More Like this

1. Estimating price sensitivity of economic agents using discontinuity in nonlinear contracts: Estimating price sensitivity using nonlinear contracts

   https://doi.org/10.3982/QE602  

   Bajari, Patrick ; Hong, Han ; Park, Minjung ; Town, Robert ( July 2017 , Quantitative Economics)
2. Optimally Designing Cybersecurity Insurance Contracts to Encourage the Sharing of Medical Data

   https://doi.org/10.1109/CDC51059.2022.9992544  

   Lee, Yoon ; Aswani, Anil ( January 2022 , IEEE Conference on Decision and Control (CDC))
3. Supply Chain Contracts That Prevent Information Leakage

   https://doi.org/10.1287/mnsc.2018.3200  

   Chen, Yiwei ; Özer, Özalp ( May 2019 , Management Science)
4. Decentralized Data Collection via Swarm Contracts: Study on Crowd-Sourced Google Maps

   https://doi.org/10.1109/ICCAR57134.2023.10151727  

   Mallikarachchi, Sanjaya ; Ho, Bonnie ; Kanj, Iyad ; Seneviratne, Oshani ; Godage, Isuru S. ( April 2023 , 2023 9th International Conference on Control, Automation and Robotics (ICCAR))

   “Data is the new oil” has become a popular catch-phrase in the world of technology, emphasizing the immense value of data in today's digital age. Most services and platforms rely on data, but collecting this data can be challenging and costly. To address this issue, we leverage a novel distributed crowdsourcing framework - termed Swarm Contracts - that utilizes blockchain and is applied to robotics technologies. The framework encourages an incentivized crowdsourcing model through open-source robots and a secure, decentralized, and transparent blockchain-based incentive system. As a demonstration of the framework's capabilities, we use it to collect Google Street View ® map data, which can be a resource-intensive task to keep up to date using traditional centralized methods. Our Swarm Contract framework uses Google Street View ® Publish API, which allows for the contribution of street view data to Google Maps @to implement the incentive-based crowdsourcing of street view images. By incorporating a swarm contract-powered framework with the Google Street View ® Publish API, we show that the incentivized crowdsourcing of street view data can be a practical solution to maintain accurate and up-to-date Google Street View ® maps. 

   more » « less
5. Embracing risk dependency in designing cyber-insurance contracts

   https://doi.org/10.1109/ALLERTON.2017.8262837  

   Khalili, Mohammad Mahdi ; Naghizadeh, Parinaz ; Liu, Mingyan ( October 2017 , 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton))

   We study the problem of designing cyber insurance policies in an interdependent network, where the loss of one agent (a primary party) depends not only on his own effort, but also on the investments and efforts of others (third parties) in the same eco-system (i.e., externalities). In designing cyber insurance policies, the conventional wisdom is to avoid insuring dependent parties for two reasons. First, simultaneous loss incidents threaten the insurer's business and capital. Second, when a loss incident can be attributed to a third party, the insurer of the primary party can get compensation from the insurer of the third party in order to reduce its own risk exposure. In this work, we analyze an interdependent network model in order to understand whether an insurer should avoid or embrace risks interdependencies. We focus on two interdependent agents, where the risk of one agent (primary party) depends on the other agent (third party), but not the other way around. We consider two potential scenarios: one in which an insurer only insures a primary party, and another one in which the insurer of the primary party further insures the third party agent. We show that it is in fact profitable for the primary party's insurer to insure both agents. Further, we show that insuring both agents not only provides higher profit for the insurer, but also reduces the collective risk. 

   more » « less