New Tools, New Rules: A Practical Guide to Effective and Responsible GenAI Use for Surveys and Experiments Research
Generative Artificial Intelligence (GenAI) tools based on Large Language Models (LLMs) are quickly reshaping how researchers conduct surveys and experiments. From reviewing the literature and designing instruments, to administering studies, coding data, and interpreting results, these tools offer substantial opportunities to improve research productivity and advance methodology. Yet with this potential comes a critical challenge: researchers often use these systems without fully understanding how they work.
Taking A Stand While Abroad? Towards A Theory of MNCs' Sociopolitical Activism in Host Countries
With multinational corporations (MNCs) increasingly taking public stances on sociopolitical issues such as immigration, LGBTQ+ rights, and racism, it is imperative that International Business (IB) research keeps pace with normative societal debates. In this paper, we introduce the concept of corporate sociopolitical activism (SPA) to the IB literature and develop theory on why MNCs consistently or inconsistently engage in SPA in response to the same issue in their home country and a host country.
Should the Government Be Paying Investment Fees on $3 Trillion of Tax-Deferred Retirement Assets?
Under standard assumptions, individuals and the government are indifferent between traditional tax-deferred retirement accounts and “front-loaded” (Roth) accounts. Adding investment fees to this benchmark, individuals are still indifferent but the government is not. We show that under weak conditions firms charge equal percent fees under both systems, yielding higher dollar fees under Traditional. We estimate that tax deferral increases demand for asset management services by $3.8 trillion, costing the government $23.4 billion in annual fees.
What Makes Consumption Experiences Feel “Special”? A Multimethod Integrative Analysis
This paper addresses a simple theoretical question of high substantive relevance: What makes a consumption experience special in a consumer’s mind?
Wikipedia Contributions in the Wake of ChatGPT
How has Wikipedia activity changed for articles with content similar to ChatGPT following its introduction? We estimate the impact using differences-in-differences models, with dissimilar Wikipedia articles as a baseline for comparison, to examine how changes in voluntary knowledge contributions and information-seeking behavior differ by article content. Our analysis reveals that newly created, popular articles whose content overlaps with ChatGPT 3.5 saw a greater decline in editing and viewership after the November 2022 launch of ChatGPT than dissimilar articles did.
The welfare impact of recommendation algorithms
In this letter, we summarize our recent work on the welfare impact of recommendation algorithms and propose questions for further study. We model recommendation algorithms as an information structure, which shapes how a third party takes actions that affect the welfare of different individuals in a population. Each recommendation algorithm thus induces a welfare profile, describing the expected payoffs of different individuals when the third party takes actions following the algorithm.
Measuring population heterogeneity requires heterogeneous populations
Any judgment about population heterogeneity depends on the definition of the sampling frame (1). In a recent paper, Holzmeister et al. (2) (HJBK hereafter) compare different sources of heterogeneity to population heterogeneity. They find that population heterogeneity is much smaller compared to design and analytic heterogeneity as a source of variation in effect sizes.
Foreign Direct Investment and Development
Multinational enterprises are at the centre of policy debates in low- and middle-income countries. As some of the most productive and innovative firms in the world, which are at the core of global supply chains, multinational enterprises (MNEs) can accelerate development in the countries hosting them, both directly with their presence, and indirectly through linkages to local economic actors.
VoxDevLit on Foreign Direct Investment
Multinational enterprises are at the centre of policy debates in low- and middle-income countries. As some of the most productive and innovative firms in the world, which are at the core of global supply chains, multinational enterprises (MNEs) can accelerate development in the countries hosting them, both directly with their presence, and indirectly through linkages to local economic actors.
Better Innovation for a Better World
We aim to stimulate discussion on how innovation research within marketing can use a better world (BW) perspective to help innovation become a driver of positive change in the world. In this "Challenging the Boundaries" series paper, we hope to provide purposeful research opportunities for scholars seeking to bridge innovation research with the BW movement. We frame our discussion with four areas of innovation research in marketing that are particularly relevant to BW objectives.
