation is of vital significance for firms to acquire and maintain sustainable competitive advantages. The construction of an innovation ecosystem and the interaction with heterogeneous participants have emerged as a new dominant model for driving sustained breakthrough technological innovation in firms. This study aims to explore the effects of collaborative modes within the innovation ecosystem on firms’ breakthrough technological innovation and the ecological legitimacy mechanisms involved.

The research employs data from 212 innovative firms and conducts empirical research using a two-stage structural equation modeling (SEM) and artificial neural network (ANN) analysis.

The results indicate that firm-firm collaboration (FF), firm-user collaboration (FU), firm-government collaboration (FG), firm-university-institute collaboration (FUI) and firm-intermediary collaboration (FI) all have significant positive effects on breakthrough technological innovation (BTI), with FU being particularly crucial. Furthermore, the results confirm the positive moderating effects of ecological legitimacy (EL) on the relationships between FF and BTI, as well as between FU and BTI. Conversely, EL has a negative moderating effect on the relationship between FUI and BTI, as well as between FI and breakthrough technological innovation. Additionally, EL does not have a significant influence on the relationship between FG and BTI.

Through resource dependence theory (RDT), this study unveils the black box of how collaboration modes within innovation ecosystems impact breakthrough technological innovation. By introducing ecological legitimacy as a contextual factor, a new research perspective is provided for collaboration innovation within innovation ecosystems. The study employs a combination of SEM and ANN for modeling, complementing nonlinear relationships and obtaining robust results in complex mechanisms.

Innovation is vital for sustainable regional development. Government is generally not a source of innovation per se, but the authors shows that by establishing and funding an industrial innovation ecosystem, it can create fertile conditions for research institutions to introduce innovative technologies into industry and for industry to introduce its gaps and needs to motivate and direct academic research. This paper aims to present a case study of the Jiangsu Industrial Technology Research Institute (JITRI) as a “triple helix” collaboration model engaging Industry-University-Research (IUR) institutions. The authors aim to provide a fresh perspective on constructing innovation ecosystems, promoting value creation and advancing the adoption of industrial technology.

Taking JITRI as a case study, this research examines its innovative approaches to interfacing with IUR organizations within China’s Yangtze Delta region. The authors propose a multilayered framework where JITRI serves as the core, facilitating the formation of a robust innovation ecosystem with diverse IUR entities.

This framework comprises three layers: core, platform and support. JITRI acts as the central nexus, binding these elements together and fostering a cohesive innovation ecosystem. By analyzing the operational mechanisms of the Jiangsu Provincial innovation system, the authors gain valuable insights into how JITRI bridges the gap between academia and industry. This facilitates the efficient commercialization of technologies. The success of the JITRI approach presents a compelling model for emulation by other provincial innovation ecosystems seeking to enhance their innovation capabilities.

This study enriches the ongoing conversation on innovation ecosystems, proposing novel avenues for further research. However, the field requires continuous monitoring through longitudinal studies. Given the long-term nature of such initiatives, the full impact of this approach might only be realized over several decades.

JITRI aims to create a robust and innovative provincial innovation ecosystem through its focus on IUR collaboration. This unique approach offers valuable insights and ideas for fostering the development of thriving innovation ecosystems in other provinces. These insights encompass new perspectives on innovation ecosystem development, value creation and industrial advancement.

This study pioneers the use of the JITRI system as a case study, offering valuable insights with potential application to innovation ecosystems across China and globally.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.