Explicit and tacit knowledge have diverging urban growth patterns

IF 9.1 Q1 ENVIRONMENTAL STUDIES npj urban sustainability Pub Date : 2023-06-15 DOI:10.1038/s42949-023-00116-x
Linzhuo Li, Nannan Zhao
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Abstract

This article utilizes an online job recruitment dataset of more than 4.6 million jobs in China to examine the urban scaling patterns of explicit and tacit knowledge. Knowledge complexity is considered essential for economic development and innovation, and recent studies find complex economic activities of many fields concentrate more in large cities. However, it remains unclear whether the urban concentration tendency would differ by explicit and tacit knowledge, given the latter is often argued as the hard core knowledge more difficult to transfer. We measure explicit/tacit knowledge in job descriptions regarding education/experience requirements. Our analysis reveals that knowledge of different natures differs to a great extent in their property of urban concentration. Specifically, jobs requiring greater explicit knowledge show higher urban scaling rates. This, however, is not true for tacit knowledge, as it demonstrates the exact opposite pattern. Our findings suggest that while cities are centers of knowledge and innovation, the engines of continued growth tend to become more biased towards explicit rather than know-how knowledge.

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显性知识和隐性知识在城市增长模式上存在差异
本文利用中国超过 460 万个职位的在线招聘数据集,研究显性知识和隐性知识的城市扩展模式。知识的复杂性被认为是经济发展和创新的必要条件,最近的研究发现,许多领域的复杂经济活动更多地集中在大城市。然而,鉴于显性知识和隐性知识通常被认为是更难转移的核心知识,城市集聚趋势是否会因显性知识和隐性知识的不同而不同,这一点仍不清楚。我们对职位描述中有关教育/经验要求的显性/隐性知识进行了衡量。我们的分析表明,不同性质的知识在城市集中度方面存在很大差异。具体来说,需要更多显性知识的工作显示出更高的城市扩展率。然而,隐性知识的情况却并非如此,因为它表现出完全相反的模式。我们的研究结果表明,虽然城市是知识和创新的中心,但持续增长的引擎却更倾向于显性知识而非隐性知识。
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