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    • All HBS Web  (6,649)
      • Faculty Publications  (82)

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      Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
      Soul and Machine (Learning)
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      • April 2021
      • Article

      Work-From-Anywhere: The Productivity Effects of Geographical Flexibility

      By: Prithwiraj Choudhury, Cirrus Foroughi and Barbara Larson
      An emerging form of remote work allows employees to work-from-anywhere, so that the worker can choose to live in a preferred geographic location. While traditional work-from-home (WFH) programs offer the worker temporal flexibility, work-from-anywhere (WFA) programs...  View Details
      Keywords: Geographic Flexibility; Work-from-anywhere; Remote Work; Telecommuting; Geographic Mobility; Uspto; Employees; Geographic Location; Performance Productivity
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      Choudhury, Prithwiraj, Cirrus Foroughi, and Barbara Larson. "Work-From-Anywhere: The Productivity Effects of Geographical Flexibility." Strategic Management Journal 42, no. 4 (April 2021): 655–683.
      • 2021
      • Working Paper

      Time Dependency, Data Flow, and Competitive Advantage

      By: Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu and Karim R. Lakhani
      Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government...  View Details
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      Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
      • February 2021
      • Tutorial

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael Toffel and Natalie Epstein
      This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and...  View Details
      Keywords: Machine Learning; Statistics; Experiments; Forecasting and Prediction; Performance Evaluation
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      Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021.
      • February 2021
      • Case

      Digital Manufacturing at Amgen

      By: Shane Greenstein, Kyle Myers and Sarah Mehta
      This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is...  View Details
      Keywords: Digital Technologies; Change; Change Management; Decision Making; Cost vs Benefits; Decisions; Information; Data and Data Sets; Innovation and Invention; Innovation and Management; Innovation Leadership; Innovation Strategy; Technological Innovation; Jobs and Positions; Knowledge; Leadership; Organizational Culture; Science; Strategy; Technology; Technology Adoption; Biotechnology Industry; Pharmaceutical Industry; United States; California; Puerto Rico; Rhode Island
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      Greenstein, Shane, Kyle Myers, and Sarah Mehta. "Digital Manufacturing at Amgen." Harvard Business School Case 621-008, February 2021.
      • January 2021
      • Case

      Anodot: Autonomous Business Monitoring

      By: Antonio Moreno and Danielle Golan
      Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product...  View Details
      Keywords: Technology Platform; Online Technology; Knowledge Sharing; Information Management; Sales; Value Creation; Product Positioning; Israel
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      Moreno, Antonio, and Danielle Golan. "Anodot: Autonomous Business Monitoring." Harvard Business School Case 621-084, January 2021.
      • January 2021 (Revised March 2021)
      • Case

      THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

      By: Jill Avery, Ayelet Israeli and Emma von Maur
      THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...  View Details
      Keywords: Data; Data Analytics; Artificial Intelligence; Ai; Ai Algorithms; Ai Creativity; Fashion; Retail; Retail Analytics; Digital Marketing; E-commerce; E-commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Data and Data Sets; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Online Advertising; Online Technology; Mobile Technology; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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      Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
      • January 2021
      • Article

      Machine Learning for Pattern Discovery in Management Research

      By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
      Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect...  View Details
      Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; Roc Curve; Confusion Matrix; Partial Dependence Plots
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      Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
      • December 2020 (Revised February 2021)
      • Case

      IBM Watson at MD Anderson Cancer Center

      By: Shane Greenstein, Mel Martin and Sarkis Agaian
      After discovering that their cancer diagnostic tool, designed to leverage the cloud computing power of IBM Watson, needed greater integration into the clinical processes at the MD Anderson Cancer Center, the development team had difficult choices to make. The Oncology...  View Details
      Keywords: Decision Making; Innovation Strategy; Knowledge Management; Knowledge Use and Leverage; Operations; Failure; Technology; Information Technology; Software; Health Care and Treatment; Product Development; Health Industry; Information Technology Industry; Technology Industry; United States; Houston; Texas
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      Greenstein, Shane, Mel Martin, and Sarkis Agaian. "IBM Watson at MD Anderson Cancer Center." Harvard Business School Case 621-022, December 2020. (Revised February 2021.)
      • Article

      Soul and Machine (Learning)

      By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
      Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to...  View Details
      Keywords: Machine Learning; Marketing Applications; Knowledge; Technological Innovation; Core Relationships; Marketing
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      Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Marketing Letters 31, no. 4 (December 2020): 393–404.
      • 2020
      • Working Paper

      Translating Information into Action: A Public Health Experiment in Bangladesh

      By: Reshmaan Hussam, Kailash Pandey, Abu Shonchoy and Chikako Yamauchi
      Standard models of technology adoption posit learning as the basis of adoption. However, hygiene campaigns centered around information provision have been overwhelmingly unsuccessful in changing behavior and improving child health across the developing world. We design...  View Details
      Keywords: Handwashing; Public Health; Health; Information; Behavior; Change
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      Hussam, Reshmaan, Kailash Pandey, Abu Shonchoy, and Chikako Yamauchi. "Translating Information into Action: A Public Health Experiment in Bangladesh." Working Paper, December 2020.
      • November 2020
      • Teaching Note

