원문정보
초록
영어
Predicting sales in a shoe industry is a typical job due to unpredictable demand of products. Many models are suggested for forecasting the product in the literature over the past few decades. Most shoe manufacturing organizations are in a continuous effort for increasing their profits and reducing their costs. Exact sales forecasting is certainly an inexpensive way to meet the organization goals. This paper studies and compares different forecasting techniques as moving average, single exponential smoothing, double exponential smoothing and winter’s method. For this, domestic sales data from a shoe industry is collected and then data were analyzed by statistics technique using Minitab 17 software. The result shows that the demand of shoes fluctuate over the period of time. The factor that influences the choice of forecasting model is the least value of Mean square deviation (MSD).
목차
1. Introduction
2. Literature Review
3. Data Collection
4. Methodology
4.1. Forecasting Methods
4.2. Measuring Forecasting Error
5. Result and Discussion
6. Conclusion
References