Political risk and MNC's location decision - a dynamic perspective
Date
2006
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Publisher
Southern New Hampshire University
Abstract
This thesis builds a dynamic modeling tool for analyzing the impact of political risk on the production location decisions of multinational corporations (MNCs). The choice of location by MNCs involves various decisional factors and the time- dependent interactions among them. A sophisticated location analysis has to incorporate these complexities in a holistic perspective. The combined impact of learning and political risk on the location decision was studied in this thesis through computation simulation. The key findings are as follows. a) The cost of operating in a host country increases with increasing political risk. Hence, a country with high political risk receives increasing investment at a later point in time than a country with lower political risk. From a country’s national perspective, FDI policy makers need to focus on reducing the transaction cost due to political risk in order to receive earlier investments .b) An increased rate of learning by MNCs helps to reduce their transaction costs and this helps them expand internationally at an earlier stage compared to a slower learning MNC. A fast learning MNC in a risky environment can outpace a slow learner in terms of lower operating costs and profitability. It thus follows that MNCs need to consider the risk of the host country in combination with their learning capacity when evaluating international production locations. c) If the alternative location choice is a cheaper destination but has high political risk, smaller MNCs cannot gain a cost advantage by investing in such a host country because they lack economies of scale necessary to utilize this potential advantage. It only makes economic sense for large MNCs to move their production locations to riskier countries for cost advantages. Finally, the dynamic methodology employed in this thesis is a novel analytical contribution to the discipline of international business. By altering the variables in the simulation model, various scenario analyses specific to a firm and country can be performed which can be of value for FDI decision makers in a variety of settings including corporate strategy, marketing, finance and economic and social policy. (Author abstract)
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Dissertation