| dc.description.abstract | Abstract
Organic vegetables are the exceptional products in the agriculture industry with many strict restrictions and regulations defined on the organic practice, which distinguishes it from the conventional agriculture and increases the production cost. In order to raise profit margin, the high production cost should be subsidized by a better price, which does require a well-balanced market demand and supply. However, most of organic vegetable producers rely on their intuition and previous experiences to forecast the market demand for the production plan without an integral and systematic production flow chain. Consequently, this kind of practice will result in a significant impact on the production strategy and management in every link of the supply chain, which is usually reflected on the reduction of profit.
Modern information technology in conjunction with effective prediction methods could assist mangers on decision making in production control to meet market demands and significantly reduce the risks of loss resulted from over-production. Sequential Grey Prediction of GM (1,1) model based on “Grey Theory” posses the properties of easy processing in non-linear problems, simple calculation and requiring less data points for prediction, therefore, GM(1,1) model has been well adopted for forecasting the demand on organic agriculture products. In this study, we particularly applied Sequential Grey Prediction of GM (1,1) model to forecast the market demand on organic agriculture products while compared to two conventional methods, Regression Model and Time-Series Analysis. After ascertaining the suitability of each method according to the analyzed results, it demonstrated that GM (1,1) model could produce much more accurate predictions and require smaller sample size than Regression Model and Time-Series Analysis could.
In addition to prediction model comparison, this study categorized the Key Success Factors (KSFs) of organic agriculture product logistics by surveying the experts in the organic production to permute the relational importance grades of KSFs. The results of local grey relational analysis showed that managers should pay great attention on logistics operation dimension; and, the results of global grey relational analysis indicated that managers should emphasize on inspecting the quality of products to establish the trust among consumers on their organic agriculture practice. The outcomes of KSFs study should benefit organic company owners and managers on setting operation policies and marketing strategies to well position themselves in a dynamic and highly competitive market. | en_US |