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  • October 2023
  • Case

Fortinet: Cybersecurity Pioneer Ken Xie Considers the Long Game
By: Tsedal Neeley, Jeff Huizinga and Emily Grandjean
Ken Xie, cofounder of cybersecurity giant Fortinet, faced a critical decision that would validate his leadership. Fortinet became the industry’s second-largest pureplay cybersecurity firm by developing differentiated hardware and investing in R&D. However, after a...  View Details
Keywords: Leadership Development; Leadership Style; Marketing Strategy; Information Technology Industry; United States; Sunnyvale
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  • 2023
  • Working Paper

Are Hospital Quality Indicators Causal?
By: Amitabh Chandra, Maurice Dalton and Douglas O. Staiger
Hospitals play a key role in patient outcomes and spending, but efforts to improve their quality are hindered because we do not know whether hospital quality indicators are causal or biased. We evaluate the validity of commonly used quality indicators, such as...  View Details
Keywords: Quality; Health Care and Treatment; Measurement and Metrics; Outcome or Result; Health Industry
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  • 2023
  • Working Paper

Emotion Regulation Contagion
By: Michael Pinus, Eran Halperin, Yajun Cao, Alin Coman, James Gross and Amit Goldenberg
In intergroup conflicts, emotion regulation interventions can decrease negative intergroup emotions and increase support for concessions. However, it is usually infeasible to provide emotion regulation interventions to everyone in a population of interest. This raises...  View Details
Keywords: Groups and Teams; Emotions; Conflict and Resolution
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  • 2023
  • Article

On Minimizing the Impact of Dataset Shifts on Actionable Explanations
By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models...  View Details
Keywords: Mathematical Methods; Analytics and Data Science
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  • Article

Update on E-liability Accounting
By: Robert Kaplan, Karthik Ramanna and Piyush Jha
Since publication of the original E-liability carbon accounting paper (HBR, Nov 2021), we created the E-liability Institute to help companies, governments, and nonprofits implement the method. The Institute’s mission is to test and validate the method, and develop...  View Details
Keywords: Decarbonization; Carbon Footprint; Supply Chain; Environmental Sustainability; Environmental Accounting
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  • 2023
  • Working Paper

Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation
By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to...  View Details
Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior
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  • May 2023 (Revised June 2023)
  • Case

Harvard University and Urban Mining Industries: Decarbonizing the Supply Chain
By: Shirley Lu and Robert S. Kaplan
The case describes Harvard University’s consideration to decarbonize its supply chain by replacing cement with a low-carbon substitute called Pozzotive®. Developed and produced by Urban Mining Industries, Pozzotive® is a ground-glass material made with post-consumer...  View Details
Keywords: Carbon Emissions; Blockchain; Supply Chain; Green Technology; Climate Change; Environmental Sustainability
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  • 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
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  • April 2023
  • Article

The Subjective Expected Utility Approach and a Framework for Defining Project Risk in Terms of Novelty and Feasibility—A Response to Franzoni and Stephan (2023), ‘Uncertainty and Risk-Taking in Science’
By: Jacqueline N. Lane
In their Discussion Paper, Franzoni and Stephan (F&S, 2023) discuss the shortcomings of existing peer review models in shaping the funding of risky science. Their discussion offers a conceptual framework for incorporating risk into peer review models of research...  View Details
Keywords: Risk and Uncertainty; Research; Resource Allocation; Perception
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  • March–April 2023
  • Article

Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market...  View Details
Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
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  • January 2023
  • Case

EKI Energy Services: One Billion Carbon Credits
By: George Serafeim
Within nine months from the time of its Initial Public Offering (IPO) in April of 2021, EKI Energy Services (EKI) shares had increased by more than 8,000%. Equally explosive was the growth of the company’s revenues and Earnings Before Interest, Taxes and Depreciation...  View Details
Keywords: Carbon Credits; Carbon Emissions; Growth; Business Analysis; Environmental Sustainability; Corporate Valuation; Climate Change; Accounting; Valuation; Transition; Renewable Energy; Analysis; Product Positioning; India
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  • 2023
  • Working Paper

The Subjective Expected Utility Approach and a Framework for Defining Project Risk in Terms of Novelty and Feasibility—A Response to Franzoni and Stephan (2023), ‘Uncertainty and Risk-Taking in Science’
By: Jacqueline N. Lane
In their Discussion Paper, Franzoni and Stephan (F&S, 2023) discuss the shortcomings of existing peer review models in shaping the funding of risky science. Their discussion offers a conceptual framework for incorporating risk into peer review models of research...  View Details
Keywords: Risk and Uncertainty; Research; Resource Allocation; Perception
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  • 2022
  • Article

Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations
By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
A critical problem in the field of post hoc explainability is the lack of a common foundational goal among methods. For example, some methods are motivated by function approximation, some by game theoretic notions, and some by obtaining clean visualizations. This...  View Details
Keywords: Mathematical Methods; Decision Choices and Conditions; Analytics and Data Science
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  • October 2022 (Revised August 2023)
  • Case

Founders First Capital Partners: An Approach to Capital Access Equity
By: Brian Trelstad, Mel Martin and Amy Klopfenstein
In June 2021, Kim T. Folsom, the founder and CEO of revenue-based financing firm Founders First Capital Partners (FFCP), must decide whether to issue another loan to OnShore Technology Group, an up-and-coming software validation company. FFCP provided revenue-based...  View Details
Keywords: Finance; Financial Instruments; Financing and Loans; Interest Rates; Investment Return; Revenue; Capital; Financial Services Industry; North and Central America; United States
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  • 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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  • September 2022
  • Article

Health Externalities and Policy: The Role of Social Preferences
By: Laura Alfaro, Ester Faia, Nora Lamersdorf and Farzad Saidi
Social preferences facilitate the internalization of health externalities, for example by reducing mobility during a pandemic. We test this hypothesis using mobility data from 258 cities worldwide alongside experimentally validated measures of social preferences....  View Details
Keywords: Social Preferences; Pandemics; Mobility; Health Externalities; Mitigation Policies; Health Pandemics; Cooperation; Behavior; Policy
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  • September–October 2022
  • Article

Seeking Purity, Avoiding Pollution: Strategies for Moral Career Building
By: Erin Reid and Lakshmi Ramarajan
This study builds theory on how people construct moral careers. Analyzing interviews with 102 journalists, we show how people build moral careers by seeking jobs that allow them to fulfill both the institution’s moral obligations and their own material aims. We...  View Details
Keywords: Personal Development and Career; Moral Sensibility
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  • June 2022
  • Teaching Note

Bespoken Spirits: Disrupting Distilling
By: Benjamin C. Esty and Daniel Fisher
Teaching Note for HBS Case No. 721-419. On October 7, 2020, Bespoken Spirits publicly announced it had received $2.6 million of seed funding for its “sustainable maturation process,” a process that could produce award-winning whiskeys in just days rather than years...  View Details
Keywords: B2B Vs. B2C; Technological Innovation; Business Startups; Cost Management; Business Model; Consumer Products Industry; Food and Beverage Industry; Service Industry
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  • 2022
  • Conference Presentation

Towards the Unification and Robustness of Post hoc Explanation Methods
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...  View Details
Keywords: AI and Machine Learning
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  • May 2022
  • Article

Embracing Field Studies as a Tool for Learning
By: Jon M. Jachimowicz
Field studies in social psychology tend to focus on validating existing insights. In addition to learning from the laboratory and bringing those insights to the field—which researchers currently favour—we should also conduct field studies that aim to learn in the field...  View Details
Keywords: Field Studies; Social Psychology; Learning
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