Lynn Wu

Lynn Wu
  • Assistant Professor of Operations, Information and Decisions

Contact Information

  • office Address:

    3730 Walnut Street
    561 Jon M. Huntsman Hall
    Philadelphia, PA 19104

Research Interests: Big Data Analytics, Artificial Intelligence, Enterprise Social Media, Innovation, information Worker Productivity, Prediction, Viral Marketing

Links: CV


Lynn Wu is an assistant professor at the Wharton School. She is interested in studying how emerging information technologies, such as enterprise social media and big data analytics, impact innovation  and productivity in organizations. Specifically, her work follows three streams. In the first stream, she studies how enterprise social media and information derived from online platforms affect individuals’ work performance and long-term career trajectories. In her second stream of research, she examines the role of investment in IT, especially the newer wave of technology advances in data analytics and artificial intelligence, affect firm innovation, labor demand, and productivity. In her third stream, Lynn leverages fine-grained nanodata available through online digital traces to predict economic indicators such as real estate trends, labor trends and product adoption.

Lynn has published articles in economics, management and computer science. Her work has been featured by the Wall Street Journal, BusinessWeek, New York Times, and The Economist

Lynn received her undergraduate degrees from MIT (Finance and Computer Science), her master’s degree from MIT (Computer Science) and her Ph.D. from MIT Sloan School of Management (Management Science)

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Past Courses


    Conducting business in a networked economy invariably involves interplay with technology. The purpose of this course is to improve understanding of technology (what it can or cannot enable) and the business drivers of technology-related decisions in firms. We will be discussing some of the new and most disruptive technologies right now to stimulate thought on new applications for commerce and new ventures, as well as their implications to the tech industry as a whole. Topics include social media, online advertising, big data, and cloud computing. The course will take a layered approach (from network infrastructure) to data infrastructure to applications infrastructure, or direct enablers of commerce) to first, understanding and then, thinking about technology enablers. Network infrastructure layers include fundamentals of wired and wireless infrastructure technologies such as protocols for networking, broadband technologies - for last (DSL, Cable etc) and other miles (advances in optical networking) and digital cellular communications. Data infrastructure layers include usage tracking technologies, search technologies and data mining. Direct application layers include personalization technologies (CRM), design technologies for content and exchanges, software renting enablers, application service provision, agents and security mechanisms. Finally some emberging technology enablers (such as bluetooth, biometrics and virtual reality) are identified and discussed.


    This course is about understanding emerging technology enablers with a goal of stimulating thinking on new applications for commerce. No prerequisite or technical background is assumed. The class is self-contained (mainly lecture-based) and will culminate in a class-driven identification of novel businesses that exploit these enablers. No prerequisite or technical background is assumed. Students with little prior technical background can use the course to become more technologically informed. Those with moderate to advanced technical background may find the course a useful survey of emerging technologies. The course is recommended for students interested in careers in consulting, investement banking and venture capital in the tech sector.

Awards and Honors

  • AIS Best Publication 2013, 2014 Description

    The best publication of the year by the Association of Information Systems

  • ISR Best Published Paper 2013, 2014 Description

    Best published paper in 2013 for the Information System Research Journal

  • Best Paper Award at HICSS, 2013
  • Best Paper Award at ICIS, 2009

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The CFO Imperative: Next-Gen Technology Drives Cost Optimization

Cost-optimization strategies must include IT and business initiatives to make sure investments are maximized for long-term growth and profits. In this effort, next-generation technology becomes a critical partner.

Knowledge @ Wharton - 2017/02/13
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Awards and Honors

AIS Best Publication 2013 2014
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