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The purpose of this paper is to analyze the symbiotic evolution decisions of digital innovation enterprises, research institutes and the government in the digital innovation ecosystem.

Based on innovation ecosystem theory and an evolutionary game model, this study constructs a tripartite symbiotic evolution game model of digital innovation ecosystems with digital innovation enterprises, research institutes and the government as the main bodies and analyzes the influencing factors as well as the evolution paths of the different behavioral strategies of each subject through numerical simulation.

The research shows that the digital innovation ecosystem has the characteristic of self-organization, which requires the symbiotic cooperation of each subject. The government plays an active role in any stage of symbiotic evolution, and the system cannot enter symbiosis under a low level of subsidies and penalties. Only when the initial willingness to cooperate of digital innovation enterprises and scientific research institutes is at a medium or high level is the system likely to become symbiotic. While digital innovation enterprises are more sensitive to government subsidies and punishments, scientific research institutes are more sensitive to the distribution proportion of cooperation income.

This study includes government regulation into the research scope, expands the research mode of the digital innovation ecosystem and overcomes the difficulties of empirical research in collecting dynamic large sample data. It vividly and systematically simulates the symbiotic evolution process of the digital innovation ecosystem, which provides a theoretical and practical reference for digital innovation ecosystem governance.

Innovation ecosystems consist of independent and yet interdependent enterprises and actors. This constitutes a challenge for innovation leadership to set the direction to pursue UN SDGs. Enhanced insights and understandings of how collaborative innovation leadership can be conducted in practice are revealed in two cases conducted using a participatory action research approach. Hereby theory and practice are linked by the ecosystem participant actions to reach competitiveness of the offshore wind energy ecosystem compared to traditional/other renewable energy sources pursuing UN SDG number 7 of ‘affordable and clean energy’. The two cases are situated in ports in offshore wind energy innovation ecosystems, respectively in the Baltic Sea and in the North Sea. The first case contains complementary ecosystem participants with both leadership and expert positions. The second case contains both complementary and competitive ecosystem participants with leadership positions. The findings note that both cases can use collaborative innovation leadership through the point of origin in the guiding star of the value proposition at ecosystem level to go beyond their own enterprise self-interest. Next, collaborative innovation leadership is based in heterogeneities of both knowledge domains and individual and organisational behaviours for the innovative imagination of future needed initiatives for collaborative design-based sensemaking. A short-term challenge is present from reduced revenue in own enterprise from future needed initiatives. This short-term impact needs to be addressed for enhanced long-term robustness. The findings are summarised in a model for dissemination of collaborative innovation leadership in ecosystems to pursue UN SDGs in practice.

In the digital economy era, digital platforms are vital infrastructure for innovation subjects to perform digital innovation activities. Achieving efficient and smooth knowledge transfer between innovation subjects through digital platforms has become a novel research subject. This study aims to examine the knowledge transfer mechanism of digital platforms in the digital innovation ecosystem through modeling and simulation to offer a theoretical basis for digital innovation subjects to acquire digital value through knowledge-sharing and thus augment their competitive advantage.

This study explores the optimal symbiotic interaction rate between different users based on the classic susceptible-infected-removed (SIR) model. Additionally, it constructs a knowledge transfer mechanism model for digital platforms in the digital innovation ecosystem by combining the theories of communication dynamics and symbiosis. Finally, Matrix Laboratory (MATLAB) software is used for the model and numerical simulation.

The results demonstrate that (1) the evolutionary path of the symbiotic model is key to digital platforms' knowledge transfer in the digital innovation ecosystem. In the symbiotic model, the knowledge transfer path of digital platforms is “independent symbiosis—biased symbiosis (user benefit)—reciprocal symbiosis,” aligning with the overall interests of the digital innovation ecosystem. (2) Digital platforms' knowledge transfer effects within the digital innovation ecosystem show significant differences. The most effective knowledge transfer model for digital platforms is reciprocal symbiosis, whereas the least effective is parochial symbiosis (platform benefit). (3) The symbiotic rate has a significant positive impact on the evolutionary dynamics of knowledge transfer on digital platforms, especially in the reciprocal symbiosis model.

