|dc.description.abstract||The result of sales forecast underpins vital production decisions, in which accurate forecast results in complete and orderly planning of overall production and sales operations, precise control over cost and predictable enterprise profit and its long-term development. Contrarily, inaccurate forecast can cause defective planning, either increasing idle and inventory cost, or enlarging stockout cost and losing customers.
It has been difficult for truck wooden boxes manufacturers to respond effectively to volatile marketing environments by predicting future sales volume through only statistics methods based on past sales data as well as intuitive judgment.
Therefore, this research, which focuses on professional manufacturers of truck wooden boxes, aims to discuss the forecast status and adaptability for variant forecast methods in hope of providing the manufacturer a more accurate method to calculate forecast results.
Widely used in forecast research recently, Gray System Theory is also adopted as one of the forecast methods, besides the two widespread methods of Moving Average and Exponential Smoothing in this field. Based on the three prediction models, the combined forecast is conducted using the separate solutions of Moving Average, Exponential Smoothing and Gray Prediction to investigate whether the combined forecast model matches the sales volume prediction of truck wooden boxes.
Empirical analyses reveal a combined forecast model, with weighting factor determined by recursive algorithms, offers better prediction in training scope, performance test scope and the whole scope, which justifies that the aforesaid model with weighting factor decided by recursive algorithms is the best one, and is suitable for sales volume prediction of truck wooden boxes.||en_US|