外文翻譯---促使消費(fèi)者網(wǎng)上評價(jià)產(chǎn)品的原因分析

1、<p>　　附錄三：外文文獻(xiàn)譯文</p><p>　　標(biāo)題：促使消費(fèi)者網(wǎng)上評價(jià)產(chǎn)品的原因分析</p><p>　　——基于在線電影評論由來的研究</p><p>　　資料來源：消費(fèi)者報(bào)告，2006 </p><p>　　作者：Chrysanthos Dellarocas and Ritu Narayan </p>&l

2、t;p><b>　　簡介</b></p><p>　　近年來，在線產(chǎn)品評價(jià)的論壇對于消費(fèi)者在產(chǎn)品選擇上所產(chǎn)生的影響已與日俱增。因此，有些公司利用這種現(xiàn)象，積極努力通過各渠道來使消費(fèi)者在網(wǎng)上關(guān)注他們的產(chǎn)品（Godes等，2005）。然而，有趣的是，即使控制產(chǎn)品銷售量的變化，仍然出現(xiàn)消費(fèi)者對于在網(wǎng)上參與不同產(chǎn)品的討論的傾向的大幅度變動。因此，關(guān)于消費(fèi)者參與在線評論激發(fā)消費(fèi)成為了一個新興的、

3、具有理論和實(shí)踐意義的研究。</p><p>　　最近，關(guān)于網(wǎng)上評論的研究主要集中于評估用戶評論內(nèi)容和產(chǎn)品銷售（2006年Chevalier和Mayzlin，2004；Senecal和Nantel，2006）之間的關(guān)系。到目前為止，很少有人研究人們參與在線產(chǎn)品評論的影響因素的研究，我們唯一所知道的（Hennig-Thurau等，2004）相關(guān)研究是采用了傳統(tǒng)的調(diào)查方法，同時要求受訪者要明確地報(bào)告他們參與在線評價(jià)的動

4、機(jī)。</p><p>　　通過尋找產(chǎn)品在特定前提下的在線評論，我們的工作為這方面的研究開辟了新的方向。在Hennig-Thurau等的關(guān)于是什么促使消費(fèi)者在網(wǎng)上評論的研究后，我們的研究著重于了解什么特定產(chǎn)品屬性可以解釋消費(fèi)者平均消費(fèi)傾向的變化，使人們發(fā)布有關(guān)于給定類別中個別商品的在線評價(jià)。此外，在關(guān)于這一主題的最早的文獻(xiàn)調(diào)查的基礎(chǔ)上，我們的工作也參考了從互聯(lián)網(wǎng)上收集的輔助數(shù)據(jù)，并作出了以實(shí)際行為為基礎(chǔ)的觀察推論。

5、最后，我們的研究特別注重網(wǎng)上媒介的一些特別的屬性，如之前發(fā)布的意見的知名度和持久性等，對后來的訪問者參與一個產(chǎn)品在線評價(jià)意愿的影響。</p><p><b>　　理論框架</b></p><p>　　我們的研究致力于以前關(guān)于口碑（WOM）交流的動機(jī)和公共物品行為經(jīng)濟(jì)學(xué)理論的貢獻(xiàn)的研究。</p><p><b>　　（1）口碑交流理論&

6、lt;/b></p><p>　　以前關(guān)于口碑交流的動機(jī)和來源的文獻(xiàn)包括，以調(diào)查為基礎(chǔ)的關(guān)于離線口碑的來源的研究（迪希特，1966；孫達(dá)拉姆等，1998），以及最近少數(shù)關(guān)于司機(jī)網(wǎng)上審查論壇的貢獻(xiàn)的研究（Hennig-Thurau等，2004）。</p><p>　　Ditche關(guān)于口碑交流的動機(jī)的開創(chuàng)性文章提出了存在的四個主要的動機(jī)類別：產(chǎn)品參與，自我參與，其他參與，和消息參與（Di

7、tcher，1966）。雖然后來的研究（恩格爾等，1993；孫達(dá)拉姆等，1998）定義了口碑細(xì)化的動機(jī)，但其中大部分與原先Ditcher建議的類別相對應(yīng)。</p><p>　?。?）公共物品的理論貢獻(xiàn)</p><p>　　在線產(chǎn)品評論代表的是經(jīng)濟(jì)學(xué)家所說的公共利益實(shí)例：人們花費(fèi)時間和努力在他們的個人捐助者，一旦為社會所知曉，其利益就會延伸到整個社會。經(jīng)濟(jì)理論所預(yù)言的，當(dāng)很多人共享公共物品的

