Review and Prospects of Green Innovation Ecosystems from the Perspective of Value Emergence

Abstract

With the rise of research on the integration of emergence theory and complex systems, value emergence has become a new model of value creation in green innovation ecosystems. Exploring the research status of green innovation ecosystems from the perspective of value emergence has become a research hotspot in the field of management science. Therefore, the purpose of this paper is to use bibliometric methods, explore the current research status of green innovation ecosystems from the perspective of value emergence, and, more importantly, provide a future direction for the integration of emergence theory into complex systems. In this paper, a search was conducted in the Web of Science and CNKI databases, with a time limit from 2009 to May 2023, and through further screening, 159 articles were collected, and CiteSpace software (CiteSpace.6.3.R1) was used for visualizing and exploring bibliometric networks. This study innovatively introduce the value emergence perspective in the context of green innovation ecosystems. The basic interaction, dynamic promotion, and feedback loop of value emergence are taken as the research framework, and the generation mechanism and dynamic evolution of the green innovation ecosystem are analyzed. Finally, three prospects for future research are presented: How do green innovation entities generate basic resources? How do digital transformation and dynamic capabilities promote emerging value? How do internal models and external identifiers promote feedback loops? This paper is highly important for promoting theoretical exploration in the field of green innovation research.

1. Introduction

From the perspective of value emergence, the study of green innovation ecosystems has become a hot topic in academic circles. The Chinese government has noted the necessity of coordinating and strengthening the coordinated promotion of green innovation ecology in different dimensions, such as technological innovation, innovation subjects, innovation mechanisms, and innovation applications. At the same time, the academic community has explored green innovation ecosystems from different perspectives. For example, Yun and Liu [1] investigated the evolution of the green innovation ecosystem from the perspective of environmental regulation, and Nylund, et al. [2] described the different evolution stages of the green innovation ecosystem from the perspective of multinational enterprises. In addition, with the rise of emergence theory and research into the integration of complex systems, scholars have gradually realized that the value of green innovation ecosystems is cocreated through multiparticipant interaction and resource integration [3]. However, existing studies on green innovation ecosystems have ignored the value that is generated by resource integration and interaction at different levels in the context of value emergence [4].

Combining the relevant studies on green innovation ecosystems from the perspective of value emergence plays an important role in explaining how a green innovation ecosystem can, as a whole, generate a system-level value. The academic community defines green innovation ecosystems as the expansion and upgrading of innovation ecosystems for research into green and low-carbon development. Research not only emphasizes the innovation-driven core and value creation attributes of innovation ecosystems but also advocates the ecological value and system concepts of green and low-carbon development. At the same time, the value emergence of green innovation ecosystems can maintain the ability to respond to the dynamic environment on the one hand and promote the production of multiple benefits, such as those for the economy and society, on the other hand [5]. Finally, by integrating relevant studies on green innovation ecosystems and value emergence, it can be found that the interaction between green innovation subjects forms the microbasis of value emergence from basic resource input to the entirety of the system. The interaction between each component of the green innovation ecosystem and the entire system forms the driving force behind value emergence. The high-level resources in the green innovation ecosystem feed back to the green innovation subject through the internal environment, and resources are subsequently exported into the external environment, to form the feedback of value emergence. There is a step-by-step relationship between the three processes. The results of the last process will become the initial value of the next process, and the value of the green innovation ecosystem will eventually emerge.

In view of the limitations of existing research, we seek to identify the knowledge structure and theoretical roots of the literature on green innovation ecosystems in the broader field of innovation and dig deeper into the relevant research on green innovation ecosystems from the perspective of value emergence. Specifically, this paper begins with a systematic review of the research status, and the concept of green innovation ecosystems mentioned in the current research is then summarized. On this basis, the theoretical analysis perspective of value emergence is introduced, a research framework for green innovation ecosystems is constructed from the perspective of value emergence, and a direction worthy of further inspiration and contributions from future research is presented.

2. Materials and Methods

2.1. Literature Source and Data Collection

The first step of bibliometric analysis is to gather the required metadata. This paper used CiteSpace to conduct a bibliometric analysis of the relevant literature on green innovation ecosystems. First, in terms of international literature collection, this paper used the core database of the Web of Science as the data source, using the so-called topic subject (TS) method. Considering the differences in different wording habits, the search was carried out with the search formula “TS = (innovation ecosystem AND green OR environmental OR sustainable OR cleaner OR circle economy)”. Second, with regard to Chinese literature collection, this paper used CNKI as the retrieval platform and limited the literature sources to the Peking University Core, Chinese Social Science Citation Index (CSSCI), and Chinese Science Citation Database (CSCD) using the same search formula, and 29 Chinese articles and 248 international articles were retrieved. The second step of bibliometric analysis was to screen the data; restrictions were applied to the year (documents published after 2009, and the search date was May 2023), document type (articles and review articles), and research area (Environmental Sciences Ecology and Business Economics). Finally, this paper selected the literature on the research topic by reading the abstracts and browsing the content, supplemented and screened the cocitation of the literature, eliminated the literature that deviated from the research theme, and ultimately obtained 159 Chinese and international studies (135 international articles and 24 Chinese articles).

2.2. Research Methods and Research Questions

CiteSpace was used for the data processing and visual analysis of the research results of a green innovation ecosystem, and quantitative analysis was used as the main research method. First, based on the analysis results of CiteSpace and with the help of Excel software (2021), the keywords, numbers, and journals of papers published in Chinese and internationally were statistically analyzed. Second, CiteSpace visualization technology was used to carry out cluster analysis on the basis of data preprocessing and cleaning, and two research directions were identified. Finally, by constructing the research framework from the perspective of value emergence, this paper analyzed the literature and proposed directions for future research to answer the following questions: (1) What is the current research status of green innovation ecosystems from the perspective of value emergence? (2) What gaps exist in existing research?

The research investigation plan is displayed in Figure 1.