The Cost of PAC Funding: Evidence on PAC Funding Refusal Across Candidate Race and Gender
Research on campaign finance suggests that Americans prefer candidates that are not funded by Political Action Committees (PACs). However, prior research has not examined how perceptions of a candidate who is PAC-funded vs. PAC free might differ for racial minority and female candidates compared to White, male candidates. Using experimental vignettes, we test the causal impact of PAC funding, race, and gender on voter perceptions of the candidate.
Personalized Game Design for Improved User Retention and Monetization in Freemium Games
One of the most crucial aspects and significant levers that gaming companies possess in designing digital games is setting the level of difficulty, which essentially regulates the user’s ability to progress within the game. This aspect is particularly significant in free-to-play (F2P) games, where the paid version often aims to enhance the player’s experience and to facilitate faster progression.
Using natural language processing to analyse text data in behavioural science
Language is a uniquely human trait at the core of human interactions. The language people use often reflects their personality, intentions and state of mind. With the integration of the Internet and social media into everyday life, much of human communication is documented as written text. These online forms of communication (for example, blogs, reviews, social media posts and emails) provide a window into human behaviour and therefore present abundant research opportunities for behavioural science.
Are Inflationary Shocks Regressive? A Feasible Set Approach
We develop a framework to measure the welfare impact of macroeconomic shocks throughout the distribution. The first-order impact of a shock is summarized by the induced movements in agents’ feasible sets: their budget constraint and borrowing constraints. We combine estimated impulse response functions with micro-data on household consumption bundles, asset holdings, and labor income for different US households. We find that inflationary oil shocks are regressive, but monetary expansions are progressive, and there is substantial heterogeneity throughout the life cycle.
Synthesis of evidence yields high social cost of carbon due to structural model variation and uncertainties
Significance: Estimating the social cost of carbon (SCC)—the cost of one additional ton of CO2 emitted—is crucial for the analysis of climate change policies. Despite numerous recent studies investigating how fundamental aspects of model structure affect SCC evaluation, findings are scattered, making the relative importance of different modeling elements hard to establish. This paper synthesizes results from the published literature over the last 20 y, revealing a wide range of SCC estimates.
Minimum Viable Signal: Venture Funding, Social Movements, and Race
How do venture capital investors react to social movements, especially those that relate to historical underrepresentation in their funding decisions? We use image and name algorithms combined with clerical review to classify race for 150,000 founders and 30,000 investors. Our new data allow us to assess the impact of George Floyd's murder on VC funding of Black entrepreneurs and identify which VCs were most responsive. Although VCs responded swiftly, investment in Black-owned startups reverted to prior levels within two years.
Leaders in Social Movements: Evidence from Unions in Myanmar
Social movements are catalysts for crucial institutional changes. To succeed, they must coordinate members’ views (consensus building) and actions (mobilization). We study union leaders within Myanmar’s burgeoning labor movement. Union leaders are positively selected on both ability and personality traits that enable them to influence others, yet they earn lower wages. In group discussions about workers’ views on an upcoming national minimum wage negotiation, randomly embedded leaders build consensus around the union’s preferred policy.
Elite Conflict and Industry Regulation: How Political Polarization Affects Local Restriction and State Preemption of the U.S. Hydraulic Fracturing Industry
We leverage Lachmann’s insight on elite conflict to explain the politics surrounding industry regulation in contemporary America and argue that conflicts between political elites create both constraints on industry players and opportunities for them to shape regulation. The widening urban-rural polarization of American society, in particular, has made urban political elites more liberal than those in state politics. The greater the political polarization of a state, the more local restrictions the nascent U.S.
CSR as Hedging Against Institutional Transition Risk: Corporate Philanthropy After the Sunflower Movement in Taiwan
Firms with political connections to a regime with an authoritarian history face a dilemma when the regime undergoes a democratic transition. Such connections provide an essential competitive advantage when the regime is in power but become a liability when an institutional transition brings democratic change. This study theorizes that when mass protests expose a regime’s distorted policies favoring elites over others and signal a high probability of regime turnover, firms may hedge against the risks associated with their political connections by engaging in philanthropy.
