Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December 8–10, 2023, Guangzhou, China

Research Article

Research on Evaluation and Spatial-Temporal Differentiation Laws of Regional Innovation Quality Based on Spatial Autocorrelation Model

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  • @INPROCEEDINGS{10.4108/eai.8-12-2023.2344367,
        author={Lin  Wang and Xue  Ding},
        title={Research on Evaluation and Spatial-Temporal Differentiation Laws of Regional Innovation Quality Based on Spatial Autocorrelation Model},
        proceedings={Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December 8--10, 2023, Guangzhou, China},
        publisher={EAI},
        proceedings_a={MSIEID},
        year={2024},
        month={4},
        keywords={regional development innovation quality spatial econometricss},
        doi={10.4108/eai.8-12-2023.2344367}
    }
    
  • Lin Wang
    Xue Ding
    Year: 2024
    Research on Evaluation and Spatial-Temporal Differentiation Laws of Regional Innovation Quality Based on Spatial Autocorrelation Model
    MSIEID
    EAI
    DOI: 10.4108/eai.8-12-2023.2344367
Lin Wang1,*, Xue Ding1
  • 1: Wuhan Business University
*Contact email: 20190115@wbu.edu.cn

Abstract

The significant improvement of the regional integration development in Yangtze River Delta and researches on its innovation efficiency have received increasing attention. This paper conducted spatial autocorrelation analysis on the innovation efficiency scores of 41 regions in the Yangtze River Delta from 2012 to 2020. Through the measurement of innovation quality by DEA-Malmquist model, it is found that the differentiation degree of innovation quality level in the Yangtze River Delta region is continuously improving. Further research on these scores through spatial autocorrelation analysis has showed that the spatial distribution of innovation quality level in the Yangtze River Delta region has a significant spatial positive correlation. With high-value regions as the center, the innovation quality level of their surrounding regions is also relatively high; and the regions with the same spatial relationship show obvious contiguous distribution characteristics according to the results of local spatial autocorrelation analysis.