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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳文方(Wen-Fang Wu) | |
| dc.contributor.author | Lin Han | en |
| dc.contributor.author | 韓琳 | zh_TW |
| dc.date.accessioned | 2021-06-08T04:15:08Z | - |
| dc.date.copyright | 2011-08-26 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-18 | |
| dc.identifier.citation | 1. 洪楚源（民94）。服裝與紡織。高雄市：國立科學工藝博物館。
2. 黃政莊（民88）。「流行趨勢預測作業」: 因應臺灣紡織業發展與流行趨勢之演變。經濟部科技研究發展專案研究報告（編號88-EC-2-A-17-0229）。未出版。 3. 李懿文（1996）。流行服裝商品企劃架構之研究。輔仁大學織品服裝研究所碩士論文，未出版，新北市。 4. Celia Frank, A.G., Amar Raheja, & Les Sztandera., Forecasting women's apparel sales using mathematical modeling. International Journal of Clothing Science and Technology, 2003. 15(2): p. 107-125. 5. Thomassey, S. and M. Happiette, A neural clustering and classification system for sales forecasting of new apparel items. Applied Soft Computing, 2007. 7(4): p. 1177-1187. 6. Zhang, G.P. and M. Qi, Neural network forecasting for seasonal and trend time series. European Journal of Operational Research, 2005. 160(2): p. 501-514. 7. Michael Nelson, T.H., William Remus, Marcus O'Connor, Time series forecasting using NNs: Should the data be deseasonalized first? Journal of Forecasting, 1999. 18(5): p. 359-367. 8. Sun, Z.-L., et al., Sales forecasting using extreme learning machine with applications in fashion retailing. Decision Support Systems, 2008. 46(1): p. 411-419. 9. Yu, Y., T.-M. Choi, and C.-L. Hui, An intelligent fast sales forecasting model for fashion products. Expert Systems with Applications, 2011. 38(6): p. 7373-7379. 10. Brown, R.G., Statistical forecasting for inventory control. 1959, New York: McGraw-Hill. 11. Brown, R.G., Smoothing, forecasting and prediction of discrete time series. 1963, Englewood Cliffs, N.J.: Prentice-Hall. 12. Muth, J.F., Optimal Properties of Exponentially Weighted Forecasts. Journal of the American Statistical Association, 1960. 55(290): p. 299-306. 13. Yule, G.U., On a Method of Investigating Periodicities in Disturbed Series, with Special Reference to Wolfer's Sunspot Numbers. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 1927. 226(ArticleType: research-article / Full publication date: 1927 / Copyright c 1927 The Royal Society): p. 267-298. 14. Nikolaevich, K.A., Stationary sequences in Hilbert space. Bull. Math. Univ. Moscow, 1941. 2(6): p. 1-40. 15. Box, G.E.P., Jenkins, Gwilym M., Time series analysis. Forecasting and control. 1976, San Francisco: Holden-Day. 16. Newbold, P., C. Agiakloglou, and J. Miller, Adventures with ARIMA software. International Journal of Forecasting, 1994. 10(4): p. 573-581. 17. 葉小蓁（2006）。時間序列分析與應用。臺北市：臺大法律學院圖書文具部總經銷。 18. Quenouille, M.H., The analysis of multiple time-series. 1957, New York: Hafner Pub. Co. 19. Bidarkota, P.V., The comparative forecast performance of univariate and multivariate models: an application to real interest rate forecasting. International Journal of Forecasting, 1998. 14(4): p. 457-468. 20. Sims, C., Macroeconomics and Reality. Econometrica, 1980. 48(1): p. 1-48. 21. Dhrymes, P.J. and D.D. Thomakos, Structural VAR, MARMA and open economy models. International Journal of Forecasting, 1998. 14(2): p. 187-198. 22. Litterman, R.B., Forecasting with Bayesian Vector Autoregressions: Five Years of Experience. Journal of Business & Economic Statistics, 1986. 4(1): p. 25-38. 23. Engle, R.F. and C.W.J. Granger, Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 1987. 55(2): p. 251-276. 24. Granger, C.W.J., Newbold, P., Spurious regressions in econometrics. Journal of Econometrics, 1974. 2(2): p. 111-120. 25. Dickey, D.A. and W.A. Fuller, Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 1979. 74(366): p. 427-431. 26. 賴景昌（2004）。總體經濟學。臺北市：雙葉書廊。 27. 行政院主計處（民56-94）。中華民國臺灣地區國民所得。台北市：作者。 28. Hiro Y. Toda, T.Y., Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 1995. 66(1-2): p. 225-250. 29. Lettau, M. and S. Ludvigson, Time-varying risk premia and the cost of capital: An alternative implication of the Q theory of investment. Journal of Monetary Economics, 2002. 49(1): p. 31-66. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22299 | - |
