Self Selection and Information Role of Online Product Reviews

Transcription

1 Self Selecton and Informaton Role of Onlne Product Revews Xnxn L Lorn M. Htt The Wharton School, Unversty of Pennsylvana Introducton Word of mouth has long been recognzed as a major drver of product sales. It can rase consumer awareness, and may be one of the few relable sources of nformaton about the qualty of experence goods. Wth the development of the Internet, word of mouth has moved beyond small groups and communtes, to beng freely avalable through largescale consumer networks (Avery, Resnck and Zeckhauser 1999). These networks have renforced the mpact of word of mouth to an unprecedented scale, and correspondngly dramatcally changed the way consumers shop, enhancng or even supplantng tradtonal sources of consumer nformaton such as advertsng. In a survey of 5,500 web consumers conducted by BzRate, 44% of respondents sad they have consulted opnon stes before makng a purchase and 59% consdered consumer-generated revews more valuable than expert revews (Pller 1999). A recent survey of DoubleClck also found that word of mouth plays a very mportant role n consumer s purchasng process for many types of products and for some goods, such as electroncs and home products, product revew webstes outrank all other meda n nfluencng customer decsons (DoubleClck 2004). Whle a large body of work has been focusng on analyzng the effcency and suffcency of ebay-lke onlne reputaton systems and ther desgn ssues (see a comprehensve revew n Dellarocas 2003a), there has been very lttle systematc research on product revew webstes. Chevaler and Mayzln (2003) and Godes and Mayzln (2003) showed n dfferent settngs that onlne consumer revews can ndeed affect product sales, although they dd not examne whether consumer revews can communcate qualty nformaton effcently. The effcacy of consumer-generated product revews may be lmted for at least two reasons. Frst, frms may manpulate onlne ratng servces by payng ndvduals to provde hgh ratngs, although theoretcal results by Dellarocas (2003b) demonstrated that ths type of behavor may not reduce ther nformatveness f producers and consumers behave optmally. Second, even n the settngs where product revews are all truthfully reported, there are stll possbltes that the reported ratngs are nconsstent wth the preferences of the general populaton. Unlke ratngs of seller qualty where hgher ratngs are unambguously better for all consumers, ratngs of products may reflect both consumer taste as well as qualty. Ths may be partcularly problematc f the perceptons of product qualty of the buyers who post revews onlne dffer from those of most consumers snce the revews wll yeld systematc bases even when they are truthful reports of perceved qualty. Ths self-selecton problem s partcularly serous n early product ntroducton perods when margnal effect of a sngle

2 revew s hgh. In the meanwhle, the fact that potental buyers may not be aware of these bases and thus do not adjust the relevance of dfferent revews accordngly bears a drect mpact on the effcency of onlne revew systems. Ths can partally explan why n realty we often observe product ratngs declnng over tme, whle a flat or even an ncreasng trend would be expected f qualty nformaton s ndeed communcated onlne effcently f consumers have lttle dfference n tastes and preferences or f benefcares of onlne revews can dstngush the types of revewers and locate the products that ft them best. In ths study, we wll examne the latter ssue utlzng ratngs and sales data collected from Amazon. We address two major research questons. Frst, do product ratngs change systematcally over tme? Our hypothess s that early adopters may have sgnfcantly dfferent preferences than later adopters whch wll create trends n ratngs as products dffuse. Second, we consder whether consumers account for these bases n ratngs when makng product purchase decsons. We use these emprcal observatons as the foundaton for a theoretcal model that examnes the relatonshp between consumer behavor and outcomes n markets where onlne revew systems play a sgnfcant role. Understandng these ssues s mportant to frms customer relatonshp management and product postonng strateges. Realzng the dsproportonate mpact of early product adopters on market outcomes, frms can respond by alterng ther marketng strateges, such as prcng and advertsng, or product desgn to encourage consumers lkely to yeld postve reports to self-select nto the market early and ncrease the average ratng when ntroducng a new product. Ths s smlar to strateges where frms promote ther products to ndvduals who have credblty n certan onlne forums (Dellarocas, 2003b), although ths study would suggest that knowledge of dosyncratc tastes of these revewers s as mportant as broad reach and nfluence. Data Collecton A random sample of 2651 hardback books was collected from Books n Prnt coverng books publshed from that also have revews on Amazon. Book characterstc nformaton was collected from Amazon ncludng ttle, author, publsher, publcaton date, category, publcaton date for correspondng paperback edtons, and all consumer revews posted on Amazon snce a book was publshed. Every Frday from March to July n 2004 we collected sales-related data for each book from Amazon ncludng sales rank, prce, the number of consumers revews, the average revew, and shppng avalablty. To control for outsde competton and promoton, each Frday we also collect prces lsted on a prce comparson engne ( for each book n our sample. Trend n consumer revews We start by usng Box-Cox transformaton to explore f there s any trend n book revews posted on Amazon over tme. The Box-Cox model s establshed as follows:

3 AvgRatng t λ T 1 α + β + u + et = λ α + β Log[ T] + u + e t when λ 0 when λ = 0, where AvgRatng t represents the average revew for book at tme t, T denotes the tme dfference (measured as the number of months) between the date the average revew was posted and the date the book was released, and u stands for the dosyncratc characterstcs of each ndvdual book that keep constant over tme. The estmated trend s pctured n Fgure 1. AvgRatng T Fgure 1 The model shows a sgnfcant declnng trend n average ratngs over tme. We also tred other models, ncludng negatve exponental model and polynomal regresson models. Usng J-test, we can not reject the hypothess that these models are equally good, but the negatve exponental model returns the mnmum sum of squared resduals. Therefore we ll use the estmates n the negatve exponental model for our subsequent analyss the ftted model s AvgRatng = exp[ T ] + ˆ + εˆ. t u t Impact of consumer revews on book sales It has been shown n Chevaler and Mayzln (2003) that onlne book ratngs do affect book sales. Based on the precedng analyss, book ratngs have an obvous trend over tme average ratngs declne over tme, showng a postve bas n revews wrtten by early buyers. We wll further nvestgate when consumers compare alternatve books, do they notce the tmng of the book ratngs and adjust the mpact of ratngs accordngly. As argued n Chevaler and Mayzln (2003) and some other studes, sales rank s a loglnear functon of book sales wth a negatve slope. We use Log[SalesRank] as dependent varable and the cross-sectonal regresson model can be establshed as follows, Log[ SalesRank ] = β 4 Promoton C 0 + β1avgratng 1Log[ P ] 2Log[ NumofRevew ] 3 Log[ P ] T CategoryDummes ShppngDummes To examne the mpact of consumer ratngs on book sales, we control other demand- + ε.

4 related factors, ncludng book prce offered by Amazon (P ), the number of revews posted on Amazon (NumofRevew ), outsde compettve prce (P C ), book promoton (Promoton ), book category (CategoryDummes ) and shppng avalablty (ShppngDummes ) 1. Consderng the possblty that sales may naturally declne over tme, we also control for how long an ndvdual book has been n market (T). Usng estmates from the negatve exponental model, average ratng can be consdered as the sum of a populaton average, εˆ + uˆ t, denoted as R whch represents underlyng qualty of book, plus a tme varyng component, 0.45 exp[ T], denoted as R T whch stands for revew bas at tme T. If we replace AvgRatng wth the value estmated from the negatve exponental model, the regresson model s changed to Log[ SalesRank ] = β 4 Promoton C 0 + β11 R + β12rt 1Log[ P ] 2 Log[ NumofRevew ] 3 Log[ P ] T CategoryDummes ShppngDummes If the consumers notce the bas n early perods and fully account for t, the tme varant component R T should have no mpact on consumer purchase decson and therefore ß 12 should be zero. We use the book sales data collected on March 19 th to ft the model (results are smlar f other tme perods are used). All estmates are sgnfcant and have the rght sgn. Wth other demand-related factors controlled for, the tme varant component R T has a sgnfcant mpact on book sales when consumers compare dfferent books at the same tme perod, whch leads to the concluson that consumers dd not fully account for the postve bas of early raters. Usng a tme seres model to study how the mpact of consumer revews on an ndvdual book evolves over tme, the same concluson s supported. Theory Model and Implcatons The emprcal nvestgaton demonstrates the potental bas n consumer revews n early product ntroducton perods and emprcally verfes that buyers generally do not fully account for ths bas when they examne onlne revews. We now utlze these observatons to motvate a theoretcal model that examnes how these based revews can mpact market outcomes. Consder a market for an experence good where n each perod a group of consumers comes nto the market and makes a decson on whether to purchase (at most) one unt of the product. An ndvdual consumer s preferences over the product can be characterzed + ε. 1 P C s measured as the mnmum prce lsted on Prcescan.com for book ; Promoton s defned as (Lst Prce Second Maxmum prce lsted on Prcescan.com) / Lst Prce for book.

5 by two components (x, q ). The element x s known by each consumer before purchasng and represents the consumer s preference over product characterstcs that can be nspected before purchase. The element q measures the qualty of the product for consumer each consumer may perceve qualty of the same product dfferently. Consumers only learn q after buyng the product, and ther demand s determned by x and ther expected qualty q e whch can be affected by onlne revew systems. In each perod, consumers who bought the product post ther (truthful) product revews onlne that are avalable to all future buyers. Because of consumers dosyncratc tastes over qualty, the reported revew may not be an unbased ndcator of product qualty. If q s unrelated to consumer characterstcs then ths smply ntroduces nose n the reported ratng snce ex-post some consumers may be more or less satsfed than they expected. However, f x and q are correlated, such as when early buyers are product afconados who are lkely to value the product hghly, revews can become systematcally based, whch n turn affects the demand for the product and the types of consumers that purchase the product n future perods. Our fndngs suggest the sgnfcance of product desgn and early perod product promoton carefully targetng the potental buyers who may self-select nto the market early and also favor your products or ncorporatng the requrements of early adopters nto producton s strategcally mportant. McFadden and Tran (1996) argued that learnng from other consumers may hurt nche products. Ths study shows that even for a potentally popular product, falure to caterng to the preferences of early buyers thus generatng unfavorable word-of-mouth n early perods may also hurt. References Avery, C., Resnck, P. and Zeckhauser, R. The Market for Evaluatons, The Amercan Economc Revew (89:3), 1999, pp Chevaler, J. and Mayzln, D. The Effect of Word of Mouth on Sales: Onlne Book Revews, Workng Paper, Yale School of Management, Dellarocas, C. The Dgtzaton of Word-of-Mouth: Promse and Challenges of Onlne Reputaton Mechansms, Management Scence (49:10), 2003a, pp Dellarocas, C. The Impact of Onlne Opnon forums on Competton and Marketng Strateges, Workng Paper, MIT-Sloan, 2003b. DoubleClck DoubleClck s Touchponts II: The Changng Purchase Process, March, Godes, D. and Mayzln, D. Usng Onlne Conversatons to Study Word of Mouth Communcaton, Workng Paper, Yale School of Management, McFadden, D. and Tran, K. E. Consumers Evaluaton of New Products: Leanng from Self and Others, Journal of Poltcal Economy (104:4), 1996, pp Pller, C. Everyone Is A Crtc n Cyberspace, Los Angeles Tmes, December 3, 1999