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Discovering the Factors Affecting the Location Selection of FDI in China*

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Intelligent Data Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 5))

Abstract

Since the late 1970s, Foreign Direct Investment (FDI) has played an important role in the economic development of China. However, the growth of FDI in China has an increasingly unbalanced development between the eastern and western provinces. In this chapter, the temporal association rule (TAR) mining method is applied in discovering the factors affecting the location selection of FDI. In the light of the data set at the provincial level in the period of 1984–2001, our analysis reveals that the factors, including incoming and saving, residential consumption, GDP, infrastructure, population, education and cumulative FDI amount, have significant impacts on attracting FDI, which is consistent with existing studies. But some of other factors such as means of transportation, the loan policy, and the degree of modernization of the eastern rural area have seldom been discussed, and may represent certain special and unique characteristics of China. Such findings may be helpful for the local governments to take proper measures for attracting more FDI.

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Da Ruan Guoqing Chen Etienne E. Kerre Geert Wets

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Zhang, L., Zhu, Y., Liu, Y., Zhou, N., Chen, G. Discovering the Factors Affecting the Location Selection of FDI in China* . In: Ruan, D., Chen, G., E. Kerre, E., Wets, G. (eds) Intelligent Data Mining. Studies in Computational Intelligence, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11004011_11

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  • DOI: https://doi.org/10.1007/11004011_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26256-5

  • Online ISBN: 978-3-540-32407-2

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