What kind of urban brand ecology attracts talent best? Grey configuration analysis of 98 Chinese cities

IF 3.2 3区 工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Zhaohu Dong, Peng Jiang, Zongli Dai, Rui Chi
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引用次数: 0

Abstract

Purpose

Talent is a key resource for urban development, and building and disseminating urban brands have an important impact on attracting talent. This paper explores what kind of urban brand ecology (UBE) can effectively enhance urban talent attraction (UTA). We explore this question using a novel grey quantitative configuration analysis (GQCA) model.

Design/methodology/approach

To develop the GQCA model, grey clustering is combined with qualitative configuration analysis (QCA). We conducted comparative configuration analysis of UTA using fuzzy set QCA (fsQCA) and the proposed GQCA.

Findings

We find that the empirical results of fsQCA may contradict the facts, and that the proposed GQCA effectively solves this problem.

Practical implications

Based on the theory of UBE, we identify bottleneck factors for improving UTA at different stages. Seven configuration paths are described for cities to enhance UTA. Theoretically, this study expands the application boundaries of UBE.

Originality/value

The proposed GQCA effectively solves the problem of inconsistent analysis and facts caused by the use of a binary threshold by the fsQCA. In practical case studies, the GQCA significantly improves the reliability of configuration comparisons and the sensitivity of QCA to cases, demonstrating excellent research performance.

什么样的城市品牌生态最能吸引人才?中国98个城市的灰色配置分析
目的人才是城市发展的重要资源,而城市品牌的建设和传播对吸引人才具有重要影响。本文探讨了什么样的城市品牌生态(UBE)能有效增强城市人才吸引力(UTA)。为了建立灰色定量配置分析模型,我们将灰色聚类与定性配置分析(QCA)相结合。我们使用模糊集定性分析(fsQCA)和所提出的 GQCA 对UTA 进行了比较配置分析。研究结果我们发现 fsQCA 的经验结果可能与事实相矛盾,而所提出的 GQCA 有效地解决了这一问题。为城市提升UTA描述了七种配置路径。原创性/价值所提出的 GQCA 有效解决了 fsQCA 使用二元阈值造成的分析与事实不一致的问题。在实际案例研究中,GQCA 显著提高了配置比较的可靠性和 QCA 对案例的灵敏度,显示出卓越的研究性能。
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来源期刊
Grey Systems-Theory and Application
Grey Systems-Theory and Application MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.80
自引率
13.80%
发文量
22
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