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  • All HBS Web  (1,564)
    • News  (204)
    • Research  (1,137)
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  • All HBS Web  (1,564)
    • News  (204)
    • Research  (1,137)
    • Events  (16)
    • Multimedia  (1)
  • Faculty Publications  (665)
← Page 11 of 1,564 Results →
  • May 2009 (Revised October 2009)
  • Case

Verne Global: Building a Green Data Center in Iceland

Verne Global, a pioneering startup created to build the first large-scale data center in Iceland, faces critical challenges regarding its green strategy. Verne Co-Founder Isaac Kato is tasked with evaluating how the company can most successfully market and sell the... View Details
Keywords: Buildings and Facilities; Business Startups; Marketing Strategy; Product Marketing; Sales; Environmental Sustainability; Pollutants; Green Technology Industry; Service Industry; Iceland
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Steenburgh, Thomas J., and Nnamdi Daniel Okike. "Verne Global: Building a Green Data Center in Iceland." Harvard Business School Case 509-063, May 2009. (Revised October 2009.)
  • 13 Jun 2017
  • Blog Post

MS/MBA: Engineering Sciences – A Q&A with Professor Robert Howe

The first MS/MBA: Engineering Sciences cohort will enroll in the MS/MBA program in August of 2018.The program is a major collaboration between HBS and the Harvard John A. Paulson School of Engineering View Details
  • 2018
  • Working Paper

Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e., nowcasting and forecasting) and by providing additional context about how the local... View Details
Keywords: Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Forecasting and Prediction
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Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change." NBER Working Paper Series, No. 24952, August 2018.
  • Article

Integration of Online and Offline Channels in Retail: The Impact of Sharing Reliable Inventory Availability Information

By: Santiago Gallino and Antonio Moreno
Using a proprietary data set, we analyze the impact of the implementation of a “buy-online, pick-up-in-store” (BOPS) project. The implementation of this project is associated with a reduction in online sales and an increase in store sales and traffic. These results can... View Details
Keywords: Retail Operations; Inventory Availability; Empirical Operations Management; Business Analytics; Online Retail; Ecommerce; Operations; Management; Distribution Channels; Consumer Behavior; E-commerce; Retail Industry
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Gallino, Santiago, and Antonio Moreno. "Integration of Online and Offline Channels in Retail: The Impact of Sharing Reliable Inventory Availability Information." Management Science 60, no. 6 (June 2014): 1434–1451. (Finalist of Management Science Best Paper award in Operations Management.)
  • 2017
  • Working Paper

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of economic activity at the local level. However, these statistics typically appear only... View Details
Keywords: Economy; Analytics and Data Science; Local Range; Social and Collaborative Networks
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Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity." Harvard Business School Working Paper, No. 18-022, September 2017. (Revised October 2017.)
  • September 2010
  • Article

Do Inventory and Gross Margin Data Improve Sales Forecasts for U.S. Public Retailers?

By: Saravanan Kesavan, Vishal Gaur and Ananth Raman
Firm-level sales forecasts for retailers can be improved if we incorporate cost of goods sold, inventory, and gross margin (defined here as the ratio of sales to cost of goods sold) as three endogenous variables. We construct a simultaneous equations model, estimated... View Details
Keywords: Sales; Forecasting and Prediction; Distribution; Goods and Commodities; Cost; Public Sector; Profit; Mathematical Methods; Analytics and Data Science; Retail Industry; United States
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Kesavan, Saravanan, Vishal Gaur, and Ananth Raman. "Do Inventory and Gross Margin Data Improve Sales Forecasts for U.S. Public Retailers?" Management Science 56, no. 9 (September 2010): 1519–1533.
  • January 2024 (Revised February 2024)
  • Course Overview Note

Managing Customers for Growth: Course Overview for Students

By: Eva Ascarza
Managing Customers for Growth (MCG) is a 14-session elective course for second-year MBA students at Harvard Business School. It is designed for business professionals engaged in roles centered on customer-driven growth activities. The course explores the dynamics of... View Details
Keywords: Customer Relationship Management; Decision Making; Analytics and Data Science; Growth Management; Telecommunications Industry; Technology Industry; Financial Services Industry; Education Industry; Travel Industry
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Ascarza, Eva. "Managing Customers for Growth: Course Overview for Students." Harvard Business School Course Overview Note 524-032, January 2024. (Revised February 2024.)
  • Research Summary

Overview

By: Kris Johnson Ferreira
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry
  • 25 Apr 2023
  • HBS Seminar

Bart Vanneste, UCL School of Management

  • 21 Aug 2017
  • Lessons from the Classroom

Companies Love Big Data But Lack the Strategy To Use It Effectively

rich and diverse backgrounds.” "It is both staggering and exciting to imagine how data and analytic... View Details
Keywords: by Dina Gerdeman
  • 2023
  • Working Paper

Black-box Training Data Identification in GANs via Detector Networks

By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
Keywords: Cybersecurity; Copyright; AI and Machine Learning; Analytics and Data Science
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Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
  • 14 Sep 2018
  • Blog Post

