Mack Institute Research Archives

Industrial Policy via Venture Capital

One-third of venture capital in Europe comes from government agencies. We study how government-backed VC, intermediated through private funds, affects firm and market outcomes. Matching EIF portfolio data to firm outcomes, we find that government financing boosts firm growth, especially when targeting young companies, and attracts private co-investment rather than crowding it out. Current policy, however, appears to favor older, later-stage “scale-ups.” We are developing a structural model to evaluate the impact of counterfactual allocation policies on venture capital flows and firm growth across Europe’s diverse financial markets.…Read More

Entrepreneurial Spawning Across Generations: How Organizational Experience Shapes First-Generation and Second-Generation Immigrant Entrepreneurship

This project studies how prior work experience shapes who becomes an entrepreneur, when they found companies, and how successful those ventures become. Focusing on first-generation immigrants, second-generation immigrants, and native-born workers in the US, the study compares careers that begin in large technology firms with those that start in early-stage startups. Using employment histories from Revelio Labs data linked with founding outcomes from Pitchbook & Crunchbase, the project sheds light on how different organizational pathways influence entrepreneurial activity and success across immigrant generations.…Read More

Learning to Learn: Algorithmic Design for Effective Education

Xufei Liu, PhD Candidate in Operations, Information and Decisions, The Wharton School; Gad Allon, Operations, Information and Decisions, The Wharton School; Ken Moon, Operations, Information and Decisions, The Wharton School Abstract: Long-term memory is key to deeper learning, yet students differ drastically in how they acquire and retain knowledge. Current…Read More

Value Creation in Supply Networks

The “value chain smile” posits that firms capture the most value at the upstream (R&D/design) and downstream (marketing/customer-facing) ends of the supply chain, yet empirical evidence remains mixed. We argue that this ambiguity arises because existing studies rely on globally anchored, industry-level measures of upstreamness that obscure firm-specific supply network structure. This project proposes to develop and empirically test a firm-centric, local value chain framework that maps how value is created and captured across a firm’s actual suppliers and customers. Leveraging detailed supply network data and firm-level financial information, we will construct local value chain curves, characterize their shapes, and study how these configurations evolve over time. The analysis will focus on identifying the role of firm-level investments—particularly R&D and marketing—in enabling firms to attain high-value positions without changing their structural network location. By deepening measurement and expanding data coverage, this project aims to reconcile conflicting evidence on the value chain smile and provide a micro-founded understanding of value creation in supply networks.…Read More

Perceptions of Fairness in Algorithmic Decision-Making

In algorithmic decision-making, it is often mathematically impossible to satisfy competing definitions of fairness simultaneously. This impossibility makes assessing stakeholders’ fairness preferences a challenging but crucial exercise. To address this, the researchers developed an interactive tool to elicit fairness preferences by projecting the complex decision space into a simple one-dimensional choice: setting risk thresholds. This design allows participants to directly manipulate algorithm parameters and visualize the resulting tradeoffs between competing fairness metrics. Participants’ decisions enable the researchers to study (1) what Pareto-optimal settings are perceived as fair and (2) whether the design of the elicitation process itself can fundamentally shape how fairness is perceived.…Read More

Improving Decision-Making in Resource Allocation: Evidence from Inpatient Admission Decisions

Routing mechanisms are crucial for efficiently matching specialized resources to customer needs at the lowest cost. Improving allocation to these specialized resources, then, is of first-order concern for many organizations. But when human decision-makers are tasked with allocation in a complex environment, it can be challenging to understand their decision processes and design systems that enhance their decision quality. Leveraging rich data derived from electronic medical records, we explore how, in the context of physicians making routing decisions of patients from the ED to inpatient medical specialties, decision-makers incorporate new information and adapt their decision-making processes.…Read More

Cybersecurity and Gray Hat Hacking

The advance of AI is rapidly increasing cybersecurity vulnerabilties and the risks that organizations face. While working with non-exploiting hackers is recognized as key to strengthening cybersecurity, we still lack a clear understanding of the challenges and dynamics that impact whether such partnerships succeed or breakdown. In this project we aim to identify when, why, and how the collaborations between companies and non-exploiting hackers succeed or fail.…Read More

