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OVERVIEW
OVERVIEW
I study how emerging technologies move from technical possibility to real-world adoption.
Across work on drones, robotics, automation, and technology-based economic development, I study how firms, workers, governments, and ecosystems respond to uncertainty. I am especially interested in why promising technologies succeed in some organizational and institutional settings while stalling in others.
My work combines qualitative and quantitative methods, including interviews, archival data, web scraping, market analysis, and policy datasets. Across projects, I turn messy evidence into frameworks, case studies, and practical insights that help people understand where adoption stalls, what conditions enable scale, and how organizations can make better decisions around emerging technologies.
Smart Machines in a Messy World
Smart Machines in a Messy World
Why do robots that work in controlled settings struggle on real job sites? Drawing on 30+ interviews, field engagement, and a mapped landscape of 300+ construction robotics companies, this project examines how workflow fit, trust, liability, and buyer readiness shape adoption. The research shows that technical capability is rarely enough: successful firms begin with narrow use cases, build credibility, and redesign the surrounding system as they scale.
Methods: Interviews, ecosystem mapping, field research, and facilitated discovery.
How One Regulation Standardized Drone Innovation
How One Regulation Standardized Drone Innovation
I expected clearer rules to set drone design free. Instead, tracking 335 agricultural drone models launched between 2000 and 2021, I found that new designs converged around the FAA's 55-pound standard: the rule itself became a design magnet. The exceptions were local. Firms near industry consortia followed the standard even more closely, while firms near farmer-facing knowledge networks kept experimenting. Regulation sets the standard. Unconventional designs survive in the places where builders and users learn together.
Methods: Longitudinal product data, regulatory filings, archival research, web archives, and quantitative analysis.
INSTITUTIONS MEET ECOSYSTEM
Yu, D. and Armanios, DE. “Institutions Meet Ecosystem: China’s Market and Institutional Infrastructure in the Commercial Drone Industry,” Strategic Management Journal, revise and resubmit.
This project examines how market and institutional infrastructure shaped the rise of China’s commercial drone industry. Using firm founding data and regional policy variation, I study how different forms of infrastructure supported different parts of the ecosystem, from component suppliers to end-product firms. The project highlights how governments can reduce uncertainty in emerging markets, but also how different policy choices shape the structure of an industry.
VARIETIES OF LOCAL GOVERNMENT EXPERIMENTATION
Armanios, DE; Lanahan, L.; and Yu, D. 2020. “Varieties of Local Government Experimentation: U.S. State-led Technology-Based Economic Development Policies, 2000 – 2015,” Academy of Management Discoveries, 6(2), 266–299.
This published study examines how U.S. state governments experiment with technology-based economic development policies. Using a dataset of 1,659 state-led initiatives, we identified different policy archetypes, including hub specialists, public entrepreneurs, industry architects, and ecosystem designers. The project helps explain how public institutions attempt to shape innovation ecosystems under uncertainty.
Dataset available to researchers to build on this work and to policymakers seeking to benchmark their state's TBED efforts to those of other states. Please visit the CMU State Government Data webpage.
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