2028 SH-DH
3620 Locust Walk
Philadelphia, PA 19104
Research Interests: intellectual property rights, start-up innovation, strategies for commercializing technological innovation, venture capital
Links: CV, Personal Website
David Hsu is the Richard A. Sapp Professor of Management at the Wharton School, University of Pennsylvania. He graduated from Stanford University with undergraduate majors in economics and political science. After a few years working in industry, he received his master’s degree in public policy from Harvard University, followed by his Ph.D. in management from the Massachusetts Institute of Technology.
Hsu’s research interests are in entrepreneurial innovation and management. Within that domain, he has investigated topics such as intellectual property management, start-up innovation, technology commercialization strategy, and venture capital. His research has appeared in leading journals such as Management Science, Journal of Finance, Strategic Management Journal, and Research Policy. He is past department and associate editor of Management Science. In 2008, Hsu was awarded an Alfred P. Sloan Foundation Industry Studies Fellowship. At Wharton, he teaches two MBA electives, Entrepreneurship and Technology Strategy. At Penn, Hsu is Associate Faculty Director of the Weiss Tech House, which encourages and supports students in the creation, development, and commercialization of innovative technologies.
David Hsu, Po-Hsuan Hsu, Tong Zhou, Arvids Ziedonis (2021), Benchmarking U.S. University Technology Commercialization Efforts: A New Approach, Research Policy.
Matt Marx and David Hsu (2021), Revisiting the Entrepreneurial Commercialization of Science: Evidence from ‘Twin’ Discoveries, Management Science.
Abstract: What factors shape the commercialization of academic scientific discoveries via startup formation? Prior literature has identified several contributing factors but does not address the fundamental problem that the commercial potential of a nascent discovery is generally unobserved and potentially confounds inference. We construct a sample of over 20,000 “twin” scientific articles, which allows us to hold constant differences in the nature of the advance and more precisely examine characteristics that predict startup commercialization. In this framework, several commonly-accepted factors appear not to influence commercialization. However, we find that teams of academic scientists whose former collaborators include “star” serial entrepreneurs are much more likely to commercialize their own discoveries via startups, as are more interdisciplinary teams of scientists.
Po-Hsuan Hsu, Dokyun Lee, Prasanna Tambe, David Hsu, Deep Learning, Text, and Patent Valuation.
Q. Chen, David Hsu, D. Zvilichovsky (Working), Inventor Commingling and Innovation in Technology Startup Mergers & Acquisitions.
Abstract: How does inventor team “commingling” (containing inventors from the acquiring and acquired firms) in technology startup acquisitions relate to innovation outcomes? Commingling reflects collaboration benefits and costs of integrating human resources across organizational boundaries. Commingled team innovation may also depend on the form of inter-organizational R&D, ranging from less (strategic alliance) to more integrated (M&A) structures. M&A control may aid innovation. We study technology startups experiencing a merger, some of which also had a prior alliance with the acquirer. Innovation outcomes (patent counts, forward citations, and patent scope) increase post-merger for firms with more intensive inventor commingling. We exploit direct flights between the M&A parties to instrument for endogenous commingling, and find robust results. Inventor-level commingling is more effective under M&A as compared to alliances.
David Hsu and Jeffrey Kuhn (Working), Resource Allocation Decision-making in Hybrid Organizations: Evidence from University Technology Licensing.
David Hsu, Po-Hsuan Hsu, Qifeng Zhao (Working), Rich on Paper? Chinese Firms’ Academic Publications, Patents, and Market Value.
Vikas Aggarwal, David Hsu, Andy Wu (2020), Organizing Knowledge Production Teams Within Firms for Innovation, Strategy Science, 5 (1), pp. 1-16.
Andrea Contigiani, David Hsu, Iwan Barankay (2018), Trade Secrets and Innovation: Evidence from the ‘Inevitable Disclosure’ Doctrine, Strategic Management Journal, 39 (11), pp. 2921-2942.
J. T. Fox, C. Yang, David Hsu (2018), Unobserved Heterogeneity in Matching Games, Journal of Political Economy, 126 (4), pp. 1339-1373.
O. Bengtsson and David Hsu (2015), Ethnic Matching in the U.S. Venture Capital Market, Journal of Business Venturing, 30 (2), pp. 338-354.
MGMT897401
WH 212401
This course is about managing large enterprises that face the strategic challenge of being the incumbent in the market and the organizational challenge of needing to balance the forces of inertia and change. The firms of interest in this course tend to operate in a wide range of markets and segments, frequently on a global basis, and need to constantly deploy their resources to fend off challenges from new entrants and technologies that threaten their established positions. The class is organized around three distinct but related topics that managers of established firms must consider: strategy, human and social capital, and global strategy.
This course is about managing during the early stages of an enterprise, when the firm faces the strategic challenge of being a new entrant in the market and the organizational challenge of needing to scale rapidly. The enterprises of interest in this course have moved past the purely entrepreneurial phase and need to systematically formalize strategies and organizational processes to reach maturity and stability, but they still lack the resources of a mature firm. The class is organized around three distinct but related topics that managers of emerging firms must consider: strategy, human and social capital, and global strategy.
