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January 2014 (Revised December 2014)
Case

GenapSys: Business Models for the Genome

By: Richard G. Hamermesh, Joseph B. Fuller and Matthew Preble

GenapSys, a California-based startup, was soon to release a new DNA sequencer that the company's founder, Hesaam Esfandyarpour, believed was truly revolutionary. The sequencer would be substantially less expensive—potentially costing just a few thousand dollars—and... View Details

Keywords: DNA Sequencing; Life Sciences; Business Model; Innovation ＆ Entrepreneurship; Health Care and Treatment; Genetics; Business Strategy; Biotechnology Industry; Pharmaceutical Industry; Technology Industry; Health Industry; Medical Devices and Supplies Industry; United States

February 2016 (Revised May 2016)
Case

Dinr: My First Start-up (A)

By: Shikhar Ghosh and Kristina Maslauskaite

In May 2012, a young employee at Google's London office, Markus Berger, was thinking whether he should quit his job and go after his dream of becoming an entrepreneur. Berger's idea was to create Dinr, a company that would offer an upscale food ingredient delivery... View Details

Keywords: Exit Strategy; Startup; Start-up; Business Exit or Shutdown; Business Startups; Entrepreneurship; Food

Research Summary

Lean Startup Management Practices

By: Thomas R. Eisenmann

Many information technology startups have embraced "lean startup" management practices. Lean startups confront high levels of uncertainty about both customer problems and product solutions: the strength of demand for new... View Details

April, 2023
Article

Reducing Information Barriers to Solar Adoption: Experimental Evidence from India

By: Meera Mahadevan, Robyn C. Meeks and Takashi Yamano

Off-grid solar technologies hold promise for unelectrified and low-quality electricity settings; however, their adoption remains low. Important barriers to adoption, such as incomplete information remain relatively unexplored in developing countries. In collaboration... View Details

Keywords: Technology Adoption; Renewable Energy; Knowledge Sharing; Developing Countries and Economies; India

2014
Other Teaching and Training Material

Marketing Reading: Segmentation and Targeting

By: Sunil Gupta

This Reading introduces two of the integral parts of any marketing strategy: segmentation and targeting. It covers, first, all of the methods, techniques, and variables with which a business first uncovers the full range of its potential customers and then... View Details

Keywords: Behavioral Segmentation; Conjoint Analysis; Demographic Segmentation; Geographic Segmentation; Market Opportunities; Market Segmentation; Marketing; Marketing Strategy; Psychographic Segmentation; Unethical Marketing Practices; United States

Article

Vungle Inc. Improves Monetization Using Big-Data Analytics

By: Bert De Reyck, Ioannis Fragkos, Yael Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin and Andrew Kritzer

The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry,... View Details

Keywords: Big Data; Monetization; Data and Data Sets; Advertising; Mobile Technology; Customization and Personalization; Performance Improvement

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13 May 2024
Research & Ideas

Picture This: Why Online Image Searches Drive Purchases

randomly provided text-and-image search refinement suggestions to only half of roughly 500,000 users, chosen randomly. A customer in the test group searching for the general term “headphones” would receive... View Details

Keywords: by Rachel Layne; Information Technology; Technology; Consumer Products; Retail

February 2020
Article

Why Prosocial Referral Incentives Work: The Interplay of Reputational Benefits and Action Costs

By: Rachel Gershon, Cynthia Cryder and Leslie K. John

While selfish incentives typically outperform prosocial incentives, in the context of customer referral rewards, prosocial incentives can be more effective. Companies frequently offer “selfish” (i.e., sender-benefiting) referral incentives, offering customers financial... View Details

Keywords: Incentives; Prosocial Behavior; Judgment And Decision-making; Referral Rewards; Motivation and Incentives; Consumer Behavior; Decision Making

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September 2010 (Revised November 2010)
Case

