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- All HBS Web
(12,422)
- Faculty Publications (1,627)
- September 2023
- Article
Measuring Time Use in Rural India: Design and Validation of a Low-Cost Survey Module
By: Erica Field, Rohini Pande, Natalia Rigol, Simone Schaner, Elena Stacy and Charity Troyer Moore
Time use data can help us understand individual labor supply choices, especially
for women who often provide unpaid care and home production. Although
enumerator-assisted diary-based time use data collection is suitable for
low-literacy populations, it is costly and... View Details
Field, Erica, Rohini Pande, Natalia Rigol, Simone Schaner, Elena Stacy, and Charity Troyer Moore. "Measuring Time Use in Rural India: Design and Validation of a Low-Cost Survey Module." Journal of Development Economics 164 (September 2023): 103105.
- September 2023
- Case
The Meteoric Rise of Skims
Since its founding in 2019 by Kim Kardashian and Jens Grede, Skims, a solutions-oriented brand creating the next generation of underwear, loungewear, and shapewear with an eye toward body-type and skin-tone inclusivity, has experienced a meteoric rise. Kardashian, who... View Details
Keywords: Brand; Branding; Direct-to-consumer; DTC; Influencers; Influencer Marketing; Fashion; Growth; Direct Marketing; Influence; Reputation; Social Inference; Consumer Goods; Consumer Products; Female Entrepreneur; Female Protagonist; Entrepreneurship And Strategy; Brand & Product Management; Competitive Advantage; Online Followers; Retail; Retail Formats; Retailing; Online Retail; Celebrities; Celebrity; Celebrity Endorsement; Go To Market Strategy; Apparel; Startup Marketing; Startups; Social Influencers; Brands and Branding; Growth and Development Strategy; Growth Management; Distribution Channels; Digital Marketing; Advertising; Power and Influence; Social Media; Fashion Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
Israeli, Ayelet, Jill Avery, and Leonard A. Schlesinger. "The Meteoric Rise of Skims." Harvard Business School Case 524-023, September 2023.
- September–October 2023
- Article
The New Era of Industrial Policy Is Here
By: Willy C. Shih
Governments around the world are increasingly intervening in the private sector through industrial policies designed to help domestic sectors reach goals that markets alone are unlikely to achieve. Companies in targeted sectors—such as automakers, energy companies, and... View Details
Keywords: Policy; Government and Politics; Business and Government Relations; Research and Development; Economic Sectors
Shih, Willy C. "The New Era of Industrial Policy Is Here." Harvard Business Review 101, no. 5 (September–October 2023): 66–75.
- August 2023
- Case
BYD, China, and Global Electric Vehicle Rivalry
By: Cynthia A. Montgomery and Max Hancock
In 2023, BYD, a Chinese electric vehicle (EV) maker, surpassed Tesla to become the world's best-selling EV brand. BYD began selling mobile phone batteries in 1995, acquired a license to sell vehicles in 2002, and spent two decades building its EV brand, growing its... View Details
Keywords: Competition; Competitive Strategy; Expansion; Segmentation; Vertical Integration; Market Participation; Environmental Sustainability; Auto Industry; Electronics Industry; China; Europe; United States; Japan; South Korea
Montgomery, Cynthia A., and Max Hancock. "BYD, China, and Global Electric Vehicle Rivalry." Harvard Business School Case 724-358, August 2023.
- August 2023
- Case
Beamery: Using Skills and AI to Modernize HR
By: Boris Groysberg, Alexis Lefort, Susan Pinckney and Carolina Bartunek
Unicorn human relationships startup Beamery evaluates it's growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management industry View Details
Keywords: Acquisition; Business Growth and Maturation; Business Startups; Competency and Skills; Experience and Expertise; Talent and Talent Management; Customers; Nationality; Learning; Entrepreneurship; Employee Relationship Management; Recruitment; Retention; Selection and Staffing; Values and Beliefs; Cross-Cultural and Cross-Border Issues; Analytics and Data Science; Applications and Software; Disruptive Innovation; Technological Innovation; Job Offer; Job Search; Job Design and Levels; Employment; Human Capital; Europe; United Kingdom; United States
Groysberg, Boris, Alexis Lefort, Susan Pinckney, and Carolina Bartunek. "Beamery: Using Skills and AI to Modernize HR." Harvard Business School Case 424-004, August 2023.
- July–August 2023
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to... View Details
Keywords: Experiments; Pricing And Revenue Management; Retailing; Demand Estimation; Pricing Algorithm; Marketing; Price; Demand and Consumers; Mathematical Methods
Ferreira, Kris, and Emily Mower. "Demand Learning and Pricing for Varying Assortments." Manufacturing & Service Operations Management 25, no. 4 (July–August 2023): 1227–1244. (Finalist, Practice-Based Research Competition, MSOM (2021) and Finalist, Revenue Management & Pricing Section Practice Award, INFORMS (2019).)
- 2023
- Working Paper
Much Ado About Nothing? Overreaction to Random Regulatory Audits
By: Samuel Antill and Joseph Kalmenovitz
Regulators often audit firms to detect non-compliance. Exploiting a natural experiment in the lobbying industry, we show that firms overreact to audits and this response distorts prices and reduces welfare. Each year, federal regulators audit a random sample of... View Details
Antill, Samuel, and Joseph Kalmenovitz. "Much Ado About Nothing? Overreaction to Random Regulatory Audits." Working Paper, August 2023.
