Innovation Opportunities and Risks Archives

Grid-Scale Mobile Battery Energy Storage Systems

Grid-scale electricity storage technologies play a vital role in balancing electricity supply and demand, particularly as renewable energy sources like wind and solar introduce greater variability into power systems. Lithium-ion batteries, accounting for 90% of U.S. electricity storage capacity, are widely regarded as essential to the clean energy transition. By storing excess electricity during periods of low demand, and thus low prices, and releasing it when demand, and thus price, is high, storage technologies smooth fluctuations in generation and earn significant revenues from arbitrage. Battery operators strategically locate systems in areas with high nodal price variability, but current practices often fail to adapt to changing market conditions, risking inefficient investments with diminishing price spread at selected locations.

Mobile Energy Storage Systems (MESS) present a transformative innovation, enabling both temporal and geographic flexibility in energy storage. Unlike existing Stationary Energy Storage Systems, MESS can be relocated to provide storage services at different points in the grid as market dynamics evolve with rapid addition of transmission and renewable generation capacity. Although MESS technologies currently find niche applications, such as disaster relief, advancements in material technology and declining battery costs make utility-scale adoption plausible. This study addresses a critical gap by modeling MESS fleet operations, analyzing their feasibility, and comparing their financial performance against stationary systems in renewable-rich grids. Our findings aim to guide developers and grid operators in leveraging MESS for enhanced energy flexibility and resilience in renewable-rich grids.…Read More

Do We Write What AI Tells Us To? LLMs as Persuasive Agents

Consumers are increasingly turning to large language models (LLMs) as an aid to everyday writing (i.e., email, text). While it is clear that LLMs can enhance the grammatical and syntactical structure of written communication, might they also lead people to communicate things that depart from their original intentions? We explored this question through an experimental paradigm in which participants were first asked to create an opinionated message, then viewed a suggested revision generated by the Chat-GPT 4 LLM that was either more positive or negative than the original. Results of our experiment reveal that LLMs do exert a substantial influence on written communication, but this effect has important moderators. Notably, participants who initially conveyed negative (vs. positive) opinions were less resistant to persuasion from LLMs, and text revisions that made a message more positive (vs. negative) were embraced more readily.…Read More

Effects of Prior Authorization on Medicaid Prescription Drug Access

Prescription drug spending has increased rapidly over the last two decades. Prior authorization represents an innovative strategy in Medicaid’s prescription drug benefit management, using administrative tools to influence prescribing behaviors and control expenses. State Medicaid programs have widely adopted prior authorization policies to curb spending and enhance the targeting of treatments. Despite the importance of these policies for Medicaid, there is limited evidence of their impact on prescription drug access and patient outcomes. In this project, we use a novel regression-discontinuity design to study the consequences of prior authorization. We study the impact of these policies on the prescribing of drugs covered by prior authorization and substitution to other drugs as well as heterogeneous impacts across geographic areas and socio-demographic characteristics. We also assess the importance of different design features of these policies and their impact on inappropriate and appropriate prescribing.…Read More

Scientific Malpractice in Alzheimer’s Research: Systematic Evidence and Impacts on Pharmaceutical Firms

Science forms the bedrock of industrial innovation, and yet the integrity of the scientific enterprise has recently been questioned across multiple fields by high-profile scandals and replication crises. How common is scientific malpractice, and what are its costs for firms that rely on scientific research to guide their innovation investments? Using advanced AI and manual validation, we estimate the prevalence and different types of data malpractice in Alzheimer’s research, both within and across papers, from 1980 to 2020. We focus on inappropriate image duplications, an objectively observed form of data malpractice widespread in a field where experimental data are often presented as figures. Preliminary findings suggest that, on average, 1.7% of all peer-reviewed papers present inappropriately duplicated images, a number that has steadily increased over time. The incidence is greater for research done in universities (relative to corporate and clinical settings), employing animal and molecular methods (relative to human subject methods), and originating from China. Our current work investigates the costs of scientific malpractice for pharmaceutical firms that base their investments on publicly available science. By tracking citations from firm patents to papers with duplicated images, we plan to estimate how much attention and resources are distorted away from findings with clinical applications and how much this may contribute to explaining the slow progress in finding a cure for Alzheimer’s disease.…Read More

