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      • March 2023 (Revised April 2024)
      • Case

      Allianz Türkiye: Adapting to Climate Change

      By: John D. Macomber and Fares Khrais
      Allianz Turkey is a property casualty insurance company operating in a region experiencing increasing losses from natural catastrophe events related to climate change, for example hail, wildfire, and flooding. There are also substantial other natural catastrophe... View Details
      Keywords: Insurance And Reinsurance; Natural Disasters; Turkey; Insurance; Climate Change; Analytics and Data Science; Insurance Industry; Financial Services Industry; Turkey
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      Macomber, John D., and Fares Khrais. "Allianz Türkiye: Adapting to Climate Change." Harvard Business School Case 223-074, March 2023. (Revised April 2024.)
      • 2023
      • Chapter

      Marketing Through the Machine’s Eyes: Image Analytics and Interpretability

      By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
      he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
      Keywords: Transparency; Marketing Research; Algorithmic Bias; AI and Machine Learning; Marketing
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      Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
      • 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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      Aouad, Ali, Adam Elmachtoub, Kris J. Ferreira, and Ryan McNellis. "Market Segmentation Trees." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 648–667.
      • 2023
      • Working Paper

      Senior Team Emotional Dynamics and Strategic Decision Making at a Platform Transition

      By: Timo O. Vuori and Michael L. Tushman
      Based on an inductive case study, we develop an emotional-temporal process model of an incumbent’s strategic decision making at a platform transition. We describe the senior team’s emotional response to this transition and the impact of these emotions on their... View Details
      Keywords: Emotions; Decision Choices and Conditions; Transition; Digital Platforms
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      Vuori, Timo O., and Michael L. Tushman. "Senior Team Emotional Dynamics and Strategic Decision Making at a Platform Transition." Harvard Business School Working Paper, No. 23-054, March 2023.
      • January–February 2023
      • Article

      Forecasting COVID-19 and Analyzing the Effect of Government Interventions

      By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
      We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
      Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
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      Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
      • February 2023
      • Article

      National Models of Climate Governance Among Major Emitters

      By: Johnathan Guy, Esther Shears and Jonas Meckling
      National climate institutions structure the process of climate mitigation policymaking and shape climate policy ambition and performance. Countries have, for example, been building science bodies, passing climate laws and creating new agencies. Here we provide the... View Details
      Keywords: Environmental Regulation; Policy; Analytics and Data Science; Climate Change
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      Guy, Johnathan, Esther Shears, and Jonas Meckling. "National Models of Climate Governance Among Major Emitters." Nature Climate Change 13, no. 2 (February 2023): 189–195.
      • 2023
      • Article

      Evaluating Explainability for Graph Neural Networks

      By: Chirag Agarwal, Owen Queen, Himabindu Lakkaraju and Marinka Zitnik
      As explanations are increasingly used to understand the behavior of graph neural networks (GNNs), evaluating the quality and reliability of GNN explanations is crucial. However, assessing the quality of GNN explanations is challenging as existing graph datasets have no... View Details
      Keywords: Analytics and Data Science
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      Agarwal, Chirag, Owen Queen, Himabindu Lakkaraju, and Marinka Zitnik. "Evaluating Explainability for Graph Neural Networks." Art. 114. Scientific Data 10 (2023).
      • 2023
      • Article

      Experimental Evaluation of Individualized Treatment Rules

      By: Kosuke Imai and Michael Lingzhi Li
      The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
      Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
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      Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
      • 2023
      • Working Paper

      Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

      By: Daniel Yue, Paul Hamilton and Iavor Bojinov
      Predictive model development is understudied despite its centrality in modern artificial intelligence and machine learning business applications. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms)... View Details
      Keywords: Analytics and Data Science
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      Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
      • December 2022
      • Article

      Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations

      By: Eva Flavia Martínez Orbegozo, Jorrit de Jong, Hannah Riley Bowles, Amy Edmondson, Anahide Nahhal and Lisa Cox
      To address complex social challenges, it is widely recognized that leaders from public, for-profit, and civic organizations should join forces. Yet, well-intended collaborators often struggle to achieve alignment and fail to gain traction in their joint efforts. This... View Details
      Keywords: Groups and Teams; Social and Collaborative Networks; Goals and Objectives
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      Orbegozo, Eva Flavia Martínez, Jorrit de Jong, Hannah Riley Bowles, Amy Edmondson, Anahide Nahhal, and Lisa Cox. "Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations." Journal of Applied Behavioral Science 58, no. 4 (December 2022): 595–645.
      • 2022
      • Article

      OpenXAI: Towards a Transparent Evaluation of Model Explanations

      By: Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik and Himabindu Lakkaraju
      While several types of post hoc explanation methods have been proposed in recent literature, there is very little work on systematically benchmarking these methods. Here, we introduce OpenXAI, a comprehensive and extensible opensource framework for evaluating and... View Details
      Keywords: Measurement and Metrics; Analytics and Data Science
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      Agarwal, Chirag, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, and Himabindu Lakkaraju. "OpenXAI: Towards a Transparent Evaluation of Model Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • 2022
      • Working Paper

