About

Ravi Bapna is the Curtis L. Carlson Chair Professor in Business Analytics and Information Systems and serves as the Academic Director of the Carlson Analytics Lab at the University of Minnesota's Carlson School of Management. He is closely affiliated with the MS in Business Analytics program and the Carlson Analytics Lab, where graduate students study a broad range of data analysis techniques and apply them to real business problems. These students are skilled in exploratory data visualization, predictive analytics, programming, data engineering, machine learning methods, and more, emerging as data science professionals. Partner organizations have the opportunity to work with these talented students while supporting the educational mission of the programs. The faculty involved with the Analytics for Good Institute, including Professor Bapna, bring expertise from various fields such as computer science, econometrics, strategy, and causal experimentation. The institute emphasizes impact, engagement, and collaboration with industry partners to leverage data analytics for social good and business innovation.

Research topics

• Business
• Psychology
• Economics
• Social psychology
• Political Science
• Labour economics
• Mathematics
• Marketing
• Microeconomics
• Demographic economics

Selected publications

• Discovery, discernment, and exploitation: Entrepreneurial mechanisms at the nexus of individual and opportunity

  Strategic Management Journal · 2023-06-07 · 13 citations

  articleOpen access1st authorCorresponding

  Abstract Research Summary Extending the opportunity‐discovery perspective on Kirznerian entrepreneurship, we propose a general framework in which new businesses emerge from three distinct mechanisms situated at the individual‐opportunity nexus: discovery , discernment , and exploitation . We propose observing opportunities in market exchanges and characterizing their profitability potential based on a component that is common to all observers and one that is specific to individual observers who vary in access to market information. Analysis of an online platform for freelance labor demonstrates our contributions in theory, measurement, and inference. In this context, discovery and exploitation mechanisms shape individuals' entrepreneurial transitions from freelancer to founder. We discuss applications of our framework across settings, extensions to other types of entrepreneurship, and the viability of opportunity as an orienting construct for entrepreneurship research. Managerial Summary Entrepreneurial opportunities are present in all markets but there is no systematic way of observing or valuing such opportunities, much less predicting where and when they become the basis for new businesses. We propose doing this with data commonly collected and archived by online platforms. We acknowledge that new businesses are often founded if one is in the right place at the right time; if one can distinguish a great opportunity from a good (or bad) one; or if one is capable of making a market. Our framework makes each of these intuitions empirically distinct, thus offering insights on where, when, and by whom new businesses are likely to be founded.

  PublisherOA PDFDOI

• How Do Employers Use Compensation History?: Evidence From a Field Experiment

  National Bureau of Economic Research · 2020-01-01 · 6 citations

  reportOpen access1st authorCorresponding

  We report the results of a field experiment in which treated employers could not observe the compensation history of their job applicants. Treated employers responded by evaluating more applicants, and evaluating those applicants more intensively. They also responded by changing what kind of workers they evaluated: treated employers evaluated workers with 5% lower past average wages and hired workers with 13%lower past average wages. Conditional upon bargaining, workers hired by treated employers struck better wage bargains for themselves.

  PublisherDOI

• How Do Employers Use Compensation History? Evidence from a Field Experiment

  Journal of Labor Economics · 2020 · 62 citations

  1st authorCorresponding
  • Labour economics
  • Economics
  • Demographic economics

  We report the results of a field experiment in which treated employers could not observe the compensation history of their job applicants. Treated employers responded by evaluating more applicants and evaluating those applicants more intensively. They also responded by changing what kind of workers they evaluated: treated employers evaluated workers with 5% lower past average wages and hired workers with 13% lower past average wages. Conditional on bargaining, workers hired by treated employers struck better wage bargains for themselves.

  PublisherOA PDFDOI

• How Do Employers Use Compensation History?: Evidence from a Field Experiment

  SSRN Electronic Journal · 2020 · 25 citations

  1st authorCorresponding
  • Political Science
  • Political Science
  • Psychology
  PublisherDOI

• Steering in Online Markets: The Role of Platform Incentives and Credibility

  Management Science · 2020 · 53 citations

  1st authorCorresponding
  • Business
  • Microeconomics
  • Marketing

  Platform marketplaces can potentially steer buyers to certain sellers by recommending or guaranteeing those sellers. Money-back guarantees—which create a direct financial stake for the platform in seller performance—might be particularly effective at steering as they align buyer and platform interests in creating a good match. We report the results of an experiment in which a platform marketplace—an online labor market—guaranteed select sellers for treated buyers. The presence of a guarantee strongly steered buyers to these guaranteed sellers, but offering guarantees did not increase sales overall, suggesting financial risk was not determinative for the marginal buyer. This preference for guaranteed sellers was not the result of their lower financial risk, but rather because buyers viewed the platform’s decision to guarantee as informative about relative seller quality. Indeed, a follow-up experiment showed that simply recommending the sellers that the platform would have guaranteed was equally effective at steering buyers. This paper was accepted by Chris Forman, information systems.