TwoMinds: Understanding How Humans and AI Systems Achieve Mutual Understanding

As artificial intelligence becomes increasingly integrated into daily life, understanding how humans and machines achieve mutual understanding has become a crucial scientific challenge. Our research addresses this challenge by developing a digital web platform that studies how humans and AI systems communicate and build shared understanding in real-time. While machines can now model our preferences and predict our behavior, they struggle to genuinely understand human meaning and intention. Our platform will generate novel data about human-AI interaction, with direct implications for improving AI systems and enhancing human-machine collaboration. By integrating insights from psychology, computer science, computational linguistics, and organizational behavior, our work builds an essential bridge between human and artificial minds—a critical need for organizations seeking to effectively deploy AI technology.…Read More

Inorganic Scaling Strategies of Adolescent Technology Ventures

This study will explore technology-oriented startups (such as deeptech) scale through inorganic modes such as ecosystem partnerships and alliances. We attempt to understand how different antecedents such as founding and scaling characteristics affect the timing of when startups engage in such modes.…Read More

Product Innovation, Market Sentiment, and Resource Allocation

Our research aims to deepen the understanding of (i) how financial markets value product innovation across various firm types, industries, and economic conditions, and (ii) how market sentiment influences the private economic value of product innovation, its impact on firms’ and competitors’ profitability, and the resulting resource reallocation—such as capital, labor, and R&D—both within and across firms.…Read More

Exploring the Role of Artificial Intelligence in Turbocharging Innovation in the Generative AI Era

rtificial intelligence (AI) has become a transformative force in fostering innovation and productivity. In our prior research (Wu et al. 2020; Wu et al. 2019), we demonstrated that AI-driven analytics can significantly enhance innovation by combining existing technologies in novel ways and refining existing technologies. With the advent of generative AI and other advanced algorithms, firms are discovering unprecedented opportunities to innovate and create new products. Yet some firms are vastly successful at using AI to innovate while the majority fails.…Read More

Consumer Crypto Confidence Index

We use monthly surveys, each based on the same five primary questions, to construct the monthly Consumer Crypto Confidence Index. We also collect demographic data, political leanings, etc., on each survey subject for each monthly survey. So far, we have collected two-years’ worth of the survey data, and also the corresponding bitcoin price data. The primary objective here is to track how consumer confidence in crypto currency changes over time.…Read More

How Do Financial Market Frictions Affect the Efficiency of Carbon Offset Markets?

High-income regions like North America and Europe currently generate most of the world’s emissions. However, most high-income countries have in recent years passed national or sub-national legislation to lower emissions, such as carbon taxes, emissions trading schemes, and clean subsidies. Add to this that Africa’s population is expected to triple, and the result is that by 2050 Africa is expected to emit twice as much CO2 per year as North America or Europe.…Read More

Silent Discrimination: How AI Watermarking Systems Create Digital Accents in Non-Native English Writing

As language model providers develop watermarking techniques to identify AI-generated content, important questions arise about their potential impact on non-native English speakers in academic settings. This study examines how proposed watermarking systems might create “digital accents”—systematic biases that could flag legitimate writing assistance used by non-native English speakers as potential AI-generated content. Through analysis of 1,500 TOEFL essays and three distinct levels of AI assistance, we demonstrate how current watermarking techniques could disproportionately impact international students who use AI tools for language learning and writing improvement. We propose a novel detection framework that reduces potential false positive rates by integrating conformal outlier detection techniques in statistics while maintaining detection accura…Read More

When Reminders Backfire: How Thinking More (vs. Less) Frequently About an Experience Affects Excitement Over Time

Thinking about a future positive experience can be enjoyable and exciting. However, we suggest that thinking too much about a future positive experience can backfire. In particular, we investigate whether people would become less excited initially when they are reminded more (vs. less often) about a future positive experience. We suggest that people can adapt to the thought of a future experience and thus would become less excited about the experience. We examine how people’s anticipatory enjoyment changes over time and how many (vs. few) reminders affect this trajectory. Further, we will also explore the downstream consequences of many (vs. few) reminders, such as a reduction in enjoyment of the planned activity and a greater likelihood of changing the planned activity.…Read More