The course is designed to meet the needs of future managers, entrepreneurs, consultants and investors who must analyze and develop business strategies in technology-based industries. The emphasis is on learning conceptual models and frameworks to help navigate the complexity and dynamism in such industries. This is not a course in new product development or in using information technology to improve business processes and offerings. We will take a perspective of both established and emerging firms competing through technological innovations, and study the key strategic drivers of value creation and appropriation in the context of business ecosystems. The course uses a combination of cases, simulation and readings. The cases are drawn primarily from technology-based industries. Note, however, that the case discussions are mainly based on strategic (not technical) issues. Hence, a technical background is not required for fruitful participation.
MGMT 801 is the foundation coures in the Entrepeurial Management program. The purpose of this course is to explore the many dimensions of new venture creation and growth. While most of the examples in class will be drawn from new venture formation, the principles also apply to entrepreneurship in corporate settings and to non-profit entrepreneurship. We will be concerned with content and process questions as well as with formulation and implementation issues that relate to conceptualizing, developing, and managing successful new ventures. The emphasis in this course is on applying and synthesizing concepts and techniques from functional areas of strategic management, finance, accounting, managerial economics, marketing, operations management, and organizational behavior in the context of new venture development. The class serves as both a stand alone class and as a preparatory course to those interested in writing and venture implementation (the subject of the semester-long course, MGMT 806). Format: Lectures and case discussions Requirements: Class participation, interim assignments, final project Enrollment limited to Wharton MBA students only.
This course is designed to provide students with an understanding of the methodological approaches we commonly think of as qualitative, with special emphasis on ethnography, semi- structured interviews, case studies, content analysis, and mixed-methods research. The course will cover the basic techniques for collecting, interpreting, and analyzing qualitative (i.e. non-numerical) data. In the spring quarter, the course will operate on two interrelated dimensions, one focused on the theoretical approaches to various types of qualitative research, the other focused on the practical techniques of data collection, such as identifying key informants, selecting respondents, collecting field notes and conducting interviews. In the fall semester, the course will operate on two interrelated dimensions, one focused on the theoretical approaches on building arguments and theory from qualitative data, the other focused on the practical techniques of data collection, such as analyzing data, writing, and presenting findings. Note: This class is part of a two-part sequence which focuses on qualitative data collection and analysis. The first of this course, offered in the Spring, focuses on data collection and the second half of the course, offered the following Fall, will focus on qualitative data analysis. Each course is seven weeks long. Students may take either class independently or consecutively.
The seminar seeks to expose students to theoretical and empirical perspectives on entrepreneurship research. We will focus on the main questions that define the field and attempt to critically examine how, using a range of methodologies, researchers have approached these questions. As we review the literature, we will seek to identify promising research areas, which may be of interest to you in the context of your dissertation research. In addition to addressing the content of the received literature, we will examine the process of crafting research papers and getting them published in top tier journals. Towards that end we will characterize the key elements of high impact papers and review the development process of such studies. Students are expected to come fully prepared to discuss and critique the readings that are assigned to each class meeting (see details below). Each student will serve as the discussion leader for one or more of the class sessions. Discussion leaders are expected to critically review several articles, identify new insights in the research that is being reviewed and evaluate its contribution to the literature, position the articles within the literature on the subject matter, raise discussion question, and act as the discussion moderator for the class session. Each discussion leader is asked to prepare a one or two page summary of the assigned papers which includes a statement of the main research question(s), the methodology, data set if any, summary of findings, a commentary with your thoughts on the reading, and proposed discussion questions. Prior to each class, the discussion leader will meet the instructor to help plan the class meeting. Towards the end of each class meeting, each student will be asked to articulate a research question that emerged from the session and describe the research design used to investigate the issue.
This quarter-length course explores key topics at the intersection of entrepreneurship and innovation. While the course primarily draws from established theory and empirics from management and economics, it will also include discussions of emerging phenomena in this rapidly evolving field. We will begin by reviewing the basic properties of ideas that uniquely shape the sources and dynamics of entrepreneurship and innovation. Subsequently, we will explore innovation-related challenges and opportunities for startups. Special focus will be placed on research application in which students design and present their own research proposal broadly in the area of entrepreneurship and innovation. Students are highly encouraged to take this course in sequence with MGMT 937.
On average, universities in the U.S. capture 16% of the value they help create in the startups spawned by their research. Two new papers co-authored by Wharton’s David Hsu look at what academic institutions need to consider when it comes to commercializing their IP.
Knowledge @ Wharton - 1/25/2021Getting a PhD wasn’t part of Tanya’s long-term plan when she started as an undergrad at Wharton. She initially aspired to work as a data scientist or analyst but soon fell in love with data in a whole different way through a research assistantship….
Wharton Stories - 09/07/2016