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| Title: | 提高銷售預測準確性：判斷式、Prophet及混合預測方法之比較分析
Enhancing sales forecasting accuracy: a comparative analysis of judgmental, prophet, and hybrid forecasting approaches |
| Authors: | 卡西歐
Finotti, Cassio C. |
| Contributors: | 莊皓鈞
Chuang, Howard
卡西歐
Cassio C. Finotti |
| Keywords: | 預測
預測模型
判斷性預測
銷售數據
時間序列分析
Forecasting
Prophet model
Judgmental forecasts
Sales data
Time-series analysis |
| Date: | 2023 |
| Issue Date: | 2023-07-06 16:34:12 (UTC+8) |
| Abstract: | .
This thesis explores how Prophet, a time-series model by Meta, can enhance judgmental forecasts for predicting the monthly demand of ten products from a single customer of a B2B manufacturing company. The dataset spans from 2018-2022, providing monthly sales data with 2022 as the focus. Forecast accuracy is assessed using the Cumulative Forecast Error (CFE) method. Results show that the Prophet model excels judgmental forecasts in 6 out of 10 products, and a Hybrid approach of incorporating judgmental forecasts as regressors improve performance, outperforming in 8 out of 10 products. The findings show the benefits of integrating advanced statistical models like Prophet into business forecasting processes to mitigate over and underforecasting and boost accuracy. The study outlines limitations and future research opportunities, such as expanding datasets, exploring new comparison metrics, and periodically updating the Prophet model. Practical implications discuss challenges and benefits of statistical forecasting models, Prophet’s accessibility, and the need to counter underforecasting and overforecasting. By harnessing new technologies, businesses can enhance operations and improve demand forecasting accuracy. This thesis highlights the potential of merging statistical models like Prophet with judgmental forecasts and proposes areas for further exploration to refine these models’ effectiveness in business contexts. |
| Reference: | Reference
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| Description: | 碩士
國立政治大學
國際經營管理英語碩士學位學程(IMBA)
110933046 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110933046 |
| Data Type: | thesis |
| Appears in Collections: | [國際經營管理英語碩士學程IMBA] 學位論文
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