Demographic pricing in the digital age: Assessing fairness perceptions in algorithmic versus human-based price discrimination
Advancements in data analytics and increased access to consumer data have revolutionized companies’ price discrimination capabilities. These technological advancements have not only changed how prices are determined but also who determines them, with companies increasingly relying on algorithms rather than humans to set prices. We examine consumers’ fairness perceptions of demographic price discrimination—a prevalent yet controversial practice that can trigger considerable consumer backlash—and find that it depends on who is responsible for setting prices.
Climate policy curves highlight key mitigation choices
The extent of future climate change is largely a policy choice. We illuminate this choice with climate policy curves (CPCs), which link climate policies to subsequent global temperatures. The estimated downward sloping CPCs highlight the key trade-off between initial policy ambition, expressed via an overall effective carbon price, and the subsequent policy burden left for future generations. We also demonstrate how different CPCs can illustrate the range of climate policy paths towards attaining the Paris Agreement temperature goals.
High-Skilled Immigration Enhances Regional Entrepreneurship
Immigrants are highly entrepreneurial. But, what is the broader relationship between high-skilled immigration and regional entrepreneurship activity beyond the ventures that immigrants establish themselves? Using administrative data on newly awarded H-1B visas in the United States, we document a positive relationship between highskilled immigration and regional entrepreneurship. A doubling of immigrants to a metropolitan statistical area is followed by a 6% increase in entrepreneurship within three years.
This is Why I Leave: Race and Voluntary Departure
Although there have been numerous studies on voluntary departure—i.e., quit behavior—the way race influences voluntary departure is not yet settled. Some studies suggest racial minorities are more apt to voluntarily depart than non-minority employees due to discrimination in the workplace. Other studies suggest racial minorities are more apt to stay due to discrimination in the labor market.
Personalized Game Design for Improved User Retention and Monetization in Freemium Mobile Games
One of the most significant levers available to gaming companies in designing digital games is setting the level of difficulty, which essentially regulates the user’s ability to progress within the game. This aspect is particularly significant in free-to-play (F2P) games, where the paid version often aims to enhance the player’s experience and to facilitate faster progression. In this paper, we leverage a large randomized control trial to assess the effect of dynamically adjusting game difficulty on players’ behavior and game monetization in the context of a popular F2P mobile game.
EXPRESS: Who Shares Fake News? Uncovering Insights from Social Media Users' Post Histories
We propose that social-media users’ own post histories are an underused yet valuable resource for studying fake-news sharing. By extracting textual cues from their prior posts, and contrasting their prevalence against random social-media users and others (e.g., those with similar socio-demographics, political news-sharers, and fact-check sharers), researchers can identify cues that distinguish fake-news sharers, predict those most likely to share fake news, and identify promising constructs to build interventions. Our research includes studies along these lines.
The Customer Journey as a Source of Information
Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile
Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling influences consumer choice in e-commerce settings even when there is no face-to-face interaction.
Unveiling the mind of the machine
Previous research has shown that consumers respond differently to decisions made by humans versus algorithms. Many tasks, however, are not performed by humans anymore but entirely by algorithms. In fact, consumers increasingly encounter algorithm-controlled products, such as robotic vacuum cleaners or smart refrigerators, which are steered by different types of algorithms. Building on insights from computer science and consumer research on algorithm perception, this research investigates how consumers respond to different types of algorithms within these products.
The Entry-Deterring Effects of Synergies in Complementor Acquisitions: Evidence from Apple’s Digital Platform Market, the iOS App Store
Acquisitions can shift the market structure of a digital platform in ways that affect subsequent entries and hence the platform’s base of complementors. Synergies that complementor acquirers accrue can be entry-deterring. We develop a two-by-two typology of acquisition synergies in a multisided platform based on the two sides of a platform market (user side or complementary-technology side) and two sources of synergies (scale or scope economies).
