Strategy

- 2025
- Working Paper
Experimental Evidence on the (Limited) Influence of Reputable Media Outlets

By: Bharat Anand, Gary King, Kiran Misra and Sascha Riaz

"High quality news outlets are widely regarded as essential to responsive, uncorrupt democratic governments. However, experimental validation of the mechanisms of this claim, whereby outlets influence citizen knowledge and views, has proven elusive because reputable outlets always try to publish the truth (and so valid control groups are hard to find), do not randomize news content, and have business models that generate massive endogeneity. We worked with a major media outlet to overcome these problems and meet both journalistic and scientific standards. The results of four experiments covering crime, the economy, the environment, and gender equity indicate that editorial decisions have large effects on readers’ factual knowledge, as implied by claims about the importance of the press, but they are only modestly larger than the effect of sponsored content on the same sites, which anyone can buy without editorial oversight. Moreover, at least in the short term, editorial decisions are no different from sponsored content purchases for other outcomes: Effects on political attitudes and policy preferences are statistically indistinguishable from each other, approximately zero, and the same across policy areas. Our results suggest that the traditional news media provides a clear but increasingly tenuous foundation for citizen education in modern democracy"
- 2025
- Working Paper
Experimental Evidence on the (Limited) Influence of Reputable Media Outlets

By: Bharat Anand, Gary King, Kiran Misra and Sascha Riaz

"High quality news outlets are widely regarded as essential to responsive, uncorrupt democratic governments. However, experimental validation of the mechanisms of this claim, whereby outlets influence citizen knowledge and views, has proven elusive because reputable outlets always try to publish the truth (and so valid control groups are hard to...
- March 2025
- Case
Niramai: An AI Solution to Save Lives

By: Rembrand Koning, Maria P. Roche and Kairavi Dey

Founded in 2017, Niramai developed Thermalytix, a breast cancer screening tool. Thermalytix used a high-resolution thermal sensing device and machine learning algorithms to analyze thermal images and detect tumors. Its patented solution leveraged big data analytics, AI, and ML for reliable, early, and accurate breast cancer screening. Early clinical trials showed that the solution was equal to or, in some instances, more accurate than mammography available in India. The team was elated that they had developed an effective, low-cost, easier-to-use, non-invasive, and less painful solution for patients. As Manjunath considered the next phase of Niramai’s growth, she wondered if it was time to raise another round of funds and conduct a new, comprehensive clinical study. Should the trial be conducted in the U.S., where it would be significantly more expensive but with the possibility of an exponentially higher payout if the trials were successful? Or should they raise a smaller round now, do a larger trial in a populous developing country such as Indonesia, and focus on lower-to-middle-income countries?
- March 2025
- Case
Niramai: An AI Solution to Save Lives

By: Rembrand Koning, Maria P. Roche and Kairavi Dey

Founded in 2017, Niramai developed Thermalytix, a breast cancer screening tool. Thermalytix used a high-resolution thermal sensing device and machine learning algorithms to analyze thermal images and detect tumors. Its patented solution leveraged big data analytics, AI, and ML for reliable, early, and accurate breast cancer screening. Early...
- March 2025
- Case
adidas (A): Defining a Strategy for Reebok

By: Ramon Casadesus-Masanell, Karolin Frankenberger and Claudio Feser
- March 2025
- Case
adidas (A): Defining a Strategy for Reebok

By: Ramon Casadesus-Masanell, Karolin Frankenberger and Claudio Feser

About the Unit

The Strategy unit studies firms as competitors in an economic landscape. Key issues include: the development and effectiveness of firm strategy at both a business and corporate level; the analysis of the competitive environment; and the sustainability of strategy over time.

Our research, course development, and teaching draws on multiple disciplines, including economics, sociology, and political science, and focuses on both domestic and global competition. The objective of the work is to generate findings and develop concepts that will help managers improve their strategic decisions while advancing the state of knowledge in the academic study of strategy and related disciplines.

Recent Publications

ZEISS: Commercializing Science

By: Maria P. Roche and Richie Zitomer

April 2025 |
Supplement |
Faculty Research

Spreadsheet Supplement for HBS Case No. 725-359.

Citation

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Experimental Evidence on the (Limited) Influence of Reputable Media Outlets

By: Bharat Anand, Gary King, Kiran Misra and Sascha Riaz

2025 |
Working Paper |
Faculty Research

"High quality news outlets are widely regarded as essential to responsive, uncorrupt democratic governments. However, experimental validation of the mechanisms of this claim, whereby outlets influence citizen knowledge and views, has proven elusive because reputable outlets always try to publish the truth (and so valid control groups are hard to find), do not randomize news content, and have business models that generate massive endogeneity. We worked with a major media outlet to overcome these problems and meet both journalistic and scientific standards. The results of four experiments covering crime, the economy, the environment, and gender equity indicate that editorial decisions have large effects on readers’ factual knowledge, as implied by claims about the importance of the press, but they are only modestly larger than the effect of sponsored content on the same sites, which anyone can buy without editorial oversight. Moreover, at least in the short term, editorial decisions are no different from sponsored content purchases for other outcomes: Effects on political attitudes and policy preferences are statistically indistinguishable from each other, approximately zero, and the same across policy areas. Our results suggest that the traditional news media provides a clear but increasingly tenuous foundation for citizen education in modern democracy"

