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学者姓名：沈能
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Digitalization and greening are inexorable trends in enterprise development today. Based on data from Chinese listed companies from 2008 to 2020, this study examines the relationship between political connections and firms' green innovation, exploring whether digitalization can break the political resource curse and promote green innovation. We find that political connections hinder firms' green innovation, indicating the existence of the political resource curse. Our moderating effect analysis shows that the higher the degree of digitalization of firms, the more significant the decrease in the negative effect of political connections on green innovation, thereby breaking the political resource curse. Heterogeneity analysis shows that the positive moderating effect of digitalization is higher on private firms and firms with more redundant resources. Finally, mechanistic analysis indicates that political connections hinder firms' green innovation by reducing operational efficiency.
Keyword ：
Digitalization Digitalization Green innovation Green innovation Operating efficiency Operating efficiency Political connections Political connections
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| GB/T 7714 | Shen, Neng , Zhang, Lin , Huang, Hao et al. Can digitalization break the political resource curse? A study on political connections and corporate green innovation [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2025 , 380 . |
| MLA | Shen, Neng et al. "Can digitalization break the political resource curse? A study on political connections and corporate green innovation" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 380 (2025) . |
| APA | Shen, Neng , Zhang, Lin , Huang, Hao , Zhang, Guoping , Zhang, Jing , Zhou, Jingwen . Can digitalization break the political resource curse? A study on political connections and corporate green innovation . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2025 , 380 . |
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China needs to promptly establish a globally competitive innovative ecosystem to ensure high-quality development of the economy. This study introduces an ecosystem characterized by innovative populations, nutrients, and biotope. We employ a suitability model embedded in the WAWBO operator that assesses the ecological niches of regional innovation systems from 2012 to 2021, followed by an in-depth study of regional differences and spatial correlations of innovation ecological niches. The investigation indicated that the national innovation niche is generally stable and shows an increasing trend. Nevertheless, the overall suitability is low, and there is a notable opportunity for improvement. Furthermore, there are regional differences in the eastern, central, and western areas, and the Gini coefficient within each region shows a clear trend of "east > central > west," demonstrating a noticeable Matthew effect. Lastly, the national innovation ecological niches display a distinct clustering pattern with low values. This study contends that it is crucial to enhance the mutually beneficial relationship between innovation subjects, logically allocate resources, reduce regional disparities, and maximize the innovation environment.
Keyword ：
Innovation ecosystem Innovation ecosystem Niche fitness Niche fitness WAWBO operator WAWBO operator
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| GB/T 7714 | Shen, Neng , Zhang, Guoping , Zhang, Lin et al. Spatiotemporal evolution characteristics of ecological niche fitness in regional innovation ecosystem: province-level evidence from China [J]. | ENVIRONMENTAL MONITORING AND ASSESSMENT , 2025 , 197 (5) . |
| MLA | Shen, Neng et al. "Spatiotemporal evolution characteristics of ecological niche fitness in regional innovation ecosystem: province-level evidence from China" . | ENVIRONMENTAL MONITORING AND ASSESSMENT 197 . 5 (2025) . |
| APA | Shen, Neng , Zhang, Guoping , Zhang, Lin , Lam, Johnny F. I. , Feng, Linjie . Spatiotemporal evolution characteristics of ecological niche fitness in regional innovation ecosystem: province-level evidence from China . | ENVIRONMENTAL MONITORING AND ASSESSMENT , 2025 , 197 (5) . |
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Data factor marketization (DFM) can fully leverage the multiplier effect of data and provide impetus for China 's carbon emission efficiency (CEE) improvement. Drawing from the panel data across 282 Chinese cities from 2011 to 2021, this research takes the establishment of data trading platforms as the quasi-natural experiment, and innovatively uses the double machine learning (DML) model to study the impact of DFM on CEE and its mechanisms. The findings indicate that: (1) DFM has a strong favorable impact on CEE. Furthermore, this conclusion remains valid following a series of robustness tests such as adjusting samples and changing models. (2) DFM can influence CEE by accelerating digital finance development, improving technological innovation level and promoting industrial structure towards the direction of advanced development (3) The effect of DFM has obvious regional heterogeneity. It is more significant for non-resource-based, high administrative level, lowintensity environmental regulation and economically developed cities. This study quantifies the promotion effect of the DFM on CEE, and provides important experience and enlightenment for comprehensively deepening the construction of data resource system and achieving sustainable development.
