Research
I study corporate and competitive strategy. My research examines entry, exit, competition, and innovation in technology infrastructure markets, including data centers, electricity generation, and wireless spectrum. A second stream examines how generative AI reshapes entrepreneurship and competitive advantage.
Job Market Paper
Ownership, Strategic Focus, and Asset Productivity: Evidence from U.S. Electricity Generation
This paper studies electricity generation as a critical infrastructure supporting the expansion of artificial intelligence. I examine how private capital affects the operation and longevity of the fossil power plants that increasingly supply data center demand. Linking high frequency production and emissions data to transaction level ownership records, I find that private equity ownership improves thermal efficiency by about 2–5%, reducing annual CO₂ emissions equivalent to those of 1.3 million passenger vehicles. These operating gains come with a countervailing effect: private equity also reduces the hazard of fossil asset retirement by roughly three-quarters, making the net climate impact depend on what capacity would otherwise replace retired plants. To discipline the mechanism, I derive and test predictions about sponsor-asset matching, heterogeneous treatment effects, and post-acquisition operating practices. The gains concentrate where owners possess technologically relevant portfolio experience and greater control over plant operations, consistent with specialist knowledge being transferred across related assets. The paper shows how ownership change can reorganize legacy infrastructure in ways that improve short-run operating performance while reshaping the long-run path of decarbonization.
Dissertation
Beyond Price: Essays on Entry and Competition in Foundational Markets
- Winner, Will Mitchell Dissertation Research Grant, Strategic Management Society, 2026–2027
- Top 10 Finalist, Three Minute Thesis (3MT) Competition, Harvard University, 2026
- Best Paper Designation (Chapter 1), Academy of Management Annual Meeting, 2025
- Best Paper Nomination (Chapter 2), Strategic Management Society Annual Meeting, 2026
Submitted Papers
Invisible Firms, Competitive Neglect, and Sustained Profit Generation
Abstract: Profit-generating firms can sustain their performance-even in the absence of barriers to entry and costly to imitate resources and capabilities-if they and the profits they generate are “invisible” to potential competitors. “Invisibility” can lead to “competitive neglect” which can enable a firm to generate “unawareness rents,” all without traditional impediments to competition. This paper explores the conditions under which “invisibility” may exist and persist, how firm “invisibility” can evolve over time, and the relationship between invisibility and other impediments to competition.
Generative AI and the Ability of Entrepreneurial Opportunities to Generate Sustained Competitive Advantages
Abstract: This paper examines how generative artificial intelligence (GenAI) affects the ability of entrepreneurial opportunities to generate sustained competitive advantage. We argue that GenAI’s impact is conditional on how those opportunities are formed. Discovery opportunities originate from exogenous industry shocks. However, widely available GenAI tools are likely to commoditize opportunity recognition in these settings and thus reduce advantages that might have been generated by exploiting these opportunities. Creation opportunities emerge endogenously, under conditions of Knightian uncertainty, through entrepreneurial action and interaction with the environment. However, GenAI cannot fully resolve the Knightian uncertainty inherent in creation settings, so sustained advantage here depends on whether resources and capabilities developed through creating an opportunity are inimitable. Unawareness opportunities rely on competitive neglect. GenAI may reduce the advantages of firms in these settings when it makes rents legible to potential competitors and when search is directed toward these invisible markets.
Wireless Communications Equipment Markets: Evolution, Classification, Measurement
Abstract: A central concern of many policy debates has been to foster more innovative wireless markets. How can policymakers assess whether this objective has been achieved? One measure of successful innovation is an increase in the breadth of markets addressed by new products. Existing product taxonomies, such as the North American Industry Classification System (NAICS), require new products to fit into legacy categories. Thus, they may fail to fully measure the development of new products from emerging wireless markets. This study proposes an experimental product code based on the compliance and certification applications for over 200,000 wireless devices in the Federal Communications Commission’s (FCC) Equipment Authorization System (EAS) database from 1982 to 2021. The taxonomy was developed using a novel methodology, in which key phrases from application product descriptions were matched to product categories. The product code is inspired by, but diverges from, the NAICS codes. It comprises three levels of nested product aggregation: 26 Classes, 83 Families, and 298 Types, offering unique avenues to analyze the cross-market scope of wireless technology over decades. The study shows that the breadth of markets for wireless products has grown over time, particularly in areas supported by unlicensed spectrum and corresponding standards, such as Wi-Fi and Bluetooth.
