Efficient Structures for Innovative Social Networks
通过重组与选择模型研究组织成员在创新早期阶段的沟通线路，发现动态轮换大量对话伙伴能加速创意产生，核心-边缘图在时间-成本效率前沿上表现突出。
What lines of communication among members of an organization are most productive in the early, ideation phase of innovation? We investigate this question with a recombination and selection model of knowledge transfer operating through a social network. We find that ideation is accelerated when people in the organization dynamically churn through a large (ideally the entire population) set of conversational partners over time, which naturally begets short path lengths and eliminates information bottlenecks. Group meetings, in which the content of conversations is available to all for consideration, are another way to learn in parallel and accelerate the ideation process, although for complex problems they may not offer significant advantages over the best decentralized networks. The idealized core-periphery graphs emerge as an important family on the time–cost efficient frontier. New sociometrics for the analyses of innovation processes emerge from this investigation.