As more people go online for shopping, understanding how they rely on e-commerce recommendation systems to make purchases is increasingly important. It is in such context that Penn State University researchers suggested that it's not just what is recommended, but how and why it's recommended, that helps to shape consumers' opinions.

The researchers found that people who like to think and solve problems for themselves -- a personality type the researchers describe as "high need for cognition" -- find content-based recommendations more persuasive.

Through the study published in the Journal of Advertising, the researchers investigated how people reacted to two product recommendation systems. The first system generated recommendations based on the user's earlier purchases -- often referred to as content-based recommendation systems.

The nature of the recommendation system and its degree of confidence in suggesting the right products can be very siggnificant in guiding people when making online purchases, said S. Shyam Sundar, James P. Jimirro Professor of Media Effects in the Donald P. Bellisario College of Communications and co-director of the Media Effects Research Laboratory.

"In the pre-Internet era, before artificial intelligence, we would ask another person at a cocktail party, 'I heard you went to Italy, can you give me some recommendations, I'm going there next month,' as a way of gathering information for making our decisions," said Sundar, who is also an affiliate of Penn State's Institute for Computational and Data Sciences. The second provided recommendations based on what other people bought - called collaborative recommendation systems.

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