
Police officers perform their duty every day under a constant threat of violence, and each year, as many as 50 police officers in the United States (U.S.) lose their lives in the line of duty. This study proposes that Information Technology (IT) could help to prevent violence against police officers. Specifically, we examine the relationship between IT and the number of police officers killed or assaulted in the line of duty. Integrating the literature on IT-enabled organizational capabilities with the criminology literature, we theorize that IT helps to develop an intelligence-led policing capability, which in turn helps to reduce violence against police officers. Our empirical analysis of 3,921 U.S. police departments shows that crime analysis and computer-aided dispatch are significantly associated with a decrease in the deaths of police officers. Computer-aided dispatch and in-field report writing are also related to fewer assaults to officers. Besides contributing to the nascent literature on the business value of IT in the public sector and the broader literature on the societal impact of IT, we expand the scope of the IS literature by theorizing and empirically demonstrating the role of IT in the occupational safety of organizations that operate in highly unpredictable, risky, and life-threatening environments.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
