Search Results (146)

Based on a comprehensive review of the current research status of ecological compensation both domestically and internationally, combined with field survey data, this study delves into the issue of multi-stakeholder participation in the ecological compensation mechanisms of the Xin’an River Basin. This research reveals that the joint participation of multiple stakeholders is crucial to achieving the goals of ecological compensation in river basins. The government plays a significant role in macro-guidance, financial support, policy guarantees, supervision, and management. It promotes the comprehensive implementation of ecological environmental protection by formulating relevant laws and regulations, guiding the public to participate in ecological conservation, and supervising and punishing pollution behaviors. The public, serving as the main force, forms strong awareness and behavioral habits of ecological protection through active participation in environmental protection, monitoring, and feedback. As participants, enterprises contribute to industrial transformation and green development by improving resource utilization efficiency, reducing pollution emissions, promoting green industries, and participating in ecological restoration projects. Scientific research institutions, as technology enablers, have effectively enhanced governance efficiency through technological research and innovation, ecosystem value accounting to provide decision-making support, and public education. Social organizations, as facilitators, have injected vitality and innovation into watershed governance by extensively mobilizing social forces and building multi-party collaboration platforms. Communities, as supporters, have transformed ecological value into economic benefits by developing characteristic industries such as eco-agriculture and eco-tourism. Based on the above findings, further recommendations are proposed to mobilize the enthusiasm of upstream communities and encourage their participation in ecological compensation, promote the market-oriented operation of ecological compensation mechanisms, strengthen cross-regional cooperation to establish joint mechanisms, enhance supervision and evaluation, and establish a sound benefit-sharing mechanism. These recommendations provide theoretical support and practical references for ecological compensation worldwide. Full article

In the context of the explosive growth of the digital economy, how inter-organizational connectivity affects corporate ambidextrous innovation has emerged as a pressing issue in the current digital economy. Based on the perspectives of the innovation ecosystem and digital coupling, this paper explores the inner mechanism of this issue through structural modeling by using the data of China’s high-tech enterprise alliance cooperation from 2015 to 2022. It is found in the empirical study that the local efficiency and reach rate of the digital innovation ecosystem have an inverted U-shaped relationship with exploratory innovation, and the local efficiency and reach rate of the digital innovation ecosystem have a negative effect on firm exploitative innovation. In addition, the level of firms’ digital transformation mediates the relationship between the local efficiency, reach rate, and ambidextrous innovation. The level of market development plays a moderating role in the relationship between the local efficiency, reach rate, and ambidextrous innovation. The findings provide a theoretical basis for the digital innovation ecosystem to realize the role of a “resource pool” through structural connections, which in turn provides important guidance for the digital transformation and innovation development of high-tech enterprises. Full article

The complexities inherent in resource management within cross-domain digital innovation ecosystems have significantly intensified, giving rise to heightened challenges in collaborative interactions among diverse stakeholders, thereby directly impacting systemic stability. Conventional governance frameworks for innovation ecosystems are inadequate in effectively managing the uncertainties and risks inherent in these environments. To address the collaborative governance dilemma and enhance governance efficiency, this paper aims to construct an effective collaborative governance mechanism for a cross-domain digital innovation ecosystem and explore the optimal strategy choices of key governance stakeholders, including the government, digital platform enterprises, and other relevant parties. This research utilizes evolutionary game theory to construct a model comprising three governing entities: the government, digital platform enterprises, and stakeholders. It investigates the evolutionary dynamics of collaborative governance strategies among these entities and the factors that influence governance. Following this, a system dynamics methodology is employed for simulation analysis. The results reveal the following: (1) As the initial intentions of the governing entities evolve, governance decisions within the system tend to stabilize, characterized by a strategic combination of proactive regulation, active cooperative governance, and engaged participation. This equilibrium governance strategy significantly fosters the stable advancement of cross-domain digital innovation ecosystems. (2) The punitive measures enacted by the government and the internal incentive structures of the system positively influence the evolution of governance decisions towards collaborative governance. (3) The cost–benefit assessment of the primary governing entity, the digital platform enterprise, demonstrates a detrimental effect on the evolution of governance decisions towards collaborative governance. These findings are vital for refining the collaborative governance frameworks of cross-domain digital innovation ecosystems and for promoting the robust and stable progression of the system. Full article

