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- 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....
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Keywords:
Data-driven Decision-making;
Decisions;
Negotiation;
Bids and Bidding;
Valuation;
Consumer Behavior;
Real Estate Industry
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....
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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....
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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
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....
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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
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
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
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...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
AI and Machine Learning;
Forecasting and Prediction
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.
- September 2022
- Case
Esas Group: Investing Together, Staying Together
By: Christina R. Wing and Alpana Thapar
This case opens in June 2022, after Esas Group, one of Turkey’s largest family-owned investment firms, implements a series of changes to professionalize the business and help transition family members from operators to responsible investors. In December 2019, the Group...
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Keywords:
Family Business;
Transition;
Business or Company Management;
Organizational Structure;
Governing and Advisory Boards;
Governance;
Financial Services Industry;
Turkey
Wing, Christina R., and Alpana Thapar. "Esas Group: Investing Together, Staying Together." Harvard Business School Case 623-027, September 2022.
- September 2022
- Article
Human Versus Machine: A Comparison of Robo-Analyst and Traditional Research Analyst Investment Recommendations
By: Braiden Coleman, Kenneth J. Merkley and Joseph Pacelli
We provide the first comprehensive analysis of the properties of investment recommendations generated by “Robo-Analysts,” which are human analyst-assisted computer programs conducting automated research analysis. Our results indicate that Robo-Analyst recommendations...
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Keywords:
Fintech;
Analysts;
Robo-analysts;
Investment Recommendations;
Investment;
Information Technology;
Performance
Coleman, Braiden, Kenneth J. Merkley, and Joseph Pacelli. "Human Versus Machine: A Comparison of Robo-Analyst and Traditional Research Analyst Investment Recommendations." Accounting Review 97, no. 5 (September 2022): 221–244.
- September 2022
- Article
Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews
By: Dennis W. Campbell and Ruidi Shang
This paper examines whether information extracted via text-based statistical methods applied to employee reviews left on the website Glassdoor.com can be used to develop indicators of corporate misconduct risk. We argue that inside information on the incidence of...
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Keywords:
Management Accounting;
Management Control;
Corporate Culture;
Corporate Misconduct;
Risk Measurement;
Organizational Culture;
Crime and Corruption;
Risk and Uncertainty;
Measurement and Metrics
Campbell, Dennis W., and Ruidi Shang. "Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews." Management Science 68, no. 9 (September 2022): 7034–7053.
- August 2022 (Revised March 2023)
- Technical Note
Real Estate iBuying
By: Michael Luca, Jesse M. Shapiro and Julia Kelley
This note provides an overview of real estate iBuying, or instant buying, a business model that involves buying homes and then reselling them at a profit. Introduced in the mid-2010s, iBuying streamlined the process of selling a home by offering instant, all-cash...
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Luca, Michael, Jesse M. Shapiro, and Julia Kelley. "Real Estate iBuying." Harvard Business School Technical Note 923-001, August 2022. (Revised March 2023.)
- August 2022
- Background Note
Retail Media Networks
By: Eva Ascarza, Ayelet Israeli and Celine Chammas
In 2022, retail media was one of the fastest growing segments in digital advertising. A retail media network (RMN) allows a retailer to use its assets for advertising. Retailers set up an advertising business by allowing marketers to buy advertising space across their...
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Keywords:
Advertisers;
Advertising Media;
Media And Broadcasting Industry;
Retail;
Retail Analytics;
Retail Promotion;
Retailing;
Ecommerce;
E-Commerce Strategy;
E-commerce;
Marketing Communication;
Targeting;
Targeted Advertising;
Targeted Marketing;
Advertising;
Marketing;
Marketing Communications;
Marketing Strategy;
Brands and Branding;
Media;
Marketing Channels;
Retail Industry;
Consumer Products Industry;
Advertising Industry;
United States
Ascarza, Eva, Ayelet Israeli, and Celine Chammas. "Retail Media Networks." Harvard Business School Background Note 523-029, August 2022.
- August 3, 2022
- Article
Why NFT Creators Are Going cc0
Strategies for building brands, communities, and content through intellectual property (IP) vary greatly across NFT projects. Some maintain more or less standard IP protections; others give just NFT owners rights to innovate upon the associated intellectual property;...
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Keywords:
Non-fungible Tokens;
NFTs;
Video Games;
Merchandising;
Creative Commons;
Intellectual Property
Flashrekt, and Scott Duke Kominers. "Why NFT Creators Are Going cc0." a16zcrypto.com (August 3, 2022).
- 2022
- Article
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations
By: Jessica Dai, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach and Himabindu Lakkaraju
As post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to ensure that the quality of the resulting explanations is consistently high across all subgroups of a population. For instance, it...
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Dai, Jessica, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach, and Himabindu Lakkaraju. "Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 203–214.
- 2022
- Article
Towards Robust Off-Policy Evaluation via Human Inputs
By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset...
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Singh, Harvineet, Shalmali Joshi, Finale Doshi-Velez, and Himabindu Lakkaraju. "Towards Robust Off-Policy Evaluation via Human Inputs." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 686–699.
- August 2022
- Article
What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features
By: Shunyuan Zhang, Dokyun Lee, Param Vir Singh and Kannan Srinivasan
We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel dataset...
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Keywords:
Sharing Economy;
Airbnb;
Property Demand;
Computer Vision;
Deep Learning;
Image Feature Extraction;
Content Engineering;
Property;
Marketing;
Demand and Consumers
Zhang, Shunyuan, Dokyun Lee, Param Vir Singh, and Kannan Srinivasan. "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features." Management Science 68, no. 8 (August 2022): 5644–5666.
- July 2022
- Article
Estimating Spillovers from Publicly Funded R&D: Evidence from the US Department of Energy
By: Kyle Myers and Lauren Lanahan
We quantify the magnitude of R&D spillovers created by grants to small firms from the US Department of Energy. Our empirical strategy leverages variation due to state-specific matching policies, and we develop a new approach to measuring both geographic and...
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Keywords:
Innovation;
Energy;
R&D;
Grants;
Innovation and Invention;
Research and Development;
Patents;
Performance;
United States
Myers, Kyle, and Lauren Lanahan. "Estimating Spillovers from Publicly Funded R&D: Evidence from the US Department of Energy." American Economic Review 112, no. 7 (July 2022): 2393–2423.
- 2022
- Working Paper
Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley W. Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a...
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Keywords:
Nonstop Flights;
Collaborative Innovation and Invention;
Patents;
Research and Development;
Air Transportation Industry
Bahar, Dany, Prithwiraj Choudhury, Do Yoon Kim, and Wesley W. Koo. "Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context." Harvard Business School Working Paper, No. 23-009, July 2022.