Abstract
This article mainly evaluates the regional innovation service capacity through the TOPSIS method. Firstly, a regional collaborative innovation network is constructed and the Yangtze River Delta region is selected for analysis. Secondly, an evaluation index is constructed for innovation service capability, fuzzy principal component analysis is used to refine quantitative and qualitative index data of innovation service capability, and the index weight is calculated. Then the region of the Yangtze River Delta is selected and TOPSIS method is used to assist in the effective decision-making process of the evaluation of innovative service capabilities. Due to the large amount of data in this article, MATLAB programming is used. Finally, through the comparative analysis of the results, countermeasures and suggestions are put forward from the perspective of the improvement of collaborative innovation service capabilities.
Highlights
In the current research trends of regional collaborative innovation, foreign scholars’ research on cross-regional collaborative innovation focuses on the research perspective, the relationship with innovation performance, and Scientific Programming influencing factors
Under the leadership of regional collaborative innovation, whether an enterprise’s innovation service capability can be improved is crucial to the overall performance of the enterprise. It can be seen by combing the relevant research at home and abroad that the existing literature provides a basic analysis framework for the expansion of innovation service capabilities and sustainable development at the practical level, but there are relatively few studies on regional innovation service capabilities, and the existing evaluation indicators. e synergy between innovation elements in the system has not been considered
This study uses TOPSIS to assist in the evaluation of innovative service capabilities
Summary
In the current research trends of regional collaborative innovation, foreign scholars’ research on cross-regional collaborative innovation focuses on the research perspective, the relationship with innovation performance, and Scientific Programming influencing factors. E research on the relationship between regional collaborative innovation and innovation performance focuses on the evaluation of cross-regional system innovation capability [7]. Under the leadership of regional collaborative innovation, whether an enterprise’s innovation service capability can be improved is crucial to the overall performance of the enterprise. It can be seen by combing the relevant research at home and abroad that the existing literature provides a basic analysis framework for the expansion of innovation service capabilities and sustainable development at the practical level, but there are relatively few studies on regional innovation service capabilities, and the existing evaluation indicators. Through a comparative analysis of the results, this article obtained an optimization plan for improving innovation service capabilities and proposed countermeasures and suggestions on how to guide the flow of innovation elements and improve regional collaborative innovation
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