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Publications

Publications

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    • All HBS Web  (3,524)
      • Faculty Publications  (311)

      Natural Field ExperimentRemove Natural Field Experiment →

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      • September 2022
      • Article

      The Limits of Inconspicuous Incentives

      By: Leslie K. John, Hayley Blunden, Katherine Milkman, Luca Foschini and Bradford Tuckfield
      Managers and policymakers regularly rely on incentives to encourage valued behaviors. While incentives are often successful, there are also notable and surprising examples of their ineffectiveness. Why? We propose a contributing factor may be that they are not... View Details
      Keywords: Motivation and Incentives; Behavior
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      John, Leslie K., Hayley Blunden, Katherine Milkman, Luca Foschini, and Bradford Tuckfield. "The Limits of Inconspicuous Incentives." Art. 104180. Organizational Behavior and Human Decision Processes 172 (September 2022).
      • Article

      All Eyes on Them: A Field Experiment on Citizen Oversight and Electoral Integrity

      By: Natalia Garbiras-Díaz and Mateo Montenegro
      Can information and communication technologies help citizens monitor their elections? We analyze a large-scale field experiment designed to answer this question in Colombia. We leveraged Facebook advertisements sent to over 4 million potential voters to encourage... View Details
      Keywords: Social Influence; Electoral Behavior; Election Outcomes; Economics; Economy; Governance; Government and Politics; Social Media; Social Marketing; Society; Political Elections; Advertising
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      Garbiras-Díaz, Natalia, and Mateo Montenegro. "All Eyes on Them: A Field Experiment on Citizen Oversight and Electoral Integrity." American Economic Review 112, no. 8 (August 2022): 2631–2668.
      • July 2022
      • Article

      The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others

      By: Ke Wang, Erica R. Bailey and Jon M. Jachimowicz
      Employees are increasingly exhorted to “pursue their passion” at work. Inherent in this call is the belief that passion will produce higher performance because it promotes intrapersonal processes that propel employees forward. Here, we suggest that the pervasiveness of... View Details
      Keywords: Passion; Self-fufilling Prophecy; Lay Beliefs; Interpersonal Processes; Employees; Performance; Attitudes; Organizational Culture; Social Psychology
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      Wang, Ke, Erica R. Bailey, and Jon M. Jachimowicz. "The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others." Journal of Experimental Social Psychology 101 (July 2022).
      • June 2022
      • Article

      Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation

      By: Jacqueline N. Lane, Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan and Karim R. Lakhani
      The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information... View Details
      Keywords: Project Evaluation; Innovation; Knowledge Frontier; Information Sharing; Negativity Bias; Projects; Innovation and Invention; Information; Knowledge Sharing
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      Lane, Jacqueline N., Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan, and Karim R. Lakhani. "Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation." Management Science 68, no. 6 (June 2022): 4478–4495.
      • 2022
      • Article

      How to Choose a Default

      By: John Beshears, Richard T. Mason and Shlomo Benartzi
      We have developed a model for setting a default when a population is choosing among ordered choices—that is, ones listed in ascending or descending order. A company, for instance, might want to set a default contribution rate that will increase employees’ average... View Details
      Keywords: Nudge; Choice Architecture; Behavioral Economics; Behavioral Science; Default; Savings; Decision Choices and Conditions; Behavior; Motivation and Incentives
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      Beshears, John, Richard T. Mason, and Shlomo Benartzi. "How to Choose a Default." Behavioral Science & Policy 8, no. 1 (2022): 1–15.
      • 2022
      • Working Paper

      Are Experts Blinded by Feasibility?: Experimental Evidence from a NASA Robotics Challenge