In the context of accelerating digital transformation and growing sustainability imperatives, entrepreneurial ecosystems increasingly rely on open innovation and strategic collaboration to foster resilient, knowledge-driven growth. This study aims to examine how leadership behaviors and strategic alliances interact as enablers of sustainable innovation across macro (systemic), meso (organizational), and micro (individual) levels. To achieve this, this study employs a literature review, supported by bibliometric analysis, as its core methodological approach. Drawing on 86 influential publications from 1992 to 2024, two major thematic streams emerge: leadership dynamics in entrepreneurial settings and the formation and governance of strategic alliances as vehicles for innovation. The findings underscore the pivotal role of transformational and ethical leadership in cultivating trust-based inter-organizational relationships, facilitating digital knowledge sharing, and catalyzing sustainable value creation. Simultaneously, strategic alliances enhance organizational agility and innovation capacity through co-creation mechanisms, digital platforms, and crowdsourcing, especially in small and medium-sized enterprises (SMEs). This paper highlights a mutually reinforcing relationship: effective leadership strategies empower alliances, while alliance participation enhances leadership capabilities through experiential learning in diverse, digitalized environments. By bridging leadership theory, open innovation practices, and digital transformation, this study offers critical insights for entrepreneurs, managers, and policymakers seeking to drive inclusive and sustainable innovation within interconnected global markets. Therefore, this study provides practical guidance for business leaders aiming to strengthen alliance performance through adaptive leadership and for policymakers seeking to foster innovation ecosystems through supportive regulatory and institutional frameworks. Full article

Having the proper infrastructure is crucial because it fosters prosperous enterprise and a skilled labor force capable of solving environmental issues. There are worries about the potential negative effects of human capital centered on innovation, despite studies showing benefits. This study examines how contextual factors such as business environment, infrastructure, and human capital, influence South Africa’s entrepreneurial ecosystem. Multiple Regression Technique was used for analysis. Findings showed that each of the three factors has a remarkable impact, with business environment showing the highest positive relationship to the Ecosystem Index. The results highlight the significance of focusing on sustainable activities when developing human capital. To promote a more sustainable entrepreneurship environment, the study suggests that policymakers should implement incentives, allocate finances for infrastructure, and establish educational and knowledge-sharing initiatives to encourage the sustainability of the entrepreneurial ecosystem. Future research directions will focus on investigating how additional contextual factors affect ecosystems in various regions and industries. The study also suggests the evaluation of gender equality in access to financial and business assistance. Full article

This paper is based on data from Chinese digital creative enterprises from 2015 to 2023. A regression model is constructed to test the driving mechanism of the digital innovation ecosystem on the digital transformation of enterprises. The Shapley Additive exPlanations (SHAP) machine learning method is also employed to reveal the key factors driving enterprise digital transformation in the digital innovation ecosystem. The results show that (1) the digital innovation ecosystem can significantly drive the digital transformation of enterprises. And this driving effect is influenced by the moderating effect of the dynamic capabilities of enterprises. The moderating effect of innovation capability and absorptive capacity on enterprise digital transformation is the most significant. (2) The heterogeneity test finds that among state-owned enterprises and enterprises with a high degree of industry competition, the digital innovation ecosystem significantly drives enterprises’ digital transformation more strongly. (3) The results of SHAP value identification indicate that the digital intelligence foundation is the most important factor in driving enterprise digital transformation. The degree of participant diversity, the enabling capacity of the system environment, and the comprehensive benefits play different roles in driving enterprise digital transformation under different heterogeneous conditions. Full article

With the shift of the global innovation model from traditional closed-loop to open ecosystems, knowledge sharing and collaborative cooperation among firms have become key to obtaining sustainable competitive advantages. However, existing studies mostly focus on the static structure, and there is an insufficient exploration of the dynamic evolutionary mechanism and multi-party game strategies. In this paper, a two-dimensional analysis framework integrating the evolutionary game and the Lotka–Volterra model is constructed to explore the behavioral and strategic evolution of core enterprises, SMEs and the government in the innovation ecosystem. Through theoretical modeling and numerical simulation, the effects of different variables on system stability are revealed. It is found that a moderately balanced benefit allocation can stimulate two-way knowledge sharing, while an over- or under-allocation ratio will inhibit the synergy efficiency of the system; a moderate difference in the knowledge stock can promote knowledge complementarity, but an over-concentration will lead to the monopoly and closure of the system; and the government subsidy needs to accurately match the cost of the openness of the enterprises with the potential benefits to the society, so as to avoid the incentive from being unused. Accordingly, it is suggested to optimize the competition structure among enterprises through the dynamic benefit distribution mechanism, knowledge sharing platform construction and classification subsidy policy, promote the evolution of the innovation ecosystem to a balanced state of mutual benefit and symbiosis, and provide theoretical basis and practical inspiration for the governance of the open innovation ecosystem. Full article

