Computational intelligence to model the export behavior of multinational corporation subsidiaries in Malaysia

Edwards, R. and Abraham, A. and Petrovic-Lazarevic, S. (2005) Computational intelligence to model the export behavior of multinational corporation subsidiaries in Malaysia. Journal of the American Society for Information Science and Technology, 56 (11). pp. 1177-1186. ISSN 1532-2882

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Abstract

The academic literature suggests that the extent of exporting by multinational corporation subsidiaries (MCSs) depends on their strategic role in the multinational corporation (MNC), their age and size, and whether their products are targeted at niche or commodity markets. In particular, it is claimed that MNCs seek to invest in a particular country if its resources adopt a vertically integrated structure, if the country grants regional or global sales mandates to their subsidiaries, or if it has been established in a host market for a longer time and is thus more likely to promote subsidiary exports. Our aim in this article is to model the complex export pattern behaviour of multinational corporation subsidiaries in Malaysia using a Takagi–Sugeno fuzzy inference system. The proposed fuzzy inference system (FIS) is optimized by using neural network learning and evolutionary computation. Empirical results clearly show that the proposed approach could model the export behaviour reasonably well compared to a direct neural network approach.

Item Type: Article
Additional Information: The first author is affiliated to Asia Pacific University of Technology & Innovation, Bukit Jalil, Kuala Lumpur.
Uncontrolled Keywords: Export behavior; Corporation subsidiaries
Subjects: H Social Sciences > HC Economic History and Conditions > HC79 Technological innovations
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HD Industries. Land use. Labor > HD72 Economic growth, development, planning
H Social Sciences > HF Commerce > HF5410 Marketing. Distribution of product.
Depositing User: Ms. Rachel Lim
Date Deposited: 22 May 2016 04:08
Last Modified: 22 May 2016 04:08
URI: https://eprints.apiit.edu.my/id/eprint/786

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