Citation

Niramai: An AI Solution to Save Lives

By: Rembrand Koning, Maria P. Roche and Kairavi Dey

March 2025 |
Case |
Faculty Research

Founded in 2017, Niramai developed Thermalytix, a breast cancer screening tool. Thermalytix used a high-resolution thermal sensing device and machine learning algorithms to analyze thermal images and detect tumors. Its patented solution leveraged big data analytics, AI, and ML for reliable, early, and accurate breast cancer screening. Early clinical trials showed that the solution was equal to or, in some instances, more accurate than mammography available in India. The team was elated that they had developed an effective, low-cost, easier-to-use, non-invasive, and less painful solution for patients. As Manjunath considered the next phase of Niramai’s growth, she wondered if it was time to raise another round of funds and conduct a new, comprehensive clinical study. Should the trial be conducted in the U.S., where it would be significantly more expensive but with the possibility of an exponentially higher payout if the trials were successful? Or should they raise a smaller round now, do a larger trial in a populous developing country such as Indonesia, and focus on lower-to-middle-income countries?

Keywords: Entrepreneurship; AI and Machine Learning; Technology Adoption; Health Care and Treatment; Technology Industry; Health Industry; Asia; India; South Asia

Citation

Educators

adidas (B): Defining a Strategy for Reebok

By: Ramon Casadesus-Masanell, Claudio Feser and Karolin Frankenberger

March 2025 |
Supplement |
Faculty Research

Citation

adidas (A): Defining a Strategy for Reebok

By: Ramon Casadesus-Masanell, Karolin Frankenberger and Claudio Feser

March 2025 |
Case |
Faculty Research

Citation

Educators

Gavi and the 'Next' Pandemic

By: Tarun Khanna and Samir Junnarkar

March 2025 |
Teaching Note |
Faculty Research

Keywords: Pharmaceutical Industry; Africa

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The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise

By: Fabrizio Dell'Acqua, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub and Karim R. Lakhani

2025 |
Working Paper |
Faculty Research

We examine how artificial intelligence transforms the core pillars of collaboration— performance, expertise sharing, and social engagement—through a pre-registered field experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods company. Working on real product innovation challenges, professionals were randomly assigned to work either with or without AI, and either individually or with another professional in new product development teams. Our findings reveal that AI significantly enhances performance: individuals with AI matched the performance of teams without AI, demonstrating that AI can effectively replicate certain benefits of human collaboration. Moreover, AI breaks down functional silos. Without AI, R&D professionals tended to suggest more technical solutions, while Commercial professionals leaned towards commerciallyoriented proposals. Professionals using AI produced balanced solutions, regardless of their professional background. Finally, AI’s language-based interface prompted more positive selfreported emotional responses among participants, suggesting it can fulfill part of the social and motivational role traditionally offered by human teammates. Our results suggest that AI adoption at scale in knowledge work reshapes not only performance but also how expertise and social connectivity manifest within teams, compelling organizations to rethink the very structure of collaborative work.

Keywords: Artificial Intelligence; Teamwork; Human-machine Interaction; Productivity; Skills; Innovation; Field Experiment; AI and Machine Learning; Groups and Teams; Competency and Skills; Performance Productivity; Collaborative Innovation and Invention; Product Development

Citation

Transferability MATTRs: Towards Understanding Antecedents of Strategic Licensing

By: Dafna F. Bearson and Maria P. Roche

2025 |
Working Paper |
Faculty Research

This paper examines the antecedents of firms’ decisions to license intellectual property (IP). We propose a conceptual framework emphasizing two critical factors: (1) transferability, which we define as the ease of moving knowledge embodied in inventions across firm boundaries, and (2) relevance, representing the invention’s importance to a firm’s value creation and capture processes. Leveraging a novel proxy for transferability—the moving-average type-token ratio (MATTR), which measures the lexical diversity of patent descriptions—we analyze licensing agreements for U.S. patents granted from 1980 to 2015, integrating this data with patent- and firm-level characteristics. The results reveal that higher MATTR is associated with a greater likelihood of licensing, suggesting that firms strategically enhance transferability for potential licensees as they apply for a patent. Moreover, the relationship between transferability and licensing is moderated by the invention’s economic and scientific value, and the degree of demand uncertainty in the industry. These findings contribute to the literature on innovation strategy and technology markets, highlighting the strategic selection of IP for licensing and the dynamic interplay of invention characteristics, firm strategy, and industry context in shaping licensing decisions.

Keywords: Technological Innovation; Innovation Strategy; Intellectual Property; Value Creation

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