Filter Results:
(321)
Show Results For
- All HBS Web (321)
- Faculty Publications (69)
Show Results For
- All HBS Web (321)
- Faculty Publications (69)
Page 1 of 321
Results →
- August 2016
- Article
The Role of (Dis)similarity in (Mis)predicting Others' Preferences
By: Kate Barasz, Tami Kim and Leslie K. John
Consumers readily indicate liking options that appear dissimilar—for example, enjoying both rustic lake vacations and chic city vacations or liking both scholarly documentary films and action-packed thrillers. However, when predicting other consumers’ tastes for the... View Details
Keywords: Perceived Similarity; Prediction Error; Preference Prediction; Self-other Difference; Social Inference; Cognition and Thinking; Perception; Forecasting and Prediction
Barasz, Kate, Tami Kim, and Leslie K. John. "The Role of (Dis)similarity in (Mis)predicting Others' Preferences." Journal of Marketing Research (JMR) 53, no. 4 (August 2016): 597–607.
- May 2017 (Revised March 2018)
- Case
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Retailing; Preference Elicitation; Big Data; Predictive Analytics; Artificial Intelligence; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; Apparel and Accessories Industry; Consumer Products Industry; Fashion Industry; Retail Industry; United States; Canada; North America
Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
- April 2023
- Article
The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences
By: Armin Falk, Anke Becker, Thomas Dohmen, David B. Huffman and Uwe Sunde
Incentivized choice experiments are a key approach to measuring preferences in economics but are also costly. Survey measures are a low-cost alternative but can suffer from additional forms of measurement error due to their hypothetical nature. This paper seeks to... View Details
Keywords: Survey Validation; Experiment; Preference Measurement; Surveys; Economics; Behavior; Measurement and Metrics
Falk, Armin, Anke Becker, Thomas Dohmen, David B. Huffman, and Uwe Sunde. "The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences." Management Science 69, no. 4 (April 2023): 1935–1950.
- November 2017
- Teaching Note
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Brands; Brand ＆ Product Management; Big Data; ＂Marketing Analytics＂; Consumer Behavior; Predictive Analytics; Forecasting; Preferences; Operation Management; Distribution Channels; Marketing; Marketing Channels; Marketing Strategy; Brands and Branding; Forecasting and Prediction; Data and Data Sets; Retail Industry; Fashion Industry; Apparel and Accessories Industry; United States; North America
- 2011
- Article
A Choice Prediction Competition for Social Preferences in Simple Extensive Form Games: An Introduction
By: Eyal Ert, Ido Erev and Alvin E. Roth
Two independent, but related, choice prediction competitions are organized that focus on behavior in simple two-person extensive form games: one focuses on predicting the choices of the first mover and the other on predicting the choices of the second mover. The... View Details
Keywords: Forecasting and Prediction; Behavior; Decision Choices and Conditions; Competition; Motivation and Incentives; Game Theory; Fairness
Ert, Eyal, Ido Erev, and Alvin E. Roth. "A Choice Prediction Competition for Social Preferences in Simple Extensive Form Games: An Introduction." Special Issue on Predicting Behavior in Games. Games 2, no. 3 (September 2011): 257–276.
- 04 Feb 2016
- Working Paper Summaries
Risk Preferences and Misconduct: Evidence from Politicians
- November 2012
- Article
An Age Penalty in Racial Preferences
By: Deborah A. Small, Devin G. Pope and Michael I. Norton
We document an age penalty in racial discrimination: charitable behavior toward African American children decreases-and negative stereotypical inferences increase-with the age of those children. Using data from an online charity that solicits donations for school... View Details
Keywords: Stereotyping; Charitable Giving; Prejudice; Prosocial Behavior; Philanthropy and Charitable Giving; Age; Race; Prejudice and Bias
Small, Deborah A., Devin G. Pope, and Michael I. Norton. "An Age Penalty in Racial Preferences." Social Psychological & Personality Science 3, no. 6 (November 2012): 730–737.
- June 2009
- Article
Highbrow Films Gather Dust: Time-inconsistent Preferences and Online DVD Rentals
By: Katherine L. Milkman, Todd Rogers and Max H. Bazerman
We report on a field study demonstrating systematic differences between the preferences people anticipate they will have over a series of options in the future and their subsequent revealed preferences over those options. Using a novel panel data set, we analyze the... View Details
Keywords: Decision Choices and Conditions; Forecasting and Prediction; Film Entertainment; Demand and Consumers; Renting or Rental; Power and Influence; Prejudice and Bias; Online Technology; Motion Pictures and Video Industry
Milkman, Katherine L., Todd Rogers, and Max H. Bazerman. "Highbrow Films Gather Dust: Time-inconsistent Preferences and Online DVD Rentals." Management Science 55, no. 6 (June 2009): 1047–1059.
- July 2019
- Article
I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice
By: Kate Barasz, Tami Kim and Ioannis Evangelidis
People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen... View Details
Keywords: Self-other Difference; Social Perception; Inference-making; Preferences; Consumer Behavior; Prediction; Prediction Error; Decision Choices and Conditions; Perception; Behavior; Forecasting and Prediction
Barasz, Kate, Tami Kim, and Ioannis Evangelidis. "I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice." Special Issue on The Cognitive Science of Political Thought. Cognition 188 (July 2019): 85–97.
