I am currently the Zhang Jindong Professor of Operations, Information and Decisions at the University of Pennsylvania, Wharton School. My central research area is on the relationship between information technology and productivity and the factors that affect the value of IT investments. Most of my recent work has been the study of complementary factors, such as organizational design and human capital, on the value of IT. Most of this work is directed at firms in all industries, although I have become increasingly interested in IT deployment in healthcare. In recent years, we have been more extensively working on the role of the IT workforce and issues that affect the demand and wages of IT workers (such as offshoring and the H1-B visa program). I have also been extensively involved in electronic business research investigating the the nature of competition in electronic markets (such as on-line travel agents), the value proposition for alternative delivery systems (such as online retail banking), the role of switching costs in determining pricing and product strategy (as in online discount brokerage), and the effect of recommender systems on consumer behavior.
I teach undergraduate and graduate courses in information systems management and economics and data analysis. I also teach the undergraduate core class in OPIM in the Fall (off-season).
In my spare time, I also consult and conduct research into the design of IT outsourcing agreements, methods for evaluating IT investments, and other questions at the intersection of information systems, economics and econometrics. I also occasionally serve as an expert witness for information technology and consumer-related litigation (intellectual property, consumer behavior in computers and consumer electronics industries, enterprise software, and software project problems).
My current research focuses on the economics of IT labor mobility, contracting in enteprise software, the influence of recommender systems on consumer behavior, measuring intangible assets, and pricing information goods. See my personal site for more information.
Abstract: We examine the relationship between data analytics and innovation, focusing on how the benefits of analytics may differ depending on how firms organize their innovative activities. Our analysis draws on prior work that has measured firm analytics capability using detailed employee-level data and matches these data to metrics on innovation structure that are constructed by analyzing intra-firm inventor networks. We apply community detection algorithms to these inventor networks to determine whether a firm has a centralized or decentralized innovation structure. In a panel of large firms from the years 1988 to 2013, we find that firms with a decentralized innovation structure have a greater demand for analytics skills and receive greater productivity benefits from their analytics capabilities, consistent with a complementarity between analytics and decentralized innovation. Furthermore, we find the complementarity is strongest for innovation involving the recombination of existing technologies. This suggests that data analytics can alleviate a weakness in decentralized innovation structures by allowing firms to search for knowledge broadly and link distant ideas to create new ones, an advantage previously available primarily to centralized innovation.
Lynn Wu, Lorin M. Hitt, Fujie Jin (2017), Are All Spillovers Created Equal? A Network Perspective on IT Labor Movements, Management Science, Forthcoming.
Lynn Wu, Lorin M. Hitt, Bowen Lou (Under Revision), Data Analytics Skills, Innovation and Firm Productivity.
Abstract: We examine the relationship between data analytics capabilities and innovation using detailed firm-level data. To measure innovative activity, we utilize a survey on process- and innovation- oriented business practices, and we use patent data to analyze the innovative output and characteristics of firms. We find that data analytics capabilities are more likely to be present and are more valuable in firms that are oriented around process improvement and that innovate by recombining existing technologies; data analytics skills have no effect on or are possibly negatively related to value in firms that focus on generating creative and truly novel innovations. We interpret these findings as consistent with data analytics skills being complementary to the exploitation rather than exploration strategies as described in the technology strategy literature.
Abstract: This paper investigates the drivers behind Tesla's decision to make its patents freely available to other electric car manufacturers. The two sides of this market, car owners and potential charging stations, rely on each other to increase the value of their investment. We show under what conditions subsidizing the competitors can be profitable. By sharing technology, Tesla may be able improve the charging station network and increase it's own profit from car sales.
Prasanna Tambe (OPIM) and Lorin M. Hitt (2011), Now IT’s Personal: Offshoring and the Shifting Skill Composition of the US Information Technology Workforce, Management Science, (forthcoming).
XinXin Li (OPIM), Lorin M. Hitt, Z. John Zhang (MKTG) (2011), Product Reviews and Competition in Markets for Repeat Purchase Products, Journal of Management Information Systems, (forthcoming).
Prasanna Tambe (OPIM), Lorin M. Hitt, Erik Brynjolfsson (2011), The Extroverted Firm: How External Information Practices Affect Productivity, Management Science, (forthcoming).
I teach four courses:
OPIM101 – Introduction to OPIM (Fall only)
OPIM105 – Data Analysis in VBA and SQL (next offering Fall, 2015)
OPIM469 – Information Strategy and Economics (next offering unknown – maybe Fall, 2016)
OPIM955 – Doctoral Seminar in IS Economics (offered Spring, 2015)
This course provides an introduction to the construction of data analysis tools that are commonly used for business applications, especially in consulting and finance. The course builds on the spreadsheet and analytical skills developed in OPIM101, providing a much more extensive treatment of spreadsheet application development and database management. The first portion of the course will focus on programming in VBA, the embedded programming language in the Microsoft Office suite of applications. This will be supplemented with discussion of industry best practice in software development, such as specification development, interface design, documentation, and testing. The second portion of the class will emphasize data access and analysis utilizing SQL, the industry standard language for interacting with database software.
This course provides an overview of some of the key Information Systems literature from the perspective of Insormation Strategy and Economics (ISE) and Information Decision Technologies (IDT). This course is intended to provide an introduction for first year OIDD doctoral students, as well as other Wharton doctoral students, to important core research topics and methods in ISE and IDT in order for students to do research in the field of Information Systems. While it is intended as a "first course" for OPIM doctoral students in ISE and IDT, it may also be useful for students who are engaged in research or plan to perform information technology related research in other disciplines.
Twitter is like a megaphone, but business should see it more like a telephone, according to this opinion piece.Knowledge @ Wharton - 2018/08/9