2.3. Research Fields of Green Innovation Ecosystems

The number of publications published from 2009 to May 2023 is illustrated in Figure 2. Studies related to the green innovation ecosystem have gradually emerged since 2009, and the number of published papers has shown an overall upward trend, with a significant increase since 2016 and an explosion in 2022. This shows that research related to green innovation ecosystems has become the focus of current academic research. In addition, we can see that, with the deepening of scholarly research, the research focus has gradually shifted from research on system generation mechanisms to research on dynamic evolution.

Table 1. Statistics of published journals.

International Journal	Quantity	Chinese Journal	Quantity
Sustainability	64	Science and Technology Progress and Policy	4
Journal of Cleaner Production	22	Science and Technology Management Research	2
Business Strategy and the Environment	12	Nankai Business Review	1
Technological Forecasting and Social Change	10	Journal of Industrial Technological Economics	1
Technovation	6	Science of Science and Management of S. & T.	1
Journal of the Knowledge Economy	4	Studies in Science of Science	1
International Journal of Environmental Research and Public Health	4	Scientific Management Research	1
Journal of Business Research	2	Systems Engineering	1
Journal of Management	2	Operations Research and Management Science	1

shows the top 9 journals in terms of the number of publications published in both Chinese and internationally, and it can be seen that they are all high-quality journals, indicating that scholars pay great attention to related research on green innovation ecosystems, providing space for the discussion and development of this topic. At the same time, compared with the number of publications in the Chinese literature, the number of publications in the international literature was significantly greater. In addition, according to the keywords with the strongest citation bursts in Figure 3, compared with those at the international level, chinese research on a green innovation ecosystem started relatively late, with its focus on the past 6 years. At present, Chinese scholars are focusing on the composition and operation mechanism of the five-helix elements of the system, while international scholars’ research has experienced the generation and evolution of the system, and the current focus is on microlevel action mechanisms, such as collaborative innovation of industry–university–research institutions, which provides guidance for China’s future research.

3. Theoretical Tracing of Green Innovation Ecosystems from the Perspective of Value Emergence

3.1. Generation Mechanism of Green Innovation Ecosystems from the Perspective of Value Emergence

Holland regards value emergence as a unique value creation process that is formed by the interaction of participants in complex adaptive systems [5]. According to the theory of complex adaptive systems, participants cocreate the internal model of the system through basic interaction and promote the generation of higher-level emergence by adapting to changes in the external environment. At the same time, Zeng, et al. [6] proposed that, in the generation of green innovation ecosystems, the interaction between green innovation subjects constitutes the internal mechanism underlying the system. The microbasis of value emergence exhibits the same dynamic interaction process as the generation of green innovation ecosystems, and a higher level of value discovery is therefore expected [7]. Thus, exploring the generation mechanism of green innovation ecosystems from the perspective of value emergence is highly important [8]. According to Adner [9], the participants in a green innovation ecosystem can be divided into value creators and nondirect value creators. Value creators are companies that directly engage in green innovation activities, while nondirect value creators are other organizations that provide a key foundation for green innovation activities through the transfer of capital, information, influence, and other contents to the core business.

First, Fan, et al. [10] claimed that value creators adopt transactional links, collaborative links, complementary links, and competitive links. Four action forms, e.g., links, constitute the internal mechanism of the green innovation ecosystem. Among them, scholars believe that transactional and complementary links are interdependent and that green innovative enterprises acquire, develop, and share knowledge, information, and other developing resources through their upstream and downstream interactions with suppliers and complementors [11]. The simultaneous enhancement of these entities’ capabilities promotes the value emergence of the system [12]. Moreover, collaborative researchers believe that competition and collaborative links are interdependent and that the resources and skills of competitors are highly complementary and relevant. Therefore, the competitive and collaborative relationships among green enterprises serve not only as an incentive for system generation but also as a source of knowledge [13]. Second, Fan, Shan, Day and Shou [10] claimed that the role of nondirect value creators in green innovation ecosystems includes regulators, facilitators, influencers, and knowledge providers. According to social exchange theory, the green innovation ecosystem is a collection of multilateral participants whose engagement is built on the basis of value exchange and mutual benefit and does not rely on strict contracts to establish contact.

3.2. Dynamic Evolution of Green Innovation Ecosystems from the Perspective of Value Emergence

According to the theory of complex adaptive systems, a green innovation ecosystem involves complex interactions between innovation subjects and innovation processes and is powered by continuous evolution [14]. Scholars have used evolutionary game theory to explore the impact of green innovation agents on the dynamic evolution of a system [15] and analyzed the role of innovation activities in promoting collaborative innovation in green innovation ecosystems [16]. Similarly, value emergence, as a result of the self-organization process of the system, enables the evolution of new characteristics among green innovation agents and their basic interactions in the development of the green innovation ecosystem [17] and exerts an impact on the entire system. On this basis, Thomas, Autio and Gann [8] linked value emergence with the dynamic evolution of the innovation ecosystem, described it as a bottom–up collective evolution process, and identified four key processes: resource configuration, value discovery, collective governance, and contextual embedding. Therefore, from the perspective of value emergence, exploring ways of enhancing the emergence value of a green innovation ecosystem through the promotion of its dynamic evolution plays an important role in promoting its performance across dimensions.

First, in the evolution of green innovation ecosystems, resource configuration and value discovery both play roles in the dynamic promotion stage of value emergence. On the one hand, Peters [18] posited that, promoted by digital transformation and dynamic capabilities, the openness of resource configuration changes the building block mechanism of a system and provides a new environment for the next iteration of value creation. On the other hand, based on the complex characteristics of a green innovation ecosystem, the dynamic evolution of such a system can promote the emergence of a efficiency-oriented and generative value. Second, collective governance and contextual embedding in the evolution of a green innovation ecosystem influence the feedback loop stage of value emergence. On the one hand, Panico and Cennamo [19] claimed that collective governance includes the establishment of the rules and order of an ecosystem, which then determine the internal model of the green innovation ecosystem and balance standardization and diversification among green innovation entities within the system. On the other hand, Thomas and Autio [20] posited that contextual embedding guarantees the legitimacy and embeddedness of the green innovation ecosystem in a wider range of market, economic, social, and cultural identifications.