Amid rapid digital transformation in the global economy, digital innovation capability has emerged as a strategic asset for enterprises to cultivate competitive advantages. However, challenges such as the complexity of digital resource integration, limitations of traditional innovation paradigms, and ecosystem fragmentation hinder the development of this capability. Combining innovation ecosystem theory with dynamic capability perspectives, this study analyzed data from 312 Chinese enterprises to examine how enterprise innovation ecosystems shape digital innovation capability. Key findings include the following: (1) the composition, operation, and relationships of enterprise innovation ecosystems exert significant positive effects on digital innovation capability, with the composition dimension demonstrating the most substantial impact.; (2) digital innovation capability comprises three hierarchical components—Digital technological capability (Foundational Capability), Digital technology-enabled Innovation Capability (Evolutionary Capability), and Value reconfiguration capability (Transformational Capability)—all dynamically supported by ecosystem interactions; (3) dynamic capabilities serve as critical mediators between ecosystems and digital innovation capability. Theoretically, this research integrates ecosystem and capability theories to reveal a transformation pathway of “ecosystem embeddedness → dynamic capabilities → digital innovation”. Practically, it offers guidance for resource allocation, ecosystem optimization, and governance, advancing sustainable digital innovation ecosystems. Full article

Community enterprises play an essential role in advancing sustainable development; however, limited strategic frameworks impede their ability to integrate economic, social, and environmental objectives effectively. This study explores the strategic roles undertaken by community enterprise entrepreneurs to address this gap. Adopting a mixed-methods design, this research integrates qualitative data from in-depth interviews and participatory observations with quantitative analysis based on 215 standardized survey responses. The findings reveal consistent emphasis on five critical strategic roles: vision and goal-setting, resource management, networking and collaboration, innovation leadership, and strategic leadership, with mean ratings between 4.45 and 4.54 on a five-point Likert scale. Qualitative insights further illuminate how entrepreneurs leverage these strategies to optimize resources, foster cross-sector partnerships, drive innovation, and strengthen organizational resilience. Policy recommendations include enhancing infrastructure, developing entrepreneurial capacity, and promoting multi-sectoral ecosystems to support community enterprises. This study contributes to the theoretical discourse by proposing a five-dimensional strategic entrepreneurship model for sustainable community development, offering practical guidelines for policymakers and entrepreneurs seeking to foster resilient, inclusive, and sustainable local economies. Full article

This study examines the application of agentic artificial intelligence (AI) frameworks within small, medium, and micro-enterprises (SMMEs), highlighting how interconnected autonomous agents improve operational efficiency and adaptability. Using the PRISMA 2020 framework, this study systematically identified, screened, and analyzed 66 studies, including peer-reviewed and credible gray literature, published between 2019 and 2024, to assess agentic AI frameworks in SMMEs. Recognizing the constraints faced by SMMEs, such as limited scalability, high operational demands, and restricted access to advanced technologies, the review synthesizes existing research to highlight the characteristics, implementations, and impacts of agentic AI in task automation, decision-making, and ecosystem-wide collaboration. The results demonstrate the potential of agentic AI to address technological, ethical, and infrastructure barriers while promoting innovation, scalability, and competitiveness. This review contributes to the understanding of agentic AI frameworks by offering practical insights and setting the groundwork for further research into their applications in SMMEs’ dynamic and resource-constrained economic environments. Full article

Enhancing residents’ green consumption is essential to fostering high-quality economic advancement. This study constructs an indicator system for residents’ green consumption based on three subsystems: green manufacturing processes, sustainable lifestyles, and environmental ecosystems. A regression model analyzes how public environmental concern affects residents’ green consumption, using panel data from 30 provinces and cities in China over the period 2011–2023. Additionally, analyses of mechanisms and heterogeneity are carried out. The study results are presented below: First, public environmental concern (PEC) can significantly enhance residents’ green consumption (RGC), with an increase of 1% in PEC leading to a 0.261% rise in RGC. Second, green technological innovation (GTI) and market-based incentive environmental regulation (MER) mediate the relationship between PEC and RGC. However, the role of command-and-control environmental regulation (CER) as a mediator is insignificant. Third, there is heterogeneity in RGC based on region, pollution emissions, and innovation foundations. The impact of PEC is notably greater in central-western regions, areas with higher pollution emissions, and regions with better innovation foundations. Therefore, this study proposes policy recommendations from three aspects: improving public environmental concern, strengthening green technological innovation in enterprises, and formulating region-specific industrial upgrading paths to promote residents’ green consumption. Full article