Secrets at Work
Organizational secrecy is central to national security, politics, business, technology, healthcare, and law, but its effects are largely unknown. Keeping organizational secrets creates social divides between those who are required to keep the secret and those who are not allowed to know it. We demonstrate that keeping organizational secrets simultaneously evokes feelings of social isolation and status, which have opposing effects on employee well-being.
Widespread misestimates of greenhouse gas emissions suggest low carbon competence
As concern with climate change increases, people seek to behave and consume sustainably. This requires understanding which behaviours, firms and industries have the greatest impact on emissions. Here we ask if people are knowledgeable enough to make choices that align with growing sustainability intentions.
Vaccine Progress, Stock Prices, and the Value of Ending the Pandemic
One measure of the ex ante cost of disasters is the welfare gain from shorten-ing their expected duration. We introduce a stochastic clock into a standard disaster model that summarizes information about progress (positive or negative) toward disaster resolution. We show that the stock market response to duration news is essentially a sufficient statistic to identify the welfare gain to interventions that alter the state.
Stable Matching on the Job? Theory and Evidence on Internal Talent Markets
A principal often needs to match agents to perform coordinated tasks, but agents can quit or slack off if they dislike their match. We study two prevalent approaches for matching within organizations: centralized assignment by firm leaders and self-organization through market-like mechanisms. We provide a formal model of the strengths and weaknesses of both methods under different settings, incentives, and production technologies. The model highlights trade-offs between match-specific productivity and job satisfaction.
Carbon Dioxide as a Risky Asset
We develop a financial-economic model for carbon pricing with an explicit representation of decision making under risk and uncertainty that is consistent with the Intergovernmental Panel on Climate Change’s sixth assessment report. We show that risk associated with high damages in the long term leads to stringent mitigation of carbon dioxide emissions in the near term, and find that this approach provides economic support for stringent warming targets across a variety of specifications.
The Topography of Thought
Whether speaking, writing, or thinking, almost everything humans do involves language. But can the semantic structure behind how people express their ideas shed light on their future success? Natural language processing of over 40,000 college application essays finds that students whose writing covers more semantic ground, while moving more slowly (i.e. moving between more semantically similar ideas), end up doing better academically (i.e. have a higher college grade point average). These relationships hold controlling for dozens of other factors (e.g.
Firms’ Rhetorical Nationalism: Theory, Measurement, and Evidence from a Computational Analysis of Chinese Public Firms
In this paper, we develop a computational measure of the firm-level rhetorical nationalism. We first review the literature and develop a four-dimensional theoretical framework of nationalism relevant to firms: national pride, anti-foreign, dominant agenda, and corporate role. We then use machine-learning-based text analysis of over 41,000 annual reports of Chinese public firms from 2000 to 2020 and identify a dictionary of words for each dimension.
The Language of (Non)replicable Social Science
Using publicly available data from 299 pre-registered replications from the social sciences, we find that the language used to describe a study can predict its replicability above and beyond a large set of controls related to the paper characteristics, study design and results, author information, and replication effort. To understand why, we analyze the textual differences between replicable and nonreplicable studies.
Valuing Financial Data
How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information
about others’ characteristics. It can value data that is public or private, about one or many assets, relevant for dividends or for sentiment. While different data types, of course, have different valuations, heterogeneous investors also value the same data
A Theory of Fiscal Responsibility and Irresponsibility
We propose a political economy mechanism that explains the presence of fiscal regimes punctuated by crisis periods. Our model focuses on the interaction between successive deficit-biased governments subject to i.i.d. fiscal shocks. We show that the economy transitions between a fiscally responsible regime and a fiscally irresponsible regime, with transitions occurring during crises when fiscal needs are large. Under fiscal responsibility, governments limit their spending to avoid transitioning to fiscal irresponsibility.
Detecting Routines: Applications to Ridesharing CRM
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines — which we define as repeated behaviors with recurring, temporal structures — for customer management. One reason for this dearth is the difficulty of measuring routines from transaction data, particularly when routines vary substantially across customers. We propose a new approach for doing so, which we apply in the context of ridesharing.