      The Limits of Decentralized Administrative Data Collection: Experimental Evidence from Colombia

      By: Natalia Garbiras-Diaz and Tara Slough
      States collect vast amounts of data for use in policymaking and public administration. To do so, central governments frequently solicit data from decentralized bureaucrats. Because central governments use these data in policymaking, decentralized bureaucrats may face... View Details
      Keywords: Decentralization; Policy-making; Policy/economics; Policy Evaluation; Governance; Government Administration; Government and Politics; Government Legislation; Policy; Public Opinion; Analytics and Data Science; Latin America; South America; Colombia
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      Garbiras-Diaz, Natalia, and Tara Slough. "The Limits of Decentralized Administrative Data Collection: Experimental Evidence from Colombia." Working Paper, December 2022.
      • December 2022
      • Article

      The Rise of People Analytics and the Future of Organizational Research

      By: Jeff Polzer
      Organizations are transforming as they adopt new technologies and use new sources of data, changing the experiences of employees and pushing organizational researchers to respond. As employees perform their daily activities, they generate vast digital data. These data,... View Details
      Keywords: Organizational Change and Adaptation; Analytics and Data Science; Technology Adoption; Employees
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      Polzer, Jeff. "The Rise of People Analytics and the Future of Organizational Research." Art. 100181. Research in Organizational Behavior 42 (December 2022). (Supplement.)
      • 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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      Han, Tessa, Suraj Srinivas, and Himabindu Lakkaraju. "Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022). (Best Paper Award, International Conference on Machine Learning (ICML) Workshop on Interpretable ML in Healthcare.)
      • November–December 2022
      • Article

      Your Company Needs a Space Strategy. Now.

      By: Matthew Weinzierl, Prithwiraj (Raj) Choudhury, Tarun Khanna, Alan MacCormack and Brendan Rosseau
      Space is becoming a potential source of value for businesses across a range of sectors, including agriculture, pharmaceuticals, consumer goods, and tourism. To understand what the opportunities are for your company, the authors advise you to consider the four ways in... View Details
      Keywords: Space Strategy; Emerging Markets; Natural Resources; Analytics and Data Science; Organizational Change and Adaptation; Adaptation; Competition; Aerospace Industry
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      Weinzierl, Matthew, Prithwiraj (Raj) Choudhury, Tarun Khanna, Alan MacCormack, and Brendan Rosseau. "Your Company Needs a Space Strategy. Now." Harvard Business Review (November–December 2022): 80–91.
      • November–December 2022
      • Article

      The Value of Descriptive Analytics: Evidence from Online Retailers

      By: Ron Berman and Ayelet Israeli
      Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an... View Details
      Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Marketing; Retail Industry
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      Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Marketing Science 41, no. 6 (November–December 2022): 1074–1096.
      • October 2022
      • Supplement

      Single Earth: Science White Paper Supplement

      By: Rembrand Koning and Emer Moloney
      Science White Paper prepared by Single.Earth to give an overview of the models and solutions it has developed. View Details
      Keywords: Business Startups; Entrepreneurship; Climate Change; Environmental Sustainability; Green Technology; Natural Resources; Pollution; Analytics and Data Science; Marketing; Product Marketing; Product Launch; Product Positioning; Markets; Market Timing; Strategy; Green Technology Industry; Estonia
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      Koning, Rembrand, and Emer Moloney. "Single Earth: Science White Paper Supplement." Harvard Business School Supplement 723-389, October 2022.
      • October 2022
      • Case

      Single.Earth

      By: Rembrand Koning and Emer Moloney
      Estonian greentech company Single.Earth is launching a nature-backed token that is linked to and funds the protection of a specific plot fo land. The first landowners had been onboarded to the company's Digital Twin, a virtual representation of the planet's natural... View Details
      Keywords: Alternative Assets; Business Startups; Entrepreneurship; Climate Change; Environmental Sustainability; Green Technology; Natural Resources; Pollution; Analytics and Data Science; Marketing; Product Marketing; Product Launch; Product Positioning; Markets; Market Timing; Strategy; Green Technology Industry; Estonia
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      Koning, Rembrand, and Emer Moloney. "Single.Earth." Harvard Business School Case 723-388, October 2022.
      • October 2022 (Revised December 2022)
      • Case

      SMART: AI and Machine Learning for Wildlife Conservation

      By: Brian Trelstad and Bonnie Yining Cao
      Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
      Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa
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      Trelstad, Brian, and Bonnie Yining Cao. "SMART: AI and Machine Learning for Wildlife Conservation." Harvard Business School Case 323-036, October 2022. (Revised December 2022.)
      • September 2022 (Revised November 2022)
      • Teaching Note

      PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

      By: Ayelet Israeli
      Teaching Note for HBS Case No. 522-046. View Details
      Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
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      Israeli, Ayelet. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Teaching Note 523-020, September 2022. (Revised November 2022.)
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