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題名 台灣季節性消費品銷售預測之研究
The investigation of forecasting models for the sales of seasonal consumer products in Taiwan
作者 潘家鋒
Pan, Jason
貢獻者 張逸民
Chang, Yegming
潘家鋒
Pan, Jason
關鍵詞 季節性消費品
銷售量預測
MSE
sales forecast
seasonal consumer products
winters
decomposition
mean square error
NCSS
日期 2010
上傳時間 5-Oct-2011 14:29:05 (UTC+8)
摘要 The trend seasonal demand pattern is encountered when both trend and seasonal influences are interactive. The problem of this research is to project the seasonal market sales using ice cream and fresh milk in Taiwan as examples. In order to improve the accuracy of forecast, two different methods are validated and the best forecasting method is selected based on the minimum Mean Square Error.
In this study, we present two forecasting models used for evaluation to predict seasonal market sales of ice cream, fresh milk, and air conditioner in Taiwan. It includes Winters multiplicative seasonal trend model and the Decomposition method. Two different methods are validated and the best forecasting method is selected based on the minimum Mean Square Error.
After the validation process, Winters multiplicative seasonal trend model is selected based on the minimum MSE, and the monthly sales forecast for the year of 2011 is conducted using the data(60 months). Number Cruncher Statistical System (NCSS) is used for analyzing the data which proves useful and powerful.
In summary, the results demonstrate that Winters multiplicative seasonal trend model has the smallest mean square error in this case. Therefore, we conclude that both Winters multiplicative seasonal trend model and the Decomposition model are well fitted for forecasting the seasonal market sales. Yet, Winters multiplicative seasonal trend model is the better method to be used in this study since it generates the smallest mean square error (MSE) during the period of validation.
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描述 碩士
國立政治大學
企業管理研究所
98355070
99
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0098355070
資料類型 thesis
dc.contributor.advisor 張逸民zh_TW
dc.contributor.advisor Chang, Yegmingen_US
dc.contributor.author (Authors) 潘家鋒zh_TW
dc.contributor.author (Authors) Pan, Jasonen_US
dc.creator (作者) 潘家鋒zh_TW
dc.creator (作者) Pan, Jasonen_US
dc.date (日期) 2010en_US
dc.date.accessioned 5-Oct-2011 14:29:05 (UTC+8)-
dc.date.available 5-Oct-2011 14:29:05 (UTC+8)-
dc.date.issued (上傳時間) 5-Oct-2011 14:29:05 (UTC+8)-
dc.identifier (Other Identifiers) G0098355070en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/51189-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所zh_TW
dc.description (描述) 98355070zh_TW
dc.description (描述) 99zh_TW
dc.description.abstract (摘要) The trend seasonal demand pattern is encountered when both trend and seasonal influences are interactive. The problem of this research is to project the seasonal market sales using ice cream and fresh milk in Taiwan as examples. In order to improve the accuracy of forecast, two different methods are validated and the best forecasting method is selected based on the minimum Mean Square Error.
In this study, we present two forecasting models used for evaluation to predict seasonal market sales of ice cream, fresh milk, and air conditioner in Taiwan. It includes Winters multiplicative seasonal trend model and the Decomposition method. Two different methods are validated and the best forecasting method is selected based on the minimum Mean Square Error.
After the validation process, Winters multiplicative seasonal trend model is selected based on the minimum MSE, and the monthly sales forecast for the year of 2011 is conducted using the data(60 months). Number Cruncher Statistical System (NCSS) is used for analyzing the data which proves useful and powerful.
In summary, the results demonstrate that Winters multiplicative seasonal trend model has the smallest mean square error in this case. Therefore, we conclude that both Winters multiplicative seasonal trend model and the Decomposition model are well fitted for forecasting the seasonal market sales. Yet, Winters multiplicative seasonal trend model is the better method to be used in this study since it generates the smallest mean square error (MSE) during the period of validation.		en_US
dc.description.tableofcontents TABLE OF CONTENTS
ACKNOWLEDGEMENTS................. i
ABSTRACT......................... ii
TABLE OF CONTENTS................ iii
TABLES........................... v
FIGURES.......................... vii
CHAPTER1Introduction............. 1
1.1 Problem Statement............ 2
1.2 Research Objectives.......... 3
1.3 Research Data................ 3
1.4 Organization of the Thesis... 4
CHAPTER 2 Literature Review...... 5
CHAPTER 3Two Forecasting Models for the Seasonal Demand........................... 12
3.1 Winters Multiplicative Trend Seasonal Model............................ 12
3.2 Decomposition Forecasting.... 16
3.3 Estimation and Validation.... 21
3.4 Forecasting Accuracy......... 21
3.5 Software used in the research 22
CHAPTER 4Data Collection and Analysis......................... 23
4.1 Data......................... 23
4.2 Results of Forecasting for the Monthly Sales of Ice Cream............................ 25
4.2.1 Validation................. 25
4.2.2 Forecasts.................. 34
4.3 Results of Forecasting for the Monthly Sales of Fresh Milk............................. 37
4.3.1 Validation ................ 37
4.3.2 Forecasts.................. 47
4.4 Results of Forecasting for the Monthly Sales of Air Conditioner...................... 51
4.4.1 Validation ................ 51
4.4.2 Forecasts.................. 60
CHAPTER 5Conclusion, Implications, and Future Research ........................ 65
5.1 Conclusions ................. 65
5.2 Implications ................ 66
5.3 Research Limitations ........ 66
5.4 Future Research ............. 67
References....................... 69
Appendix A....................... 73
Appendix B ...................... 76
Appendix C ...................... 80
Appendix D....................... 83
Appendix E ...................... 86
Appendix F....................... 91
Appendix G....................... 94
Appendix H....................... 98
Appendix I ...................... 104		zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0098355070en_US
dc.subject (關鍵詞) 季節性消費品zh_TW
dc.subject (關鍵詞) 銷售量預測zh_TW
dc.subject (關鍵詞) MSEzh_TW
dc.subject (關鍵詞) sales forecasten_US
dc.subject (關鍵詞) seasonal consumer productsen_US
dc.subject (關鍵詞) wintersen_US
dc.subject (關鍵詞) decompositionen_US
dc.subject (關鍵詞) mean square erroren_US
dc.subject (關鍵詞) NCSSen_US
dc.title (題名) 台灣季節性消費品銷售預測之研究zh_TW
dc.title (題名) The investigation of forecasting models for the sales of seasonal consumer products in Taiwanen_US
dc.type (資料類型) thesisen
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