Is Journalistic Truth Dead? Measuring How Informed Voters Are about Political News
To investigate general patterns in news information in the United States, we combine a protocol for identifying major political news stories, 11 monthly surveys with 15,000 participants, and a model of news discernment. When confronted with a true and a fake news story, 47 percent of subjects confidently choose the true story, 3 percent confidently choose the fake story, and the remaining half are uncertain. Socioeconomic differences are associated with large variations in the probability of selecting the true news story.
The New Psychology of Secrecy
Nearly everyone keeps secrets, but only recently have we begun to learn about the secrets people keep in their everyday lives and the experiences people have with their secrets. Early experimental research into secrecy sought to create secrecy situations in the laboratory, but in trying to observe secrecy in real time, these studies conflated secrecy with the act of concealment. In contrast, a new psychology of secrecy recognizes that secrecy is far more than biting our tongues and dodging others’ questions.
By the People and For the People: The Double-Edged Effects Of Platform User Mobilization On Public Policies
Constituency mobilization is a widely prevalent corporate political strategy, yet we lack systematic evidence on the scope of its effectiveness. One emerging form of constituency mobilization is user mobilization, wherein a company focuses on rallying political support among its users. This approach differs from traditional lobbying, which relies on tightly controlled insider strategies to exert influence over lawmakers. In our study of user mobilization by platform-based companies in the U.S.
Exposing Omitted Moderators: Why Effects Size Differ in the Social Sciences.
Policymakers increasingly rely on behavioral science in response to global challenges, such as climate change or global health crises. But applications of behavioral science face an important problem: Interventions often exert substantially different effects across contexts and individuals. We examine this heterogeneity for different paradigms that underlie many behavioral interventions. We study the paradigms in a series of five preregistered studies across one in-person and 10 online panels, with over 11,000 respondents in total.
Americans misperceive the frequency and format of political debate
Disagreement over divergent viewpoints seems like an ever-present feature of American life—but how common is debate and with whom do debates most often occur? In the present research, we theorize that the landscape of debate is distorted by social media and the salience of negativity present in high-profile spats. To understand the true landscape of debate, we conducted three studies (N = 2985) across online and lab samples.
Changing Central Bank Pressures and Inflation
We introduce a simple long-run aggregate demand and supply framework for evaluating long-run inflation. The framework illustrates how exogenous economic and political economy factors generate pressures that, in the presence of central bank discretion, can have an impact on long-run inflation as well as transitions between steady states. We use the analysis to provide a fresh perspective on the forces that drove global inflation downward over the past four decades.
The Economics of the Public Option: Evidence from Local Pharmaceutical Markets
We study the effects of competition by state-owned firms, leveraging the decentralized entry of public pharmacies to local markets in Chile. Public pharmacies sell the same drugs at a third of private pharmacy prices, because of stronger upstream bargaining and market power in the private sector, but are of lower quality. Public pharmacies induced market segmentation and price increases in the private sector, which benefited the switchers to the public option but harmed the stayers.
Personalized Pricing and the Value of Time: Evidence from Auctioned Cab Rides
We recover valuations of time using detailed data from a large ride-hail platform, where drivers bid on trips and consumers choose between a set of rides with different prices and wait times. Leveraging a consumer panel, we estimate demand as a function of both prices and wait times and use the resulting estimates to recover heterogeneity in the value of time across consumers. We study the welfare implications of personalized pricing and its effect on the platform, drivers, and consumers.
Using large language models to generate silicon samples in consumer and marketing research: Challenges, opportunities, and guidelines.
Should consumer researchers employ silicon samples and artificially generated data based on large language models, such as GPT, to mimic human respondents' behavior? In this paper, we review recent research that has compared result patterns from silicon and human samples, finding that results vary considerably across different domains. Based on these results, we present specific recommendations for silicon sample use in consumer and marketing research.
Central Bank Credibility and Fiscal Responsibility
We consider a New Keynesian model with strategic monetary and fiscal interactions. The fiscal authority maximizes social welfare. Monetary policy is delegated to a central bank with an anti-inflation bias that suffers from a lack of commitment. The impact of central bank hawkishness on debt issuance is non-monotonic because increased