3.3. Research on Green Innovation Ecosystems from the Perspective of Value Emergence

In summary, research on the generation mechanism and dynamic evolution positively promotes the basic interaction, dynamic promotion, and feedback loop of green innovation ecosystems from the perspective of value emergence. The following theoretical traceability model is constructed and displayed in

Table 2. Theoretical traceability of green innovation ecosystem research from the perspective of value emergence.

Value Emergence	Generation Mechanism of the Green Innovation Ecosystems	Dynamic Evolution of the Green Innovation Ecosystems	Research on the Green Innovation Ecosystems
Basic interaction	Value creators (suppliers, collaborators, complementors, competitors) and nondirect value creators (regulators, knowledge providers, facilitators, influencers)	-	Value creators (suppliers, collaborators, complementors, competitors) and nondirect value creators (regulators, knowledge providers, facilitators, influencers)
Dynamic promotion	-	Resource configuration Value discovery	Resource configuration Value discovery
Feedback Loop	-	Collective governance Contextual embedding	Collective governance Contextual embedding

and Figure 4.

4. Research Agenda on the Generation Mechanism of Green Innovation Ecosystems from the Perspective of Value Emergence

4.1. Value Creators of Green Innovation Ecosystems

First, green enterprises share information flow and material flow with upstream and downstream enterprises and complementary enterprises of the supply chain in the system. Second, green enterprises deliver a variety of basic resources to the system by cooperating with partners (such as high-tech enterprises) and competing enterprises.

4.1.1. Transactional and Complementary Links

According to the theory of symbiosis, interdependence is a core structural feature of ecosystems [21]. By strengthening connections with upstream and downstream enterprises among complementary enterprises in the green supply chain, green enterprises can obtain innovation source power, such as the raw materials and complementary resources that they require, which can be regarded as different building block components and combined according to different needs, such as organizational tasks and goals [16]. The basic interactive goal is the realization of value creation through a green supply chain, green product generation, green process improvement, and green recycling [22]. Specifically, at the source stage, a green supply chain and green process improvement imply the integration of environmentally sustainable concepts into the product life cycle, with new building block components catering to changing trends in environmentally friendly materials [23], and when working with suppliers, the team’s internal initiatives also create a direct value. For example, with the support of team-level initiatives, green enterprises can not only retain customers but also expand their ecological business. Zameer, et al. [24] noted that, in the intermediate stage, the generation of new products with low energy consumption, which becomes the initial result of the formation of building block components, was the triggering factor for enhancing the competitive advantage of green enterprises. In the final stage, green recycling becomes an indispensable link in the reorganization of constructed components.

Unlike transactional links, complementors of green innovation ecosystems generally have no fixed dependence on green enterprises. The different types of complementors form a “central radiation” structure in relation to green firms [25]. Klein, et al. [26] noted that, in the formation process of a green innovation ecosystem, digital platforms provide services or products as the basis for attracting customers to achieve complementary innovation. In recent years, with the integration of real and digital economies, digital platforms have become a hot topic, and scholars are studying the complementary links of enterprises [27]. An internal platform refers to the collection of resources involved in the product development of enterprises. For example, Haier’s COSMOPlat platform provides services or products as the basis for attracting customers and complementors [28]. External platforms can attract many complementary products to enrich their own value [29]. For example, Taobao, Jingdong, and Pinduoduo can attract companies with complementary knowledge. This can enrich the green knowledge of complementary platforms and actively promote the sharing and exchange of green logistics knowledge [30].

4.1.2. Collaborative and Competitive Links

According to resource-based theory, green enterprises can obtain resources and capabilities that they lack, including R&D investment, personnel training, intellectual property rights, etc., from their collaborators [31]. On a practical level, science and technology enterprises in Zhejiang Province actively cooperate with SMEs that exhibit strong innovation drivers, as well as with various heterogeneous innovation entities positioned outside the firm’s boundaries [32], to improve regulators’ recognition of green enterprises and their low-carbon products in the green innovation ecosystem through the use of a green service system [33]. Theoretically, the premise of interdependence is that each member has advantageous resources for the realization of a certain value proposition. Scholars believe that collaborative innovation across industry boundaries with different types of enterprises is conducive to technological synergy and reduces the uncertainty of green R&D activities [34]. Collaborative innovation enables enterprises to absorb knowledge spillovers from different enterprises, particularly high-tech enterprises, which have the capacity to inject more intellectual capital into corporate green innovation [35]. Therefore, from the perspective of system flow characteristics, the deeper the collaboration is, the more effective the knowledge flow is. In a green innovation ecosystem, entities with specific network connections exchange knowledge resources, which forms the basis for continuous innovation iteration [36].

Within the framework delineated by transaction cost theory, the competition and cooperation relationships that exist among enterprises in green innovation ecosystems are complex. Some scholars regard competition as negative. Excessive competition between Yutong Bus and BAIC Group leads to excessive resource consumption in green product production, which drives green enterprises [37] and can even erode the green innovation ecosystem [38]. In addition, competitors’ attention to green innovation may pressure green enterprises to imitate that innovation [39]. Other scholars believe that too much collaboration may also be negative, as it can hinder common value creation. For example, if partners overly adapt to each other, green innovation is weakened, so a certain degree of competition is needed to promote basic interaction [40]. Therefore, the collaborative and competitive dynamics in the green innovation ecosystem affect the green innovation of enterprises, which again suggests that competition and cooperation serve as suitable research perspectives [14]. In response, scholars have proposed various solutions, such as managing value cocreators through embedded norms and rules and managing competitors’ access through infrastructure [41].

