About

Professor Ben A. Rissing studies regulatory, mobility, and social processes that operate behind the scenes to shape important facets of modern careers. His research includes examining how government regulators influence immigrant hiring and compensation, the performance implications of worker mobility, and the functioning of new organizational recruitment systems reliant on social connections. He negotiates access to and analyzes unique personnel data within U.S. government agencies, for-profit businesses, and university admissions systems, often encompassing millions of observations. Using modern data analytics, he builds datasets by joining disparate administrative, application, and employee records to test theories with key implications for governments, workers, and practitioners. Dr. Rissing earned his doctorate in management from the Massachusetts Institute of Technology (MIT) Sloan School of Management, along with master's degrees in management science and engineering management from MIT and Duke University, respectively. He also holds a bachelor's degree in mechanical engineering from the University of Virginia. Before joining Cornell University, he served as the Hugh W. Pearson Visiting Professor of Commerce, Organizations and Entrepreneurship at Brown University and was a Postdoctoral Research Associate with the Brown University Watson Institute for International Studies. Additionally, he conducted research as a Wertheim Fellow with Harvard Law School.

Research topics

• Political Science
• Business
• Economics
• Psychology
• Engineering
• Law
• Computer Science
• Accounting
• Labour economics
• Marketing
• Mathematics
• Demographic economics
• Public relations

Selected publications

• 36 Immigrant Entrepreneurs and Inventors

  2025-04-07

  book-chapter1st authorCorresponding
  PublisherDOI

• Artificial Intelligence: Disrupting Work and Destabilizing Social Processes

  Academy of Management Proceedings · 2025-07-01

  article

  This presenter symposium advances our scholarly understanding of the unintended consequences of Artificial Intelligence (AI) in and around organizations. Through five papers, we unpack several emergent concerns of AI use: how Large Language Models could create labor market inequalities, AI's paradoxical undermining of professional decision-making, the deterioration of grievance authenticity in AI-based social activism, AI's homogenizing effects on entrepreneurial ideation, and how corporate control of AI systems compromises scholarly independence. Together, these papers demonstrate how AI is disrupting work and destabilizing social processes. The Uneven Impact of Large Language Models on Labor Market Dynamics Author: Paul Merritt; Cornell University Author: Ben A Rissing; Cornell University Generative AI as a Power Persuader: How GenAI Disrupts Professionals’ Ability to Interrogate it Author: Steven Randazzo; Author: Akshita Joshi; Author: Katherine C. Kellogg; Author: Hila Lifshitz-Assaf; Author: Fabrizio Dell'Acqua; Harvard Business School Author: Francois Candelon; Author: Karim R. Lakhani; Harvard Business School Authenticity in Social Activism: The Case of AI-Based Social Media Bots Author: Luis Hillebrand; University of Geneva Author: Forrest Briscoe; Cornell University The Effects of Generative AI on Entrepreneurial Theorizing Author: Sung Ho Park; University of Oregon Author: Alex Michael Murray; University of Oregon Corporate Empiricism: How Controlling AI Reshapes Knowledge Production Author: Christine Moser; Vrije Universiteit Amsterdam Author: Gazi Islam; Grenoble Ecole de Management

  PublisherDOI

• Outing Outsourcing: The Impact of a Mandated Transparency Initiative on Immigrant Salary

  Academy of Management Proceedings · 2025-07-01

  article1st authorCorresponding

  Growing scholarship examines the conditions under which transparency initiatives lead to more equitable outcomes in organizational settings. Yet, less is known about whether such initiatives may help to resolve salary gaps when co-located workers have different employers (such as in the widespread case of salary gaps between direct employees and contract workers employed in the same job and worksite). To address this, we study the impact of a mandated economy-wide transparency initiative within the H-1B visa program, revealing immigrant workers’ status as direct employees or contractors, in conjunction with salary. Drawing on theories related to coordination challenges, employment externalization, and the boundary of the firm, our findings indicate that in the year after the transparency initiative, the salary gap was reduced for immigrants working in the same job and worksite, but this effect is most pronounced at those worksites where employers engaged a single active contracting firm. The initiative had less of a salary impact at worksites with 2-4 contracting firms, and virtually no impact in worksites with 5 or more contracting firms. This pattern of results suggests that cross-firm coordination challenges may have blunted the initiative’s impact. Findings emphasize the complexity of achieving equitable salary outcomes in multi-employer worksites.

