在德国,知识密集型企业位于哪里?-使用指数随机图模型的解释框架
Mathias Heidinger1, Fabian Wenner1, Sebastian Sager1
1Technische Universität München, Arcisstraße 21, 80333 Munich, Germany.
概括
在德国,公司的定位选择受到区域资源和连通性的影响. 网络分析显示,虽然人口和大学等因素是有利的,但交通接入和知识库类型在很大程度上影响了这些决定.
科学领域:
- 经济地理 经济地理
- 网络分析 网络分析
- 空间经济学 空间经济学
背景情况:
- 公司的定位决策受到空间和关系因素的影响.
- 了解知识密集型企业的网络结构至关重要.
- 现有的模式往往侧重于个别城市的位置,而不是坚定的网络.
研究的目的:
- 分析德国地区的位置和关系数据如何影响基于知识的企业位置.
- 开发一种创新的网络分析方法,将指数随机图建模 (ERGM) 和互锁网络模型 (INM) 结合起来.
- 调查在公司网络中可访问性和超局部连接的重要性.
主要方法:
- 组合属性数据 (交通,大学,人口) 和关系数据 (旅行时间,关系频率).
- 利用集成ERGM和INM的网络分析来做出公司的定位决定.
- 分析了德国186个具有不同城市化程度和四种知识库类型的功能区域.
主要成果:
- 人口和大学等区域特征对公司的位置有积极的影响.
- 靠近交通基础设施是一个关键因素,在知识库中重要性不同.
- 基于可访问性和知识库类型的位置评估中观察到明显的差异.
结论:
- 该研究提供了对指导知识密集型公司位置的网络结构的见解.
- 位置和关系数据对于理解复杂的公司位置动态至关重要.
- 针对不同的以知识为基础的经济活动,可能需要量身定制的交通便利化策略.
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