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      • March 2023
      • Technical Note

      Companion to: Demand Simulator Spreadsheet Supplement

      By: Elie Ofek and Olivier Toubia
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      Ofek, Elie, and Olivier Toubia. "Companion to: Demand Simulator Spreadsheet Supplement." Harvard Business School Technical Note 523-096, March 2023.
      • March 2023
      • Supplement

      Demand Simulator

      By: Elie Ofek
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      Ofek, Elie. "Demand Simulator." Harvard Business School Spreadsheet Supplement 523-716, March 2023.
      • February 2023
      • Teaching Note

      SIMmersion: Simulating Crucial Conversations

      By: Alison Wood Brooks and Julian Zlatev
      Teaching Note for HBS Case No. 923-040. View Details
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      Brooks, Alison Wood, and Julian Zlatev. "SIMmersion: Simulating Crucial Conversations." Harvard Business School Teaching Note 923-044, February 2023.
      • February 2023
      • Case

      SIMmersion: Simulating Crucial Conversations

      By: Alison Wood Brooks, Julian Zlatev and F Katelynn Boland
      This case introduces readers to SIMmersion, a company founded in 2002 that creates and sells training programs to firms, government agencies, educational institutions, and individuals (B2B and B2C). Their training programs are built around simulations (“sims”) that... View Details
      Keywords: Decision Making; Interpersonal Communication; Training
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      Brooks, Alison Wood, Julian Zlatev, and F Katelynn Boland. "SIMmersion: Simulating Crucial Conversations." Harvard Business School Case 923-040, February 2023.
      • February 2023 (Revised March 2024)
      • Supplement

      Shanty Real Estate: Teaching Note Supplement

      By: Michael Luca and Jesse M. Shapiro
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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      Luca, Michael, and Jesse M. Shapiro. "Shanty Real Estate: Teaching Note Supplement." Harvard Business School Spreadsheet Supplement 923-715, February 2023. (Revised March 2024.)
      • 2023
      • Working Paper

      Distributionally Robust Causal Inference with Observational Data

      By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
      We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
      Keywords: AI and Machine Learning; Mathematical Methods
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      Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
      • 2023
      • Working Paper

      The Link Between Integrative Bargaining and Leadership Evaluations

      By: Julian J. Zlatev and Francis J. Flynn
      We draw from implicit leadership theory and the dual concern theory of conflict resolution to posit a link between negotiation style and leadership evaluations. Specifically, we propose that individuals who are more skilled at integrative, but not distributive,... View Details
      Keywords: Prosocial Behavior; Leadership; Negotiation; Conflict and Resolution; Performance Evaluation
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      Zlatev, Julian J., and Francis J. Flynn. "The Link Between Integrative Bargaining and Leadership Evaluations." Harvard Business School Working Paper, No. 23-044, January 2023.
      • November 2022
      • Article

      Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings

      By: Kristin Blesch, Oliver P. Hauser and Jon M. Jachimowicz
      Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the... View Details
      Keywords: Economic Inequalty; Gini Coefficient; Income Inequality; Equality and Inequality; Social Issues; Health; Status and Position
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      Blesch, Kristin, Oliver P. Hauser, and Jon M. Jachimowicz. "Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings." Nature Human Behaviour 6, no. 11 (November 2022): 1525–1536.
      • October 2022
      • Exercise

      Shanty Real Estate: Confidential Information for Homebuyer 1

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Data-driven Decision-making; Decisions; Negotiation; Bids and Bidding; Valuation; Consumer Behavior; Real Estate Industry
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for Homebuyer 1." Harvard Business School Exercise 923-016, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Confidential Information for Homebuyer 2

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for Homebuyer 2." Harvard Business School Exercise 923-017, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Confidential Information for Homebuyer 3

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for Homebuyer 3." Harvard Business School Exercise 923-018, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Confidential Information for iBuyer 1

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Algorithm; Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for iBuyer 1." Harvard Business School Exercise 923-019, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Confidential Information for iBuyer 2

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Decision Choices and Conditions; Decision Making; Market Timing; Measurement and Metrics
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for iBuyer 2." Harvard Business School Exercise 923-020, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Confidential Information for iBuyer 3

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Algorithm; Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for iBuyer 3." Harvard Business School Exercise 923-021, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Updated Confidential Information for Homebuyer

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Algorithm; Decision Choices and Conditions; Decision Making; Market Timing; Measurement and Metrics
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Updated Confidential Information for Homebuyer." Harvard Business School Exercise 923-022, October 2022.
      • October 2022
      • Exercise

      Shanty Real Estate: Updated Confidential Information for iBuyer

      By: Michael Luca, Jesse M. Shapiro and Nathan Sun
      Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
      Keywords: Algorithm; Decision Choices and Conditions; Measurement and Metrics; Market Timing; Decision Making
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      Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Updated Confidential Information for iBuyer." Harvard Business School Exercise 923-023, October 2022.
      • 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
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      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.
      • 2022
      • Article

      Nonparametric Subset Scanning for Detection of Heteroscedasticity

      By: Charles R. Doss and Edward McFowland III
      We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning... View Details
      Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics
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      Doss, Charles R., and Edward McFowland III. "Nonparametric Subset Scanning for Detection of Heteroscedasticity." Journal of Computational and Graphical Statistics 31, no. 3 (2022): 813–823.
      • 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
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      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 (Revised February 2024)
      • Case

      Applied Intuition: Powering Autonomy

      By: Andy Wu, Rocio Wu and Matt Higgins
      Applied Intuition, a leader in autonomous vehicle simulation software, has just closed on a $175 million round of Series D financing that values the four-year-old firm at $3.6 billion. With the immediate future secure, CEO Qasar Younis must now chart a strategic course... View Details
      Keywords: Autonomous Vehicles; Software; Strategy; Competitive Strategy; Growth and Development Strategy; Valuation; Auto Industry; Technology Industry; California; Detroit
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      Wu, Andy, Rocio Wu, and Matt Higgins. "Applied Intuition: Powering Autonomy." Harvard Business School Case 722-407, March 2022. (Revised February 2024.)
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