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Urban Branding and Talent Migration: The Role of Urban Image in Shaping Migration Decisions

Li, Zinan LU (2025) SGED10 20251
Human Geography
Department of Human Geography
Abstract
This study explores how urban branding intervenes in the formation and realization of migration aspirations and capabilities among talent migrants, using Chengdu as a case study. Based on the Aspirations–Capabilities framework, this study applies mixed-methods analysis, combining quantitative data analysis, digital ethnography (analyzing government urban branding narratives and post-migrants’ experience), and semi-structured interviews (potential migrants and policymakers). The findings reveal that Chengdu’s urban branding narratives are built around livability, efficient governance, and cultural inclusiveness, which stimulates migration aspirations by shaping geographical opportunities and life goals. However, qualitative evidence also... (More)
This study explores how urban branding intervenes in the formation and realization of migration aspirations and capabilities among talent migrants, using Chengdu as a case study. Based on the Aspirations–Capabilities framework, this study applies mixed-methods analysis, combining quantitative data analysis, digital ethnography (analyzing government urban branding narratives and post-migrants’ experience), and semi-structured interviews (potential migrants and policymakers). The findings reveal that Chengdu’s urban branding narratives are built around livability, efficient governance, and cultural inclusiveness, which stimulates migration aspirations by shaping geographical opportunities and life goals. However, qualitative evidence also shows structural tensions—while branding narratives enhance perceived geographical opportunities, and further influence positive and negative liberties for high-skilled migrants, mid- and low-skilled migrants often encounter institutional and emotional constraints that undermine capability realization. The study concludes by proposing a refined theoretical framework that places urban branding as a macro-level driver in the migration decision process, emphasizing its dynamic feedback loop with migrants’ experiences. (Less)
Please use this url to cite or link to this publication:
author
Li, Zinan LU
supervisor
organization
course
SGED10 20251
year
type
M2 - Bachelor Degree
subject
keywords
Chengdu, urban branding, talent migration, Aspirations–Capabilities model, urban narrative, migration decision-making, digital ethnography
language
English
id
9195015
date added to LUP
2025-06-13 12:48:23
date last changed
2025-06-13 12:48:23
@misc{9195015,
  abstract     = {{This study explores how urban branding intervenes in the formation and realization of migration aspirations and capabilities among talent migrants, using Chengdu as a case study. Based on the Aspirations–Capabilities framework, this study applies mixed-methods analysis, combining quantitative data analysis, digital ethnography (analyzing government urban branding narratives and post-migrants’ experience), and semi-structured interviews (potential migrants and policymakers). The findings reveal that Chengdu’s urban branding narratives are built around livability, efficient governance, and cultural inclusiveness, which stimulates migration aspirations by shaping geographical opportunities and life goals. However, qualitative evidence also shows structural tensions—while branding narratives enhance perceived geographical opportunities, and further influence positive and negative liberties for high-skilled migrants, mid- and low-skilled migrants often encounter institutional and emotional constraints that undermine capability realization. The study concludes by proposing a refined theoretical framework that places urban branding as a macro-level driver in the migration decision process, emphasizing its dynamic feedback loop with migrants’ experiences.}},
  author       = {{Li, Zinan}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Urban Branding and Talent Migration: The Role of Urban Image in Shaping Migration Decisions}},
  year         = {{2025}},
}