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Articles

Marshallian Sources of Relatedness and Their Effects on Firm Survival and Subsequent Success in China

Pages 346-366 | Published online: 22 May 2017
 

abstract

Relying on a large panel of Chinese firms, this article attempts to investigate the effects of technological relatedness on firm survival and subsequent success (e.g., profits and productivity). The results show that related establishments that colocate together outperform their counterparts located elsewhere, although it is not clear whether these findings are due to the presence of externalities or alternative explanations. To explore this issue, several proxies for the Marshallian sources of relatedness are further developed to better reveal the underlying mechanisms that drive relatedness. The findings show that technological proximity helps to respectively reduce the costs of moving goods, people, and ideas, thus providing strong support for Marshallian theories of agglomeration. The ownership structure of the firm matters, however. Specifically, wholly privately owned enterprises are more successful than firms where the state is a minority shareholder at converting technologically related spillovers into higher profits and higher-efficiency gains.

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Erratum

Acknowledgments

I would like to thank Canfei He, Yang Rudai, David Rigby, Ron Boschma, and other participants of the Evolutionary Economic Geography conference at Peking University for helpful comments. This project received funding support from the School of Economics at Peking University and the Natural Science Foundation of China No. 71603009.

Supplemental Material

Supplemental data for this article can be accessed here.

Notes

1 See Frenken, Cefis, and Stam (Citation2015) for a recent review of the literature.

2 As part of the 12th five-year plan, for instance, the State Council released its National New-Type Urbanization Plan (guojia xinxing chengzhen hua guihua), which aims to establish twenty new sustainable inter-city clusters by 2020.

3 A threshold of 0.35 is applied to the network, showing 1 percent of network ties, to better visualize actual relatedness between industries.

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