  PublisherDOI

• Paving the Road to M&A Success: Antecedents, Processes, and Outcomes of Post- Merger Integration

  Academy of Management Proceedings · 2019-08-01

  article

  Acquisitions enable firms to source critical capabilities and close resource gaps but often fail to achieve firms’ anticipated benefits. Reasons for M&A failure often lay in the challenges the acquirer faces in the Post-Merger Integration (PMI) process that follows M&A. The PMI literature holds many yet to be answered research questions about how the PMI process affects individuals, and how their behaviors, in turn, impact M&A outcomes. The investigation of such individual- level contextual factors in the PMI process poses particularly interesting avenues for future research. A combination of in-depth case studies and large-scale studies based on individual-level data can help scholars overcome these constraints in our knowledge of PMI. The presentations in this symposium shed light upon micro-foundational aspects of PMI from a variety of angles. The symposium fosters the academic discourse on how firms can successfully lead the PMI process, leverage and integrate acquired resources, and realize the full potential of M&A synergies. It also aims at instigating discussions about how PMI can serve as context for building theory relevant to other organizational contexts. Why Choose One? Complementarities between Technology Acquisitions and Hiring of Inventors Presenter: Arianna Marchetti; INSEAD Presenter: Philipp Meyer-Doyle; INSEAD Presenter: Ithai Stern; INSEAD Acquihired Presenter: Moshe Barach; Carlson School of Management Presenter: Weiyi Ng; National U. of Singapore Presenter: Toby E Stuart; U. of California, Berkeley Physician Organization and Incentives in Childbirth Presenter: Ambar La Forgia; Columbia U. The Effect of Employee Mobility on Post-Merger Performance Presenter: Julia Bodner; INSEAD Presenter: Andrew V. Shipilov; INSEAD Presenter: Kaisa E. Snellman; INSEAD Multi-Pace Integration Approach, Situated Attention, and Firm Performance Presenter: Natalia Vuori; Aalto U.

  PublisherDOI

• Steering in Online Markets: The Role of Platform Incentives and Credibility

  RePEc: Research Papers in Economics · 2019-01-01

  articleOpen access1st authorCorresponding

  Platform marketplaces can potentially steer buyers to certain sellers by recommending or guaranteeing those sellers. Money-back guarantees—which create a direct financial stake for the platform in seller performance—might be particularly effective at steering as they align buyer and platform interests in creating a good match. We report the results of an experiment in which a platform marketplace—an online labor market—guaranteed select sellers for treated buyers. The presence of a guarantee strongly steered buyers to these guaranteed sellers, but offering guarantees did not increase sales overall, suggesting financial risk was not determinative for the marginal buyer. This preference for guaranteed sellers was not the result of their lower financial risk, but rather because buyers viewed the platform’s decision to guarantee as informative about relative seller quality. Indeed, a follow-up experiment showed that simply recommending the sellers that the platform would have guaranteed was equally effective at steering buyers.

  OA PDF

• From Laborer to Founder: Examining Entrepreneurs' Fundamental Transitions on an Online Platform. (WITHDRAWN)

  Academy of Management global proceedings · 2019-01-28

  articleSenior author

  We present a general framework for investigating how opportunity-based entrepreneurship is shaped both by individuals and by market opportunities. Proposing measures of opportunity potential based ...

  Publisher

• Steering in Online Markets: The Role of Platform Incentives and Credibility

  National Bureau of Economic Research · 2019-06-01 · 7 citations

  preprint1st authorCorresponding

  Platform marketplaces can potentially steer buyers to certain sellers by recommending or guaranteeing those sellers.Money-back guarantees-which create a direct financial stake for the platform in seller performance-might be particularly effective at steering, as they align buyer and platform interests in creating a good match.We report the results of an experiment in which a platform marketplace-an online labor market-guaranteed select sellers for treated buyers.The presence of a guarantee strongly steered buyers to these guaranteed sellers, but offering guarantees did not increase sales overall, suggesting financial risk was not determinative for the marginal buyer.This preference for guaranteed sellers was not the result of their lower financial risk, but rather because buyers viewed the platform's decision to guarantee as informative about relative seller quality.Indeed, a follow-up experiment showed that simply recommending the sellers that the platform would have guaranteed was equally effective at steering buyers.

  PublisherDOI

• Strategic Redundancy in the Use of Big Data: Evidence from a Two-Sided Labor Market

  Strategy Science · 2019-12-01 · 15 citations

  article1st authorCorresponding

  In this study, we examine how firms use the big data capabilities of third-party platforms to find transaction partners. Although use of the platform’s big data capabilities creates value by lowering search costs, firms may capture little of this value if they become entirely dependent on the platform. We argue that firms invest in strategic redundancy, that is, they continue to rely partly on their internal screening capabilities to identify partners so as to maintain their bargaining power relative to the platform. We further predict that this reliance on internal screening is greater the lower the relative advantage of the platform’s big data capabilities and the more salient the threat to the firm’s bargaining power. We test these predictions in the context of an online labor platform, using a regression discontinuity design to examine the effect of the platform’s recommendations on the firm’s decision to hire an applicant. Consistent with our theory, we find that firms’ use of the platform’s recommendations is lower in later stages of the hiring process, in larger submarkets, and for firms with greater experience on the platform. Our study sheds new light on how firms make use of (third-party) big data techniques, showing that firms may strategically choose to limit such use in order to maintain independence.

  PublisherDOI

Frequent coauthors

• John J. Horton

  National Bureau of Economic Research

  16 shared

• Joseph M. Golden

  5 shared

• Sibo Lu

  Beijing Jiaotong University

  4 shared

• Ming D. Leung

  4 shared

• Aseem Kaul

  University of Minnesota System

  3 shared

• Christopher I. Rider

  University of Michigan–Ann Arbor

  2 shared

• Andrew V. Shipilov

  INSEAD

  1 shared

• Ithai Stern

  INSEAD

  1 shared

Education

• PhD, Business and Public Policy

  University of California Berkeley

  2016