About

Peng Huang is an Associate Professor of Information Systems at the Robert H. Smith School of Business, University of Maryland, College Park. He received his Ph.D. in Information Technology Management from the Georgia Institute of Technology. His research interests include platform ecosystems, technology and innovation management, and technology strategy. His recent work has been published in journals such as Management Science, Information Systems Research, MIS Quarterly, Journal of Marketing, Journal of Management Information Systems, and MIT Sloan Management Review. He has received several awards, including the Sandra Slaughter Early Career Award from the INFORMS Information Systems Society, the Digital Transformation Fellowship from the University of Göttingen, the Kauffman Dissertation Fellowship from the Ewing Marion Kauffman Foundation, and the Ashford Watson Stalnaker Memorial Prize from Georgia Tech. He is also an associate editor of Management Science in the Information Systems department.

Research topics

• Computer Science
• Economics
• Business
• Industrial organization
• Computer Security
• Political Science
• Law
• Management
• Marketing
• Finance
• Knowledge management
• Public relations
• Market economy

Selected publications

• Technological Innovations in China’s Steel Industry under Carbon Neutrality

  Advances in economics, business and management research/Advances in Economics, Business and Management Research · 2025-01-01

  book-chapterSenior author
  PublisherDOI

• Popularity Feedback and Adaptation Strategies in Online Dating: A Social Comparison Perspective

  MIS Quarterly · 2025-05-29 · 3 citations

  article

  Digital platforms are increasingly employing informational nudges to motivate user participation. This paper examines the provision of popularity information as a feedback mechanism and its impact on users’ adaptation strategies. Leveraging ego utility theory and self-determination theory, we hypothesize that comparative popularity information—information that facilitates social comparison—will trigger different reactions based on gender and popularity level. In collaboration with an online dating service provider, we designed and conducted two randomized field experiments in which we provided popularity feedback to platform users and investigated their post-feedback behavioral changes in two adaptation strategies: the selectiveness in choosing potential partners (i.e., selectivity calibration) and the frequency of their online profile modifications (i.e., self-marketing). In the first experiment, where we revealed information about their popularity relative to other users, we found that those who received low-popularity feedback significantly increased self-marketing efforts and lowered their selectivity, but the opposite was observed in individuals who received high-popularity feedback. We also found that men readily made adaptations to their selectivity calibration and self-marketing, whereas women’s behaviors were more persistent as they exhibited little strategic change. We then conducted a second experiment in which we revealed absolute popularity instead of comparative popularity and observed no significant changes in adaptation strategies. Comparing the outcomes of the two experiments, we argue that it is the social comparison information associated with comparative popularity that drives user behavioral changes.

  PublisherDOI

• Regional green transition under dual-carbon goals: Deconstruction, clustering, and evolution of carbon emissions in China

  Energy Reports · 2025-12-01 · 3 citations

  articleOpen access

  Synergizing the relationship between environmental crisis, economic development, and social progress within different regions is of great significance for the green transformation of different regions and industries under the dual-carbon goal. This research provided a novel analytical model of "comprehensive deconstruction-clustering characteristics-regional evolution" based on the Log-Mean Division Index (LMDI) method to address the differences of regions in Chinese provinces. On this basis, different regions are comprehensively analyzed using economic, social, energy, and carbon emission data of Chinese provinces between 2004 and 2019. The carbon emissions of different provinces and cities with different characteristics are also deconstructed and analyzed from multiple perspectives, including energy structure, energy intensity, economic development, and population size. Based on the obtained industrial structure contribution ratio and industrial carbon emission ratio, provinces with similar characteristics were analyzed by region clustering. Moreover, the carbon emission trends of representative typical provincial and municipal industries are studied by considering three industries as the demarcation points. Finally, some energy saving and emission reduction suggestions are proposed from five perspectives, including tertiary industry, secondary industry, energy distribution, industrial distribution, and low GDP, combining with the current popular carbon trading market system. • Built a “deconstruction–clustering–evolution” model for provincial carbon drivers using the LMDI method. • Decomposed provincial carbon emissions by energy structure, intensity, economic level, and population. • Clustered provinces with similar industrial and emission features for comparative analysis. • Identified key provincial emission trends and proposed targeted mitigation strategies.

  PublisherDOI

• Startup Accelerators, Information Asymmetry, and Corporate Venture Capital Investments

  Management Science · 2025-03-03 · 10 citations

  articleSenior author

  Beyond financial incentives, investments by Corporate Venture Capitalists (CVCs) are often motivated by strategic objectives, such as gaining early exposure to emerging technologies. However, in the presence of information asymmetry, CVCs tend to invest in startups with a high degree of business relatedness—startups that are less risky but lacking in knowledge novelty—which are not ideal for achieving their strategic objectives. With startup accelerators showing promise in mitigating the information asymmetry problem, we examine how a CVC’s investment pattern in a region shifts following a startup accelerator’s entry, with a particular interest in the degree of business relatedness between the CVC’s parent corporation and its portfolio companies. Analyses reveal that CVCs increase investments in startups that are dissimilar to their parent’s business following the entry of startup accelerators. We show that the two pathways through which accelerators reduce information asymmetry—quality signals, and mentorship and training—likely contribute to this change. In addition, the change is most pronounced for CVCs whose parent firm operates in an IT-using—rather than an IT-producing—industry, suggesting that accelerators help IT-using firms gain a foothold in the technology space through CVC investments. These findings deepen the understanding of the role that startup accelerators play in the entrepreneurial ecosystem against the backdrop of digital transformation occurring in nearly every industry. This paper was accepted by Kartik Hosanagar, information systems. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2020.03494 .