  PublisherDOI

• The Need for Speed: The Role of Employers in Immigrant Work Visa Regulatory Prioritization

  Industrial and Labor Relations Review · 2024-10-11 · 2 citations

  article1st authorCorresponding

  Employers are central, yet understudied, actors in the immigrant work authorization process. The authors motivate and empirically assess three central theoretical accounts to explain employers’ regulatory prioritization of specific immigrant work visa applications: the role of immigrant human capital, employers’ past filing experience, and the relative dissimilarity of the focal application to employers’ past applications. These accounts are tested using U.S. Citizenship and Immigration Services (USCIS) administrative records pertaining to the H-1B temporary work visa. The authors analyze employers’ selective visa application prioritization as reflected in their use of “premium processing” to expedite government visa adjudication, persistence to the point of adjudication (i.e., not withdrawing or abandoning the application), and requests for longer employment durations. Findings primarily support the human capital and relative dissimilarity accounts. Results underscore the role of employers in visa processing speeds, the granting of legal status, and legal status durations—outcomes more frequently attributed to regulator discretion.

  PublisherDOI

• Heeding the Bully Pulpit: Immigrant Inequality through Executive Order Anticipatory Compliance

  Academy of Management Proceedings · 2024-07-09

  article1st authorCorresponding

  We assess how President Trump’s 2017 “travel ban” Executive Order (EO) created labor market inequality for immigrants from targeted majority-Muslim countries. Our Executive Deference account suggests government evaluators may defer to Presidential priorities during employment-based visa assessments, denying more applicants from targeted countries. Our Bully Pulpit account suggests applicants from targeted countries may preemptively discontinue employment efforts. By analyzing government administrative records, we find worse labor certification outcomes for immigrants from travel ban countries following the EO, primarily due to voluntary application withdrawal. Findings emphasize how EOs may intensify inequality (and advance policy goals) by influencing applicants from targeted countries, even absent formalized regulation.

  PublisherDOI

• Collecting, Coding, and Analyzing Observational Records From Real Organizations: “Best in Class” Analytical Techniques

  2023-01-01

  book1st authorCorresponding
  PublisherDOI

• The Need for Speed: The Role of Employers in Immigrant Work Visa Acceleration and Approval

  Academy of Management Proceedings · 2022-07-06

  article1st authorCorresponding

  Why are some immigrant work visa applications processed and approved in a matter of days, while others languish for months before receiving a decision? We contend that the relative dissimilarity between a focal visa application and an employer’s past work visa filings is a key, yet unstudied, strategic value consideration affecting the sponsoring firm’s engagement with the regulatory bureaucracy. Using U.S. CIS administrative records obtained through the Freedom of Information Act detailing all H-1B visa applications from 2006 to 2015, we analyze employers’ acceleration of select applications through the “premium processing” program, which guarantees an initial visa decision in 15 days in exchange for a $1,225 per-application payment. We find that employers are more likely to use premium processing for immigrants whose countries of birth, prospective jobs, and educational experiences are dissimilar relative to the applications previously filed by that employer. Further, employers less frequently withdraw or abandon dissimilar applications, and request longer employment durations in these dissimilar applications. In contrast to prior arguments regarding immigrants’ regulatory and employment success, we argue that immigrants identical on observables and migration inclination may fare differently in the U.S. immigration system depending on their dissimilarity within the context of their sponsoring employer.