8、使用，有一個過度使用（“公地悲劇”）的激勵，而當(dāng)人們共享的義務(wù)是為他們提供時，他們往往供應(yīng)不足。行為經(jīng)濟(jì)學(xué)的一個相當(dāng)長的論段試圖解釋司機(jī)對社會的公益貢獻(xiàn)。（貝克爾，1974；伯恩海姆，1986；Andreoni，1989）。這些文獻(xiàn)提供了幾點(diǎn)啟示，也同樣適用于在線產(chǎn)品評論。</p><p>　　行為經(jīng)濟(jì)學(xué)文獻(xiàn)的一個重要貢獻(xiàn)是區(qū)分完全和非完全利他動機(jī)的一種方法。這種方法是基于對慈善貨物的貢獻(xiàn)“擠出效應(yīng)”的存在或缺乏

9、（艾布拉姆斯和Schmitz，1978；Andreoni，1989）。擠出效應(yīng)的描述情況下，如果第三方增加了自己的貢獻(xiàn)從個人的利他主義的捐款往往會減少，它直接從純粹的利他主義的定義如下：如果第三方（比如，政府）的步驟，使大的一個慈善組織捐款，來自個人的捐款將使該組織的原因與眾不同。</p><p>　　在我們設(shè)置的背景下，其他影迷已經(jīng)發(fā)布了大量的網(wǎng)上評論后，擠出效應(yīng)會轉(zhuǎn)化為一個下降的傾向?qū)τ陔娪暗木W(wǎng)上評論。測試存

10、在這樣的效果，使我們能夠區(qū)分的行為模式，否則將被歸屬到多個動機(jī)類別的可能動機(jī)。</p><p><b>　　假設(shè)</b></p><p>　　借鑒口碑的動機(jī)，我們根據(jù)討論的理論框架提出假設(shè)。列出的動機(jī)類別包括括號內(nèi)的每個假說。如果我們提交的是接受，我們將在研討會上將每一個假說都提出詳細(xì)討論。</p><p>　　H1：發(fā)表網(wǎng)上評論傾向較高的，是

11、消費(fèi)者認(rèn)為特別好或特別壞的電影。（產(chǎn)品的參與和關(guān)心他人）</p><p>　　H2：在線審查一部電影的傾向與電影的營銷量是正相關(guān)的。（留言介入）</p><p>　　H3：在線審查一部電影的傾向是否積極與公眾認(rèn)為該影片質(zhì)量的分歧量有關(guān)。（自我參與和關(guān)心他人）</p><p>　　H4：在線審查一部電影的傾向與那部電影的感知的可用性是負(fù)相關(guān)的。（自我參與和關(guān)心他人）&

12、lt;/p><p>　　H5A：以前發(fā)布有關(guān)于同一部電影的評論與再次發(fā)布的傾向是負(fù)相關(guān)的。（關(guān)心他人）</p><p>　　H5B：以前發(fā)布有關(guān)于同一部電影的評論數(shù)量與再次參與有關(guān)電影網(wǎng)上評論的傾向呈正相關(guān)。（自我參與和社會福利）</p><p>　　需要注意的是H1 - H4與純粹的利他主義和口碑的動機(jī)至少有一個其他理論相一致。因此，這些假說的實(shí)證支持，不允許我們繪制

13、清晰的對在線產(chǎn)品審查捐款背后動機(jī)的結(jié)論。假設(shè)5a/5b可以幫助解決這個潛在的歧義。</p><p><b>　　數(shù)據(jù)集</b></p><p>　　我們的數(shù)據(jù)集包括消費(fèi)類和專業(yè)評論家張貼在雅虎的評論。電影關(guān)于美國在2002年期間發(fā)布的104部電影，每一部都有詳細(xì)的生產(chǎn)數(shù)據(jù)和相同的電影廳每周框數(shù)據(jù)。它包括104部電影，1392評論家評論（平均13％的電影評論）從4629

14、4個人用戶中選出的（平均每部電影和1.4％，用戶的評論614的評論）用戶評論。即使我們調(diào)整票房量的差異，數(shù)據(jù)集已經(jīng)具有了尊重已經(jīng)為不同電影作出貢獻(xiàn)的消費(fèi)者的評論的數(shù)量的實(shí)質(zhì)性方差。這意味著在購買人口的平均消費(fèi)傾向的變異評論網(wǎng)上不同的電影。</p><p><b>　　結(jié)論</b></p><p>　　我們發(fā)現(xiàn)，采購人口的平均消費(fèi)傾向?qū)τ谠u論在線電影有：（1）一個U形的