      By: Jacqueline N. Lane, Zoe Szajnfarber, Jason Crusan, Michael Menietti and Karim R. Lakhani
      Resource allocation decisions play a dominant role in shaping a firm’s technological trajectory and competitive advantage. Recent work indicates that innovative firms and scientific institutions tend to exhibit an anti-novelty bias when evaluating new projects and... View Details
      Keywords: Evaluations; Novelty; Feasibility; Field Experiment; Resource Allocation; Technological Innovation; Competitive Advantage; Decision Making
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      Lane, Jacqueline N., Zoe Szajnfarber, Jason Crusan, Michael Menietti, and Karim R. Lakhani. "Are Experts Blinded by Feasibility? Experimental Evidence from a NASA Robotics Challenge." Harvard Business School Working Paper, No. 22-071, May 2022.
      • April 2022
      • Article

      Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft

      By: Shunyuan Zhang, Dokyun Lee, Param Singh and Tridas Mukhopadhyay
      We examine whether and how ride-sharing services influence the demand for home-sharing services. Our identification strategy hinges on a natural experiment in which Uber/Lyft exited Austin, Texas, in May 2016 due to local regulation. Using a 12-month longitudinal... View Details
      Keywords: Airbnb; Uber; Natural Experiment; Geographic Demand Dispersion; Sharing Economy; Transportation; Demand and Consumers; Geographic Scope
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      Zhang, Shunyuan, Dokyun Lee, Param Singh, and Tridas Mukhopadhyay. "Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft." Journal of Marketing Research (JMR) 59, no. 2 (April 2022): 374–391.
      • March–April 2022
      • Article

      Uncovering the Mitigating Psychological Response to Monitoring Technologies: Police Body Cameras Not Only Constrain but Also Depolarize

      By: Shefali V. Patil and Ethan Bernstein
      Despite organizational psychologists’ long-standing caution against monitoring (citing its reduction in employee autonomy and thus effectiveness), many organizations continue to use it, often with no detriment to performance and with strong support, not protest, from... View Details
      Keywords: Monitoring; Transparency; Polarization; Body Worn Cameras; Quasi Field Experiment; Analytics and Data Science; Employees; Perception; Law Enforcement
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      Patil, Shefali V., and Ethan Bernstein. "Uncovering the Mitigating Psychological Response to Monitoring Technologies: Police Body Cameras Not Only Constrain but Also Depolarize." Organization Science 33, no. 2 (March–April 2022): 541–570. (*The authors contributed equally to this manuscript.)
      • 2022
      • Working Paper

      Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment

      By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Kyle Schirmann
      Hybrid work is emerging as a novel form of organizing work globally. This paper reports causal evidence on how the extent of hybrid work—the number of days worked from home relative to days worked from the office—affects work outcomes. Collaborating with an... View Details
      Keywords: Hybrid Work; Remote Work; Work-from-home; Field Experiment; Employees; Geographic Location; Performance; Work-Life Balance
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      Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Kyle Schirmann. "Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment." Harvard Business School Working Paper, No. 22-063, March 2022.
      • 2022
      • Working Paper

      Do Startups Benefit from Their Investors' Reputation? Evidence from a Randomized Field Experiment

      By: Shai Benjamin Bernstein, Kunal Mehta, Richard Townsend and Ting Xu
      We analyze a field experiment conducted on AngelList Talent, a large online search platform for startup jobs. In the experiment, AngelList randomly informed job seekers of whether a startup was funded by a top-tier investor and/or was funded recently. We find that the... View Details
      Keywords: Startup Labor Market; Investors; Randomized Field Experiment; Certification Effect; Venture Capital; Business Startups; Human Capital; Job Search; Reputation
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      Bernstein, Shai Benjamin, Kunal Mehta, Richard Townsend, and Ting Xu. "Do Startups Benefit from Their Investors' Reputation? Evidence from a Randomized Field Experiment." Harvard Business School Working Paper, No. 22-060, February 2022.
      • March 2022
      • Article

