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Erschienen in: The Annals of Regional Science 1/2017

23.09.2016 | Original Paper

The transformation of the Prato industrial district: an organisational ecology analysis of the co-evolution of Italian and Chinese firms

Erschienen in: The Annals of Regional Science | Ausgabe 1/2017

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Abstract

This work analyses and measures the transformation of the industrial district of Prato in the last two decades, adopting the density dependence model of Organisational Ecology. The paper has two primary research aims: (i) to investigate the recent transformation of the Prato industrial district through the foundings and failure flows of its firms’ populations, and (ii) to examine the co-evolution and reciprocal influences between the populations of the district’s Italian and Chinese firms. Through an in-depth study of the foundings and failures that have occurred in Chinese and Italian textile and clothing firms over the last two decades, this study develops analysis of demographic and organisational ecology, and investigates the processes of legitimation and competition. The results of the study indicate that the district’s Italian and Chinese firms experienced two distinct evolutionary phases during the research period: while the former declined, the latter saw development in spite of recent economic crises. The analyses also demonstrate how the evolution of Italian and Chinese populations moved in opposite directions: as the first failed, the second saw increases in the number of its foundings. This indicates the presence of a substitution effect between each firms’ population at the district level.

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Fußnoten
1
Populations’ vitality flows (births and deaths) are determined by the interaction that can take place between coexisting populations, and in turn this can have an impact on the evolution of the organisational community. In fact, the community ecology analyses the way in which bonds and relationships across populations affect the survival probability of the community as a whole (Ruef 2000).
 
2
The first is that the theory takes no account of firm size, whereas large and small firms clearly have very different effects in a population; the second is that it fails to explain negative growth rates and the negative slope of the density curve beyond the peak; the third is that firms differ with respect not only to size and economic activity, but also to geographical location (spatial heterogeneity) (Van Wissen 2004).
 
3
A Chinese firm is defined as such when it has at least an owner, a manager, or an associate of Chinese nationality. It is then possible to consider also companies and not only individual firms.
 
4
There are very few joint enterprises between the two nationalities as the two communities do not collaborate in the district. Only a 0.5 % of firms are Italian–Chinese, and they were included among Chinese firms since these Italian subjects are usually only figureheads.
 
5
The period variables have been computed as dummy variables each covering 10 years: 1990–1999, 2000–2011.
 
6
There is abundant research effort and a wide variety of approaches on co-evolution, but the major theory to investigate populations’ relationships is the Community Interdependence Theory. When an evolving population interacts with other populations, the success and survival of its members depend on the nature and strength of its ecological interactions with organisations among organisational populations. Brittain and Wholey (1988) identify the following types of interactions between two populations, according to density evolution full competition, partial competition, predatory competition, and symbiosis.
 
7
A high correlation is found between first- and second-order effects of the density of the Italian population and between the two populations. This is the reason why we will insert ecological variables one by one in the models. In order to check multicollinearity, we have also calculated the condition number. See also note no. 8.
 
8
As a role of thumbs condition number should be below 30–40; otherwise, it indicates problems of multicollinearity. However, we remind that in Organizational Ecology, there is often a problem of multicollinearity as birth, deaths, and density are often highly correlated. See, for instance, the work of Singh et al. (1991) who discuss the issues of multicollinearity and autocorrelation in OE.
 
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Metadaten
Titel
The transformation of the Prato industrial district: an organisational ecology analysis of the co-evolution of Italian and Chinese firms
Publikationsdatum
23.09.2016
Erschienen in
The Annals of Regional Science / Ausgabe 1/2017
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI
https://doi.org/10.1007/s00168-016-0790-5

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