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- All HBS Web
(1,559)
- News (358)
- Research (871)
- Events (3)
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- Faculty Publications (232)
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- Research Summary
Personal Data in Marketing
By: John A. Deighton
Between 10% and 20% of all marketing activity in the United States, and a smaller proportion internationally, relies on data about individuals, whether personally identifying or pseudonomized. These data flow across a system of established and emerging firms operating... View Details
- 2019
- Working Paper
The Impact of the General Data Protection Regulation on Internet Interconnection
By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on... View Details
Keywords: Personal Data; Privacy Regulation; GDPR; Interconnection Agreements; Internet and the Web; Governing Rules, Regulations, and Reforms; European Union
Zhuo, Ran, Bradley Huffaker, KC Claffy, and Shane Greenstein. "The Impact of the General Data Protection Regulation on Internet Interconnection." NBER Working Paper Series, No. 26481, November 2019.
- March 2021
- Article
The Impact of the General Data Protection Regulation on Internet Interconnection
By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on... View Details
Keywords: Personal Data; Privacy Regulation; GDPR; Interconnection Agreements; Internet and the Web; Governing Rules, Regulations, and Reforms
Zhuo, Ran, Bradley Huffaker, KC Claffy, and Shane Greenstein. "The Impact of the General Data Protection Regulation on Internet Interconnection." Telecommunications Policy 45, no. 2 (March 2021).
- Article
One Obstacle to Curing Cancer: Patient Data Isn't Shared
By: Richard G. Hamermesh and Kathy Giusti
Precision Medicine requires large datasets to identify the mutations that lead to various cancers. Currently, genomic information is hoarded in fragmented silos within numerous academic medical centers, pharmaceutical companies, and some disease-based foundations. For... View Details
Keywords: Healthcare; Technological And Scientific Innovation; Cancer Care In The U.S.; Cancer Treatment; Precision Medicine; Personalized Medicine; Data Sharing; Technological Innovation; Analytics and Data Science; Health Disorders; Medical Specialties; Research and Development; Customization and Personalization; Health Industry; United States
Hamermesh, Richard G., and Kathy Giusti. "One Obstacle to Curing Cancer: Patient Data Isn't Shared." Harvard Business Review (website) (November 28, 2016).
- February 25, 2016
- Article
The Hodgepodge Principle in U.S. Privacy Policy
By: John A. Deighton
Data, says Professor Lawrence Summers, is the new oil, "a hugely valuable asset essential to economic life." Personal data, the kind of data that invites thoughts of privacy, is a big part of that. The European Union saw this economic fuel source coming long ago and... View Details
Keywords: Data; Privacy; Technology; Big Data; Personal Data; Marketing; Information Technology; Analytics and Data Science
Deighton, John A. "The Hodgepodge Principle in U.S. Privacy Policy." Harvard Law and Policy Review Blog (March 2, 2016). http://harvardlpr.com/2016/03/02/the-hodgepodge-principle-in-us-privacy-policy/.
- Article
Uninformed Consent
By: Leslie K. John
Companies want access to more and more of your personal data—from where you are to what’s in your DNA. Can they unlock its value while respecting consumers’ privacy? View Details
Keywords: Personal Data; Privacy; Customers; Analytics and Data Science; Ethics; Governing Rules, Regulations, and Reforms
John, Leslie K. "Uninformed Consent." Special Issue on The Big Idea: Tracked. Harvard Business Review (website) (September–October 2018).
- 2016
- Working Paper
CEO Personality and Firm Policies
By: Ian D. Gow, Steven N. Kaplan, David F. Larcker and Anastasia A. Zakolyukina
Based on two samples of high quality personality data for chief executive officers (CEOs), we use linguistic features extracted from conferences calls and statistical learning techniques to develop a measure of CEO personality in terms of the Big Five traits:... View Details
Gow, Ian D., Steven N. Kaplan, David F. Larcker, and Anastasia A. Zakolyukina. "CEO Personality and Firm Policies." NBER Working Paper Series, No. 22435, July 2016.
- 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
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).
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- January 2021
- Article
How Personality and Policy Predict Pandemic Behavior: Understanding Sheltering-in-Place in 55 Countries at the Onset of COVID-19
By: Friedrich M. Götz, Andrés Gvirtz, Adam D. Galinsky and Jon M. Jachimowicz
The spread of COVID-19 within any given country or community at the onset of the pandemic depended in part on the sheltering-in-place rate of its citizens. The pandemic led us to revisit one of psychology’s most fundamental and most basic questions in a high-stakes... View Details
Keywords: COVID; COVID-19; Pandemic; Shelter-in-place; Personality; Government; Interactionism; Health Pandemics; Behavior; Personal Characteristics; Policy; Governance Compliance
Götz, Friedrich M., Andrés Gvirtz, Adam D. Galinsky, and Jon M. Jachimowicz. "How Personality and Policy Predict Pandemic Behavior: Understanding Sheltering-in-Place in 55 Countries at the Onset of COVID-19." American Psychologist 76, no. 1 (January 2021): 39–49.
