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題名:網站評論者行為之研究:以Amazon.com為例
作者:陳華寧
作者(外文):Hua-Ning Chen
校院名稱:臺灣大學
系所名稱:商學研究所
指導教授:黃俊堯
學位類別:博士
出版日期:2011
主題關鍵詞:網路評論網路口碑Pareto/NBD模型顧客群分析網路行銷online customer reviewonline word of mouthPareto/NBD modelcustomer base analysisinternet marketing
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隨著網路與資訊科技的興起,消費者較以往更容易搜尋與分享產品資訊,網路評論相關文獻發現,網路評論對於消費者決策甚至是產品銷售有顯著影響,且研究指出,若電子商務經營者比其他競爭者擁有更多評論者以及網路評論數量,其銷售量可能高於沒有提供評論的廠商(Chevalier 與 Mayzlin 2006),因此網站上評論者發佈評論之多寡對於經營電子商務之業者實為重要。本研究主要目的為透過了解網站評論者人數之消長以及評論次數之變化,進一步探討影響評論者發佈評論的頻率以及持續性之因素。
本研究蒐集Amazon.com網站上的評論者資料進行實證研究,先採用Pareto/NBD模型進行網站評論者群分析,並運用Matlab軟體以最大概似法估計模型參數,藉以推測出網站現有的評論者群人數,並觀察評論者群隨時間演變的消長情況,以及評論者在網路上之評論頻率的變化。再者,為探討影響評論者評論頻率與持續性之因素,本研究引用Fader與Hardie (2007)提出之架構--在Pareto/NBD 模型中加入非時變解釋變數的方法,來檢驗評論者之網路評論行為,這些評論行為包含:「平均在網站上發表的評論字數」、「平均給予評論標的物的評價(rating)」、「消費者所給予評論者的回饋」 (包括評論者發佈評論所獲得的有用性票數比例與消費者的回應數目)以及「匿名性」對於評論者發表行為之影響。
研究結果發現,當評論者發表評論的平均字數越多時,評論者發表評論的頻率越高,但持續在網站上發佈評論的機率卻越低;在評論者平均發表評價(rating)方面,當評論者平均發表的評價越高時,則評論者發表評論的頻率越高,且持續發佈評論的機率也越高;再者,當評論者獲得較多的消費者回饋時,評論者持續發表評論的機率較高,且發佈評論的頻率也較高;最後,相較於匿名評論者,使用真實姓名作評論者,雖然發佈的評論頻率較低但持續做評論之機率較高。
As the emergence of Internet and information technology, it is much easier for consumers to search and share their product evaluations online. In the online review literature, consumer reviews have significant impact on consumer purchase decisions and product sales. Chevalier and Mayzlin (2006) suggest that, the sales of the online sellers who invite users to post personal product evaluations on their websites may higher than them would be without the provision of customer reviews. The objective of this research is to describe the dynamics of number of reviewers and their reviews on the website, and identify the factors which could explain the differences in frequency and continuity of their online review behaviors.
We attempt to examine the topic from an online seller’s perspective by utilizing Pareto/NBD model, which has been successfully applied in customer base analysis over past two decades. Furthermore, the current study uses the framework — incorporating time-invariant covariates into the Pareto/NBD model (Fader and Hardie 2007) — to capture the factors that impact on online review behaviors.
We collected our data using the online reviewers and their reviews available through Amazon.com. Summarizing results from an empirical study on 4,240 reviewers, we conclude our main findings as follows: the average rating of reviews and the feedback from other consumers have positively effect on both reviewing frequency and continuity. Moreover, the average length of reviews positively affects reviewing frequency but negatively affects continuity. Finally, the results suggest that, reviewers who posting reviews with real name have higher frequency but lower continuity than anonymous reviewers.
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