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    • All HBS Web  (322)
      • Faculty Publications  (44)

      Preference Prediction Remove Preference Prediction →

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      • July 2022
      • Article

      The Developmental Origins and Behavioral Consequences of Attributions for Inequality

      By: Antonya Marie Gonzalez, Lucia Macchia and Ashley V. Whillans
      Attributions, or lay explanations for inequality, have been linked to inequality-relevant behavior. In adults and children, attributing inequality to an individual rather than contextual or structural causes is linked to greater support for economic inequality and less...  View Details
      Keywords: Social Cognition; Inequality; Prosocial Behavior; Parent-child Transmission; Equality and Inequality; Cognition and Thinking; Attitudes; Behavior
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      Gonzalez, Antonya Marie, Lucia Macchia, and Ashley V. Whillans. "The Developmental Origins and Behavioral Consequences of Attributions for Inequality." Journal of Experimental Social Psychology 101 (July 2022).
      • 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
      Keywords: Burnout; Time Stress; Workplace Practices; Deadlines; Time Management; Gender; Well-being
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      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). (This article was featured as a “Research Highlight” in Nature in November, 2021.)
      • October 2021
      • Article

      Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

      By: Nicolas Padilla and Eva Ascarza
      The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...  View Details
      Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis
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      Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
      • Article

      Birds of a Feather...Enforce Social Norms? Interactions Among Culture, Norms, and Strategy

      By: Hongyi Li and Eric J. Van den Steen
      Does culture eat strategy for breakfast? This paper investigates the interactions among corporate culture, norms, and strategy, in order to better understand this issue and related questions. It first shows, through microfoundations, how the forces that drive toward...  View Details
      Keywords: Culture; Norms; Organizational Culture; Strategy; Values and Beliefs
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      Li, Hongyi, and Eric J. Van den Steen. "Birds of a Feather...Enforce Social Norms? Interactions Among Culture, Norms, and Strategy." Strategy Science 6, no. 2 (June 2021): 166–189.
      • May 2021 (Revised February 2022)
      • Teaching Note

      THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

      By: Ayelet Israeli and Jill Avery
      THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...  View Details
      Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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      Israeli, Ayelet, and Jill Avery. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Teaching Note 521-097, May 2021. (Revised February 2022.)
      • January 2021 (Revised March 2021)
      • Case

      THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

      By: Jill Avery, Ayelet Israeli and Emma von Maur
      THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...  View Details
      Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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      Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
      • 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
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      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.
      • 2020
      • Working Paper

      Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

      By: Eva Ascarza
      The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...  View Details
      Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry
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      Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Harvard Business School Working Paper, No. 19-091, February 2019. (Revised May 2020. Accepted at the Journal of Marketing Research.)
      • Article

      Maimonides' Ladder: States of Mutual Knowledge and the Perception of Charitability

      By: Julian De Freitas, Peter DiScioli, Kyle A. Thomas and Steven Pinker
      Why do people esteem anonymous charitable giving? We connect normative theories of charitability (captured in Maimonides’ Ladder of Charity) with evolutionary theories of partner choice to test predictions on how attributions of charitability are affected by states of...  View Details
      Keywords: Charity; Reciprocity; Partner Choice; Common Knowledge; Philanthropy and Charitable Giving; Knowledge; Perception
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      De Freitas, Julian, Peter DiScioli, Kyle A. Thomas, and Steven Pinker. "Maimonides' Ladder: States of Mutual Knowledge and the Perception of Charitability." Journal of Experimental Psychology: General 148, no. 1 (January 2019): 158–173.
      • January 2019
      • Article

      Making Moves Matter: Experimental Evidence on Incentivizing Bureaucrats Through Performance-Based Postings

      By: Adnan Q. Khan, Asim Ijaz Khwaja and Benjamin A. Olken
      Bureaucracies often post staff to better or worse locations, ostensibly to provide incentives. Yet we know little about whether this works, with heterogeneity in preferences over postings impacting effectiveness. We propose a performance-ranked serial dictatorship...  View Details
      Keywords: Serial Dictatorship Mechanism; Employment; Geographic Location; Motivation and Incentives; Performance
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      Khan, Adnan Q., Asim Ijaz Khwaja, and Benjamin A. Olken. "Making Moves Matter: Experimental Evidence on Incentivizing Bureaucrats Through Performance-Based Postings." American Economic Review 109, no. 1 (January 2019): 237–270.
      • 2018
      • Working Paper

