Do Recommander Systems Manipulate Consumers Preferences?

Recommender systems are important in the decision making. Those systems provide the customers suggestions. As a result of this, firms can better serve their customers. This will also lead to an increase in sales. Research has focused on the development and the improvement of recommender systems. But there is not quite much studied about the behavioral implications of using recommender systems. Are those recommender systems manipulating the customers?

Most recommender systems use the consumers ratings items as input. Those recommendations the system provide present an expectation of how well a customer will like an item. There is also a feedback loop, those are the actual ratings of the customer after the purchase has been made. The recommendations are based on the actual ratings of a customer who already has tried this product or item.

There is a possibility that people are influenced by elements in the environment when they make a decision. The first one is the anchoring issue. People are maybe consumed drawn, because the system is presenting an item to them and they choose it. It is important to know if a customer really likes it or just chooses it because it is presented in a advantageous way. It is difficult for people to see if an item is reasonable for them. It could be presented as a advantageous choice, but it will maybe be the opposite!

When there is uncertainty, a customers seeks for the most plausible item. The suggested item is viewed as the ‘correct’ answer, therefore a lot of people will choose this. The users belief that the recommender system will choose the right option for them, therefore they choose what the systems presents to them.

Users that will receive a high recommendation from the recommender system, will also give higher rating after they bought/used it and vice versa. What they saw as a rating, has influence on their own rating. They are biased. This is although not symmetric.

There is an significant effect when the recommendation is raised, but not when the recommendation is lowered. It is notable that this effect is not only taking place when the uncertainty is high, it also operates at the point of consumption.

Also is the reliability of the system important. When the system is known as reliable, the customers’ ratings will be more close to the recommendation the customer has seen before. When the system is thus less reliable, the ratings given by the customer will be less close to the recommendation.


Adomavicius, G., Bockstedt, J. C., Curley, S. P., & Zhang, J. (2013). Do recommender systems manipulate consumer preferences? A study of anchoring effects. Information Systems Research, 24(4), 956-975.

Cosley D, Lam S, Albert I, Konstan JA, Riedl J (2003) Is seeing believing? How recommender interfaces affect users’ opinions. Cockton G, Korhonen P, eds., CHI 2003 Conference, Fort Lauderdale FL (ACM, New York), 585–592.

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