決策樹應用於情境分類歸納

台灣產業以代工製造為主體，多數企業在價值鏈中的獲利往往受到擠壓，將國際知名品牌稱為正廠品牌，將以代工製造起家的企業所創的品牌稱為副廠品牌，由於品牌力量相比懸殊，副廠在這個競爭環境需要策略層次的籌劃，才能有所突破。副廠是否能經由與通路聯盟的方式，優化產品定位，在這種正廠品牌佔優勢的產業結構發揮更大影響力，改善弱勢地位、提升獲利。如何在這副廠、連鎖店通路與正廠所構成的三元結構裡的產品定位問題對不同的影響因素產生的結果作系統性歸納並找出適合的策略是關鍵的議題。情境分析可以將複雜的變數編制納入一個具有一致性、系統性、貌似真實的情節當中，發展出多種未來可能成形的情境，將可能形成的情境加以分類歸納成數種策略應用。本研究針對知識整合議題進行探討，運用決策樹分類後萃取知識來探討其分類依據的方法如何應用於情境分類歸納的議題。研究首先考慮應用案例-品牌聯盟策略的模型中不同影響因子所產生的均衡解，應用資料庫知識發掘的概念及情境分析法將所有結果建構成情境資料庫，再運用決策樹分類法將不同的情境結果作分類歸納策略。最終從情境分類結果歸納出GSBA總規模即是本研究案例中品牌聯盟策略結構問題的關鍵因素。本研究貢獻發現藉著決策樹分類工具讓我們在供應鏈研究問題中不同的情境結果能做出適當的分類，萃取出有用的知識。

關鍵字

情境分類；情境歸納；決策樹；品牌聯盟策略

並列摘要

A large part of domestic industries is rooted in contract manufacturing but the need to develop brand powers have been fully recognized in the industry. Secondary brands rooted in contract manufacturing are in weak positions in competing with name brands. Therefore, how to develop the strategic option of a secondary brand forming an alliance with a channel brand to compete with the name brands is a significant issue. Then we can develop many scenarios which will happen in the future and continuously induce them into a lot of useful strategies by scenario analysis. This paper discusses with an issue of integration of knowledge. First, we consider a model of product positioning is constructed to analyze the feasibility of such a strategy. Then we apply concepts of knowledge discovery in database and scenario analysis to construct a database of scenarios. Finally, we use decision tree method to classify different scenarios and make an induction of them. A result we obtained is the market scale of the alliance is the determinant factor.

並列關鍵字

Scenario Classification ； Scenario Induction ； Decision Tree ； a Strategy of Brand Alliance

參考文獻

[1] Breiman, L., Friedman, J., Stone, C. J., & Olshen, R. A. (1984). Classification and regression trees: CRC press.

[5] Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques: Elsevier.

[6] Kumar, N., Radhakrishnan, S., & Rao, R. C. (2010). Private label vendor selection in a supply chain: Quality and clientele effects. Journal of retailing, 86(2), 148-158.

[8] Quinlan, J. R. (1986). Induction of decision trees. Machine learning, 1(1), 81-106.

[9] Quinlan, J. R. (1993). C4. 5: Programming for machine learning. Morgan Kauffmann.

國際替代計量

決策樹應用於情境分類歸納

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