Research On Multistage Ordering Policy Of Fresh Agricultural Product

Fresh agricultural products retailers are facing many a challenge to meetcustomers’ demand and make ordering decisions, one of them is the traditional methodof demand forecasting which cannot match exactly with fresh agricultural products.Another example is the truth that retailers are forced to make multistage orderings tocater to multiple consumer preferences, since the familiar old single ordering policydoes not behave well,. Yet they always neglect effects of demand cannibalizationbrought by the multistage ordering policy. Besides, the risk preference of retailer itselfcould affect ordering decision. In this study, multistage ordering policy of freshagricultural products is analyzed, and during the process a more effective method ofdemand forecasting is proposed and analyzed, how demand cannibalization and riskpreference affect retailer’s optimized decisions is discussed at the same time.Firstly, the basic conception and the ordering policy of fresh agricultural productsare generally introduced, analyze the main related influencing factors with respect to theordering decision of fresh agricultural products, describe the demand forecastingmethod as well as its progress, and discuss two fundamental implements and methodsabout ordering policy study.Secondly, under the assumption that demand has already known by retailers, thetwo-stage ordering policy and its demand cannibalization are analyzed. When retailersells both fresher and less fresh products at the same time, customers can choose whichkind they shall buy, while in the single ordering process this is not goanna happen. Maincharacteristics are discussed as well as its effect to retailer’s optimal decision.Thirdly, consider the demand to be stochastic that will be more fit in the practice,the two-stage ordering policy and its demand cannibalization are analyzed. The mostdifference from the known demand situation is how demand is settled. Actually, demandis divided into two partitions, which are customer scale and amount a single customerwill purchase. Customer arrives at retailers’ stochastically and relies on a certain sort ofStochastic Process, when every customer will decide the quantity they need totallydepend on the freshness and price. Therefore, this method is proved to be better atforecasting demand of fresh agricultural products. Positive and comprehensive effectsthat multistage ordering has on customer scale and retailer’s profit as well as orderingdecision are also discussed. Ultimately, divide a single sale period of fresh agricultural product into three parts,during each part the customer scale and price varies from each other. Based on thesepartitions, the whole need can be generated and retailer’s ordering policy is analyzedwith considering retailer’s risk preference style. Mainly probe into the effects ofdeteriorating coefficient and risk preference coefficient on retailer’s optimal decision.