Strategic Focus: Evidence from the U.S. Power Generation Sector
An earlier version of the job market paper.
Entrepreneurial Projection Strategy: Constructing Credibility Through Grounding and Calibration
Abstract: Revenue projections in entrepreneurship are speculative: entrepreneurs can make up any number, and investors know that the number is made up. We develop a framework of entrepreneurial projection strategy explaining how these projections acquire persuasive force under bidirectional information asymmetry. Grounding makes projections analytically interpretable by disclosing entrepreneur-held assumptions and contingencies. Calibration makes projections plausible relative to investor-held benchmarks. Using 1,493 investor evaluations from 436 investors assessing 254 startup business plans, we find that larger revenue projections are evaluated more favorably when accompanied by cost estimates or risk disclosure. Projections above the evaluation cohort are rewarded, but the benefit reverses as projections stretch further beyond peers. These findings illuminate how entrepreneurs construct credibility from seemingly made-up numbers.
Working Papers
Regulating Product Innovation: Certification Reform and Market Evolution in U.S. Wireless Communications
Abstract: How does a decline in regulatory burdens shape product introduction, firm participation, and competitive dynamics in technology markets? This study examines the Federal Communications Commission’s transformation of wireless device regulation between 1997 and 2001. Using administrative records covering nearly 200,000 equipment authorization applications between 1990 and 2015, the study documents market, firm, and product outcomes following a decline in regulatory costs. The study documents four broad patterns. First, regulatory processing times fell sharply, followed by a sustained expansion in product introductions and firm participation, especially in unlicensed spectrum applications. Second, this expansion was driven disproportionately by new entrants, who contributed extensively to product variety and experimentation. Third, despite heightened entry and competition, established firms retained persistent survival advantages. Fourth, the combination of widespread entry and incumbent persistence is difficult to reconcile with strong forms of regulatory capture. Taken together, the findings suggest that well-designed regulatory reforms can simultaneously enable entrant-led experimentation while preserving incumbent persistence. The findings inform contemporary debates on regulating emerging technologies, in which similar privatized certification models are being considered.
When the Storm Hits: Climate Shocks and Multi-Unit Firm Location Strategy
Entrepreneurship and AI: Evidence from GPT-Powered Bing
Incorporating Google Trends Data Using Bayesian Structural Time Series
Abstract: The paper examines the benefits of incorporating Google Trends data in predicting consumer confidence in Sri Lanka. Increasing prediction accuracy: The Central Bank of Sri Lanka is able to forecast consumer confidence with greater certainty. Reducing time lag: The Central Bank is able to make real-time prediction of consumer confidence. The first benefit results from the ability of using Google search queries to reflect consumer confidence. Google Inc. classifies search queries into categories via Google Trends service. Incorporating Google Trends data increases the predictive power of the forecast model, compared to AR(1) baseline. The second benefit arises because Google Trends data are available in real time. Economic time series, like consumer confidence, are reported infrequently, often monthly or quarterly. Using Google Trends data reduces the time lag of consumer confidence reporting.
Other Writing
- Barney, J.B., Zhang, H., & Neumann, J. (2026). Invisible companies. Colossus.
- Zhang, H., Stewart, S., Chui, M., Manyika, J., Julien, J.P., Dame Hunt, V., Sternfels, B., & Woetzel, J. (2021). The economic state of Black America. McKinsey & Company.
- Zhang, H. (2020). Cross-country GDP comparison: Purchasing power parity sexennial update. The Financial Times.
- Laboure, M., Zhang, H., & Braunstein, J. (2018). The rise of Silicon China. Project Syndicate.
- Zhang, H. (2017). The low U.S. unemployment rate should not be celebrated. Harvard Kennedy School Review.
- Zhang, H. (2017). U.S. manufacturing jobs are not coming back. Harvard Kennedy School Review.