2021
DOI: 10.1111/sjtg.12412
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Applying Evolutionary Economic Geography beyond case studies in the Global North: Regional diversification in Vietnam

Abstract: Hitherto, the path‐dependent understanding of regional diversification in Evolutionary Economic Geography (EEG) has drawn largely on insights into industrialized countries. However, in the past few decades several regions in the Global South have undergone rapid structural transformations despite starting out with unfavourable regional asset bases. This raises the question as to whether the strong emphasis on endogenous capabilities in EEG also provides a sound theoretical framework for explaining these tremen… Show more

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Cited by 11 publications
(4 citation statements)
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References 51 publications
(133 reference statements)
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“…Zhu et al (2017) and He et al (2018) found a positive influence of relatedness on the development of new industries in Chinese regions. Breul and Pruß (2022) confirmed such a finding for regions in Vietnam. They showed that foreign-owned companies may act as global pipelines accessing external capabilities and contributing to diversification in unrelated industries in Vietnam.…”
Section: Regional Diversification In the Global Southsupporting
confidence: 72%
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“…Zhu et al (2017) and He et al (2018) found a positive influence of relatedness on the development of new industries in Chinese regions. Breul and Pruß (2022) confirmed such a finding for regions in Vietnam. They showed that foreign-owned companies may act as global pipelines accessing external capabilities and contributing to diversification in unrelated industries in Vietnam.…”
Section: Regional Diversification In the Global Southsupporting
confidence: 72%
“…We start calculating relatedness and complexity. These measures have been successfully applied both to investigate regions and countries in the Global North, as well as in the Global South (Alonso & Martín, 2019;Breul & Pruß, 2022;Galetti et al, 2021;He et al, 2018). To control for any variations, we followed Balland et al (2019) and divided the data into three non-overlapping periods: 2006-2010, 2011-2015 and 2016-2019.…”
Section: Measuring Relatedness and Complexitymentioning
confidence: 99%
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