Title :
Using an artificial neural network to forecast the market share of Thai rice
Author :
Apichottanakul, A. ; Piewthongngam, K. ; Pathumnakul, S.
Author_Institution :
Grad. Sch., Khon Kaen Univ., Khon Kaen, Thailand
Abstract :
In this paper, the artificial neural networks (ANN) is used to estimate the market share of Thai rice in the global market. Two models are formulated under two assumptions. First, the market share depending on exporting prices of rice of Thailand, Vietnam, India, USA, Pakistan, China. Second, only the export prices of rice from Thailand, Vietnam, USA, and China are considered. The export prices are used as input parameters, while the market share of Thai´s rice in the global market is the only output parameter of the models. Annual data from 1980 to 2005 are gathered from United States Department of Agriculture (USDA) and Food and Agriculture Organization of the United Nations (FAO). The study showed that the second model provide more promising results with the minimum mean absolute percent error (MAPE) of 4.69% and the average MAPE of 10.92%.
Keywords :
agricultural products; demand forecasting; food products; globalisation; neural nets; pricing; Thai rice; artificial neural network; export price; global market; market share; Agricultural products; Artificial neural networks; Demand forecasting; Economic forecasting; Globalization; Industrial relations; Production; Supply chains; US Department of Agriculture; Uncertainty; Neural networks; back propagation; demand for rice; market share;
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
DOI :
10.1109/IEEM.2009.5373247