news

Cover Comment | Reverse the information distortion and reduce the decision-making cost of online shopping

2024-08-26

한어Русский языкEnglishFrançaisIndonesianSanskrit日本語DeutschPortuguêsΕλληνικάespañolItalianoSuomalainenLatina

□Jiang Jingjing
"Is it normal that a product with sales of more than 1 million units only has a few hundred reviews?" A recent investigation by a reporter found that many consumers reported that on some online shopping platforms, the credibility of product sales, reviews, store ratings, etc., which are important reference information for online shopping, is questionable, and there are still a lot of cases of "Internet trolls" brushing up good reviews and sales. The experts interviewed believe that in order to gain an advantage in the fierce market competition, some businesses use unfair means to increase product sales and good review rates, mislead consumers, and thus increase their own trading opportunities. This phenomenon not only violates the principle of fair competition in the market, but also infringes on consumers' right to know and right to choose. (Legal Daily)
In the context of a new round of e-commerce wars, the economic cost of online shopping is lower, but the corresponding decision-making cost is on the rise. The so-called "decision-making cost" refers to the cost of making the right shopping choice, including time, energy, and the probability and loss of stepping on thunder. Due to the distortion of key information such as sales and evaluations on some e-commerce platforms, the "reference system" that consumers used to rely on is no longer reliable, which will inevitably lead to increased difficulty in online shopping. When online shopping becomes a "difficult task" that requires thrilling steps and a battle of wits and courage, the deterioration of the consumer experience it brings may not be compensated by "low price" or "cost-effectiveness".
The data of online stores should be a spontaneous presentation of the real situation, and it should be objective and accurate. But the actual problem is that with the development and growth of e-commerce, it has formed a complete set of upstream and downstream industrial chains, forming all kinds of "hidden rules" and "dark orders". Speculative operations such as brushing orders and controlling reviews have become common practices in the industry to a large extent. For some time, in some parts of the e-commerce market, the quality of goods is not as good as that of "operation and maintenance", which constitutes a strong reverse demonstration. Although "brushing orders" and "controlling reviews" are drinking poison to quench thirst, how many people in the game can really keep themselves out of trouble?
The Implementing Regulations of the Consumer Rights Protection Law, which came into effect on July 1 this year, clearly stipulated for the first time that merchants are prohibited from "faking orders and speculating on reputation", and pointed out that this is an illegal act of obtaining profits based on false transactions, which violates business ethics, disrupts market order, and should be an invalid contract. However, this kind of universal and large-scale industry fraud obviously cannot expect consumers to defend their rights in a personalized and piecemeal manner. In this process, the platform should make its attitude clear and stand firm. For sellers who "fake data", the active identification and punishment mechanism should be strengthened to promote the return of industry competition to normal track.
Many mature online shoppers can see through such ridiculously fake online stores as "more than 1 million units sold with only a few hundred reviews". What needs to be asked is why the platforms with data and technology advantages turned a blind eye to this and let it go? After becoming giants, have some e-commerce platforms also fallen into the "darkness under the lamp" dilemma of internal control failure? Have they also lost their initial decision-making, efficiency and governance capabilities due to the "big enterprise disease"?
Report/Feedback