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Show Results For
- All HBS Web
(1,621)
- People (3)
- News (450)
- Research (503)
- Events (7)
- Multimedia (32)
- Faculty Publications (154)
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- July 2008 (Revised January 2010)
- Case
Affinity Labs, Inc.
By: Joseph B. Lassiter III and Elizabeth Kind
In November 2006, Chris Michel left Military.com, which he founded in 1999, to start Affinity Labs, a global network of online communities. That month, Michel raised a Series A round of venture funding and established a partnership with Monster, which he had sold... View Details
Keywords: Mergers and Acquisitions; Business Startups; Entrepreneurship; Demand and Consumers; Partners and Partnerships; Social and Collaborative Networks; Online Technology
Lassiter, Joseph B., III, and Elizabeth Kind. "Affinity Labs, Inc." Harvard Business School Case 809-019, July 2008. (Revised January 2010.)
- 18 Aug 2011
- Lessons from the Classroom
Business Plan Contest: 15 Years of Building Better Entrepreneurs
An online shipping platform that uses social networks and smartphones. Low-cost medical care and monitoring that helps seniors to live at home. The "Skype" of broadband, offering free Internet service. On an April morning known as "Super... View Details
- April 2019
- Article
Mitigating Malicious Envy: Why Successful Individuals Should Reveal Their Failures
People often feel malicious envy, a destructive interpersonal emotion, when they compare themselves to successful peers. Across three online experiments and a field experiment of entrepreneurs, we identify an interpersonal strategy that can mitigate feelings of... View Details
Brooks, Alison Wood, Karen Huang, Nicole Abi-Esber, Ryan W. Buell, Laura Huang, and Brian Hall. "Mitigating Malicious Envy: Why Successful Individuals Should Reveal Their Failures." Journal of Experimental Psychology: General 148, no. 4 (April 2019): 667–687.
- 23 Sep 2008
- First Look
First Look: September 23, 2008
Working PapersSecuring Online Advertising: Rustlers and Sheriffs in the New Wild West Author:Benjamin G. Edelman Abstract Read the news of recent computer security guffaws, and it's striking how many problems stem from View Details
Keywords: Martha Lagace
- November–December 2022
- Article
Can AI Really Help You Sell?: It Can, Depending on When and How You Implement It
By: Jim Dickie, Boris Groysberg, Benson P. Shapiro and Barry Trailer
Many salespeople today are struggling; only 57% of them make their annual quotas, surveys show. One problem is that buying processes have evolved faster than selling processes, and buyers today can access a wide range of online resources that let them evaluate products... View Details
Dickie, Jim, Boris Groysberg, Benson P. Shapiro, and Barry Trailer. "Can AI Really Help You Sell? It Can, Depending on When and How You Implement It." Harvard Business Review 100, no. 6 (November–December 2022): 120–129.
- 15 Aug 2016
- Research & Ideas
Black Swans and Big Trends Can Ruin Anyone's Internet Prediction
how we thought about online opportunities one year after the dot-com bubble burst. In retrospect, many of my thoughts about the internet’s future evolution missed the mark. If you think history repeats itself, then these forecasting... View Details
- Research Summary
Overview
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
- 21 Oct 2024
- Research & Ideas
What Happens in Vegas Could Shape the Metaverse
competing incentives in building the metaverse, our view is that the metaverse can still succeed,” they write, “but it might call for a shift in mindset and an openness to learning from seemingly distant domains of knowledge.” Along those... View Details
- 15 Jul 2008
- First Look
First Look: July 15, 2008
turning to appraisers, actuaries, and evaluators, whether internal, external, or a combination. The Competitive Imperative of Learning Author:Amy C. Edmondson Publication:HBS Centennial Issue. Harvard Business Review 86, nos. 7/8 (July -... View Details
Keywords: Martha Lagace
- April 2001 (Revised August 2001)
- Case
UNext: Business Education and e-Learning
By: Michael G. Rukstad, David J. Collis and Tyrell Levine
UNEXT has signed agreements with Columbia, Stanford, Chicago, Carnegie Mellon, and the London School of Economics to create online business courses. The company is backed by Michael Milken and Larry Ellison and has four Nobel laureates on its advisory board. Describes... View Details
Keywords: Business Education; Curriculum and Courses; Technological Innovation; Internet and the Web; Competition; Disruptive Innovation; Performance Efficiency; Higher Education; Learning; Education Industry
Rukstad, Michael G., David J. Collis, and Tyrell Levine. "UNext: Business Education and e-Learning." Harvard Business School Case 701-014, April 2001. (Revised August 2001.)
- 2022
- Working Paper
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details
Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
- 30 May 2000
- Research & Ideas
Market Makers Bid for Success
doing these manual negotiations, why not just use online auctions? Glenn Meakhem HBS MBA '91 founder and CEO, FreeMarkets That was a pretty radical notion in June 1994, but it worked. What I learned very... View Details
- 16 Nov 2010
- First Look
First Look: November 16, 2010
games. Our dictators can purchase signals about why the recipients are poor. We find that a third of the dictators are willing to pay a dollar to learn more about their recipient. Dictators who devote resources to acquiring information... View Details
Keywords: Sean Silverthorne
- 05 Feb 2024
- Research & Ideas
The Middle Manager of the Future: More Coaching, Less Commanding
to connect groups with disparate skills—like engineering, sales, and market analysis—at key points in a project. Extensive analysis of job postings Zhang bases his conclusions on a unique linguistic analysis of more than 34 million online... View Details
Keywords: by Ben Rand
- 02 Apr 2008
- Research & Ideas
Four Companies that Conquered America
demanding market for almost everything from oil to microprocessors to premium coffee. Companies around the world aspire to do business in the U.S., or at least with U.S. companies in their home markets. By doing so, they learn much about... View Details
Keywords: by John Quelch
- 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
- 05 May 2014
- Research & Ideas
Reflecting on Work Improves Job Performance
information with others would improve the learning process. Reflection, sharing, and self-efficacy For the first study, the team recruited 202 adults for an online experiment in which they completed a series... View Details
Keywords: by Carmen Nobel
- 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).
- 08 Apr 2014
- First Look
First Look: April 8
flat and statistically insignificant. These empirical facts contradict the conventional wisdom and constitute a challenge for the existing theories on upstream capital flows and global imbalances. Download working paper: http://ssrn.com/abstract=1920472 View Details
Keywords: Sean Silverthorne
- 22 Nov 2023
- Research & Ideas
Humans vs. Machines: Untangling the Tasks AI Can (and Can't) Handle
problem-solving. The researchers designed a task “where consultants would excel, but AI would struggle without extensive guidance,” the paper explains. The BCG consultants in this group first had to understand a company’s distribution channels that included franchise,... View Details