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2011

Unsupervised neural models for country and political risk analysis

8 years 2 months ago
Unsupervised neural models for country and political risk analysis
This interdisciplinary research project focuses on relevant applications of Knowledge Discovery and Artificial Neural Networks in order to identify and analyse levels of country, business and political risk. Its main goal is to help business decision-makers understand the dynamics within the emerging market countries in which they operate. Most of the neural models applied in this study are defined within the framework of unsupervised learning. They are based on Exploratory Projection Pursuit, Topology Preserving Maps and Curvilinear Component Analysis. Two interesting real data sets are analysed to empirically probe the robustness of these models. The first case study describes information from a significant sample of Spanish Multinational Enterprises (MNEs). It analyses data pertaining to such aspects as decisions over the location of subsidiary enterprises in various regions across the world, the importance accorded to such decisions and the driving forces behind them. Through a pro...
Álvaro Herrero, Emilio Corchado, Alfredo Ji
Added 28 Aug 2011
Updated 28 Aug 2011
Type Journal
Year 2011
Where ESWA
Authors Álvaro Herrero, Emilio Corchado, Alfredo Jiménez
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