隨著科技不斷地創新，新產品從構想、開發到成功上市的時間愈來愈短，而創新的高風險與高失敗率，使得企業在新產品的開發與管理上面臨相當大的挑戰。由於創新的擴散過程受到許多因素的影響，加上擴散係數又會影響預測曲線的形狀，所以相關影響因素與係數估計是決定整個擴散模式預測準確度的主要關鍵。因此本研究之目的是結合產品價格與屬性擴散係數，建立一個運用類神經網路估計新產品擴散模式係數的方法，期望能提供一個適用於企業的新產品擴散模式。本研究引用液晶顯示器作為實證，以產品價格與屬性擴散係數為輸入變數，透過倒傳遞網路的學習能力估計出擴散係數，並與另外二種係數估計方法：以產品屬性為基礎之係數估計方法與非線性最小平方法進行比較分析，並將此三種方法所估計之係數代入 Bass 擴散模式中進行產品銷售量的預測。最後經由實證分析的結果，本研究歸納出以下兩點結論：（1）在預測能力方面，本研究所建構之模式明顯優於以產品屬性為基礎之係數估計方法，並且略優於非線性最小平方法。（2）本研究所建構之模式可以適用於企業的新產品擴散係數估計與銷售量預測。

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中文部分
葉怡成，2003年，類神經網路模式應用與實作（八版），儒林圖書有限公司
莊孟絃，2003年，估計新產品擴散模式係數之研究，國立成功大學工業管理科學系碩士班碩
士論文

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