4.2. Nondirect Value Creators of Green Innovation Ecosystems

First, the basic interaction between green enterprises and knowledge providers (industry–university–research alliances) and influencers (government governance) promotes the generation of green knowledge and technology. Second, the basic interaction of green enterprises with regulators (general consumers and government governance) and facilitators (public media and financial institutions) promotes the commercialization of green products.

4.2.1. Knowledge Providers and Influencers

Scholars have noted that the combination of knowledge providers and influencers forms the basic interaction of green innovation R&D. As far as knowledge providers are concerned, interactions among enterprises, universities, and research institutions play a positive role in improving green innovation performance and achieving breakthroughs in key technologies [42]. In this stage, with the help of creative individuals and groups on the team, scientific research institutions generate a large amount of green innovation knowledge, thereby providing knowledge resources for the subsequent stage [14]. However, the generation of green innovation knowledge is affected by its own characteristics. The first of these is the characteristic of duality. Yang, Qi, Li and Wang [12] noted that there is a problem of low efficiency in the transformation of symbiotic resource inputs and proposed that government regulation can effectively prevent the opportunistic behavior of industry, universities, and research institutes. Long-term and effective collaboration among enterprises, universities, and research institutes should be promoted in the development of green intelligent technologies [17]. The second factor is spatial correlation. Economic geographers have demonstrated the significant spatial clustering of green innovation [43], which indicates that inter-regional innovation interaction increases the output of regional green innovation. A typical example is university technology transfer. Geographical proximity promotes the transfer of knowledge and technology from the University of Turin to industry and society [44].

In the case of influencers, the existing research has focused mainly on government attention, financial subsidies, and environmental regulations. First, government concern is an effective way of coordinating collaborative innovation among green innovation system participants [45]. The number of phrases and critical terms in government reports reflects the concerns of decision makers regarding public affairs. Then, the green collaborative innovation of various entities can be promoted [46]. Second, the impact of government subsidies on enterprise green innovation mainly occurs through three channels, namely, financial support, signaling, and resource acquisition [47,48]. Unlike top–down policy tools, the incentivizing of green enterprises through the above three approaches can reflect a combination of the actions taken by society, the business sector, and the government at multiple levels and sectors [49] to provide the necessary subsidies for enterprises to improve their level of green innovation R&D. Finally, the study revealed that different environmental regulations, such as corporate credit ratings, carbon commitment values, carbon tax collection, and other restrictions, have different impacts on corporate green innovation. A good institutional environment can increase the cost of imitation and plagiarism, effectively protect the innovation achievements of pioneer enterprises, and encourage enterprises to engage in green innovation [50].

4.2.2. Regulators and Facilitators

Scholars note that regulators and facilitators jointly form the basic interaction between the generation and the commercialization of green products. For regulators, current studies are focused on the interaction between green enterprises and different green innovation entities, such as general customers and government departments. First, for general customers, there are differences in the level of demand, and potential differences can be found in interactions with customers, which play positive roles in the acquisition of market knowledge and the improvement of existing green products [33]. Moreover, according to customer-led logic, customers directly and interactively participate in the commercialization of green products, thereby promoting the search for novel solutions by green enterprises, increasing sales revenue, and increasing the perception of enterprises as innovative [51]. Second, for the government, the starting point for green innovation is the government’s public value proposition. On the one hand, green and low-carbon industries, as important parts of the industrial system of emerging economies, have received continuous attention from the government, which is in contrast with the efforts of mass production industries to meet market demand [12]. On the other hand, based on the heterogeneity of subjects, the role of the government and the content of the public value proposition shifts with the formation of a green innovation ecosystem. For example, Chinese agricultural enterprises has to consciously and continuously adapt to the green data center government procurement requirements standards to maintain the basis for value emergence [52].

With respect to facilitators, the existing research has focused on the interaction of green enterprises with innovative actors such as public media and supply chain finance. Scholars regard public media as informal environmental regulations. On the one hand, citizen attention exerts a positive impact, citizen demand can significantly stimulate the market vitality of green innovation, and the normative pressure of citizen environmental awareness can effectively supplement environmental regulatory measures, thus promoting green technological innovation among enterprises [53]. On the other hand, public opinion regarding the media has negative effects. For example, the media’s attention to the potential pollution behaviors of enterprises not only exposes enterprises to negative public opinion but also leads them to passively induce punishment mechanisms or even administrative punishment through the market [54]. Second, supply chain finance has attracted increasing research attention due to its ability to link financial incentives with green innovation goals [46]. Banks and commercial credit can be used to solve common financing problems in the green innovation process [55].

The overview of the study in basic interaction of green innovation ecosystems is displayed in

Table 3. Overview of the study of the basic interaction of green innovation ecosystems.

Value Emergence	Generation Mechanism of the Green Innovation Ecosystems	Authors
Basic interaction		Chin et al., 2022 [22]; Jiang and Zheng, 2021 [23]; Zameer et al., 2021 [24]; Klein et al., 2020 [26]; Kwak et al., 2018 [27]; Tang and Qian, 2020 [29]; Qin et al., 2022 [36]; Qu et al., 2019 [48]
		Chen et al., 2020 [42]; Polese et al., 2021 [17]; Jones and Baumgartner, 2012 [45]; Gao et al., 2023 [46]; Qu et al., 2019 [48]; Zhao et al., 2023 [33]; Trischler et al., 2020 [51]; Wong et al., 2021 [52]; Zhao et al., 2022 [53]
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5. Research Agenda of the Dynamic Evolution of Green Innovation Ecosystems from the Value Emergence Perspective

5.1. Resource Configuration of Green Innovation Ecosystems

With the help of digital transformation and dynamic capabilities, green enterprises stimulate the basic interaction of value emergence, thus making the flow of resources within the green innovation ecosystem smoother and injecting new resources into the system.