Checking Current Status More Frequently Decreases Satisfaction

From the time remaining for an Uber’s arrival to the number of likes on an Instagram post, new technologies have made it easier to check the status of desired outcomes than ever before. Smartphones and other devices enable consumers to receive updates, such as a delivery driver’s status, in real-time. But is such frequent checking always beneficial? This research explores a potential downside to checking the status of desired outcomes more…Read More

Wisdom of the Algorithmic Crowd

Ensemble models, a class of machine learning algorithms that combine the predictions of multiple algorithms to form more accurate predictions, are widely used in marketing applications. This research explores ways to enhance the adoption and perceived accuracy of these models. Thirteen experimental studies (ten in the main paper and three in the Web Appendix) collectively demonstrate that consumers have an intuitive grasp of the “wisdom of the crowd,” and they perceive machine ensembles as more accurate than single algorithms. Framing algorithms as a collection of models rather than a single algorithm boosts perc…Read More

The Efficiency of Dynamic Electricity Prices

The marginal cost of electricity fluctuates hour-by-hour, yet retail customers typically face flat prices. Using data from all seven US wholesale markets and a new method to evaluate alternative rates set in advance that accounts for equilibrium price effects, we estimate efficiency gains from time-varying price schedules that better align price with cost. We have three main results. First, time-of-use rates and critical-peak pricing, the two most common time-varying rate plans, each correct about 10% of mispricing. Second, complex rate structures based on historical prices often backfire. Third, real-time pricing with price ceilings can capture most potential efficiency gains while limiting customer risk.…Read More

High-Flying Analytics: Harnessing Wearable Sensors and AI to Safeguard Military Aviators

For military aviators, functioning without fail within a high-stress work environment is a necessity. In order to complete critical missions, they make split-second decisions while piloting 44,000 lbs of hurtling machinery accelerating at up to 9G’s in high-altitude conditions. For less experienced pilots, managing the associated physical and mental fatigue is an integral and challenging component of executing flights safely and well. We collaborate with a pioneering company that innovatively outfits aviators at 22 USAF bases with wearable sensors that record both the physical stresses of sorties (flights) and the biophysical states and reactions of pilots in real time. Then, we develop analytical methods to make timely and accurate use of such novel wearable…Read More

Can Artificial Intelligence Mitigate Inventor Productivity Decline after Co-Inventor Premature Death?

Although it is well documented that disruptive events, such as an inventor’s premature death, cause a large and persistent decline in their co-inventor’s innovation performance, strategies to mitigate these negative effects remain unexplored. This project aims to understand how an inventor’s skill and proficiency in artificial intelligence (AI) could counteract the productivity decline resulting from a co-inventor’s demise. We intend to first identify the specific challenges facing inventors in staying innovative after the unexpected death of their close collaborators. Furthermore…Read More

Perceived Momentum in Media Consumption: Optimizing Binge-Watching

Every day, millions of people engage in the popular behavior called “binge-watching”, a type of media consumption where multiple episodes of the same TV show are seen in a row (Schweidel and Moe, 2016). Given how popular “binge-watching” is and how much streaming platforms are relying on it to recommend and create new content to stream, it is very important to understand whether consumers are satisfied by their binging sessions and whether recommendation systems are well calibrated in suggesting binge-worthy content that will maximize this satisfaction.…Read More

A Second Opinion: Impact of Generative AI on Information Acquisition Processes, Performance, and Service Quality

Since ChatGPT’s launch in November 2022, a surge of studies has underscored generative AI’s potential across a wide range of applications, including improving entrepreneurial performance, spurring innovation, and even providing more ethical advice. Less attention has been garnered about how AI impacts the efficiency of a decision-maker’s information search process. In the context of health care, medical providers review existing patient information (i.e., their medical history) and then must ask a series of questions to the patient or run diagnostic tests to make their diagnosis. While there is inherent uncertainty, the provider faces a trade-off between acquiring additional information from the patient to increase certainty over a diagnosis and…Read More

Career Effects of Venture Capital on High-Technology Startup Employees

Venture capital (VC) significantly contributes to job creation and innovation in high-tech startups, with around 50% of tech companies reaching IPOs in the past three decades having VC backing. While the benefits of VC on startups and regional economies are well-documented, its impact on individual career trajectories remains underexplored. This research proposal investigates how VC financing influences employee turnover and career progression within startups. VC investment can lead to higher wages and faster promotions, enhancing employee value. However…Read More