Data-Driven Evaluation of Regional Innovation Capability

IF 4.5 3区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Journal of Global Information Management Pub Date : 2023-08-11 DOI:10.4018/jgim.327792

Yaliu Yang, Xue Wu, Yingyan Zhang, Cui Wang, F. Liu, Shuling Zhou, Fagang Hu, Conghu Liu

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引用次数: 1

Abstract

Regional innovation capability is considered an important driving force for the sustainable and high-quality development of regional economy. Therefore, data-driven evaluation method of regional innovation capability is proposed. First, the article collects regional innovation development statistics; second, min-max standardization method is used for dimensionless data processing, and anti-entropy method is used to calculate index weight; third, a composite system synergy degree model for objective and quantitative evaluation is built; finally, using Anhui Province as an example, the feasibility of the method was verified . The results indicate that the order and synergy degree of the innovation input and innovation output subsystems of Anhui Province have shown an upward trend from 2010 to 2019. However, innovation output has not been synchronized with innovation input. Therefore, suggestions for improving Anhui's regional innovation capability are proposed. This study provides theoretical and methodological support for evaluating and optimizing regional innovation capability.

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区域创新能力的数据驱动评价

区域创新能力被认为是区域经济可持续高质量发展的重要驱动力。为此，提出了基于数据驱动的区域创新能力评价方法。首先，本文收集了区域创新发展的统计数据；其次，采用最小-最大标准化方法对无量纲数据进行处理，采用反熵方法计算指标权重；第三，建立了用于客观定量评价的复合系统协同度模型；最后，以安徽省为例，验证了该方法的可行性。结果表明，2010-2019年，安徽省创新投入和创新产出子系统的有序度和协同度呈上升趋势。然而，创新产出与创新投入并不同步。为此，提出了提高安徽区域创新能力的建议。本研究为评价和优化区域创新能力提供了理论和方法支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Global Information Management INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

5.80

自引率

14.90%

发文量

118

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