Consumer Preferences and Firm Technology Choice

Published Research

Advances in technology change the way consumers search and shop for products. Emerging is the trend of home-shopping devices such as Amazon’s Alexa and Google Home, which allow consumers to search or order products. We investigate how consumer brand and technology preferences may interact with the functionalities of technology-enabled shopping (TES) devices to determine the channel structure and market competition.Read More

Opportunities and Risks in Belief Distribution Elicitations

Funded Research Proposal

Researchers and practitioners have increasingly embraced the novel practice of eliciting the entire belief distributions, as it provides a more thorough understanding of stakeholders’ beliefs. My recent paper (co-authored with Professor Joe Simmons) suggests that constructing belief distributions can sometimes inadvertently exacerbate people’s overconfidence in their predictions.Read More

Are ETFs better than Mutual Funds?

Working Papers

I study investors’ trade-off between ETFs and open-ended mutual funds in the presence of idiosyncratic liquidity risk and aggregate uncertainty. Based on a portfolio choice model, I show that ETFs and mutual funds provide liquidity at different maturities.Read More

Learning by Monitoring: The Impact of Monitoring on VC Re-Investment Performance

Funded Research Proposal

This project aims to investigate the impact of monitoring on VC reinvestment performance. Using novel data sources, I construct a proxy for monitoring and test the causal relationship between monitoring and investment outcomes. To address the endogeneity issue regarding monitoring, I use the traveling population as an instrumental variable for VC’s monitoring intensity.Read More

Leveraging Analytics to Maximize Innovation

Funded Research Proposal

Academics and practitioners will log onto an intuitive user interface and type in features of their own company (e.g., its size and industry). They will immediately be greeted with an “instant meta-analysis” that summarizes decades of academic findings related to the most important predictors of creativity and innovation in organizations.Read More

Decision-Aware Learning for Global Health Supply Chains

Funded Research Proposal

Tsai-Hsuan (Angel) Chung, Phd Candidate at the Wharton School; Osbert Bastani, Penn School of Engineering; Francis Smart, PhD Candidate at the University of Montana; Jatu Abdulai*; Patrick Bayoh*; Musa Komeh*; Vahid Rostami* Abstract: This proposal aims to develop and deploy novel methods that integrate machine learning and optimization to improveRead More

The Impact of Healthcare Price Transparency Rules

Funded Research Proposal

The US government recently required healthcare price transparency from hospitals and insurers in an attempt to control spiraling healthcare costs. On the one hand, price transparency and online search tools have been very effective in increasing competition for other products in the e-commerce space. On the other hand, healthcare is a complex product, often bought through insurance, which makes it unclear how much transparency will affect realized prices. Further, public disclosure of prices might allow healthcare providers to better negotiate with insurance companies, which might even lead to an increase in healthcare prices. Our project uses a large-scale nationwide dataset of healthcare insurance claims to analyze the potential benefits and impact of these regulations, and inform policymakers and the public about the values and risks of these reforms.Read More

Resetting the Clock: Dynamic Goal Setting Using Behavior Tracking Technology

Funded Research Proposal

Can companies providing goal-tracking technology innovate their products to better enable consumers to keep going when they inevitably fail (i.e., skip a workout or overeat calories)? Our research aims to fill this gap by testing the effectiveness of one type of goal tracking design: dynamic goal setting. Most traditional goal tracking apps focus on static goals – goals where the consumer aims to complete the same amount of goal behavior each day (i.e., working out 30 minutes a day or walking 10,000 steps a day). However, we suggest behavior tracking apps that use AI technology to vary the amount of goal behavior the consumers engage in from day to day (i.e., work out an average of 30 minutes a day, with some days being 15, some days 45, etc.) will be more effective, a type of goal tracking we term dynamic goal setting.Read More

Innovating Shift Work Design to Incorporate Heterogeneous Worker Preferences

Funded Research Proposal

Shifts are the dominant way to work in many contexts requiring 24/7 coverage, including call centers, police departments, and hospitals. While the detriments of shift work are well-documented both at the individual and organizational levels, its deployment is often unavoidable given round-the-clock staffing needs. We explore a potential organizational lever—incorporating heterogeneous preferences over shift design—to mitigate ramifications of shift work in the context of acute care bedside nurses. Using survey, administrative, and shift data, we examine whether and the extent to which individual choice over dimensions of their shifts mitigates the impact of shift work on work (dis)satisfaction and turnover of nurses.Read More

A Swing and a Hit: Optimal Disclosure Policy for Swing Pricing in Mutual Funds

Funded Research Proposal

What is the optimal disclosure policy for swing pricing by open-end mutual funds? Specifically, which disclosure rule, with respect to the swing factor and – thresholds, minimizes run risk in open-end mutual funds? Does the disclosure policy rule that is optimal from a financial stability perspective also preclude the possibility of front running by fund investors? Answering this question will likely also require a model of the optimal swing factor. By addressing this critical gap in the literature, my research aims to contribute to inform policy decisions regarding the proposed SEC rule.Read More

