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Show Results For
- All HBS Web
(593)
- People (1)
- News (92)
- Research (409)
- Events (5)
- Multimedia (1)
- Faculty Publications (212)
- March 2011 (Revised April 2011)
- Exercise
The Future of BioPasteur
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: Interpersonal Communication; Decision Choices and Conditions; Outcome or Result; Groups and Teams; Prejudice and Bias; Strategy
Gavetti, Giovanni, and Francesca Gino. "The Future of BioPasteur." Harvard Business School Exercise 711-508, March 2011. (Revised April 2011.)
- 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
Gavetti, Giovanni, and Francesca Gino. "BioPasteur: Instructions for the group discussion." Harvard Business School Supplement 711-510, March 2011.
Ideological Segregation among Online Collaborators: Evidence from Wikipedians
Do online communities segregate into separate conversations about “contestable knowledge”? We analyze the contributors of biased and slanted content in Wikipedia articles about U.S. politics, and focus on two research questions: (1) Do contributors display... View Details
- 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
Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Confidence, Self-Selection and Bias in the Aggregate." NBER Working Paper Series, No. 30262, July 2022.
- 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
Do Experts or Collective Intelligence Write with More Bias?
Co-authored by Feng Zhu
Which source of information contains greater bias and slant-text written by an expert or that constructed via collective intelligence? Do the costs of acquiring, storing, displaying, and revising information shape those... View Details
Which source of information contains greater bias and slant-text written by an expert or that constructed via collective intelligence? Do the costs of acquiring, storing, displaying, and revising information shape those... View Details
- 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
Gavetti, Giovanni, and Francesca Gino. "The Future of BioPasteur -- Supplement." Harvard Business School Supplement 711-509, March 2011.
- 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
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.
- 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
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.)
- 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
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.
- 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
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.
- 07 Jun 2019
- Working Paper Summaries
Reflexivity in Credit Markets
- 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
Goldenberg, Amit, and Robb Willer. "Amplification of Emotion on Social Media." Nature Human Behaviour 7, no. 6 (June 2023): 845–846.
- 15 Mar 2013
- News
Take Your 'Emotional Temperature' Before Making Decisions
- 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
Li, Danielle. "Expertise vs. Bias in Evaluation: Evidence from the NIH." Harvard Business School Working Paper, No. 16-053, October 2015.
- 03 Jun 2019
- Working Paper Summaries
Memory and Representativeness
- 27 Feb 2019
- News
Privacy in the Digital Age: An Interview with Leslie John
- 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
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.