A path-dependence perspective on the adoption of Internet of Things: Evidence from early adopters of smart and connected sensors in the United States

As an integral part of the Internet of Things (IoT), smart and connected sensors are emerging information and communication technologies that collect and transmit real-time data from various urban domains to inform decision-making. While smart sensors and IoT technologies have great potential to transform public service provision, their adoption in the public sector seems to be slow and incremental. Using cross-sectional data of 65 large and mid-sized cities in the United States, we examine what affects local governments' adoption of smart and connected sensors. We propose a path-dependence explanation for the incremental adoption and test if a local government's sensor adoption behavior is shaped by its existing policy priorities and managerial practices in related fields. Our results show that local governments' early adoption of smart sensors is likely to stem from their needs in specific policy domains. We also find that a local government's historical paths on urban sustainability and data-driven decision-making practices can predict its trajectory of sensor deployment, in terms of the scope and the integration of smart sensors across different urban domains. Surprisingly, a local government's e-government progressiveness is not a significant predictor. Our results confirm the incremental change in smart sensor adoption and provide implications for local governments' IoT planning.