      DayTwo: Going to Market with Gut Microbiome

      By: Ayelet Israeli
      Teaching Note for HBS Case No. 519-010. DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals....  View Details
      Keywords: Start-up Growth; Startup; Positioning; Targeting; Go To Market Strategy; B2b Vs. B2c; B2b2c; Health & Wellness; Ai; Machine Learning; Female Ceo; Female Protagonist; Science-based; Science And Technology Studies; Ecommerce; Applications; Dtc; Direct To Consumer Marketing; Us Health Care; "usa,"; Innovation; Pricing; Business Growth; Segmentation; Distribution Channels; Growth and Development Strategy; Business Startups; Science-Based Business; Health; Innovation and Invention; Marketing; Technology; Business Growth and Maturation; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
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      Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Teaching Note 521-052, November 2020.
      • 2020
      • Working Paper

      (When) Does Appearance Matter? Evidence from a Randomized Controlled Trial

      By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker
      While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between...  View Details
      Keywords: Behavioral Economics; Coronavirus; Discrimination; Homophily; Labor Market Mobility; Limited Attention; Resumes; Personal Characteristics; Prejudice and Bias
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      Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020.
      • Article

      Conversational Receptiveness: Expressing Engagement with Opposing Views

      By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
      We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then...  View Details
      Keywords: Receptiveness; Natural Language Processing; Disagreement; Interpersonal Communication; Relationships; Conflict Management
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      Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
      • August 2020 (Revised September 2020)
      • Technical Note

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools...  View Details
      Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Data and Data Sets; Analysis; Mathematical Methods
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      Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
      • August 2020
      • Article

      Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation

      By: Prithwiraj Choudhury, Evan Starr and Rajshree Agarwal
      The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic...  View Details
      Keywords: Machine Learning; Bias; Human Capital; Management; Strategy
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      Choudhury, Prithwiraj, Evan Starr, and Rajshree Agarwal. "Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation." Strategic Management Journal 41, no. 8 (August 2020): 1381–1411.
      • July 2020 (Revised September 2020)
      • Case

      MobSquad

      By: Prithwiraj Choudhury, William R. Kerr and Susie L. Ma
      Irfhan Rawji (MBA 2004) launched MobSquad in October 2018 to help American tech start-ups retain hard-to-find talent, many of whom struggled with U.S. work visa issues, such as software engineers with experience in artificial intelligence, machine learning, or data...  View Details
      Keywords: Work Visas; H1-b; Business Ventures; Business Startups; Labor; Human Capital; Human Resources; Crisis Management; Employment Industry; Canada; United States
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      Choudhury, Prithwiraj, William R. Kerr, and Susie L. Ma. "MobSquad." Harvard Business School Case 821-010, July 2020. (Revised September 2020.)
      • 2020
      • Article

      A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?

      By: Doug J. Chung, Byungyeon Kim and Niladri B. Syam
      Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role...  View Details
      Keywords: Sales Compensation; Sales Management; Sales Strategy; Principal-agent Theory; Structural Econometrics; Field Experiments; Machine Learning; Artificial Intelligence; Salesforce Management; Compensation and Benefits; Motivation and Incentives
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      Chung, Doug J., Byungyeon Kim, and Niladri B. Syam. "A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?" Foundations and Trends® in Marketing 14, no. 1 (2020): 1–52.
      • April 29, 2020
      • Article

      The Case for AI Insurance

      By: Ram Shankar Siva Kumar and Frank Nagle
      When organizations place machine learning systems at the center of their businesses, they introduce the risk of failures that could lead to a data breach, brand damage, property damage, business interruption, and in some cases, bodily harm. Even when companies are...  View Details
      Keywords: Artificial Intelligence; Machine Learning; Cybersecurity; Online Technology; Safety; Insurance
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      Kumar, Ram Shankar Siva, and Frank Nagle. "The Case for AI Insurance." Harvard Business Review Digital Articles (April 29, 2020).
      • April 2020
      • Teaching Note

      Tailor Brands: Artificial Intelligence-Driven Branding

      By: Jill Avery
      Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills...  View Details
      Keywords: Marketing; Brands and Branding; Marketing Strategy; Advertising Industry; Technology Industry; United States; North America
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      Avery, Jill. "Tailor Brands: Artificial Intelligence-Driven Branding." Harvard Business School Teaching Note 520-103, April 2020.
      • April 2020 (Revised October 2020)
      • Case

      Unilever's Response to the Future of Work

      By: William R. Kerr, Emilie Billaud and Mette Fuglsang Hjortshoej
      In February 2020, Nick Dalton, executive vice president HR business transformation at Unilever, reflected on the changing nature of work marked by rapid advances in artificial intelligence, machine learning, and automation. Launched in 2016, Unilever’s Future of Work...  View Details
      Keywords: Change Management; Human Capital; Organizational Change and Adaptation; Mission and Purpose; Organizational Structure; Transformation; Human Resources; Consumer Products Industry; Europe
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      Kerr, William R., Emilie Billaud, and Mette Fuglsang Hjortshoej. "Unilever's Response to the Future of Work." Harvard Business School Case 820-104, April 2020. (Revised October 2020.)
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      Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
      Soul and Machine (Learning)
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