Putting Big Data to Work in Government: The Case of the United States Border Patrol
研究美国边境巡逻队如何建设大数据能力，发现领导层与一线员工合作试错是成功关键，对关注公共部门技术采纳的学者和管理者有参考价值。
Abstract Investigating how the public sector adopts technologies to process and analyze very large datasets is crucial for understanding governance in the digital age. The authors of this article examine a large government agency, the United States Border Patrol (USBP), an organization that is in the early phases of building big data capabilities. They argue the wide‐scale adoption of big data analytics will require trial‐and‐error processes coordinated by organizational leadership in partnership with front‐line employees who make the technology relevant to their needs in the field. Absent engagement from both levels, organizations like USBP that face significant barriers to adoption (e.g., limited data science expertise) will struggle to leverage data at scale. The authors also extend the literature on big data in the public sector and provide a rich description of how factors, such as organizational leadership and resources, impact the innovation process.