دانلود مقاله ISI انگلیسی شماره 9712
عنوان فارسی مقاله

تجزیه و تحلیل شبکه ای برای شناسایی استراتژی های مشترک سرمایه گذاری مستقیم خارجی ایتالیایی ها

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
9712 2013 13 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Network analysis to detect common strategies in Italian foreign direct investment
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Physica A: Statistical Mechanics and its Applications , Volume 392, Issue 5, 1 March 2013, Pages 1202–1214

کلمات کلیدی
- سرمایه گذاری مستقیم خارجی - شبکه های اقتصادی - شبکه پروژه ای -
پیش نمایش مقاله
پیش نمایش مقاله تجزیه و تحلیل شبکه ای برای شناسایی استراتژی های مشترک سرمایه گذاری مستقیم خارجی ایتالیایی ها

چکیده انگلیسی

In this paper we reconstruct and discuss the network of Italian firms investing abroad, exploiting information from complex network analysis. This method, detecting the key nodes of the system (both in terms of firms and countries of destination), allows us to single out the linkages among firms without ex-ante priors. Moreover, through the examination of affiliates’ economic activity, it allows us to highlight different internationalization strategies of “leaders” in different manufacturing sectors.

مقدمه انگلیسی

Recent trade literature has highlighted highly heterogeneous behavior of individual firms [1] and [2]. To tackle the challenges of globalization, some firms have upgraded quality, others lowered costs: employing migrants, outsourcing or off-shoring; others have merged with foreign firms and/or established subsidiaries abroad. In this paper, exploiting network analysis, we reconstruct and discuss the network of Italian firms investing abroad with the aim of highlighting possible different strategies at sector level and/or the presence of common patterns. In the last decade, complex networks analysis has received a great deal of attention in both natural and social sciences [3] as a complement of standard analyses, since it allows an alternative reconstruction of the links and the evolution of the connections between different individuals/agents/firms. It has at first been widely used to understand the basic mechanisms of the Internet, and World Wide Web [4], and e-mail networks [5]. Each of these systems is formed by agents that interact and compete receiving reciprocal advantages. The interactions are quantitatively analyzed by means of topological indexes. To exploit the potentiality of network theory has allowed substantial improvements in the understanding of the underlying mechanisms. We believe that this approach should also be common in economics, since it can improve the understanding of economic systems where firms, households, individuals and the State interact. It can also help explaining stylized facts, with simple models related to stationary and non-stationary contexts. Pioneering empirical works in economics deal with the financial markets structure [6], the European firms’ network [7], the relationship between firms and banks [8], [9] and [10]; the literature is rapidly increasing also for flows of international trade [11] and [12], and migrants and FDI. To the best of our knowledge, this study is the first application of graph and network theory to Italian Foreign Direct Investment (FDI). It aims at understanding: (i) whether the internationalization modes depend on proximity (at sector and geographical level); (ii) what are the main hubs (countries/firms) within the sectors; (iii) what are the strategies employed by the main actors (firms); (iv) whether the main actors are the largest firms. In what follows, we start by explaining the methodology used (Section 2). We then sketch the literature on heterogeneous firms and internationalization modes (focus on FDI) and explain what network theory can add to existing models and empirical analyses (Section 3). Section 4 presents the general results comparing them with the implications of the theoretical models. It also presents a focus on three sectors particularly relevant for the Italian economy; Section 5 concludes.

نتیجه گیری انگلیسی

While some years ago trade was the most important mode of internationalization, nowadays firms are characterized by more complex strategies. In Italy, firms with a complete net of affiliates (for production or commercialization) are still few (and concentrated in some sectors). At the same time internationalization has been associated with a strong reorganization of the production both within and between countries and firms. Uncertainty linked with globalization has made politicians, businessmen and citizens aware that it is crucial to constantly monitor the evolution of the international markets, in order to analyze changes and to minimize the possible negative effects on the economic system in terms of domestic employment. In this paper, using the database ICE-Reprint and exploiting the new methodology of network theory, we study the network of Italian firms investing abroad. To the best of our knowledge, this is the first study of Italian FDI based on Complex Network theory. Our analysis, which builds in the theoretical literature of heterogeneous firms [1], is however intrinsically empirical. We focus on selected manufacturing sectors, highlighting the linkages among firms and detecting the key nodes of the system (both in terms of firms and countries of destination). Through an examination of affiliates’ economic activity, we can distinguish different internationalization strategies among leaders. Our study reveals a strong heterogeneity (inter- and intra-industry).19 On the one hand, there are firms that invest abroad (horizontal FDI) using middle–large countries as productive platform to export in neighboring countries through commercial affiliates. On the other hand, vertical FDI is justified by cost-saving reasons and search for professional competencies. Information from this analysis could be used for policy purposes both at macro and micro level. We can detect for which markets Italy is lagging behind in comparison to other countries. We can also detect firms with many affiliates and/or a very intense relationship (i.e “central firms”), more likely to have a positive impact on growth and productivity. This information can provide the basis for policy prescriptions.

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