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Introduction

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Book cover Evolutionary Economic Geography in China

Part of the book series: Economic Geography ((ECOGEO))

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Abstract

Regional industrial dynamics can be seen as a complex process, consisting of both qualitative and quantitative changes. Even though quantitative changes like regional growth in terms of employment, value added, and output may reflect the rise and fall of regional economies and the restructuring of industrial areas, these changes often take place as a result of qualitative changes in regional industrial structures (Neffke et al. 2011). Regions are shaped by a never-ending process of creative destruction (Schumpeter 1939, 1942), referring not only to the capability of local entrepreneurs to develop new products or processes that can replace traditional ones and render the latter obsolete in the short term but also to the capability of a certain region to generate and attract new industries to offset the destruction caused by industrial exit and decline in the long term. Such a dual process is closely related to the resilience of regional economies in face of disturbances and shocks (e.g., institutional transformation, policy changes, fluctuation of currency exchange rates, and technological shifts) that may result in decline, atrophy, or even shutdown of an entire industry in regions (Martin and Sunley 2015a, b). This view inspires plenty of economic geographers to examine the geographical implications of creative destruction (Hassink and Shin 2005; Stam and Martin 2012), and we now have several examples of where such process has forced the transformation of regional industrial structures in Europe, North America, and Japan (Grabher 1993; Hassink 2007; Schamp 2005), the Asian newly industrialized economies since the mid-1990s (Cho and Hassink 2009; Van Grunsven and Smakman 2005), and emerging regional economies such as mainland China since the 2000s (He and Wang 2012; Zhu and He 2016; Zhu et al. 2014).

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Notes

  1. 1.

    Please see Brandt et al. (2012) for further details.

  2. 2.

    We follow Neffke et al. (2011) and calculate proximity indicators based on data in one country. First, China is a large country with a high level of regional disparity, which means calculation based on data in such a big economy should be sufficient. Second, calculating proximity indicators based on Chinese export data rather than world trade data may allow us to better control China’s unique, nationwide political and economic environments.

  3. 3.

    We focus on the secondary industry and therefore exclude data on agriculture.

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  1. College of Urban and Environmental Sciences, Peking University, Beijing, China

    Canfei He & Shengjun Zhu

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He, C., Zhu, S. (2019). Introduction. In: Evolutionary Economic Geography in China. Economic Geography. Springer, Singapore. https://doi.org/10.1007/978-981-13-3447-4_1

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