Ze-gen: Commercializing Clean Tech

By: Lynda M. Applegate, Kaitlyn Lyons and Scott Prozeller

The Ze-gen case covers the first five years in the life of a clean-tech start-up. Ze-gen had developed an innovative technology that converted solid waste into synthesis gas (called syngas). This technology was in testing at the company's pilot plant, built next to the... View Details

Keywords: Business Startups; Renewable Energy; Entrepreneurship; Financing and Loans; Environmental Sustainability; Commercialization; Green Technology Industry; New Bedford

March 1998 (Revised October 2001)
Case

Teradyne: Corporate Management of Disruptive Change

By: Joseph L. Bower

Two cases deal with the introduction of a new product to Teradyne's line of semiconductor test equipment. This case deals with the problems facing the head of a start-up division responsible for developing and bringing to market a new product based on technology deemed... View Details

Keywords: Business Startups; Disruption; Management; Market Entry and Exit; Product; Problems and Challenges; Competitive Strategy; Corporate Strategy; Technology

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November 2002 (Revised August 2003)
Case

MedSource Technologies

By: Robert S. Huckman

Considers the issues facing Richard Effress, MedSource's chairman and CEO, as the firm approaches the Precision Cut project--the first test of MedSource's capabilities as an integrated, contract manufacturer in the medical device industry. MedSource Technologies was... View Details

Keywords: Product Development; Production; Mergers and Acquisitions; Product Design; Supply Chain Management; Management Teams; Medical Devices and Supplies Industry; United States

August 2008
Article

Economic Links and Predictable Returns

By: Lauren Cohen and Andrea Frazzini

This paper finds evidence of return predictability across economically linked firms. We test the hypothesis that in the presence of investors subject to attention constraints, stock prices do not promptly incorporate news about economically related firms, generating... View Details

Keywords: Economics; Price; Assets; Analytics and Data Science; Customers; Stocks; Equity; Strategy; Investment Return; Forecasting and Prediction

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August 2014
Case

Opening the Valve: From Software to Hardware (A)

By: Ethan Bernstein, Francesca Gino and Bradley Staats

Valve, one of the world's top video game software companies, has also become an iconic example of an organization with virtually no hierarchy. A 400-person organization, Valve's unique organizational form (described in detail in the case and accompanying employee... View Details

September 2020 (Revised June 2023)
Supplement

Spreadsheet Supplement to Artea Teaching Note

By: Eva Ascarza and Ayelet Israeli

Spreadsheet Supplement to Artea Teaching Note 521-041. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details

Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

September 2020 (Revised July 2022)
Exercise

Artea (D): Discrimination through Algorithmic Bias in Targeting

By: Eva Ascarza and Ayelet Israeli

This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details

Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

September 2020 (Revised July 2022)
Exercise

Artea (C): Potential Discrimination through Algorithmic Targeting

By: Eva Ascarza and Ayelet Israeli

This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details

Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

2013
Working Paper

Non-Standard Matches and Charitable Giving

By: Michael Sanders, Sarah Smith and Michael I. Norton

Many organisations, including corporations and governments, wish to encourage charitable giving, and offer incentives for their employees, customers and citizens to do so. The most common of these incentives is a match rate, where the organisation agrees to pay, for... View Details

Keywords: Motivation and Incentives; Organizational Culture; Philanthropy and Charitable Giving

September 2020 (Revised July 2022)
Exercise

Artea (B): Including Customer-Level Demographic Data

By: Eva Ascarza and Ayelet Israeli

This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details

Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

September 2020 (Revised February 2024)
Teaching Note

Artea (A), (B), (C), and (D): Designing Targeting Strategies

By: Eva Ascarza and Ayelet Israeli

Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details

Keywords: Targeted Advertising; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

25 Oct 2020
Research & Ideas

The Dark Side of Fintech Borrowing

requirement introduced by the Dodd-Frank Act for fintech lenders might serve the industry well, Di Maggio suggests. The law “forced the banks to actually make sure that the borrowers will be able to repay their loans.” “In the mortgage market, there are all these View Details

Keywords: by Rachel Layne; Financial Services; Banking

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