The challenges of high-quality development in Chinese secondary cities: A typological exploration

Yizhao Du*, Rodrigo V. Cardoso, Roberto Rocco

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

The governmental initiative of high-quality development (HQD) marks a shift in the Chinese development paradigm from prioritizing speed to prioritizing quality towards comprehensive goals of economic growth, social vitality, innovation capacity, industrial upgrading, regional cooperation, and green transformation. This initiative is increasingly discussed within the framework of mega-regions, with prior studies demonstrating that they are critical arenas for promoting HQD visions. However, unevenness within mega-regions has become an important limitation to this vision. Namely, significant disparities exist between mega-regional core cities and the smaller neighboring cities in most HQD indicators. This paper conceptualizes these smaller players as secondary cities. Based on this, this paper aims to understand and differentiate the specific challenges of secondary cities facing intra-regional unevenness in the context of HQD. We build an evaluation framework and employ the TOPSIS method to evaluate 34 core cities and 180 secondary cities. Then, we introduce typological thinking to develop a meaningful classification of secondary cities based on the results of these evaluations. K-means clustering analysis identifies five secondary city types with similar profiles. The analysis supports the discussion of the characteristics and challenges of each type and may contribute to policy recommendations for a balanced HQD in mega-regional secondary cities.

Original languageEnglish
Article number105266
JournalSustainable Cities and Society
Volume103
DOIs
Publication statusPublished - 2024

Funding

This work was supported by the Sino-Dutch Bilateral Exchange Scholarship [Reference Number CPI.2200044].

Keywords

  • High-quality development
  • Intra-regional unevenness
  • K-means clustering analysis
  • Mega-regional secondary city
  • TOPSIS
  • Typological analysis

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