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Publications

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    • All HBS Web  (1,112)
      • Faculty Publications  (132)

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      • Article

      Multitasking While Driving: A Time Use Study of Commuting Knowledge Workers to Assess Current and Future Uses

      By: Thomaz Teodorovicz, Andrew L. Kun, Raffaella Sadun and Orit Shaer
      Commuting has enormous impact on individuals, families, organizations, and society. Advances in vehicle automation may help workers employ the time spent commuting in productive work-tasks or wellbeing activities. To achieve this goal, however, we need to develop a...  View Details
      Keywords: In-vehicle User Interfaces; Time-use Study; Automated Vehicles; Knowledge Workers; Commuting
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      Teodorovicz, Thomaz, Andrew L. Kun, Raffaella Sadun, and Orit Shaer. "Multitasking While Driving: A Time Use Study of Commuting Knowledge Workers to Assess Current and Future Uses." International Journal of Human-Computer Studies 162 (June 2022).
      • Article

      Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

      By: Eva Ascarza and Ayelet Israeli

      An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”...  View Details

      Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
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      Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
      • 2022
      • Working Paper

      Can a Website Bring Unemployment Down? Experimental Evidence from France

      By: Aïcha Ben Dhia, Bruno Crépon, Esther Mbih, Louise Paul-Delvaux, Bertille Picard and Vincent Pons
      We evaluate the impact of an online platform giving job seekers tips to improve their search and recommendations of new occupations and locations to target, based on their personal data and labor market data. Our experiment used an encouragement design and was...  View Details
      Keywords: Online Platform; Digital Platform; Unemployment; Encouragement Design; Job Search; Jobs and Positions; Internet and the Web; Well-being; Outcome or Result; France
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      Ben Dhia, Aïcha, Bruno Crépon, Esther Mbih, Louise Paul-Delvaux, Bertille Picard, and Vincent Pons. "Can a Website Bring Unemployment Down? Experimental Evidence from France." NBER Working Paper Series, No. 29914, April 2022.
      • March 2022
      • Article

      Learning to Rank an Assortment of Products

      By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
      We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue...  View Details
      Keywords: Online Learning; Product Ranking; Assortment Optimization; Learning; Internet and the Web; Product Marketing; Consumer Behavior; E-commerce
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      Ferreira, Kris, Sunanda Parthasarathy, and Shreyas Sekar. "Learning to Rank an Assortment of Products." Management Science 68, no. 3 (March 2022): 1828–1848.
      • 2022
      • Working Paper

      E-commerce During COVID: Stylized Facts from 47 Economies

      By: Joel Alcedo, Alberto Cavallo, Bricklin Dwyer, Prachi Mishra and Antonio Spilimbergo
      We study e-commerce across 47 economies and 26 industries during the COVID-19 pandemic using aggregated and anonymized transaction-level data from Mastercard, scaled to represent total consumer spending. The share of online transactions in total consumption increased...  View Details
      Keywords: COVID-19 Pandemic; Health Pandemics; Spending; Internet and the Web; Global Range; Analysis; E-commerce
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      Alcedo, Joel, Alberto Cavallo, Bricklin Dwyer, Prachi Mishra, and Antonio Spilimbergo. "E-commerce During COVID: Stylized Facts from 47 Economies." NBER Working Paper Series, No. 29729, February 2022.
      • November 2021 (Revised December 2021)
      • Supplement

      PittaRosso (B): Human and Machine Learning

      By: Ayelet Israeli
      This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case.  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 (B): Human and Machine Learning." Harvard Business School Supplement 522-047, November 2021. (Revised December 2021.)
      • 2021
      • Working Paper

      Who Benefits from Online Gig Economy Platforms?