Ownership, Corporate Ambidexterity, and AI Adoption

The increasing adoption of artificial intelligence (AI) presents firms with an important choice between using these new technologies for short-term optimization (monitoring) or long-term adaptation (innovation). This study examines how corporate ownership structures influence AI implementation patterns. We argue that governance systems that emphasize optimization and rigorous performance metrics may inadvertently trigger the “exploitation trap,” where AI-driven changes undermine the exploratory activities essential for long-term adaptation and competitive advantage. By comparing owners with short-term horizons (e.g., private equity and hedge funds) against long-term-oriented owners (e.g., dedicated institutional investors), we analyze how varying levels of owner commitment and monitoring capacity shape AI adoption patterns, as well as the resulting trade-offs between exploitation and exploration. The findings contribute to the literature on strategy, corporate governance, and technological adoption, suggesting that ownership structure is an important factor in whether and how firms adopt new technologies.…Read More

AI as a Strategic Lens on Entrepreneurial Adaptation and Scaling

Entrepreneurial firms operate in environments characterized by rapid technological change, shifting demand, and heightened uncertainty. While prior research has identified factors associated with startup growth and survival, much of this work relies on static, ex post measures and offers limited insight into how firms adapt strategically in real time. This project proposes artificial intelligence as a strategic lens for studying entrepreneurial adaptation and scaling, examining whether AI-based methods can detect early signals…Read More

From Gatekeeping to Audits: Rethinking Prior Authorization in Health Care

Prior authorization (PA) is widely used to manage utilization of high-cost health services, yet it imposes administrative burdens and can delay care. As generative AI is increasingly deployed to automate both the submission of prior authorization requests by providers and authorization decisions by insurers, raising questions about the effectiveness of gatekeeping as a utilization management strategy in the AI era. This project studies whether an alternative lever—provider-level audits—can reduce administrative burden while preserving oversight for utilization management. We examine a “gold-carding” policy that exempts providers with low historical denial rates from prior authorization while conditioning continued exemption on periodic audits of ordering behavior.…Read More

Human Capital in Startups

I am interested in understanding how high-growth, knowledge-based startups acquire human capital against the backdrop of the challenges and dilemmas that come with rapid organizational expansion. Human capital is a critical resource for these firms, allowing for increased production, knowledge, and resources. However, the dynamic nature of high-growth periods also poses significant challenges. Against the backdrop of a growing firm’s temporal change, these firms face dilemmas in who and when to hire. Thus, I am interested in how growing startups attract, motivate, and retain human capital.…Read More

Improving the Efficiency of Internal Opportunity Markets

Many firms have identified opportunities to innovate, but can’t connect them with potential solutions within other parts of their organization. The purpose of this project is to test the hypothesized reasons why these internal opportunity markets are inefficient and evaluate possible ways to improve them.…Read More

AI, Skills, and Competition

In this project, we aim to present theory and empirical evidence connecting firms’ movements up the AI “stack”: the series of technology innovations leading to AI-enabled prediction and comprised of prior investments in networks, databases, big data, etc.…Read More

Assessing and Improving Emotional Experiences of Hospitalized Patients

In one of our recent studies, we found that nearly 50% of patients who desired emotional support during their hospitalizations reported that they did not always receive it. Not receiving such support is associated with poorer patient-reported care experiences, which research links to issues such as low adherence to treatment plans and ultimately worse clinical outcomes. Our project aims to improve patients’ emotional experiences during hospital stays, and thereby strengthen health care delivery, through organizational intervention. Our proposed intervention, which is based on findings from our prior studies of patient care experiences and co-designed with research site collaborators, consists of a human component paired with a technological (i.e., artificial intelligence-enabled) component. Together, these components are expected to enable assessment of emotional needs and enhanced emotional support at the times and in the forms hospitalized patients desire. We plan to test our intervention via a one-year field experiment with sites affiliated with a large medical center, evaluating the intervention using data from electronic records, surveys, and interviews of patients and hospital staff. Several industry stakeholders, especially hospitals, are expected to be interested in our results because the U.S. Centers for Medicare & Medicaid Services (CMS), as well as other purchasers of health care, adjust hospital payments partially based on hospitals’ patient experience scores.…Read More

