中国的大数据政策如何影响城市的数字经济? 来自国家大数据综合试验区的证据
Xinyun Hu1, Yanling Jiang1, Pengfei Guo2
1School of business administration, Chongqing University of Science & Technology, Chongqing, China.
Heliyon
|February 1, 2024
概括
中国的大数据政策大大促进了数字经济的增长. 较高行政级别的城市更受益,创新和人力资本是发展的关键驱动力.
科学领域:
- 经济学 经济学 经济学
- 信息科学 信息科学 信息科学
- 公共政策 公共政策
背景情况:
- 数字经济正在迅速发展,由数据技术的进步推动.
- 了解政府政策对数字经济发展的影响对于可持续增长至关重要.
- 中国国家大数据综合试点区倡议为研究政策影响提供了独特的机会.
研究的目的:
- 调查大数据政策对中国数字经济发展的因果关系.
- 分析行政层面如何影响大数据政策带来的好处.
- 确定政策有效性的关键调解因素,如技术创新和人力资本.
主要方法:
- 利用2011-2019年期间来自中国280个城市的面板数据.
- 采用一种准自然实验设计,以建立国家大数据综合试验区为中心.
- 应用计量经济学方法来分析政策影响和调解效应.
主要成果:
- 大数据政策对数字经济发展产生了显著的积极影响.
- 管理层级较高的城市从这些政策中获得更大的好处.
- 技术创新和人力资本被认为是通过政策增强数字经济的关键道.
结论:
- 大数据政策是促进数字经济增长的有效工具.
- 政策实施和效益可能会受到城市的行政层次的影响.
- 利用技术创新和人力资本对于最大限度地提高数据元素的价值和推进数字经济至关重要.
相关概念视频
Selected Data About Geographic Locations
27
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
27
Levels of Use of a GIS
52
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
52
Manipulation and Analysis
26
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
26
Sampling Plans
181
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
181
Thematic Layering in GIS
38
In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
38
Applications of GIS: Disaster Management and Emergency Response
85
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
85


