About

Lorin M. Hitt is the Zhang Jindong Professor of Operations, Information and Decisions at the University of Pennsylvania's Wharton School. His central research area focuses on the relationship between information technology and productivity, emphasizing the factors that influence the value of IT investments. His recent work investigates the role of complementary factors such as organizational design and human capital in enhancing IT value, with particular interest in IT deployment within healthcare. Hitt's research also explores electronic business, competition in electronic markets, the value proposition of online delivery systems, switching costs, and the impact of recommender systems on consumer behavior. He teaches undergraduate and graduate courses in information systems management, economics, and data analysis, including the undergraduate core class in OPIM. In addition to his academic pursuits, Hitt consults and conducts research on IT outsourcing agreements, evaluation methods for IT investments, and other topics at the intersection of information systems, economics, and econometrics. He occasionally serves as an expert witness in litigation related to information technology and consumer industries. His work has contributed significantly to understanding how data analytics, organizational structure, and human capital influence innovation, productivity, and the economic impact of IT investments.

Research topics

• Political Science
• Business
• Data Mining
• Sociology
• Marketing
• Economics
• Finance
• Computer Science
• Mathematics
• Econometrics
• Geography
• Financial system
• Microeconomics

Selected publications

• Innovation Strategy after IPO: How AI Analytics Spurs Innovation after IPO

  SSRN Electronic Journal · 2024-01-01 · 5 citations

  articleOpen accessSenior author
  PublisherDOI

• Innovation Strategy After IPO: How AI Analytics Spurs Innovation After IPO

  Management Science · 2024-06-05 · 29 citations

  articleSenior author

  We examine the role of AI analytics in facilitating innovation in firms that have gone through IPO. Using patent data on over 1,000 publicly traded firms, we find that firms acquiring AI analytics capability post-IPO experience less of a decline in innovation quality compared with similar firms that have not acquired that capability. This effect is greater when only machine learning capabilities are considered. Moreover, we find this sustained rate of innovation is driven principally by the continued development of innovations that combine existing technologies into new ones—a form of innovation that is especially well supported by analytics. By examining three main mechanisms that hampered post-IPO innovation, we find that AI analytics can ameliorate the pressure to meet short-term financial goals and disclosure requirements. However, it has limited effect in addressing managerial incentives. For firms with long product cycles, the disclosure effect is reduced to a greater extent than it is for those with short cycles. Overall, our results show the importance of examining technology as a critical input factor in innovation. We show that the increased deployment of AI analytics may reduce some of the innovative penalties suffered by IPOs and that investors and managers can potentially mitigate post-IPO reductions in innovative output by directing capital acquired in the IPO process to the acquisition of AI analytics capabilities. This paper was accepted by D. J. Wu, information systems. Funding: The authors appreciate the generous financial support from Wharton Dean’s Research Fund and Mack Institute for Innovation Management. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.01559 .

  PublisherDOI

• Social Media Alleviates Venture Capital Funding Inequality for Women and Less Connected Entrepreneurs

  Management Science · 2023 · 28 citations

  Senior authorCorresponding
  • Sociology
  • Political Science
  • Business

  Start-ups are increasingly using social media to signal quality and provide information to potential investors. However, the effectiveness of social media on venture capital (VC) financing is likely to be heterogeneous, differing by demographic and network characteristics of the founders. In this paper, we examine whether social media use can improve funding outcomes for firms founded by women and by other people also lacking connections to the investor network, two groups that face greater difficulties in securing VC financing. Using Twitter data and data on VC investment in start-ups from Crunchbase, we explore the interaction effect between Twitter usage and gender and between Twitter usage and the network constraint measure. Overall, we show that social media can mitigate some disparities in financing experienced by these firms through improving information access. We find that this effect is stronger for first-time entrepreneurs than for experienced ones, stronger for attracting new investors than repeat ones, and stronger in more competitive markets. Collectively, these results suggest that social media could primarily help women and less connected individuals obtain financing by alleviating information asymmetry between founders and investors. This paper was accepted by D. J. Wu, information systems. Funding: The authors thank Wharton Mack Institute of Innovation Management for funding support. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4728 .

  PublisherDOI

• Valuation of Personal Data

  Cambridge University Press eBooks · 2023-06-29

  book-chapter

  Data is the lifeblood of the digital economy. Much of the data in use today is generated by the everyday activities of consumers as they communicate, shop, travel, work, or engage in routine interactions with other consumers, businesses, and government entities through digital systems, platforms, and media. This has led to an enormous accumulation of data about individual consumers that can directly or indirectly provide information about their characteristics, preferences, activities, or behaviors.