- 2007
- Working Paper
Highbrow Films Gather Dust: Time-inconsistent Preferences and Online DVD Rentals
By: Katherine L. Milkman, Todd Rogers and Max H. Bazerman
We report on a field study demonstrating systematic differences between the preferences people anticipate they will have over a series of options in the future and their subsequent revealed preferences over those options. Using a novel panel data set, we analyze the... View Details
Keywords: Internet and the Web; Decision Choices and Conditions; Attitudes; Conflict and Resolution; Emotions; Film Entertainment; Cognition and Thinking; Entertainment and Recreation Industry
Milkman, Katherine L., Todd Rogers, and Max H. Bazerman. "Highbrow Films Gather Dust: Time-inconsistent Preferences and Online DVD Rentals." Harvard Business School Working Paper, No. 07-099, June 2007. (Revised July 2007, December 2007, April 2008, September 2008, January 2009.)
- 20 Jun 2016
- Research & Ideas
When Predicting Other People's Preferences, You're Probably Wrong
themselves, only 39.3 percent of the observers predicted their partners would make that choice. The observers did a better job of predicting their partners’ alternate View Details
- Article
Extension Request Avoidance Predicts Greater Time Stress Among Women
By: Ashley V. Whillans, Jaewon Yoon, Aurora Turek and Grant E. Donnelly
In nine studies using archival data, surveys, and experiments, we identify a factor that predicts gender differences in time stress and burnout. Across academic and professional settings, women are less likely to ask for more time when working under adjustable... View Details
Whillans, Ashley V., Jaewon Yoon, Aurora Turek, and Grant E. Donnelly. "Extension Request Avoidance Predicts Greater Time Stress Among Women." Proceedings of the National Academy of Sciences 118, no. 45 (November 9, 2021).
- 31 May 2007
- Working Paper Summaries
Extremeness Seeking: When and Why Consumers Prefer the Extremes
Keywords: by John T. Gourville & Dilip Soman
- 2020
- Working Paper
Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation
By: Michael Yeomans and Alison Wood Brooks
Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every... View Details
Keywords: Natural Language Processing; Interpersonal Communication; Perspective; Decision Making; Perception
Yeomans, Michael, and Alison Wood Brooks. "Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation." Harvard Business School Working Paper, No. 20-077, February 2020.
- 2018
- Working Paper
Algorithm Appreciation: People Prefer Algorithmic to Human Judgment
By: Jennifer M. Logg, Julia A. Minson and Don A. Moore
Even though computational algorithms often outperform human judgment, received wisdom suggests that people may be skeptical of relying on them (Dawes, 1979). Counter to this notion, results from six experiments show that lay people adhere more to advice when they think... View Details
Keywords: Algorithms; Accuracy; Advice Taking; Forecasting; Theory Of Machine; Mathematical Methods; Decision Making; Forecasting and Prediction; Trust
Logg, Jennifer M., Julia A. Minson, and Don A. Moore. "Algorithm Appreciation: People Prefer Algorithmic to Human Judgment." Harvard Business School Working Paper, No. 17-086, March 2017. (Revised April 2018.)
- 26 Mar 2013
- Working Paper Summaries
How Elastic Are Preferences for Redistribution? Evidence from Randomized Survey Experiments
- October 2010
- Article
Preferring Balanced vs. Advantageous Peace Agreements: A Study of Israeli Attitudes Towards a Two-State Solution
By: Deepak Malhotra and Jeremy Ginges
The paper extends research on fixed-pie perceptions by suggesting that disputants may prefer proposals that are perceived to be equally attractive to both parties (i.e., balanced) rather than one-sided, because balanced agreements are seen as more likely to be... View Details
Keywords: Fixed Pie; Balance; Peace; Negotiation; Agreements and Arrangements; Conflict and Resolution; Government and Politics; Balance and Stability; Forecasting and Prediction; Attitudes; Israel; Palestinian state
Malhotra, Deepak, and Jeremy Ginges. "Preferring Balanced vs. Advantageous Peace Agreements: A Study of Israeli Attitudes Towards a Two-State Solution." Judgment and Decision Making 5, no. 6 (October 2010): 420–427.
- Article
The Allure of Unknown Outcomes: Exploring the Role of Uncertainty in the Preference for Potential
By: Daniella Kupor, Zakary L. Tormala and Michael I. Norton
Influence practitioners often highlight a target's achievements (e.g., "she is the city's top-rated chef"), but recent research reveals that highlighting a target's potential (e.g., "she could become the city's top-rated chef") can be more effective. We examine whether... View Details
Kupor, Daniella, Zakary L. Tormala, and Michael I. Norton. "The Allure of Unknown Outcomes: Exploring the Role of Uncertainty in the Preference for Potential." Journal of Experimental Social Psychology 55 (November 2014): 210–216.
- 30 May 2023
- Research & Ideas
Can AI Predict Whether Shoppers Would Pick Crest or Colgate?
“That was pretty incredible to us, that you’re able to identify these patterns even with this simulated data.” The team then introduced two brands of toothpaste, Crest and Colgate, and set Colgate as the preferred brand. By altering the... View Details
Keywords: by Kristen Senz