Strategies for Innovating Archives

Outlier Neglect: A Decision-Making Bias with Implications for Hiring, Investment, and Consumer Choices

We propose and test a novel decision-making bias called “outlier neglect.” In general, when evaluating people, places, and opportunities with many features, people focus on the average of those features. For example, when hiring a team, people want the average performance of the team to be high, so they try to hire individuals who perform well on average. But in many cases, the relevant metric is not the average, but the best – for example, when a pharmaceutical company tests different types of malaria drugs, their success depends on the best-performing drug (not the average) because they can scale up the best and ignore lesser performers. We propose that evaluators neglect the importance of outliers in such cases and instead focus on portfolio averages. In some cases, this leads to suboptimal outcomes (e.g. in the drug scenario above, or it may be better to hire someone to join a team who is amazing at one specialized task than someone who is higher on average). We test this bias and show that across many contexts – including personnel selection, creative idea generation, consumer decisions, and investment strategy – people neglect outliers in favor of the average, leading to suboptimal decisions.…Read More

Business Model Innovation for Renewables

Consumers who want access to renewable energy have two main options: install renewable energy generation equipment “behind” the electrical meter (e.g., solar panels on the roof) or buy energy from a utility company, which would then source energy from generation companies. The first approach has obvious diseconomies of scale. It is only available to homeowners, while the second approach requires over-reliance on utility companies, which may not contract with renewable suppliers or may offer an expensive mix of renewable and nonrenewable energy. We study an alternative innovative business model, “community solar,” whereby consumers subscribe to own a portion of the energy generated by a large solar plant. We partner with Origo Energy, a Brazilian company that pioneered this model in South America, and we analyze the behavior of consumers who switch from the traditional business model to Origo’s subscription to understand boundary conditions for community solar.…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

Strategic Openness of the Innovation Portfolio

We investigate the strategic openness of firms’ innovation portfolios, focusing on the determinants and implications of disclosure strategies for diverse innovation assets, particularly in the context of artificial intelligence (AI). While firms traditionally protect innovation through patents and secrecy, open innovation frameworks have gained prominence as firms increasingly leverage external sources of innovation. This research seeks to bridge the gap between the innovation and open-source literatures by exploring how firms disclose and utilize various innovation assets—such as patents, academic publications, and open-source code—in response to their R&D strategies, market environments, and policy pressures.…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

Electric Vehicle (EV) Fleet and Charging Infrastructure: Decision-Making by Drivers in the Gig Economy

The rapid integration of electric vehicles (EVs) into gig economy platforms like Uber and Lyft presents unique challenges, particularly in driver decision-making, earnings, and operational efficiency. This study explores how EV-specific constraints, such as charging infrastructure and fleet size, influence the behavior of gig economy drivers. We analyze the role of algorithms in shaping driver earnings, pricing, and trip allocations, addressing concerns about transparency, bias, and geographic disparities. Using a proprietary dataset combined with public data on charging station locations, our research employs descriptive analysis, regression models, and simulation to examine the impact of charging accessibility on driver efficiency and service levels. The findings aim to inform algorithmic design improvements and policy interventions, fostering more equitable and efficient EV integration in gig platforms.…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

How Posting on Social Media Impacts Goal Persistence

Companies often encourage their customers to share their progress toward personal goals, such as their fitness journey, on social media. In this research, we investigate how doing so impacts motivation. While documenting goal pursuit online may increase motivation through immediate social rewards (likes, comments), accountability, and social support, it could also have no effect of even backfire—especially if people focus on social media engagement rather than the underlying goal, or become discouraged by lower-than-expected feedback. We test these possibilities through a preregistered field experiment (N = 500) in which participants are assigned to either document their goal progress by posting on Instagram or by completing a private survey. Over a three-month period, we measure their gym attendance and social media engagement. The findings of this paper would provide theoretical insight into how social media interacts with goal pursuit and potentially offer practical implications for designing scalable, low-cost interventions to promote goal achievement.…Read More

Private Equity, Corporate Acquirers, and Product Innovation in Technology Acquisitions

Private equity has become an increasingly active player in technology acquisitions in recent years, yet most prior scholarship has focused on the effects of corporate acquirer ownership on performance and innovation outcomes. As a result, research provides little guidance on how firms should choose between the two acquirer types. To remedy this gap, I construct a panel data set of acquisitions in the chemical, biopharmaceutical, and medical device industries between 1990 and 2019, tracked yearly through 2022. Then, I examine how private equity and corporate acquirers differentially affect product innovation at acquired technology targets using USPTO trademark, FDA orange book, and hand-collected new product introduction data. Our results illuminate the opportunities and tradeoffs facing managers at technology companies in choosing between private equity and corporate acquirers.…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

