The circular economy (CE) aims at cycling products and materials in closed technical and biological loops. Cradle to cradle (C2C) operationalizes the CE with a product design concept rooted in the circulation of “healthy” materials because contamination of materials with substances of concern hampers cycling and may pose risks to people in contact with them. Extant research shows that barriers often hinder organizations from successfully pursuing cradle‐to‐cradle product innovation (CPI). Innovation community theory helps to explain how to overcome barriers and further the innovation process by taking a microlevel perspective on intra‐ and interorganizational collaboration of individual promotors (or champions). We elaborate innovation community theory with a longitudinal embedded case study of a C2C frontrunner company with the goal to get a precise understanding of how promotors collaborate in the CPI process. Our contribution is threefold: We identify eight collaboration mechanisms used between promotors to sequentially overcome a hub firm's individual, organizational, value chain, and institutional level barriers to circularity. Second, we differentiate these mechanisms according to their cooperative and coordinative facets and put emphasis on the coordinative functions of those mechanisms linked to the C2C standard. Third, we highlight the importance of promotors at the linking level who facilitate the CPI process as intermediaries.

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Reputation is an important aspect of trust. If no direct trust experiences are available, one needs to rely on reputation data from other sources. In this paper we present the Neighbor-Trust metric that exploits these communication capabilities of a network by directly asking all neighbors of a target communication partner for reputation trust data. This results in a reputation path of length one, but also in a vulnerability to attacks by unknown, lying entities that try to promote not trustworthy entities. However, by adding weights for reputation data given by entities and a learning mechanism the Neighbor-Trust metric is able to identify and adapt to lying participants in the network by reducing the weight their reputation data has in future reputation calculations. We present an evaluation for the metric and show how to exclude lying participants from the network.

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