Community-Based Recommender Systems: Analyzing Business Models from a Systems Operator´s Perspective

Past research has shown that corporations benefit from using community-based recommender systems. Through them, they create digitized word-of-mouth that helps consumers make purchase decisions. While there exists much literature on the effects of re commender systems, to our knowledge, no prior studies have examined the underlying business models, nor have they considered the roles of system operators and the process for these recommender systems to achieve profitability. Based on our synthesis of relevant theory, we propose a framework for evaluating the value of re commender system business models from the viewpoint of system operators. We discuss patterns and situational characteristics that are associated with the business value of consumer-generated content and the concomitant profits of system operators.