Using a dataset of 8,907 users of OLIO, a sharing-economy app designed to facilitate peer-to-peer food sharing and redistribution in response to UN SDGs 2 and 12, this study investigates the extent to which actor-differentiation between community volunteers and regular users is possible, and a useful means for quantifying the efficacy of volunteer-based community activation for start-ups. Specifically, we find that food-collection volunteers have substantially greater unique interactions and item listing volumes. We also find that volunteers have eight times more contact with other users and 17 times higher listing volumes. Volunteers also have conversations four times sooner after listing an item for sharing, and faster transaction rates. We conduct this research against a backdrop of increased interest in data-driven research in entrepreneurship and innovation and with reference to opportunities to advance the operationalization of SDGs via innovation mobilization.

使用一个OLIO用户的8,907个数据集，该共享经济应用程序旨在响应联合国SDGs 2和12促进点对点食品共享和再分配，该研究调查了参与者差异的程度社区志愿者和常规用户之间的联系是可能的，这是一种量化基于志愿者的社区激活对初创企业的有效性的有用手段。具体而言，我们发现食物收集志愿者的互动性和物品清单数量大得多。我们还发现，志愿者与其他用户的联系增加了8倍，列表数量增加了17倍。志愿人员在列出要共享的物品后也可以更快地进行四次对话，交易速度也更快。我们在对企业家和创新的数据驱动型研究越来越感兴趣的背景下进行这项研究，并参考了通过创新动员促进可持续发展目标运营的机会。