RIROSE: Rational Information Retrieval in Online Search Environments[Formula presented]

We design a benchmark algorithm that mimics the sequential behavior of users when retrieving information from the set of alternatives provided by an engine within the first page of online search results. The benchmark defined by the algorithm is designed to evaluate deviations from the rational retrieval strategies determined by the subjective preferences and beliefs of users. The algorithm accounts for the 2047 nodes composing the binary decision tree defined by the ten alternatives ranked within the first page of results. The flexibility of the algorithm allows to incorporate modifications accounting for search frictions and different degrees of impatience on the side of users, as well as testing the categorization capacities of machine learning techniques.