15、關(guān)系??與平均價(jià)的那部電影的評論；（2）與該影片的營銷預(yù)算的正相關(guān)關(guān)系；（3）與專業(yè)評論之間的分歧水平的正相關(guān)關(guān)系那部電影；（4）與屏幕電影展的負(fù)相關(guān)關(guān)系；（5）與以前發(fā)布的評語數(shù)量相同的正相關(guān)關(guān)系。</p><p>　　因此，我們找到了假設(shè)1，2，3，4和5b的支持。我們的研究結(jié)果拒絕利他主義/關(guān)注他人發(fā)布在線產(chǎn)品評論的主要動機(jī)的假設(shè)。一個我們的實(shí)證結(jié)果分的集體閱讀，相反的，不是自我作為網(wǎng)上審查的貢獻(xiàn)背后的主導(dǎo)

16、力量的表達(dá)/自我確認(rèn)的動機(jī)：消費(fèi)者更容易評價(jià)非常好和非常糟糕的電影（因?yàn)橄M(fèi)者覺得這些電影觸發(fā)強(qiáng)烈的感情表達(dá)的沖動），有爭議的電影（因?yàn)槟敲此麄兊膶彶閷⒂枰愿嗥渌M(fèi)者尋求減少他們對這些電影的不確定性），鮮為人知的電影（的關(guān)注，因?yàn)檫@可以讓消費(fèi)者展示其折衷主義和復(fù)雜性），和電影周圍存在著他們認(rèn)為有的很多網(wǎng)上的謠言（因?yàn)檫@意味著其他人更容易閱讀評價(jià)，或僅僅是因?yàn)樗臉啡ぷ?，別人都這樣做）。有趣的是，我們發(fā)現(xiàn)電影觀眾似乎更渴望評價(jià)那些廣泛

17、發(fā)布而且票房成績不好的電影。即使我們控制所吸引人群的內(nèi)在溝通習(xí)慣的差異，這一結(jié)果依然很顯著。其結(jié)果是產(chǎn)生一個關(guān)于產(chǎn)品的“在線流言”的營銷活動的有興趣的影響，另一個有趣發(fā)現(xiàn)是，以前發(fā)布的大量評論使觀眾對同一部電影發(fā)表評論的傾向更大，即使過去有一定的量，增加額外的評語是不可能添加已經(jīng)說過的一點(diǎn)。這是設(shè)計(jì)在線產(chǎn)品討論社區(qū)的潛在影響的結(jié)果，因?yàn)樗砻?，從社會的角度來看，?lt;/p><p>　　附錄四：外文文獻(xiàn)原文<

18、/p><p>　　Title：What motivates consumers to review a product online？</p><p>　　——A study of the product-specific antecedents of online movie review</p><p>　　Material Source：Consumer Repo

19、rts, 2006</p><p>　　Author：Chrysanthos Dellarocas and Ritu Narayan </p><p>　　1. Introduction</p><p>　　In recent years online product review forums have been exerting an increasingly

20、powerful influence on consumer choice. Not surprisingly, several firms are becoming interested in leveraging this phenomenon, proactively trying to induce consumers to “spread the word” about their products online (Godes

21、 et al. 2005). Interestingly, however, even after one controls for the variance in sales volumes, there appears to be substantial variance in consumers’ propensity to discuss different products online</p><p>

22、;　　Most recent research on online reviews has focused on assessing the relationship between such user-generated content and product sales (Chevalier and Mayzlin 2006; Senecal and Nantel 2004). Little attention has, so fa

23、r, been devoted to the antecedents of online product reviews. The only relevant study that we are aware of (Hennig-Thurau et al. 2004) uses a traditional survey methodology in which respondents were explicitly asked to r

24、eport the motives behind their online communication habits. </p><p>　　Our work adds to this emerging body of knowledge by looking at the product-specific antecedents of online product reviews. While Hennig-

25、Thurau et al. look at what motivates consumers to post online reviews in general, our study focuses on understanding what product-specific attributes explain the variance in a purchasing population’s average propensity t

26、o post online reviews about individual products of a given category (motion pictures). Furthermore, while most prior literature on this topic is</p><p>　　2. Theoretical Framework </p><p>　　Our s

27、tudy draws upon prior research on the motives of word-of-mouth (WOM) communication and upon behavioral economics theories of public goods contribution.</p><p>　　(1)Theories of word-of-mouth (WOM) communicati

