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    • Research  (1,292)
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  • All HBS Web  (1,925)
    • News  (300)
    • Research  (1,292)
    • Events  (27)
    • Multimedia  (11)
  • Faculty Publications  (772)
← Page 12 of 1,925 Results →
  • April 2015 (Revised March 2017)
  • Case

Instacart and the New Wave of Grocery Startups

By: John Deighton and Leora Kornfeld
Instacart is testing an Uber-style solution to the challenge of building a home-delivered grocery business. It is backed by $220 million of venture funding. Will this model succeed where businessses like Webvan failed? What are the questions that this exploratory... View Details
Keywords: Food Retailing; Outsourced Grocery Delivery; Online Ordering; Dynamic Pricing; Data Analytics; Marketing Strategy; Food; Distribution Channels; Business Startups; Food and Beverage Industry; California
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Deighton, John, and Leora Kornfeld. "Instacart and the New Wave of Grocery Startups." Harvard Business School Case 515-089, April 2015. (Revised March 2017.)
  • October 2016
  • Article

Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance and Resource Allocation in Science

By: Kevin J. Boudreau, Eva Guinan, Karim R. Lakhani and Christoph Riedl
Selecting among alternative innovative projects is a core management task in all innovating organizations. In this paper, we focus on the evaluation of frontier scientific research projects. We argue that the "intellectual distance" between the knowledge embodied in... View Details
Keywords: Knowledge; Innovation; Novelty; Evaluation; Resource Allocation; Decision Choices and Conditions; Innovation and Management; Science-Based Business; Experience and Expertise
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Boudreau, Kevin J., Eva Guinan, Karim R. Lakhani, and Christoph Riedl. "Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance and Resource Allocation in Science." Management Science 62, no. 10 (October 2016).
  • 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; Apparel and Accessories Industry; Apparel and Accessories Industry; Singapore
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Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
  • Web

Data Practices - Research Computing Services

Data Practices Data Tips & Toolkits RCS has compiled an array of packages and tools that can help you with your data wrangling, web scraping,... View Details
  • October 2017 (Revised November 2017)
  • Case

NYC311

By: Constantine E. Kontokosta, Mitchell Weiss, Christine Snively and Sarah Gulick
Joe Morrisroe, executive director for NYC311, had some gut instincts but no definitive answer to the question he was just asked by one of the mayor’s deputies: “Are some communities being underserved by 311? How do we know we are hearing from the right people?” Founded... View Details
Keywords: New York City; NYC; 311; NYC311; Big Data; Equal Access; Bias; Data Analysis; Public Entrepreneurship; Urban Informatics; Predictive Analytics; Chief Data Officer; Data Analytics; Cities; City Leadership; Analytics and Data Science; Analysis; Prejudice and Bias; Entrepreneurship; Public Sector; City; Public Administration Industry; New York (city, NY)
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Kontokosta, Constantine E., Mitchell Weiss, Christine Snively, and Sarah Gulick. "NYC311." Harvard Business School Case 818-056, October 2017. (Revised November 2017.)
  • 01 Jun 2017
  • News

Better Hiring Through Brain Science

and the games, Polli notes, is like the difference between the scattershot of a dot matrix printer and the precision of a laser printer. HBS students were the first data... View Details
Keywords: Dan Morrell
  • Research Summary

Overview

By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data... View Details
Keywords: Channel Management; Pricing; Pricing Policies; Online Marketing; E-commerce; Analytics; Econometrics; Field Experiments; Data Analytics; Artificial Intelligence; Value Of Data
  • 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.
  • Article

Algorithms Need Managers, Too

By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details
Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science
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Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
  • April 2014 (Revised March 2015)
  • Case

GE and the Industrial Internet

By: Karim R. Lakhani, Marco Iansiti and Kerry Herman
CEO Jeff Immelt considers whether GE is moving fast enough on its new Industrial Internet initiative. The undertaking includes building out an Industrial Internet, connecting machines and devices, collecting their data and operations, and providing services to clients... View Details
Keywords: Technology; Operations Management; Strategy; Big Data; Business Analysis; Corporate Strategy; Digital Technology; Digital Innovation; General Management; General Strategy; Global Competitiveness; Global Strategy; Innovation; Innovation And Management; Industrial Internet; GE; Innovation and Invention; Information Technology; Analytics and Data Science; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; North and Central America; Asia; Europe; Middle East; Latin America
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Lakhani, Karim R., Marco Iansiti, and Kerry Herman. "GE and the Industrial Internet." Harvard Business School Case 614-032, April 2014. (Revised March 2015.)
  • 01 Mar 2018
  • News

