Department of Strategic Development, Harbin Bank, Harbin, China.
PLoS One. 2021 Jun 22;16(6):e0250802. doi: 10.1371/journal.pone.0250802. eCollection 2021.
The aims are to improve the efficiency in analyzing the regional economic changes in China's high-tech industrial development zones (IDZs), ensure the industrial structural integrity, and comprehensively understand the roles of capital, technology, and talents in regional economic structural changes. According to previous works, the economic efficiency and impact mechanism of China's high-tech IDZ are analyzed profoundly. The machine learning (ML)-based Data Envelopment Analysis (DEA) and Malmquist index measurement algorithms are adopted to analyze the dynamic and static characteristics of high-tech IDZ's economic data from 2009 to 2019. Furthermore, a high-tech IDZ economic efficiency influencing factor model is built. Based on the detailed data of a high-tech IDZ, the regional economic changes are analyzed from the following dimensions: economic environment, economic structure, number of talents, capital investment, and high-tech IDZ's regional scale, which verifies the effectiveness of the proposed model further. Results demonstrate that the comprehensive economic efficiency of all national high-tech IDZs in China is relatively high. However, there are huge differences among different regions. The economic efficiency of the eastern region is significantly lower than the national average. The economic structure, number of talents, capital investment, and economic efficiency of the high-tech IDZs show a significant positive correlation. The economic changes in high-tech IDZs can be improved through the secondary industry, employee value, and funding input. The ML technology applied can make data processing more efficient, providing proper suggestions for developing China's high-tech industrial parks.
目的是提高分析中国高新技术产业开发区（IDZ）区域经济变化的效率，确保产业结构的完整性，并全面了解资本、技术和人才在区域经济结构变化中的作用。根据以往的研究工作，深入分析了中国高新技术 IDZ 的经济效率和影响机制。采用基于机器学习（ML）的数据包络分析（DEA）和 Malmquist 指数测量算法，分析了 2009 年至 2019 年高新技术 IDZ 的经济数据的动态和静态特征。此外，还建立了一个高新技术 IDZ 经济效率影响因素模型。基于高新技术 IDZ 的详细数据，从经济环境、经济结构、人才数量、资本投资和高新技术 IDZ 的区域规模等维度分析了区域经济变化，进一步验证了所提出模型的有效性。结果表明，中国所有国家级高新技术 IDZ 的综合经济效率相对较高，但不同地区之间存在巨大差异。东部地区的经济效率明显低于全国平均水平。经济结构、人才数量、资本投资和高新技术 IDZ 的经济效率呈显著正相关。通过第二产业、员工价值和资金投入可以提高高新技术 IDZ 的经济变化。应用的 ML 技术可以使数据处理更加高效，为中国高新技术产业园区的发展提供适当的建议。