      By: Christopher Stanton and Catherine Thomas
      This paper estimates the magnitude and distribution of surplus from the knowledge worker gig economy using data from an online labor market. Labor demand elasticities determine workers’ wages, and buyers’ past market experience shapes both their job posting frequency...  View Details
      Keywords: Gig Economy; Knowledge Workers; Online Platforms; Employment; Internet and the Web; Governing Rules, Regulations, and Reforms; Wages
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      Stanton, Christopher, and Catherine Thomas. "Who Benefits from Online Gig Economy Platforms?" NBER Working Paper Series, No. 29477, November 2021.
      • October 2021 (Revised March 2022)
      • Supplement

      PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

      By: Ayelet Israeli and Fabrizio Fantini
      PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once...  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; Retail Industry; Italy
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      Israeli, Ayelet, and Fabrizio Fantini. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Spreadsheet Supplement 522-710, October 2021. (Revised March 2022.)
      • October 2021 (Revised June 2022)
      • Case

      PittaRosso: Artificial Intelligence-Driven Pricing and Promotion

      By: Ayelet Israeli
      PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once...  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; AI; 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 Case 522-046, October 2021. (Revised June 2022.)
      • 2021
      • Working Paper

      How Does Working from Home during COVID-19 Affect What Managers Do? Evidence from Time-Use Studies

      By: Thomaz Teodorovicz, Raffaella Sadun, Andrew L. Kun and Orit Shaer
      We assess how the sudden and widespread shift to working from home (WFH) during the pandemic impacted how managers allocate time throughout their working day. We analyze the results from an online time-use survey with data on 1,192 knowledge workers (out of which 973...  View Details
      Keywords: Time-use; Working-from-home; COVID; COVID-19; Managers; Knowledge Workers; Health Pandemics; Measurement and Metrics; Research and Development
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      Teodorovicz, Thomaz, Raffaella Sadun, Andrew L. Kun, and Orit Shaer. "How Does Working from Home during COVID-19 Affect What Managers Do? Evidence from Time-Use Studies." Harvard Business School Working Paper, No. 22-020, September 2021.
      • September 2021
      • Article

      Joint Problem-solving Orientation in Fluid Cross-boundary Teams

      By: Michaela J. Kerrissey, Anna T. Mayo and Amy C. Edmondson
      Using interviews, a national field survey, and an online laboratory study, we have examined teamwork in fluid cross-boundary teams. Across three studies, we qualitatively discovered and quantitatively explored "joint problem-solving orientation" as a new team factor....  View Details
      Keywords: Problem Solving; Cross-boundary Teams; Groups and Teams; Problems and Challenges; Performance
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      Kerrissey, Michaela J., Anna T. Mayo, and Amy C. Edmondson. "Joint Problem-solving Orientation in Fluid Cross-boundary Teams." Academy of Management Discoveries 7, no. 3 (September 2021): 381–405.
      • 2022
      • Working Paper

      What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data

      By: Alberto Cavallo and Oleksiy Kryvtsov
      We use a detailed micro dataset on product availability to construct a direct high-frequency measure of consumer product shortages during the 2020–2022 pandemic. We document a widespread multi-fold rise in shortages in nearly all sectors early in the pandemic. Over...  View Details
      Keywords: Prices; Stockouts; Inventories; Supply Disruptions; COVID-19 Pandemic; Macroeconomics; Inflation and Deflation; Supply Chain; Disruption; Health Pandemics; Consumer Products Industry; United States; China; Canada; France; Germany; Japan; Spain
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      Cavallo, Alberto, and Oleksiy Kryvtsov. "What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data." NBER Working Paper Series, No. 29209, September 2021.
      • 2021
      • Working Paper

      The Value of Data and Its Impact on Competition

      By: Marco Iansiti
      Common regulatory perspective on the relationship between data, value, and competition in online platforms has increasingly centered on the volume of data accumulated by incumbent firms. This view posits the existence of "data network effects," where more data leads to...  View Details
      Keywords: Online Platforms; Data Network Effects; Analytics and Data Science; Value; Competition
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      Iansiti, Marco. "The Value of Data and Its Impact on Competition." Harvard Business School Working Paper, No. 22-002, July 2021.
      • July 2021
      • Article

