臺灣博碩士論文加值系統

台灣許多產業是與電腦週邊設備、時尚服飾、及電子相關的產品，此類商品具有需求不確定性、銷售季短等特質，強調商品功能或特性尚未改變，卻因過期、過季，不再具有原先的價值，因此當銷售季結束後，只能以較低的價格售出。此種多樣化產品的供應與競爭，一般有兩種情形：第一、同業間的產品競爭；第二、不同世代商品的新舊之爭。儘管如此，一項新產品的出現並非立刻達到其銷售的顛峰，而是一個逐漸擴散的過程。新一代產品藉著增強新的應用與功能，擴大原有產品之市場潛量，並替代舊產品之使用者。
本研究蒐集產業競爭資訊，運用相關歷史資料推導各世代之市場需求函數；並根據企業知識管理系統中的相關經驗，將多世代模式訂定出的最適產量，代入賽局理論中探討寡占市場的猜測數量模型，以Stackedlberg雙占模式為基礎，考量企業動態競爭行為，設定雙方反應函數，訂定出最適競爭價格，與預期供給價格進行比較，選擇合適之定價策略，並將廠商成本結構導入並將市場線性需求函數改為非線性需求函數，以符合實際市場運作的情況。
其次，以Norton 與 Bass以擴散理論模型(Diffusion Theory Model)來解釋高科技產品世代交替的過程，並固定價格與廣告預算數值，以及將價格與廣告預算設為變數以基因演算法加以求解等兩種情境，比較多代產品總收益、最佳演化代數與產品上市時間。藉由產品上市時間點的掌握，與上市後獲利性的考量，求取整體產品線收益最大化希望可以適切表達企業競爭策略與產品生命週期對於多世代產品擴散過程的影響。

In Taiwan, Industries consist mainly in computer peripheral equipments, fashion clothing and electronic products. These kinds of goods share similar characteristics, for example uncertainty, sales season and etc. While the product functions or attributes have not been changed, however due to changes in demand, these products will have to be sold for lower prices as a result. These kinds of variety product’s supply and competence, in general, have following two conditions：(1) Product competence in the same industries；(2) Product competence from different industries. A new emerging product is not intended to achieve a high sales volume; in fact it is intended for a diffusion process. Newer generation products with enhanced applications and functions will utilize market’s full potential, hence replacing the older generation products.
Our research searches industry’s competitive information and utilizes relevant historical data to infer the market demand function of each generation. According to experiences of enterprise knowledge management system, we utilize multi-generation model to decide the fittest volume and to confer the speculated quantity model of oligopoly market for the Game Theory. On the basis of the Stackelberg duopoly model, we consider the enterprise dynamic competitive behaviors to setup the mutual reaction function and to decide the fittest competitive price, comparing with the predictive supply price to choose the fittest pricing strategy. In order to conform to the practical market situation, we combine with the industry’s cost structure and revise the market linear demand function to non-linear one.
Furthermore, utilizing the Multi-Generation Diffusion Model of the Norton and Bass to explain the technological products take the place of multi-generation models of spreading. We not only fix the product price and the advertisement budget values but also view both of them as variables to solve the both situations by means of genetic algorithms, comparing the multi-generation product’s total revenue, the best evolutionary generations, and the time to market. By way of controlling the timing of product to market and considering the profit, the findings will not only facilitate a better understanding on corporation’s strategies and the relationship between multi-generation product’s spreading process and its life cycle but also maximize its overall profit.

表目錄 IX
圖目錄 X
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 2
1.3 研究範圍與假設 3
1.4 研究方法與步驟 4
1.5 論文架構 5
第二章 文獻探討 7
2.1 賽局理論 7
2.1.1 市場結構 8
2.1.2 動態賽局介紹 9
2.2 行銷定價策略 11
2.2.1 多世代產品定價 11
2.2.2 產品生命週期 12
2.3 擴散模型 (DIFFUSION MODEL) 14
2.3.1 貝氏擴散模型 (Bass Diffusion Model) 14
2.3.2 採用者分類 16
2.3.3 參數估計 17
2.4 多代擴散模型 24
2.5 參數模式化 28
2.5.1 市場混合變數 28
2.5.2 其他 29
2.6 基因演算法之理論與運算 30
第三章 研究方法 34
3.1 研究模型建立 34
3.1.1 賽局寡占模型 35
3.1.2 建立擴散模型 36
3.2 參數估計(PARAMETER ESTIMATION) 40
3.3 統計分析 42
第四章 數值分析 43
4.1 個案情境設定 43
4.2 實證產品介紹 43
4.3 市場需求函數推估結果 45
4.4 參數估計結果 49
4.5 求解最佳演化代數與產品上市時間 50
第五章 結論與未來研究方向 56
5.1 結論 56
5.2 未來研究方向 57
參考文獻 58

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