| Title |
Smart City Investments: A Rapid Decision Framework for Public Private Partnerships |
| ID_Doc |
36940 |
| Authors |
Rayi, PS; Bothra, RL; Wallace, S; Venkatesh, M |
| Title |
Smart City Investments: A Rapid Decision Framework for Public Private Partnerships |
| Year |
2019 |
| Published |
|
| DOI |
|
| Abstract |
The city of Syracuse in New York announced an ambitious smart city plan which, when fully implemented, promises to make it the most connected city in the northeastern US. Thanks to a strategic investment by the State of New York, the city is home to what is billed as the world's first Drone Corridor for R&D. We outline a decision framework (The Syracuse Wheel) for public private partnership to help city leaders and private investors navigate the exciting implications stemming from these two strategic developments and the city's environment to augment the priority areas of Autonomous Mobility and Connectivity. The Wheel positions Syracuse as a prime market for visionary Public Private Partnership (PPP) proposals given its infrastructure and assets specific to Unmanned Aerial Systems (UASs) and Autonomous Vehicle Testing. The research also suggests ways to mitigate the problems associated with data governance and IP governance that various large-scale PPPs have faced in the past. We conclude with a decision-making framework which facilitates a fast-track approval mechanism for investment proposals from private entities as Syracuse prepares for its future as leading-edge Smart City and UAS R&D hub. |
| Author Keywords |
asset; connectivity; data governance; drones; fast-track approval; IP governance; infrastructure; environment; Autonomous Mobility; open API; public private partnership; smart city; unmanned aerial systems; winter testing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000503382900071 |
| WoS Category |
Engineering, Electrical & Electronic; Remote Sensing |
| Research Area |
Engineering; Remote Sensing |
| PDF |
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