Modeling determinants of the Generation Z regional perception on the periphery: To stay or to leave

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Regional attractiveness plays a crucial role in regional economic development and competitiveness. Despite interest in out-migration from peripheral regions, most studies overlooked Generation Z members in perceiving these factors. Therefore, the paper aims to examine the effect of the regional perception of Generation Z on their expectation of out-migration from the peripheral region. The focus group comprised 56 respondents (stakeholders) selected through purposive sampling by regional development agencies in three peripheral regions of the Czech Republic to identify regional perception indicators. The exploratory factor analysis and the principal component analysis were used to detect latent constructs of the identified regional perception indicators. Logistic regression was used to model the association between latent constructs and Generation Z’s intention to leave or to stay in the peripheral region. Economic, social, and environmental dimensions were detected as latent constructs of regional perception indicators. The first dimension represents smartness and opportunities; the second, openness, is accompanied by culture; and the third, a safe and clean environment. The estimation results suggest the effect of the economic and lifestyle dimensions (β = 0.528, p < 0.001) and the social dimension (β = 0.292, p < 0.01) of the regional perception on the intention of Generation Z to leave or stay in the peripheral region, without the effect of the environmental dimension (β = 0.033, p = 0.740). The paper emphasizes the importance of economic, lifestyle, and social indicators of regional perception in place-based policies to retain Generation Z in the peripheral regions.

Acknowledgment
This paper was supported by the Technology Agency of the Czech Republic – program ÉTA under Grant TL03000525 – Design of a Model of Metropolitan Areas in the Czech Republic affected by depopulation.

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    • Table 1. Regional perception indicators
    • Table 2. Correlation matrix of the regional perception indicators
    • Table 3. Rotated factors matrix of the regional perception indicators
    • Table 4. Coefficients of the regional perception indicators components
    • Conceptualization
      Lukaš Danko, Pavel Bednař, Kamila Voštova
    • Data curation
      Lukaš Danko
    • Formal Analysis
      Lukaš Danko, Pavel Bednař, Kamila Voštova
    • Project administration
      Lukaš Danko, Kamila Voštova
    • Visualization
      Lukaš Danko, Pavel Bednař
    • Writing – original draft
      Lukaš Danko, Pavel Bednař
    • Methodology
      Pavel Bednař
    • Supervision
      Pavel Bednař, Kamila Voštova, Šarka Harušťakova
    • Validation
      Pavel Bednař, Kamila Voštova, Šarka Harušťakova
    • Writing – review & editing
      Pavel Bednař, Kamila Voštova, Šarka Harušťakova
    • Investigation
      Kamila Voštova, Šarka Harušťakova
    • Resources
      Šarka Harušťakova