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What drives European multinationals to the European Union neighbouring countries? A mixed-methods analysis of Italian investment strategies

Andrea Ascani et al.

Environment and Planning C: politics and space2016https://doi.org/10.1177/0263774x16628180article
AJG 3ABDC B
Weight
0.57

Abstract

This article aims to investigate the economic integration between the European Union and its neighbouring countries by exploring the location drivers of Italian Multinational Enterprises in 33 destination countries including the New Member States of the European Union and the European Neighbouring Countries. The article compares market- and efficiency-seeking motivations with asset-seeking strategies. The analysis is based on a mixed-methods approach. The quantitative analysis assesses the location determinants of 518 Italian Multinational Enterprises that invested in the area in the years 2003–2008, whereas qualitative information on strategic location decisions is collected by means of in-depth interviews with executives in two of the largest Italian Multinational Enterprises active in the region. Market-seeking considerations are still predominant drivers of location decisions in European Union Neighbouring Countries together with resource-seeking motivations. However, different Multinational Enterprises develop diversified strategies to increase their access to these areas, which are of increasing interest for global investors.

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https://doi.org/https://doi.org/10.1177/0263774x16628180

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@article{andrea2016,
  title        = {{What drives European multinationals to the European Union neighbouring countries? A mixed-methods analysis of Italian investment strategies}},
  author       = {Andrea Ascani et al.},
  journal      = {Environment and Planning C: politics and space},
  year         = {2016},
  doi          = {https://doi.org/https://doi.org/10.1177/0263774x16628180},
}

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Evidence weight

0.57

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.60 × 0.4 = 0.24
M · momentum0.67 × 0.15 = 0.10
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.