The Qubit Quest Decoded: A Mixed-Methods Analysis of Innovation Policies and Ecosystem Mapping in the Race for Quantum 2.0 Technologies

This thesis presents a comprehensive examination of the evolution and dynamics of emerging Quantum 2.0 technologies through the lens of innovation ecosystems. Utilizing a mixed-methods approach that incorporates both qualitative and quantitative data, the study offers a cross-country perspective segmented by various technological, social, and policy factors. The manuscript begins with an in-depth review of the literature, capturing the current state, challenges, and scientific discourse surrounding Quantum 2.0 technologies. It then introduces an "innovation ecosystems" framework to contextualize the complex interplay of policies, strategies, and stakeholder dynamics. The concept of an "innovation pipeline" is further developed, informed by a variety of sources to draft a timeline that traces the emergence and diversification of Quantum 2.0 technologies, primarily within the U.S. context. A scientometric analysis of global quantum-related publications, U.S. patents, and worldwide venture capital investments provides a broad view of the landscape from 2010 to 2022. This data-driven approach uncovers patterns of collaboration and topic divergence, and assesses the variation in the sequential production of knowledge artifacts. The study highlights the top ten global players in the field and leverages a keyword co-occurrence analysis to further elaborate on the trends and ideas influencing Quantum Information Science (QIS). Overall, the dissertation provides valuable insights into the current state of strategic policy approaches on the nascent ecosystems of Quantum 2.0 technologies. The developed analytical frameworks serve as a reference for understanding coherence in policy actions and funding allocations, offering guidelines for future strategic innovation in both public and private sectors engaged in large-scale technological projects.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Institute for Data, Systems, and Society

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Sandoval Sandoval, Jorge I.

Advisors dc:contributor.advisor

• Metzler, Florian
• Murray, Fiona E.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/152892

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/152892