[THE VIEW] Individualized Recommendation Algorithms and Consumer Rights

Advantages in Reducing Search Costs
Concerns Over Higher Prices for Products Tailored to Consumer Preferences
Potential for Price Discrimination and Violation of Fair Trade Laws

When surfing the internet, it is surprisingly common to see news articles that match my preferences. After watching a YouTube video, the next video that appears automatically suits my taste. Also, when logging into an open market, products that match my preferences appear as advertisements without even searching.

Nowadays, ‘individualized recommendation algorithms’ that suggest services or products perfectly tailored to each consumer are common. Over the past decade, with the advancement of IT, companies have found it easier to collect personal information and internet usage records, and their information processing capabilities to predict what individual consumers want have also developed highly, making this possible.

These individualized recommendation algorithms primarily benefit consumers because they reduce search costs. Previously, individuals had to spend time and effort to find information that perfectly suited them, but now algorithms do that work instead.

However, individualized recommendation algorithms can also harm consumers. Since products that match consumer preferences tend to have a higher willingness to pay, companies can easily charge higher prices to such consumers.

This strategy of setting different prices according to consumer characteristics is called price discrimination, and algorithms further subdivide price discrimination. In an extreme example, Amazon in the United States changes prices 2.5 million times a day depending on consumer information and time of day.

However, excessively subdivided price discrimination like this can violate fair trade laws. In fact, many states including California have filed lawsuits against Amazon, claiming that such price discrimination strategies violate antitrust laws. Therefore, from a company’s perspective, avoiding extreme price discrimination may be safer.

After Amazon faced backlash from consumers due to extreme price discrimination, American companies began to hesitate in applying price discrimination. So, if uniform prices are guaranteed to all consumers, would individualized recommendation algorithms only benefit consumers? Recent research suggests otherwise. In the case of Expedia, a travel product open market, even without price discrimination, the introduction of individual algorithms raised the average price by about 5% and increased net profits.

The principle is as follows. For example, there is the same hotel product A, and the algorithm recommends A first to consumers likely to like it, and last to those less likely to like it. The latter group would find it costly in terms of time and effort to click through to the last product A, so they exclude it from consideration altogether. Therefore, the actual consumers considering product A are those with a high willingness to pay, and knowing this, the company can uniformly set a high price for A.

While individualized recommendation algorithms provide the convenience of reducing consumers’ search costs, the resulting price discrimination by companies can harm both consumers and companies, so it is important to maintain an appropriate balance.

Seo Boyoung, Professor at Indiana State University, USA

This content was produced with the assistance of AI translation services.