Searches and Recommendations: Item-finding in Complex Information Environments

Abstract

Information environments have grown vastly in complexity. Constantly added new features, such as various recommender systems, both offer alternative use approaches and compete for user attention. We studied the actual use of such complex information environments to see how users are using them and what strategies have emerged from that use.

Research has thus far largely focused on studying parts of such environments in isolation, and we wanted to see the whole picture and how the parts are used in the context of the whole. We used applied ethnography, observation with verbal protocol and semi-structured interviews, to study user behavior in Amazon, the world’s largest online retailer. Our six participants were all genuine users.

Our data shows how genuine users actually find items of interest in feature-rich information environments. Furthermore, we discuss how the participants experienced social presence in the environment. Our data is qualitative, and thus we focus on describing and discussing different aspects of and patterns in the item-finding process in addition to formulating tentative theories about user strategies that have emerged in complex information environments.

Our results underscore the need for studying information environments as whole in addition to studying them in parts because the context of the whole affects how users use the features. Neither level can be neglected when striving to build information environments that truly serve their users.

Keywords: Information environments, recommenders, applied ethnography, item-finding, strategy, social presence, user study.