  PublisherDOI

• IT and Strategic Human Capital: Impact on Knowledge-Based Processes, Networks, and Outcomes

  Academy of Management Proceedings · 2022-07-06

  article

  Advancements in information technology (IT) can have profound impacts on the development and management of human capital. Extant research has examined how human capital in markets and organizations are shaped by increased digitization and the deployment of strategies relying on collection and analysis of big data, cloud computing, social media, Internet of Things (IoT), and the like. In knowledge-intensive settings, however, IT-enabled mechanisms have heterogenous impacts on issues related to human capital. Although IT potentially expands capacity for collection, storage, and utilization of knowledge, some firms and individuals successfully leverage technology and information systems while others do not--or are even possibly left worse off. This symposium contributes to examining why such discrepancies may exist by shedding light on the market and organizational processes that underlie the intersection of IT and knowledge-based processes, networks, and outcomes as they relate to issues in strategic human capital. Can Social Media Alleviate Inequality? Evidence from Venture Capital Financing Presenter: Gavin Wang; Wharton OPIM Presenter: Lynn Wu; The Wharton School, U. of Pennsylvania Presenter: Lorin Hitt; U. of Pennsylvania Are Knowledge Sharing and Learning Tradeoffs? Linking Performance Incentives with KMS Usage Presenter: Sae-Seul Park; Carnegie Mellon U. - Tepper School of Business Cloud Adoption and Strategic Human Capital: Evidence from Norway Presenter: Derrick Choe; - Presenter: Amir Sasson; BI Norwegian Business School Presenter: Robert Channing Seamans; NYU Stern Hunting For Talent: Firm-Driven Labor Market Search in the United States Presenter: Ines Black; - Presenter: Sharique Hasan; Fuqua School of Business, Duke U.

  PublisherDOI

• You Say, Firm says: An Empirical Study on Online Employer Brand and Firm Performance

  SSRN Electronic Journal · 2022-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• Social Media Alleviates Venture Capital Funding Inequality for Women and Less Connected Entrepreneurs

  SSRN Electronic Journal · 2022 · 15 citations

  Senior authorCorresponding
  • Political Science
  • Business
  • Financial system
  PublisherDOI

• Does Employer Brand Matter: An Empirical Study on Online Job Reviews, Social Media Usage and Firm Performance

  Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2021-01-01 · 3 citations

  articleOpen access1st authorCorresponding

  In this study, we examine how employee-contributed job reviews and firm-managed social media posts jointly build up “employer brand” as an intangible asset and influence market valuation. Using large-scale datasets of job reviews, social media posts and firm performance, we study how employer band can create value distinct from overall corporate (consumer) branding. We find that more positive job ratings are associated with higher firm market value, particularly in labor-intensive industries and especially for positions which are harder to replace and have higher employee mobility. In addition, firms can complement this effect by posting more employee-related content on their social media pages. Overall, our results suggest that firms should have coordinated strategies across digital platforms, presenting a consistent employer brand, to maximize their market valuation.

  PublisherOA PDFDOI

• Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application

  Information Systems Research · 2021 · 40 citations

  • Computer Science
  • Data Mining
  • Marketing

  Search and experience goods, as well as vertical and horizontal differentiation, are fundamental concepts of great importance to business operations and strategy. In our paper, we propose a set of theory-grounded data-driven measures that allow us to measure not only product type (search vs. experience and horizontal vs. vertical differentiation) but also sources of uncertainty and to what extent consumer reviews help resolve uncertainty. We used product rating data from Amazon.com to illustrate the relative importance of fit in driving product utility and the importance of search for determining fit for each product category at Amazon. Our results also show that, whereas ratings based on verified purchasers are informative of objective product values, the current Amazon review system appears to have limited ability to resolve fit uncertainty. Industry practitioners could utilize our approaches to quantitatively measure product positioning to support marketing strategy for retailers and manufacturers, covering an expanded group of products.

  PublisherDOI

• Digital Capital and Superstar Firms

  National Bureau of Economic Research · 2020-12-01 · 138 citations

  reportOpen access

  General purpose technologies like information technology typically require complementary firmspecific investments to create value. These complementary investments produce a form of capital, which is typically intangible and which we call digital capital. We create an extended firm-level panel on IT labor investments (1990-2016) using data from LinkedIn. We then apply Hall's Quantity Revelation Theorem to compute both prices and quantities of digital capital over recent decades. We find that 1) digital capital prices vary significantly over time, peaking around the dot-com boom in 2000, 2) significant digital capital quantities have accumulated since the 1990s, with digital capital accounting for at least 25% of firms' assets by the end of our panel, 3) that digital capital has disproportionately accumulated in a small subset of "superstar" firms and its concentration is much greater than the concentration of other assets, and 4) that digital capital accumulation predicts firm-level productivity about three years in the future.

  PublisherDOI

Recent grants

• Collaborative Research: Customer Efficiency and the Management of Multi-Channel Service Delivery Systems

  NSF · $102k · 2005–2008

Frequent coauthors

• Prasanna Tambe

  University of Pennsylvania

  47 shared

• Erik Brynjolfsson

  National Bureau of Economic Research

  42 shared

• Lynn Wu

  University of Pennsylvania

  17 shared

• Eric K. Clemons

  12 shared

• Fujie Jin

  Indiana University Bloomington

  10 shared

• Bowen Lou

  7 shared

• Yili Hong

  University of Miami

  6 shared

• Xue Mei

  United Imaging Healthcare (China)

  5 shared

Labs

• Operations, Information and Decisions DepartmentPI

Education

• Ph.D. Management

  MIT

  1996