The Impact of Government Competition on Regional R&amp;D Efficiency: Does Legal Environment Matter in China’s Innovation System?

He, Baocheng; Wang, Jiawei; Wang, Jiaoyang; Wang, Kun

doi:10.3390/su10124401

Cited by 18 publications

(12 citation statements)

References 51 publications

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“…H3a, H3c, and H3d are rejected while H3b is strongly supported. This is consistent with most research results [3,52]. Excessive government subsidies have reduced the incentive for enterprises to innovate while mature technology markets are conducive to increasing innovation outputs.…”

Section: Hypothesessupporting

confidence: 91%

“…Wang et al [51] evaluated the industrial eco-efficiency of Fujian province in China with an SBM-DEA model. He et al [52] analyzed the impact of government competition on regional R&D efficiency through the DEA model. Dai et al [53] studied the spatial evolution of technological innovation efficiency and talents' sticky wages.…”

Section: Research On Innovation Efficiencymentioning

confidence: 99%

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Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model

Loh

Chen

2020

Sustainability

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As China is undergoing economic transformation and facing increasing energy and environmental problems, it is essential to pay special attention to sustainable innovation governance. This research took industrial waste and total energy consumption into consideration and uses a super efficiency slack-based measure (SBM) model to empirically evaluate the regional innovation efficiency of Chinese provinces. The results showed that the efficiency of China’s regional sustainable innovation has not changed significantly over recent years. In addition, the results also showed large and varying degrees of innovation efficiency across different provinces. Eastern China, in comparison to central and western China, showed higher innovation efficiency. In addition, we found a slightly increasing trend in terms of innovation efficiency disparities between the three areas. On the basis of these findings, the reasons for the innovation efficiency gap between different regions were analyzed. The impacts of influential factors on sustainable innovation efficiency were further explored. We found that technology market maturity affected sustainable innovation efficiency positively, while government funding had a negative impact on sustainable innovation efficiency. Industrial structure and environmental regulations had no significant effect on sustainable innovation efficiency. Finally, some implications for improving governance performance in terms of sustainable innovation were provided.

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Section: Hypothesessupporting

confidence: 91%

Section: Research On Innovation Efficiencymentioning

confidence: 99%

Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model

Loh

Chen

2020

Sustainability

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“…(2) Selection index of industrial innovation activity subsystem: select parameters according to the industrial technology innovation chain, namely, R&D investment intensity (X5), R&D full-time personnel (X6), digestion and absorption of imported technology expenditure (X7), and number of effective invention patents (X8), national or industry patent standard number (X9), and patent ownership transfer income and license income (X10) as indicators of single parameters [21,22].…”

Section: Selection Of Subsystem Indicatorsmentioning

confidence: 99%

[Retracted] Identification of Driving Factors of Scientific and Technological Innovation in the New Material Industry Based on the Theory of Complex Adaptive System: Taking the Construction of Green Innovation System as an Example

Liu

2021

Complexity

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Complex adaptation systems are the main development direction of China’s current green innovation research. New material industry is one of the key entry points to accelerate the construction of modern industrial system and promote innovation, green, and efficient development. Under the requirements of China’s current low-carbon development, China’s green innovation system is developing rapidly. Green innovation complicates traditional innovation models and their functions and improves economic development. The purpose of this paper is to study the theoretical analysis framework of applying complex adaptive systems and to analyze and calculate the characteristics of the current status of green innovation systems in multiple industries in China’s manufacturing industry. Analysis is as follows. The experimental group and the control group are set for comparison, and the data are organized by applying complex adaptive system theory and data analysis methods. Experimental data show that the coordinated development of the green innovation systems in various industries in China is not balanced, with a difference of more than three times; the parameters of the various green innovation systems within the industry are unbalanced, and the difference is more than five times. The experimental results show that the green innovation subject can strategically interact by adjusting the ratio of resource allocation through the constructed green innovation system model. The green innovation system with complex adaptive system theory is conducive to the development of the green system. It can save about 23% of green innovation time and improve efficiency by about 15%, to promote the development of green innovation in China.

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“…They concluded that competition is a very significant trigger factor for the companies to generate innovative products. Parallel to them, Blank and Naveh (2018), He et al (2018), Moen, Tvedten, and Wold (2018) and Shi, Song, and Teng (2019) also underlined the importance of this situation for their studies.…”

Section: Literature Reviewmentioning

confidence: 85%

Stochastic hybrid decision‐making based on interval type 2 fuzzy sets for measuring the innovation capacities of financial institutions

2020

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This study aims to construct a hybrid decision‐making approach to the stochastic evaluation for the innovation capacity of financial institutions. For this purpose, interval type 2 fuzzy DEMATEL‐ANP is used for weighting the criteria and dimensions. Additionally, TOPSIS and VIKOR methods based on interval type 2 fuzzy sets are considered to rank the alternatives. The novelty of the study is to propose a set of criteria and dimensions of innovation capacity with the supported literature. Another novelty is to propose an extended method of DEMATEL‐ANP by using interval type 2 fuzzy sets as well as an integrated method of interval type 2 fuzzy stochastic decision‐making with the Monte Carlo simulation. The results indicate that organizational dimension of innovation capacities has the highest importance between the set of criteria and the state‐owned banks have been more appropriate than both the private and foreign banks for generating the innovation capacities in the financial institutions. However, the analysis illustrates that stochastic decision‐making models could provide more extensive results than the conventional methods including the expert priorities. This study could be also extended by using different multicriteria decision‐making methods such as MOORA and ELECTRE and also, the cross‐country analysis could be applied for the future studies.

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The Impact of Government Competition on Regional R&D Efficiency: Does Legal Environment Matter in China’s Innovation System?

Cited by 18 publications

References 51 publications

Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model

Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model

[Retracted] Identification of Driving Factors of Scientific and Technological Innovation in the New Material Industry Based on the Theory of Complex Adaptive System: Taking the Construction of Green Innovation System as an Example

Stochastic hybrid decision‐making based on interval type 2 fuzzy sets for measuring the innovation capacities of financial institutions

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