5.1.1. Digital Transformation

Based on the theory of complex adaptive systems, the overall emergence of a system is generated on the basis of scale effects and structure effects. The literature indicates that digital transformation has not only become the focus of enterprise resource configuration optimization but also gradually become an important source of enterprise green innovation vitality [56]. The Santa Fe Institute proposed that systems emerge only upon reaching a certain scale. Through the promotion of resource configuration and integration, digital transformation expands the scale of green enterprises, and the probability of nonlinear interaction increases accordingly, thereby creating the possibility of forming an internal model [57]. Specifically, the ability of green enterprises to obtain and integrate resources is improved through the development of digital construction platforms; the government, industry, university and research systems, and investment and financing systems are thus supported by green innovation, and digital transformation means that enterprises use high-quality data analysis to make business decisions. The aggregation of tangible mass data, intangible enterprise digital culture, and digital human resources serves as the focus of resource integration and promotes the formation of scale effects in the green innovation ecosystem [58].

The research shows that green innovation agents use structural effects to promote system emergence by reorganizing the system building block mechanism and optimizing the internal model of the system. Among them, digital transformation enables the use of digital technology to provide the conditions needed for resource coordination among participants, thereby greatly promoting resource matching efficiency and the formation of structural effects [59]. For example, Papa, et al. [60] noted that big data can increase the channels for industry–university–research alliances to acquire dominant and implicit new knowledge, change the operation mode of value creators in basic interactions, and promote the dynamic ability to form digital competitive advantages through management decisions based on data analysis [58]. Second, Fu and Li [30] noted that information technology can enhance the symbiotic and trust structure relationships between platform enterprises by promoting communication in the platform ecological chain. Finally, blockchain technology has become a disruptive technology through its potential to realize green innovation; for example, two blockchain-based green experiments in the Chinese power industry have confirmed that blockchain technology can bring about institution-based trust among the participating agents [61]. Han, et al. [62] noted that blockchain technology can also reduce intermediary entities within the system to the minimum, thus facilitating the smooth flow of resources within the system.

5.1.2. Dynamic Capability

In economics, there are frequent interactive “streams” in the green innovation ecosystem, and dynamic capabilities affect the multiplier effect and recycling effect of the system by improving the quality and quantity of streams, which affects the evolution of the green innovation ecosystem [4]. This effect means that dynamic capability can effectively promote the overall interaction of the existing resources in the system and make the total effect increase by a multiplier level through network transmission [4], and the recycling effect refers to the recycling of flows, and dynamic capability can promote the circulation of resource flow in the system multiple times and through multiple nodes. In recent years, scholars have explored the dynamic capabilities of the system itself, such as perception capability, which enables green enterprises to monitor the market and meet green consumption demand [63]. Self-organization ability is a prerequisite for the survival of green innovation ecosystems. System members independently determine the selection of resource configurations and ecological niches, and nonlinear interactions among green innovation entities are a typical manifestation of this capability [64]. Absorptive ability, or the ability of green enterprises to evaluate external knowledge and apply it to a green innovation platform, is crucial to whether the green innovation R&D platform has the ability to cooperate and utilize external knowledge [65].

The number, size, and smoothness of streams in the flow space network affect the multiplier utility and recycling effect, thus influencing the evolution of green innovation ecosystems [57]. The two-way flow of effective knowledge resources through the system can effectively promote the development of flow space. Scholars have summarized these flows as the acquisition, assimilation, and integration of external knowledge and the outflow, reorganization, and business model reconstruction of internal knowledge [66]. Therefore, green knowledge learning ability can be divided into two parts, namely, green knowledge integration and green knowledge search. First, green knowledge integration refers to the dynamic identification, collection, reconstruction, and optimization of green knowledge by enterprises so that green knowledge is systematically linked and integrated [30], which can not only promote green technology innovation within enterprises but also drive enterprises to innovate across organizational boundaries. Second, green knowledge search indicates that green enterprises optimize and improve their own knowledge reserves, acquire heterogeneous knowledge, break innovation constraints, and constantly adapt to changes in the external environment through external knowledge searching [67]. The depth of such a knowledge search can lead to the acquisition of frontier knowledge in the Beijing–Tianjin–Hebei region.

5.2. Value Discovery of Green Innovation Ecosystems

Emergent value not only is a new resource generated by the part–whole interaction of value emergence in the green innovation ecosystem, but also lays the foundation for the feedback of value emergence in the green innovation ecosystem.

5.2.1. Efficiency-Oriented Value

Research shows that the green innovation ecosystem creates an efficient value and applies it to the entire system, and an efficient value means that the enterprise keeps the original resource base unchanged and creates performance by shortening the R&D cycle and saving resources. For example, in the study of the driving factors underlying green technology innovation, scholars have pointed out that five green resources, namely, government funds, foreign direct investment, pollution control investment, green product sales revenue, and green technology trading volume, can enter the system and exert a linear effect on the creation of high-level resources for green technology innovation [68]. In the study of the mechanism of action, the efficiency value does not directly affect the subject of green innovation. Rather, the internal environment of the system indirectly guides enterprises to actively adopt cleaner production technology based on the development of new technologies to achieve multiple economic, social, and environmental benefits [69]. In the practical application research of the European Union, the efficiency value re-enters the system and is used to assist green innovation entities in establishing a green support system, which not only helps to reduce the cost of digital green innovation transformation in manufacturing but also promotes deep cooperation among cross-border entities [11].

5.2.2. Generative Value

Research shows that green innovation ecosystems create a generative value and apply it throughout the entire system, and a generative value represents the ability of green enterprises to spontaneously change and adapt. For example, green business model innovation is the result of organizational learning, technology, and the market. In the study of driving factors, digitalization has been shown to promote the value discovery of green business model innovation. By working on the internal environment of the system, companies are required to analyze regulators more deeply and receive feedback on their needs [70]. In the study of the mechanism of action, an organic value has been shown to effectively integrate the internal and external resources of a company and to become the driving force underlying green enterprises’ quest to continuously create and obtain an economic, social, and environmental value [71]. In addition, it plays an important role in resolving the tension between competing firms [50]. In the practical application research, scholars have pointed out that green business model innovation is a very new value; for example, Philips and the clothing retailer H&M are undertaking green business model innovation, but green business model innovation is still in the launch stage for most enterprises [72].

