Doctoral Programs

Turning ambiguity into findings

Research doesn’t fit into a neat category. Management challenges deal with real people working in complex, rapidly changing economies and communities. At Questrom, faculty are teacher-scholars who work with you across disciplines to seek answers to management problems—problems that solve relevant organizational issues and take into account the larger effects on our communities.That’s what sets Boston University Questrom School of Business apart—an open atmosphere where we tackle the big questions, together.

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No matter the program, you’ll learn multiple inquiry methods and how to craft your questions, structure your inquiry process, and analyze the date. With 7 PhD specialty areas and hundreds of ways to break out of that area you’ll be prepared to tackle the most challenging questions that matter most to you and our society.

Application Quickguide

Application Requirements More information & Next Steps Questions? We’re happy to help.
  • Resume
  • Personal Statement
  • 3 letters of recommendation
  • Official University-Level Transcripts
  • GMAT or GRE scores
  • PhD in Mathematical Finance applicants will need to complete a prerequisite form (not required for PhD in Management)

It all comes together in Boston

The best universities in the world. Startups and industry leaders in biotech, digital technology, sustainability, social enterprise, health care. You’ll find the best of everything here. Boston has an entrepreneurial spirit and the expertise to make ideas a reality. Coming to BU means putting yourself in the heart of a thriving intellectual community. This is a place where you work across disciplines, industries, and borders to understand the forces transforming our world, be challenged by the brightest minds, and make invaluable connections everyday.

Research Projects & Opportunities

Sustainability Reporting Processes for Organizational Agility

This study investigates organizational agility in the context of sustainability reporting, looking at how firms are responding rapidly to unanticipated external changes that may impact their sustainability programs and consequent reporting. Examples of such changes might be the appearance of a new stakeholder demanding new sustainability metrics; changes in what a key competitor is reporting on; the need to integrate the sustainability metrics of a strategic partner; or anticipation of the impacts of a future merger. Sustainability reports provide a window into the internal workings of the firm, and their accuracy reflects its competence. While there has been a great deal of research on why companies do sustainability reporting, there has been almost no research on how they do it. This study opens the black box to understand how companies do their sustainability reporting, from an information management perspective. By gathering and analyzing data from the perspective of those installing enterprise-wide sustainability reporting software, we can understand impediments to optimal information flows and design solutions to reduce this friction and so improve organizational agility.

Contact: Stephanie Watts
Faculty Bio:

Retail Analytics

How does the information from online product reviews affect the product return? How do we uncover different paths the customers take to a purchase? These are some of the questions we are seeking to answer in this project using large customer activity datasets. The insights and methods developed in this research could allow a retailer to better plan reverse logistics, improve targeted advertising, and intervene at the best time during a customer’s path-to-purchase.

Contact: Nachiketa Sahoo
More information:
Faculty Bio:

Improved Healthcare Through Machine Learning

We are focused on leveraging recent advances in Machine Learning to improve both the administration and delivery of healthcare. Examples of ongoing projects include: The inference of physician social networks from administrative data, and its use in understanding the impact of insurance structure and coverage restrictions; The prediction of patient re-admissions from administrative, demographic, and chart-level data as well as potential interventions to prevent such readmission; The analysis of the raw data in new HIV blood-testing machines which will be deployed to the developing world, attempting to make them as accurate as contemporary western machines without the need for grid power, refrigerated chemicals, or highly trained technicians. Through the development and refinement of machine learning methods, there are many significant gains to be made in these and related areas.

Contact: Ben Lubin

Information Economics & Intellectual Property

In a Remix economy, how should we allocate credit and $$ to the people who create a composite good? How can we rethink intellectual property to permit more “permissionless innovation” and allow more great software, music, art, and writing to be produced? This project explores several analytic models of credit attribution and also visualization for reused works. We will also run live experiments on remix projects in an effort to develop broad policy implications.

Contact: Marshall Van Alstyne
Faculty Bio:

Platform Economics & Strategy

This research stream examines the rising development of platform firms and business ecosystems such as Android, Airbnb, Kickstarter, and Pinterest. How is innovation different in this context? Should crowds displace experts? Can we measure the health of an ecosystem and determine where to intervene? Should governments adopt platform strategies to grow their economies? How can new firms launch and overcome critical mass problems. Can we change the structure of an entire industry by placing strategic bets? This research will involve both econometric analysis of big data and analytic theory development.

More Information:
Contact: Marshall Van Alstyne
Faculty Bio:


Faculty Notes