| dc.description.abstract | 因女性服飾零售市場具有特殊產業特性，極需發展一套有效的銷售預測工具，而縮減式向量自我迴歸模型(Vector Autoregressive，簡稱VAR)是應用最廣的時間序列模型，可以同時加入多個內生變數，討論這些變數的交互影響關係，以做出適當的預測。本研究探討台灣外部經濟條件對女性服飾公司之營運影響，並特別應用VAR，選擇棉花價格、匯率、衣著類CPI指數及台灣各行業受雇員工每人月平均薪資四個變數分析國內某女性服飾公司之實際銷售數據。在衝擊反應分析方面，本研究發現薪資與銷售量最具連動關係，若薪資提高，則下一期銷售量就會增加，反之亦然。此外，誤差變異數分解發現，除銷售量自身變動因素外，薪資具有較大影響力，長期時可解釋21.5%的變異；其次為匯率，長期時可解釋10%的變異。以上經驗顯示，本研究所建模型可提供服裝銷量預測的一個新方向。 | zh_TW |
| dc.description.abstract | The women’s apparel industry has specific characteristics and requires suitable tools for sales forecast. The proposed model, VAR, widely used in various fields, can incorporate multiple endogenous variables and the interactions of these variables would lead to appropriate forecast. This study discusses how the external economic conditions in Taiwan affect women’s apparel sales performance. It applies the reduced autoregression model to analyze data collected from a certain fashion retailer. Four variables, cotton price, exchange rate, CPI index of apparel, and the average monthly salary per job in Taiwan, are chosen as the external economics environmental parameters in this article. The result from impulse response function shows the sales revenue will grow following the month of salary increase, and vice versa. It indicates a corresponding relationship between sales and salary. After analyzing the variance decomposition, it is found that excluding sales’ fluctuation, salary has the most impact on sales, accounting for 21.5% of the variation in the long term. In addition, exchange rate explains 10% as well. In conclusion, the proposed model has introduced a new direction in sales forecast for women’s apparel industry. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T04:15:08Z (GMT). No. of bitstreams: 1 ntu-100-R98546029-1.pdf: 3230887 bytes, checksum: 1f0bf72bc345ec3f3db55ec1f63a16ec (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 目錄 I
圖目錄 III 表目錄 IV 第壹章 緒論 1 1.1 研究背景 1 1.2 研究目的 3 1.3 論文架構 5 第貳章 文獻回顧 7 2.1 女性服裝產業中的「預測」 7 2.2 預測方法介紹 11 2.2.1 指數平滑法 11 2.2.2 ARIMA models 12 2.2.3 Vector ARIMA models 13 第參章 模型設定 15 3.1 平穩的時間序列 15 3.2 單根檢定 15 3.3 VAR模型 17 3.3.1 最適落後期數 18 3.4 衝擊反應函數 18 3.5 預測誤差變異數分解 20 第肆章 實證結果與分析 22 4.1 變數資料說明與處理 22 4.2 單根檢定 27 4.3 VAR模型 31 4.4 衝擊反應函數 32 4.5 預測誤差變異數分解 40 第伍章 結論與建議 42 5.1 研究結論 42 5.2 研究限制 43 5.3 研究建議 44 參考文獻 45 | |
| dc.language.iso | zh-TW | |
| dc.title | 外部經濟條件對女性服飾公司之營運影響研究–以台灣某知名女性服飾品牌業者為例 | zh_TW |
| dc.title | A Study of the Effects on External Economic Conditions on Women’s Apparel Sales Performance–Taking a Well-known Taiwanese Brand Company as an Example | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 尤政平(Cheng-Ping Yu) | |
| dc.contributor.oralexamcommittee | 王銘宗(Ming-Tzong Wang),李國光(Gwo-Guang Lee) | |
| dc.subject.keyword | 女性服飾,銷售預測,向量自我迴歸模型,衝擊反應函數,變異數分解, | zh_TW |
| dc.subject.keyword | Women’s apparel,Sales forecasting,Vector autoregression,Impulse response,Variance decomposition, | en |
| dc.relation.page | 46 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2011-08-18 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
| 顯示於系所單位： | 工業工程學研究所 | |
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| ntu-100-1.pdf 目前未授權公開取用 | 3.16 MB | Adobe PDF |
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