Private Equity and Productivity in US Healthcare

Funded Research Proposal

Private equity (PE) investment in US healthcare has increased dramatically in recent years. On one hand, widespread PE participation may be one avenue to stem rising costs and increase productivity, which have been elusive objects in US healthcare. Research from other sectors has shown that PE firms apply best-in-class management practices to improve productivity and firm value. On the other hand, high powered financial incentives for PE managers may create conflicts with the interests of consumers and of taxpayers, who finance about 45% of healthcare spending. This project aims to study how PE investment affects quality and productivity of healthcare delivery in the US, issues of first order importance for both policy and business. We have assembled the most comprehensive set of data resources used to study this question – confidential micro data on PE investments in healthcare firms, and national data on services, spending, and outcomes for about 30 million Medicare beneficiaries over 2000–17. We will deploy a differences-in differences research design, exploiting variation in the timing of PE acquisitions across firms over this long panel. We will examine effects on 1) growth 2) operating efficiency, and 3) quality of care delivered, over the short and long-run.Read More

Algorithmic Pricing and Transparency in the Gig Economy

Funded Research Proposal

Algorithms control pricing and match customers and workers in the gig economy. However, algorithms face several critiques: they lack transparency, can be biased, and can be inefficient. We empirically analyze these issues and show that algorithms lose efficiency from two sources: competition between platforms and misaligned worker incentives. We model workers’ strategic responses to variation in pricing and estimate counterfactuals on the effects of minimum wage and transparent pricing policies.Read More

Consumer Cryptocurrency Confidence Index (CCCI or C3i)

Funded Research Proposal

The Consumer Cryptoconfidence Index offers the first ongoing, consumer-centered data source specifically intended to capture sentiment related to this market exchange tool. Offering both a novel “snapshot” understanding of the typical consumer’s perception of and interaction with cryptocurrency as well as data that may be fruitfully connected to other marketplace changes, the C3i index will allow us to build our knowledge as the cryptocurrency market evolves. By developing this understanding, we hope to support decision-making among consumers, regulators, investors, and entrepreneurs, while also laying the groundwork for ongoing consumer-centered research in this domain.Read More

AI Decision Aids and Metacognition

Funded Research Proposal

The proposed research focuses on how people use and perceive innovative decision aids, for example, AI tools like ChatGPT. Individuals and organizations are increasingly outsourcing part of their labor or decision-making process to these tools. The proposed research aims to investigate the perception around using AI decision aids, both in terms of its impact on individuals’ metacognitive assessments and observers’ social judgments. Read More

Innovate or Excavate? A Raw Resource View of Induced Innovation

Funded Research Proposal

This project aims to quantify the effect of innovation on commodity price reversions. Commodity prices tend to be stationary with occasional deviations and then revert to their mean prices. There are two big forces behind this reversion. First, there are firms that invest in research that allows them to substitute away from the expensive commodity. Secondly, the commodity producers will expand extraction capacity in response to increased profitability. The former affects the demand side and the latter the supply side. The goal of this project is to estimate the magnitude of the effect of price reversion due to innovation.Read More

Thinking Structurally: How Structural Attributions Impact Support For Solutions and Willingness to Take Collective Action

Funded Research Proposal

Though nearly everyone recognizes the importance of addressing issues like climate change, gender bias, and police brutality, we face bitter and debilitating conflict with respect to the causes of these challenges. In this project, we study the consequences of “structural attributions” for social problems — that is, believing a problem was caused by policies, infrastructure, and/or institutions.Read More

Upward Digitization and Downward Novelty in Book Industry

Funded Research Proposal

Digitization has fundamentally changed how content is produced, distributed, and consumed in cultural industries where novelty is an essential and necessary ingredient for success. Using the book publishing industry as a setting, we investigate whether and how digitization impacts content novelty.Read More

The Prevalence and Consequences of Algorithms in Hiring: A Field Experiment

Funded Research Proposal

We conduct an audit study to measure the prevalence and impact of AI hiring applications on job applicants. We apply to thousands of jobs, treating half of our application resumes by embedding the job posting within the resume such that machines have access to the job posting text when screening candidates, but human evaluators would not. We can then evaluate if algorithmic resume screening is more likely to select resumes that are a closer match to postings. By also varying applicant race and gender, we can determine if these algorithmic selection algorithms have a differential impact on candidates from underrepresented backgrounds.Read More

Instant Payment Systems and Competition for Deposits

Funded Research Proposal

How do instant payment technologies impact financial intermediation? I use municipality-level data on the development of Pix in Brazil and combine it with branch-level banking data to provide evidence that instant payments positively impact deposit market competition—Pix usage increases checking, saving, and time deposits of small banks relative to large banks.Read More

Pivoting and Experimentation in Lean Startups

Funded Research Proposal

While recent scholarly and practitioner research has stressed the importance of learning in entrepreneurial settings, little scholarly work has formally examined the mechanisms through which learning drives behavior in those settings. Specifically, we investigate how an active learning process based on evaluating performance relative to an aspiration drives the pivoting and experimentation behavior of startups in environments with high degrees of uncertainty and potentially intense selection pressures.Read More