建構台灣花卉市場拍賣銷售總額之預測模型

Abstract

拍賣是商品交易的方式之一，在台灣有許多大型的拍賣市場，其中包含果菜市場、毛豬市場、魚市場以及花卉市場等。相較於其他大型拍賣市場，台灣花卉市場雖然僅有台北、台中、台南、彰化、高雄等五個市場，但其拍賣銷售總額在1990~2000年間卻高達台幣100億之多。政府若能準確地預測各個花卉種類的拍賣銷售總額，便能有效地輔導台灣各地區的花農種植合適且適量的各類花卉，以提升產地的獲利，這對台灣經濟發展將會有很大的貢獻。因此，本研究之主要目的是利用近年來台灣五大花卉市場的拍賣資料，分別建構單一特定花卉之拍賣量與拍賣均價的預測模型，然後再整合此兩個模型之預測值即可得到單一特定花卉的年拍賣銷售總額預測值。由於節慶對某些特定種類花卉的拍賣銷售總額影響非常大，故本研究以康乃馨為例，將節慶(以母親節當月為例)當作解釋變數，以時間序列分析(Time Series Analysis)中之成份分解法(Decomposition method)來建構該花卉拍賣均價的預測模型；另利用時間序列分析中之ARIMA模型來預測康乃馨的拍賣量，最後將拍賣量與拍賣均價的預測值相乘即得到康乃馨的拍賣銷售總額之預測值。其他花卉亦可利用本研究方法預測該花卉之拍賣銷售總額。政府相關單位應用本研究方法預測該花卉之拍賣銷售總額。政府相關單位應用本研究方法即可有效輔導花農種植具經濟效益之花卉及適當產量。

Auction is one of the commodity tradings. In Taiwan, there are many large auction markets which include fruit and vegetable market, hog market, fish market and flower market, etc. Although Taiwan only has five flower markets (namely, Taipei, Taichung, Tainan, Changhua and Kaohsiung), the total sales at auction between 1990 and 2000 was as high as NT $ 10 billions. Taiwanese flower market has a great contribution to Taiwan's economic development. As long as the total auction sales of various types of flowers can be predicted accurately, government can effectively advise regional flower farmers to plant the right amount and right kind of flowers to increase the profit. Therefore, the main objective of this study is to use auction information collected from five Taiwanese flower markets in recent years to construct prediction models of the auction amount and average auction price for certain type of flower, respectively. Then, integrating the predicted values of these two models to obtain the predicted value of total yearly auction sales of a certain flower. In this study, Autoregressive Integrated Moving Average (ARIMA) model is utilized to predict the auction amount of a certain flower such as carnations. As festivals (such as Mother's Day) have great impact on the total auction sales of certain types of flowers, the festival day is utilized as an explanatory variable to construct the prediction model of flower average auction price using Decomposition method in time series analysis. Finally, the total auction sales of a certain flower is obtained by multiplying its predicted auction amount and predicted average auction price. The results of the proposed method can be utilized for other kind of flowers.