Keyword ：
Carbon emission efficiency Carbon emission efficiency Data factor marketization Data factor marketization Digital finance Digital finance Double machine learning Double machine learning Industrial structure Industrial structure Technological innovation Technological innovation
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| GB/T 7714 | Shen, Neng , Zhou, Jingwen , Zhang, Guoping et al. How does data factor marketization influence urban carbon emission efficiency? A new method based on double machine learning [J]. | SUSTAINABLE CITIES AND SOCIETY , 2025 , 119 . |
| MLA | Shen, Neng et al. "How does data factor marketization influence urban carbon emission efficiency? A new method based on double machine learning" . | SUSTAINABLE CITIES AND SOCIETY 119 (2025) . |
| APA | Shen, Neng , Zhou, Jingwen , Zhang, Guoping , Wu, Lianjun , Zhang, Lin . How does data factor marketization influence urban carbon emission efficiency? A new method based on double machine learning . | SUSTAINABLE CITIES AND SOCIETY , 2025 , 119 . |
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The coordinated implementation of new energy policy and digital policy is a key institutional innovation for carbon unlocking in China. This study, based on constructing urban carbon unlocking efficiency, conducts a quasi-natural experiment on dual policy coordination empowerment through New Energy Demonstration City Pilots and the "Broadband China" Strategy. Utilizing panel data from 273 prefecture-level cities in China from 2012 to 2022 and dual machine learning models, the research examines the synergistic mechanism and multidimensional effects of dual policy in promoting carbon unlocking efficiency. The findings reveal that the dual policy exhibit a clear synergistic effect on carbon unlocking, with the empowering effect of combined policies being more pronounced compared to singular policies, a conclusion that remains robust after a series test. Moreover, the dual policy indirectly support carbon unlocking through environmental attention, technological innovation, and industrial upgrading. Heterogeneity analysis indicates that the dual policy has a more significant positive impact in central cities, cities with a high level of digital economy, and cities with a focus on environmental protection, underscoring the importance of tailored advancement of dual policy. This research provides valuable insights for governments in achieving the carbon unlocking through enhancing the coordination of "green-digital" policies.
Keyword ：
Carbon unlocking efficiency Carbon unlocking efficiency Digital policy Digital policy Double machine learning method Double machine learning method New energy policy New energy policy Policy synergy Policy synergy
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| GB/T 7714 | Shen, Neng , Zhang, Lin , Wang, Qunwei et al. The power of institutional innovation in the urban carbon unlocking: A study on collaborative empowerment of digital policy and new energy policy [J]. | ENERGY POLICY , 2025 , 206 . |
| MLA | Shen, Neng et al. "The power of institutional innovation in the urban carbon unlocking: A study on collaborative empowerment of digital policy and new energy policy" . | ENERGY POLICY 206 (2025) . |
| APA | Shen, Neng , Zhang, Lin , Wang, Qunwei , Wu, Lianjun . The power of institutional innovation in the urban carbon unlocking: A study on collaborative empowerment of digital policy and new energy policy . | ENERGY POLICY , 2025 , 206 . |
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Collaborative innovation is the key support for promoting high-quality regional development. Taking Guangdong, Fujian and Zhejiang coastal city clusters as an example, this paper analyzes the evolution mechanism of collaborative innovation network based on the 'two-wheel drive' perspective of external proximity and endogenous gravity. The results show that the difference of resource control ability among nodes in the network is decreasing, and the inverted 'V' structure with Xiamen and Putian as the main apex has evolved into a more robust 'dual core' (Fuzhou-Xiamen) radiation-type spatial structure. In addition, the evolution of regional collaborative innovation network is driven by 'two wheels'. In external proximity, institutional proximity plays the strongest role in promoting, followed by geographical proximity, and the promoting role of technological proximity is gradually weakened. In the endogenous gravity, the influence of investment in science and education is strengthening, while the influence of the administrative level is declining.
