網路口碑 (Electronic Word-of-Mouth , eWOM) 的影響力一直以來都受到學術界及行銷界的密切關注。隨著電子商務的蓬勃發展，消費者能夠輕易地取得其他消費者的評論資料，作為購物決策的參考。本研究採用推敲可能性模式作為研究架構，以認知科學的角度，分析評論中涉及理性思考的中央路徑因素及感性思考的周邊路徑因素對銷售績效之影響，以及這些因素的影響力是否會因為不同商品類型而有差異。中央路徑的因素包含評論長度、評論可讀性及理性屬性字典比例；周邊路徑的因素包含評論數量、平均評等、評論者評等、感性屬性字典比例以及情緒相關變數。
本研究蒐集Amazon網站上「搜尋品－筆記型電腦」及「經驗品－唇膏」的排名及評論，利用文字探勘的技術找出評論內容的重要特性，設計一套顧客購買因素方法，並透過多變量分析驗證這些因素對銷售排名的影響。研究結果發現，幾乎所有評論要素都會對銷售排名造成影響，但是不同商品類型在某些方面卻有些差異。例如，兩種商品中出現理性的評論皆會對銷售績效產生正向之影響，但在經驗品中偏向感性的評論則會對銷售績效不利；評論壽命對銷售績效的影響則是搜尋品遠大於經驗品。在二階模型的結果中，不同商品類型的中央路徑以及周邊路徑產生了良好的調節作用，其中周邊路徑的評論數量及平均評等的影響效果最為顯著。因此顯示出本研究應用推敲可能性模式檢驗不同商品類型的網路評論對於銷售績效之影響效果上，具備良好的解釋能力。

關鍵字：網路口碑、銷售績效、推敲可能性模式、文字探勘、情緒分析

The effects of Electronic Word-of-Mouth have been deeply concerned by academics and marketers. With the rapid development of electronic commerce, consumers can easily acquire review data from other reviewers as reference. The purpose of this study is to analyze the influence of central route factors related to rational thinking and peripheral route factors related to emotional thinking based on elaboration likelihood model from cognitive science perspective, which vary for different types of products. In the research, the factors of central route include review length, readability and ratio of rational lexicon. On the other hand, peripheral route factors include volume, ratings, reviewers’ ratings, ratio of emotional lexicon, and variables related to emotions.
We collected product reviews of laptops and lipsticks from Amazon.com and found the important features with text mining techniques. We designed an approach of customer factors and applied the multivariate analysis to verify the impact on the sales performance. The results suggest that almost all of the variables affect sales performance, but there are some differences based on product types. For example, two types of products which contain rational reviews will affect the sales performance, but emotional reviews of experience product have a negative impact on sales performance. However, reviews’ longevity of search product has a greater impact on sales performance than experience product. In the results of second-order model, the overall central route and peripheral route of different product types have good moderating effects. Besides, the effects of volume and ratings of peripheral route are more significant. It demonstrates that ELM provides a good explanatory power of the online reviews’ effects on sales performance, which vary in different types of products.
Keywords: eWOM, Sales Performance, Elaboration Likelihood Model, Text Mining, Sentiment Analysis 

論文審定書 i
公開授權書 ii
誌謝 iii
摘要 iv
Abstract v
目錄 vi
圖次 viii
表次 ix
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究流程 3
第二章 文獻探討 5
第一節 網路口碑 5
第二節 推敲可能性模式對於商品評論的影響 15
第三節 文字探勘與情緒分析 18
第三章 研究架構與假說 24
第一節 研究架構 24
第二節 研究假說 25
第四章 研究方法與資料 31
第一節 次級資料分析 31
第二節 資料來源與變數說明 31
第三節 資料處理 33
第四節 分析方法 38
第五節 分析模型 56
第五章 研究結果 59
第一節 研究模型驗證 59
第二節 結構模型方程式分析 67
第三節 顧客購買因素分析 73
第六章 結論與建議 77
第一節 研究發現 77
第二節 研究貢獻 81
第三節 研究限制與未來建議 82
參考文獻 83
附錄一 專家問卷 91
附錄二 問卷統計結果 99

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