Seeing beyond the obvious in Ex-post Evaluation of Science, Technology and Innovation Projects

Almeida, Liliane de; Pacheco, Diego Augusto de Jesus; Jung, Carlos Fernando; Caten, Carla Schwengber ten

doi:10.1080/09537325.2021.2009795

Cited by 1 publication

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“…Therefore, how to ensure the scientific nature of the urban science and technology innovation assessment system has become the main research content of the relevant experts and scholars at this stage [11]. Literature [12] detects the assessment method of the followup development of science and technology innovation projects, pointing out that the follow-up assessment method of science and technology innovation at this stage is very complex and by the premise of the establishment of specific conditions. And proposed a new testing model to better understand STI project follow-up.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Urban Science and Technology Innovation Performance Assessment Model - Based on VAR Methodology Perspective

Zhang

2024

Applied Mathematics and Nonlinear Sciences

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Conventional science and technology performance assessment methods and indicators can no longer meet the current needs of urban science and technology innovation performance assessment, and innovative research is urgently needed. In this study, the four elements of innovation input, innovation process, innovation output, and innovation guarantee are taken as the first-level indicators of the urban science and technology innovation performance assessment index system. The G1 entropy value correction method is used to assign weights to the urban science and technology innovation performance assessment index system to reduce subjective arbitrariness. Finally, the specific situation of innovation elements and innovation performance in S city was selected, and the influence relationship between innovation elements and innovation performance assessment was analyzed using a vector autoregressive model. The results show that the method of assessing the city’s science and technology innovation performance based on the VAR model is simple and easy to operate, the confidence coefficient of the assessment model is more than 0.7, and the mean value of the validity CVR is 0.703. The assessment results have a high degree of credibility and validity and effectively promote the region’s scientific and technological self-reliance and self-improvement.

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Section: Introductionmentioning

confidence: 99%

Optimization of Urban Science and Technology Innovation Performance Assessment Model - Based on VAR Methodology Perspective

Zhang

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

show abstract

Seeing beyond the obvious in Ex-post Evaluation of Science, Technology and Innovation Projects

Cited by 1 publication

References 20 publications

Optimization of Urban Science and Technology Innovation Performance Assessment Model - Based on VAR Methodology Perspective

Optimization of Urban Science and Technology Innovation Performance Assessment Model - Based on VAR Methodology Perspective

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