Driving a More Prosperous Future

Abortion Restriction Laws and Mobility of Scientists
Strategic Management Journal

We track the enactment of targeted regulation of abortion providers (TRAP) laws in the U.S. and analyze 4.98 million person-year mobility records for 535,568 biomedical scientists from 1990 to 2018. Our estimations reveal a 0.8-1.6 percentage-point increase in scientists’ relocation probability after states enacted abortion-restrictive laws, with substantially stronger effects among junior scientists (1.6-3.9 percentage points). Anti-abortion states also became less likely to be chosen as relocation destinations, particularly by higher-quality scientists. These responses appear driven by ideological misalignment and research-related concerns in fields affected by abortion-related regulation. We further find that states that have adopted TRAP laws experienced declines in scientific research quality, federal research funding, and patenting in relevant technological fields and among local firms.

Beril Yalcinkaya, postdoc, The Wharton School, University of Pennsylvania; Waverly W. Ding, Associate Professor of Strategy and Entrepreneurship, R.H. Smith School of Business, University of Maryland;

If We Build It, We Will Come: Strategies for Developing Academic Institutions and the Evolution of Career Choices by Top Talent During Japan’s Industrialization
CJEB Columbia University Working paper series

Modern day economies rely on academia—with its focus on generating new knowledge and training future work forces—as a critical complement to industry in contributing to endogenous growth. How well academia performs this role, however, depends on its ability to recruit and retain talented faculty who have lucrative alternative options in industry; moreover, such allocation of talent in academia vs. industry is conditioned by path-dependencies in the evolution of these sectors. We complement existing literature that has focused on factors in mature scientific labor markets by examining the endogenous evolution of academic institutions concurrent with industrialization in Japan during the turn of the 20th century. Our study combines historical methods with estimation of a dynamic occupational choice model and utilizes unique data on the census of university-educated engineers from the first 40 cohorts since the inception of higher technical education in Japan. The historical analysis reveals systematic shaping strategies to build institutions that catered to both monetary and non-monetary preferences, and the quantitative estimations highlight that the latter were particularly important in academia disproportionately attracting top talent in later cohorts, despite an increasing pay gap with industry.

Takuya Hiraiwa, Serguey Braguinsky, Rajshree Agarwal, University of Maryland Smith School

Technology (Non-) Emergence: The Role of (Mis-)Alignment of Uncertainty Dimensions In Alternative Solar Technology Trajectories
Organization Science

We examine industry and technology (non-) emergence by integrating actor-centric and systems perspective literature streams. We use historical methods to analyze rich data tracking investments by actors spanning private, public and academic sectors in the solar PV context. The industry took several decades after commercialization to emerge; moreover silicon and thin film technologies experienced divergent fates despite firm takeoff. By uncovering critical interdependencies across activities by different actors, we show that while attention by all actors to developing various elements of technological systems is necessary for emergence, it may not be sufficient. The industry emerged after activities by technology producers, industry associations and government agencies ensured stable institutional support that stimulated latent demand (by utilities and end consumers) and created reinforcing loops among activities by technology producers and research institutes for solar technologies to become a viable alternative to fossil fuels. Moreover, silicon experienced additional reinforcing loops in demand side and supply-side ecosystems, wherein technology producers and equipment manufacturers leveraged adjacent mature supply chains to meet demand-side scale and reliability requirements in fast growing markets. In contrast, thin film experienced balancing loops wherein nascent, firm-specific supply side alliances could not address these demand side needs. These findings showcase how dominant designs may emerge even when there is no ex-ante competitive dynamics among technology producers: while silicon may have benefited from first mover advantage at the technology level, our study highlights that ecosystem first mover advantages of silicon relative to thin film were particularly salient in their divergent fates.

Guerra, M. (Bayes Business School) & Agarwal, R. (Maryland Smith)

Flying High or Crashing Down: Pre-Entry Knowledge and the Distribution of Startup Performance
Strategic Management Journal

We examine variation in high-technology startups’ performance based on founders’ pre-entry experiences by developing a formal model and using confidential employee-employer linked microdata from the United States to examine the empirical consistency of the model propositions. The model posits that relative to insiders, a lack of industry-specific experience creates greater epistemic uncertainty regarding optimal business models at time of entry for outsiders and thus, higher post-entry adjustment costs associated with necessary pivots.  Consequently, outsiders have a higher selection threshold for the value creation potential of the underlying technical ideas. Together, these mechanisms yield propositions that relative to insiders, outsiders have lower odds of survival on average, but higher growth and probability of being acquired. The empirical results indicate strong and robust support for these propositions.

Agarwal R. (Maryland Smith) Carnahan, S., (Wash. U. at St. Louis) Campbell, B. (Ohio State University), and Choi, J. (Federal Reserve

Dynamic Investment and Product Market Rivalry: The Network Q Model
February 2026

We present a new dynamic model of corporate investment in imperfectly-competitive product markets, extending the neoclassical (Q) theory of investment to a multi-firm, multi-product, fully structural model.  The model provides an explicit formula to quantify corporate investment and characterize investment spillovers for the entire network of firms in any economy.  The model therefore provides a tool for future for researchers and policymakers alike, to understand relevant issues such as the way in which a specific merger affects all interconnected firms in the same network and consumer welfare, or how changes in aggregate discount rates affect markups and product market concentration both over time and in the cross section of firms.