- October 2017 (Revised April 2019)
- Case
Data Breach at Equifax
By: Suraj Srinivasan, Quinn Pitcher and Jonah S. Goldberg
The case discusses the events leading up to the massive data breach at Equifax, one of the three U.S. credit reporting companies, the organizational and governance issues that contributed to the breach, and the consequences of the breach. The case supplement provides... View Details
Srinivasan, Suraj, Quinn Pitcher, and Jonah S. Goldberg. "Data Breach at Equifax." Harvard Business School Case 118-031, October 2017. (Revised April 2019.)
- March 2024
- Case
Unintended Consequences of Algorithmic Personalization
By: Eva Ascarza and Ayelet Israeli
“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details
Keywords: Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Customization and Personalization; Technology Industry; Retail Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Unintended Consequences of Algorithmic Personalization." Harvard Business School Case 524-052, March 2024.
- 2021
- Article
To Thine Own Self Be True? Incentive Problems in Personalized Law
By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers
Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details
Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning
Barry, Jordan M., John William Hatfield, and Scott Duke Kominers. "To Thine Own Self Be True? Incentive Problems in Personalized Law." Art. 2. William & Mary Law Review 62, no. 3 (2021).
- January 2016
- Case
Acxiom
By: John Deighton
Acxiom built the market for personal data, yet sales have been flat for a decade during which marketing's appetite for data has exploded. Will the acquisition of a digital data onboarder LiveRamp give marketers what they want from a data broker? View Details
- August 2019
- Article
When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation
By: Yicheng Song, Nachiketa Sahoo and Elie Ofek
Sometimes we desire change, a break from the same or an opportunity to fulfill different aspects of our needs. Noting that consumers seek variety, several approaches have been developed to diversify items recommended by personalized recommender systems. However,... View Details
Keywords: Recommender Systems; Personalization; Recommendation Diversity; Variety Seeking; Collaborative Filtering; Consumer Utility Models; Digital Media; Clickstream Analysis; Learning-to-rank; Consumer Behavior; Media; Customization and Personalization; Strategy; Mathematical Methods
Song, Yicheng, Nachiketa Sahoo, and Elie Ofek. "When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation." Management Science 65, no. 8 (August 2019): 3737–3757.
- March 1998 (Revised September 1999)
- Supplement
Electronic Data Systems (EDS)Supplement: A Personal Diary of A GVD Experience, Mexico City, October 4, 1997
By: Rosabeth M. Kanter and Thomas Dretler
Supplements the case. View Details
Kanter, Rosabeth M., and Thomas Dretler. "Electronic Data Systems (EDS)Supplement: A Personal Diary of A GVD Experience, Mexico City, October 4, 1997." Harvard Business School Supplement 398-075, March 1998. (Revised September 1999.)
- 04 Jun 2024
- Research & Ideas
Navigating Consumer Data Privacy in an AI World
an answer to key questions for privacy protection, such as: What is the compliance framework for accessing and using data in various tasks? Essentially, the person is responsible for developing and regularly... View Details
- 26 Jul 2016
- Research & Ideas
Where will Pokémon Go with Your Personal Information?
all time. Data analytics firm Similar Web reported that in its first week alone, the app had been installed on nearly 11 percent of all Android phones in the United States, and surpassed Twitter’s daily usage shortly thereafter. Pokémon... View Details
- November 2023
- Article
Federated Electronic Health Records for the European Health Data Space
By: René Raab, Arne Küderle, Anastasiya Zakreuskaya, Ariel Dora Stern, Jochen Klucken, Georgios Kaissis, Daniel Rueckert, Susanne Boll, Roland Eils, Harald Wagener and Bjoern Eskofier
The European Commission's draft for the European Health Data Space (EHDS) aims to empower citizens to access their personal health data and share it with physicians and other health-care providers. It further defines procedures for the secondary use of electronic... View Details
Keywords: Analytics and Data Science; Cybersecurity; Information Management; Knowledge Sharing; Knowledge Use and Leverage; Health Industry
Raab, René, Arne Küderle, Anastasiya Zakreuskaya, Ariel Dora Stern, Jochen Klucken, Georgios Kaissis, Daniel Rueckert, Susanne Boll, Roland Eils, Harald Wagener, and Bjoern Eskofier. "Federated Electronic Health Records for the European Health Data Space." Lancet Digital Health 5, no. 11 (November 2023): e840–e847.
- September 2012
- Article
The Relationship Between Economic Preferences and Psychological Personality Measures
By: Anke Becker, Thomas Deckers, Thomas Dohmen, Armin Falk and Fabian Kosse
Although both economists and psychologists seek to identify determinants of heterogeneity in behavior, they use different concepts to capture them. In this review, we first analyze the extent to which economic preferences and psychological concepts of personality, such... View Details
Keywords: Risk Preference; Time Preference; Social Preferences; Locus Of Control; Big Five; Economics; Behavior; Personal Characteristics
Becker, Anke, Thomas Deckers, Thomas Dohmen, Armin Falk, and Fabian Kosse. "The Relationship Between Economic Preferences and Psychological Personality Measures." Annual Review of Economics 4 (September 2012): 453–478.