Platform Bundling and Competition in the Video Streaming Market

This project investigates the welfare impact of bundling between platforms affects in the video streaming market. Platform bundling has become increasingly common in recent years. For example, comcast offers an ad-supported bundle of Netflix, Apple TV, and Peacock for just $10 per month. Similarly, a bundle of Hulu, Disney Plus, and Max allows consumers to subscribe all three with a nearly 40% discount. However, the effects of such bundling on consumers remain unclear. Existing literature shows that when competing firms offer mixed bundles of their own products, bundling enables more efficient price discrimination, which harms consumers; but also intensifies competition, which benefits consumers. The streaming market presents a unique and intriguing case because these bundles often include platforms with distinct ownership. This separate ownership of bundling platforms creates potential inefficiencies, as platforms may “freeride” own their bundling partners’ content investments while reducing their own. In this project, I will develop a structural model and apply data-driven methods to quantify the impact of mixed bundling between independently owned platforms on competition and consumer welfare.…Read More

Search Strategies in Artificial Intelligence Innovation: Balancing Competition and Commercialization

This study explores how firms’ search strategies shape innovation outcomes in the context of emerging general-purpose technologies (GPTs), with a focus on artificial intelligence (AI). GPTs, defined by their broad applicability and undefined market needs, challenge traditional search theories by requiring firms to balance advancing technological capabilities (supply-side innovation) with identifying practical use cases (demand-side innovation).…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

Consumer Behavior and Cryptocurrency Confidence

In our endeavor to grasp the driving forces behind cryptocurrency prices, we have developed the Consumer Cryptocurrency Confidence Index (c3i), derived from a set of questions asked monthly to consumers across the United States. Our analysis has uncovered several initial results and pointed to an extensive, exciting research program on consumer behavior that shapes the cryptocurrency markets. Firstly, we are rigorously validating to what extent the c3i can accurately predict changes in cryptocurrency prices as a leading indicator by exploring whether this relationship is merely correlation or potentially causal. Furthermore, we are investigating if consumer characteristics such as age, gender, and political leanings can enhance the accuracy of our index in predicting cryptocurrency prices. We are also examining if the relationship observed between c3i and cryptocurrency prices extends to broader stock market indices like the S&P…Read More

E-Governance and Digital Infrastructure in India

Philip Nichols, Legal Studies & Business Ethics, The Wharton School Abstract: An in depth, qualitative and descriptive examination of India’s digital infrastructure and the e-governance functions it enables. The research should produce (1) a descriptive white paper, with an intended audience of (a) policymakers in other emerging economies, (b) scholars…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

Strategic bootstrapping and startup experimentation

New ventures are grappling with the rising costs of capital (both debt and equity). As a result, investors of high-growth, technology-based startups are shifting focus to companies that can generate immediate cash. That is, investors are prioritizing cash flow positivity over growth. A recent report has documented that high-growth, technology-driven startups that are bootstrapped outperformed those that are VC-backed on both profitability and growth. Yet, the reason for this performance differential is poorly understood given that bootstrapping is an underexplored phenomenon due to the unavailability of large datasets to answer important questions. Through this study, we first seek to build a large, novel dataset that can facilitate research on bootstrapping. In addition, we immediately respond to two important questions pertaining to why bootstrapped startups may be better able to manage the balance between cash flow positivity and growth…Read More

How vs. How and Why Nudges: When Stating Your Case Isn’t as Effective

Marketers and policymakers often use nudges to help consumers make welfare-increasing decisions, such as encouraging physically and mentally healthy choices. This research explores when one nudge is more effective than another. More specifically, it demonstrates nudges focusing on telling consumers how to do something are more effective than nudges telling consumers how and why to do something. This is because listing the reasons why a consumer should do something creates the potential for a mismatch between the listed reasons and a consumer’s personal reasons for considering engaging in a behavior. This mismatch, in turn, leads consumers to believe said behavior will benefit their quality of life less than they might have believed otherwise. These findings…Read More

Hiring Dilemmas: Assembling Human Capital in High-Growth Startups

How do 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 startups, 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. In my dissertation, am interested in understanding how growing startups attract, motivate, and retain human capital.…Read More

Enabling Personalized Learning in Large Language Models via Reinforcement Learning

This project combines GPT-4 and reinforcement learning to develop a personalized learning platform for an introductory Python programming class. In collaboration with the National Taiwan University, this project will deploy and conduct a randomized control trial (RCT) to understand how to effectively use generative AI to improve student’s learning outcomes and skill development…Read More