This article investigates the spatial distribution of Chinese–owned businesses in Milan, Italy, in 2001 and 2011. Our analyses draw on administrative data held in the business register, integrated with both business and population Census data. First, spatial scan analysis is used to explore clustering patterns of Chinese–owned businesses. Subsequently, regression analysis is applied to investigate whether, and to what extent, a selected set of business features and the characteristics of the business environment at the neighbourhood level predict the propensity of Chinese–owned businesses to cluster in space. Findings indicate that Chinese–owned businesses are not randomly distributed in Milan, but they rather tend to cluster in specific neighbourhoods. Our analyses also show that such a propensity to cluster can be predicted very well by the selected set of covariates, with some variation across time.

Pisati, M., Riva, E., Lucchini, M. (2020). The Spatial Location of Chinese Businesses: A Longitudinal Analysis of Clustering Patterns in Milan, Italy. POLIS, 34(1), 5-32 [10.1424/96438].

The Spatial Location of Chinese Businesses: A Longitudinal Analysis of Clustering Patterns in Milan, Italy

Maurizio Pisati;Egidio Riva
;
Mario Lucchini
2020

Abstract

This article investigates the spatial distribution of Chinese–owned businesses in Milan, Italy, in 2001 and 2011. Our analyses draw on administrative data held in the business register, integrated with both business and population Census data. First, spatial scan analysis is used to explore clustering patterns of Chinese–owned businesses. Subsequently, regression analysis is applied to investigate whether, and to what extent, a selected set of business features and the characteristics of the business environment at the neighbourhood level predict the propensity of Chinese–owned businesses to cluster in space. Findings indicate that Chinese–owned businesses are not randomly distributed in Milan, but they rather tend to cluster in specific neighbourhoods. Our analyses also show that such a propensity to cluster can be predicted very well by the selected set of covariates, with some variation across time.
Articolo in rivista - Articolo scientifico
Chinese–owned Businesses; Locational Patterns; Spatial Clustering; Spatial Scan Analysis; Milan.
English
2020
34
1
5
32
reserved
Pisati, M., Riva, E., Lucchini, M. (2020). The Spatial Location of Chinese Businesses: A Longitudinal Analysis of Clustering Patterns in Milan, Italy. POLIS, 34(1), 5-32 [10.1424/96438].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/270741
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