This study's results aid digital innovators in achieving efficient knowledge transfer through digital platforms and identify how symbiotic relationships affect the knowledge transfer process across the ecosystem. Accordingly, the authors propose targeted recommendations to promote the efficiency of knowledge transfer on digital platforms.

Small and medium-sized enterprises (SMEs), typically with limited resources, strive hard to obtain the trust of ecosystem participants as an orchestrator. Accordingly, the firms do not have sufficient legitimacy to persuade other parties to join their networks. This study aims to investigate how an SME operating in the publishing industry orchestrates ecosystem participants. In particular, the study analyzes how the orchestrating firm stimulates interactions among ecosystem participants.

Case study research with a qualitative approach has been documented as a well-accepted method for investigating complex phenomena and for theory building. Collected data from various informants and different collection techniques are triangulated to ensure validity. Cross-case analysis to identify common patterns is undertaken as the basis for developing a sound conclusion.

The study demonstrated what orchestrating firms should do to foster innovations and how they benefit from other participants in the ecosystem. The analysis identified the orchestrator's four roles: entrepreneurship networks, knowledge activation, innovation intermediary and network leadership. Among the four roles, there are interrelationships, and to some degree, these overlap. The orchestrating firm must emerge into the ecosystem and work together with all members of the ecosystem. Managers of the orchestrating firm and network members should collaborate to find the most beneficial configuration for all ecosystem participants.

This research is limited to the knowledge-intensive publishing industry. The use of specific industries closely related to innovation provides an advantage in the way that enables researchers to conduct depth analysis, but at the expense of generalizability, and therefore, future research can analyze different industries.

This study focuses on networks as the unit of analysis. Previous studies assumed individual firms as the unit of analysis and ignored the fact that companies interact with other companies when pursuing open innovation. The study focuses on the interactions between actors as the unit of analysis and on the role of orchestrators undertaken by an SME.

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.

This article aims to understand the dynamics between disruptive innovations and innovation ecosystems, using disruption business models as a catalyst.

This study presents an integrative literature review and a theoretical framework in order to integrate the theories of disruptions and ecosystems.

The dynamics of disruptive innovation, within an ecosystem, as an essential driver of creating new markets. The effect of creative destruction from a disruption influences business models in a coopetitive dynamic that drives the ecosystem as a whole.

Limited to theoretical research and suggested the application of the proposed model in an empirical study.

Understand the formation of new ecosystems based on the occurrence of a disruption as a way for organisations to prepare for the arrival of this new market.

The contribution of this study is based on joining the literature of disruptive innovation and innovation ecosystem, pointing to a theoretical framework and a flow of Evolution and Adaptation to the Disruptive Ecosystem that integrates this complex dynamic.

Although there is a growing body of literature on the benefits of innovation ecosystem participation for keystone/focal firms, there are limited studies on what motivates or impedes other actors’ participation (i.e. suppliers and complementors) in collaborative innovation. Hence, this study aims to address the root causes of collaborative innovation failure and develop a better understanding of the hindering factors for the generation of collaborative innovation performance in ecosystem-based manufacturing.

This study adopted a qualitative research study with 45 managers involving an online survey with open-ended questions followed by an expert focus group with seven managers from a UK-based high value manufacturing ecosystem. Data analysis and coding followed a highly iterative process using a thematic analysis approach.

This study identified six common barriers to collaborative innovation from the perspective of supplier firms. Particularly, this study found unique impeding factors in relation to revealed and deterring barriers in an ecosystem-based manufacturing context. This paper argues that suppliers and small- and medium-sized enterprises not only require financial support but also need to develop a strategic mindset, confidence, effective partnerships and knowledge about risks and returns to participate in collaborative innovation.

