| With the rapid development of e-commerce,online shopping has become an important purchase channel for consumers.E-commerce retailers take advantage of information asymmetry to manipulate online reviews to improve product demand through fake reviews.Due to the existence of fake reviews,the quality of the product that consumers learned after reading online reviews is higher than the actual,which make some consumers who would not buy the product make a purchase decision under the confusion of fake reviews.In order to regulate fake reviews,the government and e-commerce platforms have introduced various policies.However,on the one hand,a harsh punishment will make online e-commerce retailers no longer take measures to encourage consumers to create online reviews.As a result,the number of online reviews will decrease and consumers will get less product information.On the other hand,a gentle punishment will "indulge" fake reviews.Therefore,how to set up a reasonable regulatory strategy to promote online reviews and avoid fake reviews is an urgent problem for regulators to solve.This thesis analyzes the regulatory issues of false reviews from three dimensions: product,customer,and time.Firstly,according to the quality attributes of products,divides products into two types: searching products and experiencing products.Considering the vertical competition of the supply chain,Stackelberg game model is established.By comparing consumer surplus and social benefits,the optimal punishment intensity is given.Secondly,considering the horizontal competition of similar products and consumer price preference,introducing partial rational customers,signal game model is established to explore the regulation strategy of fake reviews when consumers realize the existence of fake reviews and rational customers verify the authenticity of online reviews.Finally,considering that the fake reviews in the previous stage have a negative impact on the demand of the next stage,this thesis uses dynamic planning methods to explore the supervision strategy of fake reviews under multi-period dynamic decision-making.According to the results of the analysis,this thesis gives the following regulatory recommendations for fake reviews.(1)For experiencing products,regulators need to set relatively large punishment intensity;For searching products,relatively small punishment intensity should be adopted.Such classification supervision not only expands the " reviews pool" of the products,but also keeps the exaggeration at a very low level,so that the fake reviews are similar real online reviews,increasing consumer surplus and social benefits.(2)From the perspective of vertical competition in supply chain,for experiencing products,increasing punishment intensity is beneficial to manufacturers,so regulators can cooperate with manufacturers to supervise online e-commerce.For searching products,it is beneficial for manufacturers to increase the punishment intensity,so regulators should strengthen the supervision of manufacturers,to prevent manufacturers from shielding online businesses or even "collusion" with them.(3)When similar products compete horizontally,if consumers posterior probability is small,the consumer price preference is medium and the product quality difference is large,the reduction of punishment intensity is conducive to the increase of consumer surplus and social welfare.If the consumer posterior probability is large,at this time,regardless of consumer price preference and product quality difference,severe punishment intensity should be adopted to let low-quality online e-commerce businesses no longer manipulate online reviews.(4)When the consumer posterior probability is small,the consumer price preference is medium and the product quality difference is large,the higher the proportion of rational customers,the better.Otherwise,with the increase of rational customers,the increase of the total cost of verifying online comments will be higher than the increase of the net utility obtained by consumers after verifying comments,resulting in more disadvantages than advantages.Regulators could use this feature to encourage consumers to actively validate online reviews when the quality of products is high.When the product quality difference is relatively small,consumers are encouraged to buy the product directly.(5)In multi-period dynamic decision-making,when the negative impact of fake reviews is small,the punishment intensity can be set to medium,which can maximize the increase of consumer surplus and social welfare.When the negative impact of fake reviews is large,regulators should adopt a draconian regulatory strategy to prohibit e-commerce retailers from manipulating online reviews. |