      How Much Does Your Boss Make? The Effects of Salary Comparisons

      By: Zoë B. Cullen and Ricardo Perez-Truglia
      The vast majority of the pay inequality in an organization comes from differences in pay between employees and their bosses. But are employees aware of these pay disparities? Are employees demotivated by this inequality? To address these questions, we conducted a... View Details
      Keywords: Salary; Inequality; Managers; Career Concerns; Pay Transparency; Wages; Equality and Inequality; Perception; Behavior
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      Cullen, Zoë B., and Ricardo Perez-Truglia. "How Much Does Your Boss Make? The Effects of Salary Comparisons." Journal of Political Economy 130, no. 3 (March 2022): 766–822.
      • March 2022
      • Article

      Sensitivity Analysis of Agent-based Models: A New Protocol

      By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
      Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such... View Details
      Keywords: Agent-based Modeling; Sensitivity Analysis; Design Of Experiments; Total Order Sensitivity Indices; Organizations; Behavior; Decision Making; Mathematical Methods
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      Borgonovo, Emanuele, Marco Pangallo, Jan Rivkin, Leonardo Rizzo, and Nicolaj Siggelkow. "Sensitivity Analysis of Agent-based Models: A New Protocol." Computational and Mathematical Organization Theory 28, no. 1 (March 2022): 52–94.
      • March 2022
      • Article

      Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field

      By: Reshmaan Hussam, Natalia Rigol and Benjamin N. Roth
      Identifying high-growth microentrepreneurs in low-income countries remains a challenge due to a scarcity of verifiable information. With a cash grant experiment in India we demonstrate that community knowledge can help target high-growth microentrepreneurs; while the... View Details
      Keywords: Microentrepreneurs; Community Information; Field Experiment; Loans; Entrepreneurship; Developing Countries and Economies; Financing and Loans; Information; Mathematical Methods; India
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      Hussam, Reshmaan, Natalia Rigol, and Benjamin N. Roth. "Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field." American Economic Review 112, no. 3 (March 2022): 861–898.
      (Online Appendix with Corrigendum—Thanks to Isabella Masetto, Diego Ubfal, and The Institute for Replication for identifying a minor coding error in the production of Table 4.)
      • February 2022
      • Article

      Borrowing to Save? The Impact of Automatic Enrollment on Debt

      By: John Beshears, James J. Choi, David Laibson, Brigitte C. Madrian and William L. Skimmyhorn
      Does automatic enrollment into a retirement plan increase financial distress due to increased borrowing outside the plan? We study a natural experiment created when the U.S. Army began automatically enrolling newly hired civilian employees into the Thrift Savings Plan.... View Details
      Keywords: Retirement Savings; Automatic Enrollment; Choice Architecture; Nudge; Financial Distress; Retirement; Saving; Borrowing and Debt; Behavior
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      Beshears, John, James J. Choi, David Laibson, Brigitte C. Madrian, and William L. Skimmyhorn. "Borrowing to Save? The Impact of Automatic Enrollment on Debt." Journal of Finance 77, no. 1 (February 2022): 403–447.
      • 2022
      • Article

      Alleviating Time Poverty Among the Working Poor: A Pre-Registered Longitudinal Field Experiment

      By: A.V. Whillans and Colin West
      Poverty entails more than a scarcity of material resources—it also involves a shortage of time. To examine the causal benefits of reducing time poverty, we conducted a longitudinal feld experiment over six consecutive weeks in an urban slum in Kenya with a sample of... View Details
      Keywords: Time; Subjective Well Being; Administrative Costs; Friction; Poverty; Well-being; Money; Perception; Kenya
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      Whillans, A.V., and Colin West. "Alleviating Time Poverty Among the Working Poor: A Pre-Registered Longitudinal Field Experiment." Art. 719. Scientific Reports 12 (2022).
      • January 2022
      • Article

      Pushed into a Crowd: Repositioning Costs, Resources, and Competition in the RTE Cereal Industry

      By: Young Hou and Dennis Yao
      This paper exploits a natural experiment involving self-regulation in the ready-to-eat (RTE) breakfast cereal industry to evaluate the performance impact of product repositioning. It then examines how a product's brand equity value declines with repositioning distance... View Details
      Keywords: Positioning; Resources; Brand Equity; Competitive Dynamics; Non-market Strategy; Regulation; Repositioning; Product Positioning; Performance Evaluation; Brands and Branding; Competitive Strategy; Consumer Products Industry
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      Hou, Young, and Dennis Yao. "Pushed into a Crowd: Repositioning Costs, Resources, and Competition in the RTE Cereal Industry." Strategic Management Journal 43, no. 1 (January 2022): 3–29.
      • 2022
      • Working Paper

      Rethinking Explainability as a Dialogue: A Practitioner's Perspective

      By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh
      As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details
      Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations
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      Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.
      • Article

      Megastudies Improve the Impact of Applied Behavioural Science

      By: Katherine L. Milkman, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Pepi Pandiloski, Yeji Park, Aneesh Rai, Max Bazerman, John Beshears, Lauri Bonacorsi, Colin Camerer, Edward Chang, Gretchen Chapman, Robert Cialdini, Hengchen Dai, Lauren Eskreis-Winkler, Ayelet Fishbach, James J. Gross, Samantha Horn, Alexa Hubbard, Steven J. Jones, Dean Karlan, Tim Kautz, Erika Kirgios, Joowon Klusowski, Ariella Kristal, Rahul Ladhania, Jens Ludwig, George Loewenstein, Barbara Mellers, Sendhil Mullainathan, Silvia Saccardo, Jann Spiess, Gaurav Suri, Joachim H. Talloen, Jamie Taxer, Yaacov Trope, Lyle Ungar, Kevin G. Volpp, Ashley V. Whillans, Jonathan Zinman and Angela L. Duckworth
      Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens’ decisions and outcomes. Typically, different scientists test different intervention ideas in different samples using different outcomes over different time... View Details
      Keywords: Policy Making; Behavioral Science; Behavior; Change; Decision Making; Policy
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      Milkman, Katherine L., Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Pepi Pandiloski, Yeji Park, Aneesh Rai, Max Bazerman, John Beshears, Lauri Bonacorsi, Colin Camerer, Edward Chang, Gretchen Chapman, Robert Cialdini, Hengchen Dai, Lauren Eskreis-Winkler, Ayelet Fishbach, James J. Gross, Samantha Horn, Alexa Hubbard, Steven J. Jones, Dean Karlan, Tim Kautz, Erika Kirgios, Joowon Klusowski, Ariella Kristal, Rahul Ladhania, Jens Ludwig, George Loewenstein, Barbara Mellers, Sendhil Mullainathan, Silvia Saccardo, Jann Spiess, Gaurav Suri, Joachim H. Talloen, Jamie Taxer, Yaacov Trope, Lyle Ungar, Kevin G. Volpp, Ashley V. Whillans, Jonathan Zinman, and Angela L. Duckworth. "Megastudies Improve the Impact of Applied Behavioural Science." Nature 600, no. 7889 (December 16, 2021): 478–483.
      • Article

      A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

      By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
      We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
      Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
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      McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
      • Article

      Using Fresh Starts to Nudge Increased Retirement Savings

      By: John Beshears, Hengchen Dai, Katherine L. Milkman and Shlomo Benartzi
      We conducted a field experiment to study the effect of framing future moments in time as new beginnings (or “fresh starts”). University employees (N=6,082) received mailings with an opportunity to choose between increasing their contributions to a savings plan... View Details
      Keywords: Choice Architecture; Randomized Field Experiment; Savings; New Beginning; Fresh Start; Saving; Retirement; Behavior
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      Beshears, John, Hengchen Dai, Katherine L. Milkman, and Shlomo Benartzi. "Using Fresh Starts to Nudge Increased Retirement Savings." Organizational Behavior and Human Decision Processes 167 (November 2021): 72–87.
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