In the paper, we take our model to the data for the universe of U.S. publicly traded companies and obtain five novel insights: 1) product market competition is a key force driving aggregate investment and capital allocation; 2) the persistence of firm's capital stocks increased over the past 25 years (i.e. capital has became ""stickier""); 3) monopoly rents account for a large, rising share of firms' value; 4) positive shocks to firms' cost of capital increase markups and concentration; 5) mergers consummated since 1995 have led to a modest decline in aggregate capital formation.  These findings contribute to the existing economics and finance literature analyzing the secular decline in product market competition in the US, and the impact of product markets on firms' valuations

Maria Cecilia Bustamante (UMD) and Bruno Pellegrino (Columbia)

Three Strategic Bets on AI’s Future

This paper examines competition in the consumer AI assistant market using worldwide iOS and Android app-store data from seven major AI assistants from May 2023 through December 2025. Rather than finding a winner-take-all market, we show that major product launches tend to coincide with growth in the overall category, with little evidence of direct cannibalization across leading models. In other words, the “AI war” appears less zero-sum than commonly assumed.

The analysis identifies three distinct strategic positions that currently appear viable to date. ChatGPT is pursuing scale, with by far the largest market share and substantial revenue generated from a very large user base. Google Gemini is pursuing an ecosystem defense strategy, using broad distribution and low direct monetization to support Google’s wider platform. Claude is pursuing a differentiated premium niche strategy, with a much smaller user base but much higher revenue per user.

There are three practical takeaways for managers and investors. First, firms should not assume that AI markets will necessarily converge to a single dominant winner. Second, the right AI strategy depends on structural advantage: scale, ecosystem leverage, or premium differentiation. Third, as market growth slows and capital becomes less abundant, each strategy will face different risks, making monetization quality and strategic fit more important than raw user growth alone.

Maxime C. Cohen, Professor, Desautels Faculty of Management, McGill University
Eddy Hage-Youssef, McGill University
Daniel M. McCarthy, Associate Professor of Marketing, Robert H. Smith School of Business, University of Maryland, College Park
D. Daniel Sokol, Professor, USC Gould School of Law; USC Marshall School of Business

The Public Pension Crisis: Contractual Rights and Constitutional Limits
Cambridge University Press, March 2026

A timely response to the pressing issue of public pension reform, The Public Pension Crisis explores the complex relationship between contract law and government pensions, specifically focusing on the Contract Clause and related state Pension Clauses. Analyzing over a decade of litigation, the book highlights the evolving role of pension contracts in constitutional law and examines more than 70 landmark cases to establish a clear, principled framework for determining when pension benefits qualify as contractual obligations. T. Leigh Anenson presents a unified theory to consistently treat public and private pensions, balancing the interests of employees’ earned benefits with the financial challenges facing governments. Combining legal scholarship with practical policy insights, Anenson not only provides a much-needed legal perspective on pension reform but also calls for a systematic approach to addressing the retirement security crisis.

T. Leigh Anenson, J.D., LL.M., Ph.D.

Setting Higher Referral Targets Increases the Number of Women Recommended: Evidence From the Field and Lab
Journal of Applied Psychology

Women continue to be underrepresented in numerous occupations and in the highest echelons of many organizations. This may be due, in part, to disadvantages they face in referral-based hiring and promotion processes. We propose a low-cost and easily scalable intervention to boost referrals of women in male-dominated contexts: requesting a greater target number of referrals (e.g., at least four instead of at least two referrals). Across six experiments (including two field experiments embedded in an organization’s referrals process), requesting double the number of referrals increased the number of women referred by 17%-88%. Our intervention provides a versatile, low-cost, and low-risk option for managers and leaders looking to recruit from the full range of talent available to them.

Aneesh Rai (Assistant Professor, University of Maryland, College Park); Erika Kirgios (Assistant Professor, University of Chicago); Brian Lucas (Associate Professor, Cornell University); Katherine Milkman (Professor, University of Pennsylvania)

The Caring Machine: Feeling AI for Customer Care
Journal of Marketing

Feeling skills have always been a human domain, but AI is advancing rapidly.  This article shows how AI can be used to develop feeling intelligence and build empathetic customer relationships.

Ming-Hui Huang & Roland T. Rust

Evolution of Ride Services: From Ride- Hailing to Autonomous Vehicles
Management Science

In recent years the ride service industry has been evolving rapidly, driven by disruptive technologies such as mobile apps, AI, and autonomous vehicles (AVs). While platform-based decentralized ride hailing companies have gained significant market share, vertically-integrated robotaxi services using emerging AVs are starting to enter the market. In this paper, we aim to provide insights about the evolution and the future of ride services studying these two competing business approaches. We find that in many cases in larger markets  the ride-hailing firm surprisingly gains the upper hand in competition, having higher market share and profits as well as lower service delays and higher prices, even if it has a cost disadvantage. Further, entry of the AV firm into a market with a dominant ride-hailing firm may reduce total vehicle supply and increase customer wait costs. We also find that when customers are impatient, the entry of a high cost AV firm may lead to a decrease in social welfare despite introducing competition, suggesting that regulators should be careful about introduction of robotaxi services in a market if they are not sufficiently cost efficient. From a broader perspective, our results demonstrate that platform business models in general may have significant strategic advantages over firms with traditional vertically-integrated models under competition, and platforms' dominance in a market may even result in welfare gains.

Daehoon Noh (Korea University), Tunay I. Tunca (UMD, Smith), Yi Xu (UMD, Smith)

Back to Top