Despite the transformative potential of artificial intelligence (AI), small and medium-sized enterprises (SMEs) continue to face significant challenges in its effective adoption. While prior studies have emphasized strategic benefits and readiness models, there remains a lack of operational guidance tailored to SME realities—particularly regarding implementation barriers, resource constraints, and emerging demands for responsible AI use. This study presents an analysis of AI adoption in SMEs by integrating the technology–organization–environment (TOE) framework with selected attributes from the diffusion of innovations (DOI) theory to examine adoption dynamics through a dual structural and perceptual lens. Empirical insights from sectoral and regional contexts are also incorporated. Ten critical challenges are identified and analyzed across the TOE dimensions, ranging from data access and skill shortages to cultural resistance, infrastructure limitations, and weak governance practices. Notably, the framework is expanded to incorporate responsible AI governance and democratized access to generative AI—particularly open-weight large language models (LLMs) such as LLaMA, DeepSeek-R1, Mistral, and FALCON—as emerging technological and ethical imperatives. Each challenge is paired with actionable, context-sensitive solutions. The paper is a structured, literature-based conceptual analysis enriched by empirical case study insights. As a key contribution, it introduces a structured, six-phase roadmap methodology to guide SMEs through AI adoption—offering step-by-step recommendations aligned with technological, organizational, and strategic readiness. While this roadmap is conceptual and has yet to be validated through field data, it sets a foundation for future diagnostic tools and practical assessments. The resulting study bridges theoretical insight and implementation strategy—empowering inclusive, responsible, and scalable AI transformation in SMEs. By offering both analytical clarity and practical relevance, this study contributes to a more grounded understanding of AI integration and calls for policies, ecosystems, and leadership models that support SMEs in adopting AI not merely as a tool, but as a strategic enabler of sustainable and inclusive innovation. Full article

Enterprise digital transformation has emerged as a key strategy for enhancing innovation capacity in the age of the digital economy. This article aims to analyze the influence mechanism of digital transformation on corporate innovation and evaluate the mediating function of corporate innovation and cooperative cultures between digital transformation and corporate innovation capability. This work builds a panel data model based on data from Chinese A-share listed businesses from 2012 to 2021, empirically analyzes it using the Tobit model and the fixed effects model with instrumental variables technique, and uses the mediation effect test to uncover the course of action. According to the report, digital transformation significantly enhances creativity capability; second, corporate collaborative and innovation cultures mediate the relationship between digital transformation and innovation outcomes, and cultural capital becomes a crucial link; and third, the influence of digital transformation on corporate innovation capability is greater in state-owned enterprises, non-monopoly industries, and high-tech industries. According to the study, businesses should work to realize the dual-wheel drive of “technological investment + cultural cultivation” and establish an open and collaborative innovation ecosystem, while the government should intensify the development of digital infrastructure, enhance the supporting system, encourage cultural construction and talent supply, and create an environment that supports the synergistic development of digitization and innovation. Full article

Open-source collaboration, as both an open and cooperative software development paradigm and a novel production model in the era of the industrial internet, plays a pivotal role in overcoming technological bottlenecks in the industrial software industry. However, previous studies have often treated open-source collaboration as a single unified concept and have not explored the specific types of open-source collaboration and their differential effects on technological innovation. To address these gaps, this study aims to answer two core research questions: (1) What are the different types of open-source collaboration models based on their characteristics? (2) How do these collaboration models influence technological innovation in the industrial software industry? Drawing upon four representative collaboration cases in the industrial software domain, this study conducts within-case and cross-case comparative analyses to propose a typological framework based on the dimensions of coreness and complementarity. The analysis identifies four distinct open-source collaboration models: (1) single-core with high complementarity, (2) single-core with low complementarity, (3) multi-core with high complementarity, and (4) multi-core with low complementarity. The formation of these models is shaped by three key factors: strategic intentions, resource endowments, and technological capabilities. Moreover, different collaboration types exert varied impacts on organizational characteristics, innovation strategies, and technological impacts. Theoretically, this study makes an original contribution by opening the “black box” of open-source collaboration and revealing the internal mechanisms through which it shapes innovation dynamics. Practically, the findings offer targeted insights for enterprises, policymakers, and open-source communities in selecting appropriate collaboration models that align with innovation goals, thereby supporting technological upgrading and ecosystem resilience in the industrial software industry. Full article

Patent licensing is essential for sustainable technological diffusion, fostering innovation and strengthening industrial resilience. However, the determinants influencing patent licensing decisions remain underexplored. This study investigates these factors at both the enterprise and patent levels, emphasizing their role in promoting sustainable industrial innovation and knowledge transfer. Given the low proportion of licensed patents, this research proposes a measurement framework to identify thematically similar but unlicensed patents and applies a conditional logistic regression model to analyze the factors affecting licensing decisions. Using patent abstracts from the intelligent connected vehicles (ICVs) sector, topic modeling is conducted to classify technological themes, and Kullback–Leibler divergence is applied to measure differences between licensed and unlicensed patents. The results indicate that technological prestige and depth negatively influence licensing, whereas technological breadth, advancement, and stability have a positive effect. From a sustainability perspective, enterprises should optimize technology management to support responsible knowledge transfer and green innovation. Universities should enhance patent quality and innovation impact to contribute more effectively to sustainable development. Policymakers should refine patent licensing frameworks to foster an efficient, inclusive, and sustainable intellectual property ecosystem, thereby facilitating cross-sectoral technology diffusion, advancing eco-friendly industrial transformation, and promoting sustainable economic growth. Full article