- August 2023
- Case
Reimagining Hindustan Unilever (A)
By: Sunil Gupta and Rachna Tahilyani
In the fall of 2019, the CEO and MD of Hindustan Unilever (HUL), India’s largest fast-moving consumer goods (FMCG) firm, is wondering what to do about their experiments to digitize distribution. Despite three years of intense efforts, their apps to empower retailers... View Details
Keywords: Experimentation; Digital Transformation; Digital Strategy; Leading Change; Distribution; Decisions; Organizational Change and Adaptation; Consumer Behavior; E-commerce; Competition; Performance; Business Strategy; Marketing; Transformation; Consumer Products Industry; Asia; India
Gupta, Sunil, and Rachna Tahilyani. "Reimagining Hindustan Unilever (A)." Harvard Business School Case 524-020, August 2023.
- 2025
- Working Paper
Managing Remote Work Quality: Evidence from Auditing Management Systems Standards
By: Ashley Palmarozzo, Michael W. Toffel and Melissa Ouellet
Remote work has become more common, providing operational flexibility and productivity benefits, but questions remain about whether and how it affects work quality. We investigate the quality effects of remote work in a context in which remote work separates workers... View Details
Keywords: Audit; Auditing; Remote Work; Compliance; Assessment; Environment; Management Systems; Quality Management; Quality Management System; Quality; Operations; Supply Chain Management; Environmental Management; Safety
Palmarozzo, Ashley, Michael W. Toffel, and Melissa Ouellet. "Managing Remote Work Quality: Evidence from Auditing Management Systems Standards." Harvard Business School Working Paper, No. 24-002, July 2023. (Revised February 2025.)
- July 2023 (Revised July 2024)
- Case
Miracle Therapeutics: Negotiating an IP License (A)
By: Satish Tadikonda, Michael Singer, William Marks and Wendi Yajnik
(General Experience Case) Beth Sharp and Jennifer Brilliant founded Miracle Therapeutics based on intellectual property developed by Brilliant and her post-doctoral student, John Supreme, in Brilliant’s lab at Elite University (EU). Miracle will have to obtain a... View Details
Tadikonda, Satish, Michael Singer, William Marks, and Wendi Yajnik. "Miracle Therapeutics: Negotiating an IP License (A)." Harvard Business School Case 824-020, July 2023. (Revised July 2024.)
- July 2023
- Article
Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts
By: Raghabendra P. KC, Vincent Mak and Elie Ofek
We study how payment decision timing—before versus after product delivery—influences consumer payment under pay-what-you-want pricing. We focus on situations where there is minimal change in consumer uncertainty regarding the product before versus after receiving it.... View Details
KC, Raghabendra P., Vincent Mak, and Elie Ofek. "Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts." Journal of Marketing 87, no. 4 (July 2023): 618–635.
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- July 2023
- Article
So, Who Likes You? Evidence from a Randomized Field Experiment
By: Ravi Bapna, Edward McFowland III, Probal Mojumder, Jui Ramaprasad and Akhmed Umyarov
With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by... View Details
Keywords: Online Dating; Internet and the Web; Analytics and Data Science; Gender; Emotions; Social and Collaborative Networks
Bapna, Ravi, Edward McFowland III, Probal Mojumder, Jui Ramaprasad, and Akhmed Umyarov. "So, Who Likes You? Evidence from a Randomized Field Experiment." Management Science 69, no. 7 (July 2023): 3939–3957.
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity... View Details
Gabaix, Xavier, and Thomas Graeber. "The Complexity of Economic Decisions." Harvard Business School Working Paper, No. 24-049, February 2024.
- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- June 2023
- Exercise
Experimenting with Algorithm Resume Screening
By: Michael Luca, Jesse M. Shapiro, Adrian Obleton, Evelyn Ramirez and Nathan Sun
- 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
Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.
- June 2023
- Article
Do Job Seekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures
By: Jung Ho Choi, Joseph Pacelli, Kristina M. Rennekamp and Sorabh Tomar
We examine how information about the diversity of a potential employer's workforce affects individuals’ job-seeking behavior. We embed a field experiment in job recommendation emails from a leading career advice agency in the U.S. The experimental treatment involves... View Details
Choi, Jung Ho, Joseph Pacelli, Kristina M. Rennekamp, and Sorabh Tomar. "Do Job Seekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures." Journal of Accounting Research 61, no. 3 (June 2023): 695–735.
- 2023
- Article
Provable Detection of Propagating Sampling Bias in Prediction Models
By: Pavan Ravishankar, Qingyu Mo, Edward McFowland III and Daniel B. Neill
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipeline but also to understand the downstream impacts of bias across stages. Here we consider... View Details
Ravishankar, Pavan, Qingyu Mo, Edward McFowland III, and Daniel B. Neill. "Provable Detection of Propagating Sampling Bias in Prediction Models." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (2023): 9562–9569. (Presented at the 37th AAAI Conference on Artificial Intelligence (2/7/23-2/14/23) in Washington, DC.)