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      • March 2023
      • Article

      Learning to Successfully Hire in Online Labor Markets

      By: Marios Kokkodis and Sam Ransbotham
      Hiring in online labor markets involves considerable uncertainty: which hiring choices are more likely to yield successful outcomes and how do employers adjust their hiring behaviors to make such choices? We argue that employers will initially explore the value of...  View Details
      Keywords: Selection and Staffing; Analysis; Decision Choices and Conditions
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      Kokkodis, Marios, and Sam Ransbotham. "Learning to Successfully Hire in Online Labor Markets." Management Science 69, no. 3 (March 2023): 1597–1614.
      • 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.
      • 2022
      • 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 importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of tools...  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.
      • 2022
      • Working Paper

      Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence

      By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
      Even if algorithms make better predictions than humans on average, humans may sometimes have “private” information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by...  View Details
      Keywords: Cognitive Biases; Algorithm Transparency; Forecasting and Prediction; Behavior; AI and Machine Learning; Analytics and Data Science; Cognition and Thinking
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      Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, December 2022.
      • 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
      • 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
      • Case

      Pointillist: Building a Business in Customer Journey Analytics

      By: David C. Edelman
      Growth challenges in building a SAAS business using AI for Customer Experience analysis.  View Details
      Keywords: AI; Customer Experience; Analytics; Marketing; Entrepreneurship; United States
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      Edelman, David C. "Pointillist: Building a Business in Customer Journey Analytics." Harvard Business School Case 523-026, September 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; Marketing; 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.)
      • August 2022
      • Supplement

      Zalora: Data-Driven Pricing Recommendations

      By: Ayelet Israeli
      This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the...  View Details
      Keywords: Pricing; Pricing Algorithms; Dynamic Pricing; Ecommerce; Pricing Strategy; Pricing And Revenue Management; Apparel; Singapore; Startup; Demand Estimation; Data Analysis; Data Analytics; Exercise; Price; Internet and the Web; Apparel and Accessories Industry; Retail Industry; Fashion Industry; Singapore
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      Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
      • 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...  View Details
      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
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      Ascarza, Eva, Ayelet Israeli, and Celine Chammas. "Retail Media Networks." Harvard Business School Background Note 523-029, August 2022.
      • 2022
      • Article

      Data Poisoning Attacks on Off-Policy Evaluation Methods

      By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
      Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats...  View Details
      Keywords: Analytics and Data Science; Cybersecurity; Mathematical Methods
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      Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Special Issue on Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022). Proceedings of Machine Learning Research (PMLR) 180 (2022): 1264–1274.
      • 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...  View Details
      Keywords: Prejudice and Bias; Mathematical Methods; Research; Analytics and Data Science
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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
      • Book

      Purpose + Profit: How Business Can Lift Up the World

      By: George Serafeim
      The roadmap and best practices to reap the enormous value that can emerge when your business prioritizes social and environmental goals—such as climate change, diversity and inclusion, and sustainability—right alongside the pursuit of profit.

      We not only...  View Details
      Keywords: ESG (Environmental, Social, Governance) Performance; Profitability; Business And Society; Organizations; Mission and Purpose; Goals and Objectives; Social Issues; Environmental Sustainability; Value Creation; Organizational Change and Adaptation
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      Serafeim, George. Purpose + Profit: How Business Can Lift Up the World. New York: HarperCollins Leadership, 2022.
      • 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...  View Details
      Keywords: Analytics and Data Science; Research
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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...  View Details
      Keywords: Sharing Economy; Airbnb; Property Demand; Computer Vision; Deep Learning; Image Feature Extraction; Content Engineering; Property; Marketing; Demand and Consumers
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      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.
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