      Channeled Attention and Stable Errors -- Previous Working Version

      By: Tristan Gagnon-Bartsch, Matthew Rabin and Joshua Schwartzstein
      A common critique of models of mistaken beliefs is that people should recognize their error after observations they thought were unlikely. This paper develops a framework for assessing when a given error is likely to be discovered, in the sense that the error-maker...  View Details
      Keywords: Perception; Behavior; Theory; Situation or Environment
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      Gagnon-Bartsch, Tristan, Matthew Rabin, and Joshua Schwartzstein. "Channeled Attention and Stable Errors -- Previous Working Version." Harvard Business School Working Paper, No. 18-108, June 2018.
      • 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
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      Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Teaching Note 518-053, November 2017.
      • September 2017
      • Article

      The Belief in a Favorable Future

      By: Todd Rogers, Don A. Moore and Michael I. Norton
      People believe that future others’ preferences and beliefs will change to align with their own. People holding a particular view (e.g., support of President Trump) are more likely to believe that future others will share their view than to believe that future others...  View Details
      Keywords: Social Cognition; Judgment; Prediction; Forecasting; False Consensus; Donation; Open Data; Open Materials; Preregistered; Forecasting and Prediction; Perception; Values and Beliefs; Behavior
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      Rogers, Todd, Don A. Moore, and Michael I. Norton. "The Belief in a Favorable Future." Psychological Science 28, no. 9 (September 2017): 1290–1301.
      • 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
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      Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
      • 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
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      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.
      • Article

      The Not-So-Common-Wealth of Australia: Evidence for a Cross-Cultural Desire for a More Equal Distribution of Wealth.

      By: Michael I. Norton, David T. Neal, Cassandra L. Govan, Dan Ariely and Elise Holland
      Recent evidence suggests that Americans underestimate wealth inequality in the United States and favor a more equal wealth distribution (Norton & Ariely, 2011). Does this pattern reflect ideological dynamics unique to the United States, or is the phenomenon evident in...  View Details
      Keywords: Wealth; Equality and Inequality; Australia; United States
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      Norton, Michael I., David T. Neal, Cassandra L. Govan, Dan Ariely, and Elise Holland. "The Not-So-Common-Wealth of Australia: Evidence for a Cross-Cultural Desire for a More Equal Distribution of Wealth." Analyses of Social Issues and Public Policy 14, no. 1 (December 2014): 339–351.
      • 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
      Keywords: Risk and Uncertainty; Forecasting and Prediction; Performance Evaluation
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      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.
      • October 2014
      • Teaching Note

      Financial Policy at Apple, 2013 (A) and (B)

      By: Mihir A. Desai and Elizabeth Meyer
      This is the teaching note to HBS case 214-085: Financial Policy at Apple, 2013 (A).  View Details
      Keywords: Apple; Steve Jobs; Forecast; Forecasting; Forecasting And Prediction; Shareholder Activism; Share Repurchase; Dividends; Financial Ratios; Preferred Shares; Cash Distribution; Corporate Finance; Borrowing and Debt; Financial Management; Financial Strategy; Technology Industry; Consumer Products Industry; United States; Republic of Ireland
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      Desai, Mihir A., and Elizabeth Meyer. "Financial Policy at Apple, 2013 (A) and (B)." Harvard Business School Teaching Note 215-022, October 2014.
      • October 2014
      • Supplement

      Financial Policy at Apple, 2013 Excel Supplement

      By: Mihir Desai and Elizabeth A. Meyer
      This is the Excel Supplement to Teaching Note 215-022: Financial Policy at Apple, 2013 (A) - (B).  View Details
      Keywords: Apple; Steve Jobs; Forecast; Forecasting; Forecasting And Prediction; Shareholder Activism; Share Repurchase; Dividends; Financial Ratios; Preferred Shares; Cash Distribution; Corporate Finance; Borrowing and Debt; Financial Management; Financial Strategy; United States; Republic of Ireland
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      Desai, Mihir, and Elizabeth A. Meyer. "Financial Policy at Apple, 2013 Excel Supplement." Harvard Business School Spreadsheet Supplement 215-703, October 2014.
      • October 2014
      • Supplement

      Financial Policy at Apple, 2013 Powerpoint Supplement

      By: Mihir Desai and Elizabeth A. Meyer
      This is the PowerPoint supplement to the teaching note: Financial Policy at Apple, 2013 (A) - (B), number 215-022.  View Details
      Keywords: Apple; Steve Jobs; Forecast; Forecasting; Forecasting And Prediction; Shareholder Activism; Share Repurchase; Dividends; Financial Ratios; Preferred Shares; Cash Distribution; Corporate Finance; Borrowing and Debt; Financial Management; Financial Strategy; Technology Industry; Consumer Products Industry; United States; Republic of Ireland
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      Desai, Mihir, and Elizabeth A. Meyer. "Financial Policy at Apple, 2013 Powerpoint Supplement." Harvard Business School PowerPoint Supplement 215-023, October 2014.
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