The extant literature identifies the motivations for joining innovation ecosystems and the prominence of value co-creation activity from the perspective of focal firms or orchestrators. However, this study offers insights into the need for an effective value co-appropriation setup amongst the ecosystem actors including suppliers. Importantly, this study proposes that effective value co-appropriation is essential for making collaborative innovation happen in manufacturing ecosystems.

Innovation ecosystems face many environmental challenges. The literature review shows that innovation ecosystems accelerate innovation activity, but empirical studies have not provided enough case studies focusing on the minimum-waste business strategy as one aspect of the circular economy. Various forms of interaction between members occur in the innovation ecosystems, which determines the level of cooperation. This paper aims to show the structure and forms of cooperation in an innovation ecosystem using the Czech Hemp Cluster (CHC) and its surroundings and suggest research directions in the field of interaction between members in an innovation ecosystem. Although hemp is associated with the production and distribution of narcotics, it is a versatile plant supporting the minimum-waste business strategy.

The research is based on a theoretical part of a literature review of major scientific articles on innovation ecosystems from 2016 to 2021. The case study of the CHC and the hemp ecosystem is based on qualitative research in the form of a content analysis of the mission of the cluster members. In addition to content analysis, the classic multidimensional scaling method and hierarchical cluster analysis were used to reveal ecological guilds.

The case study highlighted the specific relationship between the cluster and the ecosystem. The cluster does not determine the ecosystem boundaries, but the ecosystem is a much broader system of cooperation and interaction between organisations. Clusters emerge after an ecosystem has existed for a particular time to coordinate collaboration and information between organisations and stakeholders. The analysis of the CHC revealed the specific role of non-profit organisations (NPOs) in the innovation ecosystem. NPOs are not engaged in primary functions in the value chain, but they provide supporting activities through coordinated networking, disseminating information on innovation, awareness-raising and stakeholder education. Compared to natural ecosystems, innovation ecosystems are typically characterised by higher forms of collaboration between members.

An exciting opportunity for research on innovation ecosystems is the ecological guilds taken from natural ecosystems and whose identification can help define the boundaries of innovation ecosystems. An opportunity for further research is the comparison of NPO-based and government-based clusters playing a central role in developing innovation ecosystems. Regarding the problematic generalisability of the case study to the entire agricultural production, a challenge is a search for minimum-waste business models in agriculture characterised by the biological nature of production.

Theoretical and empirical studies have not yet considered innovation ecosystems in the minimum-waste context to a sufficient extent. The paper builds on previous scholarly studies focusing on innovation ecosystems and, for the first time, discusses the role of NPOs in the innovation ecosystem. The CHC case study adds a suitable minimum-waste business model to the still very scarce literature on sustainable innovation ecosystems. The article discusses the purpose and forms of cooperation in an innovation ecosystem, identifies a complementarity of roles in the innovation cluster and describes the interrelationship between the cluster and the ecosystem. Discussion of the ecosystem leader in the cluster-based innovation ecosystem shows the differences between Czech, Polish and German life science ecosystems.

The purpose of this study is to discuss how organizations can drive organizational performance through human capital (HC) investment through systematic thinking.

This study analyzes three companies from various industries, adopts systems thinking and uses three leading indicators from the balanced scorecard framework to explore the effects of strategic orientations for HC on innovation ecosystems and organizational performance.

In terms of academic contributions, this study broadly verifies the innovation ecosystem model for organizations and reveals that customer-oriented, internal process-oriented and innovation learning-oriented HC strategies reinforce the pathways in organizational innovation ecosystems, thereby enriching the literature on innovation ecosystems.

In terms of practical contributions, this study provides a novel HC-based perspective on developmental dynamics and details the relationships among each aspect of the innovation ecosystem and HC strategies.

The proposed architecture and strategic frameworks provide a reference for corporations to implement strategic orientations of HC, drive operations in organizational innovation ecosystems and improve organizational performance.

With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.