Forecasting the commercial attractiveness of user-generated designs using online data.An empirical study within the LEGO user community

Web 2.0 technologies and the rapid emergence of virtual user communities have created new challenges and opportunities for producer firms. The challenges concern the problem of idea overload when a large number of users are empowered to develop their own design creations. At the same time, opportunities arise because firm-hosted user communities offer a promising source of creativity outside the firms' boundaries. In this paper, we study which data present in firm-hosted online communities on user-generated designs and user-designers can be used to help a focal producer firm to reduce its workload in the selection phase by predicting which user-generated designs it would most likely perceive as commercially attractive. Prior research emphasizes that among the vast amount of ideas generated in online user communities, it is the lead users' ideas that tend to stick out in terms of commercial attractiveness. Our paper aims to provide the next step by developing a heuristic for filtering commercially attractive ideas that are generated in online user communities. Therefore, prior lead user research is used as a point of reference for our study. This research stream has produced rich insights into the characteristics of users who are capable of developing new products that are commercially attractive from the perspective of a focal producer firm, as well as the characteristics of artifacts that such users tend to develop. Based on prior lead user research, we use theories on problem solving, creativity, and new product adoption to develop hypotheses on the factors that might influence the attractiveness of user-generated designs from the focal producer firm's perspective in such a setting. Applying multilevel generalized linear modeling, 1799 designs from 116 user-designers in the LEGO user community are analyzed.