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  • 2019
  • Chapter

Behavioral Economics and Health-Care Markets

By: Amitabh Chandra, Benjamin Handel and Joshua Schwartzstein
This chapter summarizes research in behavioral health economics, focusing on insurance markets and product markets in health care. We argue that the prevalence of choice difficulties and biases leading to mistakes in these markets establish a special place for them in... View Details
Keywords: Behavioral Economics; Consumer Behavior; Economics; Health Care and Treatment; Insurance; Markets
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Chandra, Amitabh, Benjamin Handel, and Joshua Schwartzstein. "Behavioral Economics and Health-Care Markets." Chap. 6 in Handbook of Behavioral Economics: Foundations and Applications 2, edited by B. Douglas Bernheim, Stefano DellaVigna, and David Laibson, 459–502. Amsterdam: Elsevier/North-Holland, 2019.
  • March 2011
  • Supplement

BioPasteur: Instructions for the group discussion

By: Giovanni Gavetti and Francesca Gino
The purpose of this exercise is to let students experience a few biases that can be deleterious to strategic decision-making. In particular, students are induced to fall into a confirmatory trap, and to experience other biases such as anchoring and sampling bias.... View Details
Keywords: Decision Making; Groups and Teams; Prejudice and Bias; Strategy
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Gavetti, Giovanni, and Francesca Gino. "BioPasteur: Instructions for the group discussion." Harvard Business School Supplement 711-510, March 2011.
  • 2022
  • Working Paper

Confidence, Self-Selection and Bias in the Aggregate

By: Benjamin Enke, Thomas Graeber and Ryan Oprea
The influence of behavioral biases on aggregate outcomes like prices and allocations depends in part on self-selection: whether rational people opt more strongly into aggregate interactions than biased individuals. We conduct a series of betting market, auction and... View Details
Keywords: Prejudice and Bias; Cognition and Thinking; Markets; Price
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Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Confidence, Self-Selection and Bias in the Aggregate." NBER Working Paper Series, No. 30262, July 2022.
  • March 2011
  • Supplement

The Future of BioPasteur -- Supplement

By: Giovanni Gavetti and Francesca Gino
The purpose of this exercise is to let students experience a few biases that can be deleterious to strategic decision-making. In particular, students are induced to fall into a confirmatory trap, and to experience other biases such as anchoring and sampling bias.... View Details
Keywords: Decision Making; Problems and Challenges; Prejudice and Bias
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Gavetti, Giovanni, and Francesca Gino. "The Future of BioPasteur -- Supplement." Harvard Business School Supplement 711-509, March 2011.
  • 17 May 2018
  • Sharpening Your Skills

You Probably Have a Bias for Making Bad Decisions. Here's Why.

audience of the day with the president, believing the last idea he hears is the one most likely to be chosen. If true, the president is no better or worse than most of us in allowing cognitive biases to cloud our thinking. We are, for... View Details
Keywords: by Sean Silverthorne
  • December 2011 (Revised July 2013)
  • Background Note

Hypothesis-Driven Entrepreneurship: The Lean Startup

By: Thomas Eisenmann, Eric Ries and Sarah Dillard
Firms that follow a hypothesis-driven approach to evaluating entrepreneurial opportunity are called "lean startups." Entrepreneurs in these startups translate their vision into falsifiable business model hypotheses, then test the hypotheses using a series of "minimum... View Details
Keywords: Entrepreneurship; Business Startups
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Eisenmann, Thomas, Eric Ries, and Sarah Dillard. "Hypothesis-Driven Entrepreneurship: The Lean Startup." Harvard Business School Background Note 812-095, December 2011. (Revised July 2013.)
  • May 2021
  • Article

Ideology and Composition Among an Online Crowd: Evidence From Wikipedians

By: Shane Greenstein, Grace Gu and Feng Zhu
Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that... View Details
Keywords: User Segregation; Online Community; Contested Knowledge; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideology and Composition Among an Online Crowd: Evidence From Wikipedians." Management Science 67, no. 5 (May 2021): 3067–3086.
  • 16 Feb 2021
  • Working Paper Summaries

Bollywood, Skin Color, and Sexism: The Role of the Film Industry in Emboldening and Contesting Stereotypes in India after Independence

Keywords: by Sudev Sheth, Geoffrey Jones, and Morgan Spencer; Media & Broadcasting
  • Article

Price and Quality Decisions by Self-Serving Managers

By: Marco Bertini, Daniel Halbheer and Oded Koenigsberg
We present a theory of price and quality decisions by managers who are self-serving. In the theory, firms stress the price or quality of their products, but not both. Accounting for this, managers exploit any uncertainty about the cause of market outcomes to credit... View Details
Keywords: Causal Reasoning; Self-serving Bias; Strategic Orientation; Managerial Decision-making; Price; Quality; Decision Making; Theory
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Bertini, Marco, Daniel Halbheer, and Oded Koenigsberg. "Price and Quality Decisions by Self-Serving Managers." International Journal of Research in Marketing 37, no. 2 (June 2020): 236–257.
  • 07 Jun 2019
  • Working Paper Summaries