Democratizing Data to Favor Farmers

as much for the same seeds. That knowledge would help farmers haggle with dealers, but the real insight would come from analytics that go beyond consolidating seed prices to measuring a seed variety’s potential success. The most important... View Details
Keywords: Sasha Issenberg
  • 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; Analytics and Data Science; 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.)
  • July 2013
  • Case

Sample6: Innovating to Make Food Safer

By: Robert F. Higgins and Kirsten Kester
Tim Curran, CEO of Sample6, a start-up biotechnology company developing a novel food safety diagnostics platform, must decide how to partner with food industry players. How can he best convince leaders in this mature industry to adopt a new technology and improve food... View Details
Keywords: Data Analytics; Food Safety; Biotechnology; Nutrition; Entrepreneurship; Product; Partners and Partnerships; Food; Technological Innovation; Business Startups; Governing Rules, Regulations, and Reforms; Product Development; Agribusiness; Information Technology; Globalization; Performance Improvement; Safety; Technology Adoption; Agriculture and Agribusiness Industry; Agriculture and Agribusiness Industry; Agriculture and Agribusiness Industry; Agriculture and Agribusiness Industry; United States; Boston; Massachusetts
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Higgins, Robert F., and Kirsten Kester. "Sample6: Innovating to Make Food Safer." Harvard Business School Case 814-014, July 2013.
  • September 2012
  • Article

Bringing Science to the Art of Strategy

By: A. G. Lafley, Roger L. Martin, Jan W. Rivkin and Nicolaj Siggelkow
For all its emphasis on data and number crunching, conventional strategic planning is not actually scientific. It lacks the hypothesis generation and testing that's at the heart of the scientific method. To produce novel and successful strategies, teams need to adopt a... View Details
Keywords: Strategic Planning; Science
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Lafley, A. G., Roger L. Martin, Jan W. Rivkin, and Nicolaj Siggelkow. "Bringing Science to the Art of Strategy." Harvard Business Review 90, no. 9 (September 2012).
  • 2021
  • Working Paper

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; Retail Industry
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Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
  • 08 Jan 2018
  • News

HBS-Born Startup Arms Doctors with Analytics to Provide Better Care

Keywords: Ambulatory Health Care Services; Health, Social Assistance
  • June 30, 2020
  • Article

Scaling Up Behavioral Science Interventions in Online Education

By: Rene F. Kizilcec, Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph J. Williams and Dustin Tingley
Online education is rapidly expanding in response to rising demand for higher and continuing education, but many online students struggle to achieve their educational goals. Several behavioral science interventions have shown promise in raising student persistence and... View Details
Keywords: Online Learning; Behavioral Interventions; Scale; Education; Online Technology; Performance Improvement
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Kizilcec, Rene F., Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph J. Williams, and Dustin Tingley. "Scaling Up Behavioral Science Interventions in Online Education." Proceedings of the National Academy of Sciences 117, no. 26 (June 30, 2020).
  • December 2011
  • Article

Data Impediments to Empirical Work on Health Insurance Markets

By: Leemore S. Dafny, David Dranove, Frank Limbrock and Fiona Scott Morton
We compare four datasets that researchers might use to study competition in the health insurance industry. We show that the two datasets most commonly used to estimate market concentration differ considerably from each other (both in levels and in changes over time),... View Details
Keywords: Competition; Analytics and Data Science; Market Participation; Insurance Industry
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Dafny, Leemore S., David Dranove, Frank Limbrock, and Fiona Scott Morton. "Data Impediments to Empirical Work on Health Insurance Markets." B.E. Journal of Economic Analysis & Policy 11, no. 2 (December 2011).
  • Teaching Interest

Overview

By: John A. Deighton
I teach about the ecosystem of big data, the role of data in advertising and creative industries, and customer management and personal privacy in an era of individual addressability. View Details
Keywords: Digital Marketing; Database Marketing; Social Media; Data Analytics; Information; Advertising; Marketing; Media; Technology; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Entertainment and Recreation Industry
  • 2023
  • Working Paper

Feature Importance Disparities for Data Bias Investigations

By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Prejudice and Bias
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Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
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