Financial Incentives to Adopt Green Technologies

Regulators often seek to spur the adoption of green technologies (such as electric vehicles) using one of two financial subsidies: lowering the upfront cost of buying the technology (such as an electric vehicle subsidy) and lowering the marginal cost of using the technology (such as an electricity tariff subsidy). This project evaluates how the economic characteristics of a setting or technology determine which of these is more effective in terms of tons of CO2 abated per dollar of government expenditure. Between August—December 2025 we implemented a randomized study with 2,100 households in Nakuru County, Kenya to study this problem among induction stoves in Kenya, which abate approximately the same amount of CO2 per year as the switch from a gasoline vehicle to an electric vehicle. We randomly allocated loan access, fixed cost subsidies, and marginal cost subsidies to study the relative impacts on electric stove adoption. We collected more than 5 million measurements of induction stove usage (15-minute data, in Watts, for more than 600 induction stove buyers), more than 100 million temperature measurements to record charcoal cookstove usage (2-minute data, in Celsius, for more than 1,700 charcoal stove users), and more than 20,000 loan instalment payments. Over the next 12 months we will analyze these data to understand the impact of subsidy dollars on fuel…Read More

Is It Better to Pursue Goals in Sequence or in Parallel?

Sophia Pink, PhD Candidate, Operations, Information, and Decisions, The Wharton School; Jose Cervantez, PhD Candidate, Operations, Information, and Decisions, The Wharton School; Katy Milkman, Operations, Information, and Decisions, The Wharton School Abstract: When people want to build multiple habits, is it better to start them all at once or to…Read More

Leadership Composition and Personal Narrative Framing in Female-Focused Ventures: A Hiring Experiment

Tiantian Yang, Management, The Wharton School Abstract: Female-led ventures in female-focused industries (e.g., FemTech) face a unique tension between authenticity and perceived legitimacy in the eyes of potential employees. While identity-based lived experience can signal market insight and mission alignment, it may also conflict with gendered norms about who leads…Read More

The Impact of Private Equity Ownership on Medical Technologies

Private Equity (PE) investment in healthcare is growing rapidly. Because medical-technology firms shape healthcare innovation, spending, and quality—and rely heavily on public insurance reimbursements—PE ownership in this sector could have substantial long-term implications for innovation, costs, and patient outcomes. Yet most existing research on PE in health care focuses on care delivery, despite 63% of PE healthcare investments involving medical devices, pharmaceuticals, and biotechnology. Our study will provide, to our knowledge, the first causal evidence on how PE ownership affects innovation, pricing, financial performance, and product safety among medical-technology firms.…Read More

Green Subsidies with Demand Distortions

Standard Pigouvian theory predicts that externalities should be corrected at the margin. However, demand distortions such as credit constraints or behavioral biases create a wedge between marginal benefit and marginal cost. While these distortions can lower aggregate abatement, they can increase the efficiency of green subsidy spending. In theory, this happens through two channels: by shifting the marginal adopter toward higher private and social benefits and by increasing demand elasticity. We test these predictions by cross-randomizing fixed cost subsidies, marginal cost subsidies, and loan access for an induction stove among 2,134 charcoal users in Kenya. Marginal cost subsidies that lower electricity costs by up to 75% have a precise zero effect on both adoption and usage. Fixed cost subsidies abate at just US$13 per ton of CO2e, and demand distortions are responsible for making this cost low: reducing credit constraints raises abatement costs to US$22 per tCO2e. These efficiency gains operate through the two hypothesized channels: demand distortions increase the marginal positive externality by 19% and lower the subsidy cost per marginal abatement by 30%. We estimate the model to generate counterfactual simulations and find that, without any distortions, abatement costs would reach US$122 per tCO2e. The social welfare gain would be US$3.1 per subsidy dollar; demand distortions increase this to US$20. These results suggest that contexts with larger demand distortions, including many low- and middle-income economies, could generate some of the lowest-cost opportunities on the abatement cost curve.…Read More

Research Spotlight: Hamsa Bastani and Angel Tsai-Hsuan Chung On More Effective Classroom AI

Headshots of two people, one with long dark hair wearing a dark jacket and blue top, and the other with long dark hair wearing a dark blouse.

For many students, asking ChatGPT for homework help has replaced raising a hand in class or going to office hours. As AI becomes a default classroom tutor, educators are grappling with a new question: how do you design these tools so they actually support learning? A new paper from Angel Tsai-Hsuan Chung (Wharton, PhD…Read More