  PublisherDOI

• Career Mobility and Hiring Bias: Frontiers of Labor Market Research

  Academy of Management Proceedings · 2021-07-26

  articleSenior author

  The papers in this symposium collectively work at extending and developing the intersections of two current, and burgeoning, streams of contemporary labor market research. First is the move towards a better understanding of the mechanisms of hiring bias. While past research has focused on demonstrating the existence of hiring bias, recent research has endeavored to develop a much richer understanding of how and why it may develop, whether it changes over time, and how it could be mitigated. A second stream of work has tackled the question as to how technological advances will impact the labor market, such as how companies are exploiting the continued externalization of gig-economy labor force hiring and whether and how machine learning matching technologies will benefit or harm employees of employers. In our first presentation, Mahabadi and Cohen ask: How and where do people learn to hire and how does that shape labor markets? The authors explore this question in the context of startups and investigate how founders and hiring mangers there turn to outsiders for help with the critical tasks of hiring. They analyzed over 200 interviews with hiring managers, startup employees, potential job applicants and subject matter experts across over 50 startups; non-participant observation; and document review. They show that founders and hiring managers from many startups described learning from various parties in their ecosystem about several aspects of hiring, including: learning from investors, job candidates, mentors, consultants, recruiters, other entrepreneurs, and people in established organizations; learning through deliberate networking and advice seeking; and learning through less formal and less hiring-focused interactions at events such as startup fairs, conferences and social events. Based on these analyses, they categorized entrepreneurial learning into three broad categories: the very mechanical and transactional aspects of hiring; the aspects of structures closely related to hiring; the more elaborated learning of what they might do to convince people to work for them. The paper then explores the implications of these learnings for labor markets and organizations. In our second presentation, Rissing asks is hiring bias shaped through personal experience or the result of exposure to negative events? The author examines this in the context of H1B visa examiners. He engages two burgeoning, yet largely separate, literatures examining dynamic personal and contextual factors that may shape decision maker bias over time. First, experience-based theories argue that through repeated assessments of individuals belonging to different groups, decision makers may update their attitudes regarding said groups. Second, event-based theories have argued that decision maker bias may be shaped by local shocks, such as crimes or attacks associated with members of a select group that may then be perceived as a threat. There have been few opportunities for scholars to examine how these two key forms of learning might contribute to the updating of decision makers’ attitudes regarding particular groups of workers in an organizational setting. In our third presentation, Daviss and Leung ask whether or not employers change their hiring preferences, and by implication, their biases, over time. Specifically, they explore how employers’ preferences for women or men job candidates vary across multiple hiring decisions. They propose three potential patterns: stability, in which an employers’ bias and by extension their preferences remain consistent across multiple hiring decisions; reduction, in which the strength of an employers’ gender bias is reduced through direct experiences with workers; and reversion, in which an employers’ preference for women or men reverses directions due to the accumulation of moral credentials. To test these patterns, they draw on a unique longitudinal dataset from an online labor marketplace, comprising 4 million bids submitted for more than 450,000 jobs, posted by more than 128,000 employers in 2012. Using logit regression with applicant- and job-level controls, they test whether a bid’s likelihood of being selected is correlated with the gender of the worker, as well as the gender of the employer’s most recent hire and the quality of the employer’s experience with their most recent hire. They find strong evidence suggesting that employers’ preferences for women versus men are largely stable, and weak evidence that employer’s gender preferences are shaped in part by their direct experiences with workers. They do not find, however, that employers’ preferences reverse with the accumulation of moral credentials, even when employers’ moral credentials would presumably be strong. In our fourth presentation, Yang, Bao, and Leung ask whether and how racial hiring bias can be mitigated. Specifically, they examine whether and how employer perceptions of how responsible a job applicant looks may mitigate the hiring bias African Americans face. While employers are known to be biased against hiring black job applicants, when as compared to White applicants, what is less well-understood is whether and how this bias may be mitigated. The authors examine a mobile technology mediated labor market that matches employers looking to hire temporary labor with the gig-economy labor force job seekers. They ask whether or not employer perceptions of responsibility will mitigate the hiring bias black job seekers face. The particularly novel aspect of their paper is the use of a machine learned algorithm to code job applicant photos for how “responsible” they look – thereby introducing us to a computational method to measure human perception in hiring. Finally, Ng and Sherman ask whether the trend by firms who increasingly externalized labor markets to hire is justifiable. Much of the accumulated evidence suggests that it is not. For example, firms tend to pay a significant wage premium for external hires versus comparable candidates promoted from within. Furthermore, research documents declines in the performance of securities analysts, insurance agents, and bankers who switch organizations. Given these results, as well as the financial costs incurred when hiring via third-party recruiters, the rationale for sustaining external hiring at its current levels is not immediately apparent. How do firms capture value from external labor market hiring? Social capital theory suggests that external hires should produce work that is more creative than their otherwise equivalent internal counterparts. Ng and Sherman test this perspective via machine learning methods using a repository of resumes from the website LinkedIn. By relying on a matching estimator the authors find, in a sample of product managers working in large technology firms, that external hires are indeed more creative than observably equivalent internal hires. However, the authors also find that external hires have a higher turnover rate, an effect that is amplified for particularly creative external hires. This suggests that relying on external hires to catalyze creativity may be a difficult strategy to sustain in the long term. Taken together, this research offers some evidence as to why external hiring continues unabated in spite of its demonstrable detriments. Learning by Hiring: How Hiring Processes Facilitate Learning Across Startup-Ecosystem Boundaries Presenter: Sara Mahabadi; McGill U. - Desautels Faculty of Management Presenter: Lisa Ellen Cohen; McGill U. To H-1B or Not to H-1B? The Role of Experience and Events in Shaping Dynamic Bias Presenter: Ben Rissing; Cornell U. Patterned Preferences: Employers’ Preferences for Women Versus Men Across Multiple Hiring Decisions Presenter: Claire Daviss; Stanford U. Presenter: Ming De Leung; U. of California, Irvine How race moderates effect of perceived responsibility on being hired on a low-skilled labor market Presenter: Tiantian Yang; Duke U. Presenter: Jiayi Bao; UNC-Chapel Hill Presenter: Ming De Leung; U. of California, Irvine In Search of Inspiration: External Hiring, Internal Mobility, and Creative Production Presenter: Weiyi Ng; National U. of Singapore Presenter: Eliot Sherman; London Business School

