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系統識別號 U0026-2108201212142500
論文名稱(中文) 虛擬社群之潛在顧客搜索機制研發-以食品業應用為例
論文名稱(英文) Development of a Mechanism of Potential Customer Searching from Virtual Communities: Food Industry as an application
校院名稱 成功大學
系所名稱(中) 製造資訊與系統研究所碩博士班
系所名稱(英) Institue of Manufacturing Information and Systems
學年度 100
學期 2
出版年 101
研究生(中文) 劉彥辰
研究生(英文) Yan-Chen Liu
學號 p96994119
學位類別 碩士
語文別 中文
論文頁數 75頁
口試委員 指導教授-陳裕民
共同指導教授-陳宗義
口試委員-李昇暾
中文關鍵字 消費價值模式  向量空間模型  潛在顧客  潛在語意分析  倒傳遞類神經網路 
英文關鍵字 Consumption Value Theory  Virtual Community  Vector Space Mode  Latent Semantic Analysis  Back Propagation Neural Network 
學科別分類
中文摘要 過去研究顯示,開發一個顧客所消耗的成本為保留顧客的五倍。若能降低開發顧客之成本,將有助於企業提升利潤。現有之潛在顧客獲取方法多以市場調查或資料探勘為主,前者經常花費許多人力及時間;後者因無法取得競爭對手資料,導致無法了解整體市場趨勢、消費者偏好的變化。因此,如何有效率地獲取潛在顧客為當前企業重要之議題。
本研究以消費價值理論(Consumption Value Theory)為基礎,發展一自動於虛擬社群中尋找潛在顧客之機制,藉由自動化之方法獲取潛在顧客,以期降低企業所投入之人力及資源。由於消費價值理論難以量化為自動化處理之依據,本研究遂進一步提出以食品業為基之產品一般屬性模型(Product Common Attribute model,PCA)與消費價值理論對應。透過問卷調查,檢驗該理論與一般屬性模型之關聯性,進一步將所獲得之各項路徑係數建立消費價值與產品一般屬性對應之權重矩陣。本研究將虛擬社群中之網路文章,以潛在語意分析(Latent Semantic Analysis,LSA)以及倒傳遞類神經網路(Back Propagation Neural Network,BPNN) 輔以上述權重矩陣進行計算,作為識別潛在顧客之方法,篩選出可能為潛在顧客之網路使用者。
英文摘要 The cost for acquiring new customers is more than five times the cost for satisfying and retaining current customers. Thus, reducing costs of acquiring new customers is an important issue for maximizing enterprise profit.
This study aims to develop a potential customer searching mechanism based on consumption value theory. To acquiring the weight of consumption value theory in application domain , This study has proposed a product common attribute model to fit such theory by questionnaire survey. Depending on acquired weight of consumption value theory, we then develop a potential customer identification method to directly locate customers that provide further information to enterprise automatically, and enable to acquire customers without wasting human resources and money.
論文目次 摘要 I
Abstract II
誌謝 III
目錄 IV
表目錄 VI
圖目錄 VIII
第一章 緒論 1
1.1研究背景 1
1.2研究動機 2
1.3研究目的 3
1.4問題分析 3
1.5研究項目 4
1.6研究步驟 5
1.7論文架構 6
第二章 文獻探討 7
2.1 虛擬社群 7
2.2 潛在顧客 8
2.3 消費者行為 11
第三章 潛在顧客搜索模式設計 16
3.1 潛在顧客搜索模式 17
3.2 以食品業為基之產品一般屬性模型 21
3.3 研究假說與實證分析 23
3.3.1 樣本結構分析 24
3.3.2 信度與效度分析 26
3.3.3 結構方程模式評估 29
3.3.4 假說檢定 31
3.3.5 消費價值模式與產品一般屬性模型之關聯 33
第四章 潛在顧客搜索機制發展 34
4.1 虛擬社群環境模型 34
4.2 領域詞庫建立 35
4.3 關鍵字擴展 40
4.4 潛在顧客識別 48
第五章 機制驗證 55
5.1 領域詞彙淬煉門檻值實驗 55
5.2 特殊詞彙淬煉方法驗證 57
5.3 關鍵字擴展方法驗證 59
5.4 潛在語意分析維度約化 60
5.5 產品一般屬性識別訓練與測試 62
5.6 潛在顧客識別訓練與測試 63
第六章 結論與未來方向 65
6.1 總結 65
6.2 研究限制 66
6.2 未來研究方向 66
參考文獻 69
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