Research On The Factors And Influence Mechanism Of Biased Online Product Reviews In C2C Mode

With the rise of the online shopping, the disadvantages are also growing.Especially the virtual of the internet makes consumers difficult to determine the truequality of the commodities. The common measure to solve the problem is to learn fromthe existed online product reviews. However, the authenticity of online product reviewsis still questionable. If the online product reviews do not represent the real perceptionsof the mass and couldn’t convey the accurate information of the commodity, which willincrease the risk of the other consumer’s transactions and will mislead enterprisesmaking correct strategy. Given this, the paper concentrates on the topic of “TheFactors and Influence Mechanism of Online Product Reviews Bias Based on C2C Mode”to make a deep research from three different angles to explore the sources of the bias.The paper focus on the influence mechanism of the three aspects including theconsumer’s self-selection bias, the C2C site’s appraisal mechanism and the seller’smanipulation behavior to the online product reviews to explore the methods to correctthe biased online product reviews.In the beginning, measuring whether there is bias in the online product reviews ofC2C sites in China. Empirically analyzes the overall data features of the C2Ce-commerce site. Through the behavioral experiment, the paper simulates the real sceneof the online shopping to acquire the experimental data features. The C2C sites’ data,the experimental data and the existed research results are compared to explore theexistence of the bias in the online product reviews of C2C sites in China.Then, from three angles of the online product reviews main body—the consumer,the site and the seller, the paper explores the sources and the influence mechanism ofthe biased reviews.Firstly, the influence mechanism of consumer’s individual preference to the onlineproduct reviews bias. In the first place, the paper discusses the factors of the biasedreviews from the angle of consumer’s individual preference, including the consumer’sselection preference, the inactive review behavior and the consumer’s conformity ratingbehavior. Then, based on the data features of the online product reviews, we constructthe model to reflect these factors influence mechanism. At last, we put forward theconditions of the mean to be the unbiased estimator of the product quality based on thisangle so as to overcome the bias of the consumer’s individual preference. Secondly, the influence mechanism of C2C sites’ appraisal systems to the onlineproduct reviews bias. In the first place, the paper discusses the factors of the biasedreviews from the angle of the C2C site’s appraisal system, including the “DefaultGood Reviews” mechanism, and the “Return Goods” mechanism. Then, based onthe data features of the online product reviews, we construct the model to reflect thesemechanism’s influence. At last, we put forward the conditions of the mean to be theunbiased estimator of the product quality based on this angle so as to overcome the biasof the C2C sites’ appraisal system.Thirdly, the influence mechanism of seller’s manipulation to the online productreviews bias. In the first place, the paper screens the influence factors from the seller’sangle. Then, based on the data features of the feedback rate, the paper recognizes theexistence of the seller’s manipulation behavior through the mathematics deduction.Then, we construct the online product reviews model to reflect this manipulatebehavior’s influence. At last, combing with the Taobao’s actual data, we derive the ofcurvilinear equation of the seller’s manipulation and acquire the real score of the onlineproduct reviews so as to reflect the influence mechanism of the seller’s manipulationbehavior along with the time and to achieve the goal of overcoming the bias of theseller’s manipulation behavior.At last, based on the previous research, the paper reaches the conclusion. Besidesthis, we put forward the related suggestions on how to conquer the defects of theconsumer, the C2C e-commerce sites and the seller.