Modeling consumer’s behavior for packed vegetable in “Mayadin management organization of Tehran” using artificial neural network

The major factor in successful marketing and development strategies is a correct understanding of consumer behavior. Recognizing the consumer behavior is the key to market development. It is impossible to establish systematic relationship between producers and consumers while the consumer behavior is not recognized. Demand elasticities seem very important in decision-making processes and in causing different behavior of consumer in buying occasions. Producers, food processors, and retailers need to recognize consumer’s behavior in forming the demand to plan well their production and selling, thus, demand elasticities are of crucial importance. The shortage of studies in the field of estimating demand and elasticity using artificial neural networks (ANN) among the economic issues was the most important motivation of this study. Parameters were estimated using the ANN that is widely used and is called multi-layer feed-forward neural network (MLFN). It is important to point out that among the input variables, some socio-demographic variables were included, it seems that beside the traditional economic variables some non-economic factors can affect the consumers’ choices as well. In this paper the consumer’s behavior in the “Mayadin Management Organization” of Tehran for vegetable crops, summer crops like potato, onion, tomato was modeled using the ANN and particularly the demand curve and the elasticities were estimated.