Published Work

Peer-Reviewed Publications

Enabling Technologies and The Role of Private Firms: A Machine Learning Approach

ABSTRACT: Investments in enabling technologies–including 5G, artificial intelligence, and the lidar technology–are important strategic decisions for firms. A common assumption is that enabling technologies have their origins in public sector projects. In contrast, we know much less about whether, and how, private firms are involved. This paper asks how inventions that private firms developed with vs without public-sector partners differ in their enabling-technology trajectory. Using machine-learning matching, we compare patented technologies generated from over 30,000 public-private relationships with comparable technologies invented by private firms alone during a 21-year period. To measure the enabling potential of a technology, we introduce a new “Enabling Technology Index.” The findings show that private firm relationships with the public sector–in particular cooperative agreements and grants with mission agencies (NASA and Department of Defense)–are likely starting points for enabling technology trajectories. We thus put a spotlight on organizational arrangements that combine the breadth of exploration (agreements, grants) with deep exploitation in a particular domain (mission agency). A key contribution is a better understanding of the types of private-firm efforts that are associated with enabling technologies.

Human–Automation Collaboration in Occluded Trajectory Smoothing

Rathje, J.M.; Spence, L.B.; Cummings, M.L., “Human–Automation Collaboration in Occluded Trajectory Smoothing,” Human-Machine Systems, IEEE Transactions on, vol.43, no.2, pp.137,148, March 2013

ABSTRACT: Deciding if and what objects should be engaged in a ballistic missile defense system (BMDS) scenario involves a number of complex issues. The system is large, and the timelines may be on the order of a few minutes, which drives designers to automate these systems. The critical nature of ballistic missile defense engagement decisions however, suggests exploring a human-in-the-loop approach to allow for judgment, knowledge-based decisions, and the ability to override automation decisions. This BMDS problem is reflective of the function allocation conundrum faced in many supervisory control systems, which is how to determine which functions should be mutually exclusive and which should be collaborative between humans and automation. This paper motivates and outlines two experiments that quantitatively investigated human/automation tradeoffs in the specific domain of tracking problems. Participants in both experiments were tested in their ability to smooth trajectories in different scenarios. In the first experiment, they clearly demonstrated an ability to assist an algorithm in more difficult, shorter timeline scenarios. The second experiment combined the strengths of both human and automation in order to produce a collaborative effort. Comparison of the collaborative effort to the algorithm showed that adjusting the criterion for having human participation could significantly improve solutions. Future work should focus on further examination of appropriate criteria.

Opinions and Commentary

Thesis and Dissertation

Essays on Public Funding for Private Innovation

Rathje, J.M., “Essays on Public Funding for Private Innovation,” PhD Dissertation, Leland Stanford Junior University, Stanford, CA, 94305, 2019.

ABSTRACT: Despite the significant annual expenditure of public (government) research and development (R&D) funding allocated to private, for-profit firms, research is unclear as to if whether or not public funding is positively associated with firm performance. To partially address this gap, in three essays I examine the most common funding tie between public organizations and private firms in the U.S. – public-private R&D relationships. In the first two essays, I conceptualize public-private R&D relationships as institutional hybrids and argue and show that relative to technologies developed without a public-sector partner, the institutional conflict underlying public-private R&D relationships is positively related to the creation of valuable and destabilizing technologies. To provide support for my institutional hybrids’ hypotheses, I employ a novel machine learning-matching method to examine all patented technologies in the U.S. between the years 1982-2012. In the final essay, I focus on technology ventures (i.e., start-ups) that form a contractual R&D relationship with a public-consumer (e.g., NASA, DoD) and show that these start-ups produce technologies faster and survive longer than their non-contracted peers. However, due to the stabilizing dependencies inherent in public-consumer relationships, these ventures also experience slower growth. I conclude with management and policy implications.

Human-Automation Collaboration in Occluded Trajectory Smoothing

Rathje, J.M., “Human-Automation Collaboration in Occluded Trajectory Smoothing,” M.S. Thesis, MIT Aeronautics and Astronautics, Cambridge, MA, 2010.