The overview of the study in dynamic promotion of green innovation ecosystems is displayed in

Table 4. Overview of the study in dynamic promotion of green innovation ecosystems.

Value Emergence	Dynamic Evolution of the Green Innovation Ecosystems	Authors
Dynamic promotion		Li et al., 2022 [56]; Chen et al., 2022 [57]; Yoo et al., 2012 [58]; Demirel and Kesidou, 2019 [63]; Täuscher and Laudien, 2018 [65]; Zhang and Wang, 2021 [66]
		Wang and Mao, 2007 [68]; Stokke et al., 2022 [11]; Guo et al., 2023 [70]; Geissdoerfer et al., 2018 [71]; Hou et al., 2022 [50]; Santa-Maria et al., 2022 [72]
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5.3. The Collective Governance of Green Innovation Ecosystems

The collective governance of the green innovation ecosystem relies on the feedback effect of the internal environment of the system on the green innovation subjects, among which the internal environment of the green innovation ecosystem is composed of informal governance and formal governance, and is the carrier of nonlinear interactions among the innovation subjects.

5.3.1. Informal Governance of Green Enterprises

Research shows that there are two different internal model management modes in green innovation ecosystems. At the level of informal governance, first, the management of green enterprises is influenced by the performance of green innovation and facilitates the further performance of green innovation activities by supporting employees of green innovation subjects in the development of interdisciplinary cooperation, system thinking, and ethical decision-making abilities [73]. Second, organizational culture is considered a major part of the innovation evolution of green enterprises, which runs through all aspects of business operations [74] and triggers a new round of basic interaction among green innovation subjects; ultimately, an emerging value exerts a feedback effect on green innovation subjects through the internal environment. Third, from the perspective of social exchange theory, trust is emphasized as the key to evolution and progress in the green innovation ecosystem [75], and trust can be further categorized into peer trust, ability trust, and commitment trust. Collaborative performance among green enterprises promotes the deepening of trust relationships, and from the perspective of noncontractual reciprocity relationships, green innovation collaboration among green innovation entities is promoted through the combination of innovation networks and communities [76]. In addition, the psychological safety of team members and the social network of the team also plays a crucial role in enterprises accelerating the decision-making process and the process of green innovation itself.

5.3.2. Formal Governance of Green Enterprises

First, the organizational structure, as the rules of the game within a system, clarifies the flow of resources and knowledge among interacting heterogeneous participants, thus affecting the efficiency of the company’s green behavior [77]. Moreover, because system boundaries are permeable, internal rules determine the difficulty of participants entering and exiting the ecosystem and delineate the boundaries of the ecosystem and operational space available to participants [4]. Scholars point out that, in terms of organizational structure innovation, the redivision of department settings and responsibilities is crucial because it helps green innovation entities meet internal environmental requirements and realize the systematization of green innovation [78]. Second, Dan, et al. [79] noted that the construction and integration of a strong system infrastructure cause the boundaries of ecosystems to continuously expand, and green innovation ecosystems can be updated and iterated to better adapt to external environmental requirements. Therefore, ways of further expanding the original functions of infrastructure to attract more high-quality system participants to achieve a virtuous cycle and improve the ability of ecosystems to resist drastic changes in the external environment need further exploration.

5.4. Contextual Embedding of Green Innovation Ecosystems

To adapt to changes in the external environment (policy system and social environment), green innovation subjects will continue to learn and accumulate. By integrating the resources within the green innovation ecosystem, they will obtain their own unique high-level resources and continue to export them to the outside world.

5.4.1. The Policy System

Studies have shown that a green innovation ecosystem has an identifier, in which the green innovation subject selects the interaction object through the identifier, thus creating a selective interaction. This mechanism can explain the flow of elements through the system [80]. As an important mechanism, the policy system can affect the activity degree and direction of factor flow. Specifically, with the participation of cross-industry and sectoral actors, the flow of resources across levels increases, and the government creates a favorable business environment to protect the legitimacy of the system. By identifying policies, green enterprises can more actively acquire, use, and transform effective digital resources, which can lay a solid foundation for their dynamic capacity building [39]. In addition, with recent developments, scholars have proposed requirements for government policy formulation. The development of national and local antimonopoly laws and regulations must maintain pace with commercial innovation through the implementation of dynamic and accurate monitoring and evaluation to improve existing regulations and enhance the value emergence quality of the green innovation ecosystem. Some scholars have noted that the coordinated implementation of government subsidies and environmental regulation is internalized into a new institutional system of mutual integration and symbiosis between green enterprises and related industries, and environmental regulation can be divided into mandatory and incentive environmental regulation. Mandatory environmental regulation can promote enterprises to implement green innovation strategies. For example, green enterprises face environmental laws and regulations and relatively strict waste emission reduction standards and production technology standards [53]. Incentive environmental regulation strengthens the intensity of green intellectual property protection and the willingness of enterprises to foreign investment, which subsequently affects the investment in green innovation of enterprises and the economic transformation efficiency of green innovation achievements. At the same time, based on the spatial spillover characteristics of green innovation, in studies on the evolution of green innovation ecosystems, scholars have pointed out that governments should fully consider the differences between economic environments in different regions when making policies and adjusting measures according to local conditions [11]. Appropriate incentive policies should be adopted in regions with medium and low economic development levels, and mandatory environmental regulations should be implemented when the economic development level tends to increase [81].

