Research on the Mechanism and Countermeasures of Cultivating High Tech Enterprise Echelons in Yangzhou City from the Perspective of Big Data
本文从大数据视角出发,研究扬州市高新技术企业梯队培育路径与对策。通过分析企业创新能力、人才储备和融资渠道等现状,发现扬州市高新技术企业在梯队培育过程中存在创新能力不足、人才短缺和融资渠道有限等问题。为此,提出以下对策建议:一是加强企业创新能力提升,通过增加研发投入、建立研发机构和加强产学研合作,提高企业的自主创新能力;二是强化人才引进与培养,通过制定更具吸引力的人才政策、加强人才培养和优化人才环境,解决人才短缺问题;三是拓宽企业融资渠道,通过引导金融机构支持、鼓励股权融资和建立风险补偿机制,缓解企业融资难题。研究结论表明,利用大数据技术可以优化高新技术企业梯队培育机制,为扬州市高新技术企业的可持续发展提供有力支持。This study investigates the cultivation mechanisms and strategies for high-tech enterprises in Yangzhou from the perspective of big data. By analyzing the current status of innovation capabilities, talent reserves, and financing channels, the study identifies several key issues in the ladder cultivation process of high-tech enterprises in Yangzhou, including insufficient innovation capabilities, talent shortages, and limited financing options. To address these challenges, the following strategies are proposed: First, enhance corporate innovation capabilities by increasing R&D investment, establishing R&D institutions, and strengthening industry-university-research cooperation to improve enterprises’ independent innovation capabilities. Second, strengthen talent introduction and cultivation by formulating more attractive talent policies, enhancing talent training, and optimizing the talent environment to address talent shortages. Third, expand financing channels for enterprises by guiding financial institutions to provide more support, encouraging equity financing, and establishing risk compensation mechanisms to alleviate financing difficulties. The study concludes that leveraging big data technology can optimize the cultivation mechanisms for high-tech enterprises, providing strong support for the sustainable development of high-tech enterprises in Yangzhou.
Authors
- 雯 殷
Publication Details
- Journal
- E-Commerce Letters
- Published
- 2025-01-01
- DOI
- https://doi.org/10.12677/ecl.2025.144869
- Primary Topic
- E-commerce and Technology Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.00