Reflexivity in Credit Markets

Keywords: by Robin Greenwood, Samuel G. Hanson, and Lawrence J. Jin
  • June 2023
  • Article

Amplification of Emotion on Social Media

By: Amit Goldenberg and Robb Willer
Why do expressions of emotion seem so heightened on social media? Brady et al. argue that extreme moral outrage on social media is not only driven by the producers and sharers of emotional expressions, but also by systematic biases in the way people that perceive moral... View Details
Keywords: Emotion; Perception; Prejudice and Bias; Emotions; Social Media
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Goldenberg, Amit, and Robb Willer. "Amplification of Emotion on Social Media." Nature Human Behaviour 7, no. 6 (June 2023): 845–846.
  • June 2013
  • Article

Opting-in: Participation Bias in Economic Experiments

By: Robert Slonim, Carmen Wang, Ellen Garbarino and Danielle Merrett
Assuming individuals rationally decide whether to participate or not to participate in lab experiments, we hypothesize several non-representative biases in the characteristics of lab participants. We test the hypotheses by first collecting survey and experimental data... View Details
Keywords: Participation Bias; Laboratory Experiments; Prejudice and Bias; Research
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Slonim, Robert, Carmen Wang, Ellen Garbarino, and Danielle Merrett. "Opting-in: Participation Bias in Economic Experiments." Journal of Economic Behavior & Organization 90 (June 2013): 43–70.
  • November–December 2019
  • Article

Making Sense of Soft Information: Interpretation Bias and Loan Quality

By: Dennis Campbell, Maria Loumioti and Regina Wittenberg Moerman
We explore whether behavioral biases impede the effective processing and interpretation of soft information in private lending. Taking advantage of the internal reporting system of a large federal credit union, we delineate three important biases likely to affect the... View Details
Keywords: Soft Information; Lending; Banking; Information; Financing and Loans; Banks and Banking; Decision Making
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Campbell, Dennis, Maria Loumioti, and Regina Wittenberg Moerman. "Making Sense of Soft Information: Interpretation Bias and Loan Quality." Art. 101240. Journal of Accounting & Economics 68, nos. 2-3 (November–December 2019).
  • 2015
  • Working Paper

Expertise vs. Bias in Evaluation: Evidence from the NIH

By: Danielle Li
Evaluators with expertise in a particular field may have an informational advantage in separating good projects from bad. At the same time, they may also have personal preferences that impact their objectivity. This paper develops a framework for separately identifying... View Details
Keywords: Prejudice and Bias; Performance Evaluation; Experience and Expertise
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Li, Danielle. "Expertise vs. Bias in Evaluation: Evidence from the NIH." Harvard Business School Working Paper, No. 16-053, October 2015.
  • Winter 2017
  • Article

Why Big Data Isn't Enough

By: Sen Chai and Willy C. Shih
There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and... View Details
Keywords: Big Data; Science-based; Science; Scientific Research; Data Analytics; Data Science; Data-driven Management; Data Scientists; Technological Innovation; Analytics and Data Science; Mathematical Methods; Theory
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Chai, Sen, and Willy C. Shih. "Why Big Data Isn't Enough." Art. 58227. MIT Sloan Management Review 58, no. 2 (Winter 2017): 57–61.
  • Spring 2016
  • Article

The Billion Prices Project: Using Online Prices for Inflation Measurement and Research

By: Alberto Cavallo and Roberto Rigobon
New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both... View Details
Keywords: Billion Prices Project; Online Scraped Data; Online Price Index; Economics; Research; Price; Analytics and Data Science
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Cavallo, Alberto, and Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Inflation Measurement and Research." Journal of Economic Perspectives 30, no. 2 (Spring 2016): 151–178.
  • 03 Jun 2019
  • Working Paper Summaries

Memory and Representativeness

Keywords: by Pedro Bordalo, Katherine Baldiga Coffman, Nicola Gennaioli, Frederik Schwerter, and Andrei Shleifer
  • August 2020
  • Article

Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation

By: Prithwiraj Choudhury, Evan Starr and Rajshree Agarwal
The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic... View Details
Keywords: Machine Learning; Bias; Human Capital; Management; Strategy
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Choudhury, Prithwiraj, Evan Starr, and Rajshree Agarwal. "Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation." Strategic Management Journal 41, no. 8 (August 2020): 1381–1411.
  • 26 Apr 2017
  • Working Paper Summaries

Assessing the Quality of Quality Assessment: The Role of Scheduling

Keywords: by Maria Ibanez and Michael W. Toffel; Service; Food & Beverage
  • September 2023
  • Exercise

Irrationality in Action: Decision-Making Exercise

By: Alison Wood Brooks, Michael I. Norton and Oliver Hauser
This teaching exercise highlights the obstacle of biases in decision-making, allowing students to generate examples of potentially poor decision-making rooted in abundant and unwanted bias. This exercise has two parts: a pre-class, online survey in which students... View Details
Keywords: Prejudice and Bias; Decision Making
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Brooks, Alison Wood, Michael I. Norton, and Oliver Hauser. "Irrationality in Action: Decision-Making Exercise." Harvard Business School Exercise 924-007, September 2023.
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