5.4.2. The Social Environment

In the study of the evolution of green innovation ecosystems, indicators such as the economy, market, resources, and cultural environment produce positive optimization feedback regarding the green innovation development of enterprises, and the development of the system synchronously promotes the development of the social environment [82]. In studies related to the economic environment, green enterprises efficiently carry out alliance innovation under the requirements of the economic environment to accelerate the direction of low carbon and energy savings development [11]. In studies related to the market environment, scholars have pointed out that the market environment directly determines the final stage of a green innovation ecosystem. For example, by collecting and understanding feedback from the market environment, green enterprises can generate innovative practices such as new knowledge and new services, thus updating corporate culture and value propositions [83]. In studies related to resources and the environment, scholars have pointed out that resources and the environment provide support for the development of green innovation ecosystems, including both tangible resources, such as human and material resources, and intangible resources, such as knowledge and technology [84]. According to studies of the cultural environment, to realize the continuous upgrading and virtuous cycle of green innovation ecosystems, green enterprises need to make use of positive cultural environment-oriented spontaneous green innovation [51].

The overview of the study in feedback loop of green innovation ecosystems is displayed in

Table 5. Overview of the study of the feedback loop of green innovation ecosystems.

Value Emergence	Dynamic Evolution of the Green Innovation Ecosystems	Authors
Feedback loop		Jütting, 2022 [73]; Guo, 2002 [74]; Sun et al., 2023 [75]; Gutierrez, D and Macken-Walsh, 2022 [76]; Ribeiro et al., 2022 [77]; Prieto-Sandoval et al., 2019 [78]
		Wan et al., 2022 [80]; Hofer et al., 2012 [39]; Wong et al., 2021 [53]; Stokke et al., 2022 [11]; Du et al., 2021 [81]; Barile et al., 2020 [83]; Kapoor, 2018 [84]; Trischler et al., 2020 [51]
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6. Future Research Proposals and Framework Construction

Existing studies have presented preliminary discussions of the generative process and evolutionary mechanism of green innovation ecosystems, but no detailed discussion on the value creation of green innovation ecosystems has been conducted from the perspective of value emergence. Therefore, based on the relational view described above, and integrating the research framework diagram in Table 3, Table 4 and Table 5, a research framework for green innovation ecosystems is constructed from the perspective of value emergence, as shown in Figure 5, and future research directions are discussed.

In Figure 5, different shape symbols represent different subjects or resources, and different colors represent that they come from different stages, among which green represents basic interaction, orange represents dynamic promotion, and blue represents feedback loop.

6.1. Research on the Basic Interaction of Green Innovation Ecosystems

In view of existing problems such as the gradual complexity of nonlinear interactions among green innovation subjects, we propose that a more in-depth model can be constructed from the microcharacteristics of the system to describe the generation mechanism of green innovation ecosystems. Existing studies have explored two components of the system, namely, upstream and downstream suppliers and the complementary resource pool [85], but have ignored the relationship between the nonlinearity and complexity of innovation entities, and the simultaneous green innovation activities of these two entities are limited. On the one hand, the addition of complementors enhances the complexity of the green innovation ecosystem, and when complexity accumulates to a certain degree, it inhibits innovation in the system [29]. On the other hand, since the interaction of complementors is nonlinear, scholars have developed different understandings of the benefit allocation of complementors among themselves and core enterprises. Future studies can explore the effect of the addition of complementors on innovation behavior. Could the shift in benefit distributors significantly influence the generation of green innovation ecosystems (RQ1)?

Second, synergy is an important concept in the theory of complex adaptive systems. Although existing studies have pointed out that the dynamics of collaboration and competition in the green innovation ecosystem affect the green innovation of enterprises, existing studies have focused on the collaborative behavior of industry, universities, and research and have ignored the nonlinear interaction of other participants within the system. To compensate for this shortcoming, we propose that the theory of competition and cooperation can better reveal the nonlinear interaction of innovation agents in the system, especially regarding the generation of system element flow at the micro level. According to niche theory, researchers can divide the green innovation agents in the system according to resource and spatial dimensions and analyze the impact of competition and cooperation relationships in different dimensions on the generation and flow of resources. RQ2 should be considered by researchers: In terms of the resource dimension, does the way in which green innovation subjects use resources promote the generation of basic resources through its influence on competition and cooperation relationships? In the spatial dimension, how do the competition and cooperation relationships between green innovation subjects across industry and geographical boundaries affect the flow of basic resources, and what is its internal mechanism?

Finally, the heterogeneity and diversity of green innovation subjects are still worth exploring. As mentioned above, although influencers, facilitators, coordinators, and knowledge providers have their own functional positioning in the green innovation ecosystem, the roles played by heterogeneous agents are diverse. For example, the government’s public procurement plays the role of regulators, the governments attention and financial subsidies play the role of influencers, and government regulation plays the role of knowledge provider. The team not only plays the role of direct value creator and knowledge provider in the basic interaction, but also becomes the carrier of an emergent value acting on the subject of green innovation in the feedback loop. Future research can focus on the role of government governance and teams in value emergence based on specific application scenarios (RQ3).

6.2. Research on the Dynamics of Green Innovation Ecosystems

Existing studies have noted that researchers should also pay attention to the interactions between nonhuman actors, such as digital technology and dynamic capabilities, and green innovation agents. According to actor network theory, the emergence of digital transformation provides the potential for the expansion of nonhuman actors within the green innovation ecosystem based on green innovation agents. However, the large amount of “carbon emissions” brought about by digital technology and its application in the process of digital transformation have also led to doubts and disputes among scholars [86], and different understandings of the relationship between digital transformation and green innovation activities have been obtained. Future studies can explore how the driving factors of digital technology affect the operation of the internal mechanism of the system. In addition, according to the theory of complex adaptive systems, the dynamic capability of green innovation ecosystems results from the nonlinear integration of system resources. According to the adaptive needs of value goals and environmental changes, green enterprises constantly optimize basic resources to improve their resource configuration and knowledge integration capabilities. However, there are many studies on the promoting role of dynamic capability in green innovation ecosystems, and further studies on how valuable resources can be allocated to form dynamic capability and promote the generation of emergent value are needed (RQ3).

