An Application to Investigate Sales Forecast of Agricultural Products & its Supply and Sales Relationships-Using Grey Theory

碩士 === 國立嘉義大學 === 運輸與物流工程研究所 === 91 === Abstract Ever since Taiwan has been a member of the World Trade Organization (WTO). It makes a great impact on domestic traditional sales infrastructure, and also causes an imbalance problem between the supply site and demand site in agricultural pr...

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Bibliographic Details
Main Authors: Huang, Chung-Tai, 黃仲達
Other Authors: Ko, Chien-Chuan
Format: Others
Language:zh-TW
Published: 2003
Online Access:http://ndltd.ncl.edu.tw/handle/93796234814914840409
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Summary:碩士 === 國立嘉義大學 === 運輸與物流工程研究所 === 91 === Abstract Ever since Taiwan has been a member of the World Trade Organization (WTO). It makes a great impact on domestic traditional sales infrastructure, and also causes an imbalance problem between the supply site and demand site in agricultural products. Therefore, it is necessary to forecast the manufacturing and sales of the agricultural products beforehand to reduce costs and increase benefits using prediction tools. However, most of managers in the agricultural industry usually rely on old experiences to predict their sales volume. Theoretically, this will be feasible if the sales environments are stable. Once sales environments have become unstable and worse, using reliable prediction tools to maintain benefits and reduce costs is necessary for the agricultural industry. Although various prediction models for long-term or short-term prediction have been widely used in many businesses, these models often require a large amount of data to predict accurately. Most of these models may not be suitable for the forecasting of agricultural products, because its’ short-term variations caused by seasons or natural damages often will affect the prediction accuracy. The main goal of this thesis is to apply some approaches based on “Grey Theory", which have advantages such as simplicity and fewer data to predict sales and make sales decisions. Compared the results to two other traditional methods, such as Regression Model and Time-Series Analysis, it can produce better performance. “Supply Chain Management” (SCM) is increasingly important in global logistics. The cooperation relationship between the agricultural suppliers and distributors has become more important. Cooperating with stable suppliers has becomes one key factor to achieve profit for business. Therefore, the other goal of this thesis is to exploit the “Gray Relational Analysis“ in order to determine “How to select a good supplier“, and evaluate the factors that affect the cooperation relationship between the agricultural suppliers and distributors. We hoped that the manufacturers, the upper distributors, the middle distributors, and the retailers share all the profits from one another, the economic benefit among their cooperation, and management risks. The entire experiment is performed using one middle distributor in southern Taiwan who supplies bamboo shoots and squids. Based on the accuracy of the predictions, and from the evaluations of model’s grade as well as the amount of samples used, “Gray Prediction“ obtains the best performance among different comparisons using different prediction models, and thus also proves its feasibility simultaneously. Based on the investigation of the correlation factors between the suppliers and distributors. We found the factor, “willing to step back or sacrifices for certain supplier,” shows the worst performance in the proposed correlation factors. And, the top three highest correlation factors are “the flexibility of the supplier”, “whether the quality of the products from the supplier satisfies the needs”, and “the supplier’s reputation”.