Development of the evaluation model for national innovation capability

Jeon, Jeong-Hwan; Geetha, Selvaraj; Kang, Deakook; Narayanamoorthy, Samayan

doi:10.1080/09537325.2021.1900561

Cited by 7 publications

(2 citation statements)

References 12 publications

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“…Therefore, the evolutionary learning process constitutes the nature of national innovation capability (Nelson and winter, 1982). National innovation capability is recognized as the ability of the states to produce social and economic results through innovation in the field of science and technology and it consists of six factors of human resources, R&D investment, start-up investment as a result of industry-academy cooperation, inter-company cooperation, infrastructures and the culture of science education (Jeon et al , 2021). There is a difference between national innovation capability and national innovation capacity.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Designing a multi-division model of national innovation capability promotion based on social network analysis

Torabandeh

Dorri

Rabieh

et al. 2022

JSTPM

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Purpose This study aims to design a national innovation capability appraisal model. This would indicate Iran’s competitiveness situation among regional countries and suggest factors influencing Iran’s performance promotion. Design/methodology/approach The methodology included four sections: bibliometric analysis to discover intellectual evolution of innovation capability and related concepts; construction of a multi-division structure of national innovation capability according to the clusters extracted from bibliometric results, and experts’ opinions; creating dynamic network data envelope analysis (DEA) according to designed structure, and analysis of Iran’s performance among regional countries; identification and prioritization of the factors extracted from experts’ opinions that improve Iran’s performance in created network using Fuzzy decision-making trial and evaluation laboratory method. Findings The contemporary bibliometric analysis by its extracted clusters proved the necessity of a multi-division for measuring national innovation capability performance that each division and indicators of each step were designed according to clusters concepts. In designed structure, dynamic network DEA results revealed the weakness of Iran’s performance in the third division in the transformation of patents and high-tech imports to high-tech and creative exports, which led to proposing improving factors by getting experts’ opinions to enhance Iran’s performance in this division by prioritizing them. Research limitations/implications One of the limitations of this research was that the indicators used in three phases of national innovation capability in DEA were extracted only from the World Intellectual Property Organization database. Another limitation was the number of experts in focus group sessions because due to the difficulty of gathering them in one session, the researchers lost the participation of some of these recognized experts. Also, the research concentration was on the improvement of the third phase of national innovation capability, in which Iran’s performance was weak. Originality/value Creating a relationship between the divisions of dynamic network DEA, as a national innovation capability appraisal model, and the concepts of clusters extracted from reviewing the intellectual structure and evolution of innovation capability and related concepts.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Designing a multi-division model of national innovation capability promotion based on social network analysis

Torabandeh

Dorri

Rabieh

et al. 2022

JSTPM

View full text Add to dashboard Cite

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“…The first view suggests that technological innovation can significantly reduce environmental pollution as constant research and development can transform enterprises [ 9 , 10 , 11 , 12 ]. This can occur at the level of inter-provincial, municipal, or pollution-intensive industries [ 13 , 14 , 15 , 16 , 17 , 18 ]. Technological innovation can significantly reduce environmental pollution and offset the cost effect of pollution control through long-term technical effects.…”

Section: Introductionmentioning

confidence: 99%

Spatial Pattern of Technological Innovation in the Yangtze River Delta Region and Its Impact on Water Pollution

Zhang

Jiao

et al. 2022

IJERPH

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The impact of technological innovation on water pollution is an important parameter to determine and monitor while promoting and furthering a region’s economic development. Here, exploratory spatial data analysis was used to analyze: the spatial patterns of technological innovation and water pollution in the Yangtze River, the changes in technical innovation and the resulting changes in water pollution, and the impact of technological innovation on water pollution. The following major inferences were drawn from the obtained results: (1) The spatial pattern of innovation input has a single-center structure that tends to spread. The patent innovation output has evolved, from a single spatial pattern with Shanghai as the core to a diffusion structure with three cores-Hangzhou, Shanghai, and Nanjing. (2) The aggregation mode of water pollution has evolved from the original “Z” mode to a new mode of core agglomeration, and water pollution is constantly being reduced. (3) The trends of change in patent innovation output and innovation input are roughly the same, while the trends of both and that of water pollution are contrary to each other. (4) The correlations between innovation input, patented innovation output, and water pollution are relatively low. From the perspective of spatial distribution, the number of cities with medium and high levels of gray correlation with water pollution is the same.

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A cross-country analysis of the factors driving innovation performance in the Global South

Niazi

2023

Policy Studies

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Development of the evaluation model for national innovation capability

Cited by 7 publications

References 12 publications

Designing a multi-division model of national innovation capability promotion based on social network analysis

Designing a multi-division model of national innovation capability promotion based on social network analysis

Spatial Pattern of Technological Innovation in the Yangtze River Delta Region and Its Impact on Water Pollution

A cross-country analysis of the factors driving innovation performance in the Global South

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