Second, cross-level studies on the role of an emergent value are worth exploring. Although existing studies have pointed out that value discovery can have a positive impact on the evolution of green innovation ecosystems, the generation of emergent value is more nonlinear. To compensate for this deficiency, in this study, we propose that multilevel theory can better reveal the process by which an emergent value emerges based on “part-one–whole” interactions and on the conditions that enable it to emerge based on “whole–part” interactions. On the basis of multilevel theory, researchers can divide the composition of the green innovation ecosystem into different levels, establish a nonlinear multilevel model to test the nonlinear relationships between variables at different levels, and deconstruct the evolution process of the emerging value of the green innovation ecosystem from temporal and spatial dimensions. In particular, emergent values such as green technology innovation and green business model innovation promote the evolution of green innovation ecosystems but cannot, by default, guarantee the creation of a social and environmental value in addition to an economic value. This makes it necessary to conduct research on multiple companies in the same value chain through comparative analysis of multiple cases and explore the dimensions of an emergent value (RQ4).

6.3. Research on the Feedback Loops of Green Innovation Ecosystems

Previous studies have pointed out that the internal model of a green innovation ecosystem, which is composed of informal governance and formal governance, serves as the carrier of interaction between the innovation subject and the foundation of the system. This adaptive cycle can explain the sustainable dynamic mechanism of system evolution to some extent [75]. However, Fu and Li [30] found that the collective governance model varies greatly across different cases and argued that early governance decisions significantly affect the subsequent evolution of the green innovation ecosystem. The collective governance of the system can be categorized into initiation, expansion, and generation according to the differences in evolution stages. Although there are similarities among different green innovation ecosystems at the macro level, different internal models produce special evolution patterns at the micro level. Therefore, we need to further explore how green enterprises establish internal models to guide green innovation activities at different stages, how to carry out similar adaptive activities through interaction, and how to transition to a higher level under the nonlinear action of the main body (RQ5). In conclusion, this study shows that the feedback loop of a green innovation ecosystem, from the perspective of the life cycle, has strong theoretical construction potential.

Second, existing studies refer to each participant in the system as a subject, and each subject is adaptive. During the evolution of a green innovation ecosystem, contextual embedding exerts positive or negative pressure on green innovation, under which the subject of the system generates spontaneous feedback [86]. Based on the theory of complex adaptive systems, this kind of spontaneous behavior exhibits two distinct patterns, namely, positive and negative cyclic feedback. In this study, we believe that researchers can explore the effectiveness and efficiency of system circular feedback by focusing on the contextual embedding of policy systems and the social environment from the perspective of value emergence. At the level of the policy environment, digital–real economy integration and digital–green integration have become hotspots in the development of entity enterprises. Future studies can continue to explore this idea: what role does digital–real economy integration play in the evolution of green innovation ecosystems? At the level of the social environment, as mentioned above, although indicators such as the economy, market, resources, and cultural environment exert impacts on the positive feedback of the system, how can the interactions among innovation entities in the green innovation ecosystem be coordinated when the external environment (such as policy governance) dramatically changes? When the internal self-generated institutional logic of the system is in conflict, how does the green innovation ecosystem change its behavior to promote the evolutionary process (RQ6)?

7. Conclusions and Discussion

From the perspective of value emergence, based on theoretical retrospection, we review the existing studies on the generation mechanism and dynamic evolution of green innovation ecosystems, construct a framework, and propose suggestions for future research. The theoretical contributions of this paper are as follows: First, this study expands the research on green innovation ecosystems. The existing discussions and research on green innovation ecosystems are mostly conducted at the micro level, and few studies have summarized the three major research themes—basic interaction, power promotion, and feedback loop—of green innovation ecosystems from a systematic perspective to describe a relatively complete new research paradigm. Second, this study further broadens the applicable context of the value emergence perspective. The existing studies on value emergence have focused mainly on the system context, such as digital and platform contexts, but have given limited attention to the integration context of green innovation ecosystems. On the basis of a systematic review of relevant research, in this paper, we further propose a theoretical framework for the value emergence of green innovation ecosystems, which has strong theoretical value.

On the practical level, the value emergence process of green innovation ecosystems represents the development trend of enterprise management practice innovation in digital and green eras. First, green innovation based on the theory of value emergence not only has gradually become the core competitive advantage of entity enterprises but also actively assumes the function of a new value creation at the system level, thus providing theoretical support for traditional enterprise management practices that combine both digital and green practices; for example, the Pinggu District of Beijing provides whole-process digital carbon management solutions for agricultural enterprises by building agricultural Zhongguancun. Enterprises should seize the key of digital intelligence technology and give full play to its amplification, superposition, aggregation, and multiplication effects on the green development of enterprises. Second, by revealing the dynamic promotion mechanism of the green innovation ecosystem, we suggest that more attention should be given to the influence of digitalization and dynamic capability on green practices in the future; for example, the Guangxi Liuzhou Iron and Steel Group should implement green transformation with internal dynamic capabilities in a complex external environment [87]. To enable in-depth digital transformation, enterprises should cultivate dynamic capabilities driven by industrial scenarios. Third, by revealing the influence of the internal model and external environment on value emergence, we suggest that more attention should be given to strengthening the collaborative management of the internal model and external environment identification of enterprises; for example, BYD Automobile enables the construction of a green innovation ecosystem with the help of external environmental policies [88]. The government should formulate incentive regulations to promote the action mechanism of enterprise green innovation.

In short, the study of green innovation ecosystems conducted from the perspective of value emergence has a rich theoretical value and practical significance, and it is urgent for researchers to explore research problems related to local characteristics in green innovation ecosystems under specific circumstances and build and improve the relevant theoretical system.