10 Things I Learned During My First Month in the MS/MBA: Engineering Sciences Program

skills with big-picture business vision. I chose Harvard’s MS/MBA: Engineering Sciences Program to become a strong leader while also refining the skills I would need to succeed in deeply technical fields.  I arrived in Boston on an... View Details
  • 2022
  • Working Paper

The Limits of Decentralized Administrative Data Collection: Experimental Evidence from Colombia

By: Natalia Garbiras-Diaz and Tara Slough
States collect vast amounts of data for use in policymaking and public administration. To do so, central governments frequently solicit data from decentralized bureaucrats. Because central governments use these data in policymaking, decentralized bureaucrats may face... View Details
Keywords: Decentralization; Policy-making; Policy/economics; Policy Evaluation; Governance; Government Administration; Government and Politics; Government Legislation; Policy; Public Opinion; Analytics and Data Science; Latin America; South America; Colombia
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Garbiras-Diaz, Natalia, and Tara Slough. "The Limits of Decentralized Administrative Data Collection: Experimental Evidence from Colombia." Working Paper, December 2022.
  • June 2020
  • Article

Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure

By: Omar Isaac Asensio, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer and Sooji Ha
By displacing gasoline and diesel fuels, electric cars and fleets reduce emissions from the transportation sector, thus offering important public health benefits. However, public confidence in the reliability of charging infrastructure remains a fundamental barrier to... View Details
Keywords: Environmental Sustainability; Transportation; Infrastructure; Behavior; AI and Machine Learning; Demand and Consumers
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Asensio, Omar Isaac, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer, and Sooji Ha. "Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure." Nature Sustainability 3, no. 6 (June 2020): 463–471.
  • 12 Apr 2022
  • Research & Ideas

Swiping Right: How Data Helped This Online Dating Site Make More Matches

some estimates, with players such as Bumble, Tinder, and OKCupid vying to help people find love. While McFowland is not a dating expert, his work in machine learning and social View Details
Keywords: by Kara Baskin
  • March 27, 2017
  • Article

How the Water Industry Learned to Embrace Data

By: Frank V. Cespedes and Amir Peleg
Most current talk about “big data” seems to assume the disintermediation or replacement of physical assets by digital technologies. But a bigger and more impactful trend is the use of online tools to improve physical asset utilization in many traditional off-line... View Details
Keywords: Information Technology; Analytics and Data Science; Organizational Change and Adaptation; Utilities Industry
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Cespedes, Frank V., and Amir Peleg. "How the Water Industry Learned to Embrace Data." Harvard Business Review (website) (March 27, 2017).
  • May 2021 (Revised February 2024)
  • 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; Digital Platforms; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories 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 2024.)
  • July 2018
  • Article

Reimagining Health Data Exchange: An Application Programming Interface-Enabled Roadmap for India

By: Satchit Balsari, Alexander Fortenko MD, MPH, Joaquin A. Blaya PhD, Adrian Gropper MD, Malavika Jayaram LLM, Rahul Matthan LLM, Ram Sahasranam, Mark Shankar MD, Suptendra N. Sarbadhikari PhD, Barbara Bierer, Kenneth D. Mandl MD, Sanjay Mehendale MD, MPH and Tarun Khanna
In February 2018, the Government of India announced a massive public health insurance scheme extending coverage to 500 million citizens, in effect making it the world’s largest insurance program. To meet this target, the government will rely on technology to... View Details
Keywords: Health Information Exchange; India; Health APIs; Health Care and Treatment; Information; Analytics and Data Science; Information Technology; Health Industry; India
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Balsari, Satchit, Alexander Fortenko MD, MPH, Joaquin A. Blaya PhD, Adrian Gropper MD, Malavika Jayaram LLM, Rahul Matthan LLM, Ram Sahasranam, Mark Shankar MD, Suptendra N. Sarbadhikari PhD, Barbara Bierer, Kenneth D. Mandl MD, Sanjay Mehendale MD, MPH, and Tarun Khanna. "Reimagining Health Data Exchange: An Application Programming Interface-Enabled Roadmap for India." Journal of Medical Internet Research 20, no. 7 (July 2018).

    How Google Sold Its Engineers on Management

    High-performing knowledge workers often question whether managers actually contribute much, especially in a technical environment. Until recently, that was the case at Google, a company filled with self-starters who viewed management as more destructive than beneficial... View Details
    • January 2022
    • Article

    Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems

    By: David R. Clough and Andy Wu
    Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of... View Details
    Keywords: Artificial Intelligence; Data Strategy; Ecosystem; Value Capture; Digital Platforms; Analytics and Data Science; Strategy; Learning; Value Creation; AI and Machine Learning; Technology Industry; Information Technology Industry; Video Game Industry; Advertising Industry
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    Clough, David R., and Andy Wu. "Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems." Academy of Management Review 47, no. 1 (January 2022): 184–189.
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