| Over the past ten years, as the growing depth of Internet technologydevelopment and application, the online word-of-mouth with Internet ascommunication platform has begun to show its tremendous influence andsignificance. User-generated online product reviews, as one form of onlineword-of-mouth, is bringing a profound change in consumer behavior patterns, theprofit margin and market strategy of the enterprise. Related theoretical study onhow this emerging media affect consumers' perception and purchasing behavior isnot sufficient. Clearing this question can help consumers improve decision makingefficiency and effectiveness, help enterprise manage online reviews effectively topromoteprofits, andmake a good use of the advantage of online reviews.Taking behavior orientation as the research paradigm, from two views ofconsumers'perceptions and buying behaviors, applying both qualitative andquantitative analysis, this paper empirically studys how online reviews impact theconsumers'perception on reviews helpfulness and consumers'purchase behaviors.The four questions are studied. Two parts refer to reviews helpfulness: (1)Combining text mining technologywith regression analysis, we explored the impactfactors for consumers'perception on reviews helpfulness (including the textcharacteristic and published time of reviews, etc.), and further studied the methodof automatically identify review helpfulness. (2) We qualitiviely discussed thecause and impact factors of some online reviews having no helpfulness votes, andquantitatively analyzed the differences in these impact factors between the reviewswith no helpfulness votes and ones with helpfulness votes based on binaryclassification Logistic regression, the results of which are studied to further revealwhy no votes. Contents of the other two parts include: (1) Taking the individualconsumer as the research unit, we studied the moderating effects of product type,consumer expertise on the impact of the online reviews valence, according toattribute theory, prospect theory, perceived risk theory and informationavailability/diagnosticity theory.Applying the experiment design andANCOVA, wetested the moderating effects related hypothese. (2) Takingthe consumer populationas the research unit, we explored the effect of online reviews numbers and valence on product sales (used to measure the buying behaviors of the overall consumergroup) and the variation ofthe impacts with time using panel data. We also revealedthe relative effect of online reviewscompared with expertise reviews.This paper attempts to achieve theoretical and practical innovation in thefollowing four aspects.First, based on the panel data model, we empirically tested the absolute andrelative (compared with expertise reviews) effects of online reviews numbers andvalences on the overall consumer purchase behaviors. We also explored andvalidated the dynamic variation nature of the impacts with time. Our study modelcan reveal the realistic relation between online reviews and consumer populationbehaviors, offering an expalanation for present disconsistent research conclusions.These researches can also richen the relative theories and researches on the impactof online reviews and overall consumer behaviorsSecond, we first explored how product type, consumer expertise moderate theimpact of online reviews valence on individual consumer purchase behaviors. Wealso analyzed the detailed forms of moderating effects and found the asymmetriccharacteristics of moderating role of product type. Our study offers detailedsuggestions for enterprise to effectively manage online reviews under limitedresources.Third, extending researches for search goods to experience goods, weestablished one model for the impact factors of reviews perceived helpfulness. Thismodel significantly improves the forcast effect for the helpfulness of online reviews.This study can help consumers identify high quality products quikly which furtherenhance product sales.Besides, our findings can offer suggestions for enterprise onhow to post high-impact reviews and improve online word-of-mouthmarketing.Fourth, we first fill the research gap in quatitatively analyzing the causes andimpact factors of reviews not being voted for helpfulness. Besides, we attempted toreveal consumers'complex psychology and behaviors through first-hand textfeatures data of reviews, which provides a new perspective, method and means forstudying online consumer behaviors.
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