From big data to higher bureaucratic capacity: Poverty alleviation in China
研究大数据技术如何通过创建信息共享平台，提升扶贫政策的精准性和协调效率，并减少腐败，基于中国首个大数据扶贫监测平台的实地访谈。
Abstract This study explores how big data technologies can create an “information commons” shared by all policy stakeholders to alleviate the corruption and information asymmetries long endemic to poverty alleviation programs. We argue that the information commons can transform discrete data first into information with clear policy purposes and then into actionable knowledge. This process increases bureaucratic competence by improving policy accuracy and the efficiency of bureaucratic coordination and augments bureaucratic reliability by facilitating the investigation and prevention of corruption. We substantiate our propositions through extensive field interviews with officials and citizens in a Chinese province that is using China's first monitoring platform powered by big data technology to implement anti‐poverty policies. Our study illustrates the importance of data–information–knowledge chains in improving governance.