Decision model for country site selection of overseas clothing plants

Abstract

Clothing manufacturers’ direct investment and joint ventures in developing regions have grown rapidly in the last few decades. An inappropriate decision on site selection can cause adverse affects on productivity and increase manufacturing and logistical costs. Manufacturers often face with difficulties during the decision-making process, due to vague and subjective considerations. The process is hampered with variables that cannot be represented in terms of objective values, such as country risk and community facilities. The decision on plant location thus relies mostly on the subjective intuition and assessment of the manufacturer. This paper explains the development of a decision-making model for a clothing plant location, using the feed-forward neural network with an error back-propagation (EBP) learning algorithm and a fuzzy analytical hierarchy process (FAHP). Significant variables in the selection of a clothing plant location will be identified and input into the proposed decision-making model. A suitability index was computed for each site. The sites with higher suitability indices were more appropriate for the establishment of a clothing plant. It was also identified that those variables considered on plant location with lower evaluation weights can be neglected without affecting the prediction accuracy of the proposed decision model .