28、on </p><p>　　Prior literature on the motivations and antecedents of WOM communication consists of, predominantly survey-based, research on the antecedents of offline WOM (Dichter 1966, Sundaram et al. 1998

29、), as well as a small number of recent studies on drivers of contribution to online review forums (Hennig-Thurau et al. 2004).</p><p>　　Ditcher’s (1966) seminal article on WOM communication motives suggests

30、the presence of four main motivational categories: product involvement, self involvement, other involvement, and message involvement. While later studies (Engel et al. 1993, Sundaram et al. 1998) identify finer-grained m

31、otives of WOM, most of these correspond to categories originally suggested by Dichter. We present a summary below. </p><p>　　(2)Theories of public goods contribution </p><p>　　Online product re

32、views represent an instance of what economists call a public good: they cost time and effort to their individual contributors but, once available, their benefit extends to the entire society. Economic theory predicts tha

33、t when many people share the use of public goods, there is an incentive to overuse (“tragedy of the commons”), whereas when people share the obligation to provide them, they tend to undersupply. A sizeable literature in

34、behavioral economics attempts to explain th</p><p>　　An important contribution of the behavioral economics literature is a method for distinguishing between pure and impure altruistic motives. This method is

35、 based on the presence or absence of a “crowding-out effect” in the contribution of charitable goods (Abrams and Schmitz 1978; Andreoni 1989). The crowding-out effect describes situations where altruistic contributions f

36、rom private individuals tend to diminish if a third-party increases its contributions; it follows directly from the definition</p><p>　　In the context of our setting, the crowding-out effect would translate

37、to a decreased propensity to post online reviews for movies for which other moviegoers have already posted large numbers of online reviews. Testing for the presence of such an effect allows us to distinguish between the

38、likely motives of patterns of behavior that would otherwise be attributable to multiple motivational categories.</p><p>　　3. Hypotheses </p><p>　　We develop our hypotheses by drawing upon the th

39、eoretical frameworks on the motives of WOM we discuss above. We list the motivational categories that are consistent with each hypothesis in brackets. If our submission is accepted we will provide a detailed discussion o

40、f each hypothesis at the workshop. </p><p>　　H1: The propensity to post online reviews is higher for movies that are perceived by consumers to be exceptionally good or exceptionally bad. (Product involvemen

41、t and concern for others) </p><p>　　H2: The propensity to review a movie online is positively related to that movie’s marketing effort. (Message involvement) </p><p>　　H3: The propensity to revi

42、ew a movie online is positively related to the amount of public disagreement about that movie’s quality. (Self involvement and concern for others) </p><p>　　H4: The propensity to review a movie online is neg

43、atively related to that movie’s perceived availability. (Self involvement and concern for others) </p><p>　　H5a: The propensity to post online reviews about a movie is negatively related to the number of pre

44、viously posted reviews about the same movie. (Concern for others) </p><p>　　H5b: The propensity to post online reviews about a movie is positively related to the number of previously posted reviews about the

45、 same movie. (Self involvement and social benefits) </p><p>　　Note that H1-H4 are consistent with both pure altruism and at least one other theory of WOM motives. Therefore, empirical support for these hypot

46、heses does not allow us to draw sharp conclusions regarding the motivations behind online product review contributions. Hypotheses 5a/5b can help resolve this potential ambiguity.</p><p>　　4. Dataset </p&

47、gt;<p>　　Our data set consists of consumer and professional critic reviews posted on Yahoo! Movies for 104 movies that were released in the U.S. during 2002, together with detailed production and weekly box office

48、 data for the same movies. It consists of 104 movies, 1,392 critic reviews (an average of 13 reviews per movie), and 63,889 user reviews from 46,294 individual users (an average of 614 reviews per movie and 1.4 reviews p

49、er user). Even after we adjust for differences in box office volumes, the da</p><p>　　5. Conclusions </p><p>　　We find that a purchasing population’s average propensity to review a movie online

50、has: (1) a U-shaped relationship with the average valence of that movie’s reviews; (2) a positive relationship with that movie’s marketing budget; (3) a positive relationship with the level of disagreement among professi

51、onal reviews for that movie; (4) a negative relationship with the number of screens where the movie is exhibited; (5) a positive relationship with the volume of previously posted reviews for the sa</p><p>　　

52、We thus find support for Hypothesis 1, 2, 3, 4 and 5b. Our findings reject the hypothesis of altruism/concern for others as the primary motivation for posting online product reviews. A collective reading of our empirical

53、 findings points, instead, to self expression/self confirmation motives as being the dominant force behind online review contribution: consumers are more likely to review very good and very bad movies (because these movi