      Outsourcing Tasks Online: Matching Supply and Demand on Peer-to-Peer Internet Platforms

      By: Zoë Cullen and Chiara Farronato
      We study the growth of online peer-to-peer markets. Using data from TaskRabbit, an expanding marketplace for domestic tasks at the time of our study, we show that growth varies considerably across cities. To disentangle the potential drivers of growth, we look...  View Details
      Keywords: Two-sided Market; Two-sided Platforms; Peer-to-peer Markets; Platform Strategy; Sharing Economy; Platform Growth; Internet and the Web; Digital Platforms; Strategy; Market Design; Network Effects
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      Cullen, Zoë, and Chiara Farronato. "Outsourcing Tasks Online: Matching Supply and Demand on Peer-to-Peer Internet Platforms." Management Science 67, no. 7 (July 2021).
      • July 2021
      • Article

      The Effect of Price on Firm Reputation

      By: Michael Luca and Oren Reshef
      While a business's reputation can affect its pricing, prices can also affect its reputation. To explore the effect of prices on reputation, we investigate daily data on menu prices and online ratings from a large rating and ordering platform. We find that a price...  View Details
      Keywords: Pricing; Reputation Systems; IT Policy And Management; Economics Of Digital Platforms; Business Ventures; Reputation; Price; Consumer Behavior; Analysis
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      Luca, Michael, and Oren Reshef. "The Effect of Price on Firm Reputation." Management Science 67, no. 7 (July 2021).
      • May 2021
      • Simulation

      Customer Compatibility Exercise Application

      By: Ryan W. Buell
      Customers impose considerable variability on the operating systems of service organizations. They show up when they wish (arrival variability), they ask for different things (request variability), they vary in their willingness and ability to help themselves (effort...  View Details
      Keywords: Customer Compatibility; Customer Relationship Management; Strategy; Service Operations; Service Delivery; Performance Efficiency; Analysis
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      Buell, Ryan W. "Customer Compatibility Exercise Application." Harvard Business School Simulation 620-707, May 2021.
      • May 2021 (Revised February 2022)
      • Teaching Note

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

      By: Ayelet Israeli and Jill Avery
      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; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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      Israeli, Ayelet, and Jill Avery. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Teaching Note 521-097, May 2021. (Revised February 2022.)
      • April 2021 (Revised July 2021)
      • Case

      StockX: The Stock Market of Things (Abridged)

      By: Chiara Farronato, John J. Horton, Annelena Lobb and Julia Kelley
      Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust...  View Details
      Keywords: Markets; Auctions; Bids and Bidding; Demand and Consumers; Consumer Behavior; Analytics and Data Science; Market Design; Digital Platforms; Market Transactions; Marketplace Matching; Supply and Industry; Analysis; Price; Product Marketing; Product Launch; Apparel and Accessories Industry; Fashion Industry; North and Central America; United States; Michigan; Detroit
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      Farronato, Chiara, John J. Horton, Annelena Lobb, and Julia Kelley. "StockX: The Stock Market of Things (Abridged)." Harvard Business School Case 621-107, April 2021. (Revised July 2021.)
      • April 2021
      • Article

      A Model of Multi-Pass Search: Price Search Across Stores and Time

      By: Navid Mojir and K. Sudhir
      In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across...  View Details
      Keywords: Consumer Search; Multi-pass Search; Price Search; Store Search; Spatial Search; Temporal Search; Spatiotemporal Search; Dynamic Structural Models; MPEC; Price Promotions; Store Loyalty; Consumer Behavior; Price; Spending; Marketing; Mathematical Methods
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      Mojir, Navid, and K. Sudhir. "A Model of Multi-Pass Search: Price Search Across Stores and Time." Management Science 67, no. 4 (April 2021): 2126–2150.
      • 2021
      • Article

      Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring

      By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
      Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the...  View Details
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      Sühr, Tom, Sophie Hilgard, and Himabindu Lakkaraju. "Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
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