Government Sejong City, Fair Trade Commission. 2023.10.13[Photo by Yoo Dae-gil, dbeorlf123@ajunews.com]
A study by South Korea's Fair Trade Commission has revealed that algorithmic favoritism on digital platforms can distort consumer product choices. Most online shoppers tend to purchase items ranked highly by the platform, indicating that manipulating algorithms can significantly alter purchase rates.
On June 28, the Fair Trade Commission announced the release of a report titled 'Consumer Behavior Experiment on Algorithmic Self-Preference by Platforms.' This research aimed to verify how consumer choices change when platforms prioritize their own products through search, recommendation, and ranking algorithms.
The commission created a virtual shopping mall that closely replicated actual online shopping interfaces and conducted a randomized controlled experiment with 3,072 consumers. The study also analyzed the effectiveness of informational corrective measures, such as labeling.
The findings showed that consumers heavily rely on the rankings presented by algorithms. A total of 51.7% of purchases were concentrated on the top five products, and 94.6% of consumers completed their purchases on the first page. Only 25.2% of consumers changed the default sorting order, and 83.8% did not use filtering options, indicating a tendency to follow the platform's default rankings.
The study also tested the effects of self-preference by placing a replica product, identical to a lower-ranked item but priced 10% higher, at the top of search results. This resulted in a purchase rate increase of approximately 34 percentage points for that item.
Conversely, the purchase rate for existing top competitors dropped from 52% to 20%, a decline of about 32 percentage points. This demonstrates that simple ranking manipulation can significantly affect consumer choices.
The effectiveness of informational corrective measures aimed at reducing choice distortion was also found to be limited. A 'warning label' attached to self-preferred products actually increased their purchase rate by about 4.5 percentage points and discouraged active exploration by consumers. Only 10.7% of consumers confirmed the sorting criteria.
However, among some consumer groups that did check the disclosures, a trend was observed where the purchase rate for self-preferred products decreased by about 18.4 percentage points.
This research may serve as evidence in ongoing legal disputes involving major platforms. The Fair Trade Commission is currently engaged in legal battles regarding self-preference practices with companies like Kakao Mobility and Coupang.
A Fair Trade Commission official stated, "Given the confidentiality and opacity of algorithms in the platform market, proving the causal relationship between actions and market outcomes is challenging. Therefore, experimental methodologies such as randomized controlled experiments are expected to be useful analytical tools for competition policy research and law enforcement."
On June 28, the Fair Trade Commission announced the release of a report titled 'Consumer Behavior Experiment on Algorithmic Self-Preference by Platforms.' This research aimed to verify how consumer choices change when platforms prioritize their own products through search, recommendation, and ranking algorithms.
The commission created a virtual shopping mall that closely replicated actual online shopping interfaces and conducted a randomized controlled experiment with 3,072 consumers. The study also analyzed the effectiveness of informational corrective measures, such as labeling.
The findings showed that consumers heavily rely on the rankings presented by algorithms. A total of 51.7% of purchases were concentrated on the top five products, and 94.6% of consumers completed their purchases on the first page. Only 25.2% of consumers changed the default sorting order, and 83.8% did not use filtering options, indicating a tendency to follow the platform's default rankings.
The study also tested the effects of self-preference by placing a replica product, identical to a lower-ranked item but priced 10% higher, at the top of search results. This resulted in a purchase rate increase of approximately 34 percentage points for that item.
Conversely, the purchase rate for existing top competitors dropped from 52% to 20%, a decline of about 32 percentage points. This demonstrates that simple ranking manipulation can significantly affect consumer choices.
The effectiveness of informational corrective measures aimed at reducing choice distortion was also found to be limited. A 'warning label' attached to self-preferred products actually increased their purchase rate by about 4.5 percentage points and discouraged active exploration by consumers. Only 10.7% of consumers confirmed the sorting criteria.
However, among some consumer groups that did check the disclosures, a trend was observed where the purchase rate for self-preferred products decreased by about 18.4 percentage points.
This research may serve as evidence in ongoing legal disputes involving major platforms. The Fair Trade Commission is currently engaged in legal battles regarding self-preference practices with companies like Kakao Mobility and Coupang.
A Fair Trade Commission official stated, "Given the confidentiality and opacity of algorithms in the platform market, proving the causal relationship between actions and market outcomes is challenging. Therefore, experimental methodologies such as randomized controlled experiments are expected to be useful analytical tools for competition policy research and law enforcement."
* This article has been translated by AI.
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