  PublisherDOI

• Premium Processing or Processing Premiums? The Role of Selective Persistence in Regulatory Outcomes

  Academy of Management Proceedings · 2021-07-26 · 1 citations

  article1st authorCorresponding

  Organizations often employ indirect and circuitous strategies to shape regulatory outcomes in their favor. This said, key regulatory programs increasingly allow regulated organizations to directly shape their own case prioritization and evaluation deadlines, generally for a fee. Such expedited regulatory evaluations often have superior outcomes, but less understood is why. We address this gap by examining U.S. Citizenship and Immigration Services (CIS) agents’ assessments of immigrant H-1B visa applications, which can be expedited for $1,000. Through analysis of Freedom of Information Act records for all 5.2 million H-1B visa evaluations from 2001 to 2016, we find that expedited applications are more often approved than standard cases. To explain this gap, we test multiple theoretical accounts and find that organizations, not regulators, are the key actors shaping approval rate differences. We contend that organizations disproportionately use expedited processing for strategically valuable activities, and thus withdraw or abandon these applications less frequently relative to standard cases. This primarily explains the relative success of expedited applications over their standard counterparts. These findings emphasize organizational agency as an underappreciated factor shaping regulatory outcomes in fee-dependent regimes.

  PublisherDOI

• Inside Jobs: Salary Setting for Immigrants Crossing Establishment, Organizational, and National Boundaries

  ILR Review · 2021 · 2 citations

  1st authorCorresponding
  • Political Science
  • Business
  • Labour economics

  Using novel US Department of Labor administrative records, the authors test theoretical mechanisms to account for variation in immigrant workers’ starting salaries following key career transitions. Specifically, they examine differences in the base starting salaries and discretionary starting salary increases above these base starting salaries for 1) same-establishment hires, relative to 2) US-based establishment transfers, 3) international establishment transfers, 4) US-based external hires, and 5) international external hires. In support of the “insider premium” account, findings show that same-establishment hires tend to work in jobs with greater requirements, and thus higher base starting salaries. In partial support of the “outsider premium” account, findings show that US-based external hires receive larger starting salary increases than do same-establishment hires, conditional on the jobs they enter. This said, international external hires receive smaller starting salary increases than do same-establishment hires. Findings reveal distinct mechanisms, acting separately or in tandem, during salary-setting processes.

  PublisherDOI

Frequent coauthors

• Gary Gereffi

  56 shared

• Richard B. Freeman

  Harvard University

  37 shared

• Barry S. Myers

  Duke University

  36 shared

• Larry Kramer

  36 shared

• Elaine Bernardt

  Fox College

  36 shared

• Kristina M. Johnson

  Corteva (United States)

  36 shared

• Dan Siciliano

  Fox College

  36 shared

• Jeff Glass

  36 shared

Education

• Ph.D. , Institute for Work and Employment Research

  Massachusetts Institute of Technology

  2013

• Masters in Engineering Management, Engineering Management

  Duke University

  2006

• Bachelor's of Science in Mechanical Engineering, Mechanical Engineering

  University of Virginia

  2005

Awards & honors

• Chancellor's Award for Excellence in Teaching, SUNY (2023)
• Best Paper Proceedings Recipient, Academy of Management (202…
• Shah Family Dean’s Excellence Funding Award, Cornell Univers…
• MacIntyre Award for Exemplary Teaching and Advising, Cornell…
• Best Paper Proceedings Recipient, Academy of Management (201…