Keyword ：
Collaborative innovation Collaborative innovation endogenous gravity endogenous gravity external proximity external proximity two-wheel drive two-wheel drive
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| GB/T 7714 | Shen, Neng , Shang, Xiaofei , Guo, Wenna et al. Evolution of regional collaborative innovation network by the 'two-wheel drive' of external proximity and endogenous gravity [J]. | TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT , 2024 . |
| MLA | Shen, Neng et al. "Evolution of regional collaborative innovation network by the 'two-wheel drive' of external proximity and endogenous gravity" . | TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT (2024) . |
| APA | Shen, Neng , Shang, Xiaofei , Guo, Wenna , Zhang, Guoping . Evolution of regional collaborative innovation network by the 'two-wheel drive' of external proximity and endogenous gravity . | TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT , 2024 . |
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Previous studies on policy interventions prompting electric vehicle (EV) adoption have mainly involved fragmented analyses of multiple policies using system dynamics models and evolutionary games. This study integrates these two approaches to examine EV policies in mainland China and compares their impact on the interaction between governments, consumers, and manufacturers. The results indicate that the annual sales of EVs are most heavily impacted by license plate restrictions, followed by battery capacity. They are most sensitive to the dual -credit policy (DCP) and least affected by government research and development (R&D) subsidies; meanwhile, all four policies increase the sales of EVs. A substitution relationship exists between the dual -credit policy and the government's R&D subsidies. A simulation analysis of the different scenarios confirmed the multiple impacts of several policy interventions on the increase in EV sales, which should be explicitly considered in EV policymaking.
Keyword ：
Electric vehicles Electric vehicles Evolutionary game Evolutionary game Policy intervention Policy intervention Policy performance Policy performance System dynamics System dynamics
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| GB/T 7714 | Deng, Rumeng , Shen, Neng , Zhao, Yuqing . Diffusion model to analyse the performance of electric vehicle policies: An evolutionary game simulation [J]. | TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT , 2024 , 127 . |
| MLA | Deng, Rumeng et al. "Diffusion model to analyse the performance of electric vehicle policies: An evolutionary game simulation" . | TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 127 (2024) . |
| APA | Deng, Rumeng , Shen, Neng , Zhao, Yuqing . Diffusion model to analyse the performance of electric vehicle policies: An evolutionary game simulation . | TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT , 2024 , 127 . |
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PurposeIn the context of open innovation, more and more enterprises are leveraging innovation networks to drive disruptive innovation performance, but there is no consensus on the relationship between network embeddedness and enterprise disruptive innovation performance. This paper aims to systematically explore the relationship between them.Design/methodology/approachThis paper constructs a multi-level network embeddedness model and uses 58 independent studies as samples to explore the relationship between multi-level network embeddedness and enterprise disruptive innovation performance by meta-analysis.FindingsFirst, network embeddedness at the enterprise and regional levels will promote the improvement of disruptive innovation performance. Although industrial relationship embeddedness will promote the improvement of disruptive innovation performance, its structural embeddedness will bring negative effects. Second, in terms of mediating effect, policy-oriented support will promote the relationship between network embeddedness and disruptive innovation performance at the enterprise and industry levels. Compared with large enterprises, small- and medium-sized enterprises will have more advantages in the performance of multi-level network embedding and disruptive innovation performance. Under the subjective performance measurement method, the promotion effect of multi-level network embedding is more prominent.Research limitations/implicationsThis study enriches the theoretical research of network embeddedness and disruptive innovation and provides management enlightenment for the network embeddedness strategy of enterprise disruptive innovation. Limited by data samples and article length, future research can further expand literature samples to test the stability of variable relationships and test the moderating effects of more internal and external factors.Originality/valueFirst, it constructs a theoretical analysis model of "point-line-surface" multi-level network embedding and disruptive innovation performance of enterprises and expands the theoretical analysis framework of network embedding and disruptive innovation performance. The second is to explore the influence mechanism of multi-level network embeddedness and enterprise disruptive innovation performance. Third, it deepens the theoretical understanding of the moderating variables of the impact of network embeddedness and enterprise disruptive innovation performance.
Keyword ：
Disruptive innovation Disruptive innovation Meta-analysis Meta-analysis Multi-network Multi-network Network embeddedness Network embeddedness
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| GB/T 7714 | Shen, Neng , Zhang, Jing , Cao, Yangchun . Find the "best evidence" of the relationship between network embeddedness and enterprise disruptive innovation performance [J]. | BUSINESS PROCESS MANAGEMENT JOURNAL , 2024 , 30 (7) : 2456-2481 . |
| MLA | Shen, Neng et al. "Find the "best evidence" of the relationship between network embeddedness and enterprise disruptive innovation performance" . | BUSINESS PROCESS MANAGEMENT JOURNAL 30 . 7 (2024) : 2456-2481 . |
| APA | Shen, Neng , Zhang, Jing , Cao, Yangchun . Find the "best evidence" of the relationship between network embeddedness and enterprise disruptive innovation performance . | BUSINESS PROCESS MANAGEMENT JOURNAL , 2024 , 30 (7) , 2456-2481 . |
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Approaches to stimulating the initiative of collaborative cooperation of multiple subjects and the enthusiasm of public-private collaborative supervision are important to ensure the high-quality development of the social public health system. This study constructs a four-agent evolutionary game model with a medical enterprise, health administrative department, medical institution, and the social public as the core subjects. Using MATLAB 2018b to conduct simulation analysis, the cooperation strategy and operation mechanism of multiple subjects in the social public health system under public-private collaborative supervision are revealed, and the evolutionary stability strategy of multiple subjects under different situations is further explored. The results show (1) three evolutionary stability points in the system, which all exist in a state of loose government supervision. (2) Increasing the penalty limit can effectively regulate the behavior of medical enterprises and medical institutions; however, it is not conducive to the performance efficiency of the government in the long run. (3) Government incentives can stimulate the enthusiasm of all subjects to participate in the social public health system but should be controlled within a reasonable range. Excessive financial incentives make it easy for medical enterprises and institutions to form policy dependence.
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| GB/T 7714 | Shen, Neng , Zhang, Jing , Cao, Yang Chun et al. Clear the fog: Can public-private collaborative supervision promote the construction of a high-quality public health system? [J]. | MANAGERIAL AND DECISION ECONOMICS , 2024 , 46 (1) : 52-66 . |
| MLA | Shen, Neng et al. "Clear the fog: Can public-private collaborative supervision promote the construction of a high-quality public health system?" . | MANAGERIAL AND DECISION ECONOMICS 46 . 1 (2024) : 52-66 . |
| APA | Shen, Neng , Zhang, Jing , Cao, Yang Chun , Zhang, Lin , Zhang, Guoping . Clear the fog: Can public-private collaborative supervision promote the construction of a high-quality public health system? . | MANAGERIAL AND DECISION ECONOMICS , 2024 , 46 (1) , 52-66 . |
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在阐释新质生产力创新联盟主体职能与运行机制基础上,构建政府、创新企业和学研机构为主体的博弈模型,从供给、需求和环境侧角度分析政策工具组合如何推动多主体参与新质生产力创新联盟的运行演化.研究发现:政策工具组合能实现多元主体积极参与的均衡稳定策略;三类政策工具均能提升主体参与积极性,但刺激效果存在差异,并且政策工具的力度需控制在科学范围.
Keyword ：
创新联盟 创新联盟 政策工具 政策工具 新质生产力 新质生产力
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| GB/T 7714 | 沈能 , 张静 , 曹阳春 . 政策工具组合如何驱动新质生产力创新联盟运行演化? [J]. | 软科学 , 2024 , 38 (11) : 1-9 . |
| MLA | 沈能 et al. "政策工具组合如何驱动新质生产力创新联盟运行演化?" . | 软科学 38 . 11 (2024) : 1-9 . |
| APA | 沈能 , 张静 , 曹阳春 . 政策工具组合如何驱动新质生产力创新联盟运行演化? . | 软科学 , 2024 , 38 (11) , 1-9 . |
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In recent years, data has increasingly become the "new oil" for 21st-century economic development. However, there is still a gap in how the development of big data promotes the improvement of urban carbon unlocking efficiency (UCUE). Utilizing advanced double machine learning (DML) methods, and treating the big data comprehensive pilot zone (BDCPZ) as a quasi-natural experiment, we employ panel data from 282 Chinese cities spanning 2011 to 2022 to study the impact of big data policies on UCUE and its mechanisms. The study finds that: (1) Big data policies significantly enhance carbon unlocking efficiency, and their importance in carbon unlocking is confirmed even when alternative machine learning models are used.(2) Regarding the mechanisms, big data policies improve carbon unlocking efficiency through three pathways: government modernization, enterprise intelligent development, and economic transformation.(3) Heterogeneity analysis reveals that the carbon unlocking benefits of big data policies are more pronounced in large cities, old industrial base cities, digital economy dividend cities and key environmental protection cities. We also provide insights for strengthening the construction of big data, alleviating carbon emission pressures, and achieving the goals of "dual carbon".
Keyword ：
Big data policy Big data policy Double machine learning Double machine learning Mechanism analysis Mechanism analysis Urban carbon unlocking efficiency Urban carbon unlocking efficiency
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| GB/T 7714 | Shen, Neng , Zhang, Guoping , Zhou, Jingwen et al. Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 372 . |
| MLA | Shen, Neng et al. "Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 372 (2024) . |
| APA | Shen, Neng , Zhang, Guoping , Zhou, Jingwen , Zhang, Lin , Wu, Lianjun , Zhang, Jing et al. Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 372 . |
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