  PublisherDOI

• User Innovation and Product Stickiness: Evidence From Video Games

  Journal of Economics & Management Strategy · 2025-09-18

  articleSenior author

  ABSTRACT Prior research on user innovation fails to explain its low adoption rate and neglects its impact on increased product stickiness. To bridge these gaps, we conducted an empirical investigation into user innovations within the video game sector. Our study reveals that embracing user innovation leads to an upsurge in the number of active players for a game. Furthermore, the marginal effect of user innovations varies depending on their recency and quality , with low‐quality user innovations leading to user attrition. The effect is also contingent on the stage in the product life cycle in which user innovation is adopted.

  PublisherDOI

• User Innovation and Product Stickiness: Evidence from Video Games

  SSRN Electronic Journal · 2024-01-01

  articleOpen accessSenior author
  PublisherDOI

• California Exodus? A Network Model of Population Redistribution in the United States

  arXiv (Cornell University) · 2023-08-12

  preprintOpen access1st author

  Motivated by debates about California's net migration loss, we employ valued exponential-family random graph models to analyze the inter-county migration flow networks in the United States. We introduce a protocol that visualizes the complex effects of potential underlying mechanisms, and perform in silico knockout experiments to quantify their contribution to the California Exodus. We find that racial dynamics contribute to the California Exodus, urbanization ameliorates it, and political climate and housing costs have little impact. Moreover, the severity of the California Exodus depends on how one measures it, and California is not the state with the most substantial population loss. The paper demonstrates how generative statistical models can provide mechanistic insights beyond simple hypothesis-testing.

  PublisherOA PDFDOI

• Knowledge Map Analysis of Innovation and Entrepreneurship Education Based on Citespace

  Atlantis Highlights in Computer Sciences/Atlantis highlights in computer sciences · 2023-09-21

  book-chapterOpen access

  This study examines the research trends in this field by comparing the number of papers published in the past 10 years in the Web of Science (WOS) and the China National Knowledge Infrastructure (CNKI) databases.The findings reveal a steady growth in research enthusiasm among domestic scholars.A total of 1000 documents were extracted from the WOS database, of which 950 were considered effective and analyzed using Citespace 6.2 R 2 for visual analysis.The analysis included examining keyword co-occurrence networks, clustering maps, keywords with the strongest citation bursts, and timeline graphs.Based on the knowledge graph analysis, the study discusses the connection between innovation and entrepreneurship education and the higher education system and the future directions in this field.

  PublisherOA PDFDOI

• Countermeasures to Account Sharing on Media Platforms

  SSRN Electronic Journal · 2023-01-01

  articleOpen access1st authorCorresponding
  PublisherDOI

• Rooted America: Immobility and Segregation of the Intercounty Migration Network

  arXiv (Cornell University) · 2022-05-04 · 4 citations

  preprintOpen access1st author

  Despite the popular narrative that the United States is a "land of mobility," the country may have become a "rooted America" after a decades-long decline in migration rates. This article interrogates the lingering question about the social forces that limit migration, with an empirical focus on internal migration in the United States. We propose a systemic, network model of migration flows, combining demographic, economic, political, and geographic factors and network dependence structures that reflect the internal dynamics of migration systems. Using valued temporal exponential-family random graph models, we model the network of intercounty migration flows from 2011 to 2015. Our analysis reveals a pattern of segmented immobility, where fewer people migrate between counties with dissimilar political contexts, levels of urbanization, and racial compositions. Probing our model using "knockout experiments" suggests one would have observed approximately 4.6 million (27 percent) more intercounty migrants each year were the segmented immobility mechanisms inoperative. This article offers a systemic view of internal migration and reveals the social and political cleavages that underlie geographic immobility in the United States.

  PublisherOA PDFDOI

Frequent coauthors

• Chris Forman

  Cornell University

  15 shared

• Anandasivam Gopal

  Nanyang Technological University

  12 shared

• Yang Pan

  12 shared

• Marco Ceccagnoli

  10 shared

• Henry C. Lucas

  Binus University

  7 shared

• D. J. Wu

  Georgia Institute of Technology

  7 shared

• Terje Aven

  University of Stavanger

  5 shared

• Uwe Jensen

  5 shared

Education

• Ph.D.

  Georgia Institute of Technology

  2010

Awards & honors

• Sandra Slaughter Early Career Award from the Information Sys…
• Digital Transformation Fellowship from University of Götting…
• Kauffman Dissertation Fellowship from the Ewing Marion Kauff…
• Ashford Watson Stalnaker Memorial Prize from Georgia Tech
• Best Conference Paper Awards at the International Conference…