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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.

The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments.

Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle.

The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development.

Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

The purpose of this paper is to investigate three issues: how does an innovative search (local search and boundary-spanning search) impact firm innovation performance of latecomers; how does capability reconfiguration (capability evolution and capability substitution) mediates the relationship between innovative search and firm innovation performance; and how does the technological leapfrogging process (initial stage, following stage, synchronization stage and leading stage) moderate the relationship between capability reconfiguration and firm innovation performance.

A “resource-capability-performance” theoretical framework was developed to explore the relationships between local/boundary-spanning search, capability reconfiguration and firm innovation performance. The data were collected by sending out surveys to managers and employees in various industries in mainland China. These hypotheses were tested using structural equation models and hierarchical regressions.

The results showed that: innovative search has a direct causal relationship to capability reconfiguration; local search and boundary-spanning search are conducive to improve the innovation performance of latecomers; the impact of local search and boundary-spanning search on innovation performance is realized through the completion of mediating role of capability reconfiguration; there are differences in the path of local search and boundary-spanning search affecting the capability reconfiguration of enterprise innovation performance; and the relationship between innovative search, capability reconfiguration and enterprise innovation performance evolves with the enterprise in different stages of technological leapfrogging.

This study explores the relationship and the path of innovative search to firm innovation performance and analyzes the path difference between local search and boundary-spinning search, which enriches the research of organizational search and enterprise innovation. This paper reveals the whole path of innovative search affecting innovation performance, discusses the important role of capability reconfiguration and makes incremental contributions to dynamic capability theory. It studies the evolution of innovative search on innovation performance under the background of technological leapfrogging, which provides a new perspective for the study of organizational search and capability-based theory.

This paper aims to investigate how the relationships among the different actors within the business networks affect the evolution of innovation along the different steps of technology life cycle.

The study is supported by a longitudinal case study referred to a mechanical company operating in the knitting machineries industry. A triangulation method integrating multiple data sources in a multiple method design was used to gather data.

The longitudinal study supports the idea that interactions among the actors within the business networks heavily influence the technology evolution.

Although the longitudinal case study reported in this paper refers to a period of time of about 10 years, our findings refer only to a single case study in a specific sector and so they cannot be generalized.

This paper provides important guidelines on how to manage the relationships emerging within a business network to influence the new technologies development.

The paper contributes to business networks literature, filling the gaps about how the relationships among the actors involved in a network can evolve over time and influence the evolution of technology in itself.

Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity.

Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity.

The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks.

This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

This paper aims to analyze the evolution and interaction over time of the functions of a technological innovation system (TIS) based on the concept of an innovation motor.

It is a case study of the innovation system associated with the technology for producing cage-free pullets for laying eggs in Pelotas/Rio Grande do Sul (RS).

The motors proposed by the TIS approach evolve sequentially and are associated with cumulative causality mechanisms. The study's results identified two functionalities: analysis of the chain as a whole and coordination of the actors involved in the system. The study's results also identified the presence of inflection points at the beginning of each of the motors.

The absence of a more accurate detailing of the market motor in discussions of the evolution of the motors and functions of TIS cage free Pelotas.

Innovation Motors as a new guiding approach for participatory innovation initiatives in rural areas.

Application of the TIS approach in agribusiness and proposition of two new functions for motor analysis, in addition to including inflection points as activation triggers in the evolution between motors.

The paper aimed to summarize innovative rules of Chinese manufacturing enterprises, and put forward some insights in optimal allocation of innovation resources and enhancing the capability of indigenous innovation, so as to overcome the innovation dilemma.

Having diagnosed the current research of innovation flows, the authors defined the concept and stated characteristics of mainstream and new‐stream innovation. Innovation life cycle theory and technology trajectory theory were used to map two evolution patterns of mainstream and new‐stream innovation. It took weeks to stay in firms to obtain original data and interview managers, engineers, and mechanists. From the case study the authors proposed the improvement projects and opportunities for firms to overcome the “innovation dilemma”.

In the indigenous innovation process, enterprises should breed new‐stream innovation as they strengthen the mainstream innovation, view the new‐stream technology as the innovation direction, and fulfill the constant innovation in the convergent innovation and replace evolution process. Meanwhile, enterprises should take precautions both to expand and develop, and fulfill technology transition and innovation upgrade through convergent innovation. Furthermore, firms' convergent innovation, which will finally achieve the “projects‐talents‐products‐markets” collaborative innovation, should be clear about target market and project‐oriented, take the product as the carrier, and be committed to cultivate creative talents and innovative teams.

This paper enriches the existing theory on indigenous innovation by introducing the new concept of mainstream and new‐stream innovation. The findings would help firms to jump out from the innovation morass.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

This paper aims to address how an organization's multiple-dominant-logic system evolves as it grows and how does this evolution affect the way managers choose to balance ambidextrous innovation.

This paper adopts an interpretive and exploratory case study on the mechanism of how the multiple-dominant-logic system influences the decision of balanced ambidextrous innovation. Considering that the multiple-dominant-logic system will change with the development of a firm, this paper focuses on exploring how the evolution of multiple-dominant-logic system affects the way managers choose to balance ambidextrous innovation. The authors spent almost two years collecting data from M-grass Ecology and following the evolution and innovation through semi-structured interviews, archival data and observation. Then they set up a framework showing the influence mechanism by analyzing the data through a four-step process.

This research points out that an organization's multiple-dominant-logic system may change for several times in its growth. It provides a model for the evolution of a multiple-dominant-logic system. It confirms that firms' multiple-dominant-logic system is not immutable, but evolves with the change of the firm's internal resources and external environment. Also, it finds that under the influence of different multiple-dominant-logic architectures, mangers choose different ways to balance ambidextrous innovation. In this process, appropriate entrepreneurial bricolage plays a significant role in balancing ambidextrous innovation.

The findings offer some valuable insights for further research on dominant logics and ambidextrous innovation and hold important implications for managers making a decision.

The purpose of this paper is to build a symbiotic evolution model to analyze the symbiotic modes and dynamic equilibrium of mobile internet platform innovation ecosystem (MIPIE) in order to explore its evolutionary path.

From a symbiosis theory perspective, the authors studied the dynamic evolution stages and symbiotic mode of MIPIE. By adopting logistic model, the symbiotic evolution model of MIPIE is established. After calculating the steady conditions and equilibrium point of this model, numerical simulation was done with MATLAB software to illustrate the impact of symbiotic parameters on evolution path in this ecosystem.

The symbiotic evolution mode of MIPIE experienced parasitism, commensalism to asymmetric mutualism, and symmetry mutualism or independence. In given conditions, the dynamic evolution of MIPIE eventually tends to a steady equilibrium point. The evolutionary consequence of innovative subjects is not only determined by the natural growth rate, but symbiotic modes can also affect the evolutionary path. Different symbiotic modes result in different evolutionary paths.

Improved understanding of symbiosis in MIPIE could help policy makers to promote value co-creation and dynamic interests balance while facilitating the cooperation of others for successful platform ecosystem management.

The logistic model introduced here bridge theory and practice while establishing a stronger link between symbiosis theory and platform ecosystem management.