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- All HBS Web
(2,324)
- Faculty Publications (291)
- December 2022
- Article
'Just Letting You Know…': Underestimating Others' Desire for Constructive Feedback
By: Nicole Abi-Esber, Jennifer E. Abel, Juliana Schroeder and Francesca Gino
People often avoid giving feedback to others even when it would help fix a problem immediately. Indeed, in a pilot field study (N=155), only 2.6% of individuals provided feedback to survey administrators that the administrators had food or marker on their faces.... View Details
Keywords: Feedback; Helping; Prosocial Behavior; Misprediction; Relationships; Interpersonal Communication; Perspective
Abi-Esber, Nicole, Jennifer E. Abel, Juliana Schroeder, and Francesca Gino. "'Just Letting You Know…': Underestimating Others' Desire for Constructive Feedback." Journal of Personality and Social Psychology 123, no. 6 (December 2022): 1362–1385.
- December 2022
- Article
Social Skills Improve Business Performance: Evidence from a Randomized Control Trial with Entrepreneurs in Togo
By: Stefan Dimitriadis and Rembrand Koning
Recent field experiments demonstrate that advice, mentorship, and feedback from randomly assigned peers improve entrepreneurial performance. These results raise a natural question: what is preventing entrepreneurs and managers from forming these peer connections... View Details
Keywords: Social Skills; Business Performance; Entrepreneurs; Peer Relationships; Field Experiment; Entrepreneurship; Performance; Relationships; Interpersonal Communication; Togo
Dimitriadis, Stefan, and Rembrand Koning. "Social Skills Improve Business Performance: Evidence from a Randomized Control Trial with Entrepreneurs in Togo." Management Science 68, no. 12 (December 2022): 8635–8657.
- December 2022
- Article
The Rise of People Analytics and the Future of Organizational Research
By: Jeff Polzer
Organizations are transforming as they adopt new technologies and use new sources of data, changing the experiences of employees and pushing organizational researchers to respond. As employees perform their daily activities, they generate vast digital data. These data,... View Details
Keywords: Organizational Change and Adaptation; Analytics and Data Science; Technology Adoption; Employees
Polzer, Jeff. "The Rise of People Analytics and the Future of Organizational Research." Art. 100181. Research in Organizational Behavior 42 (December 2022). (Supplement.)
- November 2022
- Article
My Boss' Passion Matters as Much as My Own: The Interpersonal Dynamics of Passion Are a Critical Driver of Performance Evaluations
By: Jon M. Jachimowicz, Andreas Wihler and Adam D. Galinsky
Companies often celebrate employees who successfully pursue their passion. Academic research suggests that these positive evaluations occur because of the passion percolating inside the employee. We propose that supervisors are also a key piece of this puzzle:... View Details
Keywords: Passion; Job Performance; Motivation; Emotions; Performance Evaluation; Interpersonal Communication
Jachimowicz, Jon M., Andreas Wihler, and Adam D. Galinsky. "My Boss' Passion Matters as Much as My Own: The Interpersonal Dynamics of Passion Are a Critical Driver of Performance Evaluations." Special Issue on Work Passion Research: Taming Breadth and Promoting Depth. Journal of Organizational Behavior 43, no. 9 (November 2022): 1496–1515.
- November 2022
- Article
The Psychosocial Value of Employment: Evidence from a Refugee Camp
By: Reshmaan Hussam, Erin M. Kelley, Gregory Lane and Fatima Zahra
Employment may be important to wellbeing for reasons beyond its role as an income source. This paper presents a causal estimate of the psychosocial value of employment in refugee camps in Bangladesh. We involve 745 individuals in a field experiment with three arms: a... View Details
Hussam, Reshmaan, Erin M. Kelley, Gregory Lane, and Fatima Zahra. "The Psychosocial Value of Employment: Evidence from a Refugee Camp." American Economic Review 112, no. 11 (November 2022): 3694–3724.
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- September 16, 2022
- Article
A Causal Test of the Strength of Weak Ties
By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
The authors analyzed data from multiple large-scale randomized experiments on LinkedIn’s People You May Know algorithm, which recommends new connections to LinkedIn members, to test the extent to which weak ties increased job mobility in the world’s largest... View Details
Rajkumar, Karthik, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson, and Sinan Aral. "A Causal Test of the Strength of Weak Ties." Science 377, no. 6612 (September 16, 2022).
- 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
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
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
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 (Revised January 2025)
- Technical Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of... View Details
Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised January 2025.)
- 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
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
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
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.
- 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
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
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
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
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.
- Article
Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)
By: Eva Ascarza and Ayelet Israeli
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details
Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 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
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
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.