Health evaluation and key influencing factor analysis of green technological innovation system

Liu, Li; Zhang, Zaisheng; Wang, Zhe; Xu, Jiangtao

doi:10.1007/s11356-022-21106-z

Cited by 7 publications

(4 citation statements)

References 53 publications

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“…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.…”

Section: Efficiency-oriented Valuementioning

confidence: 99%

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

Zhou,

2024

Systems

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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.

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Section: Efficiency-oriented Valuementioning

confidence: 99%

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

Zhou,

2024

Systems

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“…Furthermore, in terms of decision analysis methods, the main methods included are the TOPSIS method, the ELimination Et Choix Traduisant la REalité (ELECTRE) method, the VIse Kriterijumski Optimizacioni Racun (VIKOR) method, etc. The TOPSIS method is widely used in social [42], industry [43], engineering [44], and other domains of judgment and assessment [45]. The ELECTRE method is a multi-criteria decision-making method that can quantify the decision-making process and resolve complex decision-making issues, but it has the drawback of requiring more factors that must be taken into account and contains non-data table factors, which can have erratic effects on decision-making and are unsuitable for long-term decision-making [46].…”

Section: The Research On Green Innovationmentioning

confidence: 99%

The Impact of Green Innovation Capacity on Urban Economic Resilience: Evidence from China’s Yangtze River Delta Region

Lv,

Zeng,

Liu

2023

Sustainability

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Urban green innovation plays a crucial role in achieving sustainable urban economic development, and urban economic resilience is an important manifestation of urban economic development. This prese nt study aims to investigate how green innovation contributes to urban economies’ resilience, which is essential for long-term urban agglomeration expansion and sustainable economic development. To decrease subjectivity and achieve comprehensive evaluation, this study first constructs an index system for evaluating green innovation capability on urban economic resilience, which contains 21 indicators in three areas, including innovation input, innovation output, and green innovation foundation, and the performs a scientific evaluation using the TOPSIS method. On this basis, using the Super-SBM model, the green innovation efficiency value of cities in the Yangtze River Delta (YRD) is calculated. Finally, ArcGIS 10.8 software is used to classify the economic resilience of the 26 cities in the YRD city cluster and analyze the spatial layout characteristics of urban economic resilience. The results show that: (1) the decision evaluation model used in this study is stable and effective, and it can effectively address the issues of subjective assessment processes and information redundancy; (2) green innovation capacity has a positive contribution to urban economic resilience, and its contribution is more significant for cities with strong economic strength; and (3) the green innovation capacity of the YRD city cluster is unevenly distributed, with Shanghai, Suzhou, Hangzhou, and Nanjing having high levels of green innovation capacity and strong urban economic resilience, thus forming the core area of cities radiating outward, showing a “core-edge” spatially. Finally, suggestions for improving the overall economic resilience of urban agglomerations are provided.

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“…Li et al [13] maintained that GTI can be divided into substantive and strategic, with the former enhancing the market value of the firm and the latter used to meet market demand. Liu et al [14] pointed out that GTI is a technology that covers product design, production, consumption, and recycling.…”

Section: Literature Review and Research Frameworkmentioning

confidence: 99%

The Driving Factors of Green Technology Innovation Efficiency—A Study Based on the Dynamic QCA Method

2023

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The problems of environmental pollution and resource shortages are becoming increasingly prominent with the advances in technology and the improvements in social productivity levels. How to coordinate the innovating subjects, and strengthen the interaction and cooperation among the subjects to improve the green technology innovation efficiency (GTI efficiency) is an important issue to be solved urgently. This paper constructs a multisubject collaborative analysis framework of “government–market–society” for the GTI efficiency based on the pluralistic co-governance theory. Using 30 provinces (or regions, cities) in China from 2016 to 2020 as research samples, we analyzed the driving factors of GTI efficiency using the dynamic QCA method. Furthermore, the configuration effects of the driving factors were further analyzed in the time and spatial dimensions. The results show that: (1) The single driving factor does not constitute the requisite condition for high GTI efficiency. (2) There are three types of paths to realize high GTI efficiency: “government–market driven”, “market–society driven”, and “government–market–society synergistic promotion”. Among them, the “government–market-driven” path is subdivided into “government—internal-market driven” and “government-supported–external-market driven”. (3) In the time dimension, the “market–society driven” path has prominently enhanced its driving effect on GTI efficiency, while the driving effect of the other three paths is little changed. In the spatial dimension, the coverage of the “government-supported–external-market driven” path appears to have obvious regional differences, and the explanation degree of the central region is higher, while the other three paths do not have obvious regional differences. Based on the perspective of configuration, these research results enrich the related research on the driving factors of GTI efficiency in the time and spatial dimension. It provides enlightenment for boosting the coordinated development of regional GTI efficiency and realizing sustainable economic growth.

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Health evaluation and key influencing factor analysis of green technological innovation system

Cited by 7 publications

References 53 publications

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

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

The Impact of Green Innovation Capacity on Urban Economic Resilience: Evidence from China’s Yangtze River Delta Region

The Driving Factors